(upbeat music) >> Welcome back to Supercloud 2, an open collaborative where we explore the future of cloud and data. Now, you might recall last August at the inaugural Supercloud event we validated the technical feasibility and tried to further define the essential technical characteristics, and of course the deployment models of so-called supercloud. That is, sets of services that leverage the underlying primitives of hyperscale clouds, but are creating new value on top of those clouds for organizations at scale. So we're talking about capabilities that fundamentally weren't practical or even possible prior to the ascendancy of the public clouds. And so today at Supercloud 2, we're digging further into the topic with input from real-world practitioners. And we're exploring the intersection of data and cloud, And importantly, the realities and challenges of deploying technology for a new business capability. I'm pleased to have with me in our studios, west of Boston, Veronika Durgin, who's the head of data at Saks. Veronika, welcome. Great to see you. Thanks for coming on. >> Thank you so much. Thank you for having me. So excited to be here. >> And so we have to say upfront, you're here, these are your opinions. You're not representing Saks in any way. So we appreciate you sharing your depth of knowledge with us. >> Thank you, Dave. Yeah, I've been doing data for a while. I try not to say how long anymore. It's been a while. But yeah, thank you for having me. >> Yeah, you're welcome. I mean, one of the highlights of this past year for me was hanging out at the airport with you after the Snowflake Summit. And we were just chatting about sort of data mesh, and you were saying, "Yeah, but." There was a yeah, but. You were saying there's some practical realities of actually implementing these things. So I want to get into some of that. And I guess starting from a perspective of how data has changed, you've seen a lot of the waves. I mean, even if we go back to pre-Hadoop, you know, that would shove everything into an Oracle database, or, you know, Hadoop was going to save our data lives. And the cloud came along and, you know, that was kind of a disruptive force. And, you know, now we see things like, whether it's Snowflake or Databricks or these other platforms on top of the clouds. How have you observed the change in data and the evolution over time? >> Yeah, so I started as a DBA in the data center, kind of like, you know, growing up trying to manage whatever, you know, physical limitations a server could give us. So we had to be very careful of what we put in our database because we were limited. We, you know, purchased that piece of hardware, and we had to use it for the next, I don't know, three to five years. So it was only, you know, we focused on only the most important critical things. We couldn't keep too much data. We had to be super efficient. We couldn't add additional functionality. And then Hadoop came along, which is like, great, we can dump all the data there, but then we couldn't get data out of it. So it was like, okay, great. Doesn't help either. And then the cloud came along, which was incredible. I was probably the most excited person. I'm lying, but I was super excited because I no longer had to worry about what I can actually put in my database. Now I have that, you know, scalability and flexibility with the cloud. So okay, great, that data's there, and I can also easily get it out of it, which is really incredible. >> Well, but so, I'm inferring from what you're saying with Hadoop, it was like, okay, no schema on write. And then you got to try to make sense out of it. But so what changed with the cloud? What was different? >> So I'll tell a funny story. I actually successfully avoided Hadoop. The only time- >> Congratulations. >> (laughs) I know, I'm like super proud of it. I don't know how that happened, but the only time I worked for a company that had Hadoop, all I remember is that they were running jobs that were taking over 24 hours to get data out of it. And they were realizing that, you know, dumping data without any structure into this massive thing that required, you know, really skilled engineers wasn't really helpful. So what changed, and I'm kind of thinking of like, kind of like how Snowflake started, right? They were marketing themselves as a data warehouse. For me, moving from SQL Server to Snowflake was a non-event. It was comfortable, I knew what it was, I knew how to get data out of it. And I think that's the important part, right? Cloud, this like, kind of like, vague, high-level thing, magical, but the reality is cloud is the same as what we had on prem. So it's comfortable there. It's not scary. You don't need super new additional skills to use it. >> But you're saying what's different is the scale. So you can throw resources at it. You don't have to worry about depreciating your hardware over three to five years. Hey, I have an asset that I have to take advantage of. Is that the big difference? >> Absolutely. Actually, from kind of like operational perspective, which it's funny. Like, I don't have to worry about it. I use what I need when I need it. And not to take this completely in the opposite direction, people stop thinking about using things in a very smart way, right? You like, scale and you walk away. And then, you know, the cool thing about cloud is it's scalable, but you also should not use it when you don't need it. >> So what about this idea of multicloud. You know, supercloud sort of tries to go beyond multicloud. it's like multicloud by accident. And now, you know, whether it's M&A or, you know, some Skunkworks is do, hey, I like Google's tools, so I'm going to use Google. And then people like you are called on to, hey, how do we clean up this mess? And you know, you and I, at the airport, we were talking about data mesh. And I love the concept. Like, doesn't matter if it's a data lake or a data warehouse or a data hub or an S3 bucket. It's just a node on the mesh. But then, of course, you've got to govern it. You've got to give people self-serve. But this multicloud is a reality. So from your perspective, from a practitioner's perspective, what are the advantages of multicloud? We talk about the disadvantages all the time. Kind of get that, but what are the advantages? >> So I think the first thing when I think multicloud, I actually think high-availability disaster recovery. And maybe it's just how I grew up in the data center, right? We were always worried that if something happened in one area, we want to make sure that we can bring business up very quickly. So to me that's kind of like where multicloud comes to mind because, you know, you put your data, your applications, let's pick on AWS for a second and, you know, US East in AWS, which is the busiest kind of like area that they have. If it goes down, for my business to continue, I would probably want to move it to, say, Azure, hypothetically speaking, again, or Google, whatever that is. So to me, and probably again based on my background, disaster recovery high availability comes to mind as multicloud first, but now the other part of it is that there are, you know, companies and tools and applications that are being built in, you know, pick your cloud. How do we talk to each other? And more importantly, how do we data share? You know, I work with data. You know, this is what I do. So if, you know, I want to get data from a company that's using, say, Google, how do we share it in a smooth way where it doesn't have to be this crazy, I don't know, SFTP file moving. So that's where I think supercloud comes to me in my mind, is like practical applications. How do we create that mesh, that network that we can easily share data with each other? >> So you kind of answered my next question, is do you see use cases going beyond H? I mean, the HADR was, remember, that was the original cloud use case. That and bursting, you know, for, you know, Thanksgiving or, you know, for Black Friday. So you see an opportunity to go beyond that with practical use cases. >> Absolutely. I think, you know, we're getting to a world where every company is a data company. We all collect a lot of data. We want to use it for whatever that is. It doesn't necessarily mean sell it, but use it to our competitive advantage. So how do we do it in a very smooth, easy way, which opens additional opportunities for companies? >> You mentioned data sharing. And that's obviously, you know, I met you at Snowflake Summit. That's a big thing of Snowflake's. And of course, you've got Databricks trying to do similar things with open technology. What do you see as the trade-offs there? Because Snowflake, you got to come into their party, you're in their world, and you're kind of locked into that world. Now they're trying to open up. You know, and of course, Databricks, they don't know our world is wide open. Well, we know what that means, you know. The governance. And so now you're seeing, you saw Amazon come out with data clean rooms, which was, you know, that was a good idea that Snowflake had several years before. It's good. It's good validation. So how do you think about the trade-offs between kind of openness and freedom versus control? Is the latter just far more important? >> I'll tell you it depends, right? It's kind of like- >> Could be insulting to that. >> Yeah, I know. It depends because I don't know the answer. It depends, I think, because on the use case and application, ultimately every company wants to make money. That's the beauty of our like, capitalistic economy, right? We're driven 'cause we want to make money. But from the use, you know, how do I sell a product to somebody who's in Google if I am in AWS, right? It's like, we're limiting ourselves if we just do one cloud. But again, it's difficult because at the same time, every cloud provider wants for you to be locked in their cloud, which is why probably, you know, whoever has now data sharing because they want you to stay within their ecosystem. But then again, like, companies are limited. You know, there are applications that are starting to be built on top of clouds. How do we ensure that, you know, I can use that application regardless what cloud, you know, my company is using or I just happen to like. >> You know, and it's true they want you to stay in their ecosystem 'cause they'll make more money. But as well, you think about Apple, right? Does Apple do it 'cause they can make more money? Yes, but it's also they have more control, right? Am I correct that technically it's going to be easier to govern that data if it's all the sort of same standard, right? >> Absolutely. 100%. I didn't answer that question. You have to govern and you have to control. And honestly, it's like it's not like a nice-to-have anymore. There are compliances. There are legal compliances around data. Everybody at some point wants to ensure that, you know, and as a person, quite honestly, you know, not to be, you know, I don't like when my data's used when I don't know how. Like, it's a little creepy, right? So we have to come up with standards around that. But then I also go back in the day. EDI, right? Electronic data interchange. That was figured out. There was standards. Companies were sending data to each other. It was pretty standard. So I don't know. Like, we'll get there. >> Yeah, so I was going to ask you, do you see a day where open standards actually emerge to enable that? And then isn't that the great disruptor to sort of kind of the proprietary stack? >> I think so. I think for us to smoothly exchange data across, you know, various systems, various applications, we'll have to agree to have standards. >> From a developer perspective, you know, back to the sort of supercloud concept, one of the the components of the essential characteristics is you've got this PaaS layer that provides consistency across clouds, and it has unique attributes specific to the purpose of that supercloud. So in the instance of Snowflake, it's data sharing. In the case of, you know, VMware, it might be, you know, infrastructure or self-serve infrastructure that's consistent. From a developer perspective, what do you hear from developers in terms of what they want? Are we close to getting that across clouds? >> I think developers always want freedom and ability to engineer. And oftentimes it's not, (laughs) you know, just as an engineer, I always want to build something, and it's not always for the, to use a specific, you know, it's something I want to do versus what is actually applicable. I think we'll land there, but not because we are, you know, out of the kindness of our own hearts. I think as a necessity we will have to agree to standards, and that that'll like, move the needle. Yeah. >> What are the limitations that you see of cloud and this notion of, you know, even cross cloud, right? I mean, this one cloud can't do it all. You know, but what do you see as the limitations of clouds? >> I mean, it's funny, I always think, you know, again, kind of probably my background, I grew up in the data center. We were physically limited by space, right? That there's like, you can only put, you know, so many servers in the rack and, you know, so many racks in the data center, and then you run out space. Earth has a limited space, right? And we have so many data centers, and everybody's collecting a lot of data that we actually want to use. We're not just collecting for the sake of collecting it anymore. We truly can't take advantage of it because servers have enough power, right, to crank through it. We will run enough space. So how do we balance that? How do we balance that data across all the various data centers? And I know I'm like, kind of maybe talking crazy, but until we figure out how to build a data center on the Moon, right, like, we will have to figure out how to take advantage of all the compute capacity that we have across the world. >> And where does latency fit in? I mean, is it as much of a problem as people sort of think it is? Maybe it depends too. It depends on the use case. But do multiple clouds help solve that problem? Because, you know, even AWS, $80 billion company, they're huge, but they're not everywhere. You know, they're doing local zones, they're doing outposts, which is, you know, less functional than their full cloud. So maybe I would choose to go to another cloud. And if I could have that common experience, that's an advantage, isn't it? >> 100%, absolutely. And potentially there's some maybe pricing tiers, right? So we're talking about latency. And again, it depends on your situation. You know, if you have some sort of medical equipment that is very latency sensitive, you want to make sure that data lives there. But versus, you know, I browse on a website. If the website takes a second versus two seconds to load, do I care? Not exactly. Like, I don't notice that. So we can reshuffle that in a smart way. And I keep thinking of ways. If we have ways for data where it kind of like, oh, you are stuck in traffic, go this way. You know, reshuffle you through that data center. You know, maybe your data will live there. So I think it's totally possible. I know, it's a little crazy. >> No, I like it, though. But remember when you first found ways, you're like, "Oh, this is awesome." And then now it's like- >> And it's like crowdsourcing, right? Like, it's smart. Like, okay, maybe, you know, going to pick on US East for Amazon for a little bit, their oldest, but also busiest data center that, you know, periodically goes down. >> But then you lose your competitive advantage 'cause now it's like traffic socialism. >> Yeah, I know. >> Right? It happened the other day where everybody's going this way up. There's all the Wazers taking. >> And also again, compliance, right? Every country is going down the path of where, you know, data needs to reside within that country. So it's not as like, socialist or democratic as we wish for it to be. >> Well, that's a great point. I mean, when you just think about the clouds, the limitation, now you go out to the edge. I mean, everybody talks about the edge in IoT. Do you actually think that there's like a whole new stove pipe that's going to get created. And does that concern you, or do you think it actually is going to be, you know, connective tissue with all these clouds? >> I honestly don't know. I live in a practical world of like, how does it help me right now? How does it, you know, help me in the next five years? And mind you, in five years, things can change a lot. Because if you think back five years ago, things weren't as they are right now. I mean, I really hope that somebody out there challenges things 'cause, you know, the whole cloud promise was crazy. It was insane. Like, who came up with it? Why would I do that, right? And now I can't imagine the world without it. >> Yeah, I mean a lot of it is same wine, new bottle. You know, but a lot of it is different, right? I mean, technology keeps moving us forward, doesn't it? >> Absolutely. >> Veronika, it was great to have you. Thank you so much for your perspectives. If there was one thing that the industry could do for your data life that would make your world better, what would it be? >> I think standards for like data sharing, data marketplace. I would love, love, love nothing else to have some agreed upon standards. >> I had one other question for you, actually. I forgot to ask you this. 'Cause you were saying every company's a data company. Every company's a software company. We're already seeing it, but how prevalent do you think it will be that companies, you've seen some of it in financial services, but companies begin to now take their own data, their own tooling, their own software, which they've developed internally, and point that to the outside world? Kind of do what AWS did. You know, working backwards from the customer and saying, "Hey, we did this for ourselves. We can now do this for the rest of the world." Do you see that as a real trend, or is that Dave's pie in the sky? >> I think it's a real trend. Every company's trying to reinvent themselves and come up with new products. And every company is a data company. Every company collects data, and they're trying to figure out what to do with it. And again, it's not necessarily to sell it. Like, you don't have to sell data to monetize it. You can use it with your partners. You can exchange data. You know, you can create products. Capital One I think created a product for Snowflake pricing. I don't recall, but it just, you know, they built it for themselves, and they decided to kind of like, monetize on it. And I'm absolutely 100% on board with that. I think it's an amazing idea. >> Yeah, Goldman is another example. Nasdaq is basically taking their exchange stack and selling it around the world. And the cloud is available to do that. You don't have to build your own data center. >> Absolutely. Or for good, right? Like, we're talking about, again, we live in a capitalist country, but use data for good. We're collecting data. We're, you know, analyzing it, we're aggregating it. How can we use it for greater good for the planet? >> Veronika, thanks so much for coming to our Marlborough studios. Always a pleasure talking to you. >> Thank you so much for having me. >> You're really welcome. All right, stay tuned for more great content. From Supercloud 2, this is Dave Vellante. We'll be right back. (upbeat music)

(upbeat music) >> Hello everyone, welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE in theCUBE Studios. We've got a special video here. We love when we have startups that are launching. It's an exclusive video of a hot startup that's launching. Got great reviews so far. You know, word on the street is, they got something different and unique. We're going to' dig into it. Amit Govrin who's the CEO and co-founder of Kubiya, which stands for Cube in Hebrew, and they're headquartered in Bay Area and in Tel Aviv. Amit, congratulations on the startup launch and thanks for coming in and talk to us in theCUBE >> Thank you, John, very nice to be here. >> So, first of all, a little, 'cause we love the Cube, 'cause theCUBE's kind of an open brand. We've never seen the Cube in Hebrew, so is that true? Kubiya is? >> Kubiya literally means cube. You know, clearly there's some additional meanings that we can discuss. Obviously we're also launching a KubCon, so there's a dual meaning to this event. >> KubCon, not to be confused with CubeCon. Which is an event we might have someday and compete. No, I'm only kidding, good stuff. I want to get into the startup because I'm intrigued by your story. One, you know, conversational AI's been around, been a category. We've seen chat bots be all the rage and you know, I kind of don't mind chat bots on some sites. I can interact with some, you know, form based knowledge graph, whatever, knowledge database and get basic stuff self served. So I can see that, but it never really scaled or took off. And now with Cloud Native kind of going to the next level, we're starting to see a lot more open source and a lot more automation, in what I call AI as code or you know, AI as a service, machine learning, developer focused action. I think you guys might have an answer there. So if you don't mind, could you take a minute to explain what you guys are doing, what's different about Kubiya, what's happening? >> Certainly. So thank you for that. Kubiya is what we would consider the first, or one of the first, advanced virtual assitants with a domain specific expertise in DevOps. So, we respect all of the DevOps concepts, GitOps, workflow automation, of those categories you've mentioned, but also the added value of the conversational AI. That's really one of the few elements that we can really bring to the table to extract what we call intent based operations. And we can get into what that means in a little bit. I'll save that maybe for the next question. >> So the market you're going after is kind of, it's, I love to hear starters when they, they don't have a Gartner Magic quadrant, they can fit nicely, it means they're onto something. What is the market you're going after? Because you're seeing a lot of developers driving a lot of the key successes in DevOps. DevOps has evolved to the point where, and DevSecOps, where developers are driving the change. And so having something that's developer focused is key. Are you guys targeting the developers, IT buyers, cloud architects? Who are you looking to serve with this new opportunity? >> So essentially self-service in the world of DevOps, the end user typically would be a developer, but not only, and obviously the operators, those are the folks that we're actually looking to help augment a lot of their efforts, a lot of the toil that they're experiencing in a day to day. So there's subcategories within that. We can talk about the different internal developer tools, or platforms, shared services platforms, service catalogs are tangential categories that this kind of comes on. But on top of that, we're adding the element of conversational AI. Which, as I mentioned, that's really the "got you". >> I think you're starting to see a lot of autonomous stuff going on, autonomous pen testing. There's a company out there doing I've seen autonomous AI. Automation is a big theme of it. And I got to ask, are you guys on the business side purely in the cloud? Are you born in the cloud, is it a cloud service? What's the product choice there? It's a service, right? >> Software is a service. We have the classic, Multi-Tenancy SAAS, but we also have a hybrid SAAS solution, which allows our customers to run workflows using remote runners, essentially hosted at their own location. >> So primary cloud, but you're agnostic on where they could consume, how they want to' consume the product. >> Technology agnostic. >> Okay, so that's cool. So let's get into the problem you're solving. So take me through, this will drive a lot of value here, when you guys did the company, what problems did you hone in on and what are you guys seeing as the core problem that you solve? >> So we, this is a unique, I don't know how unique, but this is a interesting proposition because I come from the business side, so call it the top down. I've been in enterprise sales, I've been in a CRO, VP sales hat. My co-founder comes from the bottom up, right? He ran DevOps teams and SRE teams in his previous company. That's actually what he did. So, we met each other halfway, essentially with me seeing a lot of these problems of self-service not being so self-service after all, platforms hitting walls with adoption. And he actually created his own self-service platform, within his last company, to address his own personal pains. So we essentially kind of met with both perspectives. >> So you're absolutely hardcore on self-service. >> We're enabling self-service. >> And that basically is what everybody wants. I mean, the developers want self-service. I mean, that's kind of like, you know, that's the nirvana. So take us through what you guys are offering, give us an example of use cases and who's buying your product, why, and take us through that whole piece. >> Do you mind if I take a step back and say why we believe self-service has somewhat failed or not gotten off. >> Yeah, absolutely. >> So look, this is essentially how we're looking at it. All the analysts and the industry insiders are talking about self-service platforms as being what's going to' remove the dependency of the operator in the loop the entire time, right? Because the operator, that scarce resource, it's hard to hire, hard to train, hard to retain those folks, Developers are obviously dependent on them for productivity. So the operators in this case could be a DevOps, could be a SecOps, it could be a platform engineer. It comes in different flavors. But the common denominator, somebody needs an access request, provisioning a new environment, you name it, right? They go to somebody, that person is operator. The operator typically has a few things on their plate. It's not just attending and babysitting platforms, but it's also innovating, spinning up, and scaling services. So they see this typically as kind of, we don't really want to be here, we're going to' go and do this because we're on call. We have to take it on a chin, if you may, for this. >> It's their child, they got to' do it. >> Right, but it's KTLOs, right, keep the lights on, this is maintenance of a platform. It's not what they're born and bred to do, which is innovate. That's essentially what we're seeing, we're seeing that a lot of these platforms, once they finally hit the point of maturity, they're rolled out to the team. People come to serve themselves in platform, and low and behold, it's not as self-service as it may seem. >> We've seen that certainly with Kubernetes adoption being, I won't say slow, it's been fast, but it's been good. But I think this is kind of the promise of what SRE was supposed to be. You know, do it once and then babysit in the sense of it's working and automated. Nothing's broken yet. Don't call me unless you need something, I see that. So the question, you're trying to make it easier then, you're trying to free up the talent. >> Talent to operate and have essentially a human, like in the loop, essentially augment that person and give the end users all of the answers they require, as if they're talking to a person. >> I mean it's basically, you're taking the virtual assistant concept, or chat bot, to a level of expertise where there's intelligence, jargon, experience into the workflows that's known. Not just talking to chat bot, get a support number to rebook a hotel room. >> We're converting operational workflows into conversations. >> Give me an example, take me through an example. >> Sure, let's take a simple example. I mean, not everyone provisions EC2's with two days (indistinct). But let's say you want to go and provision new EC2 instances, okay? If you wanted to do it, you could go and talk to the assistant and say, "I want to spin up a new server". If it was a human in the loop, they would ask you the following questions: what type of environment? what are we attributing this to? what type of instance? security groups, machine images, you name it. So, these are the questions that typically somebody needs to be armed with before they can go and provision themselves, serve themselves. Now the problem is users don't always have these questions. So imagine the following scenario. Somebody comes in, they're in Jira ticket queue, they finally, their turn is up and the next question they don't have the answer to. So now they have to go and tap on a friend, or they have to go essentially and get that answer. By the time they get back, they lost their turn in queue. And then that happens again. So, they lose a context, they lose essentially the momentum. And a simple access request, or a simple provision request, can easily become a couple days of ping pong back and forth. This won't happen with the virtual assistant. >> You know, I think, you know, and you mentioned chat bots, but also RPA is out there, you've seen a lot of that growth. One of the hard things, and you brought this up, I want to get your reaction to, is contextualizing the workflow. It might not be apparent, but the answer might be there, it disrupts the entire experience at that point. RPA and chat bots don't have that contextualization. Is that what you guys do differently? Is that the unique flavor here? Is that difference between current chat bots and RPA? >> The way we see it, I alluded to the intent based operations. Let me give a tangible experience. Even not from our own world, this will be easy. It's a bidirectional feedback loop 'cause that's actually what feeds the context and the intent. We all know Waze, right, in the world of navigation. They didn't bring navigation systems to the world. What they did is they took the concept of navigation systems that are typically satellite guided and said it's not just enough to drive down the 280, which typically have no traffic, right, and to come across traffic and say, oh, why didn't my satellite pick that up? So they said, have the end users, the end nodes, feed that direction back, that feedback, right. There has to be a bidirectional feedback loop that the end nodes help educate the system, make the system be better, more customized. And that's essentially what we're allowing the end users. So the maintenance of the system isn't entirely in the hands of the operators, right? 'Cause that's the part that they dread. And the maintenance of the system is democratized across all the users that they can teach the system, give input to the system, hone in the system in order to make it more of the DNA of the organization. >> You and I were talking before you came on this camera interview, you said playfully that the Siri for DevOps, which kind of implies, hey infrastructure, do something for me. You know, we all know Siri, so we get that. So that kind of illustrates kind of where the direction is. Explain why you say that, what does that mean? Is that like a NorthStar vision that you guys are approaching? You want to' have a state where everything's automated in it's conversational deployments, that kind of thing. And take us through why that Siri for DevOps is. >> I think it helps anchor people to what a virtual assistant is. Because when you hear virtual assistant, that can mean any one of various connotations. So the Siri is actually a conversational assistant, but it's not necessarily a virtual assistant. So what we're saying is we're anchoring people to that thought and saying, we're actually allowing it to be operational, turning complex operations into simple conversations. >> I mean basically they take the automate with voice Google search or a query, what's the score of the game? And, it also, and talking to the guy who invented Siri, I actually interviewed on theCUBE, it's a learning system. It actually learns as it gets more usage, it learns. How do you guys see that evolving in DevOps? There's a lot of jargon in DevOps, a lot of configurations, a lot of different use cases, a lot of new technologies. What's the secret sauce behind what you guys do? Is it the conversational AI, is it the machine learning, is it the data, is it the model? Take us through the secret sauce. >> In fact, it's all the above. And I don't think we're bringing any one element to the table that hasn't been explored before, hasn't been done. It's a recipe, right? You give two people the same ingredients, they can have complete different results in terms of what they come out with. We, because of our domain expertise in DevOps, because of our familiarity with developer workflows with operators, we know how to give a very well suited recipe. Five course meal, hopefully with Michelin stars as part of that. So a few things, maybe a few of the secret sauce element, conversational AI, the ability to essentially go and extract the intent of the user, so that if we're missing context, the system is smart enough to go and to get that feedback and to essentially feed itself into that model. >> Someone might say, hey, you know, conversational AI, that was yesterday's trend, it never happened. It was kind of weak, chat bots were lame. What's different now and with you guys, and the market, that makes a redo or a second shot at this, a second bite at the apple, as they say. What do you guys see? 'Cause you know, I would argue that it's, you know, it's still early, real early. >> Certainly. >> How do you guys view that? How would you handle that objection? >> It's a fair question. I wasn't around the first time around to tell you what didn't work. I'm not afraid to share that the feedback that we're getting is phenomenal. People understand that we're actually customizing the workflows, the intent based operations to really help hone in on the dark spots. We call it last mile, you know, bottlenecks. And that's really where we're helping. We're helping in a way tribalize internal knowledge that typically hasn't been documented because it's painful enough to where people care about it but not painful enough to where you're going to' go and sit down an entire day and document it. And that's essentially what the virtual assistant can do. It can go and get into those crevices and help document, and operationalize all of those toils. And into workflows. >> Yeah, I mean some will call it grunt work, or low level work. And I think the automation is interesting. I think we're seeing this in a lot of these high scale situations where the talented hard to hire person is hired to do, say, things that were hard to do, but now harder things are coming around the corner. So, you know, serverless is great and all this is good, but it doesn't make the complexity go away. As these inflection points continue to drive more scale, the complexity kind of grows, but at the same time so is the ability to abstract away the complexity. So you're starting to see the smart, hired guns move to higher, bigger problems. And the automation seems to take the low level kind of like capabilities or the toil, or the grunt work, or the low level tasks that, you know, you don't want a high salaried person doing. Or I mean it's not so much that they don't want to' do it, they'll take one for the team, as you said, or take it on the chin, but there's other things to work on. >> I want to add one more thing, 'cause this goes into essentially what you just said. Think about it's not the virtual system, what it gives you is not just the intent and that's one element of it, is the ability to carry your operations with you to the place where you're not breaking your workflows, you're actually comfortable operating. So the virtual assistant lives inside of a command line interface, it lives inside of chat like Slack, and Teams, and Mattermost, and so forth. It also lives within a low-code editor. So we're not forcing anyone to use uncomfortable language or operations if they're not comfortable with. It's almost like Siri, it travels in your mobile phone, it's on your laptop, it's with you everywhere. >> It makes total sense. And the reason why I like this, and I want to' get your reaction on this because we've done a lot of interviews with DevOps, we've met at every CubeCon since it started, and Kubernetes kind of highlights the value of the containers at the orchestration level. But what's really going on is the DevOps developers, and the CICD pipeline, with infrastructure's code, they're basically have a infrastructure configuration at their disposal all the time. And all the ops challenges have been around that, the repetitive mundane tasks that most people do. There's like six or seven main use cases in DevOps. So the guardrails just need to be set. So it sounds like you guys are going down the road of saying, hey here's the use cases you can bounce around these use cases all day long. And just keep doing your jobs cause they're bolting on infrastructure to every application. >> There's one more element to this that we haven't really touched on. It's not just workflows and use cases, but it's also knowledge, right? Tribal knowledge, like you asked me for an example. You can type or talk to the assistant and ask, "How much am I spending on AWS, on US East 1, on so and so customer environment last week?", and it will know how to give you that information. >> Can I ask, should I buy a reserve instances or not? Can I ask that question? 