(upbeat music) >> Welcome to our industry drill-down. This is from manufacturing. I'm here with Michael Ger who is the managing director for automotive and manufacturing solutions at Cloudera, and in this first session, we're going to discuss how to drive transportation efficiencies and improve sustainability with data. Connected trucks are fundamental to optimizing fleet performance, costs, and delivering new services to fleet operators, and what's going to happen here is Michael's going to present some data and information, and we're going to come back and have a little conversation about what we just heard. Michael, great to see you. Over to you. >> Oh, thank you, Dave, and I appreciate having this conversation today. Hey, this is actually an area, connected trucks. This is an area that we have seen a lot of action here at Cloudera, and I think the reason is kind of important because first of all, you can see that this change is happening very, very quickly. 150% growth is forecast by 2022, and I think this is why we're seeing a lot of action and a lot of growth is that there are a lot of benefits. We're talking about a B2B type of situation here. So this is truck makers providing benefits to fleet operators, and if you look at the top benefits that fleet operators expect, you see this in the graph over here. Almost 80% of them expect improved productivity, things like improved routing, so route efficiencies and improved customer service, decrease in fuel consumption, but better be, this isn't technology for technology's sake. These connected trucks are coming onto the marketplace because hey, they can provide tremendous value to the business, and in this case, we're talking about fleet operators and fleet efficiencies. So, one of the things that's really important to be able to enable this, trucks are becoming connected because at the end of the day, we want to be able to provide fleet efficiencies through connected truck analytics and machine learning. Let me explain to you a little bit about what we mean by that because how this happens is by creating a connected vehicle analytics machine learning lifecycle, and to do that, you need to do a few different things. You start off, of course, with connected trucks in the field, and you could have many of these trucks 'cause typically, you're dealing at a truck level and at a fleet level. We want to be able to do analytics and machine learning to improve performance. So you start off with these trucks, and the first you need to be able to do is connect to those trucks. You have to have an intelligent edge where you can collect that information from the trucks, and by the way, once you've conducted this information from the trucks, you want to be able to analyze that data in real-time and take real-time actions. Now, what I'm going to show you, the ability to take this real-time action is actually the result of a machine learning life cycle. Let me explain to you what I mean by that. So we have this truck, so we start to collect data from it. At the end of the day, what we'd like to be able to do is pull that data into either your data center or into the cloud where we can start to do more advanced analytics, and we start with being able to ingest that data into the cloud, into the enterprise data lake. We store that data. We want to enrich it with other data sources, so for example, if you're doing truck predictive maintenance, you want to take that sensor data that you've collected from those trucks, and you want to augment that with your dealership service information. Now, you have sensor data and the resulting repair orders. You're now equipped to do things like predict when maintenance will occur. You've got all the data sets that you need to be able to do that. So what do you do here? Like I said, you ingest it, you're storing it, you're enriching it with data. You're processing that data. You're aligning, say, the sensor data to that transactional system data from your repair maintenance systems. You're bringing it together so that you can do two things. First of all, you could do self-service BI on that data. You can do things like fleet analytics, but more importantly, what I was talking to you about before is you now have the data sets to be able to create machine learning models. So if you have the sensor values and the need, for example, for a dealership repair order so you could start to correlate which sensor values predicted the need for maintenance, and you could build out those machine learning models, and then, as I mentioned to you, you could push those machine learning models back out to the edge which is how you would then take those real-time actions I mentioned earlier. As that data that then comes through in real-time, you're running it against that model, and you can take some real-time actions. This analytics and machine learning model, machine learning life cycle, is exactly what Cloudera enables. This end-to-end ability to ingest data, store it, put a query lay over it, create machine learning models, and then run those machine learning models in real-time. Now, that's what we do as a business. Now, one such customer, and I just wanted to give you one example of a customer that we have worked with to provide these types of results is Navistar, and Navistar was kind of an early adopter of connected-truck analytics, and they provided these capabilities to their fleet operators. And they started off by connecting 475,000 trucks, up to well over a million now, and the point here is that they were centralizing data from their telematics service providers, from their trucks' telematics service providers. They're bringing in things like weather data and all those types of things, and what they started to do was to build out machine learning models aimed at predictive maintenance, and what's really interesting is that you see that Navistar made tremendous strides in reducing the expense associated with maintenance. So rather than waiting for a truck to break, and then fixing it, they would predict when that truck needs service, condition-based monitoring, and service it before it broke down so that you can do that in a much more cost-effective manner. And if you see the benefits, they reduced maintenance costs 3 cents a mile down from the industry average of 15 cents a mile down to 12 cents cents a mile. So this was a tremendous success for Navistar, and we're seeing this across many of our truck manufacturers. We're working with many of the truck OEMs, and they are all working to achieve very, very similar types of benefits to their customers. So just a little bit about Navistar. Now, we're going to turn to Q&A. Dave's got some questions for me in a second, but before we do that, if you want to learn more about how we work with connected vehicles and autonomous vehicles, please go to our website, what you see up on the screen. There's the URLs, cloudera.com/solutions/manufacturing, and you'll see a whole slew of lateral and information in much more detail in terms of how we connect trucks to fleet operators who provide analytics, use cases that drive dramatically improved performance. So with that being said, I'm going to turn it over to Dave for questions. >> Thank you, Michael. That's a great example. I love the lifecycle. We can visualize that very well. You've got an edge-use case. You're doing both real time inference, really, at the edge, and then you're blending that sensor data with other data sources to enrich your models, and you can push that back to the edge. That's that life cycle, so really appreciate that info. Let me ask you, what are you seeing as the most common connected vehicle when you think about analytics and machine learning, the use cases that you see customers really leaning into? >> Yeah, that's a great question, Dave 'cause everybody always thinks about machine learning, like this is the first thing you go to. Well, actually it's not. The first thing you really want to be able to do, and many of our customers are doing, is look, let's simply connect our trucks or our vehicles or whatever our IOT asset is, and then you can do very simple things like just performance monitoring of the piece of equipment. In the truck industry, a lot of performance monitoring of the truck, but also performance monitoring of the driver. So how is the driver performing? Is there a lot of idle time spent? What's route efficiencies looking like? By connecting the vehicles, you get insights, as I said, into the truck and into the driver, and that's not machine learning any more, but that monitoring piece is really, really important. So the first thing that we see is monitoring types of use cases. Then you start to see companies move towards more of the, what I call, the machine learning and AI models where you're using inference on the edge, and there you start to see things like predictive maintenance happening, kind of real-time route optimization and things like that, and you start to see that evolution again to those smarter, more intelligent, dynamic types of decision-making. But let's not minimize the value of good old-fashioned monitoring to give you that kind of visibility first, then moving to smarter use cases as you go forward. >> You know, it's interesting. I'm envisioning, when you talked about the monitoring, I'm envisioning you see the bumper sticker how am I driving? The only time somebody ever probably calls is when they get cut off, and many people might think, oh, it's about Big Brother, but it's not. I mean, that's yeah, okay, fine, but it's really about improvement and training and continuous improvement, and then of course the route optimization. I mean, that's bottom-line business value. I love those examples. >> Great. >> What are the big hurdles that people should think about when they want to jump into those use cases that you just talked about? What are they going to run into, the blind spots they're going to get hit with? >> There's a few different things. So first of all, a lot of times, your IT folks aren't familiar with kind of the more operational IOT types of data. So just connecting to that type of data can be a new skill set. There's very specialized hardware in the car and things like that and protocols. That's number one. That's the classic IT-OT kind of conundrum that many of our customers struggle with, but then more fundamentally is if you look at the way these types of connected truck or IOT solutions started, oftentimes the first generation were very custom built, so they were brittle. They were kind of hardwired. Then as you move towards more commercial solutions, you had what I call the silo problem. You had fragmentation in terms of this capability from this vendor, this capability from another vendor. You get the idea. One of the things that we really think that needs to be brought to the table is first of all, having an end-to-end data management platform that's kind of integrated, it's all tested together. You have a data lineage across the entire stack, but then also importantly, to be realistic, you have to be able to integrate to industry kind of best practices as well in terms of solution components in the car, the hardware, and all those types of things. So I think there's, it's just stepping back for a second, I think that there has been fragmentation and complexity in the past. We're moving towards more standards and more standard types of offerings. Our job as a software maker is to make that easier and connect those dots so customers don't have to do it all and all on their own. >> And you mentioned specialized hardware. One of the things we heard earlier in the main stage was your partnership with Nvidia. We're talking about new types of hardware coming in. You guys are optimizing for that. We see the IT and the OT worlds blending together, no question, and then that end-to-end management piece. This is different from, you're right, from IT. Normally everything's controlled, you're the data center, and this is a metadata rethinking, kind of how you manage metadata. So in the spirit of what we talked about earlier today, other technology partners, are you working with other partners to sort of accelerate these solutions, move them forward faster? >> Yeah, I'm really glad you're asking that Dave because we actually embarked on a project called Project Fusion which really was about integrating with, when you look at that connected vehicle lifecycle, there are some core vendors out there that are providing some very important capabilities. So what we did is we joined forces with them to build an end-to-end demonstration and reference architecture to enable the complete data management life cycle. Now, Cloudera's piece of this was ingesting data and all the things I talked about being storing and the machine learning. So we provide that end-to-end, but what we wanted to do is we wanted to partner with some key partners, and the partners that we did integrate with were NXP. NXP provides the service-oriented gateways in the cars. That's the hardware in the car. Wind River provides an in-car operating system that's Linux, that's hardened and tested. We then ran our Apache MiNiFi which is part of Cloudera Dataflow in the vehicle, on that operating system, on that hardware. We pumped the data over into the cloud where we did all the data analytics and machine learning and built out these very specialized models, and then we used a company called Airbiquity once we built those models to do. They specialize in automotive over-the-air updates, so they can then take those models and update those models back to the vehicle very rapidly. So what we said is, look, there's an established ecosystem, if you will, of leaders in this space. What we wanted to do is make sure that Cloudera was part and parcel of this ecosystem, and by the way, you mentioned Nvidia as well. We're working close with Nvidia now so when we're doing the machine learning, we can leverage some of their hardware to get some still further acceleration in the machine learning side of things. So yeah, one of the things I always say about these types of use cases, it does take a village, and what we've really tried to do is build out an ecosystem that provides that village so that we can speed that analytics and machine learning life cycle just as fast as it can be. >> This is, again, another great example of data-intensive workloads. It's not your grandfather's ERP that's running on traditional systems. These are really purpose built. Maybe they're customizable for certain edge-use cases. They're low cost, low power. They can't be bloated, and you're right, it does take an ecosystem. You've got to have APIs that connect, and that takes a lot of work and a lot of thought. So that leads me to the technologies that are sort of underpinning this. We talked a lot on theCUBE about semiconductor technology, and now that's changing, and the advancements we're seeing there. What do you see as some of the key technology areas that are advancing this connected vehicle machine learning? >> You know, it's interesting. I'm seeing it in a few places, just a few notable ones. I think, first of all, we see that the vehicle itself is getting smarter. So when you look at that NXP-type of gateway that we talked about, that used to be kind of a dumb gateway that was really, all it was doing was pushing data up and down and provided isolation as a gateway down from the lower level subsystems, so it was really security and just basic communication. That gateway now is becoming what they call a service oriented gateway, so it can run. It's got discs, it's got memory, it's got all this stuff. So now you could run serious compute in the car. So now, all of these things like running machine learning inference models, you have a lot more power in the car. At the same time, 5G is making it so that you can push data fast enough making low-latency computing available even on the cloud. So now you've got incredible compute both at the edge in the vehicle and on the cloud. And then on the cloud, you've got partners like Nvidia who are accelerating it still further through better GPU-based compute. So I mean the whole stack, if you look at that machine learning life cycle we talked about, no Dave, it seems like there's improvements in every step along the way. We're starting to see technology optimization just pervasive throughout the cycle. >> And then, real quick. It's not a quick topic, but you mentioned security. I mean, we've seen a whole new security model emerge. There is no perimeter anymore in a use case like this, is there? >> No, there isn't, and one of the things that we're- Remember, we're the data management platform, and the thing we have to provide is provide end-to-end lineage of where that data came from, who can see it, how it changed, and that's something that we have integrated into from the beginning of when that data is ingested through when it's stored through when it's kind of processed, and people are doing machine learning. We will provide that lineage so that security and governance is assured throughout the data learning life cycle. >> And federated, in this example, across the fleet. So, all right, Michael, that's all the time we have right now. Thank you so much for that great information. Really appreciate it. >> Dave, thank you, and thanks for the audience for listening in today. >> Yes, thank you for watching. Keep it right there. (upbeat music)

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> live in. Welcome to a special cube conversation here in Palo Alto. The Cube Studios. Jon, for your host. We're here with a special panel. Talk about the new brand of tech leaders in this era of cloud computing data. Aye, aye. And engineering excellence with us. We have Christine Heckart to CEO of Scaler J. P. Krishna of Marthe Moorthy. These s VP of engineering a Copa software and Patna saying, VP of engineering a glass door. Guys, welcome to come the Cube conversation. Welcome, engineer. And you guys are all running engineering organizations. You've been a former engineer now running a big company CEO, engineering led company. This is a big trend that's clearly defined. No one needs any validation. Cloud computing has certainly changed the game, eh? I certainly the hottest trend with respect, the data machine learning and the benefits. They're changing the cultures of companies changing how things were built, how people are hired. You're starting to see a complete shift towards old way and new ways. I want to get your thoughts about the engineering opportunities. What is engineering excellence today mean in this modern error? >> Well, for us it we talk a lot about mastery and setting up an environment where engineers have a chance to build their own mastery. But they can also have the necessary tools and technologies to be master of their domain. And these domains, especially if it's cloud base. They're very distributed. They're very, very fast moving. There's a lot of continual risk s so you have to set them up in the right way so they could be successful. >> What's your thoughts? I mean, you guys air cutting edge startup? >> Yes. For us, it's very important that the environment, the working moment for engineers, is organically inspiring. And what I mean by that is when every engineer no, why are there what are they doing? Well, how their work is impacting the company in the business initiators. At the same time, we are making sure that their interests are aligned with Albert projects and work in a way that we are also in a healthy, very extending and stretching their skills when their work has a purpose. And that's what our mission is, which is we want to make sure that everybody finds an opportunity where they feel there's a purpose that its purpose driven, that's when we feel like it. That's a great environment where they will be inspired to come every day and deliver their 110% >> J p excellence and engineering. I mean, this is what people strive for. >> So excellent points from both off them and I. I think I have a slightly different take on it as well. Today's business is we are asked to respond really, really fast, maybe hear the tongue a gel everywhere, John, right? So it's about how do we respond to the needs of the business as quickly as you can On dhe, it becomes the mantra for the organization. Having said that, there is another side to it. The dark side is technical debt. That's something we all have toe grapple with because you're moving fast, you're making decisions. You're hoping things all right, You want to prove your thesis out there, but at the same time, you don't wantto put yourself behind so that it might come and bite you later. So it's finding that balance is really, really important, and that becomes the focal point of the organization. How do you move fast, but at the same time Hold it. Oh, do you not slow yourself down in the >> future? That's a great point. I want to get probably your thoughts. That's because open source has been really a different game changer from the old way to the new way. Because you could work with people from different companies. You can work on projects that a better man for other people as well. So it's got a communal aspect to it. But also there is an element of speed the same time agile forces, this kind of concept. So technical debt. You want to move fast, we gotta recover. You kind of know how to get there. How is open source? Change that in Europe in >> well, number one thing that opens and allows all smaller company especially but more companies is that now you you can take on an open source project and start rather starting from ground zero. You can start somewhere where you know it's already helped, and you have a framework ready to start working on. So you're not every two single time we're building our thinking off a new idea you're not starting. Okay, Now let me school start from ground up, right? So you already are at a certain level, the second area where, like you said, you know, we're a Joe. Uh, we have open source, but we also have certain level of customization that the customers needed our application needs. And that's what inspires engineers as well, which is taking the challenger for K. We have a code based. Now let me build something more interesting, more innovative. And then what they also love is giving back to the community. It's we're not. The companies are not just tech community engineering team. We are have a bigger engineering community now, the whole tackle, and that's what makes a big difference for us working in Silicon Valley to even be part of that and contributing factor. >> J P Talk about technical debt when it comes back to the modern era because you can go back to It's been around for a while. Technical dead concerts, not new, but it's always been kind of the water cooler come with core lead engineer and the team. The Aussies have a term called feature creeping. You know, the old days. I don't get it. The feature creep. Actually, it kind of takes it away because of you. If you're applying technical debt properly, you're managing the velocity of the project. So the question is, how is technical debt evolved to the management levels of senior engineering managers? Because that seems to be a key variable in managing the speed and quality of the teams with managing the table. Done. Now, management is what some other conversations. >> So the game depends on the stage of the company Onda stage of the projects you are. If you're in a really mature suffer environment, very you're not making a lot of change. It's OK. It's not the primary conversation off the topic. But if you're trying to you capture a market or promote an idea, it becomes the fundamental thesis, forgetting things out there quickly Now, getting things out there quickly doesn't mean you get to let users suffer. You had to build it in the right way, needs toe work, but at the same time it needs to be just enough so that we can We can get the feedback from from the user's on. At the same time, you probably would have left out potentially features on. Maybe you didn't even make certain decisions on Let's say, hi availability or our scalability. Maybe you wanna prove it out in only one region of the world and so on. So you have to find those balances, and it becomes part of the planning conversations right in the front. And as you go into the further iterations of the product, it becomes part of the prioritization conversation of the product managers because it's not just about getting one part done and getting it out there. But as it reached the full level of maturity that you would want, >> I'm sure there's a lot of debates about an engineer organizations because, you know, engineers a very vocal you. Yeah, so you could fall in love with your product of your time to market, maybe taking some technical debt to get product market fit. And that's my baby, though, when you got a re platform or re scale it to make it scale, bringing with your point you mentioned. How do you guys manage? Because this becomes a talent management. People say, Oh, you gotta manage the ECOWAS. But if some people are managing the project in there. They're going to fire over their skis on technical debt. You gotta kind of rain that in. How do you guys manage the people side of the equation? That because it's an art and a science at the same time? What's your thoughts? >> Well, I'll say this, um, supporting al aspects of change, right? That's also is an injury leader. It's a core responsibility and call it a priority for us, not just the technical debt, but also the market shifts. Technology shifts. We have new tech coming in. We have involving in evolving every technology. So how do via dear to and make sure that it's very important that engineering is supporting and kind of coming up with these technologies a tte the same time? We are not just pulling down to their version of grades and all of them, so in a jest, it's it's a core aspect of leadership to make sure that you, as we are supporting these changes, were also making sure that these changes are not pulling us down. So that should be proper quality checks. There should be a proper conversation and roadmap items which is saying that it's not attack debt. It's more of a tech investment, and we are talking about so that we're in lock steps with our business partner and not behind, so that now we're saying Okay, we need a whole quarter to develop new things. So it's an aspect of filmmaking. Sure, team this motivated >> This comes back to culture. Next question. I want to get you guys thoughts on this building. A positive work culture given engineering led organization. Christine, you're leading that now to start up because your own real fast a lot. A lot of engineers. They're probably a lot of opinions on what that looks like. What is the cultural quick? Because this sets the DNA early on for startup. But as you're maturing organization, you gotta track the best talent. And some say, Well, we work on We saw hard problems. That's kind of cliche, but ultimately you do have to kind of have that problem solving aspect. You gotta have a culture what is a successful work culture for engineering. >> So every everybody talks about engineers wanna solve hard problems. I think that's true. But as Pablo said earlier, if you can help every engineer connect what they're doing, every day to the higher purpose. The organization to the problem that you're solving and how that makes the customers like better in our case, were accompanied by engineers for engineer. So our engineers get really excited about giving other engineers in the world a better day. We have taken it one step further recently by starting a peer network because one of my observations coming into this organization is there are so many peer networks in I t. Because it's been a 30 year industry. There are tons of pure organizations for CEOs. There are tons appear organizations