>>mhm. Welcome back to Boston. This is the cubes coverage of the Red Hat Summit 2022. The first Red Hat Summit we've done face to face in at least two years. 2019 was our last one. We're kind of rounding the far turn, you know, coming up for the home stretch. My name is Dave Valentin here with Paul Gillon. A J monger is here is a senior director of Iot. The Iot group for developer solutions and engineering at Intel. AJ, thanks for coming on the Cube. Thank you so much. We heard your colleague this morning and the keynote talking about the Dev Cloud. I feel like I need a Dev Cloud. What's it all about? >>So, um, we've been, uh, working with developers and the ecosystem for a long time, trying to build edge solutions. A lot of time people think about it. Solutions as, like, just computer the edge. But what really it is is you've got to have some component of the cloud. There is a network, and there is edge and edge is complicated because of the variety of devices that you need. And when you're building a solution, you got to figure out, like, where am I going to push the computer? How much of the computer I'm going to run in the cloud? How much of the computer? I'm gonna push it at the network and how much I need to run it at the edge. A lot of times what happens for developers is they don't have one environment where all of the three come together. And so what we said is, um, today the way it works is you have all these edge devices that customers by the instal, they set it up and they try to do all of that. And then they have a cloud environment they do to their development. And then they figure out how all of this comes together. And all of these things are only when they are integrating it at the customer at the solution space is when they try to do it. So what we did is we took all of these edge devices, put it in the cloud and gave one environment for cloud to the edge. Very good to your complete solution. >>Essentially simulates. >>No, it's not >>simulating span. So the cloud spans the cloud, the centralised cloud out to the edge. You >>know, what we did is we took all of these edge devices that will theoretically get deployed at the edge like we took all these variety of devices and putting it put it in a cloud environment. So these are non rack mountable devices that you can buy in the market today that you just have, like, we have about 500 devices in the cloud that you have from atom to call allusions to F. P. G s to head studio cards to graphics. All of these devices are available to you. So in one environment you have, like, you can connect to any of the cloud the hyper scholars, you could connect to any of these network devices. You can define your network topology. You could bring in any of your sources that is sitting in the gate repository or docker containers that may be sitting somewhere in a cloud environment, or it could be sitting on a docker hub. You can pull all of these things together, and we give you one place where you can build it where you can test it. You can performance benchmark it so you can know when you're actually going to the field to deploy it. What type of sizing you need. So >>let me show you, understand? If I want to test, uh, an actual edge device using 100 gig Ethernet versus an Mpls versus the five G, you can do all that without virtualizing. >>So all the H devices are there today, and the network part of it, we are building with red hat together where we are putting everything on this environment. So the network part of it is not quite yet solved, but that's what we want to solve. But the goal is here is you can let's say you have five cameras or you have 50 cameras with different type of resolutions. You want to do some ai inference type of workloads at the edge. What type of compute you need, what type of memory you need, How many devices do you need and where do you want to push the data? Because security is very important at the edge. So you gotta really figure out like I've got to secure the data on flight. I want to secure the data at Brest, and how do you do the governance of it. How do you kind of do service governance? So that all the services different containers that are running on the edge device, They're behaving well. You don't have one container hogging up all the memory or hogging up all the compute, or you don't have, like, certain points in the day. You might have priority for certain containers. So all of these mortals, where do you run it? So we have an environment that you could run all of that. >>Okay, so take that example of AI influencing at the edge. So I've got an edge device and I've developed an application, and I'm going to say Okay, I want you to do the AI influencing in real time. You got something? They become some kind of streaming data coming in, and I want you to persist, uh, every hour on the hour. I want to save that time stamp. Or if the if some event, if a deer runs across the headlights, I want you to persist that day to send that back to the cloud and you can develop that tested, benchmark >>it right, and then you can say that. Okay, look in this environment I have, like, five cameras, like at different angles, and you want to kind of try it out. And what we have is a product which is into, um, open vino, which is like an open source product, which does all of the optimizations you need for age in France. So you develop the like to recognise the deer in your example. I developed the training model somewhere in the cloud. Okay, so I have, like, I developed with all of the things have annotated the different video streams. And I know that I'm recognising a deer now. Okay, so now you need to figure out Like when the deer is coming and you want to immediately take an action. You don't want to send all of your video streams to the cloud. It's too expensive. Bandwidth costs a lot. So you want to compute that inference at the edge? Okay. In order to do that inference at the edge, you need some environment. You should be able to do it. And to build that solution What type of age device do you really need? What type of compute you need? How many cameras are you computing it? What different things you're not only recognising a deer, probably recognising some other objects could do all of that. In fact, one of the things happened was I took my nephew to San Diego Zoo and he was very disappointed that he couldn't see the chimpanzees. Uh, that was there, right, the gorillas and other things. So he was very sad. So I said, All right, there should be a better way. I saw, like there was a stream of the camera feed that was there. So what we did is we did an edge in friends and we did some logic to say, At this time of the day, the gorillas get fed, so there's likelihood of you actually seeing the gorilla is very high. So you just go at that point and so that you see >>it, you >>capture, That's what you do, and you want to develop that entire solution. It's based on whether, based on other factors, you need to bring all of these services together and build a solution, and we offer an environment that allows you to do it. Will >>you customise the the edge configuration for the for the developer If if they want 50 cameras. That's not You don't have 50 cameras available, right? >>It's all cameras. What we do is we have a streaming capability that we support so you can upload all your videos. And you can say I want to now simulate 50 streams. Want to simulate 30 streams? Or I want to do this right? Or just like two or three videos that you want to just pull in. And you want to be able to do the infant simultaneously, running different algorithms at the edge. All of that is supported, and the bigger challenge at the edge is developing. Solution is fine. And now when you go to actual deployment and post deployment monitoring, maintenance, make sure that you're like managing it. It's very complicated. What we have seen is over 50% 51% to be precise of developers are developed some kind of a cloud native applications recently, right? So that we believe that if you bring that type of a cloud native development model to the edge, then you're scaling problem. Your maintenance problem, you're like, how do you actually deploy it? All of these challenges can be better managed, Um, and if you run all of that is an orchestration later on kubernetes and we run everything on top of open shift, so you have a deployment ready solution already there it's everything is containerised everything. You have it as health charged Dr Composed. You have all their you have tested and in this environment, and now you go take that to the deployment. And if it is there on any standard kubernetes environment or in an open ship, you can just straight away deploy your application. >>What's that edge architecture looked like? What's Intel's and red hats philosophy around? You know what's programmable and it's different. I know you can run a S, a p a data centre. You guys got that covered? What's the edge look like? What's that architecture of silicon middleware? Describe that for us. >>So at the edge, you think about it, right? It can run traditional, Uh, in an industrial PC. You have a lot of Windows environment. You have a lot of the next. They're now in a in an edge environment. Quite a few of these devices. I'm not talking about Farage where there are tiny micro controllers and these devices I'm talking about those devices that connect to these forage devices. Collect the data. Do some analytics do some compute that type of thing. You have foraged devices. Could be a camera. Could be a temperature sensor. Could be like a weighing scale. Could be anything. It could be that forage and then all of that data instead of pushing all the data to the cloud. In order for you to do the analysis, you're going to have some type of an edge set of devices where it is collecting all this data, doing some decisions that's close to the data. You're making some analysis there, all of that stuff, right? So you need some analysis tools, you need certain other things. And let's say that you want to run like, UH, average costs or rail or any of these operating systems at the edge. Then you have an ability for you to manage all of that. Using a control note, the control node can also sit at the edge. In some cases, like in a smart factory, you have a little data centre in a smart factory or even in a retail >>store >>behind a closet. You have, like a bunch of devices that are sitting there, correct. And those devices all can be managed and clustered in an environment. So now the question is, how do you deploy applications to that edge? How do you collect all the data that is sitting through the camera? Other sensors and you're processing it close to where the data is being generated make immediate decisions. So the architecture would look like you have some club which does some management of this age devices management of this application, some type of control. You have some network because you need to connect to that. Then you have the whole plethora of edge, starting from an hybrid environment where you have an entire, like a mini data centre sitting at the edge. Or it could be one or two of these devices that are just collecting data from these sensors and processing it that is the heart of the other challenge. The architecture varies from different verticals, like from smart cities to retail to healthcare to industrial. They have all these different variations. They need to worry about these, uh, different environments they are going to operate under, uh, they have different regulations that they have to look into different security protocols that they need to follow. So your solution? Maybe it is just recognising people and identifying if they are wearing a helmet or a coal mine, right, whether they are wearing a safety gear equipment or not, that solution versus you are like driving in a traffic in a bike, and you, for safety reasons. We want to identify the person is wearing a helmet or not. Very different use cases, very different environments, different ways in which you are operating. But that is where the developer needs to have. Similar algorithms are used, by the way, but how you deploy it very, quite a bit. >>But the Dev Cloud make sure I understand it. You talked about like a retail store, a great example. But that's a general purpose infrastructure that's now customised through software for that retail environment. Same thing with Telco. Same thing with the smart factory, you said, not the far edge, right, but that's coming in the future. Or is that well, that >>extends far edge, putting everything in one cloud environment. We did it right. In fact, I put some cameras on some like ipads and laptops, and we could stream different videos did all of that in a data centre is a boring environment, right? What are you going to see? A bunch of racks and service, So putting far edge devices there didn't make sense. So what we did is you could just have an easy ability for you to stream or connect or a Plourde This far edge data that gets generated at the far edge. Like, say, time series data like you can take some of the time series data. Some of the sensor data are mostly camera data videos. So you upload those videos and that is as good as your streaming those videos. Right? And that means you are generating that data. And then you're developing your solution with the assumption that the camera is observing whatever is going on. And then you do your age inference and you optimise it. You make sure that you size it, and then you have a complete solution. >>Are you supporting all manner of microprocessors at the edge, including non intel? >>Um, today it is all intel, but the plan, because we are really promoting the whole open ecosystem and things like that in the future. Yes, that is really talking about it, so we want to be able to do that in the future. But today it's been like a lot of the we were trying to address the customers that we are serving today. We needed an environment where they could do all of this, for example, and what circumstances would use I five versus i nine versus putting an algorithm on using a graphics integrated graphics versus running it on a CPU or running it on a neural computer stick. It's hard, right? You need to buy all those devices you need to experiment your solutions on all of that. It's hard. So having everything available in one environment, you could compare and contrast to see what type of a vocal or makes best sense. But it's not >>just x 86 x 86 your portfolio >>portfolio of F. P. G s of graphics of like we have all what intel supports today and in future, we would want to open it up. So how >>do developers get access to this cloud? >>It is all free. You just have to go sign up and register and, uh, you get access to it. It is difficult dot intel dot com You go there, and the container playground is all available for free for developers to get access to it. And you can bring in container workloads there, or even bare metal workloads. Um, and, uh, yes, all of it is available for you >>need to reserve the endpoint devices. >>Comment. That is where it is. An interesting technology. >>Govern this. Correct. >>So what we did was we built a kind of a queuing system. Okay, So, schedule, er so you develop your application in a controlled north, and only you need the edge device when you're scheduling that workload. Okay, so we have this scheduling systems, like we use Kafka and other technologies to do the scheduling in the container workload environment, which are all the optimised operators that are available in an open shift, um, environment. So we regard those operators. Were we installed it. So what happens is you take your work, lord, and you run it. Let's say on an I seven device, when you're running that workload and I summon device, that device is dedicated to you. Okay, So and we've instrumented each of these devices with telemetry so we could see at the point your workload is running on that particular device. What is the memory looking like power looking like How hard is the device running? What is a compute looking like? So we capture all that metrics. Then what you do is you take it and run it on a 99 or run it on a graphic, so can't run it on an F p g a. Then you compare and contrast. And you say Huh? Okay for this particular work, Lord, this device makes best sense. In some cases, I'll tell you. Right, Uh, developers have come back and told me I don't need a bigger process that I need bigger memory. >>Yeah, sure, >>right. And some cases they've said, Look, I have I want to prioritise accuracy over performance because if you're in a healthcare setting, accuracy is more important. In some cases, they have optimised it for the size of the device because it needs to fit in the right environment in the right place. So every use case where you optimise is up to the solution up to the developer, and we give you an ability for you to do that kind >>of folks are you seeing? You got hardware developers, you get software developers are right, people coming in. And >>we have a lot of system integrators. We have enterprises that are coming in. We are seeing a lot of, uh, software solution developers, independent software developers. We also have a lot of students are coming in free environment for them to kind of play with in sort of them having to buy all of these devices. We're seeing those people. Um I mean, we are pulling through a lot of developers in this environment currently, and, uh, we're getting, of course, feedback from the developers. We are just getting started here. We are continuing to improve our capabilities. We are adding, like, virtualisation capabilities. We are working very closely with red hat to kind of showcase all the goodness that's coming out of red hat, open shift and other innovations. Right? We heard, uh, like, you know, in one of the open shift sessions, they're talking about micro shifts. They're talking about hyper shift, the talking about a lot of these innovations, operators, everything that is coming together. But where do developers play with all of this? If you spend half your time trying to configure it, instal it and buy the hardware, Trying to figure it out. You lose patience. What we have time, you lose time. What is time and it's complicated, right? How do you set up? Especially when you involve cloud. It has network. It has got the edge. You need all of that right? Set up. So what we have done is we've set up everything for you. You just come in. And by the way, not only just that what we realised is when you go talk to customers, they don't want to listen to all our optimizations processors and all that. They want to say that I am here to solve my retail problem. I want to count the people coming into my store, right. I want to see that if there is any spills that I recognise and I want to go clean it up before a customer complaints about it or I have a brain tumour segmentation where I want to identify if the tumour is malignant or not, right and I want to telehealth solutions. So they're really talking about these use cases that are talking about all these things. So What we did is we build many of these use cases by talking to customers. We open sourced it and made it available on Death Cloud for developers to use as a starting point so that they have this retail starting point or they have this healthcare starting point. All these use cases so that they have all the court we have showed them how to contain arise it. The biggest problem is developers still don't know at the edge how to bring a legacy application and make it cloud native. So they just wrap it all into one doctor and they say, OK, now I'm containerised got a lot more to do. So we tell them how to do it, right? So we train these developers, we give them an opportunity to experiment with all these use cases so that they get closer and closer to what the customer solutions need to be. >>Yeah, we saw that a lot with the early cloud where they wrapped their legacy apps in a container, shove it into the cloud. Say it's really hosting a legacy. Apps is all it was. It wasn't It didn't take advantage of the cloud. Never Now people come around. It sounds like a great developer. Free resource. Take advantage of that. Where do they go? They go. >>So it's def cloud dot intel dot com >>death cloud dot intel dot com. Check it out. It's a great freebie, AJ. Thanks very much. >>Thank you very much. I really appreciate your time. All right, >>keep it right there. This is Dave Volonte for Paul Dillon. We're right back. Covering the cube at Red Hat Summit 2022. >>Mhm. Yeah. Mhm. Mm.

>>Yeah. Hello and welcome to the Cuba's International Women's Showcase, featuring International Women's Day. I'm John, host of the Kiwi here in California. Great remote guest. She's amazing founder and C e O of Cuba, and great to see you. Okay, thanks for coming on. Um, good to see you. >>You as well. Always a pleasure. You >>know, International Women's Day is the big celebration. We're doing a lot of interviews with great people making things happen, moving and shaking things. Um, but every day, International Women's Day, As far as I'm concerned, it's happening all around the world. But these are stories of innovation, the stories of changes, the stories of transformation for the better. You've been doing a lot of things. Um and I want to get into that. But let's start with your background. Tell us a bit about who you are and what you've got going on. >>Yeah, my background is a little strange. I used to be a maritime archaeologists. So dumb shit breaks for a little bit. That was amazing. I always just It's only partial just because it's actually a bit of truth to it, that learning how to, you know, handle things at depth really does train you to be a C e o. Because you learn to control your breath and and focus on the things that matter and not be so reactive because it's three activity that will panic that will kill you. Uh, always knowing how to reframe. Return to the basics. Um, there's a really good things to hold on to, even in the world of business. Right? So I at some point, ended up doing doing a lot of things. Largely business development, following my time diving and amazing woman. Um, another woman for International Women's Day named Doctor who was a biotech entrepreneur from Japan, stepping down as her role at the helm of her company. Um, and she wanted to launch a space for a young innovators from around the world who are doing amazing work to tackle this very complex challenges we all know exist, um, and figure out a way to give them time and space to do their best work and pursue their their highest visions for change. We decided that we would focus on for-profit companies largely who were using sustainable, scalable business models to pursue both profit and purpose. Um creating a virtuous cycle between the return of money to a company and putting that into to go even further and faster towards, um, solving a problem. Um, so we now have companies over 200 companies from around the world that we have helped support tackling every single, sustainable development goal. Um, and I'm proud to say, you know, particularly related to the subject that fifty-nine percent of our companies have a woman founder or CO-FOUNDER. Um, and 69% of the founder of color. Um, so we're working with entrepreneurs from every every area of the world. Many approximate to the problem that they are trying to solve, so they intimately understand it. Um, and they're doing amazing things. >>Yeah, you can help the great mission. You have a lot of other things going on your helping women encouraging them to your career in the tech sector. Um, good statistics could be better, right? Is higher and better. So, um, what are you guys doing? What, you specifically to help and encourage women to forge their career and tech? >>Yeah. I mean, look, the good news is I do think that it's getting better. I particularly think that we will see the adventure is improving. Um, it takes a while because the companies that have been funded up until now are still working in the biggest amount in the later stages. So I think that percentage hasn't been shifting. But I have to believe that that's a bit of an illusion, and then a couple of years, we're going to start to sea level out. But you know as well as I do that they're pretty poultry statistics in terms of the amount of venture that women like cos. Capture, Um, and the other ways that women are doubted, um, in terms of their ability and potential. Um, so we we love to work with any underrepresented group of entrepreneurs, and there's ways that we do that whether it's helping them sort of find their power and hold space and be confident. And, um, you know, be able to pitch to any room, talk to any investor, talk to any customer but also working to be directed about some of the systemic challenges, both in terms of talking to existing investors and trying to educate them to see the opportunities that they're missing because there is a an economic imperative to them understanding what they're missing. Um, but there's also some things that we're doing in-house to make sure that we're also helping to close capital gaps for all our entrepreneurs. So we actually now have a suite of three capital mechanisms that are entrepreneurs can access on the back end of our incubator, a microphone fund, which is very quick turnaround, small amounts of capital for entrepreneurs who existing opportunities owns, which is a tax destination. Just this in the U. S. But that's meant to be deployed so that they can access capital towards revenue without credit checks, collateral being put up, a slow moving pace of banks and C. D. S s. It's particularly useful for people who may not raise venture. And it's useful for, uh, you know, people who maybe don't have that friends and family check that they can expect similar. We've got a great angel network who look at the best impact deals from around the world. Um, and it doesn't have to be a housing company, just a great venture that's pursuing impact on profit. Um, and then lastly, we're just about to announce that we have a fund of our own on the back end of our incubator that funds only healthy and companies. Um, it's an early stage fund. Um, but watch this space because our pipeline is just increasing your every year. We used to sort of just 16 companies here. Now, we're serving 60 this year, so, um, yeah, it's really exciting. Um, and so obviously, it's really great that, you know, we're going to be able to help scale the impact that we want to see. Uh, ideally a lot. A lot faster. >>Well, you definitely taking control. I remember when we had a few years ago. I think four years ago, you just thinking about getting going and going now with great tailwind. Um, >>and the diversity >>of sources of capital as well as diversity of firms is increasing. That's helping, uh, that we're seeing, but you're also got the back end fun for the housing companies. But also, you've been involved in we capital for a long time. Can you talk about that? Because that's a specific supporting women entrepreneurs initiative. Um, yeah. What's up with capital share? That >>was That was another venture that I-i embarked on with such coz. Um as well as Sheila Johnson and Jonny Adam, Person who runs Rethink Impact. We capital is a group of about 16 women that I pulled together women investors to invest through rethink impact, which is another fun that is looking for impact businesses but predominantly looking for those businesses that are led by women. So this investment group is women supporting women. Um, through the use of deployment of capital, um, they're doing amazingly well. They've had some really stunning news recently that I'll let you dig up. >>I'll definitely thanks for the lead there. I'm gonna go jump on that story. >>Yeah, >>the Okay, Thanks for that lead on that trend, though in Silicon Valley and certainly in other areas that are hot like New York, Boston and D. C. Where you're at, um, you're seeing now multiple years in almost a decade in of the pioneers of these women, only funds or women only firms and your investment. Um, and it's starting to increase to under all underrepresented minorities and entrepreneurs. Right? So take us through how you see that because it's just getting more popular. Is that going to continue to accelerate in your mind? Are their networks of networks. They cross pollinating. >>Yeah, I think you know, it's It's I'm glad to see it. And, you know, it's been a long time coming. I think you know, I think we all look forward to a future where it's not necessary. Um, and you know, funds. Just invest in everyone Until then, making sure that we have specific pools of capital allocated to ensure that that, you know, those entrepreneurs who have not always been equally represented get to pursue their ideas not just because they deserve to pursue their ideas, but because the world needs their ideas. Right. And as I mentioned, there is a business imperative, right? We've got lots of examples of businesses like banks that you wouldn't have gotten a shot just because the investors just didn't understand the opportunity. Um, and I think that's normal. That's human. It happens to everyone. You are successful as an investor largely because you recognize patterns. And if something is, you know, outside of your life experience, you are not going to identify it. So it's very important that we create different kinds of capital run by different types of people. Um, and, uh, and you know. I know lots of investors have every type that are investing in these funds because they recognize that, you know, perhaps the highest growth potential is gonna come out of these, you know, particular kind of funds, which is really exciting. >>That's super important, because half the world is women, and that's just like the population is inspired by many new ventures. And that's super exciting trend. I wanna ask you about your other areas of doing a lot of work in the queue has been to buy multiple times, um, initially reporting on a region out there, and that's certainly isn't important part of the world. Um, you've got a lot of good news going on there. Can you share what's going on with, uh, the social entrepreneurship going on in Bahrain around the region? >>Yeah, I'm happy to. We we've actually been so privileged to work with a W S for a very long time. Almost since the start of the incubator they've supported are entrepreneurs, all of our entrepreneurs with access to cloud credits and services. Um, and we've sort of double down with a W S in the last couple of years in areas where We both want to create an uplift, um, for small businesses and rapidly growing tax solutions to these these social environmental problems. We see. So there's been an excellent partner to do that. And one of the areas we did in the water was with rain, particularly with women, tech startups, women tech startups in Bahrain. Yeah, we did that last year. We had an amazing group of women over in D. C. Um, and we continue to support them. One of them is actually in the process of raising. I think she just closed her seed round recently. And that's why for, um, al yet, um, and she created playbook, which is an amazing, uh, platform for women to take master classes and network and really sort of level up, as one says, Um, but also, um, the mall of work. Um uh, just really talented women over in Bahrain, um, pushing the envelope and all sorts of directions, and it was wonderful to get the opportunity to work with them. Um, that has now spawned another set of programs serving entrepreneurs in the Middle East in North Africa. They were also working on with us as well as the U S. State Department. Um, so we're going to be working for the next two years with entrepreneurs to help our recovery from covid. Um, in China. Um, and then I'm also proud to say that we're working with a W s in South Africa because there is just an extraordinary energy, you know, in the continent, Um, and some amazing entrepreneurial minds working on, you know, the many problems and opportunities that they're facing and recognizing. Um So we're supporting, you know, companies that are working on finding, um, skilled refugees to be able to help them resettle and use their talents and make money. Um, sadly, are very relevant company now with what's going on in Ukraine. Um, but also, uh, zombie and satellite company, um, companies that are preventing food, food waste by providing, um, solar-powered refrigerators to rural areas in South Africa. Um, so a lot of, um, you know, just incredible talent and ideas that we're seeing globally. Um, and happy to be doubling down on that with the help of a W s. >>That's awesome. Yeah, following the work when we met in D. C. And again, you always had this international view um it's International Women's Day. It's not North America >>Women's Day. It's >>International Women's Day. Can you share your thoughts on how that landscape is changing outside the U. S. For example, and around the world and how the international peace is important and you mentioned pattern matching? Um, you also, when you see patterns, they become trends. What do you see forming that have been that that are locked in on the U. C they're locked in on that are happening that are driving. What are some of those trends that you see on the international side that's evolving? >>Yeah. You know, I think the wonderful opportunity with the Internet and social media is that, you know, both, uh, we can be more transparent about areas for improvement and put a little pressure where maybe things are moving fast enough. We've all seen the power of that, Um, the other, um, you know, things that certainly in countries where women maybe as free to move and operate, they can still acquire skills education they can set up cos they can do so so much. Um, you know, through these amazing technologies that we now have at our disposal growing an amazing rates. Um, they can connect via zoom. Right? I think that while the pandemic definitely set women back and we should acknowledge that, um, uh, the things that the pandemic perhaps helped us to exponentially scale will move women forward. And perhaps that's the target to hang on to, to feel optimistic about where we're headed. >>And also, there's a lot of problems to solve. And I think one of the things we're seeing you mentioned the Ukraine situation. You're seeing the geopolitical landscape changing radically with technology driving a lot of value. So with problems comes opportunities. Um, innovation plays a big role. Can you share some of the successful stories that you were inspired by that you've seen, um, in the past couple of years. And as you look forward, what What some of those innovation stories look like? And what are you inspired by? >>Yeah. I mean, there's so, so many. Um, you know, we just, uh, had a couple of entrepreneurs, and just the last year, Um, you know, after I think everyone sort of took an initial breath with the pandemic, They realize that they either had an opportunity or they had a problem to solve to your point. Um, and they did that well or not. And or some of them, you know, just didn't didn't have any more cards to play and had to really pivot. Um, it was really interesting to see how everyone handled handled that particular moment in time. One company that I think of is everywhere. Um, and she had created a wearable device that you can just put on your ear. It looks like an earring right at the top of your ear. Um, and it was for her for herself because she suffered from pulmonary complications. And, uh, without more discreet wearable, you know, had to wear a huge device and look around and oxygen tank and, you know, just to sort of have a good quality of life. Um, it turns out, obviously, during covid, that is a very useful item, not just for patients suffering from covid and wanting to know what their oxygen levels were doing, but also potentially athletics. So, um, she's really been able to double down as a result of the trends from the pandemic. Um, and I'm really proud of part of her. And that's actually where another great one that we just just came through. Our last 15 is Maya. Um, and she had a brick and mortar store. Um, uh, called Cherry Blossom. Intimate where she helped women have an enjoyable experience finding, uh, and fitting bras post mastectomy to include sort of, you know, the necessary, um, prosthetics and things like that. Um, she even made it so that you could go with your friends who haven't had a mistake, and she could also find some lovely luxury. Um, but the pandemic meant that that experience was sort of off the table. Um, and what they did was she decided to make it a technological one. So now she's she's essentially will be part of it. You can, you know, go to my, um, online. And you can, um, you know, order, uh, measure yourself, work with a specialist, all online, get a few different options, figure out the one that's perfect for you and the rest back. Um, and I don't think without the pandemic, that would not have happened. So she's now able to serve exponentially more. Um, you know, women who deserve to feel like themselves post it to me. >>That's also a model and inspirational. I have to ask you for the young women out there watching. What advice would you share with them as they navigate into a world that's changing and evolving and getting better with other women, mentors and entrepreneurs and or just an ecosystem of community? What advice would you give them as they step into the world and have to engage and experience life? >>Yeah, gosh, part of me always wants to resist that they don't listen to anyone to do you follow your heart, follow your gut, or at least be careful who you listen to because a lot of people will want to give you advice. I would >>say, Uh, that's good advice. Don't take my advice. Well, you've been a great leader. Love the work, you're doing it and I'll say N D. C. But all around the world and again, there's so much change going on with innovation. I mean, just the advances in technology across the board, from with machine learning and AI from linguistics and understanding. And I think we're going to be a bigger community. Your thoughts on as you see community organically becoming a big part of how people are engaging. What's your what's your view As you look out across the landscape, communities becoming a big part of tribes. What's your vision on how the role of communities place? >>You know, we we actually do you think a lot about community and healthy. And we say that are you know, alchemy really is providing space, you know, physical and mental space to think, um, access access to capital access to networks, Um, community, Um, and the community piece is very, very important. Are entrepreneurs leave us like the number one thing that they miss is being among like-minded, um, you know, slightly slightly crazy audacious people. Um, and I often joked that we're building a kind army because it is, you know, it's people who want to do it differently if people want to do it with integrity. Is people who are in it for a very different motivations than just money. Um, and, you know, you start to feel the power of that group together and its entirety and what that might look like as as a community solving global problems. Um, and it really is inspiring. Um, I do think that people are starving for FaceTime and people time, real human time after the pandemic, I think they won't go away. It's a great tool, but we all want a little bit of that, and I will mention just along those lines. And if you don't mind a quick plug for an event that we're having March 16, Um, also in partnership with a W s called Build her relevant to International Women's Day as well. People can, either. If they're in the city, they can come in person. But we also have a virtual program, and we'll be listening to some of the most inspiring. Women leaders and entrepreneurs both in government and also the private sector share their knowledge on the side of the pandemic for for, you know, the next tribal group of women entrepreneurs and leaders. >>That's great. Well, you are on our website for sure. >>Thank you. Thank you. Appreciate it. >>And we love the fact that you're in our community as well. Doing great work. Thanks for spending time with the Cube and on International Women's Day celebration. Thanks for coming on and sharing. >>Thank you, John. >>Okay. The Cube International showcase Women's Day, featuring some great guests all around the world, Not just in the U S. But all over the world. I'm your host. Thanks for watching. Yeah, Yeah, yeah, hm, Yeah.