'Cause there's always good trade offs between buying the reserve instances. I mean that's kind of the thing that. >> This is where our ecosystem actually comes in handy because we're not necessarily going to' go down every single domain and try to be the experts in here. We can tap into the partnerships, API, we have full extensibility in API and the software development kit that goes into. >> It's interesting, opinionated and declarative are buzzwords in developer language. So you started to get into this editorial thing. So I can bring up an example. Hey cube, implement the best service mesh. What answer does it give you? 'Cause there's different choices. >> Well this is actually where the operator, there's clearly guard rails. Like you can go and say, I want to' spin up a machine, and it will give you all of the machines on AWS. Doesn't mean you have to get the X one, that's good for a SAP environment. You could go and have guardrails in place where only the ones that are relevant to your team, ones that have resources and budgetary, you know, guidelines can be. So, the operator still has all the control. >> It was kind of tongue in cheek around the editorialized, but actually the answer seems to be as you're saying, whatever the customer decided their service mesh is. So I think this is where it gets into as an assistant to architecting and operating, that seems to be the real value. >> Now code snippets is a different story because that goes on to the web, that goes onto stock overflow, and that's actually one of the things. So inside the CLI, you could actually go and ask for code snippets and we could actually go and populate that, it's a smart CLI. So that's actually one of the things that are an added value of that. >> I was saying to a friend and we were talking about open source and how when I grew up, there was no open source. If you're a developer now, I mean there's so much code, it's not so much coding anymore as it is connecting and integrating. >> Certainly. >> And writing glue layers, if you will. I mean there's still code, but it's not, you don't have to build it from scratch. There's so much code out there. This low-code notion of a smart system is interesting 'cause it's very matrix like. It can build its own code. >> Yes, but I'm also a little wary with low-code and no code. I think part of the problem is we're so constantly focused on categories and categorizing ourselves, and different categories take on a life of their own. So low-code no code is not necessarily, even though we have the low-code editor, we're not necessarily considering ourselves low-code. >> Serverless, no code, low-code. I was so thrown on a term the other day, architecture-less. As a joke, no we don't need architecture. >> There's a use case around that by the way, yeah, we do. Show me my AWS architecture and it will build the architect diagram for you. >> Again, serverless architect, this is all part of infrastructure's code. At the end of the day, the developer has infrastructure with code. Again, how they deploy it is the neuron. That's what we've been striving for. >> But infrastructure is code. You can destroy, you know, terraform, you can go and create one. It's not necessarily going to' operate it for you. That's kind of where this comes in on top of that. So it's really complimentary to infrastructure. >> So final question, before we get into the origination story, data and security are two hot areas we're seeing fill the IT gap, that has moved into the developer role. IT is essentially provisioned by developers now, but the OP side shifted to large scale SRE like environments, security and data are critical. What's your opinion on those two things? >> I agree. Do you want me to give you the normal data as gravity? >> So you agree that IT is now, is kind of moved into the developer realm, but the new IT is data ops and security ops basically. >> A hundred percent, and the lines are so blurred. Like who's what in today's world. I mean, I can tell you, I have customers who call themselves five different roles in the same day. So it's, you know, at the end of the day I call 'em operators 'cause I don't want to offend anybody because that's just the way it is. >> Architectural-less, we're going to' come back to that. Well, I know we're going to' see you at CubeCon. >> Yes. >> We should catch up there and talk more. I'm looking forward to seeing how you guys get the feedback from the marketplace. It should be interesting to hear, the curious question I have for you is, what was the origination story? Why did you guys come together, was it a shared problem? Was it a big market opportunity? Was it an itch you guys were scratching? Did you feel like you needed to come together and start this company? What was the real vision behind the origination? Take a take a minute to explain the story. >> No, absolutely. So I've been living in Palo Alto for the last couple years. Previous, also a founder. So, you know, from my perspective, I always saw myself getting back in the game. Spent a few years in AWS essentially managing partnerships for tier one DevOps partners, you know, all of the known players. Some in public, some of them not. And really the itch was there, right. I saw what everyone's doing. I started seeing consistency in the pains that I was hearing back, in terms of what hasn't been solved. So I already had an opinion where I wanted to go. And when I was visiting actually Israel with the family, I was introduced by a mutual friend to Shaked, Shaked Askayo, my co-founder and CTO. Amazing guy, unbelievable technologists, probably one the most, you know, impressive folks I've had a chance to work with. And he actually solved a very similar problem, you know, in his own way in a previous company, BlueVine, a FinTech company where he was head of SRE, having to, essentially, oversee 200 developers in a very small team. The ratio was incongruent to what the SRE guideline would tell. >> That's more than 10 x rate developer. >> Oh, absolutely. Sure enough. And just imagine it's four different time zones. He finishes day shift and you already had the US team coming, asking for a question. He said, this is kind of a, >> Got to' clone himself, basically. >> Well, yes. He essentially said to me, I had no day, I had no life, but I had Corona, I had COVID, which meant I could work from home. And I essentially programed myself in the form of a bot. Essentially, when people came to him, he said, "Don't talk to me, talk to the bot". Now that was a different generation. >> Just a trivial example, but the idea was to automate the same queries all the time. There's an answer for that, go here. And that's the benefit of it. >> Yes, so he was able to see how easy it was to solve, I mean, how effective it was solving 70% of the toil in his organization. Scaling his team, froze the headcount and the developer team kept on going. So that meant that he was doing some right. >> When you have a problem, and you need to solve it, the creativity comes out of the woodwork, you know, invention is the mother of necessity. So final question for you, what's next? Got the launch, what are you guys hope to do over the next six months to a year, hiring? Put a plug in for the company. What are you guys looking to do? Take a minute to share the future vision and get a plug in. >> A hundred percent. So, Kubiya, as you can imagine, announcing ourselves at CubeCon, so in a couple weeks. Opening the gates towards the public beta and NGA in the next couple months. Essentially working with dozens of customers, Aston Martin, and business earn in. We have quite a few, our website's full of quotes. You can go ahead. But effectively we're looking to go and to bring the next operator, generation of operators, who value their time, who value the, essentially, the value of tribal knowledge that travels between organizations that could be essentially shared. >> How many customers do you guys have in your pre-launch? >> It's above a dozen. Without saying, because we're actually looking to onboard 10 more next week. So that's just an understatement. It changes from day to day. >> What's the number one thing people are saying about you? >> You got that right. I know it's, I'm trying to be a little bit more, you know. >> It's okay, you can be cocky, startups are good. But I mean they're obviously, they're using the product and you're getting good feedback. Saving time, are they saying this is a dream product? Got it right, what are some of the things? >> I think anybody who doesn't feel the pain won't know, but the folks who are in the trenches, or feeling the pain, or experiencing this toil, who know what this means, they said, "You're doing this different, you're doing this right. You architected it right. You know exactly what the developer workflows," you know, where all the areas, you know, where all the skeletons are hidden within that. And you're attending to that. So we're happy about that. >> Everybody wants to clone themselves, again, the tribal knowledge. I think this is a great example of where we see the world going. Make things autonomous, operationally automated for the use cases you know are lock solid. Why wouldn't you just deploy? >> Exactly, and we have a very generous free tier. People can, you know, there's a plugin, you can sign up for free until the end of the year. We have a generous free tier. Yeah, free forever tier, as well. So we're looking for people to try us out and to give us feedback. >> I think the self-service, I think the point is, we've talked about it on the Cube at our events, everyone says the same thing. Every developer wants self-service, period. Full stop, done. >> What they don't say is they need somebody to help them babysit to make sure they're doing it right. >> The old dashboard, green, yellow, red. >> I know it's an analogy that's not related, but have you been to Whole Foods? Have you gone through their self-service line? That's the beauty of it, right? Having someone in a loop helping you out throughout the time. You don't get confused, if something's not working, someone's helping you out, that's what people want. They want a human in the loop, or a human like in the loop. We're giving that next best thing. >> It's really the ratio, it's scale. It's a scaling. It's force multiplier, for sure. Amit, thanks for coming on, congratulations. >> Thank you so much. >> See you at KubeCon. Thanks for coming in, sharing the story. >> KubiyaCon. >> CubeCon. Cube in Hebrew, Kubiya. Founder, co-founder and CEO here, sharing the story in the launch. Conversational AI for DevOps, the theory of DevOps, really kind of changing the game, bringing efficiency, solving a lot of the pain points of large scale infrastructure. This is theCUBE, CUBE conversation, I'm John Furrier, thanks for watching. (upbeat electronic music)

(upbeat music) >> Kubernetes is maturing for example moving from quarterly releases to three per year, it's adding many of the capabilities that early on were avoided by Kubernetes committers, but now are going more mainstream, for example, more robust security and better support from mobile cluster management and other functions. But core Kubernetes by itself, doesn't get organizations where they need to go. That's why the ecosystem has stepped up to fill the gaps in application development. Developers as we know, they don't care about infrastructure, but they do care about building new apps, they care about modernizing existing apps, leveraging data, scaling, they care about automation look, they want to be cloud native. And one of the companies leading the ecosystem charge and building out more robust capabilities is Red Hat. And ahead of KubeCon Spain. It's our pleasure to welcome in Stu Miniman director of market insights at Red Hat to preview the event, Stu, good to see you, how you been? >> I'm doing awesome, Dave. Thanks for having me, great to be here. >> Yeah. So what's going on in Kube land these days? >> So it's funny Dave, if you were to kind of just listen out there in the marketplace, the CNCF has a survey that's like 96% of companies running Kubernetes production, everybody's doing it. And others will say, oh no, Kubernetes, only a small group group of people are using it, it's already probably got newer technologies that's replacing it. And the customers that I'm talking to Dave, first of all, yes, containers of Kubernetes, great growth growth rate, good adoption overall, I think we've said more than a year or two ago, we've probably crossed that chasm, the Jeff Moore, it's longer the early people just building all their own thing, taking all the open source, building this crazy stack that they need to had to do a lot of work we used to say. Chewing glass to be able to make it work right or anything, but it's still not as easy as you would like, almost no company that I talk to, if you're talking about big enterprises has Kubernetes just enterprise wide, and a hundred percent of their applications running on it. What is the tough challenge for people? And I mean, Dave, something, you and I have covered for many, many years, , that application portfolio that I have, most enterprises, hundreds, thousands of applications modernizing that having that truly be cloud native, that that's a really long journey and we are still in the midst of that, so I still still think we are in that, that if you look at the cross in the chasm that early majority chunk, so some of it is how do we mature things even better? And how do we make things simpler? Talk about things like automation, simplicity, security, we need to make sure they're all there so that it can be diffused and rolled out more broadly. And then we also need to think about where are we? We talk about the next million cloud customers, where does Kubernetes and containers and all the cloud native pieces fit into that broader discussion. Yes, there's some maturity there and we can declare victory on certain things, but there's still a lot, a lot of work that everyone's doing and that leads us into the show. I mean, dozens of projects that are already graduated, many more along that process from sandbox through a whole bunch of co-located events that are there, and it's always a great community event which Red Hat of course built on open source and community projects, so we're happy to have a good presence there as always. >> So you and I have talked about this in the past how essentially container's going to be embedded into a lot of different places, and sometimes it's hard to find, it's hard to track, but if you look at kind of the pre DevOps world skillsets like provisioning LANs, or configuring ports, or troubleshooting, squeezing more, server utilism, I mean, those who are really in high demand. If that's your skillset, then you're probably out of a job today. And so that's shifted toward things like Kubernetes. So you see and you see in the ETR data, it's along with cloud, and RPA, or automation, it is right up there I mean, it's top, the big four if you will, cloud, automation, RPA, and containers. And so we know there's a lot of spending activity going on there, but sometimes, like I said, it's hard to track I mean, if you got cloud growing at 35% a year, at least for the hyperscalers that we track, Kubernetes should be growing faster than that, should it not? >> Yeah, Dave, I would agree with you when I look at the big analyst firms that track this, I believe they've only got the container space at about a 25 per percent growth rate. >> Slower than cloud. But I compare that with Deepak Singh who runs at AWS, he has the open source office, he has all the containers and Kubernetes, and has visibility in all of that. And he says, basically, containers of the default when somebody's deploying to AWS today. Yes, serverless has its place, but it has not replaced or is not pushing down, slowing down the growth of containers or Kubernetes. We've got a strong partnership, I have lots of customers running on AWS. I guess I look at the numbers and like you, I would say that I would expect that that growth rate to be north of where just cloud in general is because the general adoption of containers and Kubernetes, we're still in the early phases of things. >> And I think a lot of the spendings Stu is actually in labor resources within companies and that's hard to track. Let's talk about what we should expect at the show. Obviously this whole notion of secure supply chain was a big deal last year in LA, what's hot? >> Yeah, so security Dave, absolutely. You said for years, it's a board level discussion, it's now something that really everyone in the organization has to know about the dev sec ops movement, has seen a lot of growth, secure supply chain, we're just trying to make sure that when I use open source, there's lots of projects, there is the huge ecosystem in marketplaces that are out there. So I want to make sure that as I grab all of the pieces that I know where they got came from the proper signature certification to make sure that the full solution that I build, I understand it. And if there are vulnerabilities, I know if there's an issue, how I patch it in the industry, we talk about CBEs, so those vulnerabilities, those exploits that come out, then everybody has to do a quick runaround to understand wait, hey, is my configuration? Am I vulnerable? Do I have to patch things? So security, absolutely still a huge, huge thing. Quick from a Red Hat standpoint, people might notice we made an acquisition a year ago of StackRox. That product itself also now has a completely fully open source project itself, also called StackRox. So the product is Red Hat advanced cluster security for Kubernetes, there's an open source equivalent for that called StackRox now, open source, community, there's a monthly office hour live streaming that a guy on my team actually does, and so there'll be a lot of activity at the show talking about security. So many other things happening at the show Dave. Another key area, you talked about the developers and what they want to worry about and what they don't. In the container space, there's a project called Knative. So Google helped create that, and that's to help me really have a serverless operational model, with still the containers and Kubernetes underneath that. So at the show, there will be the firs Knative con. And if you hadn't looked at Knative in a couple of years, one of the missing pieces that is now there is eventing. So if I look at functions and events, now that event capability is there, it's something I've talked to a lot of customers that were waiting for that to have it. It's not quite the same as like a Lambda, but is similar functionality that I can have with my containers in Kubernetes world. So that's an area that's there and so many others, I mean, GitOps are super hot at the last show. It's something that we've seen, really broad adoption since Argo CD went generally available last year, and lots of customers that are taking that to help them. That's both automation put together because I can allow GitHub to be my single source of truth for where I keep code, make sure I don't have any deviation from where the kind of the golden image if you will, it lives. >> So we're talking earlier about, how hard it is to track this stuff. So with the steep trajectory of growth and new customers coming on, there's got to be a lot of experimentation going on. That probably is being done, somebody downloads the open source code and starts playing with it. And then when they go to production that I would imagine Stu that's the point at which they say, hey, we need to fill some of these gaps. And they reach out to a company like yours and say, now we got to have certifications and trust., Do you. see that? >> So here's the big shift that happened, if we were looking four or five years ago, absolutely, I'd grab the open source code and some people might do that, but what cloud really enabled Dave, is rather than just grabbing, going to the dot the GitHub repo and pulling it down itself, I can go to the cloud so Microsoft, AWS, and Google all have their Kubernetes offering and I click a button. But that just gives me Kubernetes so there's still a steep learning curve. And as you said to build out out that full stack, that is one of the big things that we do with OpenShift is we take dozens of projects, pull them in together so you get a full platform. So you spend less time on curating, integrating, and managing that platform. And more time on the real value for your business, which is the application stack itself, the security and the like. And when we deliver OpenShift in the cloud, we have an SRE team that manages that for you. So one of the big challenges we have out there, there is a skillset gap, there are thousands of people getting certified on Kubernetes. There are, I think I saw over a hundred thousand job openings with Kubernetes mentioned in it, we just can't train people up fast enough, and the question I would have as an enterprise company is, if I'm going to the cloud, how much time do I want to build having SREs, having them focus on the infrastructure versus the things that are business specific. What did Amazon promise Dave? We're going to help you get rid of undifferentiated heavy lifting. Well, I just consume things as a service where I have an SRE team manage that environment. That might make more sense so that I can spend more time focusing on my business activities. That's a big focus that we've had on Red Hat, is our offerings that we have with the cloud providers to do and need offering. >> Yeah, the managed service capability is key. We saw, go back to the Hadoop days, we saw that's where Cloudera really struggled. They had to support every open source project. And then the customers largely had to figure it out themselves. Whereas you look at what data bricks did with spark. It was a managed service that was getting much greater adoption. So these complex areas, that's what you need. So people win sometimes when I use the term super cloud, and we getting little debates on Twitter, which is a lot of fun, but the idea is that you create the abstraction layer that spans your on-prem, your cloud, so you've got a hybrid. You want to go across clouds, what people call multi-cloud but as you know, I've sort of been skeptical of multi-cloud is really multi-vendor. But so we're talking about a substantial experience that's identical across those clouds and then ultimately out to the edge and we see a super Paas layer emerging, And people building on top of that, hiding the underlying complexity. What are your thoughts on that? How does Kubernetes in your view fit in? >> Yeah, it's funny, Dave, if you look at this container space at the beginning, Docker came out of a company called dotCloud. That was a PaaS company. And there's been so many times that that core functionality of how do I make my developers not have to worry about that underlying gank, but Dave, while the storage people might not have to worry about the LANs, somebody needs to understand how storage works, how networking works, if something breaks, how do I make sure I can take care of it. Sometimes that's a service that the SRE team manages that away from me. so that yes, there is something I don't need to think of about, but these are technically tough configurations. So first to one of your main questions, what do we see in customers with their hybrid and multi-cloud journey? So OpenShift over 10 years old, we started OpenShift before Kubernetes even was a thing. Lots of our customers run in what most people would consider hybrid, what does that mean? I have something in my data center, I have something in the cloud, OpenShift health, thanks to Kubernetes, I can have consistency for the developers, the operators, the security team, across those environments. Over the last few years, we've been doing a lot in the Kubernetes space as a whole, as the community, to get Kubernetes out to the edge. So one of the nice things, where do containers live Dave? Anywhere Linux does, is Linux going to be out of the edge? Absolutely, it can be a small footprint, we can do a lot with it. There were a lot of vendors that came out with it wasn't quite Kubernetes, they would strip certain things out or make a configuration that was smaller out at the edge, but a lot of times it was something that was just for a developer or something I could play with, and what it would break sometimes was that consistency out at the edge to what my other environments would like to have. And if I'm a company that needs consistency there. So take for example, if I have an AI workload where I need edge, and I need something in the cloud, or in my data center of consistency. So the easy use case that everybody thinks about is autonomous vehicles. We work with a lot of the big car manufacturers, I need to have when my developer build something, and often my training will be done either in the data center or in the public cloud, but I need to be able to push that out to the vehicle itself and let it run. We've actually even got Dave, we've got Kubernetes running up on the ISS. And you want to make sure that we have a consistency. >> The ultimate edge. >> Yeah, so I said, right, it's edge above and beyond the clouds even, we've gone to beyond. So that is something that the industry as a whole has been working at, from a Red Hat standpoint, we can take OpenShift to a really small footprint. Last year we launched was known as single node OpenShift. We have a project called micro shift, which is also fully open source that it has less pieces of the overall environment to be able to fit onto smaller and smaller devices there. But we want to be able to manage all of them consistently because you talked about multi cluster management. Well, what if I have thousands or 10 of thousands of devices out of the edge? I don't necessarily have network, I don't have people, I need to be able to do things from an automated standpoint. And that's where containers and Kubernetes really can shine. And where a lot of effort has been done in general and something specifically, we're working on it, Red Hat, we've had some great customers in the telecommunication space. Talk about like the 5G rollout with this, and industrial companies that need to be able to push out at the edge for these type of solutions. >> So you just kind of answered my next question, but I want to double click on it which was, if I'm in the cloud, why do I need you? And you touched on it because you've got primitives, and APIs, and AWS, Google, and Microsoft, they're different, if you're going to hide the underlying complexity of that, it takes a lot of RND and work, now extend that to a Tesla. You got to make it run there, different use case, but that's kind of what Linux and OpenShift are design to do, so double click on that. >> Yeah, so right. If I look at the discussion you've been having about super clouds is interesting because there are many companies that we work with that do live across multiple environments. So number one, if I'm a developer, if my company came to me and said, hey, you've got all your certifications and you got years of experience running on Amazon, well, we need you to go run over on Google. That developer might switch companies rather than switch clouds because they've got all of their knowledge and skillset, and it's a steep learning curve. So there's a lot of companies that work on, how can we give you tools and solutions that can live across those environments? So I know you mentioned companies like Snowflake, MongoDB, companies like Red Hat, HashiCorp, GitLab, also span all of those environments. There's a lot of work, Dave, to be different than not just, I say, I don't love the term like we're cloud agnostic, which would mean, well, you can use any cloud. >> You can run on any cloud. >> That's not what we're talking about. Look at the legacy that Red Hat has is, Red Hat has decades of running in every customer's data center and pick your X 86 server of choice. And we would have deep relationships when Dell, HP, IBM, Lenovo, you name it, comes out with a new piece of hardware that was different. We would have to make sure that the Linux primitives work from a Red Hat standpoint. Interesting Dave, we're now supporting OpenShift on Azure Stack Hub. And I talked to our head of product management, and I said, we've been running OpenShift in Azure for years, isn't Azure Stack Hub? Isn't that just Azure in your data center. He's like, yeah, but down at the operating system level, we had to change some flags and change some settings and things like that, so what do we know in IT? It's always the yeah, at the high level, it looks the same, it acts the same, it feels the same. >> Seamless. >> It's seamless in everything when you get down to the primitives level, sometimes that we need to be able to do that. I'll tell you Dave, there's things even when I look at A cloud, if I'm in US East One, or US West One, there actually could be some differences in what services are there or how things react, and so therefore we have a lot of deep work that goes into all of those environments, and it's not just Red Hat, we have a marketplace and an ecosystem, we want to make sure you've got API compatibility across all of those. So we are trying to help lift up this entire ecosystem and bring everybody along with it because you set it at the upfront, Kubernetes alone won't do it, oo one vendor gives you an entire, everything that you need for your developer tool chain. There's a lot that goes into this, and that's where we have deep commitment to partnerships. We build out and support lots of ecosystems. And this show itself is very much a community driven show. And, and therefore, that's why Red Hat has a strong presence at it, 'cause that's the open source community and everything that we built on. >> You guys are knee deep in it. You know I wrote down when you were talking about Snowflake and Mongo, HashiCorps, another one, I wrote down Dell, HP, Cisco, Lenovo, that to me, that should be their strategy. NetApp, their strategy should be to basically build out that abstraction layer, the so-called super cloud. So be interesting to see if they're going to be at this show. It requires a lot of R and D number one, number two, to your point, it requires an ecosystem. So you got all these guys, most of them now do in their own as a service, as a service is their own cloud. Their own cloud means you better have an ecosystem that's robust. I want to ask you about, do you ever think about what's next beyond Kubernetes? Or do you feel like, hey, there's just so much headroom in Kubernetes and so many active projects, we got ways to go. >> Yeah, so the Kubernetes itself Dave, should be able to fade into the background some. In many ways it does mirror what happened with Linux. So Linux is just the foundation of everything we have. We would not have the public cloud providers if it wasn't for Linux. I mean, Google, of course you wouldn't have without Linux, Amazon. >> Is on the internet. >> Right, but you might not have a lot of it. So Kubernetes, I think really goes the same way is, it is the foundational layer of what so much of it is built on top of it, and it's not really. So many people think about that portability. Oh, Google's the one that created it, and they wanted to make sure that it was easy if I want to go from the cloud provider that I had to use Kubernetes on Google cloud. And while that is a piece of it, that consistency is more important. And what I can build on top of it, it is really more of a distributed systems challenge that we are solving and that we've been working on in industry now for decades. So that is what we help solve, and what's really nice, containers and Kubernetes, it's less of an abstraction, it's more of new atomic unit of how we build things. So virtualization, I don't know what's underneath, and we spent like a decade fixing the storage networking components underneath so that the LANs matched right, and the network understood what was happening in the virtual machine. The atomic unit of a container, which is what Kubernetes manages is an application or a piece of an application. And therefore that there is less of an abstraction, more of just a rearchitecting of how we build things, and that is part of what is needed, and boy, Dave, the ecosystem, oh my God, yes, we've gone to only three releases a year, but I can tell you our roadmaps are all public on the internet and we talk heavily about them. There is still so many things that just at the basic Kubernetes piece, new architectures, arm devices are now in there, we're now supporting them, Kubernetes can support them too. So there are so many hardware pieces that are coming, so many software devices, the edge, we talked about it a bit, so there's so much that's going on. One of the areas that I love hearing about at the show, we have a community event called OpenShift Comments, which one of the main things of OpenShift Comments, is customers coming to talk about what they've been doing, and not about our products, we're talking about the projects and their journey overall. We've got a at Flenty Show, Airbus and Telefonica, are both going to be talking about what they're doing. We've seen Dave, every industry is going through their digital transformation journey. And it's great to hear straight from them what they're doing, and one of the big pieces in area, we actually spend a bunch of time on that application journey. There's a group of open source projects under what's known as Konveyor, that's conveyor with a K, Konveyor.io. It's modernization in migration. So how do I go from a VM to a container? How do I go from my data center to a cloud? How do I switch between services, open source projects to help with that journey? And, oh my gosh, Dave, I mean, you know in the cloud space, I mean that's what all the SIs and all the consultancies are throwing thousands of people at, is to help us get along that curve of that modernization journey. >> Okay, so let's see May 16th, the week of May 16th is KubeCon in Valencia Spain. theCUBE's going to be there, there was a little bit of a curfuffle on Twitter because the mask mandate was lifted in Spain and people had made plans thinking, okay, it's safe everybody's going to be wearing masks. Well, now I mean, you're going to have to make your own decisions on that front. I mean, you saw that you follow Twitter quite closely, but hey, this is the world we live in. So I'll give you the last word. >> Yeah, we'll see if Twitter still exists by the time we get to that show with. >> Could be private. What happens, but yeah, no, Dave, I'll be participating remotely, it is a hybrid event, so one of the things we'll be watching is, how many people are there in person LA was a pretty small show, core contributors, brought it back to some of the early days that you covered heavily from theCUBE standpoint, how Valencia will be? I know from Red Hat standpoint, we have people there, many of them from Europe, both speaking, we talked about many of the co-located events that are there, so a lot of pieces all participate remotely. So if you stop by the OpenShift commons event, I'll be part of the event just from a hybrid standpoint. And yeah, we've actually got the week before, we've got Red Hat Summit. So it's nice to actually to have back to back weeks. We'd had that a whole bunch of times before I remember, back to back weeks in Boston one year where we had both of those events and everything. That's definitely. >> Connective tissue. >> Keeps us busy there. You've got a whole bunch of travel going on. I'm not doing too much travel just yet, Dave, but it's good to see you and it's great to be connected with community. >> Yeah, so theCUBE will be there. John Furrier is hosting with Keith Townsend. So if you're in Valencia, definitely stop by. Stu thanks so much for coming into theCUBE Studios I appreciate it. >> Thanks, Dave. >> All right, and thank you for watching. We'll see you the week of May 16th in Valencia, Spain. (upbeat music)