for C. M. O's, but there really aren't for engineers. And if we want to help engineers really develop their career and their full skill set and therefore develop into their full potential, it's about more than just training them. It's about giving them context and full social skills and giving them places where they can learn not just from the other engineers in their company, but from engineers across the organization or across the industry at their same level, and maybe from very different industries and maybe in very different environments. So I think in our case, you know, really trying to bring these peer networks together has been one way that we can not only pay it forward for our own engineers, but also help a lot of other engineers around of the industry >> how you guys handling the engineering talent pertaining, attracting and keeping the best now. >> So I think that's where the whole company comes together, in my view. So as an injuring leader, it's not just that I said the tune of my engineering or as to what? That hiring his top priority. It's where the whole company comes together. You're recruiting team to build the stellar interview process. You are, you know, heads of other orcs to make sure that across the board you're helping define a mission for your company that resonates with your candidates who would want to work with you. So it's a collective effort of building a stellar environment for us glass door when one of the few values is transparency and we live and die by it, which means that when someone is higher, they need to see that be within the company. We are transparent, so we'd share a lot of data. A lot of information, good and bad with every single person in the company. It's never, um, hidden at the same time. We build and set up trust in them to say, Hey, it's confidential. Make sure that it doesn't leave the company and it's been 11 years and it hasn't It has never been the case. >> What class door you don't want have a glass door entry on black. Gotta be transparent. That's the culture. Culture matters minutes. Your culture is all about sharing and being open. >> You will see it. So that's what this is, what God goes down spike for as well, right? Building transparency within the company culture and more and more as we see many stories that we have seen for various companies. And sometimes I get a bad story, too, and I get an invitation. Oh, you're from class door, you know. But that helps overall Rios living and working for user's and professionals. >> Cross is big for you guys, >> absolutely professionals who are in this world looking for a job and life because you're spending a lot of time at work. So we want you to get up every day and be inspired and happy about where you're going to work and for that. That's why we have sharing a lot of the insights about the company's from reviews and ratings and CEO data to make sure that when you make your decision of the next move, you are you can be fully trust. You could be fully confident that the date of your sharing the new with that you're making a good decision. >> J. P. Your thoughts. You guys are on a tear. We've got a great coverage of your the annual conference in Vegas. Recent cube coverage. Your company on paper looks like you're targeting one segment, but you have a lot of range and you're technical platform with data. Um, how you guys articulating to engineering? How do you keep them? What if some of the stories you tell them to attract them to join you guys? >> So number one thing is about the talent that we already have in hopes. So people want to come to work at a place where they can learn, contribute on dhe, also for their Carrie Carrie Respert, both inside Cooper and as the lead on coming into Cooper. They look at it and they say, Oh, you have ah, wide variety of things going on here. You're solving a business problem. But at the same time, the technology stocks are different. You're on all the best clothes are there, so that's an easy attraction for them to come in. But also, it's not just about getting people, and how do you retain them on? We've been lucky. That had very low tuition for many years. Right now in the engineering organization, especially in the value, it is a big deal. Andi. I think part of the things that that is the collaboration and cooperation that they get from everybody on. You know, it's an age old saying diversity and thought, unity in action, right? So I really promote people thinking about radius ideas and alternatives. But there is a time for that debate. And once we agree on a solution, we all pulled in and try to make that successful. And then you repeat that often, and it becomes part of part of the culture and the way the organization operates as >> a follow up to culture. One thing that's become pretty clear is that's global engineering. You mention the valley very competitive, some start ups that they get on that rocket ship can get all the great talent. If you will public everyone. Everyone gets rich of one's happy, a good mission behind it, you know, win win outside. Some stars have to attract talent. You've got to start going on here. You might have a good colonel of great engineers, but you have development environments all over the world, so remote is a big thing. How do you manage the engineer remote? It's a time zone base. Does it put leaders in charge? Is there a philosophy in the Amazon? Has a two pizza team is their big thing. You get small groups. How did you guys view the engineering makeup? Because this becomes a part of the operational tension but operating model of engineering thoughts >> I can go first. I think there is a tension between keeping teams working on one problem on not distributing it across the world for efficiency reasons. But at the same time, how do you all owe for continuity, especially if you have a problem in one area? Can somebody else from another region step in in a different time zone continuing? That's always a problem, and then the other one is in a landscape like ours, in which is not uncommon for many, many companies. It is not that they built a lot of fragmented things. They all need to work together. So having a level of continuity within the radius remote centers is really critical on everybody has their own recipe for this one. But the ones that works for us and I've seen that played out many times, is if you can get a set off teams, toe, focus on certain problem areas and become experts in those >> cohesive within their >> within the physical, and then also have enough critical mass within a center that gives you the good balance between working on. One thing. Worse is knowing everything. So so that works for us, and I I think that's that's the way to get out >> of the operating system. It is a couple highly cohesive, >> and you need to have the right technical leaders on both sides and be willing to collaborate with each other >> partner thoughts >> I want to emphasize on the last statement you really need strong good, really, you know, trusted leaders in the location to Canada, then inculcated more bigger team everything Glassdoor groove from one location to four locations in last three years. And one thing that we learned after our first remote location that we started was that when we seeded our new remote location with few people from the original location that hoped start, you know, the similar aspects of what glassware stands for and over core at those and values. And then, as we added, new people, they just can easily just transfer to them so that hope does in a big way. And then he moved to Chicago with the same idea and, of course, Brazil. Now with the same >> knowledge transfer culture transfer, >> it all makes it easy. Even you have few people seating from the original location that was court for us. >> Pop in actually started their first remote office in San Francisco, which has now become their headquarters. So she has a lot of experience. Everyone of scale er's customers globally. You know, we sell the engineer, so we're dealing with with our customers who are dealing with this problem all the time. And in addition to culture, one thing that seems to bubble up regularly is can do you know when they need a common tool set and where they can do their own thing. How do you, you know, balance that and where do you need a single source of truth that people can agree on? And again, where can people have different points of view? >> You're talking sing associates from code base to what could >> be whatever, Like in our case, it's yeah, if you're going to troubleshoot something, you know, where the logs, the truth in the logs, Are you gonna have a single source for that? But for other people, it could be the data that they're bringing in or how they analyze the business. But if you can be proactive about understanding, when is commonality of tools of approach, of philosophy, of data, whatever, when it's commonality going to be what we drive and when are we going to allow people to do their own thing? And if you can put that framework in place than people know when they have the latitude and when they got a snap to grit and you could move a lot more quickly and there's kind of a technical debt that isn't code based? It's more about this kind of stuff, right? It's tool based its process and culture based. And if you can be more proactive about avoiding that debt, then you're gonna move more quickly. >> Videoconferencing. Very, very important. You should be able to jump on a video Constance very easily to be able to connect with someone driving just a phone calls all of these face time, different areas of face time Technology plays a big role >> technology. This is This is a modern management challenge for the new way to leave because it used to be just outsource. Here's the specs member, the old P. R. D S and M R D's. There's the specs, and you just kind of build it. Now it's much more collaborative to your point. There's really product and engineering going on, and it's gotta be. It's evolving. This is a key new ingredient >> because the expectation on the quality of product is so much more higher than competition is so much more. >> And when you know these engineers build in a lot of cases, they have to operate it now. So, like you say, whether it's a free service to a consumer, Aurens in enterprise, the expectation is perfect. No downtime, no hiccups >> and the reward incentives now become a big part of this now. New way of doing things. So I gotta ask the natural question. What's the reward system? Because Google really kind of pioneered the idea of a host 20% of your time work on your own project. That was about a decade or so ago. Now it's evolved beyond that to free lunches and all these other perks, but this has got to appeal to the human being behind it. What are some of the reward mechanisms? You guys see his management that's that's helpful in growing, nurturing and scaling up engineering organizations. >> Well, engineers are human, and as every human autonomy is critical for any aspects of moderation. And that's what please the core level. Then, of course, lunches, matter and other perks and benefits matter. Snacks of pours. Good coffee machine definitely is the core of it, but autonomy of what you want to do and is that the line. But what we want or what we are trying to deliver, and the aspect and the information of I did and rolled this out, what was the impact of it? That new should go back to that engineer who built that. So threading it through to the end and from the start is its very core for everybody to know because I want to know what I'm as I'm going every day. How is it helping >> and we really try. I personally try Thio. Make sure that each human on the team, regardless of their function, that we understand their potential and their career aspirations because a lot of times the the normal ladder, whatever that lander is, might not be right for every person. And people can pivot and use their skills in very, very different ways, and we need to invest in their ability to try new things. If it doesn't work out, let him come back. So you know, we try to spend time as a company for engineers not just in our company, but beyond. To really help them build out their own career, build out their own brands. Engineers more and more could be, you know, on TV shows and doing blog's and building out their own personal brand in their point of view. And that gives them impact. That goes beyond the one piece of code that they're writing for a company in a given day or a week. >> J. P you guys went public stock options. All these things going on as well. Your thoughts? Yeah, >> I just came back from a trip to my newest Dev center in Hyderabad, India. It's funny. I had sessions with every team over there. The number one topic was full >> s >> so excited about food. So there is something primal about food. Having said that, I think, uh, praise and recognition the age old things. They matter so much. That's what I've seen You acknowledge what somebody has done and kind of feedback to elect partner was saying, The impact that it creates, you know, it's it's a lot more fulfilling than monetary incentives. Not that they're not useful. Occasionally they are. But I think repeating that on doing it more often creates a sense off. Okay, here's what we can accomplish as a team. It is how I can contribute to it, and that creates a normal sense of purpose. >> Austin, you guys talked about tools of commonality is kind of key. It's always gonna be debates about which tools, much codes, languages to use, encoding, etcetera. But this brings up the notion of application development as you get continuous development. This is the operating model for modern engineering. What's the state of the art? What do you guys seeing as a best practice as managers to keep the machinery humming and moving along? And what what's on the horizon? What's next? >> Yeah, in my view, I would just say So what's humming and what state of the art I think I is core thio. Most of the systems and applications, the, uh, the core aspect of pretty much every company as you see, and that's the buzz word, even in Silicon Valley for the right reasons, is how we have built our platforms, insistence and ideas. But now let's make it smarter, and every company now has a lot of data. We are swimming in data, but it's very important that we can pick and pull the the core insides from that data to then power the same product and same system to make it more smarter, right? The whole goal for us ourselves is where they're making our platform or smarter, with the goal of making it more personalized and making sure that as users are navigating a project, pages they are seeing more personalized information so that they're not wasting their time there. We can make faster decisions in more rich data set, which is very catered towards them. So smart, so building that intelligence is core. >> And with continues, integration comes, continues risk. All right, so no risk, no reward. And so we live in an era of freemium. Free service is so you know why not take the risk? You don't have to do an A B test. You got digital. You do a B, C D and use all kinds of analytics. So this is actually a creative opportunity for engineering as they get to the front lines you mentioned earlier getting part of the empowerment. How is the risk taking changing the management? >> You know, I deal with class off users were willing to pay money, so I don't know if I can talk a lot about the freedom aspect of the problem. But now there's always desire for new functionality. If you want it, otherwise you don't want it. There's a lot of risk of worsens that's still floating around, especially in the interprets there today. On it is a big tension that you have to deal with. If you're not careful, then you can introduce problems on believing you're operating on the cloud and you're servicing thousands of customers. A small change can bring down the entire ecosystem, so you'll take it very seriously. You're helping others run their business, and that means you had invest in the right tools and processes. >> So you guys are actually Freemium business model, but still engineers. I got a test that they want to take the rhythms. So is it a cloud sand boxing? How is the risk taking managed? How you guys encouraging risk without having people hurt? You don't >> wantto overburden engineers to the point. They feel stifled and they cannot do anything. So there is a right balance. So you know, there are many techniques we follow the. For example, we roll out the software, tow US staging environment so customers can play around and make sure things are not breaking for their comfort more so than for us. But it is an important part of the equation, and then internally, you have to invest a lot of planning. Appropriately, there are the high risk content on the features, and then there are the low risk ones. You want to think about experimentation frameworks in no way be testing and so on and more importantly, about automation and testing. I don't think if a customer logs a bug and finds the problem, they don't want to see it one more time. Ever really have to make sure that those things don't happen when you're investing robust automation around testing processes because there isn't enough time for the complexity of these applications for destiny thing, man, >> this whale automation with cloud comes in containers kubernetes. All of >> those things, you know you heard will enable engineers with the technology said so that they contested scale. You have to provide access to production like data because you have to worry about no privacy, security and all those aspects. But at the same time, they need to have access to the variety off configurations that are out there so that they contested meaningful so to invest in all of those things. >> But I'll take it back to kind of where we started. This, which is the human factor with continuous delivery, is this continuous risk, and it doesn't matter if this engineer is supporting a free consumer application or the highest end of enterprise. When something goes wrong, this, their stress level goes through the roof and you know, how can we equipped? These people, too, solve problems in real time to have that visibility, to have whatever tool said or date or whatever they need? Because at the end of the day, a bad day for an engineer is a day when something is breaking and they're the ones that have to stay up all night and fix it and a good day for an engineer. A human being is the day they get to go home and have dinner with the family or not be woken up in the night. And there is >> for kite surfing or whatever, you >> know, whatever they dio, there's, you know, there is truly a human way. We think about engineers and engineers get up every day, and they want to change the world and they want to make an impact. And thank God we have, you know, teams of engineers that do that for all of us, and they're human beings, and there's a level of continuous stress that we've injected into their lives every day and to the extent that we, as companies and managers and leaders, can help take some of that burden off of them. The world becomes >> the whole being seeing the results of their work to is rewarding as well. >> Scaler does a lot of stuff there, so I have to call that are at the same time in a lot of very good nuggets, J P. Brother. But one more thing that has shifted in terms of how process of practice works is more of more. Engineers now participate very early on in product development is in the day. They try to understand what is the context and why are we doing. And we do a lot of users research to understand that that process, so that they have full context, that they are building in developing eso they're more of a partner now and not an afterthought. >> Think agile And Dev ops to me has proven that the notion of silos and waterfall practices has democratizing flatten. The organization's out where interdisciplinary crossovers are happening. >> Oh, yes, >> and this has been an interesting art of management is encouraging the right person that crust over the right line was you give people little taste, but sometimes they may not belong there kind of called herding cats in the old days. But now it's more of managing kind of interests and growth there. >> That original Dev ops model, though if you have anybody read the Phoenix project like years ago, but it it was really about bringing different points of view. It's a diversity thing. It's bringing different points of view around the table before the first line. It is written so that you're thinking about every angle on the problem and on the ongoing operation of whatever you're building >> Well, it's all about diversity and inclusion and diversity. I was with states, inclusion and diversity, diversity, inclusion Because male and females are involved. We have two females in tech here. This has been a discussion. We still don't have the numbers up to the senior levels within engineering in general. What has to happen to move the needle for women in tech and or inclusionary people involved in engineering to get the right perspective? What's what's >> not? Start with J P because he's actually a huge champion, and without the men involved, we don't have a solutions, >> inclusion and diversity, J. P your thoughts on this was super important. >> Yeah, Number one is recognition. I was stealing Christine yesterday. I just came back from India. That's like told you I took a picture there of my management team. Came back here, looked at it. There is no female, No right, it's crazy. I mean, it's not that we're not trying on gum it. We had the same problem and we started our center in 2015 right? There was a group picture off the team. There was like they were like two women on the thing. We put a lot of effort into it on. Two years later, a significant chunk of the organization has got women embedded in the team's came because we tried. We went out. Look, for those who are good in this area is not that we compromised on the qualifications. It's really about putting some energy in tow, getting the right resumes and then looking at it. The other thing. We're also doing his cultivation. You have to go to the grassroots because there are just enough women engineers. It's unfortunate, for whatever reasons, they're not taking up that professional military enough studies written on it So last two years we weigh, have conducted something called rails. Girls in India, 150 school age children, Women. I mean, girls come in and then we have supported them, run their classes, hold a class. And that helps, you know, even if 10% off them, you know, choose to take up this profession. It's gonna be a big boost. And we have to do a lot more of those in my opinion. >> Europe T rex President Leading Engineering. What's your view? >> Well, I'll say this, you know, for the people who are participating in helping drive this mission just like J. P. I say thank you, especially for men who are participating in it. We cannot do this without you, but for all the people who, if they're not participate in participating in helping drive this mission, I have all share this one data, uh, one of the initiative that glass or drives this gender pay gap, which is also an outcome off, not having diverse outlook at all levels into in the workplace. And we in our economic research team. They did a study and they shared a projection off when will be closed. The gender pay gap. It's 2017. That's depressing. So for for me, when I hear people who say you know, they, they don't want to participate or they don't think this is the right approach of solving for diversity in workplace, I say Okay, but that's not the reason for you to not participate and stay out. If it join it, join it in your own way. But it's only when l offers. Can I see it as a real problem and participate just like Gibby, as you said grassroot level as well as outside One of the example that I told my team when they say, You know, we don't want to drop the bar, the quality bar, I say Sure, don't drive it, but don't drop it. But if you have two candidates, one with a diverse background, Um, who who might be after cable to the same job in 2 to 3 months over someone who slam dunk today, let's invest in the person who is bringing the diverse background for 2 to 3 months and then make them successful. That's not dropping the bar that's still supporting and investing in helping diversity. >> My good friend and heat you saw at IBM. They put out a survey said Diversity, inclusion, diversity. First companies have a bit of advantage, so the investment is so much lower in the bars, more bringing perspective because if we tell about software here has male and female and that's being 17% female, it's >> not just, you know, I had two things to the comments, all of which I agree with one. It's not just a pipeline problem. It is a a culture problem where people have to feel welcome and it has to be a comfortable environment, and they have to believe that their diverse point of view matters and doesn't matter if they're men or women. But there are lots of times when we all make it hard for somebody with a different point of view to enter the conversation. So we have to do a better job of creating the culture, and secondly, there's a saying you have to see it to be it. We have to see people of diversity, gender and of every other type, cognitive diversity of all types at every level in the company. And, you know, we had the same thing, so I'm lucky enough to send a Fortune 500 public board. And I spend a lot of my time helping women and people of color and diversity get on public boards. But if you go back seven years ago, we were 14% women on public boards and it did not move and it did not move and it did not move and in one year popped over 20%. And that's before the loss. So you know, you make these linear projections we can with effort, yes, actually make >> a >> difference. It just takes a very concerted effort. And in this case, particularly for engineering and for leadership, it is making a concerted effort at every level, from board to CEO to executive team to all levels down. Making sure we have inclusion and diversity in >> this is a modern management challenge in the new way of leading managing >> this process. These things, This >> is the big challenge, folks, thanks so much for coming on. Really appreciate. Final question for you guys is what if you could summarize the new way to lead and his modern error from an engineering standpoint, building out of companies building along durable value creation with its company a product or service. What is the key keys to success >> as a leader >> as a leader has a new brand of leaders. >> I would say, You know, this lot goes into, I'm sure you need to know engineering and all the strategic aspect of your job. But the core aspect I feel, is as a leader, my success depends on the quality of relationships I'm building with my team and members that I work with. So that goes into the people aspect, the people connection that goes into it, >> J p. >> Absolutely People are are a big portion of the story. I also feel understanding the problem and driving for results. You know, it's not just about building something. It's about building for a purpose. What is it that you're you're tryingto accomplish and continuing to find that? And working with the teams is so critical for success, especially in a fast moving in Christine. >> Yeah, I agree. It is all about the people, and I think old and new. This hasn't changed. People need to feel like they belong and they're being appreciated, and they're being heard >> scaler. Glass door Copa software. You guys do a great work. Thanks for sharing the engineering inputs, Thio. Leading successful companies. >> Thank you for >> your leadership. Thank you. >> Thank you so much. >> I'm shot for the Q. Thanks for watching. >> Well.