(upbeat music) >> Hey everyone. Welcome back to theCUBE's live coverage of Women in Data Science, WiDS 2022, coming to live from Stanford University. I'm Lisa Martin. My next guest is here. Nandi Leslie, Doctor Nandi Leslie, Senior Engineering Fellow at Raytheon Technologies. Nandi, it's great to have you on the program. >> Oh it's my pleasure, thank you. >> This is your first WiDS you were saying before we went live. >> That's right. >> What's your take so far? >> I'm absolutely loving it. I love the comradery and the community of women in data science. You know, what more can you say? It's amazing. >> It is. It's amazing what they built since 2015, that this is now reaching 100,000 people 200 online event. It's a hybrid event. Of course, here we are in person, and the online event going on, but it's always an inspiring, energy-filled experience in my experience of WiDS. >> I'm thoroughly impressed at what the organizers have been able to accomplish. And it's amazing, that you know, you've been involved from the beginning. >> Yeah, yeah. Talk to me, so you're Senior Engineering Fellow at Raytheon. Talk to me a little bit about your role there and what you're doing. >> Well, my role is really to think about our customer's most challenging problems, primarily at the intersection of data science, and you know, the intersectional fields of applied mathematics, machine learning, cybersecurity. And then we have a plethora of government clients and commercial clients. And so what their needs are beyond those sub-fields as well, I address. >> And your background is mathematics. >> Yes. >> Have you always been a math fan? >> I have, I actually have loved math for many, many years. My dad is a mathematician, and he introduced me to, you know mathematical research and the sciences at a very early age. And so, yeah, I went on, I studied in a math degree at Howard undergrad, and then I went on to do my PhD at Princeton in applied math. And later did a postdoc in the math department at University of Maryland. >> And how long have you been with Raytheon? >> I've been with Raytheon about six years. Yeah, and before Raytheon, I worked at a small to midsize defense company, defense contracting company in the DC area, systems planning and analysis. And then prior to that, I taught in a math department where I also did my postdoc, at University of Maryland College Park. >> You have a really interesting background. I was doing some reading on you, and you have worked with the Navy. You've worked with very interesting organizations. Talk to the audience a little bit about your diverse background. >> Awesome yeah, I've worked with the Navy on submarine force security, and submarine tracking, and localization, sensor performance. Also with the Army and the Army Research Laboratory during research at the intersection of machine learning and cyber security. Also looking at game theoretic and graph theoretic approaches to understand network resilience and robustness. I've also supported Department of Homeland Security, and other government agencies, other governments, NATO. Yeah, so I've really been excited by the diverse problems that our various customers have you know, brought to us. >> Well, you get such great experience when you are able to work in different industries and different fields. And that really just really probably helps you have such a much diverse kind of diversity of thought with what you're doing even now with Raytheon. >> Yeah, it definitely does help me build like a portfolio of topics that I can address. And then when new problems emerge, then I can pull from a toolbox of capabilities. And, you know, the solutions that have previously been developed to address those wide array of problems, but then also innovate new solutions based on those experiences. So I've been really blessed to have those experiences. >> Talk to me about one of the things I heard this morning in the session I was able to attend before we came to set was about mentors and sponsors. And, you know, I actually didn't know the difference between that until a few years ago. But it's so important. Talk to me about some of the mentors you've had along the way that really helped you find your voice in research and development. >> Definitely, I mean, beyond just the mentorship of my my family and my parents, I've had amazing opportunities to meet with wonderful people, who've helped me navigate my career. One in particular, I can think of as and I'll name a number of folks, but Dr. Carlos Castillo-Chavez was one of my earlier mentors. I was an undergrad at Howard University. He encouraged me to apply to his summer research program in mathematical and theoretical biology, which was then at Cornell. And, you know, he just really developed an enthusiasm with me for applied mathematics. And for how it can be, mathematics that is, can be applied to epidemiological and theoretical immunological problems. And then I had an amazing mentor in my PhD advisor, Dr. Simon Levin at Princeton, who just continued to inspire me, in how to leverage mathematical approaches and computational thinking for ecological conservation problems. And then since then, I've had amazing mentors, you know through just a variety of people that I've met, through customers, who've inspired me to write these papers that you mentioned in the beginning. >> Yeah, you've written 55 different publications so far. 55 and counting I'm sure, right? >> Well, I hope so. I hope to continue to contribute to the conversation and the community, you know, within research, and specifically research that is computationally driven. That really is applicable to problems that we face, whether it's cyber security, or machine learning problems, or others in data science. >> What are some of the things, you're giving a a tech vision talk this afternoon. Talk to me a little bit about that, and maybe the top three takeaways you want the audience to leave with. >> Yeah, so my talk is entitled "Unsupervised Learning for Network Security, or Network Intrusion Detection" I believe. And essentially three key areas I want to convey are the following. That unsupervised learning, that is the mathematical and statistical approach, which tries to derive patterns from unlabeled data is a powerful one. And one can still innovate new algorithms in this area. Secondly, that network security, and specifically, anomaly detection, and anomaly-based methods can be really useful to discerning and ensuring, that there is information confidentiality, availability, and integrity in our data >> A CIA triad. >> There you go, you know. And so in addition to that, you know there is this wealth of data that's out there. It's coming at us quickly. You know, there are millions of packets to represent communications. And that data has, it's mixed, in terms of there's categorical or qualitative data, text data, along with numerical data. And it is streaming, right. And so we need methods that are efficient, and that are capable of being deployed real time, in order to detect these anomalies, which we hope are representative of malicious activities, and so that we can therefore alert on them and thwart them. >> It's so interesting that, you know, the amount of data that's being generated and collected is growing exponentially. There's also, you know, some concerning challenges, not just with respect to data that's reinforcing social biases, but also with cyber warfare. I mean, that's a huge challenge right now. We've seen from a cybersecurity perspective in the last couple of years during the pandemic, a massive explosion in anomalies, and in social engineering. And companies in every industry have to be super vigilant, and help the people understand how to interact with it, right. There's a human component. >> Oh, for sure. There's a huge human component. You know, there are these phishing attacks that are really a huge source of the vulnerability that corporations, governments, and universities face. And so to be able to close that gap and the understanding that each individual plays in the vulnerability of a network is key. And then also seeing the link between the network activities or the cyber realm, and physical systems, right. And so, you know, especially in cyber warfare as a remote cyber attack, unauthorized network activities can have real implications for physical systems. They can, you know, stop a vehicle from running properly in an autonomous vehicle. They can impact a SCADA system that's, you know there to provide HVAC for example. And much more grievous implications. And so, you know, definitely there's the human component. >> Yes, and humans being so vulnerable to those social engineering that goes on in those phishing attacks. And we've seen them get more and more personal, which is challenging. You talking about, you know, sensitive data, personally identifiable data, using that against someone in cyber warfare is a huge challenge. >> Oh yeah, certainly. And it's one that computational thinking and mathematics can be leveraged to better understand and to predict those patterns. And that's a very rich area for innovation. >> What would you say is the power of computational thinking in the industry? >> In industry at-large? >> At large. >> Yes, I think that it is such a benefit to, you know, a burgeoning scientist, if they want to get into industry. There's so many opportunities, because computational thinking is needed. We need to be more objective, and it provides that objectivity, and it's so needed right now. Especially with the emergence of data, and you know, across industries. So there are so many opportunities for data scientists, whether it's in aerospace and defense, like Raytheon or in the health industry. And we saw with the pandemic, the utility of mathematical modeling. There are just so many opportunities. >> Yeah, there's a lot of opportunities, and that's one of the themes I think, of WiDS, is just the opportunities, not just in data science, and for women. And there's obviously even high school girls that are here, which is so nice to see those young, fresh faces, but opportunities to build your own network and your own personal board of directors, your mentors, your sponsors. There's tremendous opportunity in data science, and it's really all encompassing, at least from my seat. >> Oh yeah, no I completely agree with that. >> What are some of the things that you've heard at this WiDS event that inspire you going, we're going in the right direction. If we think about International Women's Day tomorrow, "Breaking the Bias" is the theme, do you think we're on our way to breaking that bias? >> Definitely, you know, there was a panel today talking about the bias in data, and in a variety of fields, and how we are, you know discovering that bias, and creating solutions to address it. So there was that panel. There was another talk by a speaker from Pinterest, who had presented some solutions that her, and her team had derived to address bias there, in you know, image recognition and search. And so I think that we've realized this bias, and, you know, in AI ethics, not only in these topics that I've mentioned, but also in the implications for like getting a loan, so economic implications, as well. And so we're realizing those issues and bias now in AI, and we're addressing them. So I definitely am optimistic. I feel encouraged by the talks today at WiDS that you know, not only are we recognizing the issues, but we're creating solutions >> Right taking steps to remediate those, so that ultimately going forward. You know, we know it's not possible to have unbiased data. That's not humanly possible, or probably mathematically possible. But the steps that they're taking, they're going in the right direction. And a lot of it starts with awareness. >> Exactly. >> Of understanding there is bias in this data, regardless. All the people that are interacting with it, and touching it, and transforming it, and cleaning it, for example, that's all influencing the veracity of it. >> Oh, for sure. Exactly, you know, and I think that there are for sure solutions are being discussed here, papers written by some of the speakers here, that are driving the solutions to the mitigation of this bias and data problem. So I agree a hundred percent with you, that awareness is you know, half the battle, if not more. And then, you know, that drives creation of solutions >> And that's what we need the creation of solutions. Nandi, thank you so much for joining me today. It was a pleasure talking with you about what you're doing with Raytheon, what you've done and your path with mathematics, and what excites you about data science going forward. We appreciate your insights. >> Thank you so much. It was my pleasure. >> Good, for Nandi Leslie, I'm Lisa Martin. You're watching theCUBE's coverage of Women in Data Science 2022. Stick around, I'll be right back with my next guest. (upbeat flowing music)

(upbeat music) >> Welcome back to HPE Discover 2021, theCUBE's virtual coverage, continuous coverage of HPE's Annual Customer Event. My name is Dave Vellante, and we're going to dive into the intersection of high-performance computing, data and AI with Doctor Eng Lim Goh, who's a Senior Vice President and CTO for AI at Hewlett Packard Enterprise. Doctor Goh, great to see you again. Welcome back to theCUBE. >> Hello, Dave, great to talk to you again. >> You might remember last year we talked a lot about Swarm intelligence and how AI is evolving. Of course, you hosted the Day 2 Keynotes here at Discover. And you talked about thriving in the age of insights, and how to craft a data-centric strategy. And you addressed some of the biggest problems, I think organizations face with data. That's, you've got a, data is plentiful, but insights, they're harder to come by. >> Yeah. >> And you really dug into some great examples in retail, banking, in medicine, healthcare and media. But stepping back a little bit we zoomed out on Discover '21. What do you make of the events so far and some of your big takeaways? >> Hmm, well, we started with the insightful question, right, yeah? Data is everywhere then, but we lack the insight. That's also part of the reason why, that's a main reason why Antonio on day one focused and talked about the fact that we are in the now in the age of insight, right? And how to try thrive in that age, in this new age? What I then did on a Day 2 Keynote following Antonio is to talk about the challenges that we need to overcome in order to thrive in this new age. >> So, maybe we could talk a little bit about some of the things that you took away in terms of, I'm specifically interested in some of the barriers to achieving insights. You know customers are drowning in data. What do you hear from customers? What were your takeaway from some of the ones you talked about today? >> Oh, very pertinent question, Dave. You know the two challenges I spoke about, that we need to overcome in order to thrive in this new age. The first one is the current challenge. And that current challenge is, you know, stated is now barriers to insight, when we are awash with data. So that's a statement on how do you overcome those barriers? What are the barriers to insight when we are awash in data? In the Day 2 Keynote, I spoke about three main things. Three main areas that we receive from customers. The first one, the first barrier is in many, with many of our customers, data is siloed, all right. You know, like in a big corporation, you've got data siloed by sales, finance, engineering, manufacturing and so on supply chain and so on. And there's a major effort ongoing in many corporations to build a federation layer above all those silos so that when you build applications above, they can be more intelligent. They can have access to all the different silos of data to get better intelligence and more intelligent applications built. So that was the first barrier we spoke about, you know? Barriers to insight when we are awash with data. The second barrier is that we see amongst our customers is that data is raw and disperse when they are stored. And you know, it's tough to get at, to tough to get a value out of them, right? And in that case, I use the example of, you know, the May 6, 2010 event where the stock market dropped a trillion dollars in terms of minutes. We all know those who are financially attuned with know about this incident but that this is not the only incident. There are many of them out there. And for that particular May 6 event, you know, it took a long time to get insight. Months, yeah, before we, for months we had no insight as to what happened. Why it happened? Right, and there were many other incidences like this and the regulators were looking for that one rule that could mitigate many of these incidences. One of our customers decided to take the hard road they go with the tough data, right? Because data is raw and dispersed. So they went into all the different feeds of financial transaction information, took the tough, you know, took a tough road. And analyze that data took a long time to assemble. And they discovered that there was caught stuffing, right? That people were sending a lot of trades in and then canceling them almost immediately. You have to manipulate the market. And why didn't we see it immediately? Well, the reason is the process reports that everybody sees, the rule in there that says, all trades less than a hundred shares don't need to report in there. And so what people did was sending a lot of less than a hundred shares trades to fly under the radar to do this manipulation. So here is the second barrier, right? Data could be raw and dispersed. Sometimes it's just have to take the hard road and to get insight. And this is one great example. And then the last barrier has to do with sometimes when you start a project to get insight, to get answers and insight, you realize that all the data's around you, but you don't seem to find the right ones to get what you need. You don't seem to get the right ones, yeah? Here we have three quick examples of customers. One was a great example, right? Where they were trying to build a language translator or machine language translator between two languages, right? By not do that, they need to get hundreds of millions of word pairs. You know of one language compare with the corresponding other. Hundreds of millions of them. They say, well, I'm going to get all these word pairs. Someone creative thought of a willing source and a huge, it was a United Nations. You see? So sometimes you think you don't have the right data with you, but there might be another source and a willing one that could give you that data, right? The second one has to do with, there was the sometimes you may just have to generate that data. Interesting one, we had an autonomous car customer that collects all these data from their their cars, right? Massive amounts of data, lots of sensors, collect lots of data. And, you know, but sometimes they don't have the data they need even after collection. For example, they may have collected the data with a car in fine weather and collected the car driving on this highway in rain and also in snow. But never had the opportunity to collect the car in hill because that's a rare occurrence. So instead of waiting for a time where the car can drive in hill, they build a simulation by having the car collected in snow and simulated him. So these are some of the examples where we have customers working to overcome barriers, right? You have barriers that is associated. In fact, that data silo, they federated it. Virus associated with data, that's tough to get at. They just took the hard road, right? And sometimes thirdly, you just have to be creative to get the right data you need. >> Wow! I tell you, I have about a hundred questions based on what you just said, you know? (Dave chuckles) And as a great example, the Flash Crash. In fact, Michael Lewis, wrote about this in his book, the Flash Boys. And essentially, right, it was high frequency traders trying to front run the market and sending into small block trades (Dave chuckles) trying to get sort of front ended. So that's, and they chalked it up to a glitch. Like you said, for months, nobody really knew what it was. So technology got us into this problem. (Dave chuckles) I guess my question is can technology help us get out of the problem? And that maybe is where AI fits in? >> Yes, yes. In fact, a lot of analytics work went in to go back to the raw data that is highly dispersed from different sources, right? Assembled them to see if you can find a material trend, right? You can see lots of trends, right? Like, no, we, if humans look at things that we tend to see patterns in Clouds, right? So sometimes you need to apply statistical analysis math to be sure that what the model is seeing is real, right? And that required, well, that's one area. The second area is you know, when this, there are times when you just need to go through that tough approach to find the answer. Now, the issue comes to mind now is that humans put in the rules to decide what goes into a report that everybody sees. Now, in this case, before the change in the rules, right? But by the way, after the discovery, the authorities changed the rules and all shares, all trades of different any sizes it has to be reported. >> Right. >> Right, yeah? But the rule was applied, you know, I say earlier that shares under a hundred, trades under a hundred shares need not be reported. So, sometimes you just have to understand that reports were decided by humans and for understandable reasons. I mean, they probably didn't wanted a various reasons not to put everything in there. So that people could still read it in a reasonable amount of time. But we need to understand that rules were being put in by humans for the reports we read. And as such, there are times we just need to go back to the raw data. >> I want to ask you... >> Oh, it could be, that it's going to be tough, yeah. >> Yeah, I want to ask you a question about AI as obviously it's in your title and it's something you know a lot about but. And I'm going to make a statement, you tell me if it's on point or off point. So seems that most of the AI going on in the enterprise is modeling data science applied to, you know, troves of data. But there's also a lot of AI going on in consumer. Whether it's, you know, fingerprint technology or facial recognition or natural language processing. Well, two part question will the consumer market, as it has so often in the enterprise sort of inform us is sort of first part. And then, there'll be a shift from sort of modeling if you will to more, you mentioned the autonomous vehicles, more AI inferencing in real time, especially with the Edge. Could you help us understand that better? >> Yeah, this is a great question, right? There are three stages to just simplify. I mean, you know, it's probably more sophisticated than that. But let's just simplify that three stages, right? To building an AI system that ultimately can predict, make a prediction, right? Or to assist you in decision-making. I have an outcome. So you start with the data, massive amounts of data that you have to decide what to feed the machine with. So you feed the machine with this massive chunk of data, and the machine starts to evolve a model based on all the data it's seeing. It starts to evolve, right? To a point that using a test set of data that you have separately kept aside that you know the answer for. Then you test the model, you know? After you've trained it with all that data to see whether its prediction accuracy is high enough. And once you are satisfied with it, you then deploy the model to make the decision. And that's the inference, right? So a lot of times, depending on what we are focusing on, we in data science are, are we working hard on assembling the right data to feed the machine with? That's the data preparation organization work. And then after which you build your models you have to pick the right models for the decisions and prediction you need to make. You pick the right models. And then you start feeding the data with it. Sometimes you pick one model and a prediction isn't that robust. It is good, but then it is not consistent, right? Now what you do is you try another model. So sometimes it gets keep trying different models until you get the right kind, yeah? That gives you a good robust decision-making and prediction. Now, after which, if it's tested well, QA, you will then take that model and deploy it at the Edge. Yeah, and then at the Edge is essentially just looking at new data, applying it to the model that you have trained. And then that model will give you a prediction or a decision, right? So it is these three stages, yeah. But more and more, your question reminds me that more and more people are thinking as the Edge become more and more powerful. Can you also do learning at the Edge? >> Right. >> That's the reason why we spoke about Swarm Learning the last time. Learning at the Edge as a Swarm, right? Because maybe individually, they may not have enough power to do so. But as a Swarm, they may. >> Is that learning from the Edge or learning at the Edge? In other words, is that... >> Yes. >> Yeah. You do understand my question. >> Yes. >> Yeah. (Dave chuckles) >> That's a great question. That's a great question, right? So the quick answer is learning at the Edge, right? And also from the Edge, but the main goal, right? The goal is to learn at the Edge so that you don't have to move the data that Edge sees first back to the Cloud or the Call to do the learning. Because that would be the reason, one of the main reasons why you want to learn at the Edge. Right? So that you don't need to have to send all that data back and assemble it back from all the different Edge devices. Assemble it back to the Cloud Site to do the learning, right? Some on you can learn it and keep the data at the Edge and learn at that point, yeah. >> And then maybe only selectively send. >> Yeah. >> The autonomous vehicle, example you gave is great. 'Cause maybe they're, you know, there may be only persisting. They're not persisting data that is an inclement weather, or when a deer runs across the front. And then maybe they do that and then they send that smaller data setback and maybe that's where it's modeling done but the rest can be done at the Edge. It's a new world that's coming through. Let me ask you a question. Is there a limit to what data should be collected and how it should be collected? >> That's a great question again, yeah. Well, today full of these insightful questions. (Dr. Eng chuckles) That actually touches on the the second challenge, right? How do we, in order to thrive in this new age of insight? The second challenge is our future challenge, right? What do we do for our future? And in there is the statement we make is we have to focus on collecting data strategically for the future of our enterprise. And within that, I talked about what to collect, right? When to organize it when you collect? And then where will your data be going forward that you are collecting from? So what, when, and where? For what data to collect? That was the question you asked, it's a question that different industries have to ask themselves because it will vary, right? Let me give you the, you use the autonomous car example. Let me use that. And we do have this customer collecting massive amounts of data. You know, we're talking about 10 petabytes a day from a fleet of their cars. And these are not production autonomous cars, right? These are training autonomous cars, collecting data so they can train and eventually deploy commercial cars, right? Also this data collection cars, they collect 10, as a fleet of them collect 10 petabytes a day. And then when they came to us, building a storage system you know, to store all of that data, they realized they don't want to afford to store all of it. Now here comes the dilemma, right? What should I, after I spent so much effort building all this cars and sensors and collecting data, I've now decide what to delete. That's a dilemma, right? Now in working with them on this process of trimming down what they collected, you know, I'm constantly reminded of the 60s and 70s, right? To remind myself 60s and 70s, we called a large part of our DNA, junk DNA. >> Yeah. (Dave chuckles) >> Ah! Today, we realized that a large part of that what we call junk has function as valuable function. They are not genes but they regulate the function of genes. You know? So what's junk in yesterday could be valuable today. Or what's junk today could be valuable tomorrow, right? So, there's this tension going on, right? Between you deciding not wanting to afford to store everything that you can get your hands on. But on the other hand, you worry, you ignore the wrong ones, right? You can see this tension in our customers, right? And then it depends on industry here, right? In healthcare they say, I have no choice. I want it all, right? Oh, one very insightful point brought up by one healthcare provider that really touched me was you know, we don't only care. Of course we care a lot. We care a lot about the people we are caring for, right? But who also care for the people we are not caring for? How do we find them? >> Uh-huh. >> Right, and that definitely, they did not just need to collect data that they have with from their patients. They also need to reach out, right? To outside data so that they can figure out who they are not caring for, right? So they want it all. So I asked them, so what do you do with funding if you want it all? They say they have no choice but to figure out a way to fund it and perhaps monetization of what they have now is the way to come around and fund that. Of course, they also come back to us rightfully, that you know we have to then work out a way to help them build a system, you know? So that's healthcare, right? And if you go to other industries like banking, they say they can afford to keep them all. >> Yeah. >> But they are regulated, seemed like healthcare, they are regulated as to privacy and such like. So many examples different industries having different needs but different approaches to what they collect. But there is this constant tension between you perhaps deciding not wanting to fund all of that, all that you can install, right? But on the other hand, you know if you kind of don't want to afford it and decide not to start some. Maybe those some become highly valuable in the future, right? (Dr. Eng chuckles) You worry. >> Well, we can make some assumptions about the future. Can't we? I mean, we know there's going to be a lot more data than we've ever seen before. We know that. We know, well, not withstanding supply constraints and things like NAND. We know the prices of storage is going to continue to decline. We also know and not a lot of people are really talking about this, but the processing power, but the says, Moore's law is dead. Okay, it's waning, but the processing power when you combine the CPUs and NPUs, and GPUs and accelerators and so forth actually is increasing. And so when you think about these use cases at the Edge you're going to have much more processing power. You're going to have cheaper storage and it's going to be less expensive processing. And so as an AI practitioner, what can you do with that? >> Yeah, it's a highly, again, another insightful question that we touched on our Keynote. And that goes up to the why, uh, to the where? Where will your data be? Right? We have one estimate that says that by next year there will be 55 billion connected devices out there, right? 55 billion, right? What's the population of the world? Well, of the other 10 billion? But this thing is 55 billion. (Dave chuckles) Right? And many of them, most of them can collect data. So what do you do? Right? So the amount of data that's going to come in, it's going to way exceed, right? Drop in storage costs are increasing compute power. >> Right. >> Right. So what's the answer, right? So the answer must be knowing that we don't, and even a drop in price and increase in bandwidth, it will overwhelm the, 5G, it will overwhelm 5G, right? Given the amount of 55 billion of them collecting. So the answer must be that there needs to be a balance between you needing to bring all of that data from the 55 billion devices of the data back to a central, as a bunch of central cost. Because you may not be able to afford to do that. Firstly bandwidth, even with 5G and as the, when you'll still be too expensive given the number of devices out there. You know given storage costs dropping is still be too expensive to try and install them all. So the answer must be to start, at least to mitigate from to, some leave most a lot of the data out there, right? And only send back the pertinent ones, as you said before. But then if you did that then how are we going to do machine learning at the Core and the Cloud Site, if you don't have all the data? You want rich data to train with, right? Sometimes you want to mix up the positive type data and the negative type data. So you can train the machine in a more balanced way. So the answer must be eventually, right? As we move forward with these huge number of devices all at the Edge to do machine learning at the Edge. Today we don't even have power, right? The Edge typically is characterized by a lower energy capability and therefore lower compute power. But soon, you know? Even with low energy, they can do more with compute power improving in energy efficiency, right? So learning at the Edge, today we do inference at the Edge. So we data, model, deploy and you do inference there is. That's what we do today. But more and more, I believe given a massive amount of data at the Edge, you have to start doing machine learning at the Edge. And when you don't have enough power then you aggregate multiple devices, compute power into a Swarm and learn as a Swarm, yeah. >> Oh, interesting. So now of course, if I were sitting and fly on the wall and the HPE board meeting I said, okay, HPE is a leading provider of compute. How do you take advantage of that? I mean, we're going, I know it's future but you must be thinking about that and participating in those markets. I know today you are, you have, you know, Edge line and other products. But there's, it seems to me that it's not the general purpose that we've known in the past. It's a new type of specialized computing. How are you thinking about participating in that opportunity for the customers? >> Hmm, the wall will have to have a balance, right? Where today the default, well, the more common mode is to collect the data from the Edge and train at some centralized location or number of centralized location. Going forward, given the proliferation of the Edge devices, we'll need a balance, we need both. We need capability at the Cloud Site, right? And it has to be hybrid. And then we need capability on the Edge side that we need to build systems that on one hand is an Edge adapter, right? Meaning they environmentally adapted because the Edge differently are on it, a lot of times on the outside. They need to be packaging adapted and also power adapted, right? Because typically many of these devices are battery powered. Right? So you have to build systems that adapts to it. But at the same time, they must not be custom. That's my belief. It must be using standard processes and standard operating system so that they can run a rich set of applications. So yes, that's also the insight for that Antonio announced in 2018. For the next four years from 2018, right? $4 billion invested to strengthen our Edge portfolio. >> Uh-huh. >> Edge product lines. >> Right. >> Uh-huh, Edge solutions. >> I could, Doctor Goh, I could go on for hours with you. You're just such a great guest. Let's close. What are you most excited about in the future of, certainly HPE, but the industry in general? >> Yeah, I think the excitement is the customers, right? The diversity of customers and the diversity in the way they have approached different problems of data strategy. So the excitement is around data strategy, right? Just like, you know, the statement made for us was so was profound, right? And Antonio said, we are in the age of insight powered by data. That's the first line, right? The line that comes after that is as such we are becoming more and more data centric with data that currency. Now the next step is even more profound. That is, you know, we are going as far as saying that, you know, data should not be treated as cost anymore. No, right? But instead as an investment in a new asset class called data with value on our balance sheet. This is a step change, right? Right, in thinking that is going to change the way we look at data, the way we value it. So that's a statement. (Dr. Eng chuckles) This is the exciting thing, because for me a CTO of AI, right? A machine is only as intelligent as the data you feed it with. Data is a source of the machine learning to be intelligent. Right? (Dr. Eng chuckles) So, that's why when the people start to value data, right? And say that it is an investment when we collect it it is very positive for AI. Because an AI system gets intelligent, get more intelligence because it has huge amounts of data and a diversity of data. >> Yeah. >> So it'd be great, if the community values data. >> Well, you certainly see it in the valuations of many companies these days. And I think increasingly you see it on the income statement. You know data products and people monetizing data services. And yeah, maybe eventually you'll see it in the balance sheet. I know Doug Laney, when he was at Gartner Group, wrote a book about this and a lot of people are thinking about it. That's a big change, isn't it? >> Yeah, yeah. >> Dr. Goh... (Dave chuckles) >> The question is the process and methods in valuation. Right? >> Yeah, right. >> But I believe we will get there. We need to get started. And then we'll get there. I believe, yeah. >> Doctor Goh, it's always my pleasure. >> And then the AI will benefit greatly from it. >> Oh, yeah, no doubt. People will better understand how to align, you know some of these technology investments. Dr. Goh, great to see you again. Thanks so much for coming back in theCUBE. It's been a real pleasure. >> Yes, a system is only as smart as the data you feed it with. (Dave chuckles) (Dr. Eng laughs) >> Excellent. We'll leave it there. Thank you for spending some time with us and keep it right there for more great interviews from HPE Discover 21. This is Dave Vellante for theCUBE, the leader in Enterprise Tech Coverage. We'll be right back. (upbeat music)

>>Welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. We're here with Amanda Silver, corporate vice president, product developer division at Microsoft. Amanda, Great to see you you were on last year, Dr khan. Great to see you again a full year later were remote. Thanks for coming on. I know you're super busy with build happening this week as well. Thanks for making the time to come on the cube for Dr khan. >>Thank you so much for having me. Yeah, I'm joining you like many developers around the globe from my personal home office, >>developers really didn't skip a beat during the pandemic and again, it was not a good situation but developers, as you talked about last year on the front lines, first responders to creating value quite frankly, looking back you were pretty accurate in your prediction, developers did have an impact this year. They did create the kind of change that really changed the game for people's lives, whether it was developing solutions from a medical standpoint or even keeping systems running from call centres to making sure people got their their their goods or services and checks and and and kept sanity together. So. >>Yeah absolutely. I mean I think I think developers you know get the M. V. P. Award for this year because you know at the end of the day they are the digital first responders to the first responders and the pivot that we've had to make over the past year in terms of supporting remote telehealth, supporting you know online retail, curbside pickup. All of these things were done through developers being the ones pushing the way forward remote learning. You know my kids are learning at home right behind me right now so you might hear them during the interview that's happening because developers made that happen. >>I don't think mom please stop hogging the band with, they've got a gigabit. Stop it. Don't be streaming. My kids are all game anyway, Hey, great to have you on and you have to get the great keynote, exciting to see you guys continue the collaboration with Docker uh with GIT hub and Microsoft, A great combination, it's a 123 power punch of value. You guys are really kind of killing it. We heard from scott and dan has been on the cube. What's your thoughts on the partnership with the developer division team at Microsoft with Doctor, What's it all about this year? What's the next level? >>Well, I mean, I think, I think what's really awesome about this partnership is that we all have, we all are basically sharing a common mission. What we want to do is make sure that we're empowering developers, that we're focused on their productivity and that we're delivering value to them so they can do their job better so that they can help others. So that's really kind of what drives us day in and day out. So what we focus on is developer productivity. And I think that's a lot of what dana was talking about in her session, the developer division. Specifically, we really try to make sure that we're improving the state of the art from modern developers. So we want to make sure that every keystroke that they take, every mouse move that they make, it sounds like a song but every every one of those matter because we want to make sure that every developers writing the code that only they can write and in terms of the partnership and how that's going. You know my team and the darker team have been collaborating a ton on things like dr desktop and the Doctor Cli tool integrations. And one of the things that we do is we think about pain points and various workflows. We want to make sure that we're shaving off the edges of all of the user experience is the developers have to go through to piece all of these applications together. So one of the big pain points that we have heard from developers is that signing into the Azure cloud and especially our sovereign clouds was challenging. So we contributed back to uh back to doctor to actually make it easier to sign into these clouds. And so dr developers can now use dr desktop and the Doctor Cli to actually change the doctor context so that its Azure. So that makes it a lot easier to connect the other. Oh, sorry, go ahead. No, I was just >>going to say, I love the reference of the police song. Every breath you take, every >>mouth moving. Great, >>great line there. Uh, but I want to ask you while you're on this modern cloud um, discussion, what is I mean we have a lot of developers here at dr khan. As you know, you guys know developers in your ecosystem in core competency. From Microsoft, Kublai khan is a very operator like focus developed. This is a developer conference. You guys have build, what is the state of the art for a modern cloud developer? Could you just share your thoughts because this comes up a lot. You know, what's through the art? What's next jan new guard guard? It's his legacy. What is the state of the art for a modern cloud developer? >>Fantastic question. And extraordinarily relevant to this particular conference. You know what I think about often times it's really what is the inner loop and the outer loop look like in terms of cycle times? Because at the end of the day, what matters is the time that it takes for you to make that code change, to be able to see it in your test environment and to be able to deploy it to production and have the confidence that it's delivering the feature set that you need it to. And it's, you know, it's secure, it's reliable, it's performance, that's what a developer cares about at the end of the day. Um, at the same time, we also need to make sure that we're growing our team to meet our demand, which means we're constantly on boarding new developers. And so what I take inspiration from our, some of the tech elite who have been able to invest significant amounts in, in tuning their engineering systems, they've been able to make it so that a new developer can join a team in just a couple of minutes or less that they can actually make a code change, see that be reflected in their application in just a few seconds and deploy with confidence within hours. And so our goal is to actually be able to take that state of the art metric and democratize that actually bring it to as many of our customers as we possibly can. >>You mentioned supply chain earlier in securing that. What are you guys doing with Docker and how to make that partnership better with registries? Is there any update there in terms of the container registry on Azure? >>Yeah, I mean, you know, we, we we have definitely seen recent events and and it almost seems like a never ending attacks that that you know, increasingly are getting more and more focused on developer watering holes is how we think about it. Kind of developers being a primary target um for these malicious hackers. And so what it's more important than ever that every developer um and Microsoft especially uh really take security extraordinarily seriously. Our engineers are working around the clock to make sure that we are responding to every security incident that we hear about and partnering with our customers to make sure that we're supporting them as well. One of the things that we announced earlier this week at Microsoft build is that we've actually taken, get have actions and we've now integrated that into the Azure Security Center. And so what this means is that, you know, we can now do things like scan for vulnerabilities. Um look at things like who is logging in, where things like that and actually have that be tracked in the Azure security center so that not just your developers get that notification but also your I. T. Operations. Um In terms of the partnership with dR you know, this is actually an ongoing partnership to make sure that we can provide more guidance to developers to make sure that they are following best practices like pulling from a private registry like Docker hub or at your container registry. So I expect that as time goes on will continue to more in partnership in this space >>and that's going to give a lot of confidence. Actually, productivity wise is going to be a big help for developers. Great stuff is always good, good progress. They're moving the needle. >>Last time we >>spoke we talked about tools and setting Azure as the doctor context duty tooling updates here at dot com this year. That's notable. >>Yeah, I mean, I think, you know, there's one major thing that we've been working on which has a big dependency on docker is get help. Code space is now one of the biggest pain points that developers have is setting up a new DEV box, which they often have to do when they are on boarding a new employee or when they're starting a new project or even if they're just kicking the tires on a new technology that they want to be able to evaluate and sometimes creating a developer environment can actually take hours um and especially when you're trying to create a developer environment that matches somebody else's developer environment that can take like a half a day and you can spend all of your time just debugging the differences in environment variables, for example, um, containers actually makes that much easier. So what you can do with this, this services, you can actually create death environment spun up in the cloud and you can access it in seconds and you get from there are working coding environment and a runtime environment and this is repeatable via containers. So it means that there's no inadvertent differences introduced by each DEV. And you might be interested to know that underneath this is actually using Docker files and dr composed to orchestrate the debits and the runtime bits for a whole bunch of different stacks. And so this is something that we're actually working on in collaboration with the with the doctor team to have a common the animal format. And in fact this week we actually introduced a couple of app templates so that everybody can see this all in action. So if you check out a ca dot m s forward slash app template, you can see this in action yourself. >>You guys have always had such a strong developer community and one thing I love about cloud as it brings more agility, as we always talk about. But when you start to see the enterprise grow into, the direction is going now, it's almost like the developer communities are emerging, it's no longer about all the Lennox folks here and the dot net folks there, you've got windows, you've got cloud, >>it's almost >>the the the solidification of everyone kind of coming together. Um and visual studio, for instance, last year, I think you were talking about that to having to be interrogated dr composed, et cetera. >>How do you see >>this melting pot emerging? Because at the end of the day, you pick the language you love and you got devops, which is infrastructure as code doesn't matter. So give us your take on where we are with that whole progress of of making that happen. >>Well, I mean I definitely think that, you know, developer environments and and kind of, you know, our approach to them don't need to be as dogmatic as they've been in the past. I really think that, you know, you can pick the right tool and language and stand developer stack for your team, for your experience and you can be productive and that's really our goal. And Microsoft is to make sure that we have tools for every developer and every team so that they can build any app that they want to want to create. Even if that means that they're actually going to end up ultimately deploying that not to our cloud, they're going to end up deploying it to AWS or another another competitive cloud. And so, you know, there's a lot of things that we've been doing to make that really much easier. We have integrated container tools in visual studio and visual studio code and better cli integrations like with the doctor context that we had talked about a little bit earlier. We continue to try to make it easier to build applications that are targeting containers and then once you create those containers it's much easier to take it to another environment. One of the examples of this kind of work is now that we have WsL and the Windows subsystem for Lennox. This makes it a lot easier for developers who prefer a Windows operating system as their environment and maybe some tools like Visual Studio that run on Windows, but they can still target Lennox with as their production environment without any impedance mismatch. They can actually be as productive as they would be if they had a Linux box as their Os >>I noticed on this session, I got to call this out. I want to get your reaction to it interesting. Selection of Microsoft talks, the container based development. Visual studio code is one that's where you're going to show some some some container action going on with note and Visual Studio code. And then you get the machine learning with Azure uh containers in the V. S. Code. Interesting how you got, you know, containers with V. S. And now you've got machine learning. What does that tell the world about where Microsoft's at? Because in a way you got the cutting edge container management on one side with the doctor integration. Now you get the machine learning which everyone's talking about shifting, left more automation. Why are these sessions so important? Why should people attend? And what's the what's the bottom line? >>Well, like I said, like containers basically empower developer productivity. Um that's what creates the reputable environments, that's what allows us to make sure that, you know, we're productive as soon as we possibly can be with any text act that we want to be able to target. Um and so that's kind of almost the ecosystem play. Um it's how every developer can contribute to the success of others and we can amor ties the kinds of work that we do to set up an environment. So that's what I would say about the container based development that we're doing with both visual studio and visual studio code. Um in terms of the machine learning development, uh you know, the number of machine learning developers in the world is relatively small, but it's growing and it's obviously a very important set of developers because to train a machine learning uh to train an ml model, it actually requires a significant amount of compute resources, and so that's a perfect opportunity to bring in the research that are in a public cloud. Um What's actually really interesting about that particular develop developer stack is that it commonly runs on things like python. And for those of you who have developed in python, you know, just how difficult it is to actually set up a python environment with the right interpreter, with the right run time, with the right libraries that can actually get going super quickly, um and you can be productive as a developer. And so it's actually one of the hardest, most challenging developer stacks to actually set up. And so this allows you to become a machine learning developer without having to spend all of your time just setting up the python runtime environment. >>Yeah, it's a nice, nice little call out on python, it's a double edged sword. It's easier to sling code around on one hand, when you start getting working then you gotta it gets complicated can get well. Um Well the great, great call out there on the island, but good, good, good project. Let me get your thoughts on this other tool that you guys are talking about project tie. Uh This is interesting because this is a trend that we're seeing a lot of conversations here on the cube about around more too many control planes. Too many services. You know, I no longer have that monolithic application. I got micro micro applications with microservices. What the hell is going on with my services? >>Yeah, I mean, I think, you know, containers brought an incredible amount of productivity in terms of having repeatable environments, both for dev environments, which we talked about a lot on this interview already, but also obviously in production and test environments. Super important. Um and with that a lot of times comes the microservices architecture that we're also moving to and the way that I view it is the microservices architecture is actually accompanied by businesses being more focused on the value that they can actually deliver to customers. And so they're trying to kind of create separations of concerns in terms of the different services that they're offering, so they can actually version and and kind of, you know, actually improve each of these services independently. But what happens when you start to have many microservices working together in a SAS or in some kind of aggregate um service environment or kind of application environment is it starts to get unwieldy, it's really hard to make it so that one micro service can actually address another micro service. They can pass information back and forth. And you know what used to be maybe easy if you were just building a client server application because, you know, within the server tear all of your code was basically contained in the same runtime environment. That's no longer the case when every microservices actually running inside of its own container. So the question is, how can we improve program ability by making it easier for one micro service that's being used in an application environment, be to be able to access another another service and kind of all of that context. Um and so, you know, you want to be able to access the service is the the api endpoint, the containers, the ingress is everything, make everything work together as though it felt just as easy as as um you know, server application development. Um And so what this means as well is that you also oftentimes need to get all of these different containers running at the same time and that can actually be a challenge in the developer and test loop as well. So what project tie does is it improves the program ability and it actually allows you to just write a command like thai run so that you can actually in stan she ate all of these containers and get them up and running and basically deploy and run your application in that environment and ultimately make the dev testing or loop much faster >>than productivity gain. Right. They're making it simple to stand up. Great, great stuff. Let me ask you a question as we kind of wrap down here for the folks here at Dakar Con, are >>there any >>special things you'd like to talk about the development you think are important for the developers here within this space? It's very dynamic. A lot of change happening in a good way. Um, but >>sometimes it's hard to keep >>track of all the cool stuff happening. Could you take a minute to, to share your thoughts on what you think are the most important develops developments in this space? That that might be interesting to ducker con attendees. >>I think the most important things are to recognize that developer environments are moving to containerized uh, environments themselves so that they can be repeated, they can be shared, the work, configuring them can be amortized across many developers. That's important thing. Number one important thing. Number two is it doesn't matter as much what operating system you're running as your chrome, you know, desktop. What matters is ultimately the production environment that you're targeting. And so I think now we're in a world where all of those things can be mixed and matched together. Um and then I think the next thing is how can we actually improve microservices, uh programming development together um so that it's easier to be able to target multiple micro services that are working in aggregate uh to create a single service experience or a single application. And how do we improve the program ability for that? >>You know, you guys have been great supporters of DACA and the community and open source and software developers as they transform and become quite frankly the superheroes for the transformation, which is re factoring businesses. So this has been a big thing. I'd love to get your thoughts on how this is all coming together inside Microsoft, you've got your division, you get the developer division, you got GIT hub, got Azure. Um, and then just historically, and he put this up last year army of an ecosystem. People who have been contributing encoding with Microsoft and the partners for many, many decades. >>Yes. The >>heart Microsoft now, how's it all working? What's the news? I get Lincoln, Lincoln, but there's no yet developer model there yet, but probably is soon. >>Um Yeah, I mean, I think that's a pretty broad question, but in some ways I think it's interesting to put it in the context of Microsoft's history. You know, I think when I think back to the beginning of my career, it was kind of a one stack shop, you know, we was all about dot net and you know, of course we want to dot net to be the best developer environment that it can possibly be. We still actually want that. We still want that need to be the most productive developer environment. It could we could possibly build. Um but at the same time, I think we have to recognize that not all developers or dot net developers and we want to make sure that Azure is the most productive cloud for developers and so to do that, we have to make sure that we're building fantastic tools and platforms to host java applications, javascript applications, no Js applications, python applications, all of those things, you know, all of these developers in the world, we want to make sure it can be productive on our tools and our platforms and so, you know, I think that's really kind of the key of you know what you're speaking of because you know, when I think about the partnership that I have with the GIT hub team or with the Azure team or with the Azure Machine learning team or the Lincoln team, um A lot of it actually comes down to helping empower developers, improving their productivity, helping them find new developers to collaborate with, um making sure that they can do that securely and confidently and they can basically respond to their customers as quickly as they possibly can. Um and when, when we think about partnering inside of Microsoft with folks like linkedin or office as an example, a lot of our partnership with them actually comes down to improving their colleagues efficiency. We build the developer tools that office and lengthen are built on top of and so every once in a while we will make an improvement that has, you know, 5% here, 3% there and it turns into an incredible amount of impact in terms of operations, costs for running these services. >>It's interesting. You mentioned earlier, I think there's a time now we're living in a time where you don't have to be dogmatic anymore, you can pick what you like and go with it. Also that you also mentioned just now this idea of distributed applications, distributed computing. You know, distributed applications and microservices go really well together. Especially with doctor. >>Can you share >>your thoughts on the framework that you guys released called Dapper? >>Yeah, yeah. We recently released Dapper. It's called D A P R. You can look it up on GIT hub and it's a programming model for common microservices pattern, two common microservices patterns that make it really easy and automatic to create those kinds of microservices. So you can choose to work with your favorite state stores or databases or pub sub components and get things like cloud events for free. You can choose either http or g R B C so that you can get mesh capabilities like service discovery and re tries and you can bring your own secret store and easily be able to call it from any environment variable. It's also like I was talking about earlier, multi lingual. Um so you don't need to embrace dot net, for example, as you're programming language to be able to benefit from Dapper, it actually supports many programming languages and Dapper itself is actually written and go. Um and so, you know, all developers can benefit from something like Dapper to make it easier to create microservices applications. >>I mean, always great to have you on great update. Take a minute to give an update on what's going on with your division. I know you had to build conference this week. V. S has got the new preview title. We just talked about what are the things you want to get to plug in for? Take a minute to get to plug in for what you're working on, your goals, your objectives hiring, give us the update. >>Yeah, sure. I mean, you know, we we built integrated container tools in visual studio uh and the Doctor extension and Visual Studio code and cli extensions. Uh and you know, even in this most recent release of our Visual Studio product, Visual Studio 16 10, we added some features to make it easier to use DR composed better. So one of the examples of this is that you can actually have uh Oftentimes you need to be able to use multiple doctor composed files together so that you can actually configure various different container environments for a single single application. But it's hard sometimes to create the right Yeah. My file so that you can actually invoke it and invoke the the container and the micro services that you need. And so what this allows you to do is to actually have just a menu of the different doctor composed files so that you can select the runtime and test environment that you need for the subset of the portion of the application that you're working on at the end of the day. This is always about developer productivity. You know, like I said, every keystroke matters. Um and we want to make sure that you as a developer can focus on the code that only you can Right. >>Amanda Silver, corporate vice president product development division of Microsoft. Always great to see you and chat with you remotely soon. We'll be back in in real life with real events soon as we come out of the pandemic and thanks for sharing your insight and congratulations on your success this year and and congratulations on your announcement here at Dakar Gone. >>Thank you so much for having me. >>Okay Cube coverage for Dunkirk on 2021. I'm John for your host of the Cube. Thanks for watching. Mhm