>>Yeah. Hello and welcome back to the cubes coverage of AWS public sector summit here in Washington D. C. We're live on the ground for two days. Face to face conference and expo hall and everything here but keith brooks who is the director and head of technical business development for a dress government Govcloud selling brains 10th birthday. Congratulations. Welcome to the cube. Thank you john happy to be E. C. 2 15 S three is 9.5 or no, that maybe they're 10 because that's the same day as sqs So Govcloud. 10 years, 20 years. What time >>flies? 10 years? >>Big milestone. Congratulations. A lot of history involved in Govcloud. Yes. Take us through what's the current situation? >>Yeah. So um let's start with what it is just for the viewers that may not be familiar. So AWS Govcloud is isolated. AWS cloud infrastructure and services that were purposely built for our U. S. Government customers that had highly sensitive data or highly regulated data or applications and workloads that they wanted to move to the cloud. So we gave customers the ability to do that with AWS Govcloud. It is subject to the fed ramp I and D O D S R G I L four L five baselines. It gives customers the ability to address ITAR requirements as well as Seaga's N'est ce MMC and Phipps requirements and gives customers a multi region architecture that allows them to also designed for disaster recovery and high availability in terms of why we built it. It starts with our customers. It was pretty clear from the government that they needed a highly secure and highly compliant cloud infrastructure to innovate ahead of demand and that's what we delivered. So back in august of 2011 we launched AWS GovCloud which gave customers the best of breed in terms of high technology, high security, high compliance in the cloud to allow them to innovate for their mission critical workloads. Who >>was some of the early customers when you guys launched after the C. I. A deal intelligence community is a big one but some of the early customers. >>So the Department of Health and Human Services, the Department of Veterans Affairs, the Department of Justice and the Department of Defense were all early users of AWS GovCloud. But one of our earliest lighthouse customers was the Nasa jet propulsion laboratory and Nasa Jpl used AWS GovCloud to procure Procure resources ahead of demand which allowed them to save money and also take advantage of being efficient and only paying for what they needed. But they went beyond just I. T. Operations. They also looked at how do they use the cloud and specifically GovCloud for their mission programs. So if you think back to all the way to 2012 with the mars curiosity rover, Nasa Jpl actually streamed and processed and stored that data from the curiosity rover on AWS Govcloud They actually streamed over 150 terabytes of data responded to over 80,000 requests per second and took it beyond just imagery. They actually did high performance compute and data analytics on the data as well. That led to additional efficiencies for future. Over there >>were entire kicking they were actually >>hard core missing into it. Mission critical workloads that also adhere to itar compliance which is why they used AWS GovCloud. >>All these compliance. So there's also these levels. I remember when I was working on the jetty uh stories that were out there was always like level for those different classifications. What does all that mean like? And then this highly available data and highly high availability all these words mean something in these top secret clouds. Can you take us through kind of meetings >>of those? Yeah absolutely. So it starts with the federal compliance program and the two most popular programs are Fed ramp and Dodi srg fed ramp is more general for federal government agencies. There are three levels low moderate and high in the short and skinny of those levels is how they align to the fisma requirements of the government. So there's fisma low fisma moderate fisma high depending on the sensitivity of the government data you will have to align to those levels of Fed ramp to use workloads and store data in the cloud. Similar story for D. O. D. With srg impact levels to 45 and six uh impacts levels to four and five are all for unclassified data. Level two is for less sensitive public defense data levels. Four and five cover more sensitive defense data to include mission critical national security systems and impact level six is for classified information. So those form the basis of security and compliance, luckily with AWS GovCloud celebrating our 10th anniversary, we address Fed ramp high for our customers that require that and D. O. D impact levels to four and five for a sensitive defense guy. >>And that was a real nuanced point and a lot of the competition can't do that. That's real people don't understand, you know, this company, which is that company and all the lobbying and all the mudslinging that goes on. We've seen that in the industry. It's unfortunate, but it happens. Um, I do want to ask you about the Fed ramp because what I'm seeing on the commercial side in the cloud ecosystem, a lot of companies that aren't quote targeting public sector are coming in on the Fed ramp. So there's some good traction there. You guys have done a lot of work to accelerate that. Any new, any new information to share their. >>Yes. So we've been committed to supporting the federal government compliance requirements effectively since the launch of GovCloud. And we've demonstrated our commitment to Fed ramp over the last number of years and GovCloud specifically, we've taken dozens of services through Fed ramp high and we're 100% committed to it because we have great relationships with the Fed ramp, Jabor the joint authorization board. We work with individual government agencies to secure agency A. T. O. S. And in fact we actually have more agency A. T. O. S. With AWS GovCloud than any other cloud provider. And the short and skinny is that represents the baseline for cloud security to address sensitive government workloads and sensitive government data. And what we're seeing from industry and specifically highly regulated industries is the standard that the U. S. Government set means that they have the assurance to run control and classified information or other levels of highly sensitive data on the cloud as well. So Fed ramp set that standard. It's interesting >>that the cloud, this is the ecosystem within an ecosystem again within crossover section. So for instance um the impact of not getting Fed ramp certified is basically money. Right. If you're a supplier vendor uh software developer or whatever used to being a miracle, no one no one would know right bed ramp. I'm gonna have to hire a whole department right now. You guys have a really easy, this is a key value proposition, isn't it? >>Correct. And you see it with a number of I. S. V. S. And software as the service providers. If you visit the federal marketplace website, you'll see dozens of providers that have Fed ramp authorized third party SAAS products running on GovCloud industry leading SAAS companies like Salesforce dot com driven technology Splunk essay PNS to effectively they're bringing their best of breed capabilities, building on top of AWS GovCloud and offering those highly compliant fed ramp, moderate fed ramp high capabilities to customers both in government and private industry that need that level of compliance. >>Just as an aside, I saw they've got a nice tweet from Teresa Carlson now it's plunk Govcloud yesterday. That was a nice little positive gesture uh, for you guys at GovCloud, what other areas are you guys moving the needle on because architecturally this is a big deal. What are some areas that you're moving the needle on for the GovCloud? >>Well, when I look back across the last 10 years, there were some pretty important developments that stand out. The first is us launching the second Govcloud infrastructure region in 2018 And that gave customers that use GovCloud specifically customers that have highly sensitive data and high levels of compliance. The ability to build fault tolerant, highly available and mission critical workloads in the cloud in a region that also gives them an additional three availability zones. So the launch of GovCloud East, which is named AWS GovCloud Us East gave customers to regions a total of six availability zones that allowed them accelerate and build more scalable solutions in the cloud. More recently, there is an emergence of another D O D program called the cybersecurity maturity model, C M M C and C M M C is something where we looked around the corner and said we need to Innovate to help our customers, particularly defense customers and the defense industrial based customers address see MMC requirements in the cloud. So with Govcloud back in December of 2020, we actually launched the AWS compliant framework for federal defense workloads, which gives customers a turnkey capability and tooling and resources to spin up environments that are configured to meet see MMC controls and D. O. D. Srg control. So those things represent some of the >>evolution keith. I'm interested also in your thoughts on how you see the progression of Govcloud outside the United States. Tactical Edge get wavelength coming on board. How does how do you guys look at that? Obviously us is global, it's not just the jet, I think it's more of in general. Edge deployments, sovereignty is also going to be world's flat, Right? I mean, so how does that >>work? So it starts back with customer requirements and I tie it back to the first question effectively we built Govcloud to respond to our U. S. Government customers and are highly regulated industry customers that had highly sensitive data and a high bar to meet in terms of regulatory compliance and that's the foundation of it. So as we look to other customers to include those outside of the US. It starts with those requirements. You mentioned things like edge and hybrid and a good example of how we marry the two is when we launched a W. S. Outpost in Govcloud last year. So outpost brings the power of the AWS cloud to on premises environments of our customers, whether it's their data centers or Coehlo environments by bringing AWS services, a. P. I. S and service and points to the customer's on premises facilities >>even outside the United States. >>Well, for Govcloud is focused on us right now. Outside of the U. S. Customers also have availability to use outpost. It's just for us customers, it's focused on outpost availability, geography >>right now us. Right. But other governments gonna want their Govcloud too. Right, Right, that's what you're getting at, >>Right? And it starts with the data. Right? So we we we spent a lot of time working with government agencies across the globe to understand their regulations and their requirements and we use that to drive our decisions. And again, just like we started with govcloud 10 years ago, it starts with our customer requirements and we innovate from there. Well, >>I've been, I love the D. O. D. S vision on this. I know jet I didn't come through and kind of went scuttled, got thrown under the bus or whatever however you want to call it. But that whole idea of a tactical edge, it was pretty brilliant idea. Um so I'm looking forward to seeing more of that. That's where I was supposed to come in, get snowball, snowmobile, little snow snow products as well, how are they doing? And because they're all part of the family to, >>they are and they're available in Govcloud and they're also authorized that fed ramp and Gov srg levels and it's really, it's really fascinating to see D. O. D innovate with the cloud. Right. So you mentioned tactical edge. So whether it's snowball devices or using outposts in the future, I think the D. O. D. And our defense customers are going to continue to innovate. And quite frankly for us, it represents our commitment to the space we want to make sure our defense customers and the defense industrial base defense contractors have access to the best debris capabilities like those edge devices and edge capable. I >>think about the impact of certification, which is good because I just thought of a clean crows. We've got aerospace coming in now you've got D O. D, a little bit of a cross colonization if you will. So nice to have that flexibility. I got to ask you about just how you view just in general, the intelligence community a lot of uptake since the CIA deal with amazon Just overall good health for eight of his gum cloud. >>Absolutely. And again, it starts with our commitment to our customers. We want to make sure that our national security customers are defense customers and all of the customers and the federal government that have a responsibility for securing the country have access to the best of breed capability. So whether it's the intelligence community, the Department of Defense are the federal agencies and quite frankly we see them innovating and driving things forward to include with their sensitive workloads that run in Govcloud, >>what's your strategy for partnerships as you work on the ecosystem? You do a lot with strategy. Go to market partnerships. Um, it's got its public sector pretty much people all know each other. Our new firms popping up new brands. What's the, what's the ecosystem looks like? >>Yeah, it's pretty diverse. So for Govcloud specifically, if you look at partners in the defense community, we work with aerospace companies like Lockheed martin and Raytheon Technologies to help them build I tar compliant E. R. P. Application, software development environments etcetera. We work with software companies I mentioned salesforce dot com. Splunk and S. A. P. And S. To uh and then even at the state and local government level, there's a company called Pay It that actually worked with the state of Kansas to develop the Icann app, which is pretty fascinating. It's a app that is the official app of the state of Kansas that allow citizens to interact with citizens services. That's all through a partner. So we continue to work with our partner uh broad the AWS partner network to bring those type of people >>You got a lot of MST is that are doing good work here. I saw someone out here uh 10 years. Congratulations. What's the coolest thing uh you've done or seen. >>Oh wow, it's hard to name anything in particular. I just think for us it's just seeing the customers and the federal government innovate right? And, and tie that innovation to mission critical workloads that are highly important. Again, it reflects our commitment to give these government customers and the government contractors the best of breed capabilities and some of the innovation we just see coming from the federal government leveraging the count now. It's just super cool. So hard to pinpoint one specific thing. But I love the innovation and it's hard to pick a favorite >>Child that we always say. It's kind of a trick question I do have to ask you about just in general, the just in 10 years. Just look at the agility. Yeah, I mean if you told me 10 years ago the government would be moving at any, any agile anything. They were a glacier in terms of change, right? Procure Man, you name it. It's just like, it's a racket. It's a racket. So, so, but they weren't, they were slow and money now. Pandemic hits this year. Last year, everything's up for grabs. The script has been flipped >>exactly. And you know what, what's interesting is there were actually a few federal government agencies that really paved the way for what you're seeing today. I'll give you some examples. So the Department of Veterans Affairs, they were an early Govcloud user and way back in 2015 they launched vets dot gov on gov cloud, which is an online platform that gave veterans the ability to apply for manage and track their benefits. Those type of initiatives paved the way for what you're seeing today, even as soon as last year with the U. S. Census, right? They brought the decennial count online for the first time in history last year, during 2020 during the pandemic and the Census Bureau was able to use Govcloud to launch and run 2020 census dot gov in the cloud at scale to secure that data. So those are examples of federal agencies that really kind of paved the way and leading to what you're saying is it's kind >>of an awakening. It is and I think one of the things that no one's reporting is kind of a cultural revolution is the talent underneath that way, the younger people like finally like and so it's cooler. It is when you go fast and you can make things change, skeptics turned into naysayers turned into like out of a job or they don't transform so like that whole blocker mentality gets exposed just like shelf where software you don't know what it does until the cloud is not performing, its not good. Right, right. >>Right. Into that point. That's why we spend a lot of time focused on education programs and up skilling the workforce to, because we want to ensure that as our customers mature and as they innovate, we're providing the right training and resources to help them along their journey, >>keith brooks great conversation, great insight and historian to taking us to the early days of Govcloud. Thanks for coming on the cube. Thanks thanks for having me cubes coverage here and address public sector summit. We'll be back with more coverage after this short break. Mhm. Mhm mm.

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to You by Dell Technologies. >>Welcome to the Cubes Coverage of Dell Technologies World 2020. The Digital Experience. I'm Lisa Martin, and I'm pleased to welcome back a Cube alumni and a new Cube member to the program today. China. My Mondal is back with US Director of Solutions Marketing for Dell Technologies China. But it's great to see you at Dell Technologies world, even though we're very specially death. >>Happy to be back. Thank you, Lisa. >>And Thomas Henson is joining us for the first time. Global business development manager for a I and analytics. Thomas, Welcome to the Cube. >>I am excited to be here. It's my first virtual cube. >>Yeah, well, you better make it a good one. All right. I said we're talking about a I so so much has changed John to me. The last time I saw you were probably were sitting a lot closer together. So much has changed in the last 67 months, but a lot has changed with the adoption of Ai Thomas. Kick us off. What are some of the big things feeling ai adoption right now? >>Yeah, I >>would have to >>say the two biggest things right now or as we look at accelerated compute and by accelerated compute we're not just talking about the continuation of Moore's law, but how In Data Analytics, we're actually doing more processing now with GP use, which give us faster insights. And so now we have the ability to get quicker insights in jobs that may have taken, you know, taking weeks to months a song as we were measuring. And then the second portion is when we start to talk about the innovation going on in the software and framework world, right? So no longer do you have toe know C plus plus or a lower level language. You can actually do it in Python and even pull it off of Get Hub. And it's all part of that open source community. So we're seeing Mawr more folks in the field of data science and deep learning that can actually implement some code. And then we've got faster compute to be able to process that. >>Tell me, what are your thoughts? >>Think I want to add? Is the explosive growth off data on that's actually are fulfilling the AI adoption. Think off. Like all the devices we have, the i o t. On age devices are doing data are pumping data into the pipeline. Our high resolution satellite imagery, all social media generating data. No. All of this data are actually helping the adoption off a I because now we have very granular data tow our friend the AI model Make the AI models are much better. Besides, so the combination off both in, uh, data the power off Like GPU, power surfers are coupled with the inefficient in the eye after and tools helping off. Well, the AI growth that we're seeing today >>trying to make one of the things that we've known for a while now is that it's for a I to be valuable. It's about extracting value from that. Did it? You talked about the massive explosion and data, but yet we know for a long time we've been talking about AI for decades. Initiatives can fail. What can Dell Technologies do now to help companies have successfully I project? >>Yeah, eso As you were saying, Lisa, what we're seeing is the companies are trying to add up AI Technologies toe Dr Value and extract value from their data set. Now the way it needs to be framed is there is a business challenge that customers air trying to solve. The business challenge gets transformed into a data science problem. That data scientist is going toe work with the high technology, trained them on it. That data science problem gets to the data science solution on. Then it needs to be mapped to production deployment as a business solution. What happens? Ah, lot off. The time is the companies do not plan for output transition from all scale proof of concept that it a scientists are playing with, like a smaller set of data two, when it goes toe the large production deployment dealing with terabytes toe terabyte self data. Now that's where we come in. At their technologies, we have into end solutions for the, uh for the ai for pollution in the customers journeys starting from proof of concept to production. And it is all a seamless consular and very scalable. >>So if some of the challenges there are just starting with iterations. Thomas question for you as business development manager, those folks that John um I talked about the data scientists, the business. How are you helping them come together from the beginning so that when the POC is initiated, it actually can go on the right trajectory to be successful? >>No, that's a great point. And just to kind of build off of what Shonda my was talking about, You know, we call it that last mile, right? Like, Hey, I've got a great POC. How do I get into production? Well, if you have executive sponsorship and it's like, Hey, everybody was on board, but it's gonna take six months to a year. It's like, Whoa, you're gonna lose some momentum. So where we help our customers is, you know, by partnering with them to show them how to build, you know, from an i t. And infrastructure perspective what that ai architectural looks like, right? So we have multiple solutions around that, and at the end of the day, it's about just like Sean. Um, I was saying, You know, we may start off with a project that maybe it's only half a terabyte. Maybe it's 10 terabytes, but once you go into production, if it turns out to be three petabytes four petabytes. Nobody really, you know, has the infrastructure built unless they built on those solid practices. And that's where our solutions come in. So we can go from small scale laboratory all the way large scale production without having to move any of that data. Right? So, you know, at the heart of that is power scale and giving you that ability to scale your data and no more data migration so that you can handle one PC or multiple PCs as those models continue to improve as you start to move into production >>and I'm sticking with you 1st. 2nd 0, sorry. Trying to go ahead. >>So I was going to add that, uh, just like posthumous said right. So if you were a data scientist, you are working with this data science workstations, but getting the data from, uh, L M c our scales thes scale out platform and, uh, as it is growing from, you see two large kills production data can stay in place with the power scale platform. You can add notes, and it can grow to petabytes. And you can add in not just the workstations, but also our They'll power it, solve our switches building out our enter A I ready solutions are already solution for your production. Giving are very seamless experience from the data scientist with the i t. >>So China may will stick with you then. I'm curious to know in the last 6 to 7 months since 2020 has gone in a very different direction thing we all would have predicted our last Dell Technologies world together. What are you seeing? China. My in terms of acceleration or maybe different industries. What our customers needs, how they changed. I guess I should say in the in 2020. >>So in 2020 we're seeing the adoption off a I even more rapidly. Uh, if you think about customers ranging from like say, uh, media and entertainment industry toe, uh, the customer services off any organization to, uh the healthcare and life sciences with lots off genome analysts is going on in all of these places where we're dealing with large are datasets. We're seeing ah, lot off adoption foster processing off A. I R. Technologies, uh, giving with, say, the all the research that the's Biosciences organizations are happening. Uh, Thomas, I know like you are working with, like, a customer. So, uh, can you give us a little bit more example in there? >>Yes, one of the areas. You know, we're talking about 2021 of the things that we're seeing Mawr and Mawr is just the expansion of Just look at the need for customer support, right arm or folks working remotely their arm or folks that are learning remote. I know my child is going through virtual schools, So think about your I t organization and how Maney calls you're having now to expand. And so this is a great area where we're starting to see innovation within a I and model building to be ableto have you know, let's call it, you know, the next generation of chatbots rights. You can actually build these models off the data toe, augment those soup sports systems >>because you >>have two choices, right? You can either. You know, you you can either expand out your call center right for for we're not sure how long or you can use AI and analytics to help augment to help maybe answer some of those first baseline questions. The great thing about customers who are choosing power scale and Dell Technologies. Their partner is they already have. The resource is to be able to hold on to that data That's gonna help them train those models to help. >>So, Thomas, whenever we're talking about data, the explosions it brings to mind compliance. Protection, security. We've seen ransom where really skyrocket in 2020. Just you know, the other week there was the VA was hit. Um, I think there was also a social media Facebook instagram ticktock, 235 million users because there was an unsecured cloud database. So that vector is expanding. How can you help customers? Customers accelerate their AI projects? Well, ensuring compliance and protection and security of that data. >>Really? That's the sweet spot for power scale. We're talking with customers, right? You know, built on one FS with all the security features in mind. And I, too, came from the analytics world. So I remember in the early days of Hadoop, where, you know, as a software developer, we didn't need security, right? We you know, we were doing researching stuff, but then when we took it to the customer and and we're pushing to production, But what about all the security features. We needed >>the same thing >>for artificial intelligence, right? We want toe. We want to make sure that we're putting those security features and compliance is in. And that's where you know, from from an AI architecture perspective, by starting with one FS is at the heart of that solution. You can know that you're protecting for you know, all the enterprise features that you need, whether it be from compliance, thio, data strategy, toe backup and recovery as well. >>So when we're talking about big data volumes Chanda, mind we have to talk about the hyper scale er's talk to us about, you know, they each offer azure A W s Google cloud hundreds of AI services. So how does DEL help customers use the public cloud the data that's created outside of it and use all of those use that the right AI services to extract that value? >>Yeah. Now, as you mentioned, all of these hyper scholars are they differentiate with our office is like a i m l r Deep Learning Technologies, right? And as our customer, you want toe leverage based off all the, uh, all the cloud has to offer and not stuck with one particular cloud provider. However, we're talking about terabytes off data, right? So if you are happy with what doing service A from cloud provider say Google what you want to move to take advantage off another surface off from Asia? It comes with a very high English p a migration risk on time it will take to move the data itself. Now that's not good, right? As the customer, we should be able to live for it. Best off breed our cloud services for AI and for that matter, for anything across the board. Now, how we help customers is you can have all of your data say, in a managed, uh, managed cloud service provider running on power scale. But then you can connect from this managed cloud service provider directly toe any off the hyper scholars. You can connect toe aws, azure, Google Cloud and even, like even, uh, the in place analytics that power scale offers you can run. Uh, those, uh I mean, run those clouds AI services directly on that data simultaneously from these three, and I'll add like one more thing, right? Thes keep learning. Technologies need GPU power solvers, right? and cloud even within like one cloud is not homogeneous environment. Like sometimes you'll find a US East has or gp part solvers. But like you are in the West and the same for other providers. No, with our still our technologies cloud power scale for multi cloud our scale is sitting outside off those hyper scholars connected directly to our any off this on. Then you can burst into different clouds, take advantage off our spot. Instances on are like leverage. All the GP is not from one particular service provider part. All of those be our hyper scholars. So those are some examples off the work we're doing in the multi cloud world for a I >>So that's day. You're talking about data there. So powers failed for multi cloud for data that's created outside the public club. But Thomas, what about for data that's created inside the cloud? How does Del help with that? >>Yes. So, this year, we actually released a solution, uh, in conjunction with G C. P. So within Google Cloud, you can have power scale for one fs, right? And so that's that native native feature. So, you know, goes through all the compliance and all the features within being a part of that G c p natively eso counts towards your credits and your GP Google building as well. But it's still all the features that you have. And so we've been running some, actually, some benchmarks. So we've got a couple of white papers out there, that kind of detail. You know what we can do from an artificial intelligence perspective back to Sean Demise Example. We were just talking about, you know, being able to use more and more GPU. So we we've done that to run some of our AI benchmarks against that and then also, you know, jumped into the Hadoop space. But because you know, that's 11 area from a power scale, prospective customers were really interested. Um, and they have been for years. And then, really, the the awesome portion about this is for customers that are looking for a hybrid solution. Or maybe it's their first kickoff to it. So back Lisa to those compliance features that we were talking about those air still inherent within that native Google G C P one fs version, but then also for customers that have it on prim. You can use those same features to burst your data into, um, your isil on cluster using all the same native tools that you've been using for years within your enterprise. >>God, it's so starting out for power. Skill for Google Cloud Trying to get back to you Kind of wrapping things up here. What are some of the things that we're going to see next from Dell from an AI Solutions perspective? >>Yes. So we are working on many different interesting projects ranging from, uh, the latest, uh, in video Salford's that they have announced d d x a 100. And in fact, two weeks ago at GTC, uh, Syria announced take too far parts with, uh, it takes a 100 solvers. We're part off that ecosystem. And we are working with, uh, the leading, uh uh, solutions toe benchmark, our ai, uh, environments, uh, for all the storage, uh, ensuring, like we are providing, like, all the throughput and scalability that we have to offer >>Thomas finishing with you from the customer perspective. As we talked about so many changes this year alone as we approach calendar year 2021 what are some of the things that Dell is doing with its customers with its partners, the hyper scale er's and video, for example, Do you think customers are really going to be able to truly accelerate successful AI projects? >>Yeah. So the first thing I'd like to talk about is what we're doing with the D. G. S A 100. So this month that GTC you saw our solution for a reference architecture for the G s, a 100 plus power scale. So you talk about speed and how we can move customers insights. I mean, some of the numbers that we're seeing off of that are really a really amazing right. And so this is gives the customers the ability to still, you know, take all the features and use use I salon and one f s, um, like they have in the past, but now combined with the speed of the A 100 still be ableto speed up. How fast they're using those building out those deep learning models and then secondly, with that that gives them the ability to scale to. So there's some features inherent within this reference architecture that allow for you to make more use, right? So bring mawr data scientists and more modelers GP use because that's one thing you don't see Data scientist turning away right there always like, Hey, you know, I mean, this this project here needs needs a GPU. And so, you know, from a power scale one fs perspective, we want to be able to make sure that we're supporting that. So that as that data continues to grow, which, you know we're seeing is one of the large factors. Whenever we're talking about artificial intelligence is the scale for the data. We wanna them to be able to continue to build out that data consolidation area for all these multiple different workloads. That air coming in. >>Excellent, Thomas. Thanks for sharing that. Hopefully next time we get to see you guys in person and we can talk about a customer who has done something very successful with you guys. Kind of me. Always great to talk to you. Thank you for joining us. >>Thank you. Thank you >>for China. May Mandel and Thomas Henson. I'm Lisa Martin. You're watching the cubes Coverage of Dell Technologies, World 2020