>> Ladies and gentlemen, please welcome Red Hat President Products and Technologies. Paul Cormier. Boring. >> Welcome back to Boston. Welcome back. And welcome back after a great night last night of our opening with with Jim and talking to certainly saw ten Jenny and and especially our customers. It was so great last night to hear our customers in how they set their their goals and how they met their goals. All possible because certainly with a little help from red hat, but all possible because of because of open source. And, you know, sometimes we have to all due that has set goals. And I'm going to talk this morning about what we as a company and with community, have set for our goals along the way. And sometimes you have to do that. You know, audacious goals. It can really change the perception of what's even possible. And, you know, if I look back, I can't think of anything, at least in my lifetime, that's more important. Or such a big golden John F. Kennedy setting the gold to the American people to go to the moon. I believe it or not, I was really, really only three years old when he said that, honestly. But as I grew up, I remember the passion around the whole country and the energy to make that goal a reality. So let's sort of talk about in compare and contrast, a little bit of where we are technically at that time, you know, tto win and to beat and winning the space race and even get into the space race. There was some really big technical challenges along the way. I mean, believe it or not. Not that long ago. But even But back then, math Malik mathematical calculations were being shifted from from brilliant people who we trusted, and you could look in the eye to A to a computer that was programmed with the results that were mostly printed out. This this is a time where the potential of computers was just really coming on the scene and, at the time, the space race at the time of space race it. It revolved around an IBM seventy ninety, which was one of the first transistor based computers. It could perform mathematical calculations faster than even the most brilliant mathematicians. But just like today, this also came with many, many challenges And while we had the goal of in the beginning of the technique and the technology to accomplish it, we needed people so dedicated to that goal that they would risk everything. And while it may seem commonplace to us today to trust, put our trust in machines, that wasn't the case. Back in nineteen sixty nine, the seven individuals that made up the Mercury Space crew were putting their their lives in the hands of those first computers. But on Sunday, July twentieth, nineteen sixty nine, these things all came together. The goal, the technology in the team and a human being walked on the moon. You know, if this was possible fifty years ago, just think about what Khun B. Accomplished today, where technology is part of our everyday lives. And with technology advances at an ever increasing rate, it's hard to comprehend the potential that sitting right at our fingertips every single day, everything you know about computing is continuing to change. Today, let's look a bit it back. A computing In nineteen sixty nine, the IBM seventy ninety could process one hundred thousand floating point operations per second, today's Xbox one that sitting in most of your living rooms probably can process six trillion flops. That's sixty million times more powerful than the original seventy ninety that helped put a human being on the moon. And at the same time that computing was, that was drastically changed. That this computing has drastically changed. So have the boundaries of where that computing sits and where it's been where it lives. At the time of the Apollo launch, the computing power was often a single machine. Then it moved to a single data center, and over time that grew to multiple data centers. Then with cloud, it extended all the way out to data centers that you didn't even own or have control of. But but computing now reaches far beyond any data center. This is also referred to as the edge. You hear a lot about that. The Apollo's, the Apollo's version of the Edge was the guidance system, a two megahertz computer that weighed seventy pounds embedded in the capsule. Today, today the edge is right here on my wrist. This apple watch weighs just a couple of ounces, and it's ten ten thousand times more powerful than that seventy ninety back in nineteen sixty nine But even more impactful than computing advances, combined with the pervasive availability of it, are the changes and who in what controls those that similar to social changes that have happened along the way. Shifting from mathematicians to computers, we're now facing the same type of changes with regards to operational control of our computing power. In its first forms. Operational control was your team, your team within your control? In some cases, a single person managed everything. But as complexity grows, our team's expanded, just like in the just like in the computing boundaries, system integrators and public cloud providers have become an extension of our team. But at the end of the day, it's still people that are still making all the decisions going forward with the progress of things like a I and software defined everything. It's quite likely that machines will be managing machines, and in many cases that's already happening today. But while the technology at our finger tips today is so impressive, the pace of changing complexity of the problems we aspire to solve our equally hard to comprehend and they are all intertwined with one another learning from each other, growing together faster and faster. We are tackling problems today on a global scale with unsinkable complexity beyond anyone beyond what any one single company or even one single country Khun solve alone. This is why open source is so important. This is why open source is so needed today in software. This is why open sources so needed today, even in the world, to solve other types of complex problems. And this is why open source has become the dominant development model which is driving the technology direction. Today is to bring two brother to bring together the best innovation from every corner of the planet. Toe fundamentally change how we solve problems. This approach and access the innovation is what has enabled open source To tackle The challenge is big challenges, like creating the hybrid cloud like building a truly open hybrid cloud. But even today it's really difficult to bridge the gap of the innovation. It's available in all in all of our fingertips by open source development, while providing the production level capabilities that are needed to really dip, ploy this in the enterprise and solve RIA world business problems. Red Hat has been committed to open source from the very, very beginning and bringing it to solve enterprise class problems for the last seventeen plus years. But when we built that model to bring open source to the enterprise, we absolutely knew we couldn't do it halfway tow harness the innovation. We had to fully embrace the model. We made a decision very early on. Give everything back and we live by that every single day. We didn't do crazy crazy things like you hear so many do out there. All this is open corps or everything below. The line is open and everything above the line is closed. We didn't do that, and we gave everything back Everything we learned in the process of becoming an enterprise class technology company. We gave it all of that back to the community to make better and better software. This is how it works. And we've seen the results of that. We've all seen the results of that and it could only have been possible within open source development model we've been building on the foundation of open source is most successful Project Lennox in the architecture of the future hybrid and bringing them to the Enterprise. This is what made Red Hat, the company that we are today and red hats journey. But we also had the set goals, and and many of them seemed insert insurmountable at the time, the first of which was making Lennox the Enterprise standard. And while this is so accepted today, let's take a look at what it took to get there. Our first launch into the Enterprise was rail two dot one. Yes, I know we two dot one, but we knew we couldn't release a one dato product. We knew that and and we didn't. But >> we didn't want to >> allow any reason why anyone of any customer anyone shouldn't should look past rail to solve their problems as an option. Back then, we had to fight every single flavor of Unix in every single account. But we were lucky to have a few initial partners and Big Eyes v partners that supported Rehl out of the gate. But while we had the determination, we knew we also had gaps in order to deliver on our on our priorities. In the early days of rail, I remember going to ask one of our engineers for a past rehl build because we were having a customer issue on it on an older release. And then I watched in horror as he rifled through his desk through a mess of CDs and magically came up and said, I found it here It is told me not to worry that the build this was he thinks this was the bill. This was the right one, and at that point I knew that despite the promise of Lennox, we had a lot of work ahead of us. The not only convinced the world that Lennox was secure, stable, an enterprise ready, but also to make that a reality. But we did. And today this is our reality. It's all of our reality. From the Enterprise Data Center standard to the fastest computers on the planet, Red Hat Enterprise, Lennox has continually risen to the challenge and has become the core foundation that many mission critical customers run and bet their business on. And an even bigger today Lennox is the foundation of which practically every single technology initiative is built upon. Lennox is not only standard toe build on today, it's the standard for innovation that builds around it. That's the innovation that's driving the future as well. We started our story with rail two dot one, and here we are today, seventeen years later, announcing rally as we did as we did last night. It's specifically designed for applications to run across the open hybrid. Clyde Cloud. Railed has become the best operating simp system for on premise all the way out to the cloud, providing that common operating model and workload foundation on which to build hybrid applications. Let's take it. Let's take a look at how far we've come and see this in action. >> Please welcome Red Hat Global director of developer experience, burst Sutter with Josh Boyer, Timothy Kramer, Lars Carl, it's Key and Brent Midwood. All right, we have some amazing things to show you. In just a few short moments, we actually have a lot of things to show you. And actually, Tim and Brandt will be with us momentarily. They're working out a few things in the back because we have a lot of this is gonna be a live demonstration, some incredible capabilities. Now you're going to see clear innovation inside the operating system where we worked incredibly hard to make it vast cities. You're free to manage many, many machines. I want you thinking about that as we go to this process. Now, also, keep in mind that this is the basis our core platform for everything we do here. Red hat. So it is an honor for me to be able to show it to you live on stage today. And so I recognize the many of you in the audience right now. Her hand's on systems administrators, systems, architect, citizens, engineers. And we know that you're under ever growing pressure to deliver needed infrastructure. Resource is ever faster, and that is a key element to what you're thinking about every day. Well, this has been a core theme, and our design decisions find red Odd Enterprise Lennox eight and intelligent operating system, which is making it fundamentally easier for you manage machines that scale. So hold what you're about to see next. Feels like a new superpower and and that redhead azure force multiplier. So first, let me introduce you to a large. He's totally my limits guru. >> I wouldn't call myself a girl, but I I guess you could say that I want to bring Lennox and light meant to more people. >> Okay, Well, let's let's dive in. And we're not about the clinic's eight. >> Sure. Let me go. And Morgan, >> wait a >> second. There's windows. >> Yeah, way Build the weft Consul into Really? That means that for the first time, you can log in from any device including your phone or this standard windows laptop. So you just go ahead and and to my Saturday lance credentials here. >> Okay, so now >> you're putting >> your limits password and over the web. >> Yeah, that might sound a bit scary at first, but of course, we're using the latest security tech by T. L s on dh csp on. Because that's the standard Lennox off site. You can use everything that you used to like a stage keys, OTP, tokens and stuff like this. >> Okay, so now I see the council right here. I love the dashboard overview of the system, but what else can you tell us about this council? >> Right? Like right here. You see the load of the system, some some of its properties. But you can also dive into logs everything that you're used to from the command line, right? Or lookit, services. This's all the services I've running, can start and stuff them and enable >> OK, I love that feature right there. So what about if I have to add a whole new application to this environment? >> Good that you're bringing that up. We build a new future into hell called application streams. Which the way for you to install different versions of your half stack that are supported I'LL show you with Youngmin a command line. But since Windows doesn't have a proper terminal, I'll just do it in the terminal that we built into the Web console Since the browser, I can even make this a bit bigger. Go to, for example, to see the application streams that we have for Poskus. Ijust do module list and I see you know we have ten and nine dot six Both supported tennis a default on defy enable ninety six Now the next time that I installed prescribes it will pull all their lady towards from them at six. >> Ok, so this is very cool. I see two verses of post Chris right here What tennis to default. That is fantastic and the application streams making that happen. But I'm really kind of curious, right? I loved using know js and Java. So what about multiple versions of those? >> Yeah, that's exactly the idea way. Want to keep up with the fast moving ecosystems off programming language? Isn't it a business? >> Okay, now, But I have another key question. I know some people were thinking it right now. What about Python? >> Yeah. In fact, in a minimum and still like this, python gives you command. Not fact. Just have to type it correctly. You can't just install which everyone you want two or three or whichever your application needs. >> Okay, Well, that is I've been burned on that one before. Okay, so no actual. Have a confession for all you guys. Right here. You guys keep this amongst yourselves. Don't let Paul No, I'm actually not a linnet systems administrator. I'm an application developer, an application architect, And I recently had to go figure out how to extend the file system. This is for real. And I'm going to the rat knowledge base and looking up things like, you know, PV create VD, extend resized to f s. And I have to admit, that's hard, >> right? I've opened the storage space for you right here, where you see an overview of your storage. And the council has made for people like you as well not only for people that I knew that when you two lunatics, right? It's if you're running, you're running some of the commands only, you know, some of the time you don't remember them. So, for example, I haven't felt twosome here. That's a little bit too small. Let me just throw it. It's like, you know, dragging this lighter. It calls all the command in the background for you. >> Oh, that is incredible. Is that simple? Just drag and drop. That is fantastic. Well, so I actually, you know, we'll have another question for you. It looks like now this linen systems administration is no longer a dark heart involving arcane commands typed into a black terminal. Like using when those funky ergonomic keyboards you know I'm talking about right? Do >> you know a lot of people, including me and people in the audience like that dark out right? And this is not taking any of that away. It's on additional tool to bring limits to more people. >> Okay, well, that is absolute fantastic. Thank you so much for that Large. And I really love him installing everything is so much easier, including a post gra seeker and, of course, the python that we saw right there. So now I want to change gears for a second because I actually have another situation that I'm always dealing with. And that is every time I want to build a new Lenox system, not only I don't want to have to install those commands again and again, it feels like I'm doing it over and over. So, Josh, how would I create a golden image? One VM image that can use and we have everything pre baked in? >> Yeah, absolutely. But >> we get that question all the time. So really includes image builder technology. Image builder technology is actually all of our hybrid cloud operating system image tools that we use to build our own images and rolled up in a nice, easy to integrate new system. So if I come here in the web console and I go to our image builder tab, it brings us to blueprints, right? Blueprints or what we used to actually control it goes into our golden image. Uh, and I heard you and Lars talking about post present python. So I went and started typing here. So it brings us to this page, but you could go to the selected components, and you can see here I've created a blueprint that has all the python and post press packages in it. Ah, and the interesting thing about this is it build on our existing kickstart technology. But you can use it to deploy that whatever cloud you want. And it's saved so that you don't actually have to know all the various incantations from Amazon toe azure to Google, whatever it's all baked in on. When you do this, you can actually see the dependencies that get brought in as well. Okay. Should we create one life? Yes, please. All right, cool. So if we go back to the blueprints page and we click create blueprint Let's, uh let's make a developer brute blueprint here. So we click great, and you can see here on the left hand side. I've got all of my content served up by Red Hat satellite. We have a lot of great stuff, and really, But we can go ahead and search. So we'LL look for post grows and you know, it's a developer image at the client for some local testing. Um, well, come in here and at the python bits. Probably the development package. We need a compiler if we're going to actually build anything. So look for GCC here and hey, what's your favorite editor? >> A Max, Of course, >> Max. All right. Hey, Lars, about you. I'm more of a person. You Maxim v I All right, Well, if you want to prevent a holy war in your system, you can actually use satellite to filter that out. But we're going to go ahead and Adam Ball, sweetie, I'm a fight on stage. So wait, just point and click. Let the graphical one. And then when we're all done, we just commit our changes, and our image is ready to build. >> Okay, So this VM image we just created right now from that blueprint this is now I can actually go out there and easily deploys of deploy this across multiple cloud providers. And as well as this on stage are where we have right now. >> Yeah, absolutely. We can to play on Amazon as your google any any infrastructure you're looking for so you can really hit your Clyburn hybrid cloud operating system images. >> Okay. All right, listen, we >> just go on, click, create image. Uh, we can select our different types here. I'm gonna go ahead and create a local VM because it's available image, and maybe they want to pass it around or whatever, and I just need a few moments for it to build. >> Okay? So while that's taking a few moments, I know there's another key question in the minds of the audience right now, and you're probably thinking I love what I see. What Right eye right hand Priceline say. But >> what does it >> take to upgrade from seven to eight? So large can you show us and walk us through an upgrade? >> Sure, this's my little Thomas Block that I set up. It's powered by what Chris and secrets over, but it's still running on seven six. So let's upgrade that jump over to my house fee on satellite on. You see all my relate machines here, including the one I showed you what Consul on before. And there is that one with my sun block and there's a couple others. Let me select those as well. This one on that one. Just go up here. Schedule remote job. And she was really great. And hit Submit. I made it so that it makes the booms national before. So if anything was wrong Kans throwback! >> Okay, okay, so now it's progressing. Here, >> it's progressing. Looks like it's running. Doing >> live upgrade on stage. Uh, >> seems like one is failing. What's going on here? Okay, we checked the tree of great Chuck. Oh, yeah, that's the one I was playing around with Butter fest backstage. What? Detective that and you know, it doesn't run the Afghan cause we don't support operating that. >> Okay, so what I'm hearing now? So the good news is, we were protected from possible failed upgrade there, So it sounds like these upgrades are perfectly safe. Aiken, basically, you know, schedule this during a maintenance window and still get some sleep. >> Totally. That's the idea. >> Okay, fantastic. All right. So it looks like upgrades are easy and perfectly safe. And I really love what you showed us there. It's good point. Click operation right from satellite. Ok, so Well, you know, we were checking out upgrades. I want to know Josh. How those v ems coming along. >> They went really well. So you were away for so long. I got a little bored and I took some liberties. >> What do you mean? >> Well, the image Bill And, you know, I decided I'm going to go ahead and deploy here to this Intel machine on stage Esso. I have that up and running in the web. Counsel. I built another one on the arm box, which is actually pretty fast, and that's up and running on this. Our machine on that went so well that I decided to spend up some an Amazon. So I've got a few instances here running an Amazon with the web console accessible there as well. On even more of our pre bill image is up and running an azure with the web console there. So the really cool thing about this bird is that all of these images were built with image builder in a single location, controlling all the content that you want in your golden images deployed across the hybrid cloud. >> Wow, that is fantastic. And you might think that so we actually have more to show you. So thank you so much for that large. And Josh, that is fantastic. Looks like provisioning bread. Enterprise Clinic Systems ate a redhead. Enterprise Enterprise. Rhetta Enterprise Lennox. Eight Systems is Asian ever before, but >> we have >> more to talk to you about. And there's one thing that many of the operations professionals in this room right now no, that provisioning of'em is easy, but it's really day two day three, it's down the road that those viens required day to day maintenance. As a matter of fact, several you folks right now in this audience to have to manage hundreds, if not thousands, of virtual machines I recently spoke to. Gentleman has to manage thirteen hundred servers. So how do you manage those machines? A great scale. So great that they have now joined us is that it looks like they worked things out. So now I'm curious, Tim. How will we manage hundreds, if not thousands, of computers? >> Welbourne, one human managing hundreds or even thousands of'em says, No problem, because we have Ansel automation. And by leveraging Ansel's integration into satellite, not only can we spin up those V em's really quickly, like Josh was just doing, but we can also make ongoing maintenance of them really simple. Come on up here. I'm going to show you here a satellite inventory and his red hat is publishing patches. Weaken with that danceable integration easily apply those patches across our entire fleet of machines. Okay, >> that is fantastic. So he's all the machines can get updated in one fell swoop. >> He sure can. And there's one thing that I want to bring your attention to today because it's brand new. And that's cloud that red hat dot com And here, a cloud that redhead dot com You can view and manage your entire inventory no matter where it sits. Of Redhead Enterprise Lennox like on Prem on stage. Private Cloud or Public Cloud. It's true Hybrid cloud management. >> OK, but one thing. One thing. I know that in the minds of the audience right now. And if you have to manage a large number servers this it comes up again and again. What happens when you have those critical vulnerabilities that next zero day CV could be tomorrow? >> Exactly. I've actually been waiting for a while patiently for you >> to get to the really good stuff. So >> there's one more thing that I wanted to let folks know about. Red Hat Enterprise. The >> next eight and some features that we have there. Oh, >> yeah? What is that? >> So, actually, one of the key design principles of relate is working with our customers over the last twenty years to integrate all the knowledge that we've gained and turn that into insights that we can use to keep our red hat Enterprise Lennox servers running securely, inefficiently. And so what we actually have here is a few things that we could take a look at show folks what that is. >> OK, so we basically have this new feature. We're going to show people right now. And so one thing I want to make sure it's absolutely included within the redhead enterprise in that