>>Mhm. Yes. Hello. Welcome back to the cubes coverage of dr khan 2021 virtual. I'm john for your host of the cube. We're messing my fair principal technologist at AWS amazon Web services messman. Thank you for coming on the cube, appreciate it. Um >>Thank you. Thank you for having me. >>Great to see you love this amazon integration with doctor want to get into that in a second. Um Been great to see the amazon cloud native integration working well. E. C. S very popular. Every interview I've done at reinvent uh every year it gets better and better more adoption every year. Um Tell us what's going on with amazon E. C. S because you have Pcs anywhere and now that's being available. >>Yeah that's fine, that's correct, join and uh yeah so customers has been appreciating the value and the simplicity of VCS for many years now. I mean we we launched GCS back in 2014 and we have seen great adoption of the product and customers has always been appreciating. Uh the fact that it was easy to operate and easy to use. Uh This is a journey with the CS anywhere that started a few years ago actually. And we started this journey uh listening to customers that had particular requirements. Um I'd like to talk about, you know, the the law of the land and the law um uh of the physic where customers wanted to go all in into uh into the cloud, but they did have this exception that they need to uh deal with with the application that could not move to the cloud. So as I said, this journey started three years ago when we launched outpost. Um and outpost is our managed infrastructure that customers can deploy in their own data centers. And we supported Pcs on day one on outpost. Um having that said, there are lots of customers that came to us and said we love outputs but there are certain applications and certain requirements, uh such as compliance or the fact simply that we have like assets that we need to reuse in our data center uh that we want to use and before we move into into the cloud. So they were asking us, we love the simplicity of Vcs but we have to use gears that we have in our data center. That is when we started thinking about Pcs anywhere. So basically the idea of VCS anywhere is that you can use e c s E C as part of that, you know, and love um uh appreciated the simplicity of using Pcs but using your customer managed infrastructure as the data plane, basically what you could do is you can define your application within the Ec. S country plane and deploy those applications on customer own um infrastructure. What that means from a very practical perspective is that you can deploy this application on your managed infrastructure ranging from uh raspberry pis this is the demo that we show the invent when we pronounce um e c s anywhere all the way up to bare metal server, we don't really care about the infrastructure underneath. As long as it supported, the OS is supported. Um we're fine with that. >>Okay, so let's take this to the next level and actually the big theme at dr Connors developer experience, you know, that's kind of want to talk about that and obviously developer productivity and innovation have to go hand in hand. You don't want to stunt the innovation equation, which is cloud, native and scale. Right. So how does the developer experience improve with amazon ECs and anywhere now that I'm on, on premises or in the cloud? Can you take me through? What's the improvements around pcs and the developer? >>Yeah I would argue that the the what you see as anywhere solved is more for operational aspect and the requirements that more that are more akin to the operation team that that they need to meet. Uh We're working very hard to um to improve the developing experience on top of the CS beyond what we're doing with the CS anywhere. So um I'd like to step back a little bit and maybe tell a little bit of a story of why we're working on those things. So um the customer as I said before, continue to appreciate the simplicity and the easier views of E. C. S. However what we learn um over the years is that as we added more features to E. C. S, we ended up uh leveraging more easy. Um AWS services um example uh would be a load balancer integration or secret manager or Fc. Or um other things like service discovery that uses underneath other AWS products like um clubman for around 53. And what happened is that the end user experience, the developer experience became a little bit more complicated because now customers opportunity easy of use of these fully managed services. However they were responsible for time and watering all uh together in the application definition. So what we're working on to simplify this experience is we're working on tools that kind of abstract these um this verbal city that you get with pcs. Um uh An example is a confirmation template that a developer we need to use uh to deploy an application leveraging all of these features. Could then could end up being uh many hundreds of transformation lines um in the in the in the definition of the service. So we're working on new tools and new capabilities to make this experience better. Uh Some of them are C d k uh the copilot cli, dws, copilot cli those are all instruments and technologies and tools that we're building to abstract that um uh verbosity that I was alluding to and this is where actually also the doctor composed integration with the CS falls in. >>Yeah, I'm just gonna ask you that the doctor piece because actually it's dr khan all the developers love containers, they love what they do. Um This is a native, you know, mindset of shifting left with security. How is the relationship with the Docker container ecosystem going with you guys? Can you take him in to explain for the folks here watching this event and participating in the community, explain the relationship with Docker container specifically. >>Yeah, absolutely. Uh so basically we started working with dR many, many years ago, um uh Pcs was based on on DR technology when we launch it. Uh and it's still using uh DR technology and last year we started to collaborate with dR more closely um when DR releases the doctor composed specification um as an open source projects. So basically doctor is trying to use the doctor composed specification to create uh infrastructure product gnostic, uh way to deploy Docker application um uh using those specification in multiple infrastructure as part of these journey, we work with dr to support pcs as a back end um for um for the specification, basically what this means from a very practical perspective, is that you can take a doctor composed an existing doctor composed file. Um and doctor says that there are 650,000 doctor composed files spread across the top and all um uh lose control uh system um over the world. And basically you can take those doctor composed file and uh composed up and deploy transparently um into E. C. S Target on AWS. So basically if we go back to what I was alluding to before, the fact that the developer would need to author many 100 line of confirmation template to be able to take their application and deploy it into the cloud. What they need to do now is um offering a new file, a um a file uh with a very clear and easy to use dr composed syntax composed up and deploy automatically on AWS. Um and using Pcs Fargate um and many other AWS services in the back end. >>And what's the expectation in your mind as you guys look at the container service to anywhere model the on premise and without post, what does he what's the vision? Because that's again, another question mark for me, it's like, okay, I get it totally makes sense. Um, but containers are showing the mainstream enterprises, not the hyper skills. You guys always been kind of the forward thinkers, but you know, main street enterprise, I call it. They're picking up adoption of containers in a massive way. They're looking at cloud native specifically as the place for modern application development period. That's happening. What's the story? Say it again? Because I want to make sure I get this right e C s anywhere if I want to get on premises hybrid, What's it mean for me? >>Uh, this goes back to what I was saying at the beginning. So there are there are there when we have been discussing here are mostly to or token of things. Right. So the fact that we enable these big enterprises to meet their requirements and meet their um their um checkboxes sometimes to be able to deploy outside of AWS when there is a need to do that. This could be for edge use cases or for um using years that exist in the data center. So this is where e c s anywhere is basically trying, this is what uh pcs anywhere is trying to address. There is another orthogonal discussion which is developer experience, uh and that development experience is being addressed by these additional tools. Um what I like to say is that uh the confirmation is becoming a little bit like assembler in a sense, right? It's becoming very low level, super powerful, but very low level and we want to abstract and bring the experience to the next level and make it simple for developers to leverage the simplicity of some of these tools including Docker compose um and and and being able to deploy into the cloud um and getting all the benefits of the cloud scalability, electricity and security. >>I love the assembler analogy because you think about it. A lot of the innovation has been kind of like low level foundational and if you start to see all the open source activity and the customers, the tooling does matter. And I think that's where the ease of use comes in. So the simplicity totally makes sense. Um can you give an example of some simplicity piece? Because I think, you know, you guys, you know, look at looking at ec. S as the cornerstone for simplicity. I get that. Can you give an example to walk us through a day in the life of of an example >>uh in an example of simplicity? Yeah, supposedly in action. Yeah. Well, one of the examples that I usually do and there is this uh, notion of being served less and I think that there is a little bit of a, of an obsession around surveillance and trying to talk about surveillance for so many things. When I talk about the C. S, I like to use another moniker that is version less. So to me, simplicity also means that I do not have to um update my service. Right? So the way E C. S works is that engineering in the service team keeps producing and keeps delivering new features for PCS overnight for customers to wake up in the morning and consuming those features without having to deal with upgrades and updates. I think that this is a very key, um, very key example of simplicity when it comes to e C s that is very hard to find um in other, um, solutions whether there are on prime or in the cloud. >>That's a great example in one of the big complaints I hear just anecdotally around the industry is, you know, the speed of the minds of business, want the apps to move faster and the iteration with some craft obviously with security and making sure things buttoned up, but things get pulled back. It's almost slowed down because the speed of the innovation is happening faster than the compliance of some sort of old governance model or code reviews. I want to approve everything. So there's a balance between making sure what's approved, whether security or some pipeline procedures and what not. >>So that I could have. I cannot agree more with you. Yeah, no, it's absolutely true because I think that we see these very interesting um, uh, economy, I would say between startups moving super fast and enterprises try to move fast but forced to move at their own speed. So when we when we deliver services based on, for example, open source software uh, that customers need to um, look after in terms of upgrade to latest release. What we usually see is start up asking us can you move faster? There is a new version of that software, can you enable us to deploy that version? And then on the other hand of the spectrum, there are these big enterprises trying to move faster but not so much that are asking us can use lower. Can you slow down a little bit? Right, because I cannot keep that pigs. So it's a very it's a very interesting um, um, a very interesting time to be alive. >>You know, one of the, one of the things that pop up into these conversations when you talk, when I talk to VP of engineering of companies and then enterprises that the operational efficiency, you got developer productivity and you've got innovation right, you've got the three kind of things going on there knobs and they all have to turn up. People want more efficiency of the operations, they want more developed productivity and more innovation. What's interesting is you start seeing, okay, it's not that easy. There's also a team formation and I know Andy Jassy kinda referred to this in his keynote at Reinvent last year around thinking differently around your organizational but you know, that could be applied to technologists too. So I'd love to get your thoughts while you're here. I know you blog about this and you tweet about this but this is kind of like okay if these things are all going to be knobs, we turned up innovation efficiency, operationally and develop productivity. What's the makeup of the team? Because some are saying, you have an SRE embedded, you've got the platform engineering, you've got version lists, you got survival is all these things are going on all goodness. But does that mean that the teams have to change? What's your thoughts on that you want to get your perspective? >>Yeah, no, absolutely. I think that there was a joke going around that um as soon as you see a job like VP of devoPS, I mean that is not going to work, right? Because these things are needs to be like embedded into each team, right? There shouldn't be a DEVOPS team or anything, it would be just a way of working. And I totally agree with you that these knobs needs to go insane, right? And you cannot just push too hard on innovation which are not having um other folks um to uh to be able to, you know, keep that pace um with you. And we're trying to health customers with multiple uh tools and services to try to um have not only developers and making developer experience uh better but also helping people that are building these underneath platforms. Like for example, prod on AWS protein is a good example of this, where we're focusing on helping these um teams that are trying to build platforms because they are not looking themselves as being a giant or very fast. But they're they're they're measured on being secure, being compliant and being, you know, within a guardrail uh that an enterprise um regulated enterprise needs to have. So we need to have all of these people um both organizationally as well as with providing tools and technologies that have them in their specific areas um to succeed. >>Yeah. And what's interesting about all this is that you know I think we're also having conversations and and again you're starting to see things more clearly here at dr khan we saw some things that coop con which the joke there was not joke but the observation was it's less about kubernetes which is now becoming boring, lee reliable to more about cloud native applications under the covers with program ability. So as all this is going on there truly is a flip of the script. You can actually re engineer and re factor everything, not just re platform your applications in I. T. At once. Right now there's a window whether it's security or whatever. Now that the containers and and the doctor ecosystem and the container ecosystem and the The kubernetes, you've got KS and you got six far gay and all the stuff of goodness. Companies can actually do this right now. They can actually change everything. This is a unique time. This window might close are certainly changed if you're not on it now, it's the same argument of the folks who got caught in the pandemic and weren't in the cloud got flat footed. So you're seeing that example of if you weren't in the cloud up during the pandemic before the pandemic, you were probably losing during the pandemic, the ones that one where the already guys are in the cloud. Now the same thing is true with cloud native. You're not getting into it now, you're probably gonna be on the wrong side of history. What's your reaction to that? >>Yeah, No, I I I agree totally. I I like to think about this. I usually uh talk about this if I can stay back step back a little bit and I think that in this industry and I have gray areas and I have seen lots of things, I think that there has been too big Democratisation event in 90 that happened and occurred in the last 30 years. So the first one was from, you know from when um the PC technology has been introduced, distributed computing from the mainframe area and that was the first Democratisation step. Right? So everyone had access to um uh computers so they could do things if you if you fast forward to these days. Um uh what happened is that on top of that computer, whatever that became a server or whatever, there is a state a very complex stack of technologies uh that allow you to deployment and develop and deploy your application. Right. But that stack of technology and the complexity of that stack of technology is daunting in some way. Right? So it is in a bit access and democratic access to technology. So to me this is what cloud enabled, Right? So the next step of democratisation was the introduction of services that allow you to bypass that stack, which we call undifferentiated heavy lifting because you know, um you don't get paid for managing, I don't know any M. R. Server or whatever, you get paid for extracting values through application logic from that big stack. So I totally agree with you that we're in a unique position to enable everyone um with what we're building uh to innovate a lot faster and in a more secure way. >>Yeah. And what comes out, I totally agree. And I think that's a great historical view and I think let's bring this down to the present today and then bring this as the as the bridge to the future. If you're a developer you could. And by the way, no matter whether you're programming infrastructure or just writing software or even just calling a PS and rolling your own, composing your services, it's programmable and it's just all accessible. So I think that that's going to change the again back to the three knobs, developer productivity or just people productivity, operational efficiency, which is scale and then innovation, which is the business logic where I think machine learning starts to come in, right? So if you can get the container thing going, you start tapping into that control plane. It's not so much just the data control plane. It's like a software control plane. >>Yeah, no, absolutely. The fact that you can, I mean as I said, I have great hair. So I've seen a lot of things and back in the days, I mean the, I mean the whole notion of being able to call an api and get 10 servers for example or today, 10 containers. It would be like, you know, almost a joke, right? So we spent a lot of time racking and um, and doing so much manual stuff that was so ever prone because we usually talk about velocity and agility, but we, we rarely talk about, you know, the difficulties and the problems that doing things manually introduced in the process, the way that you can get wrong. >>You know, you know, it reminds me of this industry and I was like finally get off my lawn in the old days. I walk to school with no shoes on in the snow. We had to build our own colonel and our own graphics libraries and then now they have all these tools. It's like, you're just an old, you know, coder, but joking aside, you know that experience, you're bringing up appointments for the younger generation who have never loaded a Linux operating system before or had done anything like that level. It's not so much old versus young, it's more of a systems thinking, he said distributed computing. If you look at all the action, it's essentially distributed computing with new software paradigm and it's a system architecture. It's not so much software engineering, software developer, you know, this that it's just basically all engineering at this point, all software. >>It is, it is very much indeed. It's uh, it's whole software, there is no other um, there is no other way to call it. It's um, I mean we go back to talk about, you know, infrastructure as code and everything is now uh corridor software in in in a way. It's, yeah. >>This is great to have you on. Congratulations. A CS anywhere being available. It's great stuff. Um, and great to see you and, and great to have this conversation. Um, amazon web services obviously, uh, the world has has gone super cloud. Uh, now you have distributed computing with edge iot exploding beautifully, which means a lot of new opportunities. So thanks for coming on. >>Thank you very much for having me. It was a pleasure. Okay, cube >>Coverage of Dr Khan 2021 virtual. This is the Cube. I'm John for your host. Thanks for watching.

>>mhm Yes, everyone, welcome back to the cubes coverage of dr khan 2021. I'm john for your host of the cube. Got a great segment here. One of the big supporters and open source amazon web services returning back second year. Dr khan virtual Deepak Singh, vice president of the compute services at AWS Deepak, Great to see you. Thanks for coming back on remotely again soon. We'll be in real life. Reinvent is going to be in person, we'll be there. Good to see you. >>Good to see you too, john it's always good to do these. I don't know how how often I've been at the cube now, but it's great every single time your >>legend and getting on there, a lot of important things to discuss your in one of the most important areas in the technology industry right now and that is at the confluence of cloud scale and modern development applications as they shift towards as Andy Jassy says, the new guard, right. It's been happening. You guys have been a big proponent of open source and enabling open source is a service creating business models for companies. But more importantly, you guys are powering, making it easier for folks to use software. And doctor has been a big relationship for you. Could you take a minute to first talk about the doctor, a W S relationship and your involvement and what you're doing? >>Yeah, actually it goes back a long way. Uh you know, Justin, we announced PCS had reinvented 2014 and PCS at that time was very much managed orchestration service on top of DACA at that time. I think it was the first really big one out there from a cloud provider. And since then, of course, the world has evolved quite a bit and relationship with DR has evolved a lot. The thing I'd like to talk to is something that we announced that Dr last year, I don't remember if I talked about it on the cube at that time. But last year we started working with DR on how can we go from doctor Run, which customers love or DR desktop, which customers love and make it easy for people to run containers on pcs and Fergie. Uh so most new customers running containers and AWS today start with this Yes and party or half of them and we wanted to make it very easy for them to start with where they are on the laptop which is often bucket to stop and have running services the native US. So we started working with DR and that that collaboration has been very successful. We want to keep you look forward to continuing to work on evolving that where you can use Docker compose doctor, desktop, doctor run the fuel that darker customers used and the labour grand production services on the end of your side, which is the part that we've got that on. So I think that's one area where we work really well together. Uh, the other area where I think the two companies continue to work well together. It's open source in general as some of, you know, AWS has a very strong commitment to contain a. D uh, EKS our community service is moving towards community. Forget it actually runs all on community today and uh, we collaborate dr Rhonda on the Ocr specification because, you know, the Oc I am expect is becoming the de facto packaging format idea. W S. This morning we launched yesterday, we launched a service called Opera. And the main expected input for opera is an Ocr image are being in this Atlanta as well, where those ci images now a way of packaging for lambda. And I think the last one I like to call out and it has been an amazing partnership and it's an area where most people don't pay attention is amid signing. Uh, there's a project called Notary. We do the second version of the Notary Spec for remit signing and AWS Docker and a couple of other companies have been working very closely together on bringing that uh, you know, finalizing no tv too, so that at least in our case we can start building services for our customers on top of that. You know, it's it's a great relationship and I expect to see it continue. >>Well, I think one of the themes this year is developer experience. So good. Good call out there in the new announcements on the tools you have and software because that seems to be a great developer integration with Docker question I have for you is how should the customers think about things like E C. S and versus E K. S. App, Runner lambda uh for kind of running their containers. How do they understand the difference is, what's there? What's the, what's the thought process there? What's >>that? It's a good question actually been announced after. And I think there was one of the questions I started getting on twitter. You know, let's start at the very beginning. Anyone can pick up a Docker container and run it on easy to today. You can run it on easy to, we can run a light sail, but doc around works just fine. It's the limits machine. Then people want to do more complex things. They want to run large scale orchestrated services. They won't run their entire business and containers. We have customers will do that today. Uh, you know, you have people like Vanguard who runs a significant portion of the infrastructure on pcs frg or you have to elope with the heavy user of chaos, our community service. So in general, if you're running large scale systems, you're building your platforms, you're most likely to use the csny Chaos. Um, if you come from a community's background, you're, you're running communities on prem or you want the flexibility and control the communities gives you, you're gonna end up with the chaos. That's what we see our customers doing. If you just want to run containers, you want to use AWS to its fullest extent where you want the continue a P I to be part of the W A S A P. I said then you pick is yes. And I think one of the reasons you see so many customers start with the CSN, Forget is with forget to get the significant ease of use from an operational standpoint. And we see many start ups and you know, enterprises, especially security focus enterprises leaning towards farming. But there's a class of customers that doesn't want to think about orchestration that just wants. Here's my code, here's my container image just run my service for me and that's when things like happen, I can come and that's one of the reasons we launched it. Land is a little bit different. Lambda is a unique service. You buy into an event driven architecture. If you do that, then you can figure our application into this. That's they should start its magic. Uh, the container part, there is what land announced agreement where they now support containers, packaging. So instead of zip files, you can package up your functions as containers. Then lambda will run them for you. The advantage it gives you with all the tooling that you built, that you have to build your containers now works the land as well. So I won't call and a container orchestration service in the same sense of the CSC cso Afrin are but it definitely allows the container image format as a standard packaging format. I think that's the sort of universal common theme that you find across AWS at this point of time. >>You know, one of the things that we're observing at this at this event here is a lot of developers Coop con and Lennox foundations. A lot of operators to kubernetes hits that. But here's developers. And the thing is I want to ease of use, simplicity experience, but also I want the innovation. Yeah, I want all of it. When I ask you what is amazon bring to the table for the new equation, what would you say? >>Yeah, I mean for me it's always you've probably heard me say this 100 times. Many 1000 times. It's foggy fog. It's unique to us. It takes a lot of what we have learned about operating infrastructure scale. The question we asked ourselves, you know, in many ways we talk about forget even before belong pcs but we have to learn on what it meant and what customers really wanted. But the idea was when you are running clusters of instances of machines to run containers on, you have to start thinking about a lot of things that in some ways VMS but BMS in the car were taken away capacity. What kind of infrastructure to run it on? Should have been touched. Should have not been back. You know, where is my container running? Those are things. They suddenly started having to think about those kind of backwards almost. So the idea was how can we make your containerized bundles? So TCS task or community is part of the thing that you talk to and that is the main unit that you operate on. That is the unit that you get built on and meet it on. That's where Forget comes in and it allows us to do many interesting things. We've effectively changed the engine of forget since we've launched it. Uh, we run it on ec two instances and we run it on fire cracker. Uh, we have changed the forget agent architecture. We've made a lot of underneath the hood, uh, changes that even take the take advantage of the broader innovation, the rate of us, We did a whole bunch more to launch acronym trans on top of family customers don't have to think about it. They don't have to worry about it. It happens underneath the hood. It's always your engine as as you go along and it takes away all the operational pain of managing clusters of running into picking which instances to use to getting out, trying to figure out how to bend back and get efficiency. That becomes our problem. So, you know, that is an area where you should expect to see a Stuart done more. It's becoming the fabric of so many things that eight of us now. Uh, it's, you know, in some ways we're just talking a lot more to do. >>Yeah. And it's a really good time. A lot more wave of developers coming in. One of the things that we've been reporting on on Silicon England cube with our cute videos is more developers keep on coming on, more people coming in and contributing to the open source community. Even end users, not just the normal awesome hyper scholars you're talking about like classic, I call main street enterprises. So two things I want to ask you on the customer side because you have kind of to customers, you have the community that open source community and you have enterprise customers that want to make it easier. What are you seeing and hearing from customers? I know you guys work backwards from the customer. So I got to ask you work backwards from the community and work backwards from the enterprise customer. What's going on in their environment? What's the key trends that they're riding? What's the big challenges? What's the big opportunities that they're facing and saying for the community? >>Yeah, I start with the enterprise. That's almost an easier answer. Which is, you know, we're seeing increasingly enterprises moving into the cloud wholesale. Like in some ways you could argue that the pandemic has just accelerated it, but we have started seeing that before. Uh they want to move to the cloud and adult modern best practices. Uh If you see my talk agreement last few years, I've talked about modernization and all the aspects of modernization, and that's 90% of our conversation with enterprises, I've walked into a meeting supposedly to talk about containers, whatever half a conversation is spent on. How does an organization modernize? What does an organization need to do to modernize and containers and serverless play a pretty important part in it, because it gives them an opportunity to step away from the shackles of sort of fixed infrastructure and the methods and approaches that built in. But equally, we are talking about C I C. D, you know, fully automated deployments. What does it mean for developers to run their own services? What are the child, how do you monitor and uh, instrument uh, your services? How do you do observe ability in the modern world? So those are the challenges that enterprises are going towards, and you're spending a ton of time helping them there. But many of them are still running infrastructure on premises. So, you know, we have outpost for them. Uh, you know, just last week, you're talking to a bunch of our customers and they have lots of interesting ideas and things that they want to do without both, but many of them also have their own infrastructure and that's where something like UCS anywhere came from, which is hey, you like using Pcs in the cloud, You like having the safety i that just orchestrates containers for you. It does it on on his in an AWS region. It will do it in an outpost. It'll do it on wavelength, it'll do it on local zone. How about we allow you to do it on whatever infrastructure you bring to us. Uh you want to bring a raspberry pi, you can do that. You want to bring your on premises data center infrastructure, we can do that or a point of sale device, as long as you can get the agent running and you can connect to an AWS region, even though it's okay to lose connectivity every now and then. We can orchestrate a container for you over there and, you know, the same customer that likes the ease of use of Vcs. And the simplicity really resonated with that message really resonates with them. So I think where we are today with the enterprise is we've got some really good solutions for you in eight of us and we are now allowing you to take those a. P. I. S and then launch containers wherever you want to run them, whether it's the edge or whether it's your own data center. I think that's a big part of where the enterprise is going. But by and large, I think yes, a lot of them are still making that change from running infrastructure and applications the way they used to do a modern sort of, if you want to use the word cloud native way and we're helping them a lot. We've done, the community is interesting. They want to be more participatory. Uh that's where things like co pilot comes from. God, honestly, the best thing we've ever done in my order is probably are open road maps where the community can go into the road map and engage with us over there, whether it's an open source project or just trying to tell us what the feature is and how they would like to see it. It's a great engagement and you know, it's not us a lot. It's helped us prioritize correctly and think about what we want to do next. So yeah, I think that's, that >>must be very hard to do for opening up the kimono on the road map because normally that's the crown jewels and its secretive and you know, and um, now it's all out in the open. I think that is a really interesting, um, experiment and what's your reaction to that? What's been the feedback on the road map peace? Because I mean, I definitely want to see, uh, >>we do it pretty much for every service in my organization and we've been doing it now for three years. So years forget, I think about three years and it's been great. Now we are very we are very upfront, which is security and availability. Our job 000 and you know, 100 times out of 100 at altitudes between a new feature and helping our customers be available and safe. We'll do that. And this is why we don't put dates in that we just tell you directionally where we are and what we are prioritizing Uh, there every now and then we'll put something in there that, you know, well not choose not to put a feature in there because we want to keep it secret until it launches. But for the most part, 99% of our own myself there and people engaged with it. And it's not proven to be a problem because you've also been very responsible with how we manage and be very transparent on whether we can commit to something or not. And I think that's not. >>I gotta ask you on as a leader uh threaded leader on this group. Open source is super important, as you know, and you continue to do it from under years. How are you investing in the future? What's your plan? Uh plans for your team, the industry actually very inclusive, Which is very cool. It's gonna resonate well, what's the plans? Give us some details on what you're investing in, what your priorities? What's your first principles? >>Yeah, So it goes in many ways, one when I I also have the luxury also on the amazon open source program office. So, you know, I get the chance to my team, rather not me help amazon engineers participate in open source. That that's the team that helps create the tools for them, makes it easy for them to contribute, creates, you know, manages all the licenses, etcetera. I'll give you a simple example, you know, in there, just think of the cr credential helper that was written by one of our engineers and he kind of distorted because he felt it was something that we needed to do. And we made it open source in general, in in many of our teams. The first question we asked is should something the open why is this thing not open source, especially if it's a utility or some piece of software that runs along with services. So they'll step one. But we've done some big things also, I, you know, a couple of years ago we launched Lennox operating system called bottle Rocket. And right from the beginning it was very clear to us that bottle Rocket was two things. It was both in AWS product. But first it was an open source project. We've already learned a little bit from what we've done at Firecracker. But making bottle rocket and open source operating system is very important. Anyone can take part of Rocket the open source to build tooling. You can run it whatever you want. If you want to take part of Rocket and build a version and manage it for another provider. For another provider wants to do it, go for it. There's nothing stopping you from doing that. So you'll see us do a lot there. Obviously there's multiple areas. You've seen WS investing on the open source side. But to me, the winds come from when engineers can participate in small things, released little helpers or get contributions from outside. I think that's where we're still, we can always have that. We're going to continue to strive to make it better and easier. And uh, you know, I said, I have, you know, me and my team, we have an opportunity to help their inside the company and we continue to do so. But that's what gets me excited. >>Yeah, that's great stuff. And congratulations on investing in the community, really enjoys it and I know it moves the needle for the industry. Deepak, I gotta ask you why I got you here. Dr khan obviously, developers, what's the most important story that they should be paying attention to as a developer because of what's going on shift left for security day two operations also known as a I ops getups, whatever you wanna call it, you know, ongoing, you get server lists, you got land. I mean, all kinds of great things are going on. You mentioned Fargate, >>um >>what should they be paying attention to that's going to really help their life, both innovation wise and just the quality of life. >>Yeah, I would say look at, you know, in the end it is very easy developers in particular, I want to build the buildings and it's very easy to get tempted to try and get learn everything about something. You have access to all the bells and whistles and knobs, but in reality, if you want to run things you want to, you want to focus on what's important, the business application, that and you the application. And I think a lot of what I'll tell developers and I think it's a lot of where the industry is going is we have built a really solid foundation, whether it's humanity, so you CSN forget or you know, continue industries out there. We have very solid foundation that, you know, our customers and develop a goal of the world can use to build upon. But increasingly, and you know, they are going to provide tools that sort of take that wrap them up and providing a nice package solution After another great example, our collaboration, the doctor around Dr desktop are a great example where we get all the mark focus on the application and build on top of that and you can get so much done. I think that's one trend. You'll see more and more. Those things are no longer toys, their production grade systems that you can build real world applications on, even though they're so easy to use. The second thing I would add to that is uh, get uh, it is, you know, you can give it whatever name you want. There's uh, there's nuances there, but I actually think get up is the way people should be running the infrastructure, my virus in my personal, you know, it's something that we believe a lot in homicide as hard as you go towards immutable infrastructure, infrastructure, automation, we can get off plays a significant role. I think developers naturally gravitate towards it. And if you want to live in a world where development and operations are tightly linked, I think it after the huge role to play in that it's actually a big part of how we're planning to do things like yes, anywhere, for example, a significant player and that it would be a proton. I think get up will be a significant in the future of proton as well. So I think that's the other trend. If you wanted to pick a trend that people should pay attention. That's what I believe in a lot. >>Well you're an expert. So I want to get you a quick definition. What is get Ops, how would you define it? Because that's a big trend. What does it, what does that mean? >>Electricity will probably shoot me for getting this wrong. I tell you how I think about it. Which is, you know, in many cases, um, you when you're doing deployments are pushing a deployment getups is more of a full deployment. When you are pushing code to get depository, you have a system that knows that the event has happened and then pulls from there and triggers the thing as opposed to you telling it take I have this new piece of code now go deployed everywhere. So to me, the biggest changes that Two parts one is it's more for full mechanism where you're pulling because something has changed. So it needs systems like container orchestrators to keep them, you know, to keep them in sync. And the second part of the natural natural evolution of infrastructure score, which is basically everything is called the figures code. Infrastructure as code, code is code and everything is getting stored in that software repo and the software repo becomes your store of record and drives everything. Uh So for a glass of customers, that's going to be a pretty big deal. >>Yeah, when you're checking in code, that's again, it's like a compiler for the compiler, a container for the container, you've got things for each other. Automation is ultimately what we're talking about here. And that's to me where machine learning kicks in. So again, having this open source foundational fabric, as you said, forget out the muck or the undifferentiated heavy lifting. This is what we're talking about automation, isn't it? Deepak? >>Yes. I mean I said uh one thing where we hang our hat on is there's such good stuff out there in the world which we like to contribute to, but the thing we like to hang our hat on is how do you run this? How do you do it this in ways that you can uniquely bring capabilities to customers where there's things like nitro or things are nitro open stuff. Well, the fact that we have built up this operational infrastructure over the last in a decade plus or in the container space over the last seven years where we really really know how to run these things at scale and have made all the investments to make it easy to do. So that's that's where we have hanger hard keeping people safe, helping them only available applications, their new startup, that just completely takes off in over the weekend. For whatever reason, because, you know, you're the next hot thing on twitter and our goal is to support you whether you are, you know, uh enterprise that's moving from the main train or you are the next hot startup, that's you know, growing virally and uh, you know, we've done a lot to build systems help both sides and yeah, it's >>interesting if you sing about open source where it's come from, I mean I remember that base wouldn't open source wasn't open, I would be peddling software, there's a free copy of Linux, UNIX um in college and now it's all free. But I mean just what's changed now. It used to be just free software, download software. You got it now, it's a service. Service now can be monetized quickly. And what you guys are offering with AWS and cloud scale is you've done all these things as I don't have to have a developer. I get the benefits of the scale, I can bring my open source code to the table, make it a service integrated in with other services and be the next snowflake, be the next, you know, a company that could scale. And that is that's the that's the innovation, right? That's the this is a new phenomenon. So it also changes the business model. >>Yeah, actually you're you're quite right. Actually, I I like one more thing to it. But you look at how a lot of enterprises use containers today. Most of them are using something like this year, Symphony or GS to build an internal developer platform and internal developer portal. And then the question then becomes this hard to scale this modern and development practices to an entire organization. What is your big bank that's been around as thousands and thousands of ID stuff That may not all be experts are running communities running container is when you scale it out different systems that proton come into play. That was actually the inspiration is how do you help an organization where they're building these developer Portholes and developer infrastructure, developer platforms, How do you make it easy for them to build it? Be almost use it as a way to get these modern practices into the hands of all the business units, where they may not have the time to become experts at the modern ways of running infrastructure because they're busy doing other things. And I think you'll see the a lot more happening that space that's not happening in the open source community. There's proton, there's a bunch of interesting things happening here and be interesting to see how that evolves. >>And also, you know, the communal, communal aspect of not just writing code together, but succeeding, right, building something. I mean, that's when you start to see the commercial meets open kind of ethos of communal activity of working together and sharing a big part of this year's. Dakar Con is sharing not just running and shipping code but sharing. >>Yeah, I mean if you think about it uh Dockers original value was you build run and shit right? You use the same code to build it, you use the same code to ship it, the same sort of infrastructure interface and then you run it and that, you know, the fact that the doctor images such a wonderfully shareable entity uh that can run every girl is such a powerful and it's called the Ci Image. Now I still call him Dr images because it's just easier. But that to me like that is a big deal and I think it's becoming and become an even bigger deal over the years. I came from something before, Amazon has to work in The sciences and bioinformatics and you know, the ability to share codeshare dependencies, package all of that up in a container image is a big deal. It's what got me one of the reasons I got fascinated with container 78 years ago. So it will be interesting to see where all of systems. >>It's great, great stuff. Great success. And congratulations. Deepak, Great to always talk to you got a great finger on the pulse. You lead a really important organizations at AWS and you know, doctor has such a huge success with developers, even though the company has gone through kind of a uh change over and a pivot to what they're doing now. They're back to their open source roots, but they have millions and millions of developers use Docker and new developers are coming in dot net developers are coming in. Windows developers are coming in and and so it's no longer about Lennox anymore. It's about just coding. >>Yeah. And it's it's part of this big trend towards infrastructure, automation and and you know development and deployment practices that I think everyone is going to adopt faster than we think they will. But you know, companies like Doctor and opens those projects that they involved are critical in making that a lot easier for them. And then you know, folks like us get to build on top of that orbit them and make it even easier. >>Well, great testimony the doctor that you guys based your E C. S on Docker Doctor has a critical role in developing community. I run composed in their hub with dr desktop and we'll be watching amazon and and the community activity and see what kind of experiences you guys can bring to the table and continue that momentum. Thank you Deepak for coming on the >>cube. Thank you, john. That's always a pleasure. >>Okay. Mr cubes. Dr khan 2021 virtual coverage. I'm john for your host of the cube. Thanks for watching.