>> Hello, everyone. I'm Khalil Ahmad, Senior Director, Architecture at S&P Global. I have been working with S&P Global for six years now. Previously, I worked for Citigroup and Prudential. Overall, I have been part of IT industry for 30 years, and most of my professional career has been within financial sector in New York City metro area. I live in New Jersey with my wife and son, Daniel Khalil. I have a Master degree in software engineering from the University of Scranton, and Master in mathematics University of Punjab, Lahore. And currently I am pursuing TRIUM global Executive MBA. A joint program from the NYU Stern, LSE and HEC Paris. So today, I'm going to talk about building multi-cluster scalable container platform, supporting on-prem hybrid and multicloud use cases, how we leverage that with an S&P Global and what was our best story. As far as the agenda is concerned, I will go over, quickly the problem statement. Then I will mention the work of our core requirements, how we get solutioning, how Docker Enterprise helped us. And at the end, I will go over the pilot deployment for a proof of concept which we leverage. So, as far as the problem statement is concerned. Containers, as you all know, in the enterprise are becoming mainstream but expertise remains limited and challenges are mounting as containers enter production. Some companies are building skills internally and someone looking for partners that can help catalyze success, and choosing more integrated solutions that accelerate deployments and simplify the container environment. To overcome the challenges, we at S&P Global started our journey a few years back, taking advantage of both options. So, first of all, we met with all the stakeholder, application team, Product Manager and we define our core requirements. What we want out of this container platform, which supports multicloud and hybrid supporting on-prem as well. So, as you see my core requirements, we decided that we need first of all a roadmap or container strategy, providing guidelines on standards and specification. Secondly, with an S&P Global, we decided to introduce Platform as a Service approach, where we bring the container platform and provide that as a service internally to our all application team and all the Product Managers. Hosting multiple application on-prem as well as in multicloud. Third requirement was that we need Linux and Windows container support. In addition to that, we would also require hosted secure image registry with role based access control and image security scanning. In addition to that, we also started DevOps journey, so we want to have a full support of CI/CD pipeline. Whatever the solution we recommend from the architecture group, it should be easily integrated to the developer workstation. And developer workstation could be Windows, Mac or Linux. Orchestration, performance and control were few other parameter which we'll want to keep in mind. And the most important, dynamic scaling of container clusters. That was something we were also want to achieve, when we introduce this Platform as a Service. So, as far as the standard specification are concerned, we turn to the Open Container Initiative, the OCI. OCI was established in June 2015 by Docker and other leaders in the technology industry. And OCI operates under Linux Foundation, and currently contains two specification, runtime specification and image specification. So, at that time, it was a no brainer, other than to just stick with OCI. So, we are following the industry standard and specifications. Now the next step was, okay, the container platform. But what would be our runtime engine? What would be orchestration? And how we support, in our on-prem as well as in the multicloud infrastructure? So, when it comes to runtime engine, we decided to go with the Docker. Which is by default, runtime engine and Kubernetes. And if I may mention, DataDog in one of their public report, they say Docker is probably the most talked about infrastructure technology for the past few years. So, sticking to Docker runtime engine was another win-win game and we saw in future not bringing any challenge or issues. When it comes to orchestration. We prefer Kubernetes but that time there was a challenge, Kubernetes did not support Windows container. So, we wanted something which worked with a Linux container, and also has the ability or to orchestrate Windows containers. So, even though long term we want to stick to Kubernetes, but we also wanted to have a Docker swarm. When it comes to on-prem and multicloud, technically you could only support as of now, technology may change in future, but as of now, you can only support if you bring your own orchestration too. So, in our case, if we have control over orchestration control and not locked in with one cloud provider, that was the ideal situation. So, with all that, research, R&D and finding, we found Docker Enterprise. Which is securely built, share and run modern applications anywhere. So, when we come across Docker Enterprise, we were pleased to see that it meets our most of the core requirements. Whether it is coming on the developer machine, to integrating their workstation, building the application. Whether it comes to sharing those application, in a secure way and collaborating with our pipeline. And the lastly, when it comes to the running. If we run in hybrid or multicloud or edge, in Kubernetes, Docker Enterprise have the support all the way. So, three area one I just call up all the Docker Enterprise, choice, flexibility and security. I'm sure there's a lot more features in Docker Enterprise as a suite. But, when we looked at these three words very quickly, simplified hybrid orchestration. Define application centric policies and boundaries. Once you define, you're all set. Then you just maintain those policies. Manage diverse application across mixed infrastructure, with secure segmentation. Then it comes to secure software supply chain. Provenance across the entire lifecycle of apps and infrastructure through enforceable policy. Consistently manage all apps and infrastructure. And lastly, when it comes to infrastructure independence. It was easily forever lift and shift, because same time, our cloud journey was in the flight. We were moving from on-prem to the cloud. So, support for lift and shift application was one of our wishlist. And Docker Enterprise did not disappoint us. It also supported both traditional and micro services apps on any infrastructure. So, here we are, Docker Enterprise. Why Docker Enterprise? Some of the items in previous slides I mentioned. But in addition to those industry-leading platform, simplifying the IT operations, for running modern application at scale, anywhere. Docker Enterprise also has developer tools. So, the integration, as I mentioned earlier was smooth. In addition to all these tools, the main two components, the Universal Control Plane and the Docker Trusted Registry, solve lot of our problems. When it comes to the orchestration, we have our own Universal Control Plane. Which under the hood, manages Kubernetes and Docker swarm both clusters. So, guess what? We have a Windows support, through Docker swarm and we have a Linux support through Kubernetes. Now that paradigm has changed, as of today, Kubernetes support Windows container. So, guess what? We are well after the UCP, because we have our own orchestration tool, and we start managing Kubernetes cluster in Linux and introduce now, Windows as well. Then comes to the Docker Trusted Registry. Integrated Security and role based access control, made a very smooth transition from our RT storage to DTR. In addition to that, binary level scanning was another good feature from the security point of view. So that, these all options and our R&D landed the Docker Enterprise is the way to go. And if we go over the Docker Enterprise, we can spin up multiple clusters on-prem and in the cloud. And we have a one centralized location to manage those clusters. >> Khalil: So, with all that, now let's talk about how what was our pilot deployment, for proof of concept. In this diagram, you can see we, on the left side is our on-prem Data Center, on the right side is AWS, US East Coast. We picked up one region three zones. And on-prem, we picked up our Data Center, one of the Data Center in the United States of America, and we started the POC. So, our Universal Control Plane had a five nodes cluster. Docker Trusted Registry, also has a five node cluster. And the both, but in our on-prem Data Center. When it comes to the worker nodes, we have started with 18 node cluster, on the Linux side and the four node cluster on the Windows side. Because the major footprint which we have was on the Linux side, and the Windows use cases were pretty small. Also, this is just a proof of concept. And in AWS, we mimic the same web worker nodes, virtual to what we have on-prem. We have a 13 nodes cluster on Linux. And we started with four node cluster of Windows container. And having the direct connect from our Data Center to AWS, which was previously existing, so we did not have any connectivity or latency issue. Now, if you see in this diagram, you have a centralized, Universal Control Plane and your trusted registry. And we were able to spin up a cluster, on-prem as well as in the cloud. And we made this happen, end to end in record time. So later, when we deploy this in production, we also added another cloud provider. So, what you see the box on the right side, we just duplicate test that box in another cloud platform. So, now other orchestration tool, managing on-prem and multicloud clusters. Now, in your use case, you may find this little, you know, more in favor of on-prem. But that fit in our use case. Later, we did have expanded the cluster of Universal Control Plane and DTR in the cloud as well. And the clusters have gone and hundreds and thousands of worker nodes span over two cloud providers, third being discussed. And this solution has been working so far, very good. We did not see any downtime, not a single instance. And we were able to provide multicloud platform, container Platform as a Service for our S&P Global. Thank you for your time. If any questions, I have put my LinkedIn and Twitter account holder, you're welcome to ask any question

>> Instructor: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Partner Awards brought to you by, Amazon Web Services. >> Hello everyone, welcome to the special CUBE program. We are here with the Amazon Web Services public sector, partner awards program. It's a celebration of AWS, public sectors, partners and their end user customers, where there's been innovation. And we're pleased to have on the show here, the award winner for the most innovative AI, and ML artificial intelligence and machine learning solution. Axial3D is the newest partner and the end user is Belfast hospital. We got Roger Johnson, the CEO of Axial3D, and Dr. Tim Brown consulted transplant surgeon, at Belfast hospital, who has been doing amazing things, not only on the as an innovative partner, but really during COVID, making things happen, by solving the problem of the surgical gap and the number of surgeries that you're doing. Really high performance saving lives, congratulations. First of all, congratulations Roger and Dr.Tim Brown, thanks for joining me. >> We're pleasure. >> Okay, let's get into it. First of all, Dr. Tim Brown, I really want to commend you on the amazing work, that you're doing. Before we get, into some of the partnership awards conversations. You have been at the front lines solving a lot of problems around the gap, between the number of surgeries, that could take place with COVID. Tell that story real quick. I really think it's super important. Take a minute to explain. >> Yeah, thanks for the opportunity. And it's been an incredible roller coaster, for the last three months. And pretty much all of the transplant programs, across the world who have been affected, by COVID have shut down. But with some pretty innovative and real leadership and team working advances, we've managed to open a program up again and in Belfast, we have about 50 deceased donor transplants a year. Over the last three months, we've just done 90 kidney transplants and pretty much we've cleared, the whole waiting list in Northern Ireland pretty much, for people waiting for a kidney transplant in this time. And it's been a remarkable few weeks. But really is a testament to the critical care community, the people that work in intensive care, as to how much they support organ donation. And of course, our donors who have given so selflessly, at such a tragic time for them. So I'd like to pay tribute to all of our donors, and to the amazing amount of people, who have been involved in the teamwork and Belfast at this time. >> That's super amazing. Can you just I just want to pause for a minute just capture, the number of orders of magnitude, you said it was six to 10 a year and you did nine zero, 90? >> Yeah, so we have done two years work in six weeks, all in the middle of the night as well. So it's been it's been a hard work, so you can see the screen (mumbles). I'm trying to catch up with a minute. But it's been really, really satisfying, and an incredible outcome for our patients. The legacy of this program, is going to last at Belfast for 40 years. >> Brown I want to say congratulations, I'll give you my CUBE award for not changing the world, but saving the world, one person at a time. 90 interviews in six weeks. That's amazing. That's like clearing the waiting list. You're really changing lives there, congratulations. >> That's great, thank you very much. >> Roger, what a great partner and customer you have here. Talk about this award that you guys have, talk about the company. What is this all about? Why you guys in this position? Why are you winning? >> So I think our motivation for our company, is driven by our partners such as Tim, what they're doing transforms care, and even in these horrific situation are scenarios, we have the moment with COVID think you're hearing the start of an amazing story. Our job is to give surgeons like Tim, the best possible insight that he can have going into his surgeries. For the last 20 years, surgeons have relied largely on 2D imaging, so CT and MRI scans for being able to plan their surgeries, when in fact modern technology, should apply them much greater insight, before they actually perform their surgery. So we've created a technology, that platforms on AWS that allows us, to turn those traditional, hard to understand 2D images, into micromillimeter precise models of the patient's exact anatomy. The value hopefully to amazing colleagues like Tim, is that instead of trying to interpret what a 2D image CT or MRI scan might mean, he can actually see for the first time before, he opens the patient up exactly what he's going, to find when he starts the surgery, So he can really start planning, and complete that planning before, the surgery actually takes place. So hopefully, that allows a number of benefits result, whether that be shorter operations time, less surgical equipment needing to be brought, into the surgery, hopefully faster surgeries means less risk of infection, for patients means shorter time, means better outcomes the healthcare system but most importantly the patient. >> Awesome, Dr. Brown, I want to get your take on this. Can you describe the impact on your side because, you know, the future of work, which is everyone's been talking about, in the tech industry for many years. Now with COVID we were just talking about the successes, you're having and changing lives and saving lives. The notion of work workplace, workforces, work loads, work flows are all changing. Certainly the workplace people aren't as on site as they used to be. The workforce has to be protected. How does the AI and how does the Axial3D help you, in your workflows? Are you getting more done? Can you can you give specifics, around the impact to your job? >> Yeah, it's been a fantastic journey to date. And we're still learning our way. It's a journey. And we're trying to work out exactly where this lies. And the fact that COVID has not come along, which has changed our working practices means that, we have to look for different solutions. And this I think, is a very handy solution, to where it's come into my practice over the last three years has been, in terms of complex renal surgery and oncological surgery, where we have for example, a tumor in a kidney where we think my goodness, we're I have to take this kidney out and throw it in the bin because it's very badly diseased. So the index case that we were involved with, was involving a chap who wanted, to donate his kidney to his daughter. But when we worked him up, we find a tumor in his kidney, which ordinarily would have to be discarded. And but thanks to the imaging that Axial was able, to produce for us, we were able to plan well choose well cut well, and as a result, we took the kidney if we were able to plan, a removal of the tumor from the kidney itself, we were able to repair the kidney and then transplant into his daughter. So with the technology that was available, we were able to save two lives in one particular case. And it's really grown from there. And we've now been involved, in five or six different real complex cases, where the imaging has changed the outcomes for patients, who ordinarily wouldn't have been able to achieve them, as they comes, I think, the AI interface and the AI solution that we've, we've developed in our partnership with Axial. As I said, it's a journey, and we're still finding our way. But the two insights that I've really got are. The first is that what we want to do is reduce variability. And not just in our, in our observers from the way that we interpret imaging. Traditionally, as Roger said, we look at 2D images, we're now able to sit and look at this imaging in a three dimensional space on our desk. Rather than trying to reconstruct these things in our head. We can look at them and discuss the different images, with our colleagues in real time. As well as that, which I think is probably the most important thing, is that we're not able to engage our patients, in a partnership, before we've had a bit of an unfair advantage, that we're able to interpret these images. Because we've been trying to get 30 years of getting used, to doing this as professionals, and but the patients are presented, with some incredibly difficult decisions, to make by their own health. And with very little understanding, but my I can hand them a model of their own disease, they're able to understand. And that gives my patient the autonomy, to make the decisions about their own bodies back again, I think that's a hugely powerful, powerful tool for these guys to have, but potential decisions that they have, to make that will affect them for the rest of their lives. >> So the problem you were solving was one, of the technical problems, so you're trying to figure out manually get more insight, into the imaging and to the customer, or the patient in this case, customer the patient can make a better decision. Those are two problem statements. That seemed to be the big ones. Did I miss anything? >> Absolutely, no, he got one, yeah, absolutely. >> Okay, so Axial3D. You guys have a great solution. How did you get here? Tell us about your story. What's the big trajectory for you guys, in terms of this value proposition just seems to be amazing. And again highlights the advantages, how technology really solves a problem, but the outcome on the patient side is pretty phenomenal. >> So the chance for us is there, or the moment that we have made the leap we have made, is to be able to automatically turn these 2D images into 3D models. So we take each of the slices off of a MRI, or CT scan, using AWS machine learning, we construct 3D, micromillimeter precise representation of an anatomy. That's only possible, first of all, we train the algorithms that we created on the Amazon platform, using over a million pre labeled CT scans. So our system automatically detects a pixel level. What is bone, what is ligament, what is an artery or blood vessel? And with the training that we're able to perform, we've been able to with these million images, we've been able to, in effect train our system, to automatically detect the different parts of them, through this micro precise level, that hasn't been previously possible. And this technology, or the ability to create 3D models has existed for maybe 10, or 15 years. But it's needed experts like Tim to during effect, manually code, the 2D image at a pixel level and codify it so some software to turn that into 3D image, typically to either an RS of an expert like Tim to do, and the problem is Tim could only do one at a time. We estimate there are about three million, of these complex surgeries each year in the world, that need benefit greatly from this Enhanced Imaging. And we couldn't get three million months, he's selected that. So we have this process. Now on AWS platform, we have these models in parallel. And each model will take maybe a few minutes, to turn from the CT into the 3D representation. So through the power of the Amazon public cloud, we've been able to provide this powerful machine learning, automated solution that can actually scale, to the demand that we hope to see in the world. >> Dr. Tim Brown talked about the impact because I mean, Andy Jassy, the CEO of AWS always talks about this, when I interview him, he says, you know, we're here to help do the heavy lifting. This sounds like some pretty heavy lifting. What was just talked about? I mean, the manual work involved, you essentially have collective intelligence and supercomputer power with AWS. What's your take on this as this evolves? Why isn't everyone doing this? >> Yeah, well, I don't know why everyone is doing it. That's the key question it really is. From my perspective, there is no heavy lifting at all. And what I do is I push a couple of buttons, I input a bit of data and I send it off. And from my perspective, it is about as easy as it gets, it's probably as easy as sending an email, which we do hundreds of times a day. And so from my perspective, I'm delighted to say that there's no heavy lifting at all. I get a patient's data, I send the data through to Axial who will then fool me and say, listen, Tim, what is it exactly that you want? There's a great personal service from Axial, and a couple of days later, there's a delivery of a beautiful life size, 3D representation model, which I can then take to plan and treat a patient with. So the heavy lifting really has all been done. As Roger alluded to, in the past, it was hugely time consuming at work, that required a huge amount of training. But now basically, that's been replaced with pushing the button and these supercomputers taken all of my heavy lifting away. And I think this is one of the true representations, of high technology really, really advances, real world solutions. And my patients are the benefactors from this. >> Roger, Dr. Brown lay out the architecture, because first of all, pretend I want to take this every single friend, that I have here in California and around the world. I want to just deploy this what's the architecture and what's needed on the deployment side, say to Belfast as you deploy this, what's kind of involved, can you just take us through high level, I'm actually cloud scale is amazing. No doubt about it. We just talked about that but, what's involved in the architecture side, am I standing up on EC2 is there SageMaker involved me? What's the architecture and then deployment, What does that look like? >> Sure, so can you slide slight step back, one of the challenges when we as the med tech community try and introduce innovation into healthcare into hospitals, the hospitals IT infrastructure network definition, is often pretty locked down. So we're trying to bring new software and load it and install it into the hospital data system is a huge, often lengthy process that has, to jump through lots of hoops, in terms of a key network compliance, lots of different steps along the journey. And that often was for very good reasons, is a significant barrier, to the timely adoption of innovative technologies like ours. What platforming activity on AWS allies, were just another website. As Dr. Tim has said, his own though his only existence, with Axial3D in terms of interface, is dragging and dropping, the CT scan into our website, into our portal exists locally on the AWS instance, in whichever region we are working with, for example, in the US never leaves the US, we use the public cloud version. In US East, we take advantage of many features within AWS. But SageMaker is probably a core of what we do. It's not innovation that AWS introduced, you know, several years ago, that is the lightest to produce this, this machine learning trained set of algorithms, that allow us to give this disruption. >> And it sounds like the more you use it, the more get smarter is that as well. >> Absolutely, so our journey as Tim said, we're in a journey not only in terms of the technology, and you're very perceptive in terms of, yes, the more we train it, the more we train it, on specific anatomy types or pathology types or trauma types, the better our system gets, at recognizing the specific characteristics of those. But more importantly, this is about journey pipe. Having made this disruption we make the change and transformation of new standards of care pathways, Nazi innovation that we just enable. It's amazing surgical teams like Tim's, that make transformation. >> Dr. Brown now on your side you're sitting there I got a big problem trying to solve these problems. I got patients one but one better outcomes, they want to live. I don't want to throw away kidneys. I don't have to you just solve that problem. Now when they bring that over, what was it like over on your side of the house as a practitioner deploying it? You got two jobs going on. You're kind of doing IT integration on one hand and you're a surgeon on the other trying to make things happen. You know, what I see this is not a lot of it here. What's the deployment look like? >> Deployment to me is I don't know why ever as doing it, it's such a straightforward, easy situation. And it's, it's remarkable, really. It's such a good solution. I think, part of any sort of change management program, and this, again, is change management. It's challenging the way we think about things. That's challenging people's comfort zones. And anytime we need to change, we've got this anatomy of change. You've got innovators, we've got early adopters, we've got late adopters. And I think what we're going to see over the next five to 10 years is people recognizing that this technology, is a game changer, possibly being driven by their patients who say, I want a 3D model. And I want to see what this actually looks like. Because basically, that black and white picture you're showing me, doesn't make any sense to me. And I think there's going to be the two drivers is that the first is that we want to have consistency of care and the lack of variation in our care across all services. But as well as that the patience, I think, are going to drive this as well. So once once we get the innovators and the early adopters of this technology on board, then we'll see a tipping point. And that's, that's when it becomes an acceptable and normal thing for people, to do when they come into hospital. There'll be shown printout of their 3D printed model of their of their pathology, and that will be used to inform their decision making, for the treatment processes. And that's a true collaboration between doctor or surgeon and the patient. And that's, that's where we need to be in 21st century it's got to be a collaborative decision making process. And you talked about patient journeys, and, this is a really integral part. This is the roadmap of your journey to a large extent. So I think this I can see this, that's being rolled out worldwide, being driven by patients by correction and variability of health care provision. >> Its a great example, of an innovative award winner for the most innovative use of artificial intelligence and machine learning 3D images saving lives. Congratulations, Tim, Roger, it's phenomenal. Final question as we end this out. What's the scar tissue, pun intended? Well, what did you learn? What are some of the things that you could share with folks, as people look at this and say, this is an example of cloud scale and technology for good? What lessons have you learned? What can you share for folks, take a minute to explain each. But Roger, we'll start with you. >> Yeah, sure. So I think a number of lessons for us on this journey. As Tim says, this is a we're at the start of a journey, of understanding the power of what 3D imaging can bring to providing a consistent or less variable care, but also, as Tim also alluded to, in terms of the patient understanding, I think that patient understanding, is one of the huge leap forwards, that we didn't set out initially thinking, we're going to be able to help educate and better inform patients. But that was one of the derive benefits suddenly became apparent. So that was a great lesson. I think that incredible levels of adoption, that we're starting to see across the US across Europe. Because it's so easy to adopt, compared to traditional IT methods. Surgeons just register for a website, and they can start transacting and getting service from us, as opposed to having to have these huge IT programs. So I think we're now starting to really scratch the surface and start seeing the benefits of this isn't an administrative system. It's not the HR system. It's not a finance system, or maybe healthcare was comfortable in using public cloud. This is core hardcore clinical service, clinical diagnosis, clinical education, and the Amazon cloud is enabling that, just wouldn't be possible with this technology, (mumbles) the lessons we're learning are just (mumbles). >> Dr. Tim Brown and take us home and the segment, with your take, lessons learned and advice to others. >> I think the lesson learned are that doctors and healthcare providers are all extremely wary of change of new innovations. Because they feel that already, they're overburdened, and probably my colleagues in the States and across Europe feel like, we're a bit overburdened by all the things that we have to do. And this may potentially have been a more difficult or odds to your workload and actually fact, this makes your workload a lot easier and convincing people and getting people to understand that, this really does make your life a lot easier. It actually removes all the scar tissue it removes the difficulties that have been put in place by organizations. And once people realize that, that's what there is no heavy lifting. And this will make a huge difference to your practice and your patients understanding of your practice. And once that, once up, people really realize that, then the tipping point will be achieved. I'm looking forward to that date because this is going to be the new normal in the next five to 10 years. >> While the performance that you're putting up the numbers of 90 transplants successfully over six weeks, dwarfs the full year last year, really kind of shows the outcome is a game changer. And again, congratulations on your success. Roger, thank thank you for coming on. Congratulations on being the award winner, a diverse partner for the most innovative AI and machine learning solutions. Thanks for taking the time for part of this AWS partner awards program. Thank you. >> Thank you. >> Thank you. >> Okay, I'm John Furrier, we're covering the AWS public sector partner awards, program put on by the CUBE and AWS public sector partners. Thanks for watching. (bright upbeat music)

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. Welcome to the >>Special Cube program. We are here with the Amazon Web Services Public Sector Partner Awards program. It's a celebration of AWS public sectors partners and their end user customers where there's been innovation and we're pleased to have on this show here, the award winner for the most innovative AI and ML Artificial intelligence and machine learning solution. Axial three D is the partner, and the end user is Belfast Hospital. He got Roger Johnson, the CEO of actual three D, and Dr Tim Brown consulted transplant surgeon at Belfast Hospital, who has been doing amazing things not only on the as an innovative partner, but really during Covic making things happen by solving the problem of the surgical gap in the number of surgeries that you're doing really high performance saving lives. Congratulations. First of all, congratulations. Roger. Dr Kimberly. Thanks for joining me. >>Re pleasure. >>Okay, let's get into it. First of all, Dr Tim Brown, I really want to commend you on the amazing work that you're doing before we get into some of the partnership awards conversations. You have been at the front lines solving a lot of problems around the gap between the number of surgeries that could take place with Cove. It, um, tell that story real quick. I really think it's super important. Take a minute to >>explain. Yeah, thanks for the opportunity. And it's been an incredible rollercoaster for the last three months, pretty much all of the transplant programs across the world who have been affected by Coupet of shut down but with some pretty innovative on the grill leadership team Working advances with managed to open a program up again. And and Belfast, we have a bytes and 50 to 50 disease donor transplants year over the last three months, with just a 90 90 kidney transplants. Pretty much we've cleared the whole waiting list in Northern Ireland, pretty much for people waiting for a kidney transplant at this time. And it's been a remarkable few weeks, but it really is a testament to the critical care community. People that work in intensive care is the high marks, a support organ donation. Of course, our donors who have given so selflessly at such a tragic time for them. So I'd like to pay tribute to all of our donors into the amazing people who have been involved in the team. Mark belt faster this time. >>That's super amazing. Can you just I just want to pause from and just captured the number of order of magnitude. You said it was 6 to 10 year and you didn't 90 90. >>Yeah, so six weeks basically Teoh, two years work in six weeks old in the middle of the night as well. So it's been It's been hard of hard work, so you can see the sleeplessness. I'm trying to catch up with a minute, but it's been really, really satisfying. An incredible I come for patients and legacy of this of this, the program is gonna last about faster. 