>> John: Hello and welcome to this cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great conversation on making machine learning easier and more affordable in an era where everybody wants more machine learning and AI. We're featuring Neural Magic with the CEO is also Cube alumni, Brian Steve. CEO, Great to see you Brian. Thanks for coming on this cube conversation. Talk about machine learning. >> Brian: Hey John, happy to be here again. >> John: What a buzz that's going on right now? Machine learning, one of the hottest topics, AI front and center, kind of going mainstream. We're seeing the success of the, of the kind of NextGen capabilities in the enterprise and in apps. It's a really exciting time. So perfect timing. Great, great to have this conversation. Let's start with taking a minute to explain what you guys are doing over there at Neural Magic. I know there's some history there, neural networks, MIT. But the, the convergence of what's going on, this big wave hitting, it's an exciting time for you guys. Take a minute to explain the company and your mission. >> Brian: Sure, sure, sure. So, as you said, the company's Neural Magic and spun out at MIT four plus years ago, along with some people and, and some intellectual property. And you summarize it better than I can cause you said, we're just trying to make, you know, AI that much easier. And so, but like another level of specificity around it is. You know, in the world you have a lot of like data scientists really focusing on making AI work for whatever their use case is. And then the next phase of that, then they're looking at optimizing the models that they built. And then it's not good enough just to work on models. You got to put 'em into production. So, what we do is we make it easier to optimize the models that have been developed and trained and then trying to make it super simple when it comes time to deploying those in production and managing them. >> Brian: You know, we've seen this movie before with the cloud. You start to see abstractions come out. Data science we saw like was like the, the secret art of being like a data scientist now democratization of data. You're kind of seeing a similar wave with machine learning models, foundational models, some call it developers are getting involved. Model complexity's still there, but, but it's getting easier. There's almost like the democratization happening. You got complexity, you got deployment, it's challenges, cost, you got developers involved. So it's like how do you grow it? How do you get more horsepower? And then how do you make developers productive, right? So like, this seems to be the thread. So, so where, where do you see this going? Because there's going to be a massive demand for, I want to do more with my machine learning. But what's the data source? What's the formatting? This kind of a stack develop, what, what are you guys doing to address this? Can you take us through and demystify this, this wave that's hitting, that everyone's seeing? >> Brian: Yeah. Now like you said, like, you know, the democratization of all of it. And that brings me all the way back to like the roots of open source, right? When you think about like, like back in the day you had to build your own tech stack yourself. A lot of people probably probably don't remember that. And then you went, you're building, you're always starting on a body of code or a module that was out there with open source. And I think that's what I equate to where AI has gotten to with what you were talking about the foundational models that didn't really exist years ago. So you really were like putting the layers of your models together in the formulas and it was a lot of heavy lifting. And so there was so much time spent on development. With far too few success cases, you know, to get into production to solve like a business stereo technical need. But as these, what's happening is as these models are becoming foundational. It's meaning people don't have to start from scratch. They're actually able to, you know, the avant-garde now is start with existing model that almost does what you want, but then applying your data set to it. So it's, you know, it's really the industry moving forward. And then we, you know, and, and the best thing about it is open source plays a new dimension, but this time, you know, in the, in the realm of AI. And so to us though, like, you know, I've been like, I spent a career focusing on, I think on like the, not just the technical side, but the consumption of the technology and how it's still way too hard for somebody to actually like, operationalize technology that all those vendors throw at them. So I've always been like empathetic the user around like, you know what their job is once you give them great technology. And so it's still too difficult even with the foundational models because what happens is there's really this impedance mismatch between the development of the model and then where, where the model has to live and run and be deployed and the life cycle of the model, if you will. And so what we've done in our research is we've developed techniques to introduce what's known as sparsity into a machine learning model. It's already been developed and trained. And what that sparsity does is that unlocks by making that model so much smaller. So in many cases we can make a model 90 to 95% smaller, even smaller than that in research. So, and, and so by doing that, we do that in a way that preserves all the accuracy out of the foundational model as you talked about. So now all of a sudden you get this much smaller model just as accurate. And then the even more exciting part about it is we developed a software-based engine called Deep Source. And what that, what the Inference Runtime does is takes that now sparsified model and it runs it, but because you sparsified it, it only needs a fraction of the compute that it, that it would've needed otherwise. So what we've done is make these models much faster, much smaller, and then by pairing that with an inference runtime, you now can actually deploy that model anywhere you want on commodity hardware, right? So X 86 in the cloud, X 86 in the data center arm at the edge, it's like this