>>Welcome back to the doctor khan cube conversation. Dr khan 2021 virtual. I'm john for your host of the cube of mulch, Donny co founder and CTO and see so for accurate hot startup hot company. Uh, thanks for coming on the cube for dr continent and talking cybersecurity and cloud native. Super important. Thanks for coming on, >>appreciate john. Thanks for having me. >>So here dr khan. Obviously the conversations around developer experience, um, making things more productive. Obviously cloud scale cloud native with docker containers with kubernetes all lining up right in line with the trend that's now going mainstream and all commercial enterprises. I mean developer productivity security is a huge times thing if you don't get it right. So, you know, shifting left is that everyone's talking about, but this is a huge challenge. Can you, can you talk about what you guys do at your company and specifically why it relates to this conversation for developers at dr khan. >>Sure. Um, so john as we understand today, there are millions of uh, you know, code comments that are happening in cloud native environments on daily basis. Um, you know, in a recent report, Airbnb reported, they've checked in 125,000 plus times ham charts in an ear. And what that means is that, you know, the guitars revolution is here. Uh, and that also means that, well, you got your kubernetes clusters sinking up with infrastructure as code, such as ham chart customized and yarrow files right almost several times a day now, what that also means is that the opportunity to make sure that your clusters are being deployed securely by these infrastructure as code templates and deployment has called template is available before the deployment happens and not after the deployment. Also, in order to reduce the cost or detecting security challenges. The best option and opportunity is during the development time and during the deployment time, which is the pipeline time and that's what we offer. We shift your cloud, native security posture detection to left. We detect all your security posture related issues while the code is in development in the design phase as well as while it is about to get deployed, that is within the guitars pipelines or your traditional develops pipelines and not only with detect where we sell feel the code as well, specifically infrastructure as code. So we detect the problems and we fix the problem by generating the remediation code which we like to call it as remediation is called. The detection mechanisms like all this policy is called. That's the primary use case that we offer. We help developers reduce the cost of remediation and also meantime to the mediations for security problems >>and actually see them a boatload of hassle to going back and figure out how they wrote the code at that time. And kind of what happened always is a problem. Um, I gotta Okay, so I'm gonna get into this policy is code. You mentioned that also you mentioned Getafe's revolution. Let's get to that in a second. But first I want you to explain to the folks what is cloud native security and what does that mean? And what kind of attacks emerge as that surface area becomes apparent? >>Absolutely. So cloud native security is a very interesting new paradigm. Uh it's not just related with one single control pain like take, for example, Cuban haters, it's not just that, it's also the supply chain elements that go into the deployment of your cloud native clusters. Like see if kubernetes cluster you need to secure not just the application code which is running inside your container images, but also the container image itself, then the pod, then the name space, then the cluster. And also you need to do all the other cyber hygienic, high generated things that we were doing previously. So it's so much of complexity because availability of different control planes, you need to be able to make sure that you are doing security, not just right, but at a very, very cost effective in a very, very cost effective manner. And the kind of attacks that we are predicting we're going to see in cloud native world are going to be very different from what we have seen so far. Especially there's a new attack type that I am have coined. I call that as cloud native waterhole attack. What it means is that imagine that most of the cloud native infrastructures are developed out of a lot of different open source components and pieces. So imagine you're pulling up a container image from a open source container agency and that continued which contains a man there container image can directly land into your cluster and not only can enter into your so called secure cluster environment. Usually the cluster control planes are not exposed to internet but deployment of one supply chain element like a Mallory's container image and exposed to an entire cluster. And that's what is waterhole attack when it comes to chlorinated water hole attacks to supply chains. So these are some very innovative and noble attacks that you know, we Uh you know, predict are going to come to our weigh in next 12-18 months. >>So you say it's a waterhole attack. That's the that's the coin term that you've made. So basically what you're saying is the container could be infected with all the properties that is containing into a secure cluster. It's almost been penetrated like malware would or spear phishing attack, it targets the cluster and then infects it. >>So not only that because your continuing images that you're pulling in um from your registries registries can be located anywhere right? If you do not do proper sanitization and checking off your supply chain components such as a continuing image, it can land insecure zones like this. So not only in a cluster, it can become part of a system named space very soon and and that's where the risks are that, you know, you had a parameter, you know, at least of some sort when it was non cloud native environments. And now you have a kind of false sense of security that I have equivalent is cluster, which sort of air gap in one way like there's no exposure to internet of the control plane control being a P. I. Is not supposed to Internet, that doesn't mean anything. A container enters into your cluster can take over the entire cluster. >>All right, so that's cool. So I love that attacks kind of attack. So back to cloud native security definition. So you're defining cloud native security as cloud native clusters. Is it specific around kubernetes or what specifically the cloud native security? What's the category? If the if water holds the attack vector, what's cloud native security means? >>So what it means is that you need to worry about multiple different control planes in a cloud native environment. It's not just a single control pain that you have to worry about. You have to worry about your uh as I said, kubernetes control plane, you have service measures on top of it, You could have server less layers on top of it and when you have to worry about so many different control pains, but it also means is that the security needs to become part of and has to get baked into the entire process of building cloud native environment, not afterthought or it shouldn't happen after the fact. >>See the containers for containers that watch the containers security for the security to watch the security. So you get so let's get we'll get to that. I want to get back to the solution, but one more thing. Um this one piece. So your c so um there you have a lot of shops in there from your background, I know that. Um So if if people out there, other Csos are looking at expanding, You know, day one day 2 ongoing, you know, ai ops get upstate to operate what everyone call it cloud native environments. How do they consider figuring out how to deploy and understand cloud need to secure? What do they have to do if you're a c So knowing what, you know, what steps are you taking? >>Yeah, it's funny that, you know, there's a big silo today between the sea, so organizations and the devops and get ops teams. Uh so the number one priority, in my opinion, that the sea so s uh you know, have to really follow is having visibility into the uh developers. So developers who are developing not just code but also infrastructure as code. So there is a slight difference between writing python code versus writing uh say ham charts or customized templates. Right? So you need as a see saw, you know, see so our needs to have full visibility into Okay, out of 100 developers, how many do I have who are writing deployment as code? And then how many of them are continuously checking in code and introducing security issues? Those issues have to be visualized while the issues are written in code and as they are getting checked into the repositories, so catch the security issues while the code is getting checked into the repository. And the next best stages catch the issues while the pipelines are picking up the code from the repository. So sisters needs to have visibility into this. I call it as shift left visibility for CSOS. So sisters need to know, okay, what are my top 10 developers who are writing infrastructure as code? How many of those developers are committing wonderful code. How many of these pull requests which have been raised have got security violations? How many of them have been fixed and how many have not been fixed? That's what is the visibility that can uh you know, provide opportunities to seize organizations to >>react and more things to put KPI S around two to understand where the gaps are and where the potential blind spots are. Okay, shift left visibility to see. So if you've got the get ups revolution, you got the waterhole attacks. You have multiple control planes obviously complex. The benefits of cloud native though are significant and people doing modern applications are seeing that. So clearly this is direction that everyone's going. The consensus is clear. So how do you solve this? You mentioned policy as code. I'm kind of connecting the dots here. If I'm going to understand what's going on in real time as the code is in flight as it's checking in. For instance, this is kind of in the pipeline as you say. So this has to be solved. What is the answer to this? Because it's clearly the way people want it. No one wants to come back and say we got hacked or development being pulled off task to figure out what they fixed or didn't do what's the policy is code angle? >>So um you know, of course, you know, there could be more than one ways to solve this problem. The way we are solving this problem is that first thing we are bringing all top type of infrastructure as code and the control planes into a single uniform format, which we like to call it as cloud, as code. The reason why we do that so that we can normalize the representation of these different data sets in one single normalized format. And then we apply open policy agent which is a C N C F uh graduated project, which is kind of the de facto standard to do any kind of policy is called use cases in the cloud native world today. So we apply open policy agent to this middleware that we create, which basically brings all these different control plane data, all the different infrastructures code into anomalous format. We apply O P A and we use policies to apply uh Opie on this data this way. What happens is that we write, for example, we want to write a policy, you don't want certain parts to be exposed to Internet in a given name space. You can write such a policy. This policy, you can run on life cluster as well as on the hand charts, which is your development side of the artifact. Right. Because we're bringing both these datasets into middleware. So in short, one of the solutions that we are proposing is that different control planes, different infrastructures, code has to be brought into a normalized format. And then you apply frameworks like Opie a open policy agent to achieve your policy is called use cases. >>What is the attraction for this direction? O. P. A. In particular obviously controlled planes. I get that. I can see the benefit of having this abstraction away with the normalization. I think that would enable a lot of innovation on top of it. Um Makes a lot of sense, totally cool. What's the attraction? What's the vibe? Are people reacting to this? Uh Some people might say whoa hold on, you're taking on too much uh your eyes are bigger than your stomach. You're taking on too much territory. Whoa, slow down. I can I I want to own that control plane. There's a lot of people trying to own the control plane. So again it's a little bit of politics here. What's your what's your thoughts on the momentum? What's the support, what's it look like? >>Yeah, I think you are getting it right, the political side of things. So, um, you know, one responses that, look, we have launched our open source project contour a scan uh last year and uh you know, we're doing pretty well. It's a full opium based uh in a project which allows you to do policies code on not only new cloud control planes, like, you know, kubernetes and others, but also the traditional control planes provided by CSP s like cloud security, cloud service providers. So parents can can be used not just for hand charts and customized, but also for terra form. What we are uh promoting is open culture. With scan. We want community to contribute, become part of it. Um yes, we are promoting a middleware here uh but we want to do it with the help of the community and our reaction what we're getting is very very good. We are in our commercial offering also we use opa we have good adoption going on right now. We believe will be able to uh you know with the developer community, you have this thing going for us. >>I love cloud as code. It's so much more broader than infrastructure as code and I'll see the control plane benefits. You know when I talk to customers, I want to get your reaction to this because I really appreciate your experience and and leadership here. I talked to customers all the time and I wont say name, I won't name names but they're big, big and fintech and you'll big and life sciences in other areas. They all say we want to bring best to breed together but it's too hard to make it all work. We can get it done, but it's a lot of energy. So obviously building code and getting into production that is just brute force. Anyway, they got to get that done and they're working on their pipe lining. But getting other best of breed stuff together and making it work is really hard. Does this solve that? Do you, are you helping solve that problem? Is this an integration opportunity? >>Yes, that and that is true and we have realized it, you know, uh long back. So that's why we do not introduce any new tooling into the existing developer workflows, no new tool whatsoever. We integrate with all existing developer workflows. So if you are a, you know, modern uh, you know, get off shop and you're using flux or Argo, we integrate terrace can seamlessly integrated flux in Argo, you don't even get to know that you already have what policy is called enabled if you're using flux Argo or any equivalent, you know, getups, toolkit. Likewise, if you are using any kind of uh, you know, say existing developer pipeline or workflows such as, you know, the pipelines available on guitar, get lab, you know, get bucket and other pipelines. We seamlessly integrate our motor is very, very simple. We don't want to introduce one more two for developers, we want to introduce one more per security. We want to get good old days, >>no one wants another tool in the tool shed. I mean it's like, it's like really like the tool shit, they get all these tools laying around. But everyone again, this is back to the platform wars in the old days when I was younger. Breaking into the early days of the web platforms were everything you have to build your own proprietary platform Wasn't some open source being used, but mostly it was full stack. Now platforms are inter operating with hybrid and now Edge. So I want to get your thoughts on and I'm just really a little bit off topic. But it's kind of related. How should companies think about platform engineering? Because you now have the cloud scale, which in a way is half a stack. You don't really if you're gonna have horizontal scalability and you're gonna have these kind of unified control planes and infrastructure as code. Then in a way you don't really need that full stack developer. I mean I could program the network. I don't need to get into the weeds on that. I got now open policy agent on with terrorists. Can I really can focus on developing this is kind of like an OS concept. So how should companies think about platforms and hiring platform engineers and and something that will scale and have automation and all the benefits and goodness of the cloud scale. >>Yeah, I mean you actually nailed it when you began uh we've been experienced since we've been experiencing now since last at least 18 months that and if I were specifically also, I'll touch based on the security side of things as well. But platform engineering and platforms, especially now everything is about interoperability and uh, what we have started experiencing is that it has to be open. The credibility any platform can gain is only through openness interoperability and also neutrality. If these three elements are missing, it's very hard to push and capture the mind share of the users to adopt the platform. And why do you want to build a platform to actually attract partners who can build integrations and also to build apps on top of it or plug ins on top of it? And that can only be encouraged if there is, you know, totally openness, key components have to be open source, especially in security. I can give you several examples. The future of security is absolutely open source, the credibility cannot be gained without that. A quick example of that is cystic. I mean, who thought they were gonna be pulling such a huge, you know, funding round, of course that all is on the background of Falco, Right? So what I'm trying to play and sing and same for psyllium, Right? So what I'm clearly able to see is the science are that especially in cybersecurity community, you are delivering open source based platforms, you will have the credibility because that's where you will get the mindshare developers will come and you know, and work with you of course, you know, I have no shame naming fellow vendors right, who are doing this right and this is the right way to do it. >>Yeah. And I think it's it's totally true and you see the validation on that just to verify your point out that we have a little love fest here on open source, it's pretty obvious the the end user communities are controlled not the hard core and users like the hyper scholars, you know, classic enterprises are are starting not only contribute participate but add value more than they've ever have. The question I want to ask you is okay. I totally agree on open as data becomes super important because remember data is only as good as what you have and the more data the better the machine learning the better the data scale, um, sharing is important. So open sharing kind of ties into open source. What's your thoughts on data? Data policy, is this going to extend out into data control planes? What's your thoughts there? I'd love to get your input. >>We are a little little bit early in that thought. I think it's gonna take a little while uh for you know, the uh for the industry bosses to come to terms to that uh data lakes and uh you know, data control planes eventually will open up. But you know, I I see there is resistance in that space today uh but eventually it's gonna come around. You know, that has because that would be the next level of openness, you know, once the platforms uh in a mature as an example right today. Um you want to write uh you know, any kind of say policies for your same products, right. Uh you have the option available to write policies and customized, you know, languages. But then many platforms are coming up which are supporting policy is developed in in languages which are open and that's data which is going to open up, you know very soon. So you will not be measured in terms of how many policies you have as a product, but you will be measured. Can you consume? Open policies are not so i that it is going to go there, it's going to take a little while, but I think he is going to move that. >>It makes sense. Get the apparatus built on the infrastructure side. Once you have some open policy capability that's going to build an abstraction on top of it, then you can program data to be more policy driven or dynamic based upon contextual behavioural dynamics. So it makes a lot of sense. Oh, great insight here, love the conversation, Congratulations on your success. Love the vision. Love the openness. I'll see. We think uh data as code is big too. Obviously media's data where CUBA is open. We have we have the same philosophy. So thanks for sharing. Love the vision. Take a minute to plug the company. What are you guys looking to do? Uh you guys hiring, take a minute to put the plug out for the for the company? >>Absolutely. We are absolutely hiring great ingenious, you know, a great startup mind folks who want to come and work for a very, very innovative environment. Uh we are very research and development, you know driven and have brought various positions available today. Um we are trying to do something which has not been attempted before. Our focus is 100% on reducing the cost of security. And uh you know, in order to do that, you really have to do things that previously were not in development environments. And that's where we're going. We're open source uh, you know, open source initiatives, big open source lovers and we welcome people come in and apply our positions, >>reduce the cost of security, do the heavy lifting for the customer with code and have great performance, that's the ultimate goal. Great stuff. Cloud need security, threat modeling, deV stickups, shifting left in real time. You guys got a lot of hard problems you're attacking? >>Um well, you know, some of the good things uh that we're doing is also because of the team that we have right. Most of our co team comes from very heavy threat modeling, threat analysis and third intelligence background. So we have we're blending a very unique perspective of allowing developers to tackle the threats, which they're not supposed to even understand how they work. We do the heavy lifting from threat intelligence point of view, we just let the developers work on the code that we generate for them to fix those threats. So we're shipping threat intelligence and threat modeling also to left. Uh we're one of the first companies to create threat models just out of infrastructure is called, we read your infrastructure as code and we create a digital twin of your cloud late at one time, even before it has been actually built. So we do some of those things which we like to call it just advanced bridge card prediction where we can predict whether you have reach parts a lot in your runtime environment that would have been committed. >>And then the Holy Grail obviously the automation and self healing um is really kind of where you've got to get to. Right, that's the whole that's the whole ballgame, right? They're making that productive. Oh, thank you for coming on a cube here. Dr khan 2021 sharing your insights, co founder and CTO and see so. Oh much Danny. Thank you for coming on. I appreciate it, >>monsieur john thank you for having >>Okay Cube coverage of Dr Khan 2021. Um your host, John Fury? The Cube. Thanks for watching. Yeah.

>>Welcome welcome back to the cubes coverage of dr khan 2021. I'm john for a host of the cube. We're here to talk about observe ability in the enterprise, enabling developers. Fabian lang VP of engineering and co founder of Istana, now part of IBM. Fabian, Congratulations on everything and great to have you on the cube here for dr gone. >>Thank you. Thanks for having me. >>So I'm in Palo Alto, you're in Germany were doing the remote thing obviously virtual second year in a row for dr khan. Soon real life is coming back. Uh no real impact of developers as they continue to be more productive than ever. The hottest conversation topic being discussed, being funded by venture capitalists and private equity is observe ability. This is an area you guys are playing in aggressively and you got some product observe ability. What's the big deal about Docker con Docker containers observe ability kubernetes, Why is observe ability at the center of all these conversations and the center of the value. >>So observe ability basically means you understand what's going on and today it's more important than ever to understand what's going on because there is so much more going on. If you think back five years maybe before Dr even was featured prominently, you had very little things that you needed to control that you need to understand and then micro service and coordinative became more popular and became really more important to understand what all those moving parts are doing. And that's where observe ability was born out of what we have been doing before at that time it was called application performance monitoring A PM. It's now called observe ability. It's really understanding all those parts of your architecture, of your stack of the application and in the end of the end user experience, you want to know if a user is experiencing a slow service and what's the reason for that? Because today, so many things are moving so many things that maybe even outsourced into cloud providers, it's more important than ever to know what's going on. >>Well we're here at Dunkirk on 2021 virtual. I want to get you to take a minute if you don't mind explaining to the folks why Dr and Dr Khan is important to Astana. >>So I, I said we were founded like six years ago and at that time Doctor was the rising star. It was promoting a lot of new technology. It was giving developers new abilities to develop applications in a very agile away. Microservices were enabled by Doctor before you had to deploy those things somehow it was a city Rome and then you needed to install >>debian >>package but with microservices you have so many more things to install. So it was really, I would say instrumental to the success of microservices to have a platform like docker that was really the next gen of technology that helped to enable those applications. And for us it was really an important driver to understand the whole stack, the traditional tools where eyes are oriented to infrastructure monitoring. So you understand the quality of your host if it's running slow or to look into application of an application was throwing errors but everything was disconnected and unique functionality of Astana is to connect all those bits and pieces of the application together and for that containers. And now kubernetes is a really important part to understand because it is part of this whole picture. >>Did you talk about the problem that you guys solve? Um obviously with those availability, I mean the general concept, we kind of get that great, great overview on your part, but when you start to get into devoPS teams, you start looking at def sec off, start looking at cloud native applications. I see Docker containers provides all that goodness and kubernetes, orchestration, etcetera. What problem do you guys solve? And um what's the benefit? >>The main problem that in stana solves is getting all this understanding that I said is required to provide a good experience of to your users, to your end customers uh without requiring you to do all the instrumentation work or the capture and configuration work because in stana is very automatic, it automatically sees all the works lords that are running in your communities, for example, that are running in Dr containers, but it also connects to legacy databases, fully automatic. So no configuration required also means that with a high rate of change that some of those applications hard have is that we will see all those change happening in real time. And you can't forget to make a configuration to enable your observe ability. So it's really return of investment on the viability solution that we provide and we provide a lot of this insight uh that you can get and that enables you to provide better service for your users. >>So you guys aren't just a doctor monitoring service and company, you guys actually run on Docker. Right, is that true? >>That's correct. So we are not only monitoring doctor and all these things connected to applications, but we are running on a doctor or platform as a service. SaAS software as a service. We run for you so you don't need to operate and stana, we are running it on managed kubernetes clusters and uh, IBM cloud and amazon cloud in google cloud. We have all that and it's it's all running on docker containers and that gives us so many features that are really great with DACA. So all the configuration that specific to microservices are being baked into the images and you can just roll it out, especially for monitoring products that is dependent on the data, that the performance depends on the data our customers send. Um, these ease of scalability with doctor is just so much bigger than it would be with a traditional deployment type. We can just add worker notes to our cluster and have ports auto scale to new notes and this is functionality that wasn't there before and that's great and that's important, essential for our business. >>You know, one of the conversations that's being talked about here at dr khan and in the industry at large is this idea of happy developers and everyone wants to keep developers happy. I've been hearing that conversation, have many chats with folks, you know, productivity and innovation, um but productivity and happy developers of the concept, but also, you know, on the, on the business side or on the developer side, it's more accelerated pipeline. Right? So, so how do you manage to flow, keep that productivity going, But also enabling happy developers, what do you guys do to help there? I mean what if someone asks you, hey, how do you make my developers happier and accelerate my pipeline? >>Well, that's really dependent on what makes the developers happy. I think most developers really want to get their functionality. They are working on their passionate about into production into the hands of end users. So um, skipping out a lot of the manual configuration work that's boring and not really appealing to develop us, helps everything is pre packaged and configured automatically. So that's a big, big plus. And the standard monitoring as I said, uh, is also automatic. So you don't need to configure it, your, your application on how to monitor it. So developers can just focus on delivering features and whenever there is something we will tell them, I think they enjoy that >>innovations creates great, that's a benefit. Can you talk about the on prem version of installing a, that's something that you guys are talking about and featuring um what is that about? Can you take a minute to explain beyond prem version of in Astana for dr containers? >>Yeah, it's a, it's an interesting topic, especially at the conference like dr khan, where it's all about virtualization, container realization and going into the cloud, that there are still companies, enterprises government mental entity that are very heavily invested on an on premise solution. They want to have control or are legally required to have control over what they have been deployed. So we knew when we founded in Astana that our solution, unlike our competitors, can't be only software as a service. We want to have a fantastic software as a service product and experience, but it should be equally good on premises as well. And when we were looking at ways how to actually do it, how to deliver an architecture that a little bit complicated to on premises customers to have themselves as the solution. We saw that doctor solves a lot of problems for us. We don't need to manually petra around operating system that customers, we don't have different versions of packages installed. It's all the same and actually it's not only all the same for all the deployment of all our customers, but it's also the same technology that we run as a software. As a service customers can run it now on their own. So we have feature parity, it's not lagging behind and this is also ease of support for us. >>So why was it, what was the motivation behind that was just customer demand? Um, more efficiency? What was the motivation behind moving on, supporting the on prem version? >>Uh, so for a start up, it's all about addressing the market share. Right? So you wanna have everything you can get, you don't want to spend any extra money on it. And as I said, the enterprise market is big. There are still many players that want to have the data in house. This is potentially sensitive data that's being tracked. So an on premise solution having, it was really instrumental to the success of in Stana because we were able to target and help those customers even in a fully adapt scenario, for example where they don't even have internet access. >>Take me through the process of DACA rising the product sitting on prime product that you get the thing going on there, like okay, let's do this. What does that look like? How did that work out? >>So as I said, we looked at this from the beginning and we picked DACA as a technology from the beginning, so there wasn't really like a shift and left type of scenario that other customers might be having. We were doing it from the beginning and we were aligning our architecture so that there are no fundamental differences between an on premise solution and anti size solution. That's of course configuration, that's different. But that configuration we just put into a single configuration file and that turned out to be a great idea because this is how you nowadays configure your application kubernetes, you'll make a customer resource for example, and then have an operator run the product, any kind of product, but also in stana, you run on premises with an operator that just works on the single configuration that you give it. And this is actually great because our customers are used to operating products like that, their own software, everything customers are running in dhaka in kubernetes, they are used to operating it that way. And that helped us because our customers now get the same functionality that we offer as a, as a service on premises very easily very quickly. And that make them happier. We talked about developer happiness that makes them happy because now they are not lagging behind but it also enables us to give better quality support, lot fixes faster and helps us to no longer support very old presence because they don't exist. They are frequently updated. I think this is really a benefit of container realization is also how easy it is to upgrade because you just stop apart and start a part in the new version and then you have a new verse. >>That's also great insights may be great to chat with you on that. I got to ask you on a personal note, you've been in the industry for a while and your leader, um you know, that's a performance geek, you'll have to build fast code. I was been chatting with other VPs of engineering and we were talking about the shift in engineering and with devops you've got kind of s our reaction, you have some just straight up application coding, just modernize that cloud native applications and you've got a kind of under the devoPS as the world's shifts. It seems like there's more of an architectural systems engineering approach or a systems mindset and that seems to be changing the mindset of a developer from Iterate fast. And then the line I heard was you can iterate and pump out code fast, but it might not be good, might be crap. So, so this notion of iterating code and crafting good product because with now this module Ization with containers, you're doing a lot more design work. So craft seems to be coming back to coding. Uh, I don't think it's coming back, it's been there, but it just seems more of like, hey, let's do this, right? And it's not just ship code. What's your take on that? >>So I think this always was there. It's just that traditionally companies approached software engineering similar to how companies approach manufacturing. So somebody writing a designs back and somebody verifying it and then it's going onto the line to mass production. But software doesn't work that way. We make way more changes, it's way harder to understand it up front. So the developed the iterative and exile development that has been ongoing is really, is really what people want and develops well. There is this notion of being a being waking up in the middle of the night and that's what developers don't want. So you need to prepare your application, you need to make it resilient against that. And developers are very eager to build in functionality that helps them to troubleshoot to make their application available. With a high rate of change. There is a high rate of risk as you said and I think the ability to deploy 1000 times per day is great but you don't necessarily need to do that. I think it's also important for your users that you find the right pace of when you deliver functionality and when you deliver fixes. >>I was just talking to a friend the other day and we were just talking about organizations and teams and yeah, we always riff on the the two pizza team or having more agility and you have this democratization because of the agility is also a benefit for any developer to add value if they have the right perspective or creativity. But it kind of disrupts the kind of the old way of thinking. I'm the principal engineer is my job. No, I'm the chief architect. So you have these titles and you have roles, the roles are changing and sometimes just the arguments. Oh wait, that's my job is that I'm this kind of changes. What's your thoughts on, how do you manage that dynamic? Because as you have more, uh, I won't say surface here more democratized engineering with virtual teams and whatnot You have compose ability with, with with code. You have more of a systems are a lot more going on. It's not your standard engineering mindset. What's your thinking on this as a leader in engineering and visionary? >>Well as we know the architecture of a software full of the organization that the company has. That creates. All right. So I think what you want when you want to have a micro service architecture, you want to have a micro service teams. You want to have teams, we call him at and standard delivery teams that work more or less independently on a certain set of features and are responsible for them and to end. So my engineers, they are talking to our customers figuring out how to make a feature better. They are then designing this with our user designers and then they are developing and deploying it and this really entry and responsibility. And we don't really have those titles like architect anymore. I think those roles are still there but it's more like a shared responsibility. So you of course want an architecture, you want to have your components talk to each other in an efficient way and it's more really communities of practice that are establishing. So you will find out that you have people and your teams who have specific skills who like to work on architecture. Some of them like to work on continuous delivery systems And then you you form those cross functional teams dynamically and when it's no longer hit this bands. And I think that's a major difference to assigning a person to a road. >>Yeah and and also that with you have new trends like observe ability, enterprise observe ability you know new things are happening um And new net new things like new architecture and also new roles and responsibilities. I'll see new patterns to with the data you have services being stood up and turned down all the time. You have a lot of dynamic environment. So you know having a happy developers one eliminate the manual work what you do but also giving them good work assignments to work on some good hard problems. So what is what are those hard problems that engineers like to work on these days? Is it like design? Is it coding? I mean I know it depends as you mentioned on the personalities but generally speaking as dev ops def sec Ops becomes much more of an agile edge hybrid play. What's the hard problem? >>I think big data is not really a new term but I think this is still a very interesting territory because you can apply various aspects to it. You have this data science aspect to it to understand how to detect pattern in it. And then automation is actually artificial intelligence. Right? So you automate data science and that's very interesting because those are large scale problems and new problems and new solutions. So yes there are existing frameworks but there's so much innovation to be found and making this work efficiently is another dimension of the same problem. That's also not easy and challenging problems. Make developers happy and then you can even have people think about the financial aspects. So it should also be cheap Big data and AI is usually very expensive because it requires so much hardware. So not only tried to make it fast but maybe even make it efficient. So this whole domain is very appealing. There is new technology to be invented, tough problems and I think that's really exciting to developed. >>Fabian Lang, vice president of engineering co founder and stand a great to have you on the q Great insight. Thank you for sharing that knowledge there. And the overview of installing here at dr khan observe ability very relevant for next gen next level solutions. Thanks for coming on the cube. Right, okay. I'm john Fury with the queue here. Dr khan 2021 coverage. Thanks for watching. Mm.