40 years. >>Well, I want to say congratulations. I'll give you my Cube Award for not changing the world but saving the world. One person at a time. 90 interviews and six weeks. That's amazing. That's like thinking clearing the waiting list. You really changing lives there. Congratulations. >>That's very kind of you. Thank you very much. >>Roger. Good. A great partner and customer. You have here. Talk about this award. You guys have talked about the company? What is this all about? Why you guys in this position? Why are you winning? >>Yes, So I think our motivation for our company is driven by our partners, such such as? In what they're doing transforms care And even in these horrific situation, our scenarios. We have the moment with Kobe. Think you're hearing the start of the amazing story our job is to give Surgeons liked him the best possible insight that he can have going into his surgeries For the last 20 years, surgeons of relied largely on two D imaging, so C, t and memory scans or for being able to plan their surgeries when it's murdered, technology should apply them much greater insight or they actually perform the surgery. So we've created a technology that platforms on AWS that allows us to turn those traditional hard to understand to the images into micro millimeter precise models off the patients exact anatomy. The value hopefully, two amazing colleagues like Tim is that instead of trying to interpret what a two D image CD or memory scan might mean he can actually see for the first time before he opens the patient up exactly what he's going to find when when he when he starts the surgery. So he immediately start to complete that planning before the surgery actually takes. So hopefully that analyze a number of benefits to results without the shorter operations. Find less surgical meeting we brought into the surgery. Hopefully, faster Surgeries names last risk of infection For patients being shorter Time means most >>awesome. Dr. Brian, I want to get your take on this. Can you describe the impact on your side because you know the future of work, which is everyone's been talking about in the tech industry for many years now, with code we were just talking about. The success is you're having and changing lives and saving lives. The notion of work workplace work, forces, work loads, work flows are all changing. Certainly the workplace people aren't as on site as they used to be. The workforce has to be protected. How does the AI and how does the actual three D help you and your work flows? Are you getting more done? Can you give specifics around the impact to your job? >>Yeah, it's a bit It's been a fantastic journey to date. We're still learning away. It's a journey. We're trying to work out exactly where this lies in. The fact that Kubla does not come along, which has changed, or working practices, that means that we have to look for different solutions on this, I think, is very 100 solution to amend. My practice over the last three years has been in terms of complex and real surgery on oncological surgery, where we have, for example, a tumor and kidney where we think, my goodness, we're gonna have to take this kidney I and throw it in the bin because it's very badly disease. So the index case that we were involved with that was building a child who wanted to donate his kidney to his daughter. But when we worked him up, we find a tumor in his kidney, which ordinarily would have to be discarded. But thanks to the imaging that Excel was able to produce for us, we were able to plan Well, geez, well cut well and as a result of kidney, I really plan a removal of the tumor from the kidney itself. We really repair kidney and then transplant it into his daughter. So with the technology that was available, we were able to save two lives on one particular case on, and it's really grown from there on. We've been involved in five or six different, really complex cases where the imaging has changed the outcomes for our patients who ordinarily wouldn't have been able to. Chief insight comes, I think, the AI interface on the AI solution we've developed in our partnership with the Excel. As I said, it's a journey and we're still finding our way. But to insights that I've really got our the first is that what we want to do is reduce variability, not just in our in our observers, from the way that we interpret imaging tradition is what you're saying is, look a two D images. We're now able to sit and look at this, emerging in a three dimensional space on our desk. Rather than trying to reconstruct these things in your head, we can look at them and discuss the different images with our colleagues in real time, a zealous that which I think is probably the most important thing, is that we're not able to engage our patients and a partnership. Before we had a bit of an unfair advantage that we're able to interpret these images because 20 or 30 years of getting used to doing this as professionals. But the patients are presented with some incredibly difficult decisions to make by their own health and with very little understanding that. But now I can handle the model of their own disease very easy to understand, and that gives my patient autonomy to make the decisions about their own bodies back again. And I think that's a hugely powerful, powerful tool for these guys have about potential decisions that they have to make that more effective for the rest of their lives. >>So the problem you're solving was one of the technical problem. So you're trying to figure out manually, get more insight into the the imaging and to the customer or the patient. This case customer, the patient. I can make a better decision. Those are two problems, statements that seem to be the big ones that I missed. Anything? >>Absolutely, absolutely. >>Okay, so actual three d you guys have a great solution? How >>did you >>get here? Tell us about your story. What's what's What's the big trajectory for you guys? In terms of the value proposition, it seems to be amazing and again highlights. The advantages of technology really solves the problem. But the outcome on the patient side is pretty phenomenal. >>Yes, so the chance for us is there or the development that we have made. The lately, we admit, is to be able to automatically turn these two D images into three D models. So we take each of the slices off of memory or cities. Using AWS is machine learning. We construct three D macro millimeter precise representation of For me. That's only possible. First of all, we treat the algorithms that we created on Amazon platform using over a 1,000,000 pre labeled CDs. Consume our system automatically detect. Yeah, it's a level. What is bone? What is ligament? What is on our earlier vessel? With the training that we're able to perform, we've been able to with with these 1,000,000 images we've been able to in effect, tree and our system automatically detect the parts of me with this micro service level that hasn't been previously possible. This technology, or the ability to create three D models, has existed for maybe 10 or 15 years, but it's it's needed. Experts like him who were, in effect manually code the two D image pixel level and could affect so some software and turn it into a three D image. Typically, too, it's in ours, often expert like them to do. And the problem is, Tim could only do one of the time. We estimate there about three million of these complex surgeries each year in the world that need open effort from greatly from this enhanced imaging. And we couldn't get 33 million under these, especially. And that. So we have this process no on the AWS platform, with dozens of these models in parallel, and each more will take maybe a few minutes to turn from the CD into the into the three D representation. So through the park off the Amazon Public cloud, we've been able to provide this this powerful machine learning automated solution that can actually scale toe man >>Dr Brian talk about the impact because, I mean Andy Jassy, the CEO of AWS, always talks about this. When I interviewed him, he says, you know, we're here to help do the heavy lifting this sounds like some pretty heavy lifting. What was just talked about? I mean, the manual work involved. You essentially have a collective intelligence and supercomputer power with AWS. What's your take on this as this evolves? Why isn't everyone doing this? >>Yeah, well, I don't know why. Every minute. That's that's That's the key question. It really is. From my perspective, there is no heavy lifting at all, and what I do is I push a couple buttons. I put a bit of data, and I send it off. From my perspective, it is about as easy as it gets is probably a ZTE sending email, which we do hundreds of times a day. And so, from from my perspective, I'm delighted to say there's no heavy lifting until I get a patient's data. I send data through to excel, who will then fool me and say, Listen to what is it exactly that we want to have a personal service from actual on? A couple days later, there's a delivery of a beautiful life size three D representation model, will check and then take to plan on and treat a patient with. So the heavy lifting really has all been done. A Z Roger alluded to in the past. It was hugely time consuming work that required a huge amount of training. But basically that's being replaced with a push of a button on. These supercomputers have taken all of my heavy lifting away on, and I think this is one of the true representation. Zoff technology really, really advances real world solutions and my patients are benefactors. From this >>Roger Dr Brown. Lay out the architecture because, first of all, pretend I want to take this every single friend that I have here in California and around the world. I want to just deploy this. What's the architecture and what's needed on the deployment side? Say it to Belfast as you deploy this. What's kind of involved in you? Just take us through high level. I must be cloud scales. Amazing, No doubt about it. We just talked about that. But what's involved in the architecture side of my standing? A bunch PC two's Is there sage maker involvement? What's the architecture and then deployment? What does that look like? >>Sure, So again, a slight step back. One of the challenges when, when we is the MedTech community try and introduce innovation into health and hospitals that the hospitals i t. Infrastructure network definition is often very locked on. So we're trying to bring new software and load it and install it in the hospital data system. That is a huge, often lengthy process that has to be done through lots of hoops in terms off Hey, network a compliance. Lots of different steps along the journey and that often wants from a good reasons, is a significant barrier to the timely adoption off innovative technologies in the cars. What a what a platform a selfie on AWS allies were just another website, as Tennis said, is, uh, only that, though his only existence with actual three D in terms of the interface is dragging and dropping the CT scan into our website into a portal portal exists quickly on the AWS instance. In one of our region, we are working with a little in the US. Never leave the US We use the the public client version in US East. We take advantage of many features within AWS, but a sage maker is probably a core of what we do. It's not innovation that AWS introduced know several years ago that was like juice this this machine learning trained set of algorithms that allow us to give this disruption. >>And it sounds like the more you use it, the more get smarter. Or is that as well? >>Absolutely. So our journey is, As Tim said, we're on a journey not only in terms off the technology and you're very receptive. In terms of yes, the more we train it, the more we treated on specific anatomy types or pathology types or trouble types, the better our system gets recognizing the specific characteristics of those. More importantly, this is about a journey I having made this disruption, we make the change and transformation off new standards of care pathways. That's the innovation that we just enable. It's amazing. Surgical teams like hymns. Let me transformation >>Dr Brown on your side. You're sitting there. I got a big problem trying to solve these problems. I got patients one but one better outcomes. They want to live. I don't want to throw away kitty, so I don't have to you to solve that problem that when when they bring that over, what was it like over on your side of the house is a practitioner. Deploying it. You've got you've got two jobs going. You're kind of doing I t integration on one hand and you're a surgeon on the other, trying to make things happen. You know what I see? This is not a lot of I t here. What's the deployment? Looks like. >>Yeah, deployment means I don't know. Why ever announces doing that. Such a straightforward, easy situation. It's that's remarkable. Ready? It's such a good solution, and I think part of any sort of change management program, and this again is change management. It's challenging the way we think about things. It's challenging people's comfort zones on any time we need to do change. We've got this anatomy of change. You've got innovators go early, adopters will lead the doctors, and I think what we're going to see over the next 5 to 10 years is people are recognizing that this technology is a game changer, possibly being driven by their patients who say I'm on the three D model and I want to see what this actually looks like because basically not black and white picture you're showing me doesn't make any sense to me and I think there's going to be the two drivers is that the first is that we want to have a consistency of care on the lack of variation in our care across across old old services. But as well is that patients? I think we're gonna drive this as well. So once once we get the innovators and the early adopters of this technology on board, then we'll see a tipping point. And that's that's when it becomes an acceptable normal thing for people to do. When they come in the hospital, they'll be sure print tight off their three d printed like moral off their pathology. I'm not a huge demand for their decision making for treatment processes, and that's a true collaboration between doctor or surgeon on the patient. That's that's where we need to be in the 21st century. It's it's going to be a collaborative decision making process. You talked about the pressures, journeys and this This is a really integral part. This is the roadmap of your journey to a large extent. So I think this I can see this being rolled out worldwide, being driven by patients buying a correction and variability of healthcare provision. >>That's a great example is an innovative award winner for the most innovative use of artificial intelligence and machine learning. Three D images saving lives Congratulations, Tim Rogers. Phenomenal Final question As we end this out, what's the scar tissue pun intended? You know, What did you learn? What was some of the things that you could share with folks as people look at this and say This is an example of cloud scale and the technology for good. What lessons have you learned? What can you share for folks? Take a minute to explain the split. Roger. We'll start with you. >>Yeah, sure. So I think a number off lessons for us on this journey Assistances, This is Ah, we're at the start of a journey of understanding the power off the what three d imaging can bring just to providing a consistent use variable care, but also as a stem also alluded to in terms of off the patient understanding, I think that patient understanding is one of the huge leap forwards that way. Didn't set out initially thinking we're going to be able to help educate on better inform patients. But that was one of the derive benefits suddenly part. So that was a great lesson. I think there is incredible levels of adoption that we're starting to see across the US across Europe because it's so easy to adopt. Compared to traditional methods, surgeons registered for Canadian start transacting and instead of us almost as opposed to having to have these huge I t programs. So I think we're now starting to really scratch the surface and start seeing the benefits of this isn't an administrative system. It's not me. HR system. It's not a finance system. Or maybe a healthcare was comfortable. And using public like this is core hard core clinical services, clinical diagnosis. Clinical education on the Amazon cloud is enabling that it just wouldn't be possible with this technology we started. Actually, the lessons were learning or just just >>Dr Tim Brown and take us home and the segment with your take lessons learned and advice to others. >>I think the lessons learned are the doctors and health care providers are all extremely wary off change of new innovations because they feel that already they're overburdened. Probably my colleagues in the states and across Europe perfectly like they were a bit over, burdened by all the things that we have to do, and this may potentially have been more difficult or wants to your workloads. And actually, let's make your workload along each year convincing people and getting people to understand that this really does make your life a lot easier. It actually removes all the scar tissue, removes the difficulties that have been put in place by by organizations on once. People realize that, that's what that there is no heavy lifting. And this will make a huge difference to your practices, your patients understanding of your practice, and we'll stop so people really realize that the tipping point will be achieved. I'm looking forward to that day because this this is going to be the new normal in the next 5 to 10 years. >>While the performance that you're putting up the numbers of 90 transplant successfully over six weeks dwarfs the full year, last year really kind of shows the outcome is a game changer. And again, congratulations on your success. Roger think Thank you for coming on Corrections on being the award winner. Eight of his partner for the most innovative AI and machine learning solutions. Thanks for taking the time for this 80 s partner awards program. Thank you. >>Thank you. >>Okay, I'm John Furrier. We're covering the AWS Public Sector Partner Awards program put on by the Cube and AWS Public Sector Partners. Thanks for watching. Yeah, Yeah, yeah, yeah, yeah.

>> Instructor: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Over welcome to the special CUBE program. We are here with the Amazon Web Services public sector, partner awards program. It's a celebration of AWS, public sectors, partners and their end user customers, where there's been innovation. And we're pleased to have on the show here, the award winner for the most innovative AI, and ML artificial intelligence and machine learning solution. Axial3D is the newest partner and the end user is Belfast hospital. We got Roger Johnson, the CEO of Axial3D, and Dr. Tim Brown consulted transplant surgeon, at Belfast hospital, who has been doing amazing things, not only on the as an innovative partner, but really during COVID, making things happen, by solving the problem of the surgical gap and the number of surgeries that you're doing. Really high performance saving lives, congratulations. First of all, congratulations Roger and Dr.Tim Brown, thanks for joining me. >> We're pleasure. >> Okay, let's get into it. First of all, Dr. Tim Brown, I really want to commend you on the amazing work, that you're doing. Before we get, into some of the partnership awards conversations. You have been at the front lines solving a lot of problems around the gap, between the number of surgeries, that could take place with COVID. Tell that story real quick. I really think it's super important. Take a minute to explain. >> Yeah, thanks for the opportunity. And it's been an incredible roller coaster, for the last three months. And pretty much all of the transplant programs, across the world who have been affected, by COVID have shut down. But with some pretty innovative and real leadership and team working advances, we've managed to open a program up again and in Belfast, we have about 50 deceased donor transplants a year. Over the last three months, we've just done 90 kidney transplants and pretty much with with care, the whole wedding list in Northern Ireland pretty much, for people waiting for kidney transplant in this time. And it's been a remarkable few weeks. But really is a testament to the critical care community, the people that work in intensive care, as to how much they support organ donation. And of course, our donors who have given so selflessly, at such a tragic time for them. So I'd like to pay tribute to all of our donors, and to the amazing amount of people, who have been involved in the team mark and Belfast at this time. >> That's super amazing. Can you just I just want to pause for a minute just capture, the number of orders of magnitude, you said it was six to 10 a year and you did nine zero, 90? >> Yeah, so we have done two years work in six weeks, all in the middle of the night as well. So it's been it's been a hard work, so you can see the screen (mumbles). I'm trying to catch up with a minute. But it's been really, really satisfying, and an incredible outcome for our patients. The legacy of this program, is going to last at Belfast for 40 years. >> Brown I want to say congratulations, I'll give you my CUBE award for not changing the world, but saving the world, one person at a time. 90 interviews in six weeks. That's amazing. That's like clearing the waiting list. You're really changing lives there, congratulations. >> That's great, thank you very much. >> Roger, what a great partner and customer you have here. Talk about this award that you guys have, talk about the company. What is this all about? Why you guys in this position? Why are you winning? >> So I think our motivation for our company, is driven by our partners such as Tim, what they're doing transforms care, and even in these horrific situation are scenarios, we have the moment with COVID think you're hearing the start of an amazing story. Our job is to give surgeons like Tim, the best possible insight that he can have going into his surgeries. For the last 20 years, surgeons have relied largely on 2D imaging, so CT and MRI scans for being able to plan their surgeries, when in fact modern technology, should apply them much greater insight, before they actually perform their surgery. So we've created a technology, that platforms on AWS that allows us, to turn those traditional, hard to understand 2D images, into micromillimeter precise models of the patient's exact anatomy. The value hopefully to amazing colleagues like Tim, is that instead of trying to interpret what a 2D image CT or MRI scan might mean, he can actually see for the first time before, he opens the patient up exactly what he's going, to find when he starts the surgery, So he can really start planning, and complete that planning before, the surgery actually takes place. So hopefully, that allows a number of benefits result, whether that be shorter operations time, less surgical equipment meeting we brought, into the surgery, hopefully faster. surgeries means less risk of infection, for patients means shorter time, means the healthcare system (mumbles). >> Awesome, Dr. Brown, I want to get your take on this. Can you describe the impact on your side because, you know, the future of work, which is everyone's been talking about, in the tech industry for many years. Now with COVID we were just talking about the successes, you're having and changing lives and saving lives. The notion of work workplace, workforces, work loads, work flows are all changing. Certainly the workplace people aren't as on site as they used to be. The workforce has to be protected. How does the AI and how does the Axial3D help you, in your workflows? Are you getting more done? Can you can you give specifics, around the impact to your job? >> Yeah, it's been a fantastic journey to date. And we're still learning our way. It's a journey. And we're trying to work out exactly where this lies. And the fact that COVID has not come along, which has changed our working practices means that, we have to look for different solutions. And this I think, is a very handy solution, to where it's come into my practice over the last three years has been, in terms of complex renal surgery and oncological surgery, where we have for example, a tumor in a kidney where we think my goodness, we're I have to take this kidney out and throw it in the bin because it's very badly diseased. So the index case that we were involved with, was involving a chap who wanted, to donate his kidney to his daughter. But when we worked him up, we find a tumor in his kidney, which ordinarily would have to be discarded. And but thanks to the imaging that Axial was able, to produce for us, we were able to plan well choose well cut well, and as a result, we took the kidney if we were able to plan, a removal of the tumor from the kidney itself, we were able to repair the kidney and then transplant into his daughter. So with the technology that was available, we were able to save two lives in one particular case. And it's really grown from there. And we've now been involved, in five or six different real complex cases, where the imaging has changed the outcomes for patients, who ordinarily wouldn't have been able to achieve them, as they comes, I think, the AI interface and the AI solution that we've, we've developed in our partnership with Axial. As I said, it's a journey, and we're still finding our way. But the two insights that I've really got are. The first is that what we want to do is reduce variability. And not just in our, in our observers from the way that we interpret imaging. Traditionally, as Roger said, we look at 2D images, we're now able to sit and look at this imaging in a three dimensional space on our desk. Rather than trying to reconstruct these things in our head. We can look at them and discuss the different images, with our colleagues in real time. As well as that, which I think is probably the most important thing, is that we're not able to engage our patients, in a partnership, before we've had a bit of an unfair advantage, that we're able to interpret these images. Because we've been trying to get 30 years of getting used, to doing this as professionals, and but the patients are presented, with some incredibly difficult decisions, to make by their own health. And with very little understanding, but my I can hand them a model of their own disease, they're able to understand. And that gives my patient the autonomy, to make the decisions about their own bodies back again, I think that's a hugely powerful, powerful tool for these guys to have, but potential decisions that they have, to make that will affect them for the rest of their lives. >> So the problem you were solving was one, of the technical problems, so you're trying to figure out manually get more insight, into the imaging and to the customer, or the patient in this case, customer the patient can make a better decision. Those are two problem statements. That seemed to be the big ones. Did I miss anything? >> Absolutely, no, he got one, yeah, absolutely. >> Okay, so Axial3D. You guys have a great solution. How did you get here? Tell us about your story. What's the big trajectory for you guys, in terms of this value proposition just seems to be amazing. And again highlights the advantages, how technology really solves a problem, but the outcome on the patient side is pretty phenomenal. >> So the chance for us is there, or the moment that we have made the leap we have made, is to be able to automatically turn these 2D images into 3D models. So we take each of the slices off of a MRI, or CT scan, using AWS machine learning, we construct 3D, micromillimeter precise representation of an anatomy. That's only possible, first of all, we train the algorithms that we created on the Amazon platform, using over a million pre labeled CT scans. So our system automatically detects a pixel level. What is bone, what is ligament, what is an artery or blood vessel? And with the training that we're able to perform, we've been able to with these million images, we've been able to, in effect train our system, to automatically detect the different parts of them, through this micro precise level, that hasn't been previously possible. And this technology, or the ability to create 3D models has existed for maybe 10, or 15 years. But it's needed experts like Tim to during effect, manually code, the 2D image at a pixel level and codify it so some software to turn that into 3D image, typically to either an RS of an expert like Tim to do, and the problem is Tim could only do one at a time. We estimate there are about three million, of these complex surgeries each year in the world, that need benefit greatly from this Enhanced Imaging. And we couldn't get three million months, he's selected that. So we have this process. Now on AWS platform, we have these models in parallel. And each model will take maybe a few minutes, to turn from the CT into the 3D representation. So through the power of the Amazon public cloud, we've been able to provide this powerful machine learning, automated solution that can actually scale, to the demand that we hope to see in the world. >> Dr. Tim Brown talked about the impact because I mean, Andy Jassy, the CEO of AWS always talks about this, when I interview him, he says, you know, we're here to help do the heavy lifting. This sounds like some pretty heavy lifting. What was just talked about? I mean, the manual work involved, you essentially have collective intelligence and supercomputer power with AWS. What's your take on this as this evolves? Why isn't everyone doing this? >> Yeah, well, I don't know why everyone is doing it. That's the key question it really is. From my perspective, there is no heavy lifting at all. And what I do is I push a couple of buttons, I input a bit of data and I send it off. And from my perspective, it is about as easy as it gets, it's probably as easy as sending an email, which we do hundreds of times a day. And so from my perspective, I'm delighted to say that there's no heavy lifting at all. I get a patient's data, I send the data through to Axial who will then fool me and say, listen, Tim, what is it exactly that you want? There's a great personal service from Axial, and a couple of days later, there's a delivery of a beautiful life size, 3D representation model, which I can then take to plan and treat a patient with. So the heavy lifting really has all been done. As Roger alluded to, in the past, it was hugely time consuming at work, that required a huge amount of training. But now basically, that's been replaced with pushing the button and these supercomputers taken all of my heavy lifting away. And I think this is one of the true representations, of high technology really, really advances, real world solutions. And my patients are the benefactors from this. >> Roger, Dr. Brown lay out the architecture, because first of all, pretend I want to take this every single friend, that I have here in California and around the world. I want to just deploy this what's the architecture and what's needed on the deployment side, say to Belfast as you deploy this, what's kind of involved, can you just take us through high level, I'm actually cloud scale is amazing. No doubt about it. We just talked about that but, what's involved in the architecture side, am I standing up on EC2 is there SageMaker involved me? What's the architecture and then deployment, What does that look like? >> Sure, so can you slide slight step back, one of the challenges when we as the med tech community try and introduce innovation into healthcare into hospitals, the hospitals IT infrastructure network definition, is often pretty locked down. So we're trying to bring new software and load it and install it into the hospital data system is a huge, often lengthy process that has, to jump through lots of hoops, in terms of a key network compliance, lots of different steps along the journey. And that often was for very good reasons, is a significant barrier, to the timely adoption of innovative technologies like ours. What platforming activity on AWS allies, were just another website. As Dr. Tim has said, his own though his only existence, with Axial3D in terms of interface, is dragging and dropping, the CT scan into our website, into our portal exists locally on the AWS instance, in whichever region we are working with, for example, in the US never leaves the US, we use the public cloud version. In US East, we take advantage of many features within AWS. But SageMaker is probably a core of what we do. It's not innovation that AWS introduced, you know, several years ago, that is the lightest to produce this, this machine learning trained set of algorithms, that allow us to give this disruption. >> And it sounds like the more you use it, the more get smarter is that as well. >> Absolutely, so our journey as Tim said, we're in a journey not only in terms of the technology, and you're very perceptive in terms of, yes, the more we train it, the more we train it, on specific anatomy types or pathology types or trauma types, the better our system gets, at recognizing the specific characteristics of those. But more importantly, this is about journey pipe. Having made this disruption we make the change and transformation of new standards of care pathways, Nazi innovation that we just enable. It's amazing surgical teams like Tim's, that make transformation. >> Dr. Brown now on your side you're sitting there I got a big problem trying to solve these problems. I got patients one but one better outcomes, they want to live. I don't want to throw away kidneys. I don't have to you just solve that problem. Now when they bring that over, what was it like over on your side of the house as a practitioner deploying it? You got two jobs going on. You're kind of doing IT integration on one hand and you're a surgeon on the other trying to make things happen. You know, what I see this is not a lot of it here. What's the deployment look like? >> Deployment to me is I don't know why ever as doing it, it's such a straightforward, easy situation. And it's, it's remarkable, really. It's such a good solution. I think, part of any sort of change management program, and this, again, is change management. It's challenging the way we think about things. That's challenging people's comfort zones. And anytime we need to change, we've got this anatomy of change. You've got innovators, we've got early adopters, we've got late adopters. And I think what we're going to see over the next five to 10 years is people recognizing that this technology, is a game changer, possibly being driven by their patients who say, I want a 3D model. And I want to see what this actually looks like. Because basically, that black and white picture you're showing me, doesn't make any sense to me. And I think there's going to be the two drivers is that the first is that we want to have consistency of care and the lack of variation in our care across all services. But as well as that the patience, I think, are going to drive this as well. So once once we get the innovators and the early adopters of this technology on board, then we'll see a tipping point. And that's, that's when it becomes an acceptable and normal thing for people, to do when they come into hospital. There'll be shown printout of their 3D printed model of their of their pathology, and that will be used to inform their decision making, for the treatment processes. And that's a true collaboration between doctor or surgeon and the patient. And that's, that's where we need to be in 21st century it's got to be a collaborative decision making process. And you talked about patient journeys, and, this is a really integral part. This is the roadmap of your journey to a large extent. So I think this I can see this, that's being rolled out worldwide, being driven by patients by correction and variability of health care provision. >> Its a great example, of an innovative award winner for the most innovative use of artificial intelligence and machine learning 3D images saving lives. Congratulations, Tim, Roger, it's phenomenal. Final question as we end this out. What's the scar tissue, pun intended? Well, what did you learn? What are some of the things that you could share with folks, as people look at this and say, this is an example of cloud scale and technology for good? What lessons have you learned? What can you share for folks, take a minute to explain each. But Roger, we'll start with you. >> Yeah, sure. So I think a number of lessons for us on this journey. As Tim says, this is a we're at the start of a journey, of understanding the power of what 3D imaging can bring to providing a consistent or less variable care, but also, as Tim also alluded to, in terms of the patient understanding, I think that patient understanding, is one of the huge leap forwards, that we didn't set out initially thinking, we're going to be able to help educate and better inform patients. But that was one of the derive benefits suddenly became apparent. So that was a great lesson. I think that incredible levels of adoption, that we're starting to see across the US across Europe. Because it's so easy to adopt, compared to traditional IT methods. Surgeons just register for a website, and they can start transacting and getting service from us, as opposed to having to have these huge IT programs. So I think we're now starting to really scratch the surface and start seeing the benefits of this isn't an administrative system. It's not the HR system. It's not a finance system, or maybe healthcare was comfortable in using public cloud. This is core hardcore clinical service, clinical diagnosis, clinical education, and the Amazon cloud is enabling that, just wouldn't be possible with this technology, (mumbles) the lessons we're learning are just (mumbles). >> Dr. Tim Brown and take us home and the segment, with your take, lessons learned and advice to others. >> I think the lesson learned are that doctors and healthcare providers are all extremely wary of change of new innovations. Because they feel that already, they're overburdened, and probably my colleagues in the States and across Europe feel like, we're a bit overburdened by all the things that we have to do. And this may potentially have been a more difficult or odds to your workload and actually fact, this makes your workload a lot easier and convincing people and getting people to understand that, this really does make your life a lot easier. It actually removes all the scar tissue it removes the difficulties that have been put in place by organizations. And once people realize that, that's what there is no heavy lifting. And this will make a huge difference to your practice and your patients understanding of your practice. And once that, once up, people really realize that, then the tipping point will be achieved. I'm looking forward to that date because this is going to be the new normal in the next five to 10 years. >> While the performance that you're putting up the numbers of 90 transplants successfully over six weeks, dwarfs the full year last year, really kind of shows the outcome is a game changer. And again, congratulations on your success. Roger, thank thank you for coming on. Congratulations on being the award winner, a diverse partner for the most innovative AI and machine learning solutions. Thanks for taking the time for part of this AWS partner awards program. Thank you. >> Thank you. >> Thank you. >> Okay, I'm John Furrier, we're covering the AWS public sector partner awards, program put on by the CUBE and AWS public sector partners. Thanks for watching. (bright upbeat music)