state. >> Yes. Oh, that's Ah, that's an announcement that we're making this week is that this is a brand new feature that's integrated with Red Hat Enterprise clinics, and it's available to everybody that has a red hat enterprise like subscription. So >> I believe everyone in this room right now has a rail subscriptions, so it's available to all of them. >> Absolutely, absolutely. So let's take a quick look and try this out. So we actually have. Here is a list of about six hundred rules. They're configuration security and performance rules. And this is this list is growing every single day, so customers can actually opt in to the rules that are most that are most applicable to their enterprises. So what we're actually doing here is combining the experience and knowledge that we have with the data that our customers opt into sending us. So customers have opted in and are sending us more data every single night. Then they actually have in total over the last twenty years via any other mechanism. >> Now there's I see now there's some critical findings. That's what I was talking about. But it comes to CVS and things that nature. >> Yeah, I'm betting that those air probably some of the rail seven boxes that we haven't actually upgraded quite yet. So we get back to that. What? I'd really like to show everybody here because everybody has access to this is how easy it is to opt in and enable this feature for real. Okay, let's do that real quick, so I gotta hop back over to satellite here. This is the satellite that we saw before, and I'll grab one of the hosts and we can use the new Web console feature that's part of Railly, and via single sign on I could jump right from satellite over to the Web console. So it's really, really easy. And I'LL grab a terminal here and registering with insights is really, really easy. Is one command troops, and what's happening right now is the box is going to gather some data. It's going to send it up to the cloud, and within just a minute or two, we're gonna have some results that we can look at back on the Web interface. >> I love it so it's just a single command and you're ready to register this box right now. That is super easy. Well, that's fantastic, >> Brent. We started this whole series of demonstrations by telling the audience that Red Hat Enterprise Lennox eight was the easiest, most economical and smartest operating system on the planet, period. And well, I think it's cute how you can go ahead and captain on a single machine. I'm going to show you one more thing. This is Answerable Tower. You can use as a bell tower to managing govern your answerable playbook, usage across your entire organization and with this. What I could do is on every single VM that was spun up here today. Opt in and register insights with a single click of a button. >> Okay, I want to see that right now. I know everyone's waiting for it as well, But hey, you're VM is ready. Josh. Lars? >> Yeah. My clock is running a little late now. Yeah, insights is a really cool feature >> of rail. And I've got it in all my images already. All >> right, I'm doing it all right. And so as this playbook runs across the inventory, I can see the machines registering on cloud that redhead dot com ready to be managed. >> OK, so all those onstage PM's as well as the hybrid cloud VM should be popping in IRC Post Chris equals Well, fantastic. >> That's awesome. Thanks to him. Nothing better than a Red Hat Summit speaker in the first live demo going off script deal. Uh, let's go back and take a look at some of those critical issues affecting a few of our systems here. So you can see this is a particular deanna's mask issue. It's going to affect a couple of machines. We saw that in the overview, and I can actually go and get some more details about what this particular issue is. So if you take a look at the right side of the screen there, there's actually a critical likelihood an impact that's associated with this particular issue. And what that really translates to is that there's a high level of risk to our organization from this particular issue. But also there's a low risk of change. And so what that means is that it's really, really safe for us to go ahead and use answerable to mediate this so I can grab the machines will select those two and we're mediate with answerable. I can create a new playbook. It's our maintenance window, but we'LL do something along the lines of like stuff Tim broke and that'LL be our cause. We name it whatever we want. So we'Ll create that playbook and take a look at it, and it's actually going to give us some details about the machines. You know what, what type of reboots Efendi you're going to be needed and what we need here. So we'LL go ahead and execute the playbook and what you're going to see is the outputs goingto happen in real time. So this is happening from the cloud were affecting machines. No matter where they are, they could be on Prem. They could be in a hybrid cloud, a public cloud or in a private cloud. And these things are gonna be remediated very, very easily with answerable. So it's really, really awesome. Everybody here with a red hat. Enterprise licks Lennox subscription has access to this now, so I >> kind of want >> everybody to go try this like, we really need to get this thing going and try it out right now. But >> don't know, sent about the room just yet. You get stay here >> for okay, Mr. Excitability, I think after this keynote, come back to the red hat booth and there's an optimization section. You can come talk to our insights engineers. And even though it's really easy to get going on your own, they can help you out. Answer any questions you might have. So >> this is really the start of a new era with an intelligent operating system and beauty with intelligence you just saw right now what insights that troubles you. Fantastic. So we're enabling systems administrators to manage more red in private clinics, a greater scale than ever before. I know there's a lot more we could show you, but we're totally out of time at this point, and we kind of, you know, when a little bit sideways here moments. But we need to get off the stage. But there's one thing I want you guys to think about it. All right? Do come check out the in the booth. Like Tim just said also in our debs, Get hands on red and a prize winning state as well. But really, I want you to think about this one human and a multitude of servers. And if you remember that one thing asked you upfront. Do you feel like you get a new superpower and redhead? Is your force multiplier? All right, well, thank you so much. Josh and Lars, Tim and Brent. Thank you. And let's get Paul back on stage. >> I went brilliant. No, it's just as always, >> amazing. I mean, as you can tell from last night were really, really proud of relate in that coming out here at the summit. And what a great way to showcase it. Thanks so much to you. Birth. Thanks, Brent. Tim, Lars and Josh. Just thanks again. So you've just seen this team demonstrate how impactful rail Khun b on your data center. So hopefully hopefully many of you. If not all of you have experienced that as well. But it was super computers. We hear about that all the time, as I just told you a few minutes ago, Lennox isn't just the foundation for enterprise and cloud computing. It's also the foundation for the fastest super computers in the world. In our next guest is here to tell us a lot more about that. >> Please welcome Lawrence Livermore National Laboratory. HPC solution Architect Robin Goldstone. >> Thank you so much, Robin. >> So welcome. Welcome to the summit. Welcome to Boston. And thank thank you so much for coming for joining us. Can you tell us a bit about the goals of Lawrence Livermore National Lab and how high high performance computing really works at this level? >> Sure. So Lawrence Livermore National >> Lab was established during the Cold War to address urgent national security needs by advancing the state of nuclear weapons, science and technology and high performance computing has always been one of our core capabilities. In fact, our very first supercomputer, ah Univac one was ordered by Edward Teller before our lab even opened back in nineteen fifty two. Our mission has evolved since then to cover a broad range of national security challenges. But first and foremost, our job is to ensure the safety, security and reliability of the nation's nuclear weapons stockpile. Oh, since the US no longer performs underground nuclear testing, our ability to certify the stockpile depends heavily on science based science space methods. We rely on H P C to simulate the behavior of complex weapons systems to ensure that they can function as expected, well beyond their intended life spans. That's actually great. >> So are you really are still running on that on that Univac? >> No, Actually, we we've moved on since then. So Sierra is Lawrence Livermore. Its latest and greatest supercomputer is currently the Seconds spastic supercomputer in the world and for the geeks in the audience, I think there's a few of them out there. We put up some of the specs of Syrah on the screen behind me, a couple of things worth highlighting our Sierra's peak performance and its power utilisation. So one hundred twenty five Pata flops of performance is equivalent to about twenty thousand of those Xbox one excess that you mentioned earlier and eleven point six megawatts of power required Operate Sierra is enough to power around eleven thousand homes. Syria is a very large and complex system, but underneath it all, it starts out as a collection of servers running Lin IX and more specifically, rail. >> So did Lawrence. Did Lawrence Livermore National Lab National Lab used Yisrael before >> Sierra? Oh, yeah, most definitely. So we've been running rail for a very long time on what I'll call our mid range HPC systems. So these clusters, built from commodity components, are sort of the bread and butter of our computer center. And running rail on these systems provides us with a continuity of operations and a common user environment across multiple generations of hardware. Also between Lawrence Livermore in our sister labs, Los Alamos and Sandia. Alongside these commodity clusters, though, we've always had one sort of world class supercomputer like Sierra. Historically, these systems have been built for a sort of exotic proprietary hardware running entirely closed source operating systems. Anytime something broke, which was often the Vander would be on the hook to fix it. And you know, >> that sounds >> like a good model, except that what we found overtime is most the issues that we have on these systems were either due to the extreme scale or the complexity of our workloads. Vendors seldom had a system anywhere near the size of ours, and we couldn't give them our classified codes. So their ability to reproduce our problem was was pretty limited. In some cases, they've even sent an engineer on site to try to reproduce our problems. But even then, sometimes we wouldn't get a fix for months or else they would just tell us they weren't going to fix the problem because we were the only ones having it. >> So for many of us, for many of us, the challenges is one of driving reasons for open source, you know, for even open source existing. How has how did Sierra change? Things are on open source for >> you. Sure. So when we developed our technical requirements for Sierra, we had an explicit requirement that we want to run an open source operating system and a strong preference for rail. At the time, IBM was working with red hat toe add support Terrell for their new little Indian power architecture. So it was really just natural for them to bid a red. A rail bay system for Sierra running Raylan Cyril allows us to leverage the model that's worked so well for us for all this time on our commodity clusters any packages that we build for X eighty six, we can now build those packages for power as well as our market texture using our internal build infrastructure. And while we have a formal support relationship with IBM, we can also tap our in house colonel developers to help debug complex problems are sys. Admin is Khun now work on any of our systems, including Sierra, without having toe pull out their cheat sheet of obscure proprietary commands. Our users get a consistent software environment across all our systems. And if the security vulnerability comes out, we don't have to chase around getting fixes from Multan slo es fenders. >> You know, you've been able, you've been able to extend your foundation from all the way from X eighty six all all the way to the extract excess Excuse scale supercomputing. We talk about giving customers all we talked about it all the time. A standard operational foundation to build upon. This isn't This isn't exactly what we've envisioned. So So what's next for you >> guys? Right. So what's next? So Sierra's just now going into production. But even so, we're already working on the contract for our next supercomputer called El Capitan. That's scheduled to be delivered the Lawrence Livermore in the twenty twenty two twenty timeframe. El Capitan is expected to be about ten times the performance of Sierra. I can't share any more details about that system right now, but we are hoping that we're going to be able to continue to build on a solid foundation. That relish provided us for well over a decade. >> Well, thank you so much for your support of realm over the years, Robin. And And thank you so much for coming and tell us about it today. And we can't wait to hear more about El Capitan. Thank you. Thank you very much. So now you know why we're so proud of realm. And while you saw confetti cannons and T shirt cannons last night, um, so you know, as as burned the team talked about the demo rail is the force multiplier for servers. We've made Lennox one of the most powerful platforms in the history of platforms. But just as Lennox has become a viable platform with access for everyone, and rail has become viable, more viable every day in the enterprise open source projects began to flourish around the operating system. And we needed to bring those projects to our enterprise customers in the form of products with the same trust models as we did with Ralph seeing the incredible progress of software development occurring around Lennox. Let's let's lead us to the next goal that we said tow, tow ourselves. That goal was to make hybrid cloud the default enterprise for the architecture. How many? How many of you out here in the audience or are Cesar are? HC sees how many out there a lot. A lot. You are the people that our building the next generation of computing the hybrid cloud, you know, again with like just like our goals around Lennox. This goals might seem a little daunting in the beginning, but as a community we've proved it time and time again. We are unstoppable. Let's talk a bit about what got us to the point we're at right right now and in the work that, as always, we still have in front of us. We've been on a decade long mission on this. Believe it or not, this mission was to build the capabilities needed around the Lenox operating system to really build and make the hybrid cloud. When we saw well, first taking hold in the enterprise, we knew that was just taking the first step. Because for a platform to really succeed, you need applications running on it. And to get those applications on your platform, you have to enable developers with the tools and run times for them to build, to build upon. Over the years, we've closed a few, if not a lot of those gaps, starting with the acquisition of J. Boss many years ago, all the way to the new Cuban Eddie's native code ready workspaces we launched just a few months back. We realized very early on that building a developer friendly platform was critical to the success of Lennox and open source in the enterprise. Shortly after this, the public cloud stormed onto the scene while our first focus as a company was done on premise in customer data centers, the public cloud was really beginning to take hold. Rehl very quickly became the standard across public clouds, just as it was in the enterprise, giving customers that common operating platform to build their applications upon ensuring that those applications could move between locations without ever having to change their code or operating model. With this new model of the data center spread across so many multiple environments, management had to be completely re sought and re architected. And given the fact that environments spanned multiple locations, management, real solid management became even more important. Customers deploying in hybrid architectures had to understand where their applications were running in how they were running, regardless of which infrastructure provider they they were running on. We invested over the years with management right alongside the platform, from satellite in the early days to cloud forms to cloud forms, insights and now answerable. We focused on having management to support the platform wherever it lives. Next came data, which is very tightly linked toe applications. Enterprise class applications tend to create tons of data and to have a common operating platform foyer applications. You need a storage solutions. That's Justus, flexible as that platform able to run on premise. Just a CZ. Well, as in the cloud, even across multiple clouds. This let us tow acquisitions like bluster, SEF perma bitch in Nubia, complimenting our Pratt platform with red hat storage for us, even though this sounds very condensed, this was a decade's worth of investment, all in preparation for building the hybrid cloud. Expanding the portfolio to cover the areas that a customer would depend on to deploy riel hybrid cloud architectures, finding any finding an amplifying the right open source project and technologies, or filling the gaps with some of these acquisitions. When that necessarily wasn't available by twenty fourteen, our foundation had expanded, but one big challenge remained workload portability. Virtual machine formats were fragmented across the various deployments and higher level framework such as Java e still very much depended on a significant amount of operating system configuration and then containers happened containers, despite having a very long being in existence for a very long time. As a technology exploded on the scene in twenty fourteen, Cooper Netease followed shortly after in twenty fifteen, allowing containers to span multiple locations and in one fell swoop containers became the killer technology to really enable the hybrid cloud. And here we are. Hybrid is really the on ly practical reality in way for customers and a red hat. We've been investing in all aspects of this over the last eight plus years to make our customers and partners successful in this model. We've worked with you both our customers and our partners building critical realm in open shift deployments. We've been constantly learning about what has caused problems and what has worked well in many cases. And while we've and while we've amassed a pretty big amount of expertise to solve most any challenge in in any area that stack, it takes more than just our own learning's to build the next generation platform. Today we're also introducing open shit for which is the culmination of those learnings. This is the next generation of the application platform. This is truly a platform that has been built with our customers and not simply just with our customers in mind. This is something that could only be possible in an open source development model and just like relish the force multiplier for servers. Open shift is the force multiplier for data centers across the hybrid cloud, allowing customers to build thousands of containers and operate them its scale. And we've also announced open shift, and we've also announced azure open shift. Last night. Satya on this stage talked about that in depth. This is all about extending our goals of a common operating platform enabling applications across the hybrid cloud, regardless of whether you run it yourself or just consume it as a service. And with this flagship release, we are also introducing operators, which is the central, which is the central feature here. We talked about this work last year with the operator framework, and today we're not going to just show you today. We're not going to just show you open shift for we're going to show you operators running at scale operators that will do updates and patches for you, letting you focus more of your time and running your infrastructure and running running your business. We want to make all this easier and intuitive. So let's have a quick look at how we're doing. Just that >> painting. I know all of you have heard we're talking to pretend to new >> customers about the travel out. So new plan. Just open it up as a service been launched by this summer. Look, I know this is a big quest for not very big team. I'm open to any and all ideas. >> Please welcome back to the stage. Red Hat Global director of developer Experience burst Sutter with Jessica Forrester and Daniel McPherson. All right, we're ready to do some more now. Now. Earlier we showed you read Enterprise Clinic St running on lots of different hardware like this hardware you see right now And we're also running across multiple cloud providers. But now we're going to move to another world of Lennox Containers. This is where you see open shift four on how you can manage large clusters of applications from eggs limits containers across the hybrid cloud. We're going to see this is where suffer operators fundamentally empower human operators and especially make ups and Deb work efficiently, more efficiently and effectively there together than ever before. Rights. We have to focus on the stage right now. They're represent ops in death, and we're gonna go see how they reeled in application together. Okay, so let me introduce you to Dan. Dan is totally representing all our ops folks in the audience here today, and he's telling my ops, comfort person Let's go to call him Mr Ops. So Dan, >> thanks for with open before, we had a much easier time setting up in maintaining our clusters. In large part, that's because open shit for has extended management of the clusters down to the infrastructure, the diversity kinds of parent. When you take >> a look at the open ship console, >> you can now see the machines that make up the cluster where machine represents the infrastructure. Underneath that Cooper, Eddie's node open shit for now handles provisioning Andy provisioning of those machines. From there, you could dig into it open ship node and see how it's configured and monitor how it's behaving. So >> I'm curious, >> though it does this work on bare metal infrastructure as well as virtualized infrastructure. >> Yeah, that's right. Burn So Pa Journal nodes, no eternal machines and open shit for can now manage it all. Something else we found extremely useful about open ship for is that it now has the ability to update itself. We can see this cluster hasn't update available and at the press of a button. Upgrades are responsible for updating. The entire platform includes the nodes, the control plane and even the operating system and real core arrests. All of this is possible because the infrastructure components and their configuration is now controlled by technology called operators. Thes software operators are responsible for aligning the cluster to a desired state. And all of this makes operational management of unopened ship cluster much simpler than ever before. All right, I >> love the fact that all that's been on one console Now you can see the full stack right all way down to the bare metal right there in that one console. Fantastic. So I wanted to scare us for a moment, though. And now let's talk to Deva, right? So Jessica here represents our all our developers in the room as my facts. He manages a large team of developers here Red hat. But more importantly, she represents our vice president development and has a large team that she has to worry about on a regular basis of Jessica. What can you show us? We'LL burn My team has hundreds of developers and were constantly under pressure to deliver value to our business. And frankly, we can't really wait for Dan and his ops team to provisioned the infrastructure and the services that we need to do our job. So we've chosen open shift as our platform to run our applications on. But until recently, we really struggled to find a reliable source of Cooper Netease Technologies that have the operational characteristics that Dan's going to actually let us install through the cluster. But now, with operator, How bio, we're really seeing the V ecosystem be unlocked. And the technology's there. Things that my team needs, its databases and message cues tracing and monitoring. And these operators are actually responsible for complex applications like Prometheus here. Okay, they're written in a variety of languages, danceable, but that is awesome. So I do see a number of options there already, and preaches is a great example. But >> how do you >> know that one? These operators really is mature enough and robust enough for Dan and the outside of the house. Wilbert, Here we have the operator maturity model, and this is going to tell me and my team whether this particular operator is going to do a basic install if it's going to upgrade that application over time through different versions or all the way out to full auto pilot, where it's automatically scaling and tuning the application based on the current environment. And it's very cool. So coming over toothy open shift Consul, now we can actually see Dan has made the sequel server operator available to me and my team. That's the database that we're using. A sequel server. That's a great example. So cynics over running here in the cluster? But this is a great example