>> Welcome to this IBM Watson Health client conversation. And we're probing the dynamics of the relationship between IBM and it's clients. We're going to look back at some of the challenges of 2020 and look forward to, you know, present year's priorities. We'll also touch on the future state of healthcare. My name is Dave Vellante. I'll be your host and I'm from theCUBE. And with me are Doctor Alex Towbin, who's Associate Chief Clinical Operations and Informatics at Cincinnati ChilDoctoren's Hospital and John Chrisman of course from IBM Watson health. Welcome gentlemen, Good to see you. Thanks for coming on. >> Thanks for having us. >> Yeah, thanks for having me. >> Yeah I know from talking to many clients around the world, of course virtually this past year, 11 months or so that relationships with technology partners they've been critical over during the pandemic to really help folks get through that. Not that we're through it yet but, we're still through the year now, there's I'm talking professionally and personally and Doctor Towbin, I wonder if you could please talk about 2020 and what role the IBM partnership played in helping Cincinnati children's, you know press on in the face of incredible challenges? >> Yeah, I think our story of 2020 really starts before the pandemic and we were fortunate to be able to plan a disaster and do disaster drill scenarios. And so, as we were going through those disaster drill scenarios, we were trying to build a solution that would enable us to be able to work if all of our systems were down and we worked with IBM Watson Health to design that solution to implement it, it involves using other solutions from our primary one. And we performed that disaster drill in the late January, early February timeframe of 2020. And while that drill had nothing to do with COVID it got us thinking about how to deal with a disaster, how to prepare for a disaster. And so we've just completed that and COVID was coming on the horizon. I'm starting to hear about it coming into the U.S for the first time. And we took that very seriously on our department. And so, because we had prepared for this this disaster drill had gone through the entire exercise and we built out different scenarios for what could happen with COVID what would be our worst case scenarios and how we would deal with them. And so we were able to then bring that to quickly down to two options on how our department and our hospital would handle COVID and deal with that within the radiology department and like many other sites that becomes options of working from home or working in a isolated way and an and an office scenario like where I'm sitting now and we planned out both scenarios and eventually made the decision. Our decision at that point was to work in our offices. We're fortunate to have private offices where we can retreat to and something like that. And so then our relationship with IBM was helpful and that we needed to secure more pieces of hardware. And so even though IBM is our PACS vendor and our enterprise imaging vendor, they also help us to secure the high resolution monitors that are needed. And we needed a large influx of those during the pandemic and IBM was able to help us to get those. >> Wow! So yeah you were able to sort of test your organization resilience before the pandemic. I mean, John, that's quite an accomplishment for last year. I'm sure there are many others. I wonder if one of you could pick it up from here and bring your perspectives into it and, you know maybe ask any questions that you would like to ask them. >> Yeah, sure, Doctor Towbin, that's great that we were able to help you with the hardware and procure things. So I'm just curious before the pandemic how many of the radiologists ever got to read from home, was that a luxury back then? And then post pandemic, are you guys going to shift to how many are on-site versus remote? >> Yeah, so we have a couple of scenarios. We've had talk about it both from our PACS perspective as well as from our VNA enterprise imaging perspective from PACS perspective we always designed our solution to be able to work from a home machine. Our machines, people would access that through a hospital-based VPN. So they would log in directly to VPN and then access the PACS that way. And that worked well. And many of our radiologists do that particularly when they're on call works best for our neuroradiologist who are on call a little bit more frequently. And so they do read from home in that scenario. With enterprise imaging and are used to the enterprise viewer and iConnect access. We always wanted that solution to work over the internet. And so it's set up securely through the internet but not through the VPN. And we have radiologists use that as a way to view studies from home, even not from home, so it can be over one of their mobile devices, such as an iPad and could be at least reviewing studies then. We, for the most part for our radiologist in the hospital that's why we made the decision to stay in the hospital. At COVID time, we have such a strong teaching mission in our department in such a commitment to the education of our trainees. We think that hospital being in the hospital is our best way to do that, it's so hard. We find to do it over something like zoom or other sharing screen-sharing technology. So we've stayed in and I think we'll continue to stay in. There will be some of those needs from a call perspective for example, reading from home, and that will continue. >> And then what's your success been with this with the technology and the efficiency of reading from home? Do you feel like you're just as efficient when you're at home versus onsite? >> The technology is okay. The, our challenges when we're reading from the PACS which is the preferred way to do it rather than the enterprise archive, the challenge is we have to use the PACS So we have to be connected through VPN which limits our bandwidth and that makes it a little bit slower to read. And also the dictation software is a little bit slower when we're doing it. So moving study to study that rapid turnover doesn't happen but we have other ways to make, to accelerate the workflow. We cashed studies through the worklist. So they're on the machine, they load a little bit more rapidly and that works pretty well. So not quite as fast, but not terrible. >> We appreciate your partnership. I know it's been going on 10 years. I think you guys have a policy that you have to look at the market again every 10 years. So what do you think of how the market's changed and how we've evolved with the VNA and with the zero footprint viewers? A lot of that wasn't available when you initially signed up with Amicas years ago, so. >> Yeah, we signed up so we've been on this platform and then, you know now the IBM family starting in 2010, so it's now now 11 years that we're, we've been on as this version of the PACS and about eight, seven or eight years from the iConnect platform. And through that, we've seen quite an evolution. We were one of the first Amicas clients to be on version six and one of the largest enterprises. And that went from, we had trouble at the launch of that product. We've worked very closely with Amicas then to merge. And now IBM from the development side, as well as the support side to have really what we think is a great product that works very well for us and drives our entire workflow all the operations of our department. And so we've really relished that relationship with now IBM. And it's been a very good one, and it's allowed us to do the things like having disaster drill planning that we talked about earlier as far as where I see the market I think PACS in particular is on the verge of the 3.0 version as a marketplace. So PACSS 1 one was about building the packs, I think, and and having electronic imaging digital imaging, PACS 2.0 is more of web-based technology, getting it out of those private networks within a radiology department. And so giving a little bit more to the masses and 3.0 is going to be more about incorporating machine learning. I really see that as the way the market's going to go and to where I think we're at the infancy of that part of the market now about how do you bring books in for machine learning algorithms to help to drive workflow or to drive some image interpretation or analysis, as far as enterprise imaging, we're on the cusp of a lot there as well. So we've been really driving deep with enterprise imaging leading nationally enterprise imaging and I have a role in the MSAM Enterprise Imaging Community. And through all of that work we've been trying to tackle works well from enterprise imaging point of view the challenges are outside of radiology, outside of cardiology and the places where we're trying to deal with medical photos, the photographs taken with a smart device or a digital camera of another type, and trying to have workflow that makes sense for providers not in those specialty to that don't have tools like a DICOM modality workloads store these giant million-dollar MRI scanners that do all the work for you, but dealing with off the shelf, consumer electronics. So making sure the workflow works for them, trying to tie reports in trying to standardize the language around it, so how do we tag photos correctly so that we can identify relevancy all of those things we're working through and are not yet standard within our, within the industry. And so we're doing a lot there and trying and seeing the products in the marketplace continuing to evolve around that on the viewer side, there's really been a big emergence as you mentioned about the zero footprint viewers or the enterprise viewer, allowing easy access easy viewing of images throughout the enterprise of all types of imaging through obtained in the enterprise and will eventually incorporate video pathology. The market is also trying to figure out if there can be one type of viewer that does them all that and so that type of universal viewer, a viewer that cardiologists can use the same as a radiologist the same as a dermatologist, same as a pathologist we're all I think a long way away from that. But that's the Marcus trying to figure those two things out. >> Yeah, I agree with you. I agree with your assessment. You talked about the non DICOM areas, and I know you've you've partnered with us, with ImageMover and you've got some mobile device capture taking place. And you're looking to expand that more to the enterprise. Are you also starting to use the XDS registry? That's part of the iConnect enterprise archive, or as well as wrapping things in DICOM, or are you going to stick with just wrapping things in DICOM? >> Yeah, so far we've been very bunched pro DICOM and using that throughout the enterprise. And we've always thought, or maybe we've evolved to think that there is going to be a role for XDS are I think our early concerns with XDS are the lack of other institutions using it. And so, even though it's designed for portability if no one else reads it, it's not portable. If no one else is using that. But as we move more and more into other specialties things like dermatology, ophthalmology, some of the labeling that's needed in those images and the uses, the secondary uses of those images for education, for publication, for dermatology workflow or ophthalmology workflow, needs to get back to that native file and the DICOM wrap may not make sense for them. And so we've been actively talking about switching towards XDS for some of the non DICOM, such as dermatology. We've not yet done that though. >> Given the era children's hospital has the impact on your patient load, then similar to what regular adult hospitals are, or have you guys had a pretty steady number of studies over the last year? >> In relay through the pandemic, we've had, it has been decreased, but children fortunately have not been as severely affected as adults. There is definitely disease in children and we see a fair amount of that. There are some unique things that happen in kids but that fortunately rare. So there's this severe inflammatory response that kids can get and can cause them to get very sick but it is quite rare. Our volumes are, I think I'm not I think our volumes are stable and our advanced imaging things like CT, MRI, nuclear medicine, they're really most decreased in radiography. And we see some weird patterns, inpatient volumes are relatively stable. So our single view chest x-rays, for example, have been stable. ER, visits are way down because people are either wearing masks, isolating or not wanting to come to the ER. So they're not getting sick with things like the flu or or even common colds or pneumonias. And so they're not coming into the ER as much. So our two view x-rays have dropped by like 30%. And so we were looking at this just yesterday. If you follow the graphs for the two we saw a dip of both around March, but essentially the one view chest were a straight line and the two view chest were a straight line and in March dropped 30 to 50% and then stayed at that lower level. Other x-rays are on the, stay at that low level side. >> Thanks, I know in 2021 we've got a big upgrade coming with you guys soon and you're going to stay in our standalone mode. I understand what the PACSS and not integrate deeply to the VNA. And so you'll have a couple more layers of storage there but can you talk about your excitement about going to 8.1 and what you're looking forward to based on your testimony. >> Yeah we're actually in, we're upgrading as we're talking which is interesting, but it's a good time for talking. I'm not doing that part of the work. And so our testing has worked well. I think we're, we are excited. We, you know, we've been on the product as I mentioned for over 10 years now. And for many of those years we were among the first, at each version. Now we're way behind. And we want to get back up to the latest and greatest and we want to stay cutting edge. There've been a lot of reasons why we haven't moved up to that level, but we do. We're very careful in our testing and we needed a version that would work for us. And there were things about previous versions that just didn't and as you mentioned, we're staying in that standalone mode. We very much want to be on the integrated mode in our future because enterprise imaging is so important and understanding how the comparisons fit in with the comparison in dermatology or chest wall deformity clinic, or other areas how those fit into the radiology story is important and it helped me as a radiologist be a better radiologist to see all those other pictures. So I want them there but we have to have the workflow, right. And so that's the part that we're still working towards and making sure that that fits so we will get there. It'll probably be in the next year or two to get to that immigrating mode. >> As you, look at the number of vendors you have I think you guys prefer to have less vendor partners than than more I know in the cardiology area you guys do some cardiology work. What has been the history or any, any look to the future of that related to enterprise imaging? Do you look to incorporate more of that into a singular solution? >> Cardiology is entirely part of our enterprise imaging solution. We all the cardiology amendments go to our vendor neutral archive on the iConnect platform. All of them are viewed across the enterprise using our enterprise viewer. They have their unique specialty viewer which is, you know, fine. I'm a believer that specialty, different specialties, deserve to have their specialty viewers to do theirs specialty reads. And at this point I don't think the universal viewer works or makes sense until we have that. And so all the cardiology images are there. They're all of our historical cardiology images are migrated and part of our enterprise solution. So they're part of the entire reference the challenge is they're just not all in PACSS. And so that's where, you know, an example, great example, why we need to get to this to the integrated mode to be able to see those. And the reason we didn't do that is the cardiology archive is so large to add a storage to the PACS archive. Didn't make sense if we knew we were going to be in an integrated mode eventually, and we didn't want to double our PACS storage and then get rid of it a couple of years later. >> So once you're on a new version of merge PACS and you're beyond this, what are your other goals in 2021? Are you looking to bring AI in? Are you using anybody else's AI currently? >> Yeah, we do have AI clinical it's phone age, so it's not not a ton of things but we've been using it clinically, fully integrated, it launches. When I open a study, when I opened a bone age study impacts it launches we have a bone age calculator as well that we've been using for almost two decades now. And so that we have to use that still but launching that automatically includes the patient's sex and birth date, which are keys for determining bone age, and all that information is there automatically. But at the same time, the images are sent to the machine learning algorithm. And in the background the machine determines a bone age that in the background it sends it straight to our dictation system and it's there when we opened the study. And so if I agree with that I signed the report and we're done. If I disagree, I copy it from my calculator and put it in until it takes just a couple of clicks. We are working on expanding. We've done a lot of research in artificial intelligence and the department. And so we've been things are sort of in the middle of translation of moving it from the research pure research realm to the clinical realm, something we're actively working on trying to get them in. Others are a little bit more difficult. >> That's the question on that John, Doctor, when you talk about injecting, you know machine intelligence into the equation. >> Yeah. >> What, how do you sort of value that? Does that give you automation? Does it improve your quality? Does it speed the outcome and maybe it's all of those but how do you sort of evaluate the impact to your organisation? >> I there's a lot of ways you can do it. And you touched on one of my favorite one of my favorite talking points, in a lot of what we've been doing and early machine learning is around image interpretation helping me as a radiologist to see a finding. Unfortunately, most of the things are fairly simple tasks that it's asking us to do. Like, is there a broken bone? Yes or no, I'm not trying to sound self-congratulatory or anything, but I'm really good at finding broken bones. I get, I've been doing it for a long time and, and radio, you know so machines doing that, they're going to perform as well as I can perform, you know, and that's the goal. Maybe they'll perform a little bit better maybe a little bit worse but we're talking tiny increments there they're really to me, not much value of that it's not something I would want. I don't value that at a time where I think machine learning can have real value around more on some of the things that you mentioned. So can it make me more efficient? Can it do the things that are so annoying that and they'd take, they're so tedious that they make me unhappy. A lot of little measurements for example are like that an example. So in a patient with cancer, we measure a little tumors everywhere and that's really important for their care, but it's tedious and so if a machine could do that in an automated way and I checked it that, you know, patient when because he or she can get that good quality care and I have a, you know, a workflow efficiency game. So that one's important. Another one that would be important is if the machine can see things I can't see. So I'm really good at finding fractures. I'm not really good at understanding what all the pixels mean and, you know in that same patient with cancer, oh what do all the pixels mean in that tumor? I know it's a tumor. I can see the tumor, I can say it's a tumor but sometimes those pixels have a lot of information in them and may give us prognosis, you know, say that this patient may, maybe this patient will do well with this specific type of chemotherapy or a specific or has a better prognosis with one with one drug compared to another. Those are things that we can't usually pick out. You know, it's beyond the level of that are I can perceive that one is really the cutting edge of machine learning. We're not there yet and then the other thing are things that, you know just the behind the scenes stuff that I don't necessarily need to be doing, or, you know so it's the non interpretive artificial intelligence. >> Dave: Right. >> And that's what I've been also trying to push. So an example of when the algorithms that we've been developing here we check airways. And this is a little bit historical in our department, but we want to make sure we're not missing a severe airway infection. That can be deadly, it's incredibly rare. Vaccines have made it go away completely but we still check airways. And so what happens is the technologist takes the x-ray. They come in to ask us if it's okay, we are interrupted from what we're doing. We open up the study, say yes or no. Okay, not okay, if it's not okay they go back, take another study. Then come back to us again and say, is it okay or not? And we repeat this a couple of times it takes them time that they don't need to spend and takes us time. And so we have, we've built an algorithm where the machine can check that and their machine is as good or a little bit worse than us, but give can give that feedback. >> Dave: Got it. >> The challenge is getting that feedback to the technologist quickly. And so that's, that's I think part for us to work on stuff. >> Thank you for that. So, John, we've probably got three or four minutes left. I'll let you bring it home and appreciate that Doctor Towbin >> I think one of the biggest impacts probably I knew this last year with the pandemic, Doctor Towbin is this, I know you're a big foodie. So having been to some good restaurants and dinners with the hot nurse in a house how's the pandemic affected you personally. And some of the things you like to do outside of work. >> Everything is shut down. And everything has changed. I have not left the house since March besides come to work and my family hasn't either. And so we're hardcore quarantining and staying you know, staying out and keeping it home. So we've not gone out to dinner or done much else. >> So its DoorDash and Uber Eats or just learned to cook at home. >> It's all cooking at home. We're fortunate, my wife loves to cook. My kids love to cook. I enjoy cooking, but I don't have the time as often. So we've done a lot of different are on our own experimenting. Maybe when the silver lining one of the things I've really relished about all this is all this time I get to spend with my family. And that closeness that we've been able to achieve because of being confined in our house the whole time. And so I've played get to play video games with my kids every night. We'd been on a big Fortnite Keck lately since it's been down making. So we've been playing that every night since we've watched movies a lot. And so as a family, we've, I it's something I'll look back fondly even though it's been a very difficult time but it's been an enjoyable time. >> I agree, I've enjoyed more family time this year as well, but final question is in 2021, beyond the PACS upgrade what are the top other two projects that you want to accomplish with us this year? And how can we help you? >> I think our big one is are the big projects are unexpanded enterprise imaging. And so we want to continue rolling out to other areas that will include eventually incorporating scopes, all the images from the operating room. We need to be able to get into pathology. I think the pathology is really going to be a long game. Unfortunately, I've been saying that already for 10 years and it's still probably another 10 years ago but we need to go. We can start with the gross pathology images all the pictures that we take for tumor boards and get those in before we start talking about whole slide scanning and getting in more of the more of the photographs in the institution. So we have a route ambulatory but we need inpatient and ER. >> All right one last question. What can IBM do to be a better partner for you guys? >> I think it's keep listening keep listening and keep innovating. And don't be afraid to be that innovative partner sort of thinking as the small company that startup, rather than the giant bohemoth that can sometimes happen with large companies, it's harder. It is fear to turn quickly, but being a nimble company and making quick decisions, quick innovations. >> Great, quick question. How would you grade IBM, your a tough grader? >> It depends on what I am a tough grader but it depends on what, you know as the overall corporate partnership? >> Yeah the relationship. >> I'd say it's A minus. >> Its pretty good. >> I think, I mean, I, we get a lot of love from IBM. I'm talking specifically in the imaging space. I not, maybe not, I don't know as much on the hardware side but we, yeah, we have a really good relationship. We feel like we're listened to and we're valued. >> All right, well guys, thanks so much. >> So even if it's not an A plus- >> Go ahead. >> I think there's some more to, you know, from the to keep innovating side there's little things that we just let you know we've been asking for that we don't always get but understand the company has to make business decisions not decisions on what's best for me. >> Of course got to hold that carrot out too. Well thanks guys, really appreciate your time. Great conversation. >> Yeah, thank you. >> All right and thank you for spending some time with us. You're watching client conversations with IBM Watson Health.

>>all right, We're five minutes after the hour. That's all aboard. Who's coming aboard? Welcome everyone to the tutorial track for our launchpad of them. So for the next couple of hours, we've got a SYRIZA videos and experts on hand to answer questions about our new product, Doctor Enterprise Container Cloud. Before we jump into the videos and the technology, I just want to introduce myself and my other emcee for the session. I'm Bill Milks. I run curriculum development for Mirant us on. And >>I'm Bruce Basil Matthews. I'm the Western regional Solutions architect for Moran Tissue esa and welcome to everyone to this lovely launchpad oven event. >>We're lucky to have you with us proof. At least somebody on the call knows something about your enterprise Computer club. Um, speaking of people that know about Dr Enterprise Container Cloud, make sure that you've got a window open to the chat for this session. We've got a number of our engineers available and on hand to answer your questions live as we go through these videos and disgusting problem. So that's us, I guess, for Dr Enterprise Container Cloud, this is Mirant asses brand new product for bootstrapping Doctor Enterprise Kubernetes clusters at scale Anything. The airport Abu's? >>No, just that I think that we're trying Thio. Uh, let's see. Hold on. I think that we're trying Teoh give you a foundation against which to give this stuff a go yourself. And that's really the key to this thing is to provide some, you know, many training and education in a very condensed period. So, >>yeah, that's exactly what you're going to see. The SYRIZA videos we have today. We're going to focus on your first steps with Dr Enterprise Container Cloud from installing it to bootstrapping your regional child clusters so that by the end of the tutorial content today, you're gonna be prepared to spin up your first documentary prize clusters using documented prize container class. So just a little bit of logistics for the session. We're going to run through these tutorials twice. We're gonna do one run through starting seven minutes ago up until I guess it will be ten fifteen Pacific time. Then we're gonna run through the whole thing again. So if you've got other colleagues that weren't able to join right at the top of the hour and would like to jump in from the beginning, ten. Fifteen Pacific time. We're gonna do the whole thing over again. So if you want to see the videos twice, you got public friends and colleagues that, you know you wanna pull in for a second chance to see this stuff, we're gonna do it all. All twice. Yeah, this session. Any any logistics I should add, Bruce that No, >>I think that's that's pretty much what we had to nail down here. But let's zoom dash into those, uh, feature films. >>Let's do Edmonds. And like I said, don't be shy. Feel free to ask questions in the chat or engineers and boosting myself are standing by to answer your questions. So let me just tee up the first video here and walk their cost. Yeah. Mhm. Yes. Sorry. And here we go. So our first video here is gonna be about installing the Doctor Enterprise Container Club Management cluster. So I like to think of the management cluster as like your mothership, right? This is what you're gonna use to deploy all those little child clusters that you're gonna use is like, Come on it as clusters downstream. So the management costs was always our first step. Let's jump in there >>now. We have to give this brief little pause >>with no good day video. Focus for this demo will be the initial bootstrap of the management cluster in the first regional clusters to support AWS deployments. The management cluster provides the core functionality, including identity management, authentication, infantry release version. The regional cluster provides the specific architecture provided in this case, eight of us and the Elsie um, components on the UCP Cluster Child cluster is the cluster or clusters being deployed and managed. The deployment is broken up into five phases. The first phase is preparing a big strap note on this dependencies on handling with download of the bridge struck tools. The second phase is obtaining America's license file. Third phase. Prepare the AWS credentials instead of the adduce environment. The fourth configuring the deployment, defining things like the machine types on the fifth phase. Run the bootstrap script and wait for the deployment to complete. Okay, so here we're sitting up the strap node, just checking that it's clean and clear and ready to go there. No credentials already set up on that particular note. Now we're just checking through AWS to make sure that the account we want to use we have the correct credentials on the correct roles set up and validating that there are no instances currently set up in easy to instance, not completely necessary, but just helps keep things clean and tidy when I am perspective. Right. So next step, we're just going to check that we can, from the bootstrap note, reach more antis, get to the repositories where the various components of the system are available. They're good. No areas here. Yeah, right now we're going to start sitting at the bootstrap note itself. So we're downloading the cars release, get get cars, script, and then next, we're going to run it. I'm in. Deploy it. Changing into that big struck folder. Just making see what's there. Right now we have no license file, so we're gonna get the license filed. Oh, okay. Get the license file through the more antis downloads site, signing up here, downloading that license file and putting it into the Carisbrook struck folder. Okay, Once we've done that, we can now go ahead with the rest of the deployment. See that the follow is there. Uh, huh? That's again checking that we can now reach E C two, which is extremely important for the deployment. Just validation steps as we move through the process. All right, The next big step is valid in all of our AWS credentials. So the first thing is, we need those route credentials which we're going to export on the command line. This is to create the necessary bootstrap user on AWS credentials for the completion off the deployment we're now running an AWS policy create. So it is part of that is creating our Food trucks script, creating the mystery policy files on top of AWS, Just generally preparing the environment using a cloud formation script you'll see in a second will give a new policy confirmations just waiting for it to complete. Yeah, and there is done. It's gonna have a look at the AWS console. You can see that we're creative completed. Now we can go and get the credentials that we created Today I am console. Go to that new user that's being created. We'll go to the section on security credentials and creating new keys. Download that information media Access key I D and the secret access key. We went, Yeah, usually then exported on the command line. Okay. Couple of things to Notre. Ensure that you're using the correct AWS region on ensure that in the conflict file you put the correct Am I in for that region? I'm sure you have it together in a second. Yes. Okay, that's the key. Secret X key. Right on. Let's kick it off. Yeah, So this process takes between thirty and forty five minutes. Handles all the AWS dependencies for you, and as we go through, the process will show you how you can track it. Andi will start to see things like the running instances being created on the west side. The first phase off this whole process happening in the background is the creation of a local kind based bootstrapped cluster on the bootstrap node that clusters then used to deploy and manage all the various instances and configurations within AWS. At the end of the process, that cluster is copied into the new cluster on AWS and then shut down that local cluster essentially moving itself over. Okay. Local clusters boat just waiting for the various objects to get ready. Standard communities objects here Okay, so we speed up this process a little bit just for demonstration purposes. Yeah. There we go. So first note is being built the best in host. Just jump box that will allow us access to the entire environment. Yeah, In a few seconds, we'll see those instances here in the US console on the right. Um, the failures that you're seeing around failed to get the I. P for Bastian is just the weight state while we wait for a W s to create the instance. Okay. Yes. Here, beauty there. Okay. Mhm. Okay. Yeah, yeah. Okay. On there. We got question. Host has been built on three instances for the management clusters have now been created. We're going through the process of preparing. Those nodes were now copying everything over. See that? The scaling up of controllers in the big Strap cluster? It's indicating that we're starting all of the controllers in the new question. Almost there. Yeah. Yeah, just waiting for key. Clark. Uh huh. Start to finish up. Yeah. No. What? Now we're shutting down control this on the local bootstrap node on preparing our I. D. C. Configuration. Fourth indication, soon as this is completed. Last phase will be to deploy stack light into the new cluster the last time Monitoring tool set way Go stack like to plan It has started. Mhm coming to the end of the deployment Mountain. Yeah, America. Final phase of the deployment. Onda, We are done. Okay, You'll see. At the end they're providing us the details of you. I log in so there's a keeper clogging. You can modify that initial default password is part of the configuration set up with one documentation way. Go Councils up way can log in. Yeah, yeah, thank you very much for watching. >>Excellent. So in that video are wonderful field CTO Shauna Vera bootstrapped up management costume for Dr Enterprise Container Cloud Bruce, where exactly does that leave us? So now we've got this management costume installed like what's next? >>So primarily the foundation for being able to deploy either regional clusters that will then allow you to support child clusters. Uh, comes into play the next piece of what we're going to show, I think with Sean O'Mara doing this is the child cluster capability, which allows you to then deploy your application services on the local cluster. That's being managed by the ah ah management cluster that we just created with the bootstrap. >>Right? So this cluster isn't yet for workloads. This is just for bootstrapping up the downstream clusters. Those or what we're gonna use for workings. >>Exactly. Yeah. And I just wanted to point out, since Sean O'Mara isn't around, toe, actually answer questions. I could listen to that guy. Read the phone book, and it would be interesting, but anyway, you can tell him I said that >>he's watching right now, Crusoe. Good. Um, cool. So and just to make sure I understood what Sean was describing their that bootstrap er knows that you, like, ran document fresh pretender Cloud from to begin with. That's actually creating a kind kubernetes deployment kubernetes and Docker deployment locally. That then hits the AWS a p i in this example that make those e c two instances, and it makes like a three manager kubernetes cluster there, and then it, like, copies itself over toe those communities managers. >>Yeah, and and that's sort of where the transition happens. You can actually see it. The output that when it says I'm pivoting, I'm pivoting from my local kind deployment of cluster AP, I toothy, uh, cluster, that's that's being created inside of AWS or, quite frankly, inside of open stack or inside of bare metal or inside of it. The targeting is, uh, abstracted. Yeah, but >>those air three environments that we're looking at right now, right? Us bare metal in open staff environments. So does that kind cluster on the bootstrap er go away afterwards. You don't need that afterwards. Yeah, that is just temporary. To get things bootstrapped, then you manage things from management cluster on aws in this example? >>Yeah. Yeah. The seed, uh, cloud that post the bootstrap is not required anymore. And there's no, uh, interplay between them after that. So that there's no dependencies on any of the clouds that get created thereafter. >>Yeah, that actually reminds me of how we bootstrapped doctor enterprise back in the day, be a temporary container that would bootstrap all the other containers. Go away. It's, uh, so sort of a similar, similar temporary transient bootstrapping model. Cool. Excellent. What will convict there? It looked like there wasn't a ton, right? It looked like you had to, like, set up some AWS parameters like credentials and region and stuff like that. But other than that, that looked like heavily script herbal like there wasn't a ton of point and click there. >>Yeah, very much so. It's pretty straightforward from a bootstrapping standpoint, The config file that that's generated the template is fairly straightforward and targeted towards of a small medium or large, um, deployment. And by editing that single file and then gathering license file and all of the things that Sean went through, um, that that it makes it fairly easy to script >>this. And if I understood correctly as well that three manager footprint for your management cluster, that's the minimum, right. We always insist on high availability for this management cluster because boy do not wanna see oh, >>right, right. And you know, there's all kinds of persistent data that needs to be available, regardless of whether one of the notes goes down or not. So we're taking care of all of that for you behind the scenes without you having toe worry about it as a developer. >>No, I think there's that's a theme that I think will come back to throughout the rest of this tutorial session today is there's a lot of there's a lot of expertise baked him to Dr Enterprise Container Cloud in terms of implementing best practices for you like the defaulter, just the best practices of how you should be managing these clusters, Miss Seymour. Examples of that is the day goes on. Any interesting questions you want to call out from the chap who's >>well, there was. Yeah, yeah, there was one that we had responded to earlier about the fact that it's a management cluster that then conduce oh, either the the regional cluster or a local child molester. The child clusters, in each case host the application services, >>right? So at this point, we've got, in some sense, like the simplest architectures for our documentary prize Container Cloud. We've got the management cluster, and we're gonna go straight with child cluster. In the next video, there's a more sophisticated architecture, which will also proper today that inserts another layer between those two regional clusters. If you need to manage regions like across a BS, reads across with these documents anything, >>yeah, that that local support for the child cluster makes it a lot easier for you to manage the individual clusters themselves and to take advantage of our observation. I'll support systems a stack light and things like that for each one of clusters locally, as opposed to having to centralize thumb >>eso. It's a couple of good questions. In the chat here, someone was asking for the instructions to do this themselves. I strongly encourage you to do so. That should be in the docks, which I think Dale helpfully thank you. Dale provided links for that's all publicly available right now. So just head on in, head on into the docks like the Dale provided here. You can follow this example yourself. All you need is a Mirante license for this and your AWS credentials. There was a question from many a hear about deploying this toe azure. Not at G. Not at this time. >>Yeah, although that is coming. That's going to be in a very near term release. >>I didn't wanna make promises for product, but I'm not too surprised that she's gonna be targeted. Very bracing. Cool. Okay. Any other thoughts on this one does. >>No, just that the fact that we're running through these individual pieces of the steps Well, I'm sure help you folks. If you go to the link that, uh, the gentleman had put into the chat, um, giving you the step by staff. Um, it makes it fairly straightforward to try this yourselves. >>E strongly encourage that, right? That's when you really start to internalize this stuff. OK, but before we move on to the next video, let's just make sure everyone has a clear picture in your mind of, like, where we are in the life cycle here creating this management cluster. Just stop me if I'm wrong. Who's creating this management cluster is like, you do that once, right? That's when your first setting up your doctor enterprise container cloud environment of system. What we're going to start seeing next is creating child clusters and this is what you're gonna be doing over and over and over again. When you need to create a cluster for this Deb team or, you know, this other team river it is that needs commodity. Doctor Enterprise clusters create these easy on half will. So this was once to set up Dr Enterprise Container Cloud Child clusters, which we're going to see next. We're gonna do over and over and over again. So let's go to that video and see just how straightforward it is to spin up a doctor enterprise cluster for work clothes as a child cluster. Undocumented brands contain >>Hello. In this demo, we will cover the deployment experience of creating a new child cluster, the scaling of the cluster and how to update the cluster. When a new version is available, we begin the process by logging onto the you I as a normal user called Mary. Let's go through the navigation of the U I so you can switch. Project Mary only has access to development. Get a list of the available projects that you have access to. What clusters have been deployed at the moment there. Nan Yes, this H Keys Associate ID for Mary into her team on the cloud credentials that allow you to create access the various clouds that you can deploy clusters to finally different releases that are available to us. We can switch from dark mode to light mode, depending on your preferences, Right? Let's now set up semester search keys for Mary so she can access the notes and machines again. Very simply, had Mississippi key give it a name, we copy and paste our public key into the upload key block. Or we can upload the key if we have the file available on our local machine. A simple process. So to create a new cluster, we define the cluster ad management nodes and add worker nodes to the cluster. Yeah, again, very simply, you go to the clusters tab. We hit the create cluster button. Give the cluster name. Yeah, Andi, select the provider. We only have access to AWS in this particular deployment, so we'll stick to AWS. What's like the region in this case? US West one release version five point seven is the current release Onda Attach. Mary's Key is necessary Key. We can then check the rest of the settings, confirming the provider Any kubernetes c r D r I p address information. We can change this. Should we wish to? We'll leave it default for now on. Then what components? A stack light I would like to deploy into my Custer. For this. I'm enabling stack light on logging on Aiken. Sit up the retention sizes Attention times on. Even at this stage, at any customer alerts for the watchdogs. E consider email alerting which I will need my smart host details and authentication details. Andi Slack Alerts. Now I'm defining the cluster. All that's happened is the cluster's been defined. I now need to add machines to that cluster. I'll begin by clicking the create machine button within the cluster definition. Oh, select manager, Select the number of machines. Three is the minimum. Select the instant size that I'd like to use from AWS and very importantly, ensure correct. Use the correct Am I for the region. I commend side on the route device size. There we go, my three machines obviously creating. I now need to add some workers to this custom. So I go through the same process this time once again, just selecting worker. I'll just add to once again, the AM is extremely important. Will fail if we don't pick the right, Am I for a boon to machine in this case and the deployment has started. We can go and check on the bold status are going back to the clusters screen on clicking on the little three dots on the right. We get the cluster info and the events, so the basic cluster info you'll see pending their listen cluster is still in the process of being built. We kick on, the events will get a list of actions that have been completed This part of the set up of the cluster. So you can see here we've created the VPC. We've created the sub nets on We've created the Internet gateway. It's unnecessary made of us and we have no warnings of the stage. Yeah, this will then run for a while. We have one minute past waken click through. We can check the status of the machine bulls as individuals so we can check the machine info, details of the machines that we've assigned, right? Mhm Onda. See any events pertaining to the machine areas like this one on normal? Yeah. Just watch asked. The community's components are waiting for the machines to start. Go back to Custer's. Okay, right. Because we're moving ahead now. We can see we have it in progress. Five minutes in new Matt Gateway on the stage. The machines have been built on assigned. I pick up the U. S. Thank you. Yeah. There we go. Machine has been created. See the event detail and the AWS. I'd for that machine. Mhm. No speeding things up a little bit. This whole process and to end takes about