>> David: It's the cube covering the virtual Vertica Big Data conference 2020 brought to you by Vertica. Hello, buddy, welcome to this special digital presentation of the cube. We're tracking the Vertica virtual Big Data conferences, the cubes. I think fifth year doing the BDC. We've been to every big data conference that they've held and really excited to be helping with the digital component here in these interesting times. Ron Cormier is here, Principal database engineer at the Trade Desk. Ron, great to see you. Thanks for coming on. >> Hi, David, my pleasure, good to see you as well. >> So we're talking a little bit about your background you got, you're basically a Vertica and database guru, but tell us about your role at Trade Desk and then I want to get into a little bit about what Trade Desk does. >> Sure, so I'm a principal database engineer at the Trade Desk. The Trade Desk was one of my customers when I was working with Hp, at HP, as a member of the Vertica team, and I joined the Trade Desk in early 2016. And since then, I've been working on building out their Vertica capabilities and expanding the data warehouse footprint and as ever growing database technology, data volume environment. >> And the Trade Desk is an ad tech firm and you are specializing in real time ad serving and pricing. And I guess real time you know, people talk about real time a lot we define real time as before you lose the customer. Maybe you can talk a little bit about you know, the Trade Desk in the business and maybe how you define real time. >> Totally, so to give everybody kind of a frame of reference. Anytime you pull up your phone or your laptop and you go to a website or you use some app and you see an ad what's happening behind the scenes is an auction is taking place. And people are bidding on the privilege to show you an ad. And across the open Internet, this happens seven to 13 million times per second. And so the ads, the whole auction dynamic and the display of the ad needs to happen really fast. So that's about as real time as it gets outside of high frequency trading, as far as I'm aware. So we put the Trade Desk participates in those auctions, we bid on behalf of our customers, which are ad agencies, and the agencies represent brands so the agencies are the madman companies of the world and they have brands that under their guidance, and so they give us budget to spend, to place the ads and to display them and once the ads get displayed, so we bid on the hundreds of thousands of auctions per second. Once we make those bids, anytime we do make a bid some data flows into our data platform, which is powered by Vertica. And, so we're getting hundreds of thousands of events per second. We have other events that flow into Vertica as well. And we clean them up, we aggregate them, and then we run reports on the data. And we run about 40,000 reports per day on behalf of our customers. The reports aren't as real time as I was talking about earlier, they're more batch oriented. Our customers like to see big chunks of time, like a whole day or a whole week or a whole month on a single report. So we wait for that time period to complete and then we run the reports on the results. >> So you you have one of the largest commercial infrastructures, in the Big Data sphere. Paint a picture for us. I understand you got a couple of like 320 node clusters we're talking about petabytes of data. But describe what your environment looks like. >> Sure, so like I said, we've been very good customers for a while. And we started out with with a bunch of enterprise clusters. So the Enterprise Mode is the traditional Vertica deployment where the compute and the storage is tightly coupled all raid arrays on the servers. And we had four of those and we're doing okay, but our volumes are ever increasing, we wanted to store more data. And we wanted to run more reports in a shorter period of time, was to keep pushing. And so we had these four clusters and then we started talking with Vertica about Eon mode, and that's Vertica separation of compute and storage where you get the compute and the storage can be scaled independently, we can add storage without adding compute or vice versa or we can add both, like. So that was something that we were very interested in for a couple reasons. One, our enterprise clusters, we're running out of disk, like when adding disk is expensive. In Enterprise Mode, it's kind of a pain, you got to add, compute at the same time, so you kind of end up in an unbalanced place. So beyond mode that problem gets a lot better. We can add disk, infinite disk because it's backed by S3. And we can add compute really easy to scale, the number of things that we run in parallel concurrency, just add a sub cluster. So they are two US East and US west of Amazon, so reasonably diverse. And and the real benefit is that they can, we can stop nodes when we don't need them. Our workload is fairly lumpy, I call it. Like we, after the day completes, we do the ingest, we do the aggregation for ingesting and aggregating all day, but the final hour, so it needs to be completed. And then once that's done, then the number of reports that we need to run spikes up, it goes really high. And we run those reports, we spin up a bunch of extra compute on the fly, run those reports and then spin them down. And we don't have to pay for that, for the rest of the day. So Eon has been a nice Boone for us for both those reasons. >> I'd love to explore you on little bit more. I mean, it's relatively new, I think 2018 Vertica announced Eon mode, so it's only been out there a couple years. So I'm curious for the folks that haven't moved the Eon mode, can you which presumably they want to for the same reasons that you mentioned why by the stories and chunks when you're on Storage if you don't have to, what were some of the challenges that you had to, that you faced in going to Eon mode? What kind of things did you have to prepare for? Were there any out of scope expectations? Can you share that experience with us? >> Sure, so we were an early adopter. We participated in the beta program. I mean, we, I think it's fair to say we actually drove the requirements and a lot of ways because we approached Vertica early on. So the challenges were what you'd expect any early adopter to be going through. The sort of getting things working as expected. I mean, there's a number of cases, which I could touch upon, like, we found an efficiency in the way that it accesses the data on S3 and it was accessing the data too frequently, which ended up was just expensive. So our S3 bill went up pretty significantly for a couple of months. So that was a challenge, but we worked through that another was that we recently made huge strides in with Vertica was the ability to stop and start nodes and not have to start them very quickly. And when they start to not interfere with any running queries, so when we create, when we want to spin up a bunch to compute, there was a point in time when it would break certain queries that were already running. So that that was a challenge. But again, the very good team has been quite responsive to solving these issues and now that's behind us. In terms of those who need to get started, there's or looking to get started. there's a number of things to think about. Off the top of my head there's sort of new configuration items that you'll want to think about, like how instance type. So certainly the Amazon has a variety of instances and its important to consider one of Vertica's architectural advantages in these areas Vertica has this caching layer on the instances themselves. And what that does is if we can keep the data in cache, what we've found is that the performance is basically the same performance of Enterprise Mode. So having a good size cast when needed, can be a little worrying. So we went with the I three instance types, which have a lot of local NVME storage that we can, so we can cache data and get good performance. That's one thing to think about. The number of nodes, the instance type, certainly the number of shards is a sort of technical item that needs to be considered. It's how the data gets, its distributed. It's sort of a layer on top of the segmentation that some Vertica engineers will be familiar with. And probably I mean, the, one of the big things that one needs to consider is how to get data in the database. So if you have an existing database, there's no sort of nice tool yet to suck all the data into an Eon database. And so I think they're working on that. But we're at the point we got there. We had to, we exported all our data out of enterprise cluster as cache dumped it out to S3 and then we had the Eon cluster to suck that data. >> So awesome advice. Thank you for sharing that with the community. So but at the end of the day, so it sounds like you had some learning to do some tweaking to do and obviously how to get the data in. At the end of the day, was it worth it? What was the business impact? >> Yeah, it definitely was worth it for us. I mean, so right now, we have four times the data in our Eon cluster that we have in our enterprise clusters. We still run some enterprise clusters. We started with four at the peak. Now we're down to two. So we have the two young clusters. So it's been, I think our business would say it's been a huge win, like we're doing things that we really never could have done before, like for accessing the data on enterprise would have been really difficult. It would have required non trivial engineering to do things like daisy chaining clusters together, and then how to aggregate data across clusters, which would, again, non trivial. So we have all the data we want, we can continue to grow data, where running reports on seasonality. So our customers can compare their campaigns last year versus this year, which is something we just haven't been able to do in the past. We've expanded that. So we grew the data vertically, we've expanded the data horizontally as well. So we were adding columns to our aggregates. We are, in reaching the data much more than we have in the past. So while we still have enterprise kicking around, I'd say our clusters are doing the majority of the heavy lifting. >> And the cloud was part of the enablement, here, particularly with scale, is that right? And are you running certain... >> Definitely. >> And you are running on prem as well, or are you in a hybrid mode? Or is it all AWS? >> Great question, so yeah. When I've been speaking about enterprise, I've been referring to on prem. So we have a physical machines in data centers. So yeah, we are running a hybrid now and I mean, and so it's really hard to get like an apples to apples direct comparison of enterprise on prem versus Eon in the cloud. One thing that I touched upon in my presentation is it would require, if I try to get apples to apples, And I think about how I would run the entire workload on enterprise or on Eon, I had to run the entire thing, we want both, I tried to think about how many cores, we would need CPU cores to do that. And basically, it would be about the same number of cores, I think, for enterprise on prime versus Eon in the cloud. However, Eon nodes only need to be running half the course only need to be running about six hours out of the day. So the other the other 18 hours I can shut them down and not be paying for them, mostly. >> Interesting, okay, and so, I got to ask you, I mean, notwithstanding the fact that you've got a lot invested in Vertica, and get a lot of experience there. A lot of you know, emerging cloud databases. Did you look, I mean, you know, a lot about database, not just Vertica, your database guru in many areas, you know, traditional RDBMS, as well as MPP new cloud databases. What is it about Vertica that works for you in this specific sweet spot that you've chosen? What's really the difference there? >> Yeah, so I think the key differences is the maturity. There are a number, I am familiar with another, a number of other database platforms in the cloud and otherwise, column stores specifically, that don't have the maturity that we're used to and we need at our scale. So being able to specify alternate projections, so different sort orders on my data is huge. And, there's other platforms where we don't have that capability. And so the, Vertica is, of course, the original column store and they've had time to build up a lead in terms of their maturity and features and I think that other other column stores cloud, otherwise are playing a little bit of catch up in that regard. Of course, Vertica is playing catch up on the cloud side. But if I had to pick whether I wanted to write a column store, first graph from scratch, or use a defined file system, like a cloud file system from scratch, I'd probably think it would be easier to write the cloud file system. The column store is where the real smarts are. >> Interesting, let's talk a little bit about some of the challenges you have in reporting. You have a very dynamic nature of reporting, like I said, your clients want to they want to a time series, they just don't want to snap snapshot of a slice. But at the same time, your reporting is probably pretty lumpy, a very dynamic, you know, demand curve. So first of all, is that accurate? Can you describe that sort of dynamic, dynamism and how are you handling that? >> Yep, that's exactly right. It is lumpy. And that's the exact word that I use. So like, at the end of the UTC day, when UTC midnight rolls around, that's we do the final ingest the final aggregate and then the queue for the number of reports that need to run spikes. So the majority of those 40,000 reports that we run per day are run in the four to six hours after that spikes up. And so that's when we need to have all the compute come online. And that's what helps us answer all those queries as fast as possible. And that's a big reason why Eon is advantage for us because the rest of the day we kind of don't necessarily need all that compute and we can shut it down and not pay for it. >> So Ron, I wonder if you could share with us just sort of the wrap here, where you want to take this you're obviously very close to Vertica. Are you driving them in a heart and Eon mode, you mentioned before you'd like, you'd have the ability to load data into Eon mode would have been nice for you, I guess that you're kind of over that hump. But what are the kinds of things, If Column Mahoney is here in the room, what are you telling him that you want the team, the engineering team at Vertica to work on that would make your life better? >> I think the things that need the most attention sort of near term is just the smoothing out some of the edges in terms of making it a little bit more seamless in terms of the cloud aspects to it. So our goal is to be able to start instances and have them join the cluster in less than five minutes. We're not quite there yet. If you look at some of the other cloud database platforms, they're beating that handle it so I know the team is working on that. Some of the other things are the control. Like I mentioned, while we like control in the column store, we also want control on the cloud side of things in terms of being able to dedicate cluster, some clusters specific. We can pin workloads against a specific sub cluster and take advantage of the cast that's over there. We can say, okay, this resource pool. I mean, the sub cluster is a new concept, relatively new concept for Vertica. So being able to have control of many things at sub cluster level, resource pools, configuration parameters, and so on. >> Yeah, so I mean, I personally have always been impressed with Vertica. And their ability to sort of ride the wave adopt new trends. I mean, they do have a robust stack. It's been, you know, been 10 plus years around. They certainly embraced to do, the embracing machine learning, we've been talking about the cloud. So I actually have a lot of confidence to them, especially when you compare it to other sort of mid last decade MPP column stores that came out, you know, Vertica is one of the few remaining certainly as an independent brand. So I think that speaks the team there and the engineering culture. But give your final word. Just final thoughts on your role the company Vertica wherever you want to take it. >> Yeah, no, I mean, we're really appreciative and we value the partners that we have and so I think it's been a win win, like our volumes are, like I know that we have some data that got pulled into their test suite. So I think it's been a win win for both sides and it'll be a win for other Vertica customers and prospects, knowing that they're working with some of the highest volume, velocity variety data that (mumbles) >> Well, Ron, thanks for coming on. I wish we could have met face to face at the the Encore in Boston. I think next year we'll be able to do that. But I appreciate that technology allows us to have these remote conversations. Stay safe, all the best to you and your family. And thanks again. >> My pleasure, David, good speaking with you. >> And thank you for watching everybody, we're covering this is the Cubes coverage of the Vertica virtual Big Data conference. I'm Dave volante. We'll be right back right after this short break. (soft music)

>> Narrator: Live from New York, it's theCube! Covering AWS Global Summit 2019, brought to you by Amazon Web Services. >> Welcome back, we're here at the Javits Center in New York City for AWS Summit, I'm Stu Miniman, my cohost is Corey Quinn and happy to welcome to the program Scott Mullins, who's the head of Worldwide Financial Services Business Development with Amazon Web Services based here in The Big Apple, thanks so much for joining us. >> Thanks for having me, Stu, thanks for having me, Corey. >> All right so we had obviously financial services big location here in New York City. We just had FINRA on our program, had a great conversation about how they're using AWS for their environments, but give us a thumbnail if you will about your business, your customers and what you're seeing there. >> Sure, we're working with financial institutions all the way from the newest FinTech startups, all the way to organizations like FINRA, the largest exchanges and brokers dealers like Nasdaq, as well as insurers and the largest banks. And I've been here for five years and in that time period I actually went from being a customer speaking at the AWS Summit here in the Javits Center on stage like Steve Randich was today to watching more and more financial institutions coming forward, talking about their use in the cloud. >> Yeah before we get into technology, one of the biggest trends of moving to cloud is I'm moving from CapEx more to OpEx and oh my gosh there's uncertainty because I'm not locking in some massive contract that I'm paying up front or depreciating over five years but I've got flexibility and things are going to change. I'm curious what you're seeing as the financial pieces of how people both acquire and keep on the books what they're doing. >> Yeah it can be a little bit different, right, then what most people are used to. They're used to kind of that muscle memory and that rhythm of how you procured technology in the past and there can be a stage of adjustment, but cost isn't really the thing that people I think look to the most when it comes to cloud today, it's all about agility and FINRA is a great example. Steve has talked about over and over again over the last several years how they were able to gain such business agility and actually to do more, the fact that they're now processing 155 billion market events every night and able to run all their surveillance routines. That's really indicative of the value that people are looking for. Being able to actually get products to market faster and reducing development cycles from 18 months to three months, like Allianz, one of our customers over in Europe has been able to do. Being able to go faster I think actually trumps cost from the standpoint of what that biggest value driver that we're seeing our customers going after in financial services. >> We're starting to see such a tremendous difference as far as the people speaking at these keynotes. Once upon a time you had Netflix and folks like that on stage telling a story about how they're using cloud to achieve all these amazing things, but when you take a step back and start blinking a little bit, they fundamentally stream movies and yes, produce some awesome original content. With banks and other financial institutions if the ATM starts spitting out the wrong number, that's a different point on the spectrum of are people going to riot in the street. I'm not saying it's further along, people really like their content but it's still a different use case with a different risk profile. Getting serious companies that have world shaking impact to trust public cloud took time and we're seeing it with places like FINRA, Capital One has been very active as far as evangelizing their use of cloud. It's just been transformative. What does that look like, from being a part of that? >> Well you know it's interesting, so you know you just said it, financial services is the business of risk management. And so to get more and when you see more and more of these financial institutions coming forward and talking about their use of cloud, what that really equates to is comfort, they've got that muscle memory now, they've probably been working with us in some way, shape or form for some great period of time and so if you look at last year, you had Dean Del Vecchio from Guardian Life Insurance come out on stage at Reinvent and say to the crowd "Hey we're a 158 year old insurance company but we've now closed our data center and we're fully on AWS and we've completed the transformation of our organization". The year before you saw Goldman Sachs walk out and say "Yeah we've been working with AWS for about four years now and we're actually using them for some very interesting use cases within Goldman Sachs". And so typically what you've seen is that over the course of about a two year to sometimes a four year time period, you've got institutions that are working deeply with us, but they're not talking about it. They're gaining that muscle memory, they're putting those first use cases to begin to scale that work up and then when they're ready man, they're ready to talk about it and they're excited to talk about it. What's interesting though is today we're having this same summit that we're having here in Cape Town in Africa and we had a customer, Old Mutual, who's one of the biggest insurers there, they just started working with us in earnest back in May and they were on stage today, so you're seeing that actually beginning to happen a lot quicker, where people are building that muscle memory faster and they're much more eager to talk about it. You're going to see that trend I think continue in financial services over the next few years so I'm very excited for future summits as well as Reinvent because the stories that we're going to see are going to come faster. You're going to see more use cases that go a lot deeper in the industry and you're going to see it covering a lot more of the industry. >> It's very much not, IT is no longer what people think of in terms of Tech companies in San Francisco building products. It's banks, it's health care and these companies are transitioning to become technology companies but when your entire, as you mentioned, the entire industry becomes about risk management, it's challenging sometimes to articulate things when you're not both on the same page. I was working with a financial partner years ago at a company I worked for and okay they're a financial institution, they're ready to sign off on this but before that they'd like to tour US East one first and validate that things are as we say they are. The answer is yeah me too, sadly, you folks have never bothered to invite me to tour an active AZ, maybe next year. It's challenging to I guess meet people where they are and speak the right language, the right peace for a long time. >> And that's why you see us have a financial services team in the first place, right? Because your financial services or health care or any of the other industries, they're very unique and they have a very specific language and so we've been very focused on making sure that we speak that language that we have an understanding of what that industry entails and what's important to that industry because as you know Amazon's a very customer obsessed organization and we want to work backwards from our customers and so it's been very important for us to actually speak that language and be able to translate that to our service teams to say hey this is important to financial services and this is why, here's the context for that. I think as we've continued to see more and more financial institutions take on that technology company mindset, I'm a technology company that happens to run a bank or happens to run an exchange company or happens to run an insurance business, it's actually been easier to talk to them about the services that we offer because now they have that mindset, they're moving more towards DevOps and moving more towards agile. And so it's been really easy to actually communicate hey, here are the appropriate changes you have to make, here's how you evolve governance, here's how you address security and compliance and the different levels of resiliency that actually improve from the standpoint of using these services. >> All right so Scott, back before I did this, I worked for some large technology suppliers and there were some groups on Wall Street that have huge IT budgets and IT staffs and actually were very cutting edge in what they were building, in what they were doing and very proud of their IT knowledge, and they were like, they have some of the smartest people in the industry and they spend a ton of money because they need an edge. Talking about transactions on stock markets, if I can translate milliseconds into millions of dollars if I can act faster. So you know, those companies, how are they moving along to do the I need to build it myself and differentiate myself because of my IT versus hey I can now have access to all the services out there because you're offering them with new ones every day, but geez how do I differentiate myself if everybody can use some of these same tools. >> So that's my background as well and so you go back that and milliseconds matter, milliseconds are money, right? When it comes to trading and actually building really bespoke applications on bespoke infrastructure. So I think what we're seeing from a transitional perspective is that you still have that mindset where hey we're really good at technology, we're really good at building applications. But now it's a new toolkit, you have access to a completely new toolkit. It's almost like The Matrix, you know that scene where Neo steps into that white room and hey says "I need this" and then the shelves just show up, that's kind how it is in the cloud, you actually have the ability to leverage the latest and greatest technologies at your fingertips when you want to build and I think that's something that's been a really compelling thing for financial institutions where you don't have to wait to get infrastructure provisioned for you. Before I worked for AWS, I worked for large financial institutions as well and when we had major projects that we had to do that sometimes had a regulatory implication, we were told by our infrastructure team hey that's going to be six months before we can actually get your dev environment built so you can actually begin to develop what you need. And actually we had to respond within about thirty days and so you had a mismatch there. With the cloud you can provision infrastructure easily and you have an access to an array of services that you can use to build immediately. And that means value, that means time to market, that means time to answering questions from customers, that means really a much faster time to answering questions from regulatory agencies and so we're seeing the adoption and the embrace of those services be very large and very significant. >> It's important to make sure that the guardrails are set appropriately, especially for a risk managed firm but once you get that in place correctly, it's an incredible boost of productivity and capability, as opposed to the old crappy way of doing governance of oh it used to take six weeks to get a server in so we're going to open a ticket now whenever you want to provision an instance and it only takes four, yay we're moving faster. It feels like there's very much a right way and a wrong way to start embracing cloud technology. >> Yeah and you know human nature is to take the run book you have today and try to apply it to tomorrow and that doesn't always work because you can use that run book and you'll get down to line four and suddenly line four doesn't exist anymore because of what's happened from a technological change perspective. Yeah I think that's why things like AWS control tower and security hub, which are those guardrails, those services that we announced recently that have gone GA. We announced them a couple of weeks ago at Reinforce in Boston. Those are really interesting to financial services customers because it really begins to help automate a lot of those compliance controls and provisioning those through control tower and then monitoring those through security hub and so you've seen us focus on how do we actually make that easier for customers to do. We know that risk management, we know that governance and controls is very important in financial services. We actually offer our customers a way to look from a country specific angle, add the different countries and the rule sets and the requirements that exist in those countries and how you map those to our controls and how you map those into your own controls and all the considerations that you have, we've got them on our public website. If you went to atlas.aws right now, that's our compliance center, you could actually pick the countries you're interested in and we'll have that mapping for you. So you'll see us continue to invest in things like that to make that much easier for customers to actually deploy quickly and to evolve those governance frameworks. >> And things like with Artifact, where it's just grab whatever compliance report you need, submit it and it's done without having to go through a laborious process. It's click button, receive compliance in some cases. >> If you're not familiar with it you can go into the AWS console and you've got Artifact right there and if you need a SOC report or you need some other type of artifact, you can just download it right there through the console, yeah it's very convenient. >> Yeah so Scott you know we talked about some of the GRC pieces in place, what are you seeing trends out there kind of globally, you know GDRP was something that was on everybody's mind over the last year or so. California has new regulations that are coming in place, so anything specific in your world or just the trends that you're seeing that might impact our environments-- >> I think that the biggest trends I would point to are data analytics, data analytics, data analytics, data analytics. And on top of that obviously machine learning. You know, data is the lifeblood of financial services, it's what makes everything go. And you can look at what's happening in this space where you've got companies like Bloomberg and Refinitiv who are making their data products available on AWS so you can get B-Pipe on AWS today, you can also get the elektron platform from Refintiv and then what people are trying to do in relation to hey I want to organize my data, I want to make it much easier to actually find value in data, both either from the standpoint of regulatory reporting, as you heard Steve talk about on stage today. FINRA is building a very large data repository that they have to from the standpoint of a regulatory perspective with CAT. Broker dealers have to actually feed the CAT and so they are also worried about here in the US, how do I actually organize my data, get all the elements I have to report to CAT together and actually do that in a very efficient way. So that's a big data analytic project. Things that are helping to make that much easier are leg formations, so we came up with leg formation last year and so you've got many financial institutions that are looking at how do you make building a data leg that much easier and then how do you layer analytics on top of that, whether it's using Amazon elastic map reduce or EMR to actually run regulatory reporting jobs or how do I begin to leverage machine learning to actually make my data analytics from a standpoint of trade surveillance or fraud detection that much more enriched and actually looking for those anomalies rather than just looking for a whole bunch of false positives. So data analytics I think is what I would point to as the biggest trend and how to actually make data more useful and how to get to data insights faster. >> On the one end it seems like there's absolutely a lot of potential in this, on the other it feels in many cases with large scale data analytics, it's we have all these tools for machine learning and the rest that we can wind up passing out to you but you need to figure out what to do with them, how to make it work and it's unclear outside of a few specific use cases and I think you've alluded to a couple of those how to take in a typical business that maybe doesn't have an enormous pile of data and start applying machine learning to it in a way that makes intelligent sense. That feels right now like a storytelling failure to some extent industry wide. We're starting to see some stories emerge but it still feels a little "Gold Rush"-y to some extent. >> Yeah I would say, and my advice would be don't try to boil the ocean or don't try to boil the data leg, meaning you want to do machine learning, you've got a great amount of earnestness about that but picture use case, really hone in on what you're trying to accomplish and work backwards from that. And we offer tooling that can be really helpful in that, you know with stage maker you can train your models and you can actually make data science available to a much broader array of people than just your data scientists. And so where we see people focusing first, is where it matters to their business. So if you've got a regulatory obligation to do surveillance or fraud detection, those are great use cases to start with. How do I enhance my existing surveillance or fraud detection, so that I'm not just wading again through a sea of false positives. How do I actually reduce that workload for a human analyst using machine learning. That's a one step up and then you can go from there, you can actually continue to work deeper into the use cases and say okay how do I treat those parameters, how do I actually look for different things that I'm used to with the rules based systems. You can also look at offering more value to customers so with next best offer with Amazon Personalize, we now have encapsulated the service that we use on the amazon.com retail site as a service that we offer to customers so you don't have to build all that tooling yourself, you can actually just consume Personalize as a service to help with those personalized recommendations for customers. >> Scott, really appreciate all the updates on your customers in the financial services industry, thanks so much for joining us. >> Happy to be here guys, thanks for having me. >> All right for Corey Quinn, I'm Stu Miniman, back with more here at AWS Summit in New York City 2019, thanks as always for watching theCube.