for a developer. What if I want to create a new secret server instance? Sure, we're so it's as easy as provisioning any other service from the developer catalog. We come in and I can type for sequel server on what this is actually creating is, ah, native resource called Sequel Server, and you can think of that like a promise that a sequel server will get created. The operator is going to see that resource, install the application and then manage it over its life cycle, KAL, and from this install it operators view, I can see the operators running in my project and which resource is its managing Okay, but I'm >> kind of missing >> something here. I see this custom resource here, the sequel server. But where the community's resource is like pods. Yeah, I think it's cool that we get this native resource now called Sequel Server. But if I need to, I can still come in and see the native communities. Resource is like your staple set in service here. Okay, that is fantastic. Now, we did say earlier on, though, like many of our customers in the audience right now, you have a large team of engineers. Lost a large team of developers you gotta handle. You gotta have more than one secret server, right? We do one for every team as we're developing, and we use a lot of other technologies running on open shift as well, including Tomcat and our Jenkins pipelines and our dough js app that is gonna actually talk to that sequel server database. Okay, so this point we can kind of provisions, Some of these? Yes. Oh, since all of this is self service for me and my team's, I'm actually gonna go and create one of all of those things I just said on all of our projects, right Now, if you just give me a minute, Okay? Well, right. So basically, you're going to knock down No Jazz Jenkins sequel server. All right, now, that's like hundreds of bits of application level infrastructure right now. Live. So, Dan, are you not terrified? Well, I >> guess I should have done a little bit better >> job of managing guests this quota and historically just can. I might have had some conflict here because creating all these new applications would admit my team now had a massive back like tickets to work on. But now, because of software operators, my human operators were able to run our infrastructure at scale. So since I'm long into the cluster here as the cluster admin, I get this view of pods across all projects. And so I get an idea of what's happening across the entire cluster. And so I could see now we have four hundred ninety four pods already running, and there's a few more still starting up. And if I scroll to the list, we can see the different workloads Jessica just mentioned of Tomcats. And no Gs is And Jenkins is and and Siegel servers down here too, you know, I see continues >> creating and you have, like, close to five hundred pods running >> there. So, yeah, filters list down by secret server, so we could just see. Okay, But >> aren't you not >> running going around a cluster capacity at some point? >> Actually, yeah, we we definitely have a limited capacity in this cluster. And so, luckily, though, we already set up auto scale er's And so because the additional workload was launching, we see now those outer scholars have kicked in and some new machines are being created that don't yet have noticed. I'm because they're still starting up. And so there's another good view of this as well, so you can see machine sets. We have one machine set per availability zone, and you could see the each one is now scaling from ten to twelve machines. And the way they all those killers working is for each availability zone, they will. If capacities needed, they will add additional machines to that availability zone and then later effect fast. He's no longer needed. It will automatically take those machines away. >> That is incredible. So right now we're auto scaling across multiple available zones based on load. Okay, so looks like capacity planning and automation is fully, you know, handle this point. But I >> do have >> another question for year logged in. Is the cluster admin right now into the console? Can you show us your view of >> operator suffer operators? Actually, there's a couple of unique views here for operators, for Cluster admits. The first of those is operator Hub. This is where a cluster admin gets the ability to curate the experience of what operators are available to users of the cluster. And so obviously we already have the secret server operator installed, which which we've been using. The other unique view is operator management. This gives a cluster I've been the ability to maintain the operators they've already installed. And so if we dig in and see the secret server operator, well, see, we haven't set up for manual approval. And what that means is if a new update comes in for a single server, then a cluster and we would have the ability to approve or disapprove with that update before installs into the cluster, we'LL actually and there isn't upgrade that's available. Uh, I should probably wait to install this, though we're in the middle of scaling out this cluster. And I really don't want to disturb Jessica's application. Workflow. >> Yeah, so, actually, Dan, it's fine. My app is already up. It's running. Let me show it to you over here. So this is our products application that's talking to that sequel server instance. And for debugging purposes, we can see which version of sequel server we're currently talking to. Its two point two right now. And then which pod? Since this is a cluster, there's more than one secret server pod we could be connected to. Okay, I could see right there the bounder screeners they know to point to. That's the version we have right now. But, you know, >> this is kind of >> point of software operators at this point. So, you know, everyone in this room, you know, wants to see you hit that upgrade button. Let's do it. Live here on stage. Right, then. All >> right. All right. I could see where this is going. So whenever you updated operator, it's just like any other resource on communities. And so the first thing that happens is the operator pot itself gets updated so we actually see a new version of the operator is currently being created now, and what's that gets created, the overseer will be terminated. And that point, the new, softer operator will notice. It's now responsible for managing lots of existing Siegel servers already in the environment. And so it's then going Teo update each of those sickle servers to match to the new version of the single server operator and so we could see it's running. And so if we switch now to the all projects view and we filter that list down by sequel server, then we should be able to see us. So lots of these sickle servers are now being created and the old ones are being terminated. So is the rolling update across the cluster? Exactly a So the secret server operator Deploy single server and an H A configuration. And it's on ly updates a single instance of secret server at a time, which means single server always left in nature configuration, and Jessica doesn't really have to worry about downtime with their applications. >> Yeah, that's awesome dance. So glad the team doesn't have to worry about >> that anymore and just got I think enough of these might have run by Now, if you try your app again might be updated. >> Let's see Jessica's application up here. All right. On laptop three. >> Here we go. >> Fantastic. And yet look, we're We're into two before we're onto three. Now we're on to victory. Excellent on. >> You know, I actually works so well. I don't even see a reason for us to leave this on manual approval. So I'm going to switch this automatic approval. And then in the future, if a new single server comes in, then we don't have to do anything, and it'll be all automatically updated on the cluster. >> That is absolutely fantastic. And so I was glad you guys got a chance to see that rolling update across the cluster. That is so cool. The Secret Service database being automated and fully updated. That is fantastic. Alright, so I can see how a software operator doesn't able. You don't manage hundreds if not thousands of applications. I know a lot of folks or interest in the back in infrastructure. Could you give us an example of the infrastructure >> behind this console? Yeah, absolutely. So we all know that open shift is designed that run in lots of different environments. But our teams think that as your redhead over, Schiff provides one of the best experiences by deeply integrating the open chief Resource is into the azure console, and it's even integrated into the azure command line toll and the easy open ship man. And, as was announced yesterday, it's now available for everyone to try out. And there's actually one more thing we wanted to show Everyone related to open shit, for this is all so new with a penchant for which is we now have multi cluster management. This gives you the ability to keep track of all your open shift environments, regardless of where they're running as well as you can create new clusters from here. And I'll dig into the azure cluster that we were just taking a look at. >> Okay, but is this user and face something have to install them one of my existing clusters? >> No, actually, this is the host of service that's provided by Red hat is part of cloud that redhead that calm and so all you have to do is log in with your red hair credentials to get access. >> That is incredible. So one console, one user experience to see across the entire hybrid cloud we saw earlier with Red update. Right and red embers. Thank Satan. Now we see it for multi cluster management. But home shift so you can fundamentally see. Now the suffer operators do finally change the game when it comes to making human operators vastly more productive and, more importantly, making Devon ops work more efficiently together than ever before. So we saw the rich ice vehicle system of those software operators. We can manage them across the Khyber Cloud with any, um, shift instance. And more importantly, I want to say Dan and Jessica for helping us with this demonstration. Okay, fantastic stuff, guys. Thank you so much. Let's get Paul back out here >> once again. Thanks >> so much to burn his team. Jessica and Dan. So you've just seen how open shift operators can help you manage hundreds, even thousands of applications. Install, upgrade, remove nodes, control everything about your application environment, virtual physical, all the way out to the cloud making, making things happen when the business demands it even at scale, because that's where it's going to get. Our next guest has lots of experience with demand at scale. and they're using open source container management to do it. Their work, their their their work building a successful cloud, First platform and there, the twenty nineteen Innovation Award winner. >> Please welcome twenty nineteen Innovation Award winner. Cole's senior vice president of technology, Rich Hodak. >> How you doing? Thanks. >> Thanks so much for coming out. We really appreciate it. So I guess you guys set some big goals, too. So can you baby tell us about the bold goal? Helped you personally help set for Cole's. And what inspired you to take that on? Yes. So it was twenty seventeen and life was pretty good. I had no gray hair and our business was, well, our tech was working well, and but we knew we'd have to do better into the future if we wanted to compete. Retails being disrupted. Our customers are asking for new experiences, So we set out on a goal to become an open hybrid cloud platform, and we chose Red had to partner with us on a lot of that. We set off on a three year journey. We're currently in Year two, and so far all KP eyes are on track, so it's been a great journey thus far. That's awesome. That's awesome. So So you Obviously, Obviously you think open source is the way to do cloud computing. So way absolutely agree with you on that point. So So what? What is it that's convinced you even more along? Yeah, So I think first and foremost wait, do we have a lot of traditional IAS fees? But we found that the open source partners actually are outpacing them with innovation. So I think that's where it starts for us. Um, secondly, we think there's maybe some financial upside to going more open source. We think we can maybe take some cost out unwind from these big fellas were in and thirdly, a CZ. We go to universities. We started hearing. Is we interviewed? Hey, what is Cole's doing with open source and way? Wanted to use that as a lever to help recruit talent. So I'm kind of excited, you know, we partner with Red Hat on open shift in in Rail and Gloucester and active M Q and answerable and lots of things. But we've also now launched our first open source projects. So it's really great to see this journey. We've been on. That's awesome, Rich. So you're in. You're in a high touch beta with with open shift for So what? What features and components or capabilities are you most excited about and looking forward to what? The launch and you know, and what? You know what? What are the something maybe some new goals that you might be able to accomplish with with the new features. And yeah, So I will tell you we're off to a great start with open shift. We've been on the platform for over a year now. We want an innovation award. We have this great team of engineers out here that have done some outstanding work. But certainly there's room to continue to mature that platform. It calls, and we're excited about open shift, for I think there's probably three things that were really looking forward to. One is we're looking forward to, ah, better upgrade process. And I think we saw, you know, some of that in the last demo. So upgrades have been kind of painful up until now. So we think that that that will help us. Um, number two, A lot of our open shift workloads today or the workloads. We run an open shifts are the stateless apse. Right? And we're really looking forward to moving more of our state full lapse into the platform. And then thirdly, I think that we've done a great job of automating a lot of the day. One stuff, you know, the provisioning of, of things. There's great opportunity o out there to do mohr automation for day two things. So to integrate mohr with our messaging systems in our database systems and so forth. So we, uh we're excited. Teo, get on board with the version for wear too. So, you know, I hope you, Khun, we can help you get to the next goals and we're going to continue to do that. Thank you. Thank you so much rich, you know, all the way from from rail toe open shift. It's really exciting for us, frankly, to see our products helping you solve World War were problems. What's you know what? Which is. Really? Why way do this and and getting into both of our goals. So thank you. Thank you very much. And thanks for your support. We really appreciate it. Thanks. It has all been amazing so far and we're not done. A critical part of being successful in the hybrid cloud is being successful in your data center with your own infrastructure. We've been helping our customers do that in these environments. For almost twenty years now, we've been running the most complex work loads in the world. But you know, while the public cloud has opened up tremendous possibilities, it also brings in another type of another layer of infrastructure complexity. So what's our next goal? Extend your extend your data center all the way to the edge while being as effective as you have been over the last twenty twenty years, when it's all at your own fingertips. First from a practical sense, Enterprises air going to have to have their own data centers in their own environment for a very long time. But there are advantages of being able to manage your own infrastructure that expand even beyond the public cloud all the way out to the edge. In fact, we talked about that very early on how technology advances in computer networking is storage are changing the physical boundaries of the data center every single day. The need, the need to process data at the source is becoming more and more critical. New use cases Air coming up every day. Self driving cars need to make the decisions on the fly. In the car factory processes are using a I need to adapt in real time. The factory floor has become the new edge of the data center, working with things like video analysis of a of A car's paint job as it comes off the line, where a massive amount of data is on ly needed for seconds in order to make critical decisions in real time. If we had to wait for the video to go up to the cloud and back, it would be too late. The damage would have already been done. The enterprise is being stretched to be able to process on site, whether it's in a car, a factory, a store or in eight or nine PM, usually involving massive amounts of data that just can't easily be moved. Just like these use cases couldn't be solved in private cloud alone because of things like blatant see on data movement, toe address, real time and requirements. They also can't be solved in public cloud alone. This is why open hybrid is really the model that's needed in the only model forward. So how do you address this class of workload that requires all of the above running at the edge? With the latest technology all its scale, let me give you a bit of a preview of what we're working on. We are taking our open hybrid cloud technologies to the edge, Integrated with integrated with Aro AM Hardware Partners. This is a preview of a solution that will contain red had open shift self storage in K V M virtual ization with Red Hat Enterprise Lennox at the core, all running on pre configured hardware. The first hardware out of the out of the gate will be with our long time. Oh, am partner Del Technologies. So let's bring back burn the team to see what's right around the corner. >> Please welcome back to the stage. Red Hat. Global director of developer Experience burst Sutter with Kareema Sharma. Okay, We just how was your Foreign operators have redefined the capabilities and usability of the open hybrid cloud, and now we're going to show you a few more things. Okay, so just be ready for that. But I know many of our customers in this audience right now, as well as the customers who aren't even here today. You're running tens of thousands of applications on open chef clusters. We know that disappearing right now, but we also know that >> you're not >> actually in the business of running terminators clusters. You're in the business of oil and gas from the business retail. You're in a business transportation, you're in some other business and you don't really want to manage those things at all. We also know though you have lo latest requirements like Polish is talking about. And you also dated gravity concerns where you >> need to keep >> that on your premises. So what you're about to see right now in this demonstration is where we've taken open ship for and made a bare metal cluster right here on this stage. This is a fully automated platform. There is no underlying hyper visor below this platform. It's open ship running on bare metal. And this is your crew vanities. Native infrastructure, where we brought together via mes containers networking and storage with me right now is green mush arma. She's one of her engineering leaders responsible for infrastructure technologies. Please welcome to the stage, Karima. >> Thank you. My pleasure to be here, whether it had summit. So let's start a cloud. Rid her dot com and here we can see the classroom Dannon Jessica working on just a few moments ago From here we have a bird's eye view ofthe all of our open ship plasters across the hybrid cloud from multiple cloud providers to on premises and noticed the spare medal last year. Well, that's the one that my team built right here on this stage. So let's go ahead and open the admin console for that last year. Now, in this demo, we'LL take a look at three things. A multi plaster inventory for the open Harbor cloud at cloud redhead dot com. Second open shift container storage, providing convert storage for virtual machines and containers and the same functionality for cloud vert and bare metal. And third, everything we see here is scuba unit is native, so by plugging directly into communities, orchestration begin common storage. Let working on monitoring facilities now. Last year, we saw how continue native actualization and Q Bert allow you to run virtual machines on Cabinet is an open shift, allowing for a single converge platform to manage both containers and virtual machines. So here I have this dark net project now from last year behead of induced virtual machine running it S P darknet application, and we had started to modernize and continue. Arise it by moving. Parts of the application from the windows began to the next containers. So let's take a look at it here. I have it again. >> Oh, large shirt, you windows. Earlier on, I was playing this game back stage, so it's just playing a little solitaire. Sorry about that. >> So we don't really have time for that right now. Birds. But as I was saying, Over here, I have Visions Studio Now the window's virtual machine is just another container and open shift and the i d be service for the virtual machine. It's just another service in open shift open shifts. Running both containers and virtual machines together opens a whole new world of possibilities. But why stop there? So this here be broadened to come in. It is native infrastructure as our vision to redefine the operation's off on premises infrastructure, and this applies to all matters of workloads. Using open shift on metal running all the way from the data center to the edge. No by your desk, right to main benefits. Want to help reduce the operation casts And second, to help bring advance good when it is orchestration concept to your infrastructure. So next, let's take a look at storage. So open shift container storage is software defined storage, providing the same functionality for both the public and the private lads. By leveraging the operator framework, open shift container storage automatically detects the available hardware configuration to utilize the discs in the most optimal vein. So then adding my note, you don't have to think about how to balance the storage. Storage is just another service running an open shift. >> And I really love this dashboard quite honestly, because I love seeing all the storage right here. So I'm kind of curious, though. Karima. What kind of storage would you What, What kind of applications would you use with the storage? >> Yeah, so this is the persistent storage. To be used by a database is your files and any data from applications such as a Magic Africa. Now the A Patrick after operator uses school, been at this for scheduling and high availability, and it uses open shift containers. Shortest. Restore the messages now Here are on premises. System is running a caf co workload streaming sensor data on DH. We want toe sort it and act on it locally, right In a minute. A place where maybe we need low latency or maybe in a data lake like situation. So we don't want to send the starter to the cloud. Instead, we want to act on it locally, right? Let's look at the griffon a dashboard and see how our system is doing so with the incoming message rate of about four hundred messages for second, the system seems to be performing well, right? I want to emphasize this is a fully integrated system. We're doing the testing An optimization sze so that the system can Artoo tune itself based on the applications. >> Okay, I love the automated operations. Now I am a curious because I know other folks in the audience want to know this too. What? Can you tell us more about how there's truly integrated communities can give us an example of that? >> Yes. Again, You know, I want to emphasize everything here is managed poorly by communities on open shift. Right. So you can really use the latest coolest to manage them. All right. Next, let's take a look at how easy it is to use K native with azure functions to script alive Reaction to a live migration event. >> Okay, Native is a great example. If actually were part of my breakout session yesterday, you saw me demonstrate came native. And actually, if you want to get hands on with it tonight, you can come to our guru night at five PM and actually get hands on like a native. So I really have enjoyed using K. Dated myself as a software developer. And but I am curious about the azure functions component. >> Yeah, so as your functions is a function is a service engine developed by Microsoft fully open source, and it runs on top of communities. So it works really well with our on premises open shift here. Right now, I have a simple azure function that I already have here and this azure function, you know, Let's see if this will send out a tweet every time we live My greater Windows virtual machine. Right. So I have it integrated with open shift on DH. Let's move a note to maintenance to see what happens. So >> basically has that via moves. We're going to see the event triggered. They trigger the function. >> Yeah, important point I want to make again here. Windows virtue in machines are equal citizens inside of open shift. We're investing heavily in automation through the use of the operator framework and also providing integration with the hardware. Right, So next, Now let's move that note to maintain it. >> But let's be very clear here. I wanna make sure you understand one thing, and that is there is no underlying virtual ization software here. This is open ship running on bear. Meddle with these bare metal host. >> That is absolutely right. The system can automatically discover the bare metal hosts. All right, so here, let's move this note to maintenance. So I start them Internets now. But what will happen at this point is storage will heal itself, and communities will bring back