fifteen minutes. Run the clock forward, you'll notice is the machines continue to bold the in progress. We'll go from in progress to ready. A soon as we got ready on all three machines, the managers on both workers way could go on and we could see that now we reached the point where the cluster itself is being configured. Mhm, mhm. And then we go. Cluster has been deployed. So once the classes deployed, we can now never get around our environment. Okay, Are cooking into configure cluster We could modify their cluster. We could get the end points for alert alert manager on See here The griffon occupying and Prometheus are still building in the background but the cluster is available on you would be able to put workloads on it the stretch to download the cube conflict so that I can put workloads on it. It's again three little dots in the right for that particular cluster. If the download cube conflict give it my password, I now have the Q conflict file necessary so that I can access that cluster Mhm all right Now that the build is fully completed, we can check out cluster info on. We can see that Allow the satellite components have been built. All the storage is there, and we have access to the CPU. I So if we click into the cluster, we can access the UCP dashboard, right? Shit. Click the signing with Detroit button to use the SSO on. We give Mary's possible to use the name once again. Thing is, an unlicensed cluster way could license at this point. Or just skip it on. There. We have the UCP dashboard. You can see that has been up for a little while. We have some data on the dashboard going back to the console. We can now go to the griffon, a data just being automatically pre configured for us. We can switch and utilized a number of different dashboards that have already been instrumented within the cluster. So, for example, communities cluster information, the name spaces, deployments, nodes. Mhm. So we look at nodes. If we could get a view of the resource is utilization of Mrs Custer is very little running in it. Yeah. General dashboard of Cuba navies cluster one of this is configurable. You can modify these for your own needs, or add your own dashboards on de scoped to the cluster. So it is available to all users who have access to this specific cluster, all right to scale the cluster on to add a notice. A simple is the process of adding a mode to the cluster, assuming we've done that in the first place. So we go to the cluster, go into the details for the cluster we select, create machine. Once again, we need to be ensure that we put the correct am I in and any other functions we like. You can create different sized machines so it could be a larger node. Could be bigger disks and you'll see that worker has been added from the provisioning state on shortly. We will see the detail off that worker as a complete to remove a note from a cluster. Once again, we're going to the cluster. We select the node would like to remove. Okay, I just hit delete On that note. Worker nodes will be removed from the cluster using according and drawing method to ensure that your workouts are not affected. Updating a cluster. When an update is available in the menu for that particular cluster, the update button will become available. And it's a simple as clicking the button, validating which release you would like to update to. In this case, the next available releases five point seven point one. Here I'm kicking the update by in the background We will coordinate. Drain each node slowly go through the process of updating it. Andi update will complete depending on what the update is as quickly as possible. Girl, we go. The notes being rebuilt in this case impacted the manager node. So one of the manager nodes is in the process of being rebuilt. In fact, to in this case, one has completed already on In a few minutes we'll see that there are great has been completed. There we go. Great. Done. Yeah. If you work loads of both using proper cloud native community standards, there will be no impact. >>Excellent. So at this point, we've now got a cluster ready to start taking our communities of workloads. He started playing or APs to that costume. So watching that video, the thing that jumped out to me at first Waas like the inputs that go into defining this workload cost of it. All right, so we have to make sure we were using on appropriate am I for that kind of defines the substrate about what we're gonna be deploying our cluster on top of. But there's very little requirements. A so far as I could tell on top of that, am I? Because Docker enterprise Container Cloud is gonna bootstrap all the components that you need. That s all we have is kind of kind of really simple bunch box that we were deploying these things on top of so one thing that didn't get dug into too much in the video. But it's just sort of implied. Bruce, maybe you can comment on this is that release that Shawn had to choose for his, uh, for his cluster in creating it. And that release was also the thing we had to touch. Wanted to upgrade part cluster. So you have really sharp eyes. You could see at the end there that when you're doing the release upgrade enlisted out a stack of components docker, engine, kubernetes, calico, aled, different bits and pieces that go into, uh, go into one of these commodity clusters that deploy. And so, as far as I can tell in that case, that's what we mean by a release. In this sense, right? It's the validated stack off container ization and orchestration components that you know we've tested out and make sure it works well, introduction environments. >>Yeah, and and And that's really the focus of our effort is to ensure that any CVS in any of the stack are taken care of that there is a fixes air documented and up streamed to the open stack community source community, um, and and that, you know, then we test for the scaling ability and the reliability in high availability configuration for the clusters themselves. The hosts of your containers. Right. And I think one of the key, uh, you know, benefits that we provide is that ability to let you know, online, high. We've got an update for you, and it's fixes something that maybe you had asked us to fix. Uh, that all comes to you online as your managing your clusters, so you don't have to think about it. It just comes as part of the product. >>You just have to click on Yes. Please give me that update. Uh, not just the individual components, but again. It's that it's that validated stack, right? Not just, you know, component X, y and Z work. But they all work together effectively Scalable security, reliably cool. Um, yeah. So at that point, once we started creating that workload child cluster, of course, we bootstrapped good old universal control plane. Doctor Enterprise. On top of that, Sean had the classic comment there, you know? Yeah. Yeah. You'll see a little warnings and errors or whatever. When you're setting up, UCP don't handle, right, Just let it do its job, and it will converge all its components, you know, after just just a minute or two. But we saw in that video, we sped things up a little bit there just we didn't wait for, you know, progress fighters to complete. But really, in real life, that whole process is that anything so spend up one of those one of those fosters so quite quite quick. >>Yeah, and and I think the the thoroughness with which it goes through its process and re tries and re tries, uh, as you know, and it was evident when we went through the initial ah video of the bootstrapping as well that the processes themselves are self healing, as they are going through. So they will try and retry and wait for the event to complete properly on. And once it's completed properly, then it will go to the next step. >>Absolutely. And the worst thing you could do is panic at the first warning and start tearing things that don't don't do that. Just don't let it let it heal. Let take care of itself. And that's the beauty of these manage solutions is that they bake in a lot of subject matter expertise, right? The decisions that are getting made by those containers is they're bootstrapping themselves, reflect the expertise of the Mirant ISS crew that has been developing this content in these two is free for years and years now, over recognizing humanities. One cool thing there that I really appreciate it actually that it adds on top of Dr Enterprise is that automatic griffon a deployment as well. So, Dr Enterprises, I think everyone knows has had, like, some very high level of statistics baked into its dashboard for years and years now. But you know our customers always wanted a double click on that right to be able to go a little bit deeper. And Griffon are really addresses that it's built in dashboards. That's what's really nice to see. >>Yeah, uh, and all of the alerts and, uh, data are actually captured in a Prometheus database underlying that you have access to so that you are allowed to add new alerts that then go out to touch slack and say hi, You need to watch your disk space on this machine or those kinds of things. Um, and and this is especially helpful for folks who you know, want to manage the application service layer but don't necessarily want to manage the operations side of the house. So it gives them a tool set that they can easily say here, Can you watch these for us? And Miran tas can actually help do that with you, So >>yeah, yeah, I mean, that's just another example of baking in that expert knowledge, right? So you can leverage that without tons and tons of a long ah, long runway of learning about how to do that sort of thing. Just get out of the box right away. There was the other thing, actually, that you could sleep by really quickly if you weren't paying close attention. But Sean mentioned it on the video. And that was how When you use dark enterprise container cloud to scale your cluster, particularly pulling a worker out, it doesn't just like Territo worker down and forget about it. Right? Is using good communities best practices to cordon and drain the No. So you aren't gonna disrupt your workloads? You're going to just have a bunch of containers instantly. Excellent crash. You could really carefully manage the migration of workloads off that cluster has baked right in tow. How? How? Document? The brass container cloud is his handling cluster scale. >>Right? And And the kubernetes, uh, scaling methodology is is he adhered to with all of the proper techniques that ensure that it will tell you. Wait, you've got a container that actually needs three, uh, three, uh, instances of itself. And you don't want to take that out, because that node, it means you'll only be able to have to. And we can't do that. We can't allow that. >>Okay, Very cool. Further thoughts on this video. So should we go to the questions. >>Let's let's go to the questions >>that people have. Uh, there's one good one here, down near the bottom regarding whether an a p I is available to do this. So in all these demos were clicking through this web. You I Yes, this is all a p. I driven. You could do all of this. You know, automate all this away is part of the CSC change. Absolutely. Um, that's kind of the point, right? We want you to be ableto spin up. Come on. I keep calling them commodity clusters. What I mean by that is clusters that you can create and throw away. You know, easily and automatically. So everything you see in these demos eyes exposed to FBI? >>Yeah. In addition, through the standard Cube cuddle, Uh, cli as well. So if you're not a programmer, but you still want to do some scripting Thio, you know, set up things and deploy your applications and things. You can use this standard tool sets that are available to accomplish that. >>There is a good question on scale here. So, like, just how many clusters and what sort of scale of deployments come this kind of support our engineers report back here that we've done in practice up to a Zeman ia's like two hundred clusters. We've deployed on this with two hundred fifty nodes in a cluster. So were, you know, like like I said, hundreds, hundreds of notes, hundreds of clusters managed by documented press container fall and then those downstream clusters, of course, subject to the usual constraints for kubernetes, right? Like default constraints with something like one hundred pods for no or something like that. There's a few different limitations of how many pods you can run on a given cluster that comes to us not from Dr Enterprise Container Cloud, but just from the underlying kubernetes distribution. >>Yeah, E. I mean, I don't think that we constrain any of the capabilities that are available in the, uh, infrastructure deliveries, uh, service within the goober Netease framework. So were, you know, But we are, uh, adhering to the standards that we would want to set to make sure that we're not overloading a node or those kinds of things, >>right. Absolutely cool. Alright. So at this point, we've got kind of a two layered our protection when we are management cluster, but we deployed in the first video. Then we use that to deploy one child clustering work, classroom, uh, for more sophisticated deployments where we might want to manage child clusters across multiple regions. We're gonna add another layer into our architectural we're gonna add in regional cluster management. So this idea you're gonna have the single management cluster that we started within the first video. On the next video, we're gonna learn how to spin up a regional clusters, each one of which would manage, for example, a different AWS uh, US region. So let me just pull out the video for that bill. We'll check it out for me. Mhm. >>Hello. In this demo, we will cover the deployment of additional regional management. Cluster will include a brief architectures of you how to set up the management environment, prepare for the deployment deployment overview and then just to prove it, to play a regional child cluster. So, looking at the overall architecture, the management cluster provides all the core functionality, including identity management, authentication, inventory and release version. ING Regional Cluster provides the specific architecture provider in this case AWS on the LCN components on the D you speak Cluster for child cluster is the cluster or clusters being deployed and managed? Okay, so why do you need a regional cluster? Different platform architectures, for example aws who have been stack even bare metal to simplify connectivity across multiple regions handle complexities like VPNs or one way connectivity through firewalls, but also help clarify availability zones. Yeah. Here we have a view of the regional cluster and how it connects to the management cluster on their components, including items like the LCN cluster Manager we also Machine Manager were held. Mandel are managed as well as the actual provider logic. Mhm. Okay, we'll begin by logging on Is the default administrative user writer. Okay, once we're in there, we'll have a look at the available clusters making sure we switch to the default project which contains the administration clusters. Here we can see the cars management cluster, which is the master controller. And you see, it only has three nodes, three managers, no workers. Okay, if we look at another regional cluster similar to what we're going to deploy now, also only has three managers once again, no workers. But as a comparison, here's a child cluster This one has three managers, but also has additional workers associate it to the cluster. All right, we need to connect. Tell bootstrap note. Preferably the same note that used to create the original management plaster. It's just on AWS, but I still want to machine. All right. A few things we have to do to make sure the environment is ready. First thing we're going to see go into route. We'll go into our releases folder where we have the kozberg struck on. This was the original bootstrap used to build the original management cluster. Yeah, we're going to double check to make sure our cube con figures there once again, the one created after the original customers created just double check. That cute conflict is the correct one. Does point to the management cluster. We're just checking to make sure that we can reach the images that everything is working. A condom. No damages waken access to a swell. Yeah. Next we're gonna edit the machine definitions. What we're doing here is ensuring that for this cluster we have the right machine definitions, including items like the am I. So that's found under the templates AWS directory. We don't need to edit anything else here. But we could change items like the size of the machines attempts. We want to use that The key items to ensure where you changed the am I reference for the junta image is the one for the region in this case AWS region for utilizing this was no construct deployment. We have to make sure we're pointing in the correct open stack images. Yeah, okay. Set the correct and my save file. Now we need to get up credentials again. When we originally created the bootstrap cluster, we got credentials from eight of the U. S. If we hadn't done this, we would need to go through the u A. W s set up. So we're just exporting the AWS access key and I d. What's important is CAAs aws enabled equals. True. Now we're sitting the region for the new regional cluster. In this case, it's Frankfurt on exporting our cube conflict that we want to use for the management cluster. When we looked at earlier Yeah, now we're exporting that. Want to call the cluster region Is Frank Foods Socrates Frankfurt yet trying to use something descriptive It's easy to identify. Yeah, and then after this, we'll just run the bootstrap script, which will complete the deployment for us. Bootstrap of the regional cluster is quite a bit quicker than the initial management clusters. There are fewer components to be deployed. Um, but to make it watchable, we've spent it up. So we're preparing our bootstrap cluster on the local bootstrap node. Almost ready on. We started preparing the instances at W s and waiting for that bastard and no to get started. Please. The best you nerd Onda. We're also starting to build the actual management machines they're now provisioning on. We've reached the point where they're actually starting to deploy. Dr. Enterprise, this is probably the longest face. Yeah, seeing the second that all the nerds will go from the player deployed. Prepare, prepare. Yeah, You'll see their status changes updates. He was the first night ready. Second, just applying second already. Both my time. No waiting from home control. Let's become ready. Removing cluster the management cluster from the bootstrap instance into the new cluster running the date of the U. S. All my stay. Ah, now we're playing Stockland. Switch over is done on. Done. Now I will build a child cluster in the new region very, very quickly to find the cluster will pick. Our new credential has shown up. We'll just call it Frankfurt for simplicity a key and customs to find. That's the machine. That cluster stop with three managers. Set the correct Am I for the region? Yeah, Do the same to add workers. There we go test the building. Yeah. Total bill of time Should be about fifteen minutes. Concedes in progress. It's going to expect this up a little bit. Check the events. We've created all the dependencies, machine instances, machines, a boat shortly. We should have a working cluster in Frankfurt region. Now almost a one note is ready from management. Two in progress. Yeah, on we're done. Clusters up and running. Yeah. >>Excellent. So at this point, we've now got that three tier structure that we talked about before the video. We got that management cluster that we do strapped in the first video. Now we have in this example to different regional clustering one in Frankfurt, one of one management was two different aws regions. And sitting on that you can do Strap up all those Doctor enterprise costumes that we want for our work clothes. >>Yeah, that's the key to this is to be able to have co resident with your actual application service enabled clusters the management co resident with it so that you can, you know, quickly access that he observation Elson Surfboard services like the graph, Ana and that sort of thing for your particular region. A supposed to having to lug back into the home. What did you call it when we started >>the mothership? >>The mothership. Right. So we don't have to go back to the mother ship. We could get >>it locally. Yeah, when, like to that point of aggregating things under a single pane of glass? That's one thing that again kind of sailed by in the demo really quickly. But you'll notice all your different clusters were on that same cluster. Your pain on your doctor Enterprise Container Cloud management. Uh, court. Right. So both your child clusters for running workload and your regional clusters for bootstrapping. Those child clusters were all listed in the same place there. So it's just one pane of glass to go look for, for all of your clusters, >>right? And, uh, this is kind of an important point. I was, I was realizing, as we were going through this. All of the mechanics are actually identical between the bootstrapped cluster of the original services and the bootstrapped cluster of the regional services. It's the management layer of everything so that you only have managers, you don't have workers and that at the child cluster layer below the regional or the management cluster itself, that's where you have the worker nodes. And those are the ones that host the application services in that three tiered architecture that we've now defined >>and another, you know, detail for those that have sharp eyes. In that video, you'll notice when deploying a child clusters. There's not on Lee. A minimum of three managers for high availability management cluster. You must have at least two workers that's just required for workload failure. It's one of those down get out of work. They could potentially step in there, so your minimum foot point one of these child clusters is fine. Violence and scalable, obviously, from a >>That's right. >>Let's take a quick peek of the questions here, see if there's anything we want to call out, then we move on to our last want to my last video. There's another question here about, like where these clusters can live. So again, I know these examples are very aws heavy. Honestly, it's just easy to set up down on the other us. We could do things on bare metal and, uh, open stack departments on Prem. That's what all of this still works in exactly the same way. >>Yeah, the, uh, key to this, especially for the the, uh, child clusters, is the provision hers? Right? See you establish on AWS provision or you establish a bare metal provision or you establish a open stack provision. Or and eventually that list will include all of the other major players in the cloud arena. But you, by selecting the provision or within your management interface, that's where you decide where it's going to be hosted, where the child cluster is to be hosted. >>Speaking off all through a child clusters. Let's jump into our last video in the Siri's, where we'll see how to spin up a child cluster on bare metal. >>Hello. This demo will cover the process of defining bare metal hosts and then review the steps of defining and deploying a bare metal based doctor enterprise cluster. So why bare metal? Firstly, it eliminates hyper visor overhead with performance boost of up to thirty percent. Provides direct access to GP use, prioritize for high performance wear clothes like machine learning and AI, and supports high performance workloads like network functions, virtualization. It also provides a focus on on Prem workloads, simplifying and ensuring we don't need to create the complexity of adding another opera visor. Lay it between so continue on the theme Why Communities and bare metal again Hyper visor overhead. Well, no virtualization overhead. Direct access to hardware items like F p G A s G p us. We can be much more specific about resource is required on the nodes. No need to cater for additional overhead. Uh, we can handle utilization in the scheduling. Better Onda we increase the performances and simplicity of the entire environment as we don't need another virtualization layer. Yeah, In this section will define the BM hosts will create a new project will add the bare metal hosts, including the host name. I put my credentials I pay my address the Mac address on then provide a machine type label to determine what type of machine it is for later use. Okay, let's get started. So well again. Was the operator thing. We'll go and we'll create a project for our machines to be a member off helps with scoping for later on for security. I begin the process of adding machines to that project. Yeah. So the first thing we had to be in post, Yeah, many of the machine A name. Anything you want, que experimental zero one. Provide the IAP my user name type my password. Okay. On the Mac address for the common interface with the boot interface and then the i p m I i p address These machines will be at the time storage worker manager. He's a manager. Yeah, we're gonna add a number of other machines on will. Speed this up just so you could see what the process looks like in the future. Better discovery will be added to the product. Okay. Okay. Getting back there we have it are Six machines have been added, are busy being inspected, being added to the system. Let's have a look at the details of a single note. Yeah, you can see information on the set up of the node. Its capabilities? Yeah. As well as the inventory information about that particular machine. I see. Okay, let's go and create the cluster. Yeah, So we're going to deploy a bare metal child cluster. The process we're going to go through is pretty much the same as any other child cluster. So we'll credit custom. We'll give it a name, but if it were selecting bare metal on the region, we're going to select the version we want to apply. No way. We're going to add this search keys. If we hope we're going to give the load. Balancer host I p that we'd like to use out of dress range on update the address range that we want to use for the cluster. Check that the sea ideal blocks for the Cuban ladies and tunnels are what we want them to be. Enable disabled stack light. Yeah, and soothe stack light settings to find the cluster. And then, as for any other machine, we need to add machines to the cluster. Here. We're focused on building communities clusters, so we're gonna put the count of machines. You want managers? We're gonna pick the label type manager and create three machines is the manager for the Cuban eighties. Casting Okay thing. We're having workers to the same. It's a process. Just making sure that the worker label host level are I'm sorry. On when Wait for the machines to deploy. Let's go through the process of putting the operating system on the notes validating and operating system deploying doctor identifies Make sure that the cluster is up and running and ready to go. Okay, let's review the bold events waken See the machine info now populated with more information about the specifics of things like storage and of course, details of a cluster etcetera. Yeah, yeah, well, now watch the machines go through the various stages from prepared to deploy on what's the cluster build? And that brings us to the end of this particular demo. You can see the process is identical to that of building a normal child cluster we got our complaint is complete. >>All right, so there we have it, deploying a cluster to bare metal. Much the same is how we did for AWS. I guess maybe the biggest different stepwise there is there is that registration face first, right? So rather than just using AWS financials toe magically create PM's in the cloud. You got a point out all your bare metal servers to Dr Enterprise between the cloud and they really come in, I guess three profiles, right? You got your manager profile with a profile storage profile which has been labeled as allocate. Um, crossword cluster has appropriate, >>right? And And I think that the you know, the key differentiator here is that you have more physical control over what, uh, attributes that love your cat, by the way, uh, where you have the different attributes of a server of physical server. So you can, uh, ensure that the SSD configuration on the storage nodes is gonna be taken advantage of in the best way the GP use on the worker nodes and and that the management layer is going to have sufficient horsepower to, um, spin up to to scale up the the environments, as required. One of the things I wanted to mention, though, um, if I could get this out without the choking much better. Um, is that Ah, hey, mentioned the load balancer and I wanted to make sure in defining the load balancer and the load balancer ranges. Um, that is for the top of the the cluster itself. That's the operations of the management, uh, layer integrating with your systems internally to be able to access the the Cube Can figs. I I p address the, uh, in a centralized way. It's not the load balancer that's working within the kubernetes cluster that you are deploying. That's still cube proxy or service mesh, or however you're intending to do it. So, um, it's kind of an interesting step that your initial step in building this, um and we typically use things like metal L B or in gen X or that kind of thing is to establish that before we deploy this bear mental cluster so that it can ride on top of that for the tips and things. >>Very cool. So any other thoughts on what we've seen so far today? Bruce, we've gone through all the different layers. Doctor enterprise container clouds in these videos from our management are regional to our clusters on aws hand bear amount, Of course, with his dad is still available. Closing thoughts before we take just a very short break and run through these demos again. >>You know, I've been very exciting. Ah, doing the presentation with you. I'm really looking forward to doing it the second time, so that we because we've got a good rhythm going about this kind of thing. So I'm looking forward to doing that. But I think that the key elements of what we're trying to convey to the folks out there in the audience that I hope you've gotten out of it is that will that this is an easy enough process that if you follow the step by steps going through the documentation that's been put out in the chat, um, that you'll be able to give this a go yourself, Um, and you don't have to limit yourself toe having physical hardware on prim to try it. You could do it in a ws as we've shown you today. And if you've got some fancy use cases like, uh, you you need a Hadoop And and, uh, you know, cloud oriented ai stuff that providing a bare metal service helps you to get there very fast. So right. Thank you. It's been a pleasure. >>Yeah, thanks everyone for coming out. So, like I said we're going to take a very short, like, three minute break here. Uh, take the opportunity to let your colleagues know if they were in another session or they didn't quite make it to the beginning of this session. Or if you just want to see these demos again, we're going to kick off this demo. Siri's again in just three minutes at ten. Twenty five a. M. Pacific time where we will see all this great stuff again. Let's take a three minute break. I'll see you all back here in just two minutes now, you know. Okay, folks, that's the end of our extremely short break. We'll give people just maybe, like one more minute to trickle in if folks are interested in coming on in and jumping into our demo. Siri's again. Eso For those of you that are just joining us now I'm Bill Mills. I head up curriculum development for the training team here. Moran Tous on Joining me for this session of demos is Bruce. Don't you go ahead and introduce yourself doors, who is still on break? That's cool. We'll give Bruce a minute or two to get back while everyone else trickles back in. There he is. Hello, Bruce. >>How'd that go for you? Okay, >>Very well. So let's kick off our second session here. I e just interest will feel for you. Thio. Let it run over here. >>Alright. Hi. Bruce Matthews here. I'm the Western Regional Solutions architect for Marantz. Use A I'm the one with the gray hair and the glasses. Uh, the handsome one is Bill. So, uh, Bill, take it away. >>Excellent. So over the next hour or so, we've got a Siris of demos that's gonna walk you through your first steps with Dr Enterprise Container Cloud Doctor Enterprise Container Cloud is, of course, Miranda's brand new offering from bootstrapping kubernetes clusters in AWS bare metal open stack. And for the providers in the very near future. So we we've got, you know, just just over an hour left together on this session, uh, if you joined us at the top of the hour back at nine. A. M. Pacific, we went through these demos once already. Let's do them again for everyone else that was only able to jump in right now. Let's go. Our first video where we're gonna install Dr Enterprise container cloud for the very first time and use it to bootstrap management. Cluster Management Cluster, as I like to describe it, is our mother ship that's going to spin up all the other kubernetes clusters, Doctor Enterprise clusters that we're gonna run our workloads on. So I'm gonna do >>I'm so excited. I can hardly wait. >>Let's do it all right to share my video out here. Yeah, let's do it. >>Good day. The focus for this demo will be the initial bootstrap of the management cluster on the first regional clusters. To support AWS deployments, the management cluster provides the core functionality, including identity management, authentication, infantry release version. The regional cluster provides the specific architecture provided in this case AWS and the Elsom components on the UCP cluster Child cluster is the cluster or clusters being deployed and managed. The deployment is broken up into five phases. The first phase is preparing a bootstrap note on its dependencies on handling the download of the bridge struck tools. The second phase is obtaining America's license file. Third phase. Prepare the AWS credentials instead of the ideas environment, the fourth configuring the deployment, defining things like the machine types on the fifth phase, Run the bootstrap script and wait for the deployment to complete. Okay, so here we're sitting up the strap node. Just checking that it's clean and clear and ready to go there. No credentials already set up on that particular note. Now, we're just checking through aws to make sure that the account we want to use we have the correct credentials on the correct roles set up on validating that there are no instances currently set up in easy to instance, not completely necessary, but just helps keep things clean and tidy when I am perspective. Right. So next step, we're just gonna check that we can from the bootstrap note, reach more antis, get to the repositories where the various components of the system are available. They're good. No areas here. Yeah, right now we're going to start sitting at the bootstrap note itself. So we're downloading the cars release, get get cars, script, and then next we're going to run it. Yeah, I've been deployed changing into that big struck folder, just making see what's there right now we have no license file, so we're gonna get the license filed. Okay? Get the license file through more antis downloads site signing up here, downloading that license file and putting it into the Carisbrook struck folder. Okay, since we've done that, we can now go ahead with the rest of the deployment. Yeah, see what the follow is there? Uh huh. Once again, checking that we can now reach E C two, which is extremely important for the deployment. Just validation steps as we move through the process. Alright. Next big step is violating all of our AWS credentials. So the first thing is, we need those route credentials which we're going to export on the command line. This is to create the necessary bootstrap user on AWS credentials for the completion off the deployment we're now running in AWS policy create. So it is part of that is creating our food trucks script. Creating this through policy files onto the AWS, just generally preparing the environment using a cloud formation script, you'll see in a second, I'll give a new policy confirmations just waiting for it to complete. And there is done. It's gonna have a look at the AWS console. You can see that we're creative completed. Now we can go and get the credentials that we created. Good day. I am console. Go to the new user that's being created. We'll go to the section on security credentials and creating new keys. Download that information media access Key I. D and the secret access key, but usually then exported on the command line. Okay, Couple of things to Notre. Ensure that you're using the correct AWS region on ensure that in the conflict file you put the correct Am I in for that region? I'm sure you have it together in a second. Okay, thanks. Is key. So you could X key Right on. Let's kick it off. So this process takes between thirty and forty five minutes. Handles all the AWS dependencies for you. Um, as we go through, the process will show you how you can track it. Andi will start to see things like the running instances being created on the AWS side. The first phase off this whole process happening in the background is the creation of a local kind based bootstrapped cluster on the bootstrap node that clusters then used to deploy and manage all the various instances and configurations within AWS at the end of the process. That cluster is copied into the new cluster on AWS and then shut down that local cluster essentially moving itself over. Yeah, okay. Local clusters boat. Just waiting for the various objects to get ready. Standard communities objects here. Yeah, you mentioned Yeah. So we've speed up this process a little bit just for demonstration purposes. Okay, there we go. So first note is being built the bastion host just jump box that will allow us access to the entire environment. Yeah, In a few seconds, we'll see those instances here in the US console on the right. Um, the failures that you're seeing around failed to get the I. P for Bastian is just the weight state while we wait for AWS to create the instance. Okay. Yeah. Beauty there. Movies. Okay, sketch. Hello? Yeah, Okay. Okay. On. There we go. Question host has been built on three instances for the management clusters have now been created. Okay, We're going through the process of preparing. Those nodes were now copying everything over. See that scaling up of controllers in the big strapped cluster? It's indicating that we're starting all of the controllers in the new question. Almost there. Right? Okay. Just waiting for key. Clark. Uh huh. So finish up. Yeah. No. Now we're shutting down. Control this on the local bootstrap node on preparing our I. D. C configuration, fourth indication. So once this is completed, the last phase will be to deploy stack light into the new cluster, that glass on monitoring tool set, Then we go stack like deployment has started. Mhm. Coming to the end of the deployment mountain. Yeah, they were cut final phase of the deployment. And we are done. Yeah, you'll see. At the end, they're providing us the details of you. I log in. So there's a key Clark log in. Uh, you can modify that initial default possible is part of the configuration set up where they were in the documentation way. Go Councils up way can log in. Yeah. Yeah. Thank you very much for watching. >>All right, so at this point, what we have we got our management cluster spun up, ready to start creating work clusters. So just a couple of points to clarify there to make sure everyone caught that, uh, as advertised. That's darker. Enterprise container cloud management cluster. That's not rework loans. are gonna go right? That is the tool and you're gonna use to start spinning up downstream commodity documentary prize clusters for bootstrapping record too. >>And the seed host that were, uh, talking about the kind cluster dingy actually doesn't have to exist after the bootstrap succeeds eso It's sort of like, uh, copies head from the seed host Toothy targets in AWS spins it up it then boots the the actual clusters and then it goes away too, because it's no longer necessary >>so that bootstrapping know that there's not really any requirements, Hardly on that, right. It just has to be able to reach aws hit that Hit that a p I to spin up those easy to instances because, as you just said, it's just a kubernetes in docker cluster on that piece. Drop note is just gonna get torn down after the set up finishes on. You no longer need that. Everything you're gonna do, you're gonna drive from the single pane of glass provided to you by your management cluster Doctor enterprise Continue cloud. Another thing that I think is sort of interesting their eyes that the convict is fairly minimal. Really? You just need to provide it like aws regions. Um, am I? And that's what is going to spin up that spending that matter faster. >>Right? There is a mammal file in the bootstrap directory itself, and all of the necessary parameters that you would fill in have default set. But you have the option then of going in and defining a different Am I different for a different region, for example? Oh, are different. Size of instance from AWS. >>One thing that people often ask about is the cluster footprint. And so that example you saw they were spitting up a three manager, um, managing cluster as mandatory, right? No single manager set up at all. We want high availability for doctrine Enterprise Container Cloud management. Like so again, just to make sure everyone sort of on board with the life cycle stage that we're at right now. That's the very first thing you're going to do to set up Dr Enterprise Container Cloud. You're going to do it. Hopefully exactly once. Right now, you've got your management cluster running, and they're gonna use that to spend up all your other work clusters Day today has has needed How do we just have a quick look at the questions and then lets take a look at spinning up some of those child clusters. >>Okay, e think they've actually been answered? >>Yeah, for the most part. One thing I'll point out that came up again in the Dail, helpfully pointed out earlier in surgery, pointed out again, is that if you want to try any of the stuff yourself, it's all of the dogs. And so have a look at the chat. There's a links to instructions, so step by step instructions to do each and every thing we're doing here today yourself. I really encourage you to do that. Taking this out for a drive on your own really helps internalizing communicate these ideas after the after launch pad today, Please give this stuff try on your machines. Okay, So at this point, like I said, we've got our management cluster. We're not gonna run workloads there that we're going to start creating child clusters. That's where all of our work and we're gonna go. That's what we're gonna learn how to do in our next video. Cue that up for us. >>I so love Shawn's voice. >>Wasn't that all day? >>Yeah, I watched him read the phone book. >>All right, here we go. Let's now that we have our management cluster set up, let's create a first child work cluster. >>Hello. In this demo, we will cover the deployment experience of creating a new child cluster the scaling of the cluster on how to update the cluster. When a new version is available, we begin the process by logging onto the you I as a normal user called Mary. Let's go through the navigation of the u I. So you can switch Project Mary only has access to development. Uh huh. Get a list of the available projects that you have access to. What clusters have been deployed at the moment there. Man. Yes, this H keys, Associate ID for Mary into her team on the cloud credentials that allow you to create or access the various clouds that you can deploy clusters to finally different releases that are available to us. We can switch from dark mode to light mode, depending on your preferences. Right. Let's now set up some ssh keys for Mary so she can access the notes and machines again. Very simply, had Mississippi key give it a name. We copy and paste our public key into the upload key block. Or we can upload the key if we have the file available on our machine. A very simple process. So to create a new cluster, we define the cluster ad management nodes and add worker nodes to the cluster. Yeah, again, very simply, we got the clusters tab we had to create cluster button. Give the cluster name. Yeah, Andi, select the provider. We only have access to AWS in this particular deployment, so we'll stick to AWS. What's like the region in this case? US West one released version five point seven is the current release Onda Attach. Mary's Key is necessary key. We can then check the rest of the settings, confirming the provider any kubernetes c r D a r i p address information. We can change this. Should we wish to? We'll leave it default for now and then what components of stack light? I would like to deploy into my custom for this. I'm enabling stack light on logging, and I consider the retention sizes attention times on. Even at this stage, add any custom alerts for the watchdogs. Consider email alerting which I will need my smart host. Details and authentication details. Andi Slack Alerts. Now I'm defining the cluster. All that's happened is the cluster's been defined. I now need to add machines to that cluster. I'll begin by clicking the create machine button within the cluster definition. Oh, select manager, Select the number of machines. Three is the minimum. Select the instant size that I'd like to use from AWS and very importantly, ensure correct. Use the correct Am I for the region. I convinced side on the route. Device size. There we go. My three machines are busy creating. I now need to add some workers to this cluster. So I go through the same process this time once again, just selecting worker. I'll just add to once again the am I is extremely important. Will fail if we don't pick the right. Am I for a Clinton machine? In this case and the deployment has started, we can go and check on the bold status are going back to the clusters screen on clicking on the little three dots on the right. We get the cluster info and the events, so the basic cluster info you'll see pending their listen. Cluster is still in the process of being built. We kick on, the events will get a list of actions that have been completed This part of the set up of the cluster. So you can see here. We've created the VPC. We've created the sub nets on. We've created the Internet Gateway. It's unnecessary made of us. And we have no warnings of the stage. Okay, this will then run for a while. We have one minute past. We can click through. We can check the status of the machine balls as individuals so we can check the machine info, details of the machines that we've assigned mhm and see any events pertaining to the machine areas like this one on normal. Yeah. Just last. The community's components are waiting for the machines to start. Go back to customers. Okay, right. Because we're moving ahead now. We can see we have it in progress. Five minutes in new Matt Gateway. And at this