>> Announcer: Live from New York. It's the Cube. Covering AWS Global Summit 2019. Brought to you by Amazon Web Services. >> Welcome back rush hour's started a little bit early here in New York City with over 10,000 people in attendance for AWS summit in New York City. I'm Stu Miniman, my co host for today is Corey Quinn. Happy to welcome to the program two first time guests from our host, Amazon Web Services. To my right here is Deepak Singh, who's the Director of Compute Services. Sitting to his right is Aaron Kao, who's the Senior Manager of Product Marketing. Gentlemen, thanks so much for joining us. >> Thank you for having us. >> Thank you for having us. >> Alright, so we know that every day we wake up and there's new announcements coming from Amazon and the only way most of us keep up with it is trying to read Corey's newsletter here. But in your group in compute, we know there's a lot going on and quite a few announcements. So Aaron, why don't you kick us off with some of the hard news that went through this morning? >> Yeah, we just launched Amazon EventBridge. It's a serverless event boss that allows you to connect your applications with data from sources like SaaS applications, AWS resources and your own applications. >> All right, so Deepak, I would love to dig into that a little bit. Like you said you that Amazon, you've learned a lot from CloudWatch and building this tool. Everybody looking at kind of, you know, Lambda in the serverless space is like, Okay, how are all these pieces going to come together? Is it all Amazon services all the time? And of course, Amazon has a huge ecosystem, but help us understand or layer down you know how this works? >> Yeah so as you know, AWS services send events to CloudWatch events. They consume events from CloudWatch events. One of the best ways to do it is through Lambda. One of Lambda's biggest strengths is the number of integrations we have with event sources, both taking in events and triggering events. But to your point, there are always events inside database ecosystem. And I think one of the things as a service owner that really excites me about EventBridge is how now customers have access not just to event triggers inside AWS, but also to our partners like Zendesk and the applications you can build will be really exciting. >> Alright, quite a few other announcements, maybe walk us through some of them. >> Yeah, CDK is another announcement where it's an open source software development framework that allows you to model your applications using programming language like TypeScript, Java, Python and .net. You know, the whole thing with building in the cloud, it's slightly different. You used to take your code, put it on a server and run it. Now people are building things a little more distributed, using a lot of different resources for their applications. So it's getting, provisioning your infrastructure is a little bit harder, right? You either have to do a lot of things manually or maybe you're writing a lot of scripts or using a domain specific language. But with CDK, you're now able to use the programming languages that you're programming your applications with, to model and provision your infrastructure. So it's super helpful. Really think it's going to help developers increase their development velocity. They're able to use things like loops, conditions, object oriented programming, they don't have to do context switching and just with a few lines of code, they're able to do a lot more. >> All right. >> I wound up playing with it a little bit when it was in preview and one of the things that I found that it was extremely helpful was, it was a lot easier for me to write something in using CDK, and then see what that rendered down to in terms of cloud formation and then oh, I guess that's how I do it in cloud formation, which was great. The counterpoint though, is it also felt at times like it was super wordy. So if I read that what it generates compared to what I normally write, which is admittedly awful, but I almost start to feel like I'm doing it wrong with that and then with amplify and with Sam and the rest, there's a lot of higher level abstractions that build cloud formation for you. But then it renders down in a few different and key ways. Under the hood, how much are these products that you're coming out with starting to shape the direction of cloud formation itself, or is that mostly baked and done? >> There's a lot of products that we're building that you know, are complementing cloud formation. You know, cloud formation is the templating modeling language to provision AWS resources. But on top of that, we have things like Sam right, that provides a declarative a more high level abstract declarative way to build on top of cloud formation, you know, we have Amplified that also uses cloud formation to help you build mobile applications and front end development. And then finally, you have CDK for just general use. So, these things are all complementing and, you know, things customers are asking for and helping us shape the ecosystem there. >> Yeah, Deepak the container space, of course, has been you know, one of these tidal waves that we've been watching and it's fundamentally changing the way people architect their applications and has huge impact on your product line. Give us the update. If you could just start with some of the high level, I remember first when I talked to you a couple of years ago it was when the whole Kubernetes piece was sorting out. So you know, ECS, EKS, used to have a much longer name that Cory would constantly >> Only for Cory >> Finally you've fixed the compensation problem where someone was getting compensated based upon number of syllables and a service name so good on you on that one. >> Right and you know the acronym A-M-I maybe you can you know settle once and for all you know how how we pronounce that. >> I'm old school it'll always be AMI. (laughs loudly) >> Walk us through kind of, you know your container services. >> I think the great thing about containers is as you said the adoption is everywhere. And what we find is there's a growth of ECS, the growth of EKS whether you're running it on EC2 or Fargate everything is growing like crazy, because people find new interesting ways to run applications based on what they know and what they're comfortable with. We have customers, customers like SNAP that know Kubernetes well and they are building on there're building a big chunk of their new infrastructure on EKS on AWS and it basically helps the developer velocity. On the flip side, you have customers like Turner Broadcasting that run a lot of their web services or the Comedy Central content properties like that on Fargate because they can just stamp them out. They all you know, it's a website, it's a service that they can just keep expanding. So it boils down to what are the key things that you're comfortable with? What are the reasons you've picked something. So if you're running like SNAP across, you know, in many different places, you are likely to choose Kubernetes and standardize on that. So that's the best part for me is, people have choices and then they pick based on what they need at that point in time, which can be two different teams at the same place, picking a different solution. I will add that one of the areas that we are focused on now is observe ability and developer experience. Those are areas that our customers have been asking for. CDK plays into that you saw in the demo this morning and with observe ability with container insights and with the fluid plugins that we announced. I think those are areas that you'll see us do a lot more going forward. >> So right, that was one of news today, CloudWatch container insights just to explain what that one is. >> So historically, when you do CloudWatch look, it's very BM-centric, you're looking at CPU memory, you assuming an application, instances run for a particular period of time. In the container world, you have services where the underlying tasks come and go, all you know, at a very different rate. CloudWatch container insights is meant to be a world that's aware of the fact that your containerized applications are tasks and services and pods, so you're able to get more fine grained metrics on the things that container customers care about and you're not trying to use BM-centric language to look at a containerized infrastructure. So that's the biggest reason for doing that. And then on the Fluent Bit side was, our customers want log routing to whatever they want to do it on. Whether they want it to send to S3 or the Elasticsearch We do that with Kinesis Data Firehose. So we basically wrote a bunch of open source plugins for Fluent Bit that just send your logs where you want them to go. So that's kind of where we are focused. >> Yeah, I view it as more of a log router than I do almost anything else. >> It is that. >> Yeah. A question of: Where does it come from? Where does it go? How do you keep it straight? >> Yeah. >> It's at this point, what does it output to you these days? Are there are various destination options, third party vendors, CloudWatch, history? >> So we wrote two plugins one was for well three, I don't know. One for S3 because so many people don't understand the data to S3. The other one was a Kinesis Data Firehose. So from there, you can send it to Redshift, you can send it to you can send it to Elasticsearch. So based on what you however you want another analyze it, you can send it to a custom resource that's Kinesis. So, you're using some third party provider, you can just send your logs over to those. >> Yeah, Corey, you know, you're dealing with a lot of customers, you know, there's now so many, you know, different instance types and some of the pieces, you know, what's the feedback you're giving to, you know, Amazon these days? >> Entirely depends upon the service teams and it ranges from this is amazing, excellent job to okay, it's a good start. And it's always a question though, it's when you have what 200 service options or darn near it at this point, 170. It's impossible to wind up with something that is evenly consistent and you have services that are sub components of other services and built on top. I mean, I think the, I guess the feedback I've been giving almost universally across the board is, assume that I am about 20% as smart as you right now seem to think I am and then explain it to me and then I'll probably understand it a lot better. It comes down to service to storytelling, more or less of meeting people at various points along their journey and then I was mentioning in our editorial session just before this segment, that that's something that AWS has markedly improved on the last two or three years. Where you have customer stories that are rapidly moving up the stack as far as leverage services. It's not just we took the VMs and now we run them somewhere else. Now it's about building a high, extremely volume intensive applications on top of a whole bunch of managed services and these are serious companies. These are regulators it's not just Twitter for pets anymore. >> Nothing wrong with that. >> No. >> So, you know, we were discussing, like FINRA was a great case study this morning and they talked about in the four years that they've been on, they've re-architected three times. You know, how do you balance all of these new instances coming out with, you know, and how do I make sure that I deploy something today that I've got the flexibility to change, but you know, I want to be able to lock in my pricing and make it easier. >> So actually, we think about that quite a bit. One of the reasons we built app match the way we did, as something that sits outside the container orchestrator, was it doesn't lock you into choosing one or the other or even choosing an architecture. You can start off with a monolith, start putting side cards on it, getting visibility into all your traffic, then portions of your applications you can start breaking out, you can put them on Fargate, you can put them on ECS, you can put them on the EC2. I think that is something we did very consciously because so many of our customers are in that position and I think more and more are going to go higher up the stack using managed databases, using Lambda, but it's not decision they need to make all up front. They can do it piecemeal, and we see our customers find another good example, they've done that. >> One of the philosophies of it, like AWS is giving customers building blocks to build things on. So the whole thing is, here's a new primitive that you can use, then you can take it out, replace something with something else, depending on your needs. So we give customers flexibility and choice. >> And part of the problem is that, that very much becomes a double-edged sword. I mean, most recently, you've had effectively declared war on Alphabet. I don't mean the large cloud provider that turns things off for a living. I'm talking about the English alphabet, where you take a look at all the different EC2 instance types. I think in US East one now there's over what is it 190 different instances you can pick from. It leads to analysis paralysis, which one do I pick? What's the right answer? What am I committing to, what am I not? And you see, that's a microcosm of the larger service problem. I want to build a web app that does a thing, which services do I use, you open up the service listing and you just get this sort of sinking sensation? I get that I can't imagine what someone new to the space is getting to there. >> All right, and this is where things like Amplify, Fargate, AWS Batch where you don't need to select an instance. Where you just tell us what your requirements are and Batch makes that selection for you. The core building blocks are important because you can't really figure out what to do. But then you'll see us do much more about the stack to help people get there. It's an ongoing thing that will keep trying to tackle but you'll see a lot more of that. >> It's controversial. One of my favorite things about Lambda, for example, is there's one knob RAM and as you turn that up, other performance characteristics increase and people complain about it but I love the simplicity, because I don't have to sit and think and make all these different decisions. It's one access. >> Yeah, but if you want more knobs, you can use Fargate. So I think that, that's the beauty of it that you do have that choice. >> Yeah, one of the lines Aaron, I really liked in Werner's keynote is he said, "we've really, you know, my words commoditized IT. "We all have access to all of the tools now." You know, that was, you know what big data originally and cloud also was, you know, you used to have to be a nation state or fortune 100 to be able to do some of these things so, you know, what do you hear from customers? You know, how do they make sure, you know, they're staying competitive and ahead, and therefore, in that relationship between the business and IT, what do you hear from your customers these days? >> In terms of that? Well, I think for, you know, for customers, like I think EventBridge is a, a pretty good example of that, in terms of customers asking us for ability to, you know, integrate their SaaS providers, integrate a lot of different things and not have to, you know, not have to do a lot of undifferentiated heavy lifting and things like that and, you know, customers are increasingly moving towards like event driven architectures and they asked us, hey, we really like CloudWatch events and how you do things with IT automation and then bringing SaaS providers in and, we want to, you know, we don't want to build pulling infrastructure in order to access API's and do all all those heavy liftings. What we did was we built out, we took CloudWatch events and added new features for SaaS applications and built that into a separate service for people to use. So that's like, you know, a lot of the relationships we have with our customers, listening to what they need and giving them what they want. >> And I think that, that's a very valuable thing. You know, we used to say, you know, five years ago, you would talk about, you know, let's get rid of undifferentiated heavy lifting. >> Yeah. >> Well, now it's like, no, no, let's enable, you know, something that you would have thought was heavy lifting and we're daunted to be able to do it but now hopefully, it's easier, because a lot of this stuff, you know, as Corey said, this is still a little bit daunting and you know, well you've got a lot of ecosystem and service providers and services to help us, you know, take care of, you know, because it's the Paradox of Choice with all the options that you have. >> And I think that's the beauty of what, I mean our customers are smart, they manage to find it interesting ways to keep challenging us and they keep us busy. But I also think that really, really many of them, the ones who have been able to be successful, have figured out what it means to take all the tools we give them, which are the ones where they want to completely hand it over to AWS and give us the responsibility and then which ones do they really feel they care about and the ones who can find their balance are the ones that we see moving the fastest. I think that's what we're trying to do. >> All right, now and one thing that does absolutely permeates virtually every service team I've worked with at AWS, I mean, you I've had this experience with you, where I talked about how my use case isn't a terrific fit for your product and your response is always well, what is your use case? It's not, is starting off from the baseline assumption that my use case is ridiculous, which let's face it, it probably is. But being able to address a customer need and understand that even if it doesn't dictate roadmap, is incredibly valuable and I don't find that there are too many players in any space, let alone this one that are willing to have the patience to listen to, frankly, some loud person wearing a suit. >> We try, I mean, I think you heard Andy say there's so much like a big chunk 85, 90% of our roadmap is customer requests, I would say that even the remaining 10% is maybe not things that they've directly asked for but things that we've observed they've run into or that we've run into working with, you know, the one or two customers who are ahead of the pack. And Okay, they have this problem, how do you generalize that? And we try and understand what it means. One of the reasons we made the container roadmap public, was this space is moving so quickly, it's almost impossible for us to talk to enough customers to figure that out. So like, Okay, this gives us an avenue for them to come to us and just tell us, GitHub issues. >> Yeah, so right. Final question I have for both of you. Directionally looking forward, you know, the roadmap, we love when there is publicly facing material not under the NDAs that we normally have to be able to hear. So what are you hearing from your customers? What direction are they pulling you towards and that we should expect to watch AWS kind of further, as we head towards re:Invent later this year. >> I think customers are asking us for different things for developer experience, especially event driven architectures. I think there's going to be a lot of interesting things happening in the Lambda space and that entire space. >> Yeah and to add to that, I think, to your point earlier, helping them simplify choices is going to be a big part of it. Meeting them where they are, in their IDEs with a tooling is a big part of what you'll see us do. So, you know, I think you saw examples today and we'll keep building on top of those. >> All right, well, send our congratulations to the two pizza teams that worked on all of the projects that were announced today. Look forward to seeing you, you know, down the road. Thanks so much and welcome to being Cube alumni. >> Thank you for have us. >> Thank you for having us on. >> Appreciate it. >> Aaron, Deepak you know, from AWS. He's Corey Quinn, I'm Stu Miniman. Back with lots more coverage from AWS summit, here in New York City, thanks for watching the Cube.