the same level of service for the CAFTA application by launching a part on another note and the virtual machine belive my great right and this will create communities events. So we can see. You know, the events in the event stream changes have started to happen. And as a result of this migration, the key native function will send out a tweet to confirm that could win. It is native infrastructure has indeed done the migration for the live Ian. Right? >> See the events rolling through right there? >> Yeah. All right. And if we go to Twitter? >> All right, we got tweets. Fantastic. >> And here we can see the source Nord report. Migration has succeeded. It's a pretty cool stuff right here. No. So we want to bring you a cloud like experience, but this means is we're making operational ease a fuse as a top goal. We're investing heavily in encapsulating management knowledge and working to pre certify hardware configuration in working with their partners such as Dell, and they're dead already. Note program so that we can provide you guidance on specific benchmarks for specific work loads on our auto tuning system. >> All right, well, this is tow. I know right now, you're right thing, and I want to jump on the stage and check out the spare metal cluster. But you should not right. Wait After the keynote didn't. Come on, check it out. But also, I want you to go out there and think about visiting our partner Del and their booth where they have one. These clusters also. Okay, So this is where vmc networking and containers the storage all come together And a Kurban in his native infrastructure. You've seen right here on this stage, but an agreement. You have a bit more. >> Yes. So this is literally the cloud coming down from the heavens to us. >> Okay? Right here, Right now. >> Right here, right now. So, to close the loop, you can have your plaster connected to cloud redhead dot com for our insights inside reliability engineering services so that we can proactively provide you with the guidance through automated analyses of telemetry in logs and help flag a problem even before you notice you have it Beat software, hardware, performance, our security. And one more thing. I want to congratulate the engineers behind the school technology. >> Absolutely. There's a lot of engineers here that worked on this cluster and worked on the stack. Absolutely. Thank you. Really awesome stuff. And again do go check out our partner Dale. They're just out that door I can see them from here. They have one. These clusters get a chance to talk to them about how to run your open shift for on a bare metal cluster as well. Right, Kareema, Thank you so much. That was totally awesome. We're at a time, and we got to turn this back over to Paul. >> Thank you. Right. >> Okay. Okay. Thanks >> again. Burned, Kareema. Awesome. You know, So even with all the exciting capabilities that you're seeing, I want to take a moment to go back to the to the first platform tenant that we learned with rail, that the platform has to be developer friendly. Our next guest knows something about connecting a technology like open shift to their developers and part of their company. Wide transformation and their ability to shift the business that helped them helped them make take advantage of the innovation. Their Innovation award winner this year. Please, Let's welcome Ed to the stage. >> Please welcome. Twenty nineteen. Innovation Award winner. BP Vice President, Digital transformation. Ed Alford. >> Thanks, Ed. How your fake Good. So was full. Get right into it. What we go you guys trying to accomplish at BP and and How is the goal really important in mandatory within your organization? Support on everyone else were global energy >> business, with operations and over seventy countries. Andi. We've embraced what we call the jewel challenge, which is increasing the mind for energy that we have as individuals in the world. But we need to produce the energy with fuel emissions. It's part of that. One of our strategic priorities that we >> have is to modernize the whole group on. That means simplifying our processes and enhancing >> productivity through digital solutions. So we're using chlo based technologies >> on, more importantly, open source technologies to clear a community and say, the whole group that collaborates effectively and efficiently and uses our data and expertise to embrace the jewel challenge and actually try and help solve that problem. That's great. So So how did these heart of these new ways of working benefit your team and really the entire organ, maybe even the company as a whole? So we've been given the Innovation Award for Digital conveyor both in the way it was created and also in water is delivering a couple of guys in the audience poll costal and brewskies as he they they're in the team. Their teams developed that convey here, using our jail and Dev ops and some things. We talk about this stuff a lot, but actually the they did it in a truly our jail and develops we, um that enabled them to experiment and walking with different ways. And highlight in the skill set is that we, as a group required in order to transform using these approaches, we can no move things from ideation to scale and weeks and days sometimes rather than months. Andi, I think that if we can take what they've done on DH, use more open source technology, we contain that technology and apply across the whole group to tackle this Jill challenge. And I think that we use technologists and it's really cool. I think that we can no use technology and open source technology to solve some of these big challenges that we have and actually just preserve the planet in a better way. So So what's the next step for you guys at BP? So moving forward, we we are embracing ourselves, bracing a clothed, forced organization. We need to continue to live to deliver on our strategy, build >> over the technology across the entire group to address the jewel >> challenge and continue to make some of these bold changes and actually get into and really use. Our technology is, I said, too addresses you'LL challenge and make the future of our planet a better place for ourselves and our children and our children's children. That's that's a big goal. But thank you so much, Ed. Thanks for your support. And thanks for coming today. Thank you very much. Thank you. Now comes the part that, frankly, I think his best part of the best part of this presentation We're going to meet the type of person that makes all of these things a reality. This tip this type of person typically works for one of our customers or with one of with one of our customers as a partner to help them make the kinds of bold goals like you've heard about today and the ones you'll hear about Maura the way more in the >> week. I think the thing I like most about it is you feel that reward Just helping people I mean and helping people with stuff you enjoy right with computers. My dad was the math and science teacher at the local high school. And so in the early eighties, that kind of met here, the default person. So he's always bringing in a computer stuff, and I started a pretty young age. What Jason's been able to do here is Mohr evangelize a lot of the technologies between different teams. I think a lot of it comes from the training and his certifications that he's got. He's always concerned about their experience, how easy it is for them to get applications written, how easy it is for them to get them up and running at the end of the day. We're a loan company, you know. That's way we lean on accounting like red. That's where we get our support front. That's why we decided to go with a product like open shift. I really, really like to product. So I went down. The certification are out in the training ground to learn more about open shit itself. So my daughter's teacher, they were doing a day of coding, and so they asked me if I wanted to come and talk about what I do and then spend the day helping the kids do their coding class. The people that we have on our teams, like Jason, are what make us better than our competitors, right? Anybody could buy something off the shelf. It's people like him. They're able to take that and mold it into something that then it is a great offering for our partners and for >> customers. Please welcome Red Hat Certified Professional of the Year Jason Hyatt. >> Jason, Congratulations. Congratulations. What a what a big day, huh? What a really big day. You know, it's great. It's great to see such work, You know that you've done here. But you know what's really great and shows out in your video It's really especially rewarding. Tow us. And I'm sure to you as well to see how skills can open doors for for one for young women, like your daughters who already loves technology. So I'd liketo I'd like to present this to you right now. Take congratulations. Congratulations. Good. And we I know you're going to bring this passion. I know you bring this in, everything you do. So >> it's this Congratulations again. Thanks, Paul. It's been really exciting, and I was really excited to bring my family here to show the experience. It's it's >> really great. It's really great to see him all here as well going. Maybe we could you could You guys could stand up. So before we leave before we leave the stage, you know, I just wanted to ask, What's the most important skill that you'LL pass on from all your training to the future generations? >> So I think the most important thing is you have to be a continuous learner you can't really settle for. Ah, you can't be comfortable on learning, which I already know. You have to really drive a continuous Lerner. And of course, you got to use the I ninety. Maxwell. Quite. >> I don't even have to ask you the question. Of course. Right. Of course. That's awesome. That's awesome. And thank you. Thank you for everything, for everything that you're doing. So thanks again. Thank you. You know what makes open source work is passion and people that apply those considerable talents that passion like Jason here to making it worked and to contribute their idea there. There's back. And believe me, it's really an impressive group of people. You know you're family and especially Berkeley in the video. I hope you know that the redhead, the certified of the year is the best of the best. The cream of the crop and your dad is the best of the best of that. So you should be very, very happy for that. I also and I also can't wait. Teo, I also can't wait to come back here on this stage ten years from now and present that same award to you. Berkeley. So great. You should be proud. You know, everything you've heard about today is just a small representation of what's ahead of us. We've had us. We've had a set of goals and realize some bold goals over the last number of years that have gotten us to where we are today. Just to recap those bold goals First bait build a company based solely on open source software. It seems so logical now, but it had never been done before. Next building the operating system of the future that's going to run in power. The enterprise making the standard base platform in the op in the Enterprise Olympics based operating system. And after that making hybrid cloud the architecture of the future make hybrid the new data center, all leading to the largest software acquisition in history. Think about it around us around a company with one hundred percent open source DNA without. Throughout. Despite all the fun we encountered over those last seventeen years, I have to ask, Is there really any question that open source has won? Realizing our bold goals and changing the way software is developed in the commercial world was what we set out to do from the first day in the Red Hat was born. But we only got to that goal because of you. Many of you contributors, many of you knew toe open source software and willing to take the risk along side of us and many of partners on that journey, both inside and outside of Red Hat. Going forward with the reach of IBM, Red hat will accelerate. Even Mohr. This will bring open source general innovation to the next generation hybrid data center, continuing on our original mission and goal to bring open source technology toe every corner of the planet. What I what I just went through in the last hour Soul, while mind boggling to many of us in the room who have had a front row seat to this overto last seventeen plus years has only been red hats. First step. Think about it. We have brought open source development from a niche player to the dominant development model in software and beyond. Open Source is now the cornerstone of the multi billion dollar enterprise software world and even the next generation hybrid act. Architecture would not even be possible without Lennox at the core in the open innovation that it feeds to build around it. This is not just a step forward for software. It's a huge leap in the technology world beyond even what the original pioneers of open source ever could have imagined. We have. We have witnessed open source accomplished in the last seventeen years more than what most people will see in their career. Or maybe even a lifetime open source has forever changed the boundaries of what will be possible in technology in the future. And in the one last thing to say, it's everybody in this room and beyond. Everyone outside continue the mission. Thanks have a great sum. It's great to see it

>> Live from San Francisco, it's theCUBE, covering Google Cloud Next '19. Brought to you by Google Cloud and its ecosystem partners. >> Hi everyone, welcome back to the third day of live coverage of theCUBE here in San Francisco for Google Cloud Next 2019. I'm John Furrier, the host of theCUBE, my co-host Stu Miniman, Stu, good to see you this morning. >> Great to see you, John. >> Got a very special guest here, George Kurian, the CEO of NetApp, not to be confused with Thomas Kurian, his twin brother, who's the CEO of Google Cloud, George, it's great to see you. >> Good morning. >> Thanks for stopping by. >> Thank you for having me. >> So, when you've been walking through the hallways, you getting like, a lot of looks and some selfies, um, people want to take a selfie with you, thinking you're Thomas, the famous? >> Quite a few, quite a few. >> So what's it like? >> Oh, it's exciting to see all of the innovation here and the real commitment that Google's made to building out an enterprise platform. We've been working with them for many years, and, uh, we're excited at all of the potential new opportunities that creates, alongside Google's customers and ours. >> Yeah, George, it's got to be interesting, it's almost a little bit of a mirror image, is Google is looking to get deeper into the enterprise, and of course we've been documenting NetApp for many years now, has moved beyond just being an enterprise company, you've been moving to the cloud, maybe, just go back, tell us a little bit- some of the lessons you've learned, and, you know, what you're seeing happen, dynamics in the space. >> I think customers, Thomas said, you know, many of the core tenets that we see which is customers want to operate in a hybrid, multi-cloud world. They want to have cloud technology integrated into their data centers and conversely their applications be portable with a common programming model. I think it's come a long way. You know, I think our technologies now available natively in the Google Cloud, I think the programming model with microservices and containers, and with Kubernetes as an orchestration layer, truly allows, you know, this kind of hybrid world to operate, and I think our opportunity there is to help our customers use data properly across all of these landscapes, understand where it is, you know, orchestrate new applications as well as traditional, uh, so that they can progress the business. And so it's, you know I tell you coming to these conferences over the last three to five years, you can see the pace of change really start to accelerate. I'm interested in what you guys think about. >> Well, one of the things we've been commenting on theCUBE in our opening segments is kind of looking at how the transformation of Google Cloud from Google large-scale, they know data, they know tech, into becoming an enterprise, so, a lot of window dressing around the event, you know, digital transformation, all the right words, but they got the technology. And, you know, one of the things I'd love to get your perspective of because it's not- it's no secret that the Kurian brothers, yourself and your brother, Thomas, are, have great tech chops, also have tons of enterprise experiences, you specifically have been involved in a lot of ecosystems. That's been a big topic here. Can Google really get an ecosystem up and running, I mean, they participated in the CNCF with Cloud Native, but, as an organization, this is something that you're very familiar with, uh, at NetApp, you've been in many ecosystems, you've seen the formula. How, how, how should that evolve, because it's changing, the service's base, I think you're part of the Console Google Cloud from what I've been reporting here. What's the ecosystem formula for, for this new cloud world? >> You know, I'll tell you that, uh, enterprises expect their providers to work together, that's always been the expectation, and, uh, we've had to coexist with even our competitors for a long period of time. I think the core ideas there are to keep the customer at the center of the discussion and figure out how to best solve their problems, regardless of whether it is having to coexist with someone else, right? I think what's been interesting to me is, Linux has really become sort of the core underpinning of the cloud, and Linux was an open-source technology that, in the early years, IBM backed and sponsored. I think containers together with uh, you know, what Google's doing to sponsor it, has really become the opportunity to create the next, kind of layer of, you know, common development model, programming model, common orchestration. I think there's that promise, I think, uh, it's got to be realized. >> George, you, uh, you talked about, uh, the change that we see in the industry, and, you know, we know enterprise is not like, oh, let's just redo everything we were doing, whether I'm a five year old or a, you know, hundred and fifty year old company, I have things that I need to look at, and, I mean, the applications are really tough. It'd be wonderful if I just had a clean sheet of paper, and I can make it all serverless or containerize all my pieces there. Um, the message I heard a lot this week is, you know, meeting customers where they are. It's not just, Google we know has great tech, and smart people, maybe a little too smart sometimes, but, you know, I'd love to hear your viewpoint is, you know, those enterprise customers, are they catching up to the pace of innovation faster and making more change, or, you know, is it still one of these things that we're going to measure in decades as to how long it takes to move things. >> I think it, you know, I see it in a couple of, uh, ways. One is which industry are you in, and the impact of, you know, transformation to your industry. I think if you are in a highly digitally-oriented industry, like media and entertainment, you've got to transform quickly because the whole industry's getting transformed, right? I think conversely, if you're in an industry where digitization helps your workforce be more productive, I think you can take more time. What we see also is, in the places that, uh, are common, for example, in how you evolve your customer experience and how you interact with customers, we see virtually every company needing to transform, right? So I see that, you know, this is a long transformation, it's not going to happen overnight. I think that customers will pragmatically choose to, you know, either refactor existing applications or bill Net New, on a case-by-case, business-process by business-process basis. And that's why we see hybrid, sort of being the de facto operating model. >> George, I want to get your thoughts on multi-cloud and hybrid, obviously the modern application renaissance and revolutions kind of happening, whether you call it a renaissance or revolution, applications are exploding. That's clear. Multi-cloud and hybrid-cloud are key architectural shifts. I'm writing a story right now about the Department of Defense big contract that was awarded to, or to, shorthand, Microsoft and AWS. But, one of the things that have people arguing is that it should be multi-cloud! Now, the Department of Defense is an example, and this is public sector, but also enterprises have the same makeup, they have hundreds of cloud projects. Hundreds! And the Department of Defense is five hundred cloud projects. So there's not one cloud, that's not Amazon. So, this is a world where workloads and cloud selection and the parts of the architecture have to support multiple clouds. Can you explain that, kind of, what that means to customers? Because people get often confused coming from the old way. I'm buying IBM, I'm buying Oracle, I'm buying Google Cloud, and we're done. No, it's really not that case. Can you, kind of, can you react to that? >> Most enterprises that we speak to have hundreds of applications, everything from, you know, mainframe-based core business processing, to highly digital, you know, mobile-based, customer interaction applications. I think they have, sort of, a portfolio approach to manage those, where they say, hey, some of those are going to stay on premise, some of those are going to stay in a private cloud, and then I've got this palette of, you know, choices around whether I choose software as a service or infrastructure or platform as a service. And I think that when you look at a, you know, a reasonably large company like ours, we run about five hundred applications in the company. There's no single palette, right? You've got to have these inter-operate, I think from a governance standpoint from how you integrate the data across these landscapes, and from how you ensure compliance, security, and so on. And I, so I think, you know whenever a company tries to say that I can do everything, I think that's a little bit facetious, to be honest. >> And so, the reality is, multiple workloads, multiple cloud projects will happen, multiple vendors, but in a new way. Workload driven, with the data, obviously the data's critical, storage is key. Um, Stu, you want to- >> Yeah, so, you know, I think back to the storage world, storage was always a fragmented marketplace, and I had my application silos that I, that did this. Now, what have we learned from multi-cloud, that would, from multi-vendor, as we go into multi-cloud and, how can we allow customers to really unlock that value of data, because if it all stays fragmented in silos, it's a lot harder to be able to actually leverage it, use it, for all the, you know, AI, ML, or data, uh, value. >> Absolutely, I think, you know, one of the long-term theses we've had is that the world gradually moves from system-centric or process-centric to a data-centric world where the core asset that you're operating on is not the value of an individual business process, but the integration across your business processes, right? And so, this is why we think in a hybrid world, you need something like a data fabric to stitch together all of these landscapes. Those landscapes need to increasingly be stitched together in real time because of the speed of decision making or the use of, you know, real time analytics or real time business deci-, you know, processing. And so that's why we've integrated our technology into multiple landscapes, right, both traditional, but increasingly containerized or cloud-based, cloud-native applications. And I think that's again a multi-year journey. I think IT has to transform, IT architectures has to transform, and frankly businesses need to as well. They need to think about data as a property of the whole business, rather than a for function or a department. >> So just to click on that, double click on that for a second because, what you're saying is, a data fabric allows for multiple data to move around the workloads. So what you're saying is, if you want to take it- well, I'm saying- want to take advantage of machine learning and AI, the data has to be addressable in real time. Meaning, you don't have time to go fetch it from a database that may or may not be available at any given time, so making data addressable, horizontally scalable, for whatever workload, at any given time from retail to personalization, or whatever, right? >> Absolutely, right, so for example, if you look at the way a, um, AI or an ML data pipeline works, there's a period in the pipeline which is about training and feature engineering where you're trying to develop the model the right way. And then you're going to let the model run, but the model's going to be reacting to real time data input and constantly making transformations to how the business reacts. I think that data input needs to be fed in from all of the business processes that support the business, right, rather than a, hey I'm going to create an artifact that's, uh, static artifact that's trained once and then you're going to run the business. So that's why we think you've got to operate the hybrid world as an integrated world at the data layer. >> Yeah, George, one of the interest, there's a study, uh, that Google put out that they had acquired a group, DORA that looks at high performing environments, uh, and you know, what differentiates kind of, the, you know, the leaders of the pack. You talk to a lot of companies, and I'm sure you must, you know, have some, you know, opinions on this. Tell us, what, what is separating, you know, the leaders in the end user space, as to, uh, you know, from, from those that are, that are following. >> I think that, uh, the leaders, you know, are, have the capability to transform themselves, and transformation, you know, people talk about digital transformation. I think the most important part of that is actually the transformation part, and it's organizing people to allow experimentation, learning from experimentation, to celebrate failure, I think that's hard for big companies to do, right? Because you're set up to ensure that you're managing the risk of not failing, on the other hand, I think, in a world where there's a new game being created, you got to be able to allow the organization to try different things and it's okay to fail. >> And the speed pressure, too, to go faster, certainly with cloud, everything's accelerated from time to market, time to value, technology development. >> Absolutely. And I think that is also one of the fundamental changes going on in the industry. We were at the end of a paradigm where there were horizontal slices of expertise, which is really the ultimate optimization of an existing paradigm. The new paradigm isn't exactly clear, so, you know, to move faster, IT is creating vertically integrated squads. You look at, you know, Google's creation of a site reliability engineer, it's really a way to accelerate the creation of digital services and optimize the infrastructure associated with it, so. It's a time of change, I think, you know, our view is you got to lean into it, and, uh, you've got to trust the fact that the skills and the cultural values that you've brought are going to help you innovate into the future, not necessarily just the products and the ways that you've done them. And so that's why we think culture is a massively important part of these transformations. >> We're here with George Kurian, CEO of NetApp, not to be confused with Thomas Kurian, CEO of Google who's also walking around the floor, show floor, talking to customers. George, thanks for coming on and sharing your insight, you guys are awesome, the twins are super smart, running two big companies, thanks for spending time. Share us personal story, with George, I mean Thomas hasn't come on yet, he's too busy, we'll get him later on theCUBE, but share a story about him, what's he like, who wins the arm wrestling matches, share a- what's he like, tell a personal story. >> I think he's shy, uh I think we're both really, we realize how lucky we are, you know, we grew up in places where people, you know, some of us had sort of unmerited grace, you know, the blessings of being born to extraordinary, good families and parents, and so we're always cognizant of that. It's amazing that two guys in India, who had never seen a computer till we left India to come to the United States, now have the opportunity to be a big part of the computer industry, so we're just really grateful, and God's been good to us. >> Well congratulations, love the tech chops, value and culture, big deal right now, thanks for spending the time sharing the insights, appreciate it. >> Thank you for having me. >> George Kurian here on theCUBE with John Furrier, myself, and Stu Miniman, more CUBE coverage after this short break. (upbeat music)