stage, the machines have been built on assigned. I pick up the U S. Yeah, yeah, yeah. There we go. Machine has been created. See the event detail and the AWS. I'd for that machine. No speeding things up a little bit this whole process and to end takes about fifteen minutes. Run the clock forward, you'll notice is the machines continue to bold the in progress. We'll go from in progress to ready. A soon as we got ready on all three machines, the managers on both workers way could go on and we could see that now we reached the point where the cluster itself is being configured mhm and then we go. Cluster has been deployed. So once the classes deployed, we can now never get around. Our environment are looking into configure cluster. We could modify their cluster. We could get the end points for alert Alert Manager See here the griffon occupying and Prometheus are still building in the background but the cluster is available on You would be able to put workloads on it at this stage to download the cube conflict so that I can put workloads on it. It's again the three little dots in the right for that particular cluster. If the download cube conflict give it my password, I now have the Q conflict file necessary so that I can access that cluster. All right, Now that the build is fully completed, we can check out cluster info on. We can see that all the satellite components have been built. All the storage is there, and we have access to the CPU. I. So if we click into the cluster, we can access the UCP dashboard, click the signing with the clock button to use the SSO. We give Mary's possible to use the name once again. Thing is an unlicensed cluster way could license at this point. Or just skip it on. Do we have the UCP dashboard? You could see that has been up for a little while. We have some data on the dashboard going back to the console. We can now go to the griffon. A data just been automatically pre configured for us. We can switch and utilized a number of different dashboards that have already been instrumented within the cluster. So, for example, communities cluster information, the name spaces, deployments, nodes. Um, so we look at nodes. If we could get a view of the resource is utilization of Mrs Custer is very little running in it. Yeah, a general dashboard of Cuba Navies cluster. What If this is configurable, you can modify these for your own needs, or add your own dashboards on de scoped to the cluster. So it is available to all users who have access to this specific cluster. All right to scale the cluster on to add a No. This is simple. Is the process of adding a mode to the cluster, assuming we've done that in the first place. So we go to the cluster, go into the details for the cluster we select, create machine. Once again, we need to be ensure that we put the correct am I in and any other functions we like. You can create different sized machines so it could be a larger node. Could be bigger group disks and you'll see that worker has been added in the provisioning state. On shortly, we will see the detail off that worker as a complete to remove a note from a cluster. Once again, we're going to the cluster. We select the node we would like to remove. Okay, I just hit delete On that note. Worker nodes will be removed from the cluster using according and drawing method to ensure that your workloads are not affected. Updating a cluster. When an update is available in the menu for that particular cluster, the update button will become available. And it's a simple as clicking the button validating which release you would like to update to this case. This available releases five point seven point one give you I'm kicking the update back in the background. We will coordinate. Drain each node slowly, go through the process of updating it. Andi update will complete depending on what the update is as quickly as possible. Who we go. The notes being rebuilt in this case impacted the manager node. So one of the manager nodes is in the process of being rebuilt. In fact, to in this case, one has completed already. Yeah, and in a few minutes, we'll see that the upgrade has been completed. There we go. Great. Done. If you work loads of both using proper cloud native community standards, there will be no impact. >>All right, there. We haven't. We got our first workload cluster spun up and managed by Dr Enterprise Container Cloud. So I I loved Shawn's classic warning there. When you're spinning up an actual doctor enterprise deployment, you see little errors and warnings popping up. Just don't touch it. Just leave it alone and let Dr Enterprises self healing properties take care of all those very transient temporary glitches, resolve themselves and leave you with a functioning workload cluster within victims. >>And now, if you think about it that that video was not very long at all. And that's how long it would take you if someone came into you and said, Hey, can you spend up a kubernetes cluster for development development A. Over here, um, it literally would take you a few minutes to thio Accomplish that. And that was with a W s. Obviously, which is sort of, ah, transient resource in the cloud. But you could do exactly the same thing with resource is on Prem or resource is, um physical resource is and will be going through that later in the process. >>Yeah, absolutely one thing that is present in that demo, but that I like to highlight a little bit more because it just kind of glides by Is this notion of, ah, cluster release? So when Sean was creating that cluster, and also when when he was upgrading that cluster, he had to choose a release. What does that didn't really explain? What does that mean? Well, in Dr Enterprise Container Cloud, we have released numbers that capture the entire staff of container ization tools that will be deploying to that workload costume. So that's your version of kubernetes sed cor DNs calico. Doctor Engineer. All the different bits and pieces that not only work independently but are validated toe work together as a staff appropriate for production, humanities, adopted enterprise environments. >>Yep. From the bottom of the stack to the top, we actually test it for scale. Test it for CVS, test it for all of the various things that would, you know, result in issues with you running the application services. And I've got to tell you from having, you know, managed kubernetes deployments and things like that that if you're the one doing it yourself, it can get rather messy. Eso This makes it easy. >>Bruce, you were staying a second ago. They I'll take you at least fifteen minutes to install your release. Custer. Well, sure, but what would all the other bits and pieces you need toe? Not just It's not just about pressing the button to install it, right? It's making the right decision. About what components work? Well, our best tested toe be successful working together has a staff? Absolutely. We this release mechanism and Dr Enterprise Container Cloud. Let's just kind of package up that expert knowledge and make it available in a really straightforward, fashionable species. Uh, pre Confederate release numbers and Bruce is you're pointing out earlier. He's got delivered to us is updates kind of transparent period. When when? When Sean wanted toe update that cluster, he created little update. Custer Button appeared when an update was available. All you gotta do is click. It tells you what Here's your new stack of communities components. It goes ahead. And the straps those components for you? >>Yeah, it actually even displays at the top of the screen. Ah, little header That says you've got an update available. Do you want me to apply? It s o >>Absolutely. Another couple of cool things. I think that are easy to miss in that demo was I really like the on board Bafana that comes along with this stack. So we've been Prometheus Metrics and Dr Enterprise for years and years now. They're very high level. Maybe in in previous versions of Dr Enterprise having those detailed dashboards that Ravana provides, I think that's a great value out there. People always wanted to be ableto zoom in a little bit on that, uh, on those cluster metrics, you're gonna provides them out of the box for us. Yeah, >>that was Ah, really, uh, you know, the joining of the Miranda's and Dr teams together actually spawned us to be able to take the best of what Morantes had in the open stack environment for monitoring and logging and alerting and to do that integration in in a very short period of time so that now we've got it straight across the board for both the kubernetes world and the open stack world. Using the same tool sets >>warm. One other thing I wanna point out about that demo that I think there was some questions about our last go around was that demo was all about creating a managed workplace cluster. So the doctor enterprise Container Cloud managers were using those aws credentials provisioned it toe actually create new e c two instances installed Docker engine stalled. Doctor Enterprise. Remember all that stuff on top of those fresh new VM created and managed by Dr Enterprise contain the cloud. Nothing unique about that. AWS deployments do that on open staff doing on Parramatta stuff as well. Um, there's another flavor here, though in a way to do this for all of our long time doctor Enterprise customers that have been running Doctor Enterprise for years and years. Now, if you got existing UCP points existing doctor enterprise deployments, you plug those in to Dr Enterprise Container Cloud, uh, and use darker enterprise between the cloud to manage those pre existing Oh, working clusters. You don't always have to be strapping straight from Dr Enterprises. Plug in external clusters is bad. >>Yep, the the Cube config elements of the UCP environment. The bundling capability actually gives us a very straightforward methodology. And there's instructions on our website for exactly how thio, uh, bring in import and you see p cluster. Um so it it makes very convenient for our existing customers to take advantage of this new release. >>Absolutely cool. More thoughts on this wonders if we jump onto the next video. >>I think we should move press on >>time marches on here. So let's Let's carry on. So just to recap where we are right now, first video, we create a management cluster. That's what we're gonna use to create All our downstream were closed clusters, which is what we did in this video. Let's maybe the simplest architectures, because that's doing everything in one region on AWS pretty common use case because we want to be able to spin up workload clusters across many regions. And so to do that, we're gonna add a third layer in between the management and work cluster layers. That's gonna be our regional cluster managers. So this is gonna be, uh, our regional management cluster that exists per region that we're going to manage those regional managers will be than the ones responsible for spending part clusters across all these different regions. Let's see it in action in our next video. >>Hello. In this demo, we will cover the deployment of additional regional management. Cluster will include a brief architectural overview, how to set up the management environment, prepare for the deployment deployment overview, and then just to prove it, to play a regional child cluster. So looking at the overall architecture, the management cluster provides all the core functionality, including identity management, authentication, inventory and release version. ING Regional Cluster provides the specific architecture provider in this case, AWS on the L C M components on the d you speak cluster for child cluster is the cluster or clusters being deployed and managed? Okay, so why do you need original cluster? Different platform architectures, for example AWS open stack, even bare metal to simplify connectivity across multiple regions handle complexities like VPNs or one way connectivity through firewalls, but also help clarify availability zones. Yeah. Here we have a view of the regional cluster and how it connects to the management cluster on their components, including items like the LCN cluster Manager. We also machine manager. We're hell Mandel are managed as well as the actual provider logic. Okay, we'll begin by logging on Is the default administrative user writer. Okay, once we're in there, we'll have a look at the available clusters making sure we switch to the default project which contains the administration clusters. Here we can see the cars management cluster, which is the master controller. When you see it only has three nodes, three managers, no workers. Okay, if we look at another regional cluster, similar to what we're going to deploy now. Also only has three managers once again, no workers. But as a comparison is a child cluster. This one has three managers, but also has additional workers associate it to the cluster. Yeah, all right, we need to connect. Tell bootstrap note, preferably the same note that used to create the original management plaster. It's just on AWS, but I still want to machine Mhm. All right, A few things we have to do to make sure the environment is ready. First thing we're gonna pseudo into route. I mean, we'll go into our releases folder where we have the car's boot strap on. This was the original bootstrap used to build the original management cluster. We're going to double check to make sure our cube con figures there It's again. The one created after the original customers created just double check. That cute conflict is the correct one. Does point to the management cluster. We're just checking to make sure that we can reach the images that everything's working, condone, load our images waken access to a swell. Yeah, Next, we're gonna edit the machine definitions what we're doing here is ensuring that for this cluster we have the right machine definitions, including items like the am I So that's found under the templates AWS directory. We don't need to edit anything else here, but we could change items like the size of the machines attempts we want to use but the key items to ensure where changed the am I reference for the junta image is the one for the region in this case aws region of re utilizing. This was an open stack deployment. We have to make sure we're pointing in the correct open stack images. Yeah, yeah. Okay. Sit the correct Am I save the file? Yeah. We need to get up credentials again. When we originally created the bootstrap cluster, we got credentials made of the U. S. If we hadn't done this, we would need to go through the u A. W s set up. So we just exporting AWS access key and I d. What's important is Kaz aws enabled equals. True. Now we're sitting the region for the new regional cluster. In this case, it's Frankfurt on exporting our Q conflict that we want to use for the management cluster when we looked at earlier. Yeah, now we're exporting that. Want to call? The cluster region is Frankfurt's Socrates Frankfurt yet trying to use something descriptive? It's easy to identify. Yeah, and then after this, we'll just run the bootstrap script, which will complete the deployment for us. Bootstrap of the regional cluster is quite a bit quicker than the initial management clusters. There are fewer components to be deployed, but to make it watchable, we've spent it up. So we're preparing our bootstrap cluster on the local bootstrap node. Almost ready on. We started preparing the instances at us and waiting for the past, you know, to get started. Please the best your node, onda. We're also starting to build the actual management machines they're now provisioning on. We've reached the point where they're actually starting to deploy Dr Enterprise, he says. Probably the longest face we'll see in a second that all the nodes will go from the player deployed. Prepare, prepare Mhm. We'll see. Their status changes updates. It was the first word ready. Second, just applying second. Grady, both my time away from home control that's become ready. Removing cluster the management cluster from the bootstrap instance into the new cluster running a data for us? Yeah, almost a on. Now we're playing Stockland. Thanks. Whichever is done on Done. Now we'll build a child cluster in the new region very, very quickly. Find the cluster will pick our new credential have shown up. We'll just call it Frankfurt for simplicity. A key on customers to find. That's the machine. That cluster stop with three manages set the correct Am I for the region? Yeah, Same to add workers. There we go. That's the building. Yeah. Total bill of time. Should be about fifteen minutes. Concedes in progress. Can we expect this up a little bit? Check the events. We've created all the dependencies, machine instances, machines. A boat? Yeah. Shortly. We should have a working caster in the Frankfurt region. Now almost a one note is ready from management. Two in progress. On we're done. Trust us up and running. >>Excellent. There we have it. We've got our three layered doctor enterprise container cloud structure in place now with our management cluster in which we scrap everything else. Our regional clusters which manage individual aws regions and child clusters sitting over depends. >>Yeah, you can. You know you can actually see in the hierarchy the advantages that that presents for folks who have multiple locations where they'd like a geographic locations where they'd like to distribute their clusters so that you can access them or readily co resident with your development teams. Um and, uh, one of the other things I think that's really unique about it is that we provide that same operational support system capability throughout. So you've got stack light monitoring the stack light that's monitoring the stack light down to the actual child clusters that they have >>all through that single pane of glass that shows you all your different clusters, whether their workload cluster like what the child clusters or usual clusters from managing different regions. Cool. Alright, well, time marches on your folks. We've only got a few minutes left and I got one more video in our last video for the session. We're gonna walk through standing up a child cluster on bare metal. So so far, everything we've seen so far has been aws focus. Just because it's kind of easy to make that was on AWS. We don't want to leave you with the impression that that's all we do, we're covering AWS bare metal and open step deployments as well documented Craftsman Cloud. Let's see it in action with a bare metal child cluster. >>We are on the home stretch, >>right. >>Hello. This demo will cover the process of defining bare metal hosts and then review the steps of defining and deploying a bare metal based doctor enterprise cluster. Yeah, so why bare metal? Firstly, it eliminates hyper visor overhead with performance boost of up to thirty percent provides direct access to GP use, prioritize for high performance wear clothes like machine learning and AI, and support high performance workouts like network functions, virtualization. It also provides a focus on on Prem workloads, simplifying and ensuring we don't need to create the complexity of adding another hyper visor layer in between. So continuing on the theme Why communities and bare metal again Hyper visor overhead. Well, no virtualization overhead. Direct access to hardware items like F p g A s G p, us. We can be much more specific about resource is required on the nodes. No need to cater for additional overhead. We can handle utilization in the scheduling better Onda. We increase the performance and simplicity of the entire environment as we don't need another virtualization layer. Yeah, In this section will define the BM hosts will create a new project. Will add the bare metal hosts, including the host name. I put my credentials. I pay my address, Mac address on, then provide a machine type label to determine what type of machine it is. Related use. Okay, let's get started Certain Blufgan was the operator thing. We'll go and we'll create a project for our machines to be a member off. Helps with scoping for later on for security. I begin the process of adding machines to that project. Yeah. Yeah. So the first thing we had to be in post many of the machine a name. Anything you want? Yeah, in this case by mental zero one. Provide the IAP My user name. Type my password? Yeah. On the Mac address for the active, my interface with boot interface and then the i p m i P address. Yeah, these machines. We have the time storage worker manager. He's a manager. We're gonna add a number of other machines on will speed this up just so you could see what the process. Looks like in the future, better discovery will be added to the product. Okay, Okay. Getting back there. We haven't Are Six machines have been added. Are busy being inspected, being added to the system. Let's have a look at the details of a single note. Mhm. We can see information on the set up of the node. Its capabilities? Yeah. As well as the inventory information about that particular machine. Okay, it's going to create the cluster. Mhm. Okay, so we're going to deploy a bare metal child cluster. The process we're going to go through is pretty much the same as any other child cluster. So credit custom. We'll give it a name. Thank you. But he thought were selecting bare metal on the region. We're going to select the version we want to apply on. We're going to add this search keys. If we hope we're going to give the load. Balancer host I p that we'd like to use out of the dress range update the address range that we want to use for the cluster. Check that the sea idea blocks for the communities and tunnels are what we want them to be. Enable disabled stack light and said the stack light settings to find the cluster. And then, as for any other machine, we need to add machines to the cluster. Here we're focused on building communities clusters. So we're gonna put the count of machines. You want managers? We're gonna pick the label type manager on create three machines. Is a manager for the Cuban a disgusting? Yeah, they were having workers to the same. It's a process. Just making sure that the worker label host like you are so yes, on Duin wait for the machines to deploy. Let's go through the process of putting the operating system on the notes, validating that operating system. Deploying Docker enterprise on making sure that the cluster is up and running ready to go. Okay, let's review the bold events. We can see the machine info now populated with more information about the specifics of things like storage. Yeah, of course. Details of a cluster, etcetera. Yeah, Yeah. Okay. Well, now watch the machines go through the various stages from prepared to deploy on what's the cluster build, and that brings us to the end of this particular do my as you can see the process is identical to that of building a normal child cluster we got our complaint is complete. >>Here we have a child cluster on bare metal for folks that wanted to play the stuff on Prem. >>It's ah been an interesting journey taken from the mothership as we started out building ah management cluster and then populating it with a child cluster and then finally creating a regional cluster to spread the geographically the management of our clusters and finally to provide a platform for supporting, you know, ai needs and and big Data needs, uh, you know, thank goodness we're now able to put things like Hadoop on, uh, bare metal thio in containers were pretty exciting. >>Yeah, absolutely. So with this Doctor Enterprise container cloud platform. Hopefully this commoditized scooping clusters, doctor enterprise clusters that could be spun up and use quickly taking provisioning times. You know, from however many months to get new clusters spun up for our teams. Two minutes, right. We saw those clusters gets better. Just a couple of minutes. Excellent. All right, well, thank you, everyone, for joining us for our demo session for Dr Enterprise Container Cloud. Of course, there's many many more things to discuss about this and all of Miranda's products. If you'd like to learn more, if you'd like to get your hands dirty with all of this content, police see us a training don Miranda's dot com, where we can offer you workshops and a number of different formats on our entire line of products and hands on interactive fashion. Thanks, everyone. Enjoy the rest of the launchpad of that >>thank you all enjoy.

>>Hello, everyone. My name is Rick Pew. I'm a senior product manager at Mirant. This and I have been working on the Doctor Enterprise Container Cloud for the last eight months. Today we're gonna be talking about multi cloud kubernetes. So the first thing to kind of look at is, you know, is multi cloud rial. You know, the terms thrown around a lot and by the way, I should mention that in this presentation, we use the term multi cloud to mean both multi cloud, which you know in the technical sense, really means multiple public clouds and hybrid cloud means public clouds. And on Prem, uh, we use in this presentation will use the term multi cloud to refer to all different types of multiple clouds, whether it's all public cloud or a mixture of on Prem and Public Cloud or, for that matter, multiple on Prem clouds as doctor and price container. Cloud supports all of those scenarios. So it really well, let's look at some research that came out of flex era in their 2020 State of the cloud report. You'll notice that ah, 33% state that they've got multiple public and one private cloud. 53% say they've got multiple public and multiple private cloud. So if you have those two up, you get 86% of the people say that they're in multiple public clowns and at least one private cloud. So I think at this stage we could say that multi cloud is a reality. According to 4 51 research, you know, a number of CEO stated that the strong driver their desire was to optimize cost savings across their private and public clouds. Um, they also wanted to avoid vendor lock in by operating in multiple clouds and try to dissuade their teams from taking too much advantage of a given providers proprietary infrastructure. But they also indicated that there the complexity of using multiple clouds hindered the rate of adoption of doing it doesn't mean they're not doing it. It just means that they don't go assed fast as they would like to go in many cases because of the complexity. And here it Miranda's. We surveyed our customers as well, and they're telling us similar things, you know. Risk management, through the diversification of providers, is key on their list cost optimization and the democratization of allowing their development teams, uh, to create kubernetes clusters without having to file a nightie ticket. But to give them a self service, uh, cloud like environment, even if it's on prem or multi cloud to give them the ability to create their own clusters, resize their own clusters and delete their own clusters without needing to have I t. Or of their operations teams involved at all. But there are some challenges with this, with the different clouds you know require different automation. Thio provisioned the underlying infrastructure or deploy and operating system or deployed kubernetes, for that matter, in a given cloud. You could say that they're not that complicated. They all have, you know, very powerful consoles and a P I s to do that. But did you get across three or four or five different clouds? Then you have to learn three or four or five different AP ice and Web consoles in order to make that happen on in. That scenario is difficult to provide self service for developers across all the cloud options, which is what you want to really accelerate your application innovation. So what's in it for me? You know We've got a number of roles and their prizes developers, operators and business leaders, and they have somewhat different needs. So when the developer side the need is flexibility to meet their development schedules, Number one you know they're under constant pressure to produce, and in order to do that, they need flexibility and in this case, the flexibility to create kubernetes clusters and use them across multiple clouds. Now they also have C I C D tools, and they want them to be able to be normalized on automated across all of the the on prim and public clouds that they're using. You know, in many cases they'll have a test and deployment scenario where they'll want to create a cluster, deploy their software, run their test, score the tests and then delete that cluster because the only point of that cluster, perhaps, was to test ah pipeline of delivery. So they need that kind of flexibility. From the operator's perspective, you know, they always want to be able to customize the control of their infrastructure and deployment. Uh, they certainly have the desire to optimize their optics and Capex fans. They also want to support their develops teams who many times their their customers through a p I access for on Prem and public clouds burst. Scaling is something operators are interested in, and something public clouds can provide eso the ability to scale out into public clouds, perhaps from there on prem infrastructure in a seamless manner. And many times they need to support geographic distribution of applications either for compliance or performance reasons. So having you know, data centers all across the world and be able to specifically target a given region, uh, is high on their list. Business leaders want flexibility and confidence to know that you know, they're on prim and public cloud uh, deployments. Air fully supported. They want to be able, like the operator, optimize their cloud, spends business leaders, think about disaster recovery. So having the applications running and living in different data centers gives them the opportunity to have disaster recovery. And they really want the flexibility of keeping private data under their control. On on Prem In certain applications may access that on Prem. Other applications may be able to fully run in the cloud. So what should I look for in a container cloud? So you really want something that fully automates these cluster deployments for virtual machine or bare metal. The operating system, uh, and kubernetes eso It's not just deploying kubernetes. It's, you know, how do I create my underlying infrastructure of a VM or bare metal? How do I deploy the operating system? And then, on top of all that, I want to be able to deploy kubernetes. Uh, you also want one that gives a unified cluster lifecycle management across all the clouds. So these clusters air running software gets updated. Cooper Netease has a new release cycle. Uh, they come out with something new. It's available, you know, How do you get that across all of your clusters? That air running in multiple clouds. We also need a container cloud that can provide you the visibility through logging, monitoring and alerting again across all the clouds. You know, many offerings have these for a particular cloud, but getting that across multiple clouds, uh, becomes a little more difficult. The Doctor Enterprise Container cloud, you know, is a very strong solution and really meets many of these, uh, dimensions along the left or kind of the dimensions we went through in the last slide we've got on Prem and public clouds as of RG A Today we're supporting open stack and bare metal for the on Prem Solutions and AWS in the public cloud. We'll be adding VM ware very soon for another on Prem uh, solution as well as azure and G C P. So thank you very much. Uh, look forward, Thio answering any questions you might have and we'll call that a rap. Thank you. >>Hi, Rick. Thanks very much for that. For that talk, I I am John James. You've probably seen me in other sessions. I do marketing here in Miran Tous on. I wanted to to take this opportunity while we had Rick to ask some more questions about about multi cloud. It's ah, potentially a pretty big topic, isn't it, Rick? >>Yeah. I mean, you know, the devil's in the details and there's, uh, lots of details that we could go through if you'd like, be happy to answer any questions that you have. >>Well, we've been talking about hybrid cloud for literally years. Um, this is something that I think you know, several generations of folks in the in the I. A s space doing on premise. I s, for example, with open stack the way Miran Tous Uh does, um, found, um, you know, thought that that it had a lot of potential. A lot of enterprises believed that, but there were There were things stopping people from from making it. Really, In many cases, um, it required a very, ah, very high degree of willingness to create homogeneous platforms in the cloud and on the premise. Um, and that was often very challenging. Um, but it seems like with things like kubernetes and with the isolation provided by containers, that this is beginning to shift, that that people are actually looking for some degree of application portability between their own Prem and there and their cloud environments. And that this is opening up, Uh, you know, investment on interest in pursuing this stuff. Is that the right perception? >>Yeah. So let's let's break that down a little bit. So what's nice about kubernetes is through the a. P. I s are the same. Regardless of whether it's something that Google or or a W s is offering as a platform as a service or whether you've taken the upstream open source project and deploy it yourself on parameter in a public cloud or whatever the scenario might be or could be a competitor of Frances's product, the Kubernetes A. P I is the same, which is the thing that really gives you that application portability. So you know, the container itself is contained arising, obviously your application and minimizing any kind of dependency issues that you might have And then the ability to deploy that to any of the coup bernetti clusters you know, is the same regardless of where it's running, the complexity comes and how doe I actually spend up a cluster in AWS and open stack and D M Where and gp An azure. How do I build that infrastructure and and spin that up and then, you know, used the ubiquitous kubernetes a p I toe actually deploy my application and get it to run. So you know what we've done is we've we've unified and created A I use the word normalized. But a lot of times people think that normalization means that you're kind of going to a lowest common denominator, which really isn't the case and how we've attacked the the enabling of multi cloud. Uh, you know, what we've done is that we've looked at each one of the providers and are basically providing an AP that allows you to utilize. You know, whatever the best of you know, that particular breed of provider has and not, uh, you know, going to at least common denominator. But, you know, still giving you a ah single ap by which you can, you know, create the infrastructure and the infrastructure could be on Prem is a bare metal infrastructure. It could be on preeminent open stack or VM ware infrastructure. Any of the public clouds, you know, used to have a a napi I that works for all of them. And we've implemented that a p i as an extension to kubernetes itself. So all of the developers, Dev ops and operators that air already familiar operating within the, uh, within the aapi of kubernetes. It's very, very natural. Extension toe actually be able to spend up these clusters and deploy them >>Now that's interesting. Without giving away, obviously what? Maybe special sauce. Um, are you actually using operators to do this in the Cooper 90? Sense of the word? >>Yes. Yeah, we've extended it with with C R D s, uh, and and operators and controllers, you know in the way that it was meant to be extended. So Kubernetes has a recipe on how you extend their A P I on that. That's what we used as our model. >>That, at least to me, makes enormous sense. Nick Chase, My colleague and I were digging into operators a couple of weeks ago, and that's a very elegant technology. Obviously, it's a it's evolving very fast, but it's remarkably unintimidating once you start trying to write them. We were able toe to compose operators around Cron and other simple processes and just, >>you know, >>a couple of minutes on day worked, which I found pretty astonishing. >>Yeah, I mean, you know, Kubernetes does a lot of things and they spent a lot of effort, um, in being able, you know, knowing that their a p I was gonna be ubiquitous and knowing that people wanted to extend it, uh, they spent a lot of effort in the early development days of being able to define that a p I to find what an operator was, what a controller was, how they interact. How a third party who doesn't know anything about the internals of kubernetes could add whatever it is that they wanted, you know, and follow the model that makes it work. Exactly. Aziz, the native kubernetes ap CSTO >>What's also fascinating to me? And, you know, I've I've had a little perspective on this over the past, uh, several weeks or a month or so working with various stakeholders inside the company around sessions related to this event that the understanding of how things work is by no means evenly distributed, even in a company as sort of tightly knit as Moran Tous. Um, some people who shall remain nameless have represented to me that Dr Underprice Container Cloud basically works. Uh, if you handed some of the EMS, it will make things for you, you know, and this is clearly not what's going on that that what's going on is a lot more nuanced that you are using, um, optimal resource is from each provider to provide, uh, you know, really coherent architected solutions. Um, the load balancing the d. N s. The storage that this that that right? Um all of which would ultimately be. And, you know, you've probably tried this. I certainly have hard to script by yourself in answerable or cloud formation or whatever. Um, this is, you know, this is not easy work. I I wrote a about the middle of last year for my prior employer. I wrote a dip lawyer in no Js against the raw aws a piece for deployment and configuration of virtual networks and servers. Um, and that was not a trivial project. Um, it took a long time to get thio. Uh, you know, a dependable result. And to do it in parallel and do other things that you need to do in order to maintain speed. One of the things, in fact, that I've noticed in working with Dr Enterprise Container Cloud recently, is how much parallelism it's capable of within single platforms. It's It's pretty powerful. I mean, if you want to clusters to be deployed simultaneously, that's not hard for Doc. Aerated price container cloud to dio on. I found it pretty remarkable because I have sat in front of a single laptop trying to churn out of cluster under answerable, for example, and just on >>you get into that serial nature, your >>poor little devil, every you know, it's it's going out and it's ssh, Indian Terminals and it's pretending it's a person and it's doing all that stuff. This is much more magical. Um, so So that's all built into the system to, isn't it? >>Yeah. Interesting, Really Interesting point on that. Is that you know, the complexity isn't not necessarily and just creating a virtual machine because all of these companies have, you know, spend a lot of effort to try to make that as easy as possible. But when you get into networking, load balancing, routing, storage and hooking those up, you know, two containers automating that if you were to do that in terror form or answerable or something like that is many, many, many lines of code, you know, people have to experiment. Could you never get it right the first or second or the third time? Uh, you know, and then you have to maintain that. So one of the things that we've heard from customers that have looked a container cloud was that they just can't wait to throw away their answerable or their terror form that they've been maintaining for a couple of years. The kind of enables them to do this. It's very brittle. If if the clouds change something, you know on the network side, let's say that's really buried. And it's not something that's kind of top of mind. Uh, you know, your your thing fails or maybe worse, you think that it works. And it's not until you actually go to use it that you notice that you can't get any of your containers. So you know, it's really great the way that we've simplified that for the users and again democratizing it. So the developers and Dev ops people can create these clusters, you know, with ease and not worry about all the complexities of networking and storage. >>Another thing that amazed me as I was digging into my first, uh, Dr Price container Cloud Management cluster deployment was how, uh, I want I don't want to use the word nuanced again, but I can't think of a better word. Nuanced. The the security thinking is in how things air set up. How, um, really delicate the thinking about about how much credential power you give to the deploy. Er the to the seed server that deploys your management cluster as opposed thio Um uh or rather the how much how much administrative access you give to the to the administrator who owns the entire implementation around a given provider versus how much power the seed server gets because that gets its own user right? It gets a bootstrap user specifically created so that it's not your administrator, you know, more limited visibility and permissions. And this whole hierarchy of permissions is then extended down into the child clusters that this management cluster will ultimately create. So that Dev's who request clusters will get appropriate permissions granted within. Ah, you know, a corporate schema of permissions. But they don't get the keys to the kingdom. They don't have access to anything they don't you know they're not supposed to have access to, but within their own scope, they're safe. They could do anything they want, so it's like a It's a It's a really neat kind of elegant way of protecting organizations against, for example, resource over use. Um, you know, give people the power to deploy clusters, and basically you're giving them the power toe. Make sure that a big bill hits you know, your corporate accounting office at the end of the billing cycle, um so there have to be controls and those controls exist in this, you know, in this. >>Yeah, And there's kind of two flavors of that. One is kind of the day one that you're doing the deployment you mentioned the seed servers, you know, And then it creates a bastion server, and then it creates, you know, the management cluster and so forth, you know, and how all those permissions air handled. And then once the system is running, you know, then you have full access to going into key cloak, which is a very powerful open source identity management tool on you have dozens of, you know, granular permissions that you can give to an individual user that gives them permission to do certain things and not others within the context of kubernetes eso. It's really well thought out. And the defaults, you know, our 80% right. You know, there's very few people are gonna have to go in and sort of change those defaults. You mentioned the corporate directory. You know, hooks right upto l bap or active directory can suck everybody down. So there's no kind of work from a day. One perspective of having to go add. You know everybody that you can think of different teams and groupings of of people. Uh, you know, that's kind of all given from the three interface to the corporate directory. And so it just makes kind of managing the users and and controlling who can do what? Uh, really easy. And, you know, you know, day one day two it's really almost like our one hour to write because it's just all the defaults were really well thought out. You can deploy, you know, very powerful doctor and price container cloud, you know, within an hour, and then you could just start using it. And you know, you can create users if you want. You can use the default users. That air set up a time goes on, you can fine tune that, and it's a really, really nice model again for the whole frictionless democratization of giving developers the ability to go in and get it out of, you know, kind of their way and doing what they want to do. And I t is happy to do that because they don't like dozens of tickets and saying, you know, create a cluster for this team created cluster for that team. You know, here's the size of these guys. Want to resize when you know let's move all that into a self service model and really fulfill the prophecy of, you know, speeding up application development. >>It strikes me is extremely ironic that one of the things that public cloud providers bless them, uh, have always claimed, is that their products provide this democratization when in the experience, I think my own experience and the experience of most of the AWS developers, for example, not toe you know, name names, um, that I've encountered is that an initial experience of trying to start start a virtual machine and figuring out how to log into it? A. W s could take the better part of an afternoon. It's just it's not familiar once you have it in your fingers. Boom. Two seconds, right. But, wow, that learning curve is steep and precipitous, and you slip back and you make stupid mistakes your first couple 1000 times through the loop. Um, by letting people skip that and letting them skip it potentially on multiple providers, in a sense, I would think products like this are actually doing the public cloud industry is, you know, a real surface Hide as much of that as you can without without taking the power away. Because ultimately people want, you know, to control their destiny. They want choice for a reason. Um, and and they want access to the infinite services And, uh, and, uh, innovation that AWS and Azure and Google are all doing on their platforms. >>Yeah, you know, and they're solving, uh, very broad problems in the public clouds, you know, here were saying, you know, this is a world of containers, right? This is a world of orchestration of these containers. And why should I have to worry about the underlying infrastructure, whether it's a virtual machine or bare metal? You know, I shouldn't care if I'm an application developer developing some database application. You know, the last thing I wanna worry about is how do I go in and create a virtual machine? Oh, this is running. And Google. It's totally different than the one I was creating. An AWS I can't find. You know where I get the I P address in Google. It's not like it was an eight of us, you know, and you have to relearn the whole thing. And that's really not what your job is. Anyways, your job is to write data base coat, for example. And what you really want to do is just push a button, deploy a nor kiss traitor, get your app on it and start debugging it and getting it >>to work. Yep. Yeah, it's It's powerful. I've been really excited to work with the product the past week or so, and, uh, I hope that folks will look at the links at the bottoms of our thank you slides and, uh, and, uh, avail themselves of of free trial downloads of both Dr Enterprise Container, Cloud and Lens. Thank you very much for spending this extra time with me. Rick. I I think we've produced some added value here for for attendees. >>Well, thank you, John. I appreciate your help. >>Have a great rest of your session by bike. >>Okay, Thanks. Bye.