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> Welcome back. Rush hours started a little bit early here in New York City, with over 10,000 people in attendance for any of US Summit in New York City. I'm stupid, and my co host for today is Corey Quinn. Having a welcome to the program to first time guests from our host Amazon Web service is to my right. Here is Deepak Singh, who is the director of Compute Service's. To his right is Aaron Cow, Who's the senior manager product marketing Gentlemen, thanks so much for joining us. Thank >> you for having us >> for having us, all right, so we know that every day we wake up and there's new announcements coming from Amazon, and the only way most of us keep up with it is trying to re Cory's newsletter here. But in your group and computer, we know there's a lot going on and quite a few announcements. So, Aaron, what do you kick us off with? Some of the hard news that went >> through this morning? Yeah, we just launched Amazon event. Bridgette's Ah, serverless event boss that allows youto connect your applications with data from sources like sass applications. A devious resource is in your own applications. >> All right, So Deepak would look to dig into that a little bit. I like you said, you that Amazon. You learned a lot from cloudwatch in building this tool. Everybody looking at kind of lambda and the service faces, Like Okay, how all these pieces together is that all? Amazon service is all the time. And, of course, Amazon has a huge ecosystem. But help help us understand a layer down. You know how this works. >> Yeah. So, you know, a dress service send events watchman consumer event from one of the best ways to do it is through Lando. Lando. One of London's biggest trends is the number off integration we have with events both taking in events and triggering event. But to your point there already events inside database system. I think one of the things as a service owner, that really excites me about event. How now? Customers of access, not just two ventricles inside eight of us were awesome apartments extended so that the application you can build will be really exciting. >> Quite a few other announcements maybe August or someone CK >> is another announcement where it's open. Source. Software development framework allows you to model your applications using programming language like typescript Job a python and got that. You know the whole thing with building in the cloud. It's slightly different. You usedto take your coat. Put it on a servant. Run it. Now people are building things a little more distributed. Using a lot of different resource is for their applications, so it's getting provisioning. Your infrastructure is a little bit harder, right? Either Have to do a lot of things manually. Are maybe you're writing. A lot of scripts are using a domain specific language, But with CD Kay, you're now able to use the programming languages that you're hurting your applications with two model and provisions your infrastructure. So it's super helpful. Really think it's gonna help developers increase their development velocity? They're able to use things like loops, conditions, object oriented programming. They don't have to do context switching and just a few lines of code. They're able to do a lot more. All right, >> I want I want a playing with it a little bit when it was in review, and one of things that I found that it was extremely helpful was it was a lot easier for me to write something in using CD kay and then see what that rendered down to in terms of cloud formation. And then, oh, I guess that's how I do it in cloud formation, which was great. The counterpoint, though, is it also felt, at times like it was super wordy. So if I read that what it generates compared to what I normally right, which is admittedly awful. But it's all right, we'll start to feel like I'm doing it wrong with that. And then with amplify and with Sam and the rest. There's a lot of higher level abstractions that build cloud formation for you. But then it renders down in a few different key ways under the hood. How much are these products that you're coming out with starting to shape the direction of confirmation itself? Or is that mostly baked and done? >> There's a lot of products that we're building that you know are complimenting information. Information is the template ing modeling language to provisional abusive resource is put on top of that. We have things like Sam, right? That provides a declared of ATM or high level abstracted declared way to build on topical information. You know, we have amplified also use this information to help you build mobile applications in front development and then finally have see decay for general use other things. They're all complimenting and you know are things customers are asking for helping us >> get the ecosystem. Deepak. The container space, of course, has been You know what one of these tidal waves that we've been watching on It's fundamentally changing the way people architect their applications. That huge impact on your product line Give us the update. If you could just start with some of the high level. Remember first when I talk to you. A couple of years ago, the whole kubernetes piece was sorting out. So you know, e c s E. K s usedto have a much longer name that Cory >> Cory. Finally, you fix the compensation problem where someone was getting compensated based upon number of syllables in a service name. So good on you on that one. >> Right on. Uh, you know, acronym, am I? Maybe you can you know, settle once and for all. You know how how we pronounce that >> I'm old school in love with the Army. >> But what what walk us through? Kind of. You know, your container service is, >> I think, the great thing about container, I said, adoption is everywhere on what we find. It brought a VCs the growth of cares where they're running it on to our fargate. Everything is growing like crazy because people find new interesting ways to run applications based on what they know. One what they're comfortable with their customers. Customers like Snap. There's no community well, and they're building on their building a big chunk of their new infrastructure on kneecaps or need to be with, and it basically helped develop a velocity. On the flip side, your customers like Turner Broadcasting that run a lot of their Web service is the comedy central content properties like that on Fargate because they can just stamp them out. They all you know, it's about time. It's a service that you can just keep expanding. So it boils down to one of the key things that you're comfortable with. One of the reasons you fix something if you are running like snap across. You know, in many different looks places you are likely to choose community and standardize on that. So that's the best part for me is people have choices and then the pic based on what they need. At that point in time, it can be two different teams at the same place. Picking a different solution. I will add that one of the areas that we are focused on now is a dub ability and develop experience, though the areas that our customers have been asking for CD Kay played into that record in the demo this morning. And with the probability with container inside on with the fluid that be announced, I think though that area, they do a lot more >> going forward, right? That was one of those cloudwatch container insights. Just explain what that one is >> so historically, when you do cloudwatch look very bm centric, you're looking at CPU memory. You're zooming application. We are instances run for a particular period of time. At the container world you have service is with the underlying tasks. Come and go all you know, a very different rate container inside. It's meant to be a world aware of the fact that you're containerized application that fast service is and part, they're able to get more fine grained metrics on the things that container customers care about. And you're not trying to use the BM centric language to look at the content. That's the biggest reason for doing that. And then on the floor in bedside Boy, our customers want loud rounding to whatever they want to do it on where they understand three or elasticsearch. We do that with data borrows. So we basically wrote a bunch of open source plug in for fluent, but they just end your log where you want them to go. That's kind of maybe a >> Yeah, I view it as more of a log router than I do. Almost anything else? Yeah, a question of where did it come from? Where does it go? How do you do? Keep straight. It's at this point. What is it out? What is it output to these days of their various destination options? Third party vendors cloudwatch history >> to plug in 14315413 because so many people in the center there with three the other one was like Anita. There. Apart from there, you can send it to read, Chef, you can send it todo you can send it to elasticsearch. So based on what however you want and I'll analyze it, you can send it to a custom resource. So you want you're using some third party provider. You can just send your logs over to those. >> Corey, you know, you're dealing with a lot of customers. You know, there's so many, you know, different instance types and some of some of the pieces. You know, what's the feedback you're giving? You know, Amazon these days >> entire depends upon the service teams, and it ranges from This is amazing. Excellent job, too. Okay, it's a good start, and it's always a question, though. It's when you have what 200 service options are darn near. It at this point aren't 70. It's impossible to wind up with something that is evenly consistent, and you have service is that air sub components of other service is built on top. I mean, I think the uh, I guess the feedback I've been giving almost universally across the board is assume that I am about 20% as smart as you right now seem to think I am and then explain it to me, and then I'll probably understand it a lot better. It comes down to service the storytelling more or less of meeting people of various points along their journey, and that I was mentioning in our editorial session just before this segment that that's something that AWS has markedly improved on the last two or three years, where you have customer stories that are rapidly moving up the up the stack as Faras Leverage Service's It's not just we took the EMS, and now we run them somewhere else. Now it's about building of extremely volume intensive applications on top of a whole bunch of managed service is and these air serious cos these air regulators. It's not just Twitter for pets anymore. >> Nothing wrong with that. No, >> So way were discussing like Enron was a great case this morning, and they talked about in the four years that they've been on, they re architected three times, you know, how do you balance all of these new wins is coming out with, you know, how do we make sure that I deploy something today that I've got the flexibility to change. But, you know, I want to be able to lock in my pricing and make it easier. >> Actually, we think about that quite a bit. One of the reasons we met, the way we did something that sits outside a container orchestrator. What? It doesn't lock you into choosing one or the other or even using an architecture. You can start over the monolith, start putting sidecars on it. It's getting with the ability to all your traffic portions of applications. You can start breaking out. You can put them on target. You can put them on PCs. You can put them on it, too. I think that is something we did very consciously because so many of our customers are in that position. And I think more and more are going to go higher up the stock using managed databases. You think lambda. But it's not decision they need to make all up front. They can do it piecemeal, and we see a custom fender. The good example there done that. >> I think one of the >> philosophies of like eight of us is giving customers building blocks the buildings on, so the whole thing is here's a new primitive that you can use. Then you can take it out, replace something with something else, depending on your needs. So we give customers flexibility and choice. >> And part of the problem is that that very much becomes a double edged sword. I mean, most recently you've had effectively declared war on alphabet. I don't mean the large cloud provider that turns things off for a living. I'm talking about the English alphabet where you take a look at all the different ec2 instance types. I think in US East one. Now there's over. What is it? 100 90 different instances you can pick from. It leads to analysis paralysis. Which one do I pick? What's the right answer? What am I committing to? What am I not? And you see that? That's a microcosm. The larger service problem. I want to build a Web app that does a thing. Which service is do I use? You open up the service listing and you just get this sort of sinking sensation. I get that. I can't imagine what someone new to the space is getting to >> you, and this is where things like amplify fargate aws patch. You don't need to select an instance where you just tell us for your requirements are on Batch makes that collection for you the core building. What's important because you can't really figure out what to do. But then you see us too much more about the attack to help people get there. It's an ongoing thing that will keep trying to tackle, but you see a lot more of that. >> It's controversial. One of my favorite things about Lambda, for example, is there's one knob ram, and as you turn that up, other performance characteristics increase and people complain about it. But I love the simplicity because I don't have to sit and think and make all these different decisions. It's one access, >> but if you want more knob, you can you fuck it. So I think that that's the beauty ofit that you do have that choice. >> Yeah, one lines there, and I really liked it. Borders keynote. Is he said way? Really? You know my words, commoditized. I t We all have access to all of the tools now, you know that was you know what big date originally file. It also was used to have to be a nation state 4100 to be able to do some of these things. So, you know, what do you hear from customers? How do they make sure you know, they're staying competitive and ahead on their four in that relationship between the business and I T. What do you hear from your customers these days? >> In terms of that? Well, I think, um, for you know, for customers like I think of Emperor age is a, uh, a pretty good example off that in terms of customers asking us for ability to, you know, integrate their SAS providers and a great a lot of different things and not have thio you No, no, no. >> I have >> to do a lot of undifferentiated heavy lifting and things like that. And customers are increasingly moving towards, like avenger oven architectures. And they asked us, Hey, we really like cloudwatch events and how you do things with a iittie automation and then bringing SAS providers and on way wantto you know, we don't want to build a polling infrastructure and orderto access athe eyes and do all all the heavy lifting. What we did was we built out way took cloudwatch events and added new features for SAS applications and build that into a separate service for people to use. That's like, you know, a lot of the relationships we have our customers listening to what they need and giving them what they want. >> I think that that's a very valuable thing. We used to say, You know, five years ago you would talk about, you know, let's get rid of indifferent, heavy lifting Well, now it's like, No, no, let's enable you know some thing that you would have thought was heavy lifting and we're daunted to be able to do it. But now hopefully it's easier because a lot of this stuff, you know, he said, This is still a little bit daunting, and you know, you've got a lot of ecosystem and service providers, and service is help us. You take care of, you know, because it's the paradox of choice. With all the options that you >> have on. I think that's the beauty of what I'm in a customer that smart. They managed to find interesting ways to keep challenging us and keep us busy. But I also think that really, really many of them the ones who've been able to be successful. I figured out what it needs to be. Take all the tools to give them which other ones where they want to completely hand it over to AWS and give us the responsibility. And then which ones today really feeling, get they care about and the ones who can find their balance of the ones that we see moving faster. I think that's what we're trying to >> write that one thing that does absolutely permeates virtually every service team I've worked with that AWS. I mean, I've had this experience with you where I talk about how my use case isn't a terrific fit for your product, and your response is always well, what is your use case? It's not. Is starting off on the baseline assumption that my use cases ridiculous, which, let's face it, it probably is. But being able to address a customer need to understand that even if it doesn't dictate, road map is incredibly valuable, and I don't find there are too many players in any space, let alone this one that are willing to have the patience to listen to. Frankly, some loud person wearing a suit. >> Way try. I mean, I think you heard me say this so much like a big junk. 85 90% of a road map. Customer request. I would say that even though remember remaining 10% maybe not think that they're directly asked for but think that you observed their running to or that we run into working with, you know, the one of the customers go ahead of the pack. Okay. They have this problem, Baker. How do you generalize that? And we try and understand what it means. One of the reasons to be made the container road map public was This space is moving so quickly. It's almost impossible for us to talk to enough customers to figure that out. So, like, okay, that gives us an avenue for them to come to us and just tell us and get have >> issues. Yeah, s o right. Final question for both of you directions. Looking forward, you know, the road map we love when there is publicly facing material, not under the NBA's that we normally have to be able to hear. So what are you hearing from your customers? What direction are they pulling you towards and that we should expect tow watch aws kind of a cz we head towards reinvent later this year. Yeah, >> like customers are asking us for different things for developer experience, especially event driven architectures. I think there's gonna be a lot of interesting things happening in the land of space and that entire space >> on to add to that. I think your point earlier helping the simplified choices is going to be a big part of it. Meeting them where they are in their ideas with the cooling is a big part of what you'll see us do. So you know, I think you saw examples today. We'll keep building on top of >> All right. Well, send our congratulations to the two pizza teams that worked on all of the projects that were announced today. Look forward to seeing you. You know, down the road in tracking down. Thanks so much. And welcome to be in Cuba one night having us Deepak, you know, from AWS. He's Cory Quinn on student back with lots more coverage from 80 West Summit here in New York City. Thanks for watching

>> Live from Washington D.C. It's theCUBE, covering the AWS Public Sector Summit 2018. Brought to you by Amazon Web Services, and its eco-system partners. (upbeat music) >> Welcome back to the nation's capitol. I'm Stu Miniman and you're watching theCUBE's coverage of AWS Public Sector Summit 2018. Joining me for the wrap-up of day one, John Furrier, Dave Vellante. So John, thanks for bringing us down. So you were here last year. We've interviewed Teresa Carlson a number of times at Reinvent, but we've got to start with you. Since you were here last year, watching this explode. I said, this reminds me of Reinvent three years ago, how big it is, 14,500 people, wow. >> Yeah, so you're right on. This is definitely a Reinvent kind of vibe, in a way to describe what happened with Amazon Reinvent, their annual conference which we were at the 2nd year, 2013, and have been every year. Reinvent got bigger every year, and just became more prominent, and the solutions scaled, the number of announcements, as we know Amazon today is packed, it's bigger than ever. The public sector market, which is defined as government, education, and global public sector countries like Bahrain and other countries, are really the target. They have unique requirements. So what's happening is that that market is being disrupted, and there's been similar moments in the public sector here in the United States, as well known. The fail of the website that Obama. You know, the health care sight was one. The government initiatives that have been going on. The government is not modern and people are frustrated. The IT workers are living in cages, they're strapped in. It's like, not good. The tooling's old, old client server, old vendors like Oracle and IBM and others that are trying to keep that business, and they're not modernizing. So, this modernization wave has hit the public sector across the board, and what's happening is they can actually build newer systems faster, and get lower cost, more efficiency, done faster. And this is disrupting not only their business model, but how they buy technology, the role of the supplier in that piece of the equation, and also just overall faster innovation. So, this is driving it. The shocker of all of it is the security conversation has been up leveled, meaning it's not a real issue. Certainly the security is a real issue, but in terms of a barrier that stops everything, that's not the case anymore. The CIA is really the most notable that came on and said the worst day in cloud security is better than anything we got working today. So that's a really interesting thing and the Department of Defense Jedi project is billions of dollars that would have gone to say, an Oracle, IBM, and all the incumbents, or, beltway bandits, as they've been called. Those days are over. So that to me is a really exciting thing for the country. But, Amazon is running the tables too. So again, this year, more of the same, bigger. Big agencies. Small partners and big, all riding the wave of growth. And, it's a new operating model, and again, we'll predict it here in theCUBE, as we always say, and then we'll be right again. This is going to be a special market for Amazon going forward. >> I think government market is definitely a microcosm of the overall marketplace as John said. It's very bureaucratic, they're slower to move, you got to regime change every four or eight years, so a lot of turnover. It's really hard to get. Okay, we're going to go with strategy, cause the strategy as they start stop, it's a near to mid term strategies are affected in the government. Obviously, there's a greater focus on security. Cloud addresses a lot of those. We certainly heard that from the CIA. I don't think you can talk about cloud and federal, without talking about that milestone CIA deal. That really was a watershed moment. It was a wake up call to the old guard. IBM, as you might recall, tried to fight the government, because the CIA awarded the contract to Amazon. IBM lost that case, they were eviscerated by the judge. It forced IBM to go out and pay two billion dollars for software. It was years later that Oracle really got in. So, Amazon, to an earlier guest's point, has a huge lead. The estimate was five to 10 years, I heard, over some of the legacy suppliers. Interesting, not sure exactly where Microsoft fits in there. Stu, I'd love to get your thoughts. The thing about cloud that we've, John, you talk about being right, for years, we've talked about the economics of cloud, the scale of cloud, the marginal economics, looking much more like software. That's clearly been to Amazon's advantage. And, they're mopping the floor with guys who can't keep pace. And so, that's played out in a big way, and this seems to be a winner take all market. Or, a few companies take all market. >> Yeah, the thing that I actually wanted to comment on that's really interesting to dig in here, is if you talk about application modernization. Yes, it is super challenging, and it's not happening overnight, but, have heard universities, non profits, they're moving. It's not just mobility, moving to the web, but talking about how they are decoupling and creating cloud native microservices environments. So, was talking to a large, government healthcare organization that was super excited to show me how he was going to take his really old application, and start pulling together services at a time. And, he's like, I've got 130 services. And here's how I'll stick a router in here and I'll start pulling them off to the cloud. Talked to a big university and said, how are they going from, my data center, which I'm out of power, I'm out of capacity. I'm going to use the VMWare thing, but over time, I'm moving to containers, I'm moving to serverless. That modernization, we know it's not moving all of it to the public cloud, but that migration is happening. It is challenging and as I've said many times in many of these Amazon shows, Dave and John, it's the companies that come here. They're the ones that are trying cool stuff. They're are able to play in some of these environments and they make progress. So, the thing that really excites me too, is when you hear government agencies that are doing innovative, cool things. It's like, how do I leverage my data and give back to the communities I serve. Help charities, help our communities, and do it in cost effective ways. >> Stu, I got to say, Dave, Theresa Carlson just came by theCUBE, we gave her a wave. She's the CEO of Public Sector, as I call her, she's the chief, she's in charge. Andy Jackson's the CEO of AWS, but again, public sector's almost its own little pocket of AWS. Her leadership, I think, is a real driving force of why it was successful so fast. Theresa Carleson is hard charging, she knows the government game. She's super nice, but she can fight. And she motivates her team. But she listens to the customers, and she takes advantage of that Amazon vibe, which is solve a problem, lower prices, make things go faster, that's the flywheel of the culture. And she brings it to a whole nother level. She's brought together a group of people that are succeeding with her. She leans on her partners, so partners are making money. She's bringing in cloud native kind of culture. I mean, CrowdStrike, you can't get any better than seeing guys like CrowdStrike raise 200 million dollars, Dave, today announced, worth over three billion dollars, because they built their system to work for cloud scale. CloudChecker, another company. Purpose built for the cloud and is extremely successful because they're not trying to retrofit an enterprise technology and make it cloudified. They actually built it for the cloud. This, to me, is a signal of what has to happen on successful deployments, from a customer standpoint. And I think that's what attracting the customers and they will change their operations 'cause the benefits are multifold and they're pretty big. Financially, operationally, culturally, it's disruptive. So I think that's a key point. >> Yeah, and I think again, this a microcosm of the larger AWS, which is a microcosm of the larger Amazon, but, some of the things we heard today, some of the benchmarks and milestones from Theresa on the keynote. 60 consultancies that she put up on the slide, 200 ISVs ans SAAS companies, 950 third-party software providers, this is all GovCloud. And then Aurora now in GovCloud, which is, you know, you see here, it lags. >> Database. >> Amazon and Specter, you've heard a lot about database. Amazon and Specter, which manages security configurations. We heard about the intent to go forward with the VMWare partnership, the VMWare cloud in GovCloud. So, a little bit behind where you see the Amazon web services in commercial. But, taking basically the same strategy as John said. The requirements are different. I also think, Stu and John, it's important to point out just the progress of AWS. We're talking about tracking to 22 billion dollars this year. They're growing still at 15 percent, that massive number. 26 percent operating income. Their operating income is growing at 54 percent a year. So, just to compare Amazon web services to other so called infrastructure providers, HPE's operating income is eight percent, IBM's is nine percent, VMWare, which is a software company, is at 19 percent, Amazon's at 26 percent. It's Cisco level of profitability. Only companies like Oracle and Microsoft are showing better operating income. This is that marginal economics, that we've talked about for years. And Amazon is crushing it, just in terms of the economic model. >> Yeah, and they bring in the public sector. Can you imagine that disruption for that incumbent mindset of these government kind of agencies that have been the frog in boiling water for so many years around IT. It's like Boom, what a wake up call. If you know IT, you know what it's like. Older tools, huge budget cycles, massive amounts of technology trends in terms of time to value. I mean, Stu, you've seen this buoy before. >> Yeah, absolutely, and it's interesting. Some of the things we heard is there's challenge in the government sometimes, moving from capex to opex. The way that government is used to buying is they buy out of the GSA catalog, they are making that move. We actually had on the federal CTO for Cohesity, came from the GSA, and he said we're making progress as an industry on this. Dave, you mentioned a whole lot of stats here. I mean, year after year, Q1 Amazon was up 49 percent revenue growth. So, you know, you always hear on the news, it's like, oh well, market share is shifting. Amazon is still growing at such a phenomenal pace, and in the GovCloud, one of the things I thought Kind of interesting that gets overlooked is the GovCloud is about five years, no it launched in August of 2011, so it's coming up on seven years. It's actually based out of the West Coast. They have GovCloud, US East is coming later this year. And we talked in the VMWare interview that we did today about why some of the lag and you need to go through the certification and you need to make sure there's extra security levels. Because, there's not only GovCloud, then they've got the secret region, the top secret region, so special things that we need to make sure that you're FedRAMP compliant and all these things. Amazon is hitting it hard, and definitely winning in this space. >> Yeah, and they have a competitive advantage, I mean, they're running the table, literally. Because no body else has secret cloud, right? So, Amazon, Google, others, they don't have what the spec requires on these big agencies, like the DOD. So, it's not a sole source deal. And we saw the press that President Trump had dinner with Safra Catz, the CEO of Oracle. And, that Amazon, that people are crying foul. Making a multicloud, multivendor kind of, be fair, you know fairness. Amazon's not asking for sole source, they're just saying we're responding to the bid. And, we're the only ones that actually can do it. You know, John Wood, the CEO of Telos, said it best on theCUBE today, Amazon is well down the road, five years advantage over any cloud, five years he said. >> There's no compression algorithm for experience, right? >> Right, right, but this is a real conundrum for the government buyers, the citizens, and the vendors. So, typically, let's face it, technology, IBM, HPE, Oracle, Dell, they can all pretty much do the same thing. Granted, they got software, Cisco, whatever. They got their different spaces, but head to head, they all pretty much can do what the RFP requires. But what you just pointed out John, is Amazon's the only one that can do a lot of this stuff, and so, when they say, okay let's make it fair, what they're really saying is, let's revert back to the mean. Is that the right thing for the citizens? That's the kind of question that's on the table now. As a citizen, do you want the government pushing the envelope... >> That's what he said from CrowdStrike, why go backwards? >> Right, right, but that's essentially what the old guard is saying. Come back to us, make it fair, is that unfair? >> You're too successful, let the competition catch up, so it can be fair. No, they've got to match up the value proposition. And that fundamentally is going to put the feet to fire of government and it's going to be a real critical tell sign on how much teeth to the mission that the government modernization plan is. If that mission to be modernizing government has teeth, they will stay in the course. Now, if they have the way to catch up, that's great. I can already hear it on Twitter, John, you don't really know what you're talking about. Microsoft's right there. Okay, you can say you're doing cloud, but as they teach you in business school, there's diseconomies of scale, to try to match a trajectory of an experienced cloud vendor. Stu, you just mentioned that, let's explore that. If I want to match Amazon's years of experience, I can say I'm up there with all these services, but you can't just match that overnight. There's diseconomies of scale, reverse proxies, technical debt, all kinds of stuff. So, Microsoft, although looking good on paper, is under serious pressure and those diseconomies of scales creates more risk. That more risk is more downtime. They just saw 11 hours of downtime on Microsoft Azure in Europe, 11 hours. That's massive, it's not like, oh, something just happened for a day. >> Here's the behind the scenes narrative that you hear from certain factions. Is, hey, we hire people, let's say I'm talkin' about Microsoft, we hire people out of Amazon too, we know where they're at. We think we've narrowed that lead down to six months. You and I have both heard that. When you talk to people on the other side of the table, it's like, no way, there's no way. We're movin' faster, in fact, our lead is extended. So, the proof is in the pudding. In the results that you see in the marketplace. >> Well, and just to build on that, the customers. Amazon has the customers, you talk to anybody that's in these agencies, you know, like any industry, they're all moving around. Not only the federal, but, I had a great interview with Nutanix this morning, he said this was the best collection of state and local government that I ever had. It's like I got to meet all my customers in person last year when they came here. So, the fed kind of sets the bar, and then state, local, education, they all learn there. So, as you said, John, Theresa and her team have really built a flywheel of customers, and those customers, they understand the product. They're going deeper on that. >> But look, Microsoft has success where it has a software state. Clearly there are a lot of Microsoft customers in the government, and they're going to do very well there. But it's really different. We're talkin' about the inventor, essentially, of infrastructure as a service in Public Cloud and Amazon with a clean sheet of paper. >> Microsoft, Google and the others, they have to catch up. So, really if you look at, let's compare and contrast. Amazon, first mover, they did the heavy lifting up front. They win the CIA deal three, four years ago. Now they're going to win the DOD deal and more. So, they've got the boiler plate, and they've got scale, economies of scale. Microsoft's got to catch up, so, they've got diseconomies of scale. Google is kind of backing out, we heard. Some Google employees revolting cause they don't want to work on these AI projects for drones or what not. But, Google's approach is not tryin' to match Amazon speed for speed, they're thing is they have leverage. Their Android, their security, the data. So, Google's staying much more pragmatic. And they're humble, they're saying, look, we're not tryin' to match Amazon. But we're going to have a badass cloud from a Google perspective. Microsoft hasn't yet said that, they just try to level up. I think if Microsoft takes that approach, they will do well. >> Well, you got to give Microsoft a lot of credit, obviously for the transformation that's occurred. Again it's still tied to the company's software estate, in my view anyway. >> All right Stu, what's your impression, what's your take? >> So, John, like every Amazon show I've been to, I'm impressed, it set a high bar. We go to a lot of shows and not only are there more people here, but the quality of people, the energy, the passion, the discussion of innovation and change, is just super impressive. >> You and I cover cloud data pretty deep. We go to all the shows, obviously the Lennox Foundation and Amazon Reinvent, and others. Does the Public Sector have that vibe in your opinion? What's your sense of it? >> Oh, yeah, no, I've already had a couple of conversations about Kubernetes and Lambda, you know, more serverless conversations at this show than almost any show I go to, other than probably KubeCon or the Serverless conf. So, no, advanced users, these are not the ones, a couple of years ago, oh I'm checking what this is. No, no, no, they're in, they're deep, they're using. >> Yeah, I notice also, near the press room, they had the certification stickers, now levels of certifications. So, they're just movin' the ball down the field at Amazon. Dave, I want to go to you and ask you what your impression is. Obviously, you know, we've done shows like HPE Reinvent, which we didn't do this year. That's goin' down its own path. We've got other shows. >> HPE Discover you mean. >> What did I say? >> You said Reinvent. >> Okay, every year they break. >> There's two ends of the spectrum. >> You know, there's is going to try to transform. What's your take of this show, Public Sector? What's your view? >> Well, first of all, it's packed. And, the ecosystem here is really robust. I mean, you see the consultancies, you see every technology vendor, I mean, it's quite amazing. They got to figure out the logistics, right? I've never seen a line so long. The line to get into registration was longer than Disney lines this morning. I mean, really, it was amazing. >> It's a Disneyland for Public Sector. >> It really is, and people are excited here. I think you were touching upon it before. They've sort of been hit with this bureaucratic, you know, cemented infrastructure. And now, it's like they're takin' the gloves off and they're really excited. >> Stu and Dave, I really got to say, I'm not a big federal person, over the years in my career but my general impression over the past couple years, diggin' in here, is that most of the people in the agency want to do a good job. I saw that last year, it's like, these are real innovators. And finally they can break away, right, and do some real, good. Not do shadow IT, do it legit with a cloud. So, good stuff. Guys, thanks for commentating, Stu? >> Yeah, so let me bring it on home. I just want to say, this goes up in a podcast, if you go to your favorite podcast player and look for theCUBE Insights, you'll find this as well as the key analysis from our team from all of the shows. Of course, as always, go to theCube dot net to get all the research. If you want the exclusive, more detail on Theresa Carlson, just search John Ferrier in Forbes and you'll find that article. This is the end of Day One of two days live coverage from AWS Public Sector. Of course, theCUBE dot net, come find us, we've got stickers if you're at the show. For Dave Vellante, John Furrier, I'm Stu Miniman. And as always, thanks so much for watching theCUBE. (techno music)