(upbeat music) >> Narrator: Live, from San Francisco, it's theCUBE. Covering Google Cloud Next '19. Brought to you by Google Cloud and its ecosystem partners. >> Hey, welcome back everyone. Live coverage here with theCUBE in San Francisco, California, Moscone South. I'm John Furrier with Dave Vellante. Here at Google Next 2019 we have here in theCUBE for the first time as a Google employee, Cube alumni, Amit Zavery. Head of platform for Google Cloud. Great to see you. >> No, thanks for having me. It's always a pleasure to see you guys again. >> So you're just now on the job, not even two months. 25 years, 23? >> Amit: Close to 25, yes. >> Three years at Oracle. TK's over here as CEO, part of Google. They got a lot of action going on here. >> Oh definitely, it's very exciting times. I've spent some time kind of learning and hearing about what the vision at Google has been and it's very clear they're here to win it and we have the investment that they're making, the innovation which is going on is very attractive and very exciting, I think. >> Always love our conversations in the past in theCUBE around platform You got a deep technical background. Um you've been in the business. You've seen many waves of innovation up and down the stack. So it's not, I don't think there is a move you haven't seen in the business. But Cloud, there's some new things happening, it's going to, but it's all part of other things, kind of meshing together. Pun intended, service meshes. >> Yeah. >> But as customers move to the cloud from on prem, having cloud, multiple clouds, multiple dimensions of change. >> Yes. What's your take on this because, I think, you have a unique perspective in that 20 something years at Oracle, leader in databases and software? >> Yeah. >> Google's got great leadership in tech. >> Yep. >> But now they're standing up a whole new cloud business, at a whole 'nother level. Your thoughts? >> Yeah, yeah, I think if you look at what's going on and I talk to a lot of customers and developers and IT teams and clearly, I think, they are overwhelmed with different things, you said, going on in this space, so how do you make it simple? How do you make it open? How do you make it hybrid so you have flexibility of choices? It's becoming top of the mind for many of the users nowadays. The lock-in, which many vendors currently provide, becomes very difficult for many of this uh users who kind of keep moving around and meet the business requirements. So I think having a solution and a technology stack, which is really understanding the complexity around that and making it simple enough to adopt, I think is important. >> You know, one of these things, we watch these key notes very carefully. Especially when you have a new CEO, Thomas Kurian. We follow NetApp as well as his twin brother. But his first opening line was a little you know, tip of the cap to Diane Greene, which I thought was very classy. We hear all the other things. Scale, the multi-cloud piece. And then Jennifer Lynn gave a great demo, and she said something in her demo I want to get your reaction to. What are the business benefits of Anthos' negotiating contracts? Meaning choice. >> Yes. So lock-in's shifting. This means lock-in is not your grandfather's lock-in. You know, you worked at Oracle which has an amazing lock-in spec in databases. This is a whole new world, it's capabilities, the new lock-in. Or what is the new, I mean I guess lock-in is a function of-- >> Amit: No I mean, (mumbles) Again, it's not ideas. Lock-in is definitely not the right way of kind of looking at it. The way to kind of really make sure you attract users and attract customers, is to really make a value add capabilities in there. Right and then if the customers really love it they're going to keep on using it. In respective you call it lock-in or provide some propriotariness or not. >> Value. >> Right. Value is complete, exactly. I think it's important to really think about how you build some of the services and technologies which give this value. But also give you the choice of moving if you want to. That I think, if you start from the beginning that there's no choice, then the value doesn't come out, ever. >> John: So value's the new lock-in. >> It has to be, it has to be. >> Alright, talk about apogee. because you're one of the key piece of the platform is apogee. Talk about your focus, you're still learning, getting your feet wet. But again, you've got your running shoes on, you're experienced. What is that platform that you're handling. Give a quick description. >> Apogee, an acquisition, which Google made a few years ago. And I think it's a kind of center spaced offering which allows customers to really do the life cycle and digital transformation of the technology they have in the back end. Right and uh the apogee team has done a great job of keeping, being the market leader and keeping innovating. I think the next phase for us as we look forward is one is to make it very completely integrated and make it very seamless with all the rest of Google properties we have and the assets we have and second thing is to really add other capabilities around it so that customers depending on what they want to do like line of business or IT steams to be able to now unlock a lot of the application data they have and expose it to both the customer, spotners, as well as internal employees in a simple easy manner. So a lot of wantization can happen, monitoring, all these things can be really great for them. >> John: So there's a lot of head room in apogee. >> Very very much yes. >> By technology and business benefit. >> Dave: So head of platform. You know we in the industry we hear platform and we kind of understand what it's all about. People outside the industry maybe, some of an inmorphis concept to them. So my first question though before we get into this, what attracted you to Google? >> No I think that basically if I look at the strength Google brings as a organization, be it in terms of innovation, be it in terms of investment, the infrastructure and the willingness to invest in the long term. I think that is really really attractive. I think for me to kind of have the ability to kind of invest and grow a lot of the footprint we have to offer to a customer and solve the business problems in a little more longer term than short term oriented, I think is very very exciting. >> So let's talk more about platforms. You think of platforms as a set of capabilities steeped in sort of an architectural premise, there's maybe some dog mutt in there that you've got have have these capabilities then ultimately you're going to deliver value and turn into products and customer value. What is platform to you and what's that sort of how should we think about that fly wheel effect? >> Yeah in the way that I look at the platform is basically one is capabilities the customer require, one to build an application, integrate it, and be able to secure it and manage it right? So all the different capabilities you'd acquire instead of having to get piece meal of it and have to tie it all together yourself, you can now do it with a much easier fashion and one that provides you the capability as one integrated capability right? So that's really what I think of the platform. >> So your constituencies are obviously your internal developers, your external developers. Who are you serving with that platform? >> A few audiences. No doubt to others to be able to build an application. But I think the bigger audience if you go beyond that is really, apps IT and a line of business. So to them more and more line of business at doing extension to an application. The doing integration without having the right code. And if you can provide a powerful tool where any person who is not a professional developer can do that kind of tasks and get more power out of the application of the business systems they're running, the value is immense. And that's really I think the audience we need to be able to attract and be able to now cater to so that they have a lot more benefits from using the Google platform. >> Is that part technical capability, part you know, go to market? How do you view that? >> It's definitely a lot of work to be done from the product perspective to make it simple um make it more consumable by apps IT and line of business user where such professional developers but also in terms of how you design it and make it self service and attractive enough for an audience who is not really kind of having to do deal with a lot of this themselves. >> Okay so that's presumably what we should be expecting from you. Maybe talk about your priorities and give us a little you know, how should we be, sort of, judging you down the road, judging you not the right term but what milestones should we be looking for? >> A little too early, I mean this is four weeks at Google but I think uh, the way to look at this is are we basically catering to all the new requirements you see from a lot of the next generation users and I think uh, the ability for us to kind of expand that capability in a platform offering so it's not just catering to one kind of an audience but also new buyers which we seeing as users coming into the platform. So over the next six months or nine months we start seeing some of those things which you do. >> Is this a new role? Was it sort of by committee before or? >> No I think Google has been doing a lot of these things I think when you start to think about a rationalized skew of the areas and how do you keep on expanding. There's a lot of headroom for Google cloud to go and we continue to kind of look at where we need to be and how we can keep on expanding and meet those requirements. >> Amit talk about Thomas Kurian also known as TK onstage. He's been busy, he's going to come on the queue eventually. He's talking to a lot of customers we heard. Hundreds of customers been promoted. You worked in that oracle, what's he like? Share some color commentary on TK, he set the chops obviously in enterprise. What's he like? People, he's new CEO. >> Yeah, yeah I've worked with Thomas for 18 plus years and I think he's probably one of the smartest person I've worked with for sure. But I think it's very strategic vision and clear execution. I think combination is rare for a lot of people. We have a very clear vision but how do you execute and get operationally make those things possible? I think that really what Thomas brings to any any place he gets into. Right so he has a very clear idea where we should be going, he talks to a lot of customers, get you all the input and has a clear plan in terms of how we deli, what we should be doing. And then he gets very involved wit the execution operational work we should be doing right? So that is the unique thing to bring to the table. >> John: He can get down and dirty if you want him to do it. >> Yeah oh very much, yes yes. (laughs) He's fun to work with in that way. >> So I want to ask you a personal question I know we've been following your career, certainly you got a great, great technical background as well. As you look at the cloud, and having all that enterprise experience, you see many ways in innovation, hardware, software, evolution to the cloud. As you look at the modern enterprise, you mentioned IT apps, apps IT, it's a whole new app revolution renaissance happening. You got hybrid and multi cloud. What does it mean to be enterprise ready? If you could take all the learnings in your career, as you look at the new, you know, out in the new pasture, of the next ten years plus, you see changes happening, what's your vision? >> I think that enterprise ready for us, I mean I think that's what we are doing a lot, if you saw today from Thomas' announcements, there's a lot of things we are planning and we have been doing already and we need to do as well. But I think it's understanding the existing landscape of a customer. And enterprise, let's use them on and invest on many customers we've made and systems you can't rip and replace instantly. And to be able to understand how you operate in that kind of constrains as well as context is very important when you build new generational applications. So kind of having the connectivity and the tissue of kind of making it all work together, while you kind of modernize and digitally transform your offering, I think is a critical way of thinking. And I think that's what you'll start seeing a lot more of that from the product planning, product delivery perspective and understanding that yet many customers have to pay before they can move everywhere right? So you saw today with Thomas' announcement about hybrid which allows you to kind of inter operate with existing investments. Multicloud because you might be running into multiple environments. As well as you saw some the things we doing to really make it easy and simple to integrate with the existing portfolio that customers have. >> You know what's interesting is that you know, he also mentioned industries, which you guys at Oracle certainly you know every industry's got unique requirements. What's interesting and kind of validates on a queue we've, Dave and I have talked for years that the clouds horizontally scalable yet with data and AI you can be differentiated in the industry level so you can actually have best of both worlds now. That's what I see kind of coming together at the platform 'cause you have to have a platform that enables. How do you see that? Do you agree with that? Do you see that shaping out? How would you see that ability to take advantage of the horizontal scale, the ability, connective tissue, plus enabling this horizontal specialization for industry solutions? >> Yeah, no I think you saw again some of the announcements around that, with how do you make it not pertinent to a particular end user. Alright each industry has specific data models, specific use cases and you need to be able to provide and cater to that. So you have to have a horizontal platform which can cater to multiple, different things you want to do. But then you'd have to provide the main specific content and that's when you'll start seeing as you think that Oracle does some of the things that other companies do that and we will do some of that stuff as well. >> Well that's interesting point because you're in a point of a horizontal scaling because it creates this, uh, another disruption agenda. Yeah you can disrupts search and productivity software but you can also triverse industries with your partners. We were talking about apogee before with the API economy. You can see Google and its partners getting the healthcare, financial services, autonomist vehicles, I mean virtually every industry because it's data and that to me is the exciting part of platform. >> Oh no doubt. I think Google also brings a lot strength in terms of the modeling and the AI work they've been doing for many years and that can really exhilarate capabilities around these things in a much more easier way than it could be otherwise. >> And you kind of have a clean sheet of paper in the enterprise >> That's right. >> Amit great to see you, I'm glad we can get your first public appearance at Google here in theCUBE. Appreciate the commentary, I want to finally, final question is, personal question. If you were a cloud architect for a large enterprise that had complex to simple work loads and everything in between, what would you be doing in advising and setting up and architecting, what would you, what would you do? >> I think that the best thing to do I think is to identify different categories of applications. I don't think it's one thing fits all right? So define what are the categories of applications you have. Some of them are cloud ready and make sure that you can, status are ready and adoption and moving to more agile delivery model. Second on the application which you might want to now start thinking about rewriting and then having a road map associated with that so you're not trying to go and rip and replace because that has an impact on your business and capabilities right? And then third thing we might want to look at retiring some of the staff and then hey you have to modernize, I mean there's nothing, there's no way out of it. Just like software goes through cycles of innovation and changes every ten years you see a new stack of technologies come out and you have to remain competitive by adopting some of the states. So I think that's kind of in recognizing what you have and how you adopt is probably the number one thing. >> And you'll be probably driving containers throughout >> No doubt, I think the technologies out there now with the containerization, much much simpler to kind of go and run and write one's, run anywhere kind of thing. >> Those scenarios is kind of what the guy from Kohl's was saying today in the key note >> Yeah they're very similar yeah. >> He didn't say this, this one use case of just leave it there which was interesting to me. So, do nothing was not his strategy. It is, it is for some. >> Amit Zavery here on theCUBE. Great, great insight, thanks for sharing. Thanks for taking the time out of your busy schedule. Amit Zavery head of platform at Google Cloud here on theCUBE. I'm John Furrier. See us with more day one coverage. We're here for three days. Live, we'll be right back after this short break. (upbeat music)

>> [Narrator] Live from Los Angeles, it's The Cube, covering E3 2018. Brought to you by SiliconANGLE Media. >> Hey, welcome back, everybody. Jeff Frick here with The Cube. We're actually in the Warner Brothers games booth. This humongous booth, we're kind of in the inner sanctum here at E3 in the LA Convention Center. Lot of stuff going on with Warner Brother Games. A lot of really cool combinations of brands and games and movies. But this is a very special one, Hitman 2. We're all excited to be here and learn more about it with Jacob Mikkelsen. He's actually the game director for IO Interactive. Jacob, great to see you. >> Oh, thank you. >> So let's just get to the basics. First off, when is Hitman 2 coming out? What do people need to know, we'll get that out of the way, and then we'll get into it. >> Hitman 2 is out November 13. And if you pre-order now, you have a special pre-order bonus where you get access to a new game mode called Sniper Assassin, which is a sniper-only mission. And then for the first time in Hitman history, we also have a co-op mode where you can snipe alongside a friend, into the mission and create all sorts of havoc. It's still deeply founded in the roots of the game's DNA, where it's all about getting away with the sniping without anyone noticing that you're there. So it has a very, very strong puzzle element to it. So it's about peeling off the layers of an onion, without anyone noticing you're there. >> So you talked a little bit before we turned on the cameras about the freedom that a player gets, not like in a traditional game, where they can can choose a lot of different options of how they're gonna do the mission. So how do you guys come up with that? How is that all determined? And how do you actually still keep the game true to the mission? >> Well, the thing is that as you say, it's very much, we call that hyper-detailed sandbox. So when you play a Hitman mission, we don't give you a linear path through the level that you follow. We give you an open sandbox where you have to figure out how do you want to approach this mission. And in the case of the mission we're showing here at E3, it's a race event in Miami. And your target is one of the race drivers, actually. That's our half of the mission. And she's roaming around the track. So the whole thing in the demo today is like, "Okay, so how do you get close to Sierra's car?" And then in order to do that, then you need to obtain disguises, which is a key element in the Hitman franchise, that you can disguise as the characters you meet in the scene. So you can knock them out and become, take their uniforms on, and then infiltrate the areas. Some guards are more suspicious of you than others, so you have to mingle your way through the level. So it's very much up to you if you want to sneak in and try not to do the disguise stuff, or you can go for the disguise stuff and then make your way. And then the game adapts, in a way, because we have to foresee all these different permutations of play. So there's a lot of things you can do in the game, in terms of which way you take and how you get there. >> So I'm just curious from a game development point of view, in terms of building in difficulty, 'cause you want to have enough difficulties that it's a challenge and people feel satisfaction in rising to the challenge, but clearly you could make it so they just got wiped out every time. You could make it an impossible game. So how do you find that balance? How do you tune that balance? What are some of the things you think about when you're trying to get in degree of difficulty? >> Well, that's a really, how difficult should it be, that's a really hard question to answer in a Hitman game, because of the many ways that the players can do it. So we have an initial idea about where we want to challenge the players and where we want to give them a bit more leash where they can just roam around. But once you get a new disguise, then it's a different scenario. And we have to account for that in our design. So we do a lot of iterations on this. Okay, so if I went to the right and went this way in through the level but there was no resistance, I didn't have to do anything, I could just walk straight in the main door, then we have to go back to the drawing board and then jiggle around the characters, maybe add some new ones, remove some, and change the amount of guards, so the player will have challenges no matter how they approach it. But in the end, the crazy thing is, no matter how hard we make it or how challenging we make it, they will always find crazy ways of bypassing the systems and bending the rules of the game so much. And that's what makes Hitman great, is that you can do all of these things. Just, okay, can I do this? Yes, and you go and try it, and maybe it worked out, maybe it was not a good idea in the end. But it's very much up to you, as the player, to figure out how you want to be creative in this. >> So we're doing this series as part of the Western Digital data makes possible. And data is such a bit part of what you guys do. And really, as gaming has moved off of the pure console into the connected world, gives you an opportunity as a developer to see really, how are people interacting with the game? How are they making decisions? So how did you guys look at the analytics? You must be doing more and more and more analytics on all these various movements and potential options that they have. >> We have systems in place to figure out where people get spotted, so we can actually see that. The tricky part about metrics is that during development, there's actually not that many people playing the game besides ourselves. So we rely heavily on user testing, where we subdue people to the, we place people in front of the game in very early stages, to see if our core ideas are working. And then based on that, we then look at video footage, interviews, and all that stuff. That feeds back into the design loop of the process. >> And have you mapped every potential option, or are you using AI? You just used the example, some guy's too smart, we really need to have more guards for this guy. Is there AI and intelligence in the game that you can make little fine-tuned adjustments along the path as people actually play the game? 