massive unlock that happens because you get the, the state-of-the-art models, but you get 'em, you know, on the IT assets and the commodity infrastructure. That is where all the applications are running today. >> John: I want to get into the inference piece and the deep sparse you mentioned, but I first have to ask, you mentioned open source, Dave and I with some fellow cube alumnis. We're having a chat about, you know, the iPhone and Android moment where you got proprietary versus open source. You got a similar thing happening with some of these machine learning modules where there's a lot of proprietary things happening and there's open source movement is growing. So is there a balance there? Are they all trying to do the same thing? Is it more like a chip, you know, silicons involved, all kinds of things going on that are really fascinating from a science. What's your, what's your reaction to that? >> Brian: I think it's like anything that, you know, the way we talk about AI you think had been around for decades, but the reality is it's been some of the deep learning models. When we first, when we first started taking models that the brain team was working on at Google and billing APIs around them on Google Cloud where the first cloud to even have AI services was 2015, 2016. So when you think about it, it's really been what, 6 years since like this thing is even getting lift off. So I think with that, everybody's throwing everything at it. You know, there's tons of funded hardware thrown at specialty for training or inference new companies. There's legacy companies that are getting into like AI now and whether it's a, you know, a CPU company that's now building specialized ASEX for training. There's new tech stacks proprietary software and there's a ton of asset service. So it really is, you know, what's gone from nascent 8 years ago is the wild, wild west out there. So there's a, there's a little bit of everything right now and I think that makes sense because at the early part of any industry it really becomes really specialized. And that's the, you know, showing my age of like, you know, the early pilot of the two thousands, you know, red Hat people weren't running X 86 in enterprise back then and they thought it was a toy and they certainly weren't running open source, but you really, and it made sense that they weren't because it didn't deliver what they needed to at that time. So they needed specialty stacks, they needed expensive, they needed expensive hardware that did what an Oracle database needed to do. They needed proprietary software. But what happens is that commoditizes through both hardware and through open source and the same thing's really just starting with with AI. >> John: Yeah. And I think that's a great point before we to call that out because in any industry timing's everything, right? I mean I remember back in the 80s, late 80s and 90s, AI, you know, stuff was going on and it just wasn't, there wasn't enough horsepower, there wasn't enough tech. >> Brian: Yep. >> John: You mentioned some of the processing. So AI is this industry that has all these experts who have been itch scratching that itch for decades. And now with cloud and custom silicon. The tech fundamental at the lower end of the stack, if you will, on the performance side is significantly more performant. It's there you got more capabilities. >> Brian: Yeah. >> John: Now you're kicking into more software, faster software. So it just seems like we're at a tipping point where finally it's here, like that AI moment or machine learning and now data is, is involved. So this is where organizations I see really jumping in with the CEO mandate. Hey team, make ML work for us. Go figure it out. It's got to be an advantage for us. >> Brian: Yeah. >> John: So now they go, okay boss, we will. So what, what do they do? What's the steps does an enterprise take to get machine learning into their organizations? Cause you know, it's coming down from the boards, you know, how does this work for rob? >> Brian: Yeah. Like the, you know, the, what we're seeing is it's like anything, like it's, whether that was source adoption or whether that was cloud adoption, it always starts usually with one person. And increasingly it is the CEO, which realizes they're getting further behind the competition because they're not leaning in, you know, faster. But typically it really comes down to like a really strong practitioner that's inside the organization, right? And, that realizes that the number one goal isn't doing more and just training more models and and necessarily being proprietary about it. It's really around understanding the art of the possible. Something that's grounded in the art of the possible, what, what deep learning can do today and what business outcomes you can deliver, you know, if you can employ. And then there's well proven paths through that. It's just that because of where it's been, it's not that industrialized today. It's very much, you know, you see ML project by ML project is very snowflakey, right? And that was kind of the early days of open source as well. And so, we're just starting to get to the point where it's getting easier, it's getting more industrialized, there's less steps, there's less burdensome on developers, there's less burdensome on, on the deployment side. And we're trying to bring that, that whole last mile by saying, you know what? Deploying deep learning and AI models should be as easy as the as to deploy your application, right? You shouldn't have to take an extra step to deploy an AI model. It shouldn't have to require a new hardware, it shouldn't require a new process, a new DevOps model. It should be as simple as what you're already doing. >> John: What is the best practice for companies to effectively bring an acceptable level of machine learning and performance into their organizations? >> Brian: Yeah, I think like the, the number one start is like what you hinted at before is they, they have to know the use case. They have to, in most cases, you're going to find across every industry you know, that that problem's been tackled by some company, right? And then you have to have the best practice around fine-tuning the models already exist