>>Hi, Oleg. So great of you to join us today. I'm really looking forward to our session. Eso Let's get started. So if I can get you to give a quick intro to yourself and then if you can share with us what you're going to be discussing today >>Hi, Jake. In my name is Oleg Elbow. I'm a product architect and the Doctor Enterprise Container Cloud team. Uh, today I'm going to talk about running kubernetes on bare metal with a container cloud. My goal is going to tell you about this exciting feature and why we think it's important and what we actually did to make it possible. >>Brilliant. Thank you very much. So let's get started. Eso from my understanding kubernetes clusters are typically run in virtual machines in clouds. So, for example, public cloud AWS or private cloud maybe open staff based or VM ware V sphere. So why why would you go off and run it on their mettle? >>Well, uh, the Doctor Enterprise container cloud already can run Coburn eighties in the cloud, as you know, and the idea behind the container clouds to enable us to manage multiple doctor enterprise clusters. But we want to bring innovation to kubernetes. And instead of spending a lot of resources on the hyper visor and virtual machines, we just go all in for kubernetes directly environmental. >>Fantastic. So it sounds like you're suggesting then to run kubernetes directly on their mettle. >>That's correct. >>Fantastic and without a hyper visor layer. >>Yes, we all know the reasons to run kubernetes and virtual machines it's in The first place is mutual mutual isolation off workloads, but virtualization. It comes with the performance, heat and additional complexity. Uh, another. And when Iran coordinated the director on the hardware, it's a perfect opportunity for developers. They can see performance boost up to 30% for certain container workloads. Uh, this is because the virtualization layer adds a lot off overhead, and even with things like enhanced placement awareness technologies like Numa or processor opinion, it's it's still another head. By skipping over the virtualization, we just remove this overhead and gained this boost. >>Excellent, though it sounds like 30% performance boost very appealing. Are there any other value points or positive points that you can pull out? >>Yes, Besides, the hyper visor over had virtual machines. They also have some static resource footprint. They take up the memory and CPU cycles and overall reintroduces the density of containers per host. Without virtual machines, you can run upto 16% more containers on the same host. >>Excellent. Really great numbers there. >>One more thing to point out directly. Use environmental makes it easier to use a special purpose hardware like graphic processors or virtual no virtual network functions for don't work interfaces or the field programmable gate arrays for custom circuits, Uh, and you can share them between containers more efficiently. >>Excellent. I mean, there's some really great value points you pulled out there. So 30% performance boost, 60% density boost on it could go off and support specialized hardware a lot easier. But let's talk about now. The applications. So what sort of applications do you think would benefit from this The most? >>Well, I'm thinking primarily high performance computations and deep learning will benefit, Uh, which is the more common than you might think of now they're artificial Intelligence is gripping into a lot off different applications. Uh, it really depends on memory capacity and performance, and they also use a special devices like F P G s for custom circuits widely sold. All of it is applicable to the machine learning. Really? >>And I mean, that whole ai piece is I mean, really exciting. And we're seeing this become more commonplace across a whole host of sectors. So you're telcos, farmers, banking, etcetera. And not just I t today. >>Yeah, that's indeed very exciting. Uh, but creating communities closer environmental, unfortunately, is not very easy. >>Hope so it sounds like there may be some challenges or complexities around it. Ondas this, I guess. The reason why there's not many products then out there today for kubernetes on their metal on baby I like. Could you talk to us then about some of the challenges that this might entail? >>Well, there are quite a few challenges first, and for most, there is no one way to manage governmental infrastructures Nowadays. Many vendors have their solutions that are not always compatible with each other and not necessarily cover all aspects off this. Um So we've worked an open source project called metal cube metal cooped and integrated it into the doctor Enterprise Container Cloud To do this unified bar middle management for us. >>And you mentioned it I hear you say is that open source? >>There is no project is open source. We had a lot of our special sauce to it. Um, what it does, Basically, it enables us to manage the hardware servers just like a cloud server Instances. >>And could you go? I mean, that's very interesting, but could you go into a bit more detail and specifically What do you mean? As cloud instances, >>of course they can. Generally, it means to manage them through some sort of a p I or programming interface. Uh, this interface has to cover all aspects off the several life cycle, like hardware configuration, operating system management network configuration storage configuration, Uh, with help off Metal cube. We extend the carbonated C p i to enable it to manage bare metal hosts. And aled these suspects off its life cycle. The mental que project that's uses open stack. Ironic on. Did it drops it in the Cuban. It s a P I. And ironic does all the heavy lifting off provisioned. It does it in a very cloud native way. Uh, it configures service using cloud they need, which is very familiar to anyone who deals with the cloud and the power is managed transparently through the i p my protocol on. But it does a lot to hide the differences between different hardware hosts from the user and in the Doctor Enterprise Container Cloud. We made everything so the user doesn't really feel the difference between bare metal server and cloud VM. >>So, Oleg, are you saying that you can actually take a machine that's turned off and turn it on using the commands? >>That's correct. That's the I. P M I. R Intelligent platform management interface. Uh, it gives you an ability to interact directly with the hardware. You can manager monitor things like power, consumption, temperature, voltage and so on. But what we use it for is to manage the food source and the actual power state of the server. So we have a group of service that are available and we can turn them on. And when we need them, just if we were spinning the VM >>Excellent. So that's how you get around the fact that while aled cloud the ends of the same, the hardware is all different. But I would assume you would have different server configurations in one environment So how would you get around that? >>Uh, yeah, that Zatz. Excellent questions. So some elements of the berm mental management the FBI that we developed, they are specifically to enable operators toe handle wider range of hardware configurations. For example, we make it possible to consider multiple network interfaces on the host. We support flexible partitioning off hard disks and other storage devices. We also make it possible thio boot remote live using the unified extended firmware interface for modern systems. Or just good old bias for for the legacy ones. >>Excellent. So yeah, thanks. Thanks for sharing that that. Now let's take a look at the rest of the infrastructure and eggs. So what about things like networking and storage house that managed >>Oh, Jakey, that's some important details. So from the networking standpoint, the most important thing for kubernetes is load balancing. We use some proven open source technologies such a Zengin ICS and met a little bit to handle. Handle that for us and for the storage. That's ah, a bit more tricky part. There are a lot off different stories. Solutions out. There s o. We decided to go with self and ah cooperator for self self is very much your and stable distributed stories system. It has incredible scalability. We actually run. Uh, pretty big clusters in production with chef and rock makes the life cycle management for self very robust and cloud native with health shaking and self correction. That kind of stuff. So any kubernetes cluster that Dr Underprice Container Cloud provision for environmental Potentially. You can have the self cluster installed self installed in this cluster and provide stories that is accessible from any node in the cluster to any port in the cluster. So that's, uh, called Native Storage components. Native storage. >>Wonderful. But would that then mean that you'd have to have additional hardware so mawr hardware for the storage cluster, then? >>Not at all. Actually, we use Converse storage architecture in the current price container cloud and the workloads and self. They share the same machines and actually managed by the same kubernetes cluster A. Some point in the future, we plan to add more fully, even more flexibility to this, uh, self configuration and enable is share self, where all communities cluster will use a single single self back, and that's that's not the way for us to optimize our very basically. >>Excellent. So thanks for covering the infrastructure part. What would be good is if we can get an understanding them for that kind of look and feel, then for the operators and the users of the system. So what can they say? >>Yeah, the case. We know Doc Enterprise Container Cloud provides a web based user interface that is, uh, but enables to manage clusters. And the bare metal management actually is integrated into this interface and provides provides very smooth user experience. A zone operator, you need to add or enrolled governmental hosts pretty much the same way you add cloud credentials for any other for any other providers for any other platforms. >>Excellent. I mean, Oleg, it sounds really interesting. Would you be able to share some kind of demo with us? It be great to see this in action. Of >>course. Let's let's see what we have here. So, >>uh, thank you. >>Uh, so, first of all, you take a bunch of governmental service and you prepare them, connect and connect them to the network is described in the dogs and bootstrap container cloud on top of these, uh, three of these bare metal servers. Uh, once you put through, you have the container cloud up and running. You log into the u I. Let's start here. And, uh, I'm using the generic operator user for now. Its's possible to integrate it with your in the entity system with the customer and the entity system and get real users there. Mhm. So first of all, let's create a project. It will hold all off our clusters. And once we created it, just switched to it. And the first step for an operator is to add some burr metal hosts of the project. As you see it empty, uh, toe at the berm. It'll host. You just need a few parameters. Uh, name that will allow you to identify the server later. Then it's, ah, user name and password to access the IBM. My controls off the server next on, and it's very important. It's the hardware address off the first Internet port. It will be used to remotely boot the server over network. Uh, finally, that Z the i p address off the i p m i n point and last, but not the least. It's the bucket, uh, toe Assign the governmental host to. It's a label that is assigned to it. And, uh, right now we offer just three default labels or buckets. It's, ah, manager, manager, hosts, worker hosts and storage hosts. And depending on the hardware configuration of the server, you assign it to one of these three groups. You will see how it's used later in the phone, so note that least six servers are required to deploy managed kubernetes cluster. Just as for for the cloud providers. Um, there is some information available now about the service is the result of inspection. By the way, you can look it up. Now we move. Want to create a cluster, so you need to provide the name for the cluster. Select the release off Dr Enterprise Engine and next next step is for provider specific information. You need to specify the address of the Class three guy and point here, and the range of feathers is for services that will be installed in the cluster. The user war close um kubernetes Network parameter school be changed as well, but the defaults are usually okay. Now you can enable or disable stack light the monitoring system for the Burnett's cluster and provide some parameters to eat custom parameters. Uh, finally you click create to create the cluster. It's an empty cluster that we need to add some machines to. So we need a least three manager notes. The form is very simple. You just select the roll off the community snowed. It's either manager of worker Onda. You need to select this label bucket from which the environmental hospital we picked. We go with the manager label for manager notes and work your label for the workers. Uh, while question is deploying, let's check out some machine information. The storage data here, the names off the disks are taken from the environmental host Harbor inspection data that we checked before. Now we wait for servers to be deployed. Uh, it includes ah, operating system, and the government is itself. So uh, yeah, that's that's our That's our you user interface. Um, if operators need to, they can actually use Dr Enterprise Container Container cloud FBI for some more sophisticated, sophisticated configurations or to integrate with an external system, for example, configuration database. Uh, all the burr mental tasks they just can be executed through the carbonated C. P. I and by changing the custom resources customer sources describing the burr mental notes and objects >>Mhm, brilliant. Well, thank you for bringing that life. It's always good. Thio See it in action. I guess from my understanding, it looks like the operators can use the same tools as develops or developers but for managing their infrastructure, then >>yes, Exactly. For example, if you're develops and you use lands, uh, to monitor and manage your cluster, uh, the governmental resources are just another set of custom resources for you. Uh, it is possible to visualize and configure them through lands or any other developer to for kubernetes. >>Excellent. So from what I can see, that really could bridge the gap, then between infrastructure operators on develops and developer teams. Which is which is a big thing? >>Yes, that's that's Ah, one of our aspirations is to unify the user experience because we've seen a lot of these situations when infrastructure is operated by one set of tools and the container platform uses agnostic off it end users and offers completely different set of tools. So as a develops, you have to be proficient in both, and that's not very sustainable for some developers. Team James. >>Sure. Okay, well, thanks for covering that. That's great. E mean, there's obviously other container platforms out there in the market today. It would be great if you could explain only one of some of the differences there and in how Dr Enterprise Container Cloud approaches bare metal. >>Yeah, that's that's a That's an excellent question, Jake. Thank you. So, uh, in container cloud in the container Cloud Burr Mental management Unlike another container platforms, Burr metal management is highly and is tightly integrated in the in the product. It's integrated on the U and the A p I, and on the back and implementation level. Uh, other platforms typically rely on the user to provision in the ber metal hosts before they can deploy kubernetes on it. Uh, this leaves the operating system management hardware configuration hardware management mostly with dedicated infrastructure greater steam. Uh, Dr Enterprise Container Cloud might help to reduce this burden and this infrastructure management costs by just automated and effectively removing the part of responsibility from the infrastructure operators. And that's because container cloud on bare metal is essentially full stack solution. It includes the hardware configuration covers, operating system lifecycle management, especially, especially the security updates or C e updates. Uh, right now, at this point, the only out of the box operating system that we support is you, Bhutto. We're looking to expand this, and, as you know, the doctor Enterprise engine. It makes it possible to run kubernetes on many different platforms, including even Windows. And we plan to leverage this flexibility in the doctor enterprise container cloud full extent to expand this range of operating systems that we support. >>Excellent. Well, Oleg, we're running out of time. Unfortunately, I mean, I've thoroughly enjoyed our conversation today. You've pulled out some excellent points you talked about potentially up to a 30% performance boost up to 60% density boost. Um, you've also talked about how it can help with specialized hardware and make this a lot easier. Um, we also talked about some of the challenges that you could solve, obviously, by using docker enterprise container clouds such as persistent storage and load balancing. There's obviously a lot here, but thank you so much for joining us today. It's been fantastic. And I hope that we've given some food for thoughts to go out and try and deployed kubernetes on Ben. It'll so thanks. So leg >>Thank you for coming. BJ Kim

>>Hey, everyone, Thanks for taking them to join the story. Hope you and your loved ones are safe during these tough times. Let me start by introducing myself. My name is Michelle. When I walk for GlaxoSmithKline, GSK as an engineering manager in my current role, A little protocol platform A P s, which is part of the already data platform here in G S, K R and D Tech. I live in Dallas, Texas. I have a Masters degree in computer science on a bachelor's in electronics and communication engineering. I started my career as a software developer on over these years again a lot of experience in leading and building, not scale and predicts products and solutions. I also have a complete accountability for container platforms here at GSK or any tick. I've been working very closely with Dr Enterprise, which is no Miranda's for more than three years to enable container platforms that yes, came on mainly in our own Itek. So that's me. Let >>me give you a quick overview on agenda for today's talk. I'll start with what we do here at GSK on what is RND data platform. Then I'll give you an overview on What are the business drivers that >>motivated US toe? Take this container Germany on some insight into learnings on accomplishments over these years. Working with Dr Enterprise on the container platforms Lately, you must have seen a lot of articles off there which talk about how ts case liberating technologies like artificial intelligence, mission learning, UN data and analytics for the Douglas Corey process. I'm very excited to see the progress we have made in technology, but what makes us truly unique is our commitment to the patient. >>We're G escape, help millions of people, do more, feel better and live longer. Wear a global company that is focused on three were tickles pharmaceuticals vaccines on consumer healthcare. Our main intent is to lower the >>burden on the impact of diseases on the patients. Here at GSK, we allow science to drive the technology. This helps us toe build innovative products. That's helps our scientists to make better and faster additions throughout the drug discovery by plane. >>With that, let me give you some >>context on what currently data platform is how it is enabled. A T escape started in mid 2016. What used to be called us are any information platform whose main focus was to centralize curate on rationalized all the data produced within the others are in the business systems in orderto drive, a strategic business value, standardization of clinical trials, Genome Wide Association Study Analysis, also known as Jesus Storage and Crossing Off Rheal. World Evidence data some of the examples off how the only platform was used to deliver the business value four years later. No, a new set off business rivals of changing our landscape. The irony Information Platform is evolving to be a hybrid, multi cloud solution and is known as already did a platform refering to 20 >>19 GSK's annual report. These are the four teams that there are any platform will be mainly focused on. We're expanding our data capabilities to support the use. Escape by a former company on evolving into a hybrid medical platform is one of the many steps that we're taking to be future ready. Our key focus will still be making >>greater recommendations better and faster by using that wants us. We're making the areas like artificial intelligence and machine learning. No doc brings us toe. What is Germany is important. Why are we taking this German with that? Let me take you to the next topic off. Like the process of discovery, Francisco is not an easy process. Talking about the recent events occurred over the last few months on the way. How all our lives are impacted. It is a lot of talk on information going about. Why did drug discovery process is so tough working for a global health care company? I get asked this question very frequently. From many people I interact with. Question is like, Why is that? This car is so tough on why it takes so much time. Drug discovery is a complex process that involves multiple different stages on at each and every stage. There is huge amounts of data that the scientists have took process to make some decisions. Studies have shown that only 3% off small molecules entering the human studies actually become medicines. If you're new to drug discovery, you may ask, like what is the targets? Targets so low? We humans are very complex species, >>not going into the details of the process. We're G escape >>have made a lot of investments into technology that enabled us to make data river conditions. Throw the drug Discovery pipeline >>as we implement. As we started implementing these tools and technologies to enable already did a platform, we started to get a better appreciation off how these tools in track on integrate >>with each other. Our goal wants to make this platform a jail, the platform that can work at scale so that we can provide a great user experience and contribute back to the bread discovery pipeline so that the scientists can make faster editions. We want our ardently users to consume the data, and the service is available on the platform seamlessly in a self service fashion. And we also have to accomplish this by establishing trust. And then we have to end also enable the academic partnerships, acquisitions, collaborations that DSK has, which actually brings a lot of data on value to our scientists. So when we talk about so many collaborations and a lot of these systems, what this brings in is wide range off systems and platforms that are fundamentally built on different infrastructure. This is where Doctor comes into fiction on our containers significance. >>We have realized the power of containers on how we can simplify this complex ecosystem by using containers and provide a faster access off data to war scientists who didn't go >>back and contribute back to the drug discovery by play. >>With that, let me take talk to you about >>the containers journey and she escaped. So we started our container journey in late 2017. We started working with Dr Enterprise to enable the container platform. This is on our on prem infrastructure Back then, or first year or so we walked through multiple Pelosis did a lot of testing to make sure our platform is stable before we onboard either the data or the user applications. I was part of this complete journey on Dr Stream has worked with us very closely towards you. The first milestone off establishing a stable container platform. A tsk. Now, getting into 2019 we started deploying our applications in production environment. I cannot go into the details of what this Absar, but they do include both data pipelines as well as Web services. You know, initial days we have worked a lot on swamp, but in 2019 is when we started looking into communities in the same year, we enable kubernetes orchestration on the doctor and replace platform here at GSK and also made it as a de facto orchestra coming into 2020. All our micro service applications are undead. A pipelines are migrated to the container platforms on all of these are orchestrated by Cuban additional on these air applications that are running in production. As of today, we have made the container forced approach as an architectural standard across already taking GSK. We also started deploying our AML training models onto containers on All this work is happening on our Doctor Enterprise platform. Also as part off are currently platforms hybrid multicolored journey. We started enabling container and kubernetes based platforms on public clubs. Now going into 2021 on future. Enabling our RND users to easily access data and applications in a platform agnostic way is very crucial for our success because previously we had only onto him. Now we have public clothes that are getting involved on One of >>the many steps we're taking through this journey is to >>watch allies the data on ship data and containers or kubernetes volumes on demand to our our end users of scientists. And this allows us to deliver data to our scientists wherever they want in a very security on. We're leveraging doctor to do it. So that's >>our future. Learning on with that, let's take a deep dive into fuel for >>our accomplishments over these years. I want to start with a general demand and innovative one very interesting use case that we developed on Dr. This is a rapid prototyping capability that enabled our scientists seamlessly to Monday cluster communication. This was one off the biggest challenges which way his face for a long time and with the help of containers, were able to solve this on provide this as a capability to our scientists. We actually have shockers this capability in one of the doctor conferences before next. As I've said before, by migrating all over web services into containers, we not only achieved horizontal scalability for those specific services, but also saved more than 50% in support costs for the applications which we have migrated by making Docker image as an immutable artifact In our bill process, we are now able to deploy our APS or models in any container or Cuban, its base platform, either in on Prem or in a public club. We also made significant improvements towards the process. A not a mission By leveraging docker containers, containers have played a significant role in keeping US platform agnostic and thus enabling our hybrid multi cloud Germany valuable for out already did scientists. As I mentioned before, data virtualization is another viewpoint we have in terms off our next steps off where we want to take kubernetes on where we wanna leverage open it. Us. What you see here are just a few off many accomplishments which we have our, um, achieved by using containers for the past three years or so. So with that before I close all the time and acknowledge all our internal partners who has contributed a lot to this journey mainly are in the business are on the deck on the broader take. Organizations that escape also want to time document present Miranda's for being such a great partner throughout this journey and also giving us an opportunity to share this success story today. Lastly, thanks for everyone to listening to the stop and please feel free to reach out. If you have any questions or suggestions, let's be fit safe. Thank you

>>from around the globe. It's the cue with digital coverage of active EO data driven 2020. Brought to you by activity. We're back. This is the cubes coverage. Our ongoing coverage of active FiOS data driven. Of course, we've gone virtual this year. Ash. Ashutosh is here. He's the founder, president and CEO of Active Eo. Great to see you again. >>Likewise, They always always good to see you. >>We have We're in a little meet up, You and I in Boston. I always enjoy our conversations. Little did we know that, You know, a few months later, we would only be talking at this type of distance and, uh and of course, it's sad. I mean, a data driven is one of our favorite events is intimate, its customer content driven. The theme this year is you call it the next normal. Some people call it the new abnormal, the next normal. What's that all about? >>I think it's pretty pretty fascinating to see when we walked in in March, all of us were shocked by the effect of this pandemic. And for a while we all scrambled around trying to figure out How do you react to this one, and everybody reacted very differently. But most people have this tendency to think that this is going to be a pretty broom environment with lots of unknown variables, and it is important for us to try to figure out how to get a get our hands on this. By the time we came on. For six weeks into that, almost all of us have figured out this is Ah, this is not something you fight again. This is not something you wait, what, it to go away? But this is one. Did you figure out how to live in and you figured out how to work around it? And that, we believe, is the next long. It's not about trying to create a new abnormal. It's not about creating a new normal, but it's truly one that basically says that is it. That is a way, perhaps packed forward. There's a is a way to create this next normal, and you just figured out how to live with the environment, behalf and the normal outcomes of companies that have done remarkably well as a result of these actions. Fact. If you're being one of them, >>it's quite amazing isn't it? I mean, I've talked to a lot of tech companies, CEOs and their customers, and it's almost like they feel the first reaction was course they cared about their there, their employees and their broader families. Number one number two was many companies, as you know, saw a tailwind, and it initially didn't want to be seen as ambulance chasing. And then, of course, the entrepreneurial spirit kicked in and they said, Okay, we can only control what we can control and tech companies in particular just exceedingly Well, I don't think anybody really predicted that early >>on. Yeah, I, um I think of the heart, We're all human beings, and the first reaction was to take it off. Four constituencies, right? One. Take care of your family. Take it off your community, take care of your employees, take care of your customers. And that was the hardest part. The first 4 to 6 weeks was to figure out How do you do each of those four. Once you figured that part out or you figured out ways to get around to making sure you can take it off those you really found the next mom, you really start forgetting our out of continue to innovate Could, you know to support each of those four constituencies and people have done different things. I know it's amazing how, um, Cuba continues to operate As far as a user is concerned, they're all watching anymore. Yes, we don't have the wonderful desk, and we all get to chat and look in the eye. But the content of the messages asked powerful as what it waas a few months ago. So I'm sure this is how we're all going to figure out how to make through this new next normal >>and digital transformation kind of went from from push to pull. I mean, every conference you go to, they say, Well, look at uber, you know, look at Airbnb and it put up the examples you have to do this to, and then all of sudden the industry dragged you along. Some Curis esta is toe. How and and I guess the other point there is digital means data. We've said that many, many times. If you didn't have a digital strategy during the height of the lock down, you couldn't transact business and still many restaurants is still trying to figure this out, But so how did it affect you and your customers? >>Yeah, it's very interesting. And I we spend a lot of time with several of our customers were managing some of the largest I T organizations. We talk about very interesting phenomena that happened some better beginning of this year. About 20 years ago, we used to worry about this thing called the Digital Divide, those who have access the network and Internet and those who don't. And now there is this beta divide, the divide between organizations that know how to leverage, exploit and absolutely excellent the business using data and those adorable. I think we're seeing this effect so very clearly among organizations that unable to come back and address some of this stuff. And it's fascinating. Yes, we all have the examples off the lights off. People are doing delivery. People are doing retailing, but there are so many little things you're seeing organizations. And just the other day, he had a video from Century Days Is Central Data System, which is helping accelerate Cohen 19 research because it will get copies of the data faster than they would get access to data so that these are just much, much faster. Sometimes you know, several days to a few minutes. It's that that level of effect, it's not just down to some seven. You know, you almost think of it as nice to have, but it's must have life threatening stuff. Essential stuff or just addressing. Korea was running a very pretty in a wonderful article about this supercomputer in That's Doing an Aristo covert 19 and how it's figured out most of these symptoms they're able to figure out by just crunching a ton of data. And almost every one of those symptoms that the computer has predicted Supercomputer is predicted has being accurate. It's about data. It is absolutely about data, which is why I think this is a phenomenal time for companies. Toe Absolutely go change. Make this information about data exploration, data leverage, exploitation. And there's a ton of it all over all around us. >>Yeah, and and part of that digital transformation, the mandate is to really put data at the core. I mean, we've we've certainly seen this with the top market cap companies. They've got dated at the core, and and now, as they say it's it's become a A mandate. And, you know, there's been several things that we've clearly noticed. I mean, you saw the work from home required laptops and, you know, endpoint security and things of that. VD. I made a comeback, and certainly Cloud was there. But I've been struck by the reality of multi Cloud. I was kind of a multi cloud skeptic early on. >>Yeah, >>I said many times I thought it was more of a symptom than it was a strategy, but it's that's completely flipped. Ah, recently in r e t r surveys, we saw multi cloud popping up all over the place. I wonder what you're seeing when you talk to your customers and other CEOs. >>Yeah, So fascinating, though really is the first flower part of sometime in 2018. End of 2018 >>Go right, Yeah, >>the act if you'll go on world, which is a phenomenal way to completely change the way you think about the using object storage in the flower for two years that we saw about 20% of our business. By the end of two years, the beginning of this year, 20% of our business was built on never it in the cloud since March. So that was end of our almost ended the Q one. So now we just limit left you three in six months. We added 12 more percent of the business literally weeded in six months. What we did not do before for 18 months before that, right? Significantly more than what we did for a year and a half before that. And there are really three reasons and we see this old nor again, we have a large customer. We closed in January. Ironically, were deploying out of UK, a very large marketing organization. Got everything deployed, running the they're back up and beyond and a separate data center. And they had a practical problem of not being able to access the second sight literally in the middle of deployment. Mystere that customer, Did you see me Google Cloud? Because they were simply no way for them to continue protecting their data, being able to develop new applications with that data that simply had no access. So there was. This was the number one reason the inability for already physically access, but put their their employees at rest and have before the plow would be the infrastructure. That's number one, so that first of all, drove the reason for the cloud. And then there's a second reason there are practical reasons. And why some clerk platforms that good one working the other ones are not. So where, uh, some other more fuels. And so if I'm an organization that has that spans everything, I've got no power PC and X 86 machine A vm I got container platforms. I got Oracle. They got a C P. There is no single cloud platform that supports all my work loaders efficiently. It's available in all the agents I want. So inevitably I have to go at our different about barefoot. So that's a second practical visa. And then there's a strategic reason. No, when no customer what's really locked into anyone card back at least two. You're gonna go pear more likely? Three. So those are the reasons. And then, interestingly enough, have you were on a panel with as global Cee Io's and in addition to just the usual cloud providers of you all know and love inside the U. S. Across the world, in Europe, in Asia, there's a rise off the regional flower fire. See you take all this factor. So have you got absolute physical necessity? You got practical constraints of what can the club provided support the strategic reasons on why either Because I don't want to be locked into a part for better or because there is a rise off data nationalism that's going on, that people want to keep their data within the country bombs all of these reasons. But the foundations or why multiplier is almost becoming a de facto. It's impossible. What a decent size organization to assume. They were just different on one car ready. >>The big trend we're seeing, I wonder if you could comment. Is this this notion of the data life cycle of the data pipeline? It's a very complex situation for a lot of organizations, their data siloed. We hear that a lot. They have data scientists, data engineers, developers, data quality engineers, just a lot of different constituencies and lines of business. And it's kind of a mess. And so what they're trying to do is bring that together. So they've done that data. Scientists complain they spend all their time wrangling data, but but ultimately the ones that are succeeding to putting data at the core is, we've just been discussing are seeing amazing outcomes by being able to have a single version of the truth, have confidence in that data, create self serve for their for their lines of business and actually reduce the end and cycle times. It's driving your major monetization, whether that's cost cutting or revenue. And I'm curious as to what you're seeing. You guys do a lot of work. Heavy work in Dev ops and hard core database those air key components of that data Lifecycle. Yeah, you're seeing in that regard regarding that data pipeline. >>Yeah, it's a It's a phenomenal point if you really want to go back and exploit data within an organization. If you really want to be a data driven organization, the very first thing you have to do is break down the silos. Ironically, every organization has all the data required to make the decisions they want to. They just can't either get to it or it's so hard to make the silos. That is just not what trying to make it happen. And 10 years ago we set out on this mission rather than keep this individual silos of data. Why don't we flip it open and making it a pipeline, which looks like a data cloud where essentially anybody who's consuming it has access to it based on the governance rules based on the security rules that the operations people have said and based on the kind of format they want to see data. Not everyone even want to see the data in a database. Former, maybe you want the database for my convert CSP for my before you don't analytics And this idea of making data, the new infrastructure, this idea of having the operations people provide this new layer for data, it's finally come to roost. I mean, it's it's fascinating. I was the numbers last quarter. We just finished up. You do now. 45% of our customer base is uses activity or for reuse is the back of data for things that excellent. The business things that make the business move faster, more productive or you will survive. That was the mission. That was what we set out to do 10 years ago. We were talking to an analyst this morning, and now this is question off. You know, it looks like there's a team of backup data being reused, said Yeah, that's kind of what we've been saying for 10 years. Backup cannot be an insurance back up in order to your destination. It has to be something that you could use as an asset and that I think it's finally coming to the point with you can use back up a single source of truth only if you designed it right from the beginning. For that purpose, you cannot just lots of lots of ways to fake it. Make it try to pretend like you're doing it. But that was a trooper was off making date of the new infrastructure, making it a cloud, making it something that is truly an ask. And it's fascinating to see our businesses. You take any of our larger counts and the way they've gone about transforming not just basic backup. India. Yes, we are the world's glasses back up in most Kayla will be our solution. That's that's a starting point. But do we will be used after Devil applications 8, 10 times faster? Ron Analytics, 100 ex pastor. The more data you have, the more people who use data you have, the better this return makeups. >>You know, that is interesting to hear you talk about that because that has been the holy Grail of backup. Was toe go beyond insurance to actually create business value. And you're actually seeing some underlying trends We talked about that data pipeline in one of the areas that is the most interesting is in database, which was so boring for so many years. Ah, and you're seeing new workloads emerge. Take the data warehouse beyond your reporting. Never really lived up to its Ah, it's promise of 360 degree view. You mentioned analytics. That's really starting toe happen. Ah, and it's all about data John, for Used to say that your data is that is the new development kit. You call it the new infrastructure, and it's sort of the same same type of theme. So maybe some of the trends you're seeing in ah in database enoughto talk about that for a little bit and then pick your brains and some other tech like object storage is another one that we've really seen takeoff? >>Yeah. So I think our journey with object story began in 16 4017 as we started or Doctor Cloud platform in response to the user requirements, Uh, we did more like most companies have done and unfortunately continue to do to take the in print product. And then it's smooth under the cloud. And one of the things we saw was there was a fundamental difference off how the design points of flower engineering is all about what they're designed it for object story, that one of those one of those primitives fundamental stories, primitives that the cloud providers actually produced that we know really exploited. There was. It was used as a graveyard for data. It's a replacement for me, please, where data goes to die. And then we look at it really closely and say, Well, this is actually a massively scalable, very low cost storage, but it has some problems. It has an interface that you cannot use with traditional servers. Uh, it has some issues around not being able to read, modify right the data. So it feels like a consuming a lot of stories. So we're going to solve those problems because a good two years to come back with something on world that fundamentally creeds objects the lady like this massive use capable high performer disk? Yes, except it is ridiculously low cost and optimize the capacity. So this finger on world that patented has really become the foundation of how everything in our works without using CPU Ray, that is simply nothing at a lower PCO that if you wanted to basic backup, the, uh, more importantly, use that to do this a massive analytics and you don't know more data warehouse data leaks. It is not a good deal of Lake House aladi. All of these are still silent. All of these are people trying to take some data from somewhere put into one of the new construct and have it being controlled by somebody else. This is artist thing. It's just you just move the silos from some place to another place instead of creating a pipeline. If you want to really create a pipeline object story has been integral part of the pipeline, not a separate bucket by itself. And that's what we did. And same thing with databases, you know, most business, most of the critical business and I was on a daily basis, and the ability to find a way to leverage those. Move them on our leverage in terms of whichever format databases access. Which location or Saxes doesn't know how big it is. Lots of work has gone into trying to figure figure that one out. And we we had some very, very good partners in some of the largest customers who help take the journey with us. I'm pretty much all of the global 2000 accounts you see across the board, but an integral part of a process. >>You mentioned the word journey and triggered a thought. Is your discussion with Robbie, the CEO of of Seeing >>A. It was a customer years. >>Ah, and what he said. I liked what he said. He course he used the term journey. We all do. But he said, You know what? I kind of don't like that term because I want to inject the sense of urgency essentially what he was saying. I want speed, you know, journeys like Okay, kids get in the car, were in a drive across country. We're gonna make some stops. And so, while there's a journey, he also was was really trying to push the organization hard and he talked about culture. Ah, as some of the most difficult things and it goes like many. See, I said, Now the technology is almost the easy part. It's true when it works. Oh, I thought that was a great discussion that you had. What were some of your takeaways >>with thinking? Robbie's is very astute. Ah, I t executive was being around the block for so long and one of the fascinating things, but a asking this question about what's the biggest challenge was just gone through this a couple of times. What is the biggest challenge? Taking an organization as vulnerable as well known A C gate is. I mean, this is a data company. This is This is the heart of the Oliver Half the world's data is on seeing stuff. How are you today was, or company has been around for long in the middle of Silicon Valley and make it into ah into a fast growing transformation company that's responding to the newer challenges. And I thought he was going to come back with Well, you know, I gotta go to the abuses. I picked this technology that techno in. Surely that is exactly what I expected he would end up with. There's nothing through technology in this day and age when you can have an Elon Musk and send a card of Mars. It's not many technologies that we can really solve many covered 19 ism. Next one Do we gotta go solve? Well, frankly, he kid upon the one thing that matters to every company. It is the fundamental culture to create a biased of action. It's a fundamental culture where you have to come back and have a deliverable that moves the ball forward every day, every month, every quarter, as opposed to have this CDs off. Like you said, a journey that say's and we all know this right? People talk about, we're going to do this in face one. We're gonna do this and face to and good food release and face three nothing and what happens Invasive. Nobody gets a number feast. I think he did a great job of saying I fundamentally had to go change the culture that was my biggest take away, and this I've heard this so many times the most effective I D execs wait a transformation. It actually shows in the people that they have. It's not the technology, it's the people. And some. This history is replete with organizations that have done remarkably well, not by leveraging the heck out of the technology, but truly by leveraging the change in the people's mindset. And, of course, that at that point that leverages technology where a proper here. But Robbie's a insightful person, always such a They lied to talk them, said they like for him to have chosen us as a its information technology for him to go pull his data warehouses and completely transformed how I was doing manufacturing across the globe. >>You know, I want to have some color of what you just said because some key keep takeaways that from what you just said, ashes is You know, you're right when you look back at the history of the computer industry used to be very well known processes, but the technology was the big mystery and the and the big risk and you think about with Cove it were it not for Technology Way didn't know what was coming. We were inventing new processes literally every day, every week, every month. It's so technology was pretty well understood. It and enabled that. And when you when you think when we talked earlier about putting data at the core, it was interesting to hear Robbie. He basically said, Yeah, we had a big data team in the U. S. A big tainted TV in Europe. We actually organized around silos and and so you guys played a role you were very respectful about, you know, touting active video with him. You did ask him, You know what role you play, But it is interesting to hear and talk about how he had to address that both culturally. And of course, there's technology underneath to enable that unification of data that silo busting, if you will. And you guys played a role in that. >>Yeah, I always enjoy, um, conversation with folks who have taken a problem, identified what needs to be done and then just get it done. And its That's more fascinating than you. Of course, I video plays a small part in a lot of things, and we're proud to have played a small part in his big initiative, and that's true of know the thousands of customers we talk about. But it's such a fascinating story to have leaders who come back and make this transformation happen, and to understand how they went about making those decisions, how they identified where the problem with these are so hard. We all see them in our own life, right? We see there is a there's a problem, but sometimes it takes a wider don't understand. How do you identify them and what do you have to do and more importantly, actually do it? And so whenever use, whenever I get an opportunity with people like Robbie, I think understanding that there's a way to help, uh, we always make sure that we play our own small part, and we're privileged to be a part of those kinds of journeys. >>Well, I think what's interesting about activity on the company that you created is essentially that. We're talking about the democratisation of data, that whole data pipeline, that discussion, that we had the self service of that data to the lines of business and, you know, you guys clearly play a role there. The multi cloud discussion fits into that. I mean that these air all trends that are tail winds for companies that can that can help sort of you know, flattened the data globe. If you if you will, your final thoughts. >>Yeah, I know you said something that is so much at the heart of every idea Exactly that you're talking to, if they truly is. The fundamental asset that I finally end up with is an organization. The democratization of data. Where I do not lock this into another silo, another platform, another ploughed. Another application has to be part of my foundation design and therefore my ability to use each of this cloud platform for the services they provide. While I and they were to move the data to where I needed to be. That is so critical. So you almost start to think about the one possession and organization now has. And we talked about this with a group of CEOs. They might be some pretty soon. Not too far off, but data stolen asset. I might actually have our data mark data market, just like you. I was stopped working, but I can start to sell my data. You know, imagine a coup in 19. There's so many organization that have so much data, and many of them have contributed to this research because this is an existence of issue. But you can see this turning into a next level. So, yes, we've got activities, will move the data toe one level higher where it's become a foundation construct for the organization. The next part is gonna actually done. This is the one asset would actually monetize someone stuff. And it will be not too long when you need to talk about how there's this new exchange and what's the rate of data for this company? Was, is that company in the future trading options? Who knows is gonna be really interesting. >>Well, I think you're right on this notion of a data. Marketplaces is coming, and it's not not that far away, Blash. It's always great to talk to you. I hope next year a data driven weaken we could be face to face. But I mean, look, this has been we we've dealt with it. It's it's actually created opportunities for us toe to reinvent ourselves. So congratulations on the success that you've had and ah, and thank you for coming on the Cube. >>No, thank you for hosting us and always a big fan off Cube. You guys, you engage with you since early days, and it is fascinating to see how this company has grown. And it's probably many people don't even know how much you've grown behind the seats, technologies and culture that you created yourself. So it's hopefully one day we'll strict the table that I would be another side and asking of our transformation. Digital transformation of Cuban cell >>I would love to. I'd love to do that index again. And thank you, everybody for watching our continuous coverage of active fio data driven keeper Right there. We'll be back with our next guest right after this short break. >>Thank you.