'Cause you're gonna have a whole lot more data by December first than you have today. >> Precisely, the amount of data we get is pretty wild in the end. But the core of the game, the characters are AI-driven. They have their own plans that they want to do. And the way it works is that we then build stories on top of this core AI. So the designers, they have freedom to create custom moments. But at some point when things go in the fence for the player, you get spotted or someone sees through your disguise, then the AI takes over. And I dare to say that we have some of the most complex AI systems in the industry. We go to great lengths to have them be very living and communicating a lot. So if one guy finds a body, then it's one situation. If he has a friend, then they begin to talk about what they've just experienced. And they work together to figure out what is actually going on. So there's a very high level of AI running behind the scenes in the Hitman game. >> Now, do you do that at the level of the characters? So it's really how a character responds to different stimuli-- >> Yes. >> Versus just a generic overlay for the whole game? >> Well, it's a mix. Some of them are different kinds of characters, guards or civilians, and they have different behaviors, based on what happens. But each character is more or less himself. And then he is not hive-mind controlled. It is a lot of agents that are running around in the world, trying to figure out what this player's up to, creating havoc behind the scenes. So it's a lot of fun to work with it, because it's also so unpredictable. And then all of a sudden, something happens that you didn't expect. >> Right, 'cause you can't possibly scenario every potential outcome, right? >> Exactly, we have some control, but it's systemically based. So we kind of, the way we normally say it is, we encourage the characters to do things. And then they might do it. For instance, you and I having an interview right now, that requires that you're standing in your spot and I'm standing in my spot. If I were to create that scene in the game, then there is a certain chance that one of us is lying in a dumpster somewhere and never shows up for the interview. And then the next question is, okay, so what do you do? So we have to construct the game in a way so that you won't break down and stop here. I don't know if you remember in season one of Westworld, if you've seen that? >> I have seen season one. I haven't caught up on season two yet, but yeah, season one. >> I haven't seen season two yet. But in season one, there's this scene where there's a bonfire scene that breaks down, where all the characters just stop. And then it turns out that the guy who went for firewood has been killed. So he never returned with the firewood, and thereby, the entire bonfire scene just grinds to a halt. >> [Jeff] Just freezes. >> That is Hitman gave development in a nutshell. Then we have a bug when that thing happens. And that can happen during development, we do that stuff. >> It's gotta be so cool, to discover how people actually work their way through the game. >> Absolutely. >> 'Cause the other thing I think it's interesting that you guys always have to balance is you have narrative, you want to have a narrative. You have a story, you have characters, and a look and feel. At the same time, you have individual operators, the players, that bring in their own point of view to the game. So how do you balance? When does one take priority to the other? How do you keep it on that narrative flow? >> It's been one of these returning challenges of making a Hitman game. And with the previous game, we narrowed in on, okay, so how do we do this? So we have a main story that is told outside the levels, which the levels don't directly affect. So the overall main arc and storyline is set. But what happens in the levels stays in the levels, so to speak. So in season one, we actually managed to go through the main story with some characters left alive, which is good. Because now in the second, in Hitman 2, we're going to get closer to them. And the story evolves around Agent 47, and we get a glimpse into his past, which is a bit of some things we haven't told yet. So that's going to be very exciting to see that, as well. >> Right, well Jacob, thanks for spending a few minutes. And good luck with the launch, congrats on the new product. >> Thank you very much, nice talking to you. >> He's Jacob, I'm Jeff, you're watching The Cube. We're in the Warner Brothers games booth at E3, LA Convention Center. Thanks for watching. (upbeat electronic music)

>> Narrator: Live from New York City, it's theCUBE covering IBM Data Science For All brought to you by IBM. >> Welcome back here on theCUBE. We are live in New York continuing our coverage here for Data Science for All where all things happen. Big things are happening. In fact, there's a huge event tonight I'm going to tell you about a little bit later on, but Tricia Wang who is our next guest is a part of that panel discussion that you'll want to tune in for live on ibmgo.com. 6 o'clock, but more on that a little bit later on. Along with Dave Vellante, John Walls here, and Tricia Wang now joins us. A first ever for us. How are you doing? >> Good. >> A global tech ethnographer. >> You said it correctly, yay! >> I learned a long time ago when you're not sure slow down. >> A plus already. >> Slow down and breathe. >> Slow down. >> You did a good job. Want to do it one more time? >> A global tech ethnographer. >> Tricia: Good job. >> Studying ethnography and putting ethnography into practice. How about that? >> Really great. >> That's taking on the challenge stretch. >> Now say it 10 times faster in a row. >> How about when we're done? Also co-founder of Sudden Compass. So first off, let's tell our viewers a little bit about Sudden Compass. Then I want to get into the ethnography and how that relates to tech. So let's go first off about Sudden Compass and the origins there. >> So Sudden Compass, we're a consulting firm based in New York City, and we help our partners embrace and understand the complexity of their customers. So whenever there are, wherever there's data and wherever there's people, we are there to help them make sure that they can understand their customers at the end of the day. And customers are really the most unpredictable, the most unknown, and the most difficult to quantify thing for any business. We see a lot of our partners really investing in big data data science tools and they're hiring the most amazing data scientists, but we saw them still struggling to make the right decisions, they still weren't getting their ROI, and they certainly weren't growing their customer base. And what we are helping them do is to say, "Look, you can't just rely only on data science. "You can't put it all into only the tool. "You have to think about how to operationalize that "and build a culture around it "and get the right skillsets in place, "and incorporate what we call the thick data, "which is the stuff that's very difficult to quantify, "the unknown, "and then you can figure out "how to best mathematically scale your data models "when it's actually based on real human behavior, "which is what the practice of ethnography is there to help "is to help you understand what do humans actually do, "what is unquantifiable. "And then once you find out those unquantifiable bits "you then have the art and science of figuring out "how do you scale it into a data model." >> Yeah, see that's what I find fascinating about this is that you've got hard and fast, right, data, objective, black and white, very clear, and then you've got people, you know? We all react differently. We have different influences, and different biases, and prejudices, and all that stuff, aptitudes. So you are meshing this art and science. >> Tricia: Absolutely. >> And what is that telling you then about how best to your clients and how to use data (mumbles)? >> Well, we tell our clients that because people are, there are biases, and people are not objective and there's emotions, that all ends up in the data set. To think that your data set, your quantitative data set, is free of biases and has some kind of been scrubbed of emotion is a total fallacy and it's something that needs to be corrected, because that means decision makers are making decisions based off of numbers thinking that they're objective when in fact they contain all the biases of the very complexity of the humans that they're serving. So, there is an art and science of making sure that when you capture that complexity ... We're saying, "Don't scrub it away." Traditional marketing wants to say, "Put your customers in boxes. "Put them in segments. "Use demographic variables like education, income. "Then you can just put everyone in a box, "figure out where you want to target, "figure out the right channels, "and you buy against that and you reach them." That's not how it works anymore. Customers now are moving faster than corporations. The new net worth customer of today has multiple identities is better understood when in relationship to other people. And we're not saying get rid of the data science. We're saying absolutely have it. You need to have scale. What is thick data going to offer you? Not scale, but it will offer you depth. So, that's why you need to combine both to be able to make effective decisions. >> So, I presume you work with a lot of big consumer brands. Is that a safe assumption? >> Absolutely. >> Okay. So, we work with a lot of big tech brands, like IBM and others, and they tend to move at the speed of the CIO, which tends to be really slow and really risk averse, and they're afraid to over rotate and get ahead over their skis. What do you tell folks like that? Is that a mistake being so cautious in this digital age? >> Well, I think the new CIO is on the cutting edge. I was just at Constellation Research Annual Conference in Half Moon Bay at-- >> Our friend Ray Wang. >> Yeah, Ray Wang. And I just spoke about this at their Constellation Connected Enterprise where they had the most, I would have to say the most amazing forward thinking collection of CIOs, CTOs, CDOs all in one room. And the conversation there was like, "We cannot afford to be slow anymore. "We have to be on the edge "of helping our companies push the ground." So, investing in tools is not enough. It is no longer enough to be the buyer, and to just have a relationship with your vendor and assume that they will help you deliver all the understanding. So, CIOs and CTOs need to ensure that their teams are diverse, multi-functional, and that they're totally integrated embedded into the business. And I don't mean just involve a business analyst as if that's cutting edge. I'm saying, "No, you need to make sure that every team "has qualitative people, "and that they're embedded and working closely together." The problem is we don't teach these skills. We're not graduating data scientists or ethnographers who even want to talk to each other. In fact, each side thinks the other side is useless. We're saying, "No, "we need to be able to have these skills "being taught within companies." And you don't need to hire a PhD data scientist or a PhD ethnographer. What we're saying is that these skills can be taught. We need to teach people to be data literate. You've hired the right experts, you have bought the right tools, but we now need to make sure that we're creating data literacy among decision makers so that we can turn these data into insights and then into action. >> Let's peel that a little bit. Data literate, you're talking about creativity, visualization, combining different perspectives? Where should the educational focus be? >> The educational focus should be on one storytelling. Right now, you cannot just be assuming that you can have a decision maker make a decision based on a number or some long PowerPoint report. We have to teach people how to tell compelling stories with data. And when I say data I'm talking about it needs the human component and it needs the numbers. And so one of the things that I saw, this is really close to my heart, was when I was at Nokia, and I remember I spent a decade understanding China. I really understood China. And when I finally had the insight where I was like, "Look, after spending 10 years there, "following 100 to 200 families around, "I had the insight back in 2009 that look, "your company is about to go out of business because "people don't want to buy your feature phones anymore. "They're going to want to buy smartphones." But, I only had qualitative data, and I needed to work alongside the business analysts and the data scientists. I needed access to their data sets, but I needed us to play together and to be on a team together so that I could scale my insights into quantitative models. And the problem was that, your question is, "What does that look like?" That looks like sitting on a team, having a mandate to say, "You have to play together, "and be able to tell an effective story "to the management and to leadership." But back then they were saying, "No, "we don't even consider your data set "to be worthwhile to even look at." >> We love our candy bar phone, right? It's a killer. >> Tricia: And we love our numbers. We love our surveys that tell us-- >> Market share was great. >> Market share is great. We've done all of the analysis. >> Forget the razor. >> Exactly. I'm like, "Look, of course your market share was great, "because your surveys were optimized "for your existing business model." So, big data is great if you want to optimize your supply chain or in systems that are very contained and quantifiable that's more or less fine. You can get optimization. You can get that one to two to five percent. But if you really want to grow your company and you want to ensure its longevity, you cannot just rely on your quantitative data to tell you how to do that. You actually need thick data for discovery, because you need to find the unknown. >> One of the things you talk about your passion is to understand how human perspectives shape the technology we build and how we use it. >> Tricia: Yes, you're speaking my language. >> Okay, so when you think about the development of the iPhone, it wasn't a bunch of surveys that led Steve Jobs to develop the iPhone. I guess the question is does technology lead and shape human perspectives or do human perspectives shape technology? >> Well, it's a dialectical relationship. It's like does a hamburger ... Does a bun shape the burger or does the bun shape the burger? You would never think of asking someone who loves a hamburger that question, because they both shape each other. >> Okay. (laughing) >> So, it's symbiote here, totally symbiotic. >> Surprise answer. You weren't expecting that. >> No, but it is kind of ... Okay, so you're saying it's not a chicken and egg, it's both. >> Absolutely. And the best companies are attuned to both. The best companies know that. The most powerful companies of the 21st century are obsessed with their customers and they're going to do a great job at leveraging human models to be scaled into data models, and that gap is going to be very, very narrow. You get big data. We're going to see more AI or ML disasters when their data models are really far from their actual human models. That's how we get disasters like Tesco or Target, or even when Google misidentified black people as gorillas. It's because their model of their data was so far from the understanding of humans. And the best companies of the future are going to know how to close that gap, and that means they will have the thick data and big data closely integrated. >> Who's doing that today? It seems like there are no ethics in AI. People are aggressively AI for profit and not really thinking about the human impacts and the societal impacts. >> Let's look at IBM. They're doing it. I would say that some of the most innovative projects that are happening at IBM with Watson, where people are using AI to solve meaningful social problems. I don't think that has to be-- >> Like IBM For Social Good. >> Exactly, but it's also, it's not just experimental. I think IBM is doing really great stuff using Watson to understand, identify skin cancer, or looking at the ways that people are using AI to understand eye diseases, things that you can do at scale. But also businesses are also figuring out how to use AI for actually doing better things. I think some of the most interesting ... We're going to see more examples of people using AI for solving meaningful social problems and making a profit at the same time. I think one really great example is WorkIt is they're using AI. They're actually working with Watson. Watson is who they hired to create their engine where union workers can ask questions of Watson that they may not want to ask or may be too costly to ask. So you can be like, "If I want to take one day off, "will this affect my contract or my job?" That's a very meaningful social problem that unions are now working with, and I think that's a really great example of how Watson is really pushing the edge to solve meaningful social problems at the same time. >> I worry sometimes that that's like the little device that you put in your car for the insurance company to see how you drive. >> How do you brake? How do you drive? >> Do people trust feeding that data to Watson because they're afraid Big Brother is watching? >> That's why we always have to have human intelligence working with machine intelligence. This idea of AI versus humans is a false binary, and I don't even know why we're engaging in those kinds of questions. We're not clearly, but there are people who are talking about it as if it's one or the other, and I find it to be a total waste of time. It's like clearly the best AI systems will be integrated with human intelligence, and we need the human training the data with machine learning systems. >> Alright, I'll play the yeah but. >> You're going to play the what? >> Yeah but! >> Yeah but! (crosstalk) >> That machines are replacing humans in cognitive functions. You walk into an airport and there are kiosks. People are losing jobs. >> Right, no that's real. >> So okay, so that's real. >> That is real. >> You agree with that. >> Job loss is real and job replacement is real. >> And I presume you agree that education is at least a part the answer, and training people differently than-- >> Tricia: Absolutely. >> Just straight reading, writing, and arithmetic, but thoughts on that. >> Well what I mean is that, yes, AI is replacing jobs, but the fact that we're treating AI as some kind of rogue machine that is operating on its own without human guidance, that's not happening, and that's not happening right now, and that's not happening in application. And what is more meaningful to talk about is how do we make sure that humans are more involved with the machines, that we always have a human in the loop, and that they're always making sure that they're training in a way where it's bringing up these ethical questions that are very important that you just raised. >> Right, well, and of course a lot of AI people would say is about prediction and then automation. So think about some of the brands that you serve, consult with, don't they want the machines to make certain decisions for them so that they can affect an outcome? >> I think that people want machines to surface things that is very difficult for humans to do. So if a machine can efficiently surface here is a pattern that's going on then that is very helpful. I think we have companies that are saying, "We can automate your decisions," but when you actually look at what they can automate it's in very contained, quantifiable systems. It's around systems around their supply chain or logistics. But, you really do not want your machine automating any decision when it really affects people, in particular your customers. >> Okay, so maybe changing the air pressure somewhere on a widget that's fine, but not-- >> Right, but you still need someone checking that, because will that air pressure create some unintended consequences later on? There's always some kind of human oversight. >> So I was looking at your website, and I always look for, I'm intrigued by interesting, curious thoughts. >> Tricia: Okay, I have a crazy website. >> No, it's very good, but back in your favorite quotes, "Rather have a question I can't answer "than an answer I can't question." So, how do you bring that kind of there's no fear of failure to the boardroom, to people who have to make big leaps and big decisions and enter this digital transformative world? >> I think that a lot of companies are so fearful of what's going to happen next, and that fear can oftentimes corner them into asking small questions and acting small where they're just asking how do we optimize something? That's really essentially what they're asking. "How do we optimize X? "How do we optimize this business?" What they're not really asking are the hard questions, the right questions, the discovery level questions that are very difficult to answer that no big data set can answer. And those are questions ... The questions about the unknown are the most difficult, but that's where you're going to get growth, because when something is unknown that means you have not either quantified it yet or you haven't found the relationship yet in your data set, and that's your competitive advantage. And that's where the boardroom really needs to set the mandate to say, "Look, I don't want you guys only answering "downstream, company-centric questions like, "'How do we optimize XYZ?"'" which is still important to answer. We're saying you absolutely need to pay attention to that, but you also need to ask upstream very customer-centric questions. And that's very difficult, because all day you're operating inside a company . You have to then step outside of your shoes and leave the building and see the world from a customer's perspective or from even a non existing customer's perspective, which is even more difficult. >> The whole know your customer meme has taken off in a big way right now, but I do feel like the pendulum is swinging. Well, I'm sanguined toward AI. It seems to me that ... It used to be that brands had all the power. They had all the knowledge, they knew the pricing, and the consumers knew nothing. The Internet changed all that. I feel like digital transformation and all this AI is an attempt to create that asymmetry again back in favor of the brand. I see people getting very aggressive toward, certainly you see this with Amazon, Amazon I think knows more about me than I know about myself. Should we be concerned about that and who protects the consumer, or is just maybe the benefits outweigh the risks there? >> I think that's such an important question you're asking and it's totally important. A really great TED talk just went up by Zeynep Tufekci where she talks about the most brilliant data scientists, the most brilliant minds of our day, are working on ad tech platforms that are now being created to essentially do what Kenyatta Jeez calls advertising terrorism, which is that all of this data is being collected so that advertisers have this information about us that could be used to create the future forms of surveillance. And that's why we need organizations to ask the kind of questions that you did. So two organizations that I think are doing a really great job to look at are Data & Society. Founder is Danah Boyd. Based in New York City. This is where I'm an affiliate. And they have all these programs that really look at digital privacy, identity, ramifications of all these things we're looking at with AI systems. Really great set of researchers. And then Vint Cerf (mumbles) co-founded People-Centered Internet. And I think this is another organization that we really should be looking at, it's based on the West Coast, where they're also asking similar questions of like instead of just looking at the Internet as a one-to-one model, what is the Internet doing for communities, and how do we make sure we leverage the role of communities to protect what the original founders of the Internet created? >> Right, Danah Boyd, CUBE alum. Shout out to Jeff Hammerbacher, founder of Cloudera, the originator of the greatest minds of my generation are trying to get people to click on ads. Quit Cloudera and now is working at Mount Sinai as an MD, amazing, trying to solve cancer. >> John: A lot of CUBE alums out there. >> Yeah. >> And now we have another one. >> Woo-hoo! >> Tricia, thank you for being with us. >> You're welcome. >> Fascinating stuff. >> Thanks for being on. >> It really is. >> Great questions. >> Nice to really just change the lens a little bit, look through it a different way. Tricia, by the way, part of a panel tonight with Michael Li and Nir Kaldero who we had earlier on theCUBE, 6 o'clock to 7:15 live on ibmgo.com. Nate Silver also joining the conversation, so be sure to tune in for that live tonight 6 o'clock. Back with more of theCUBE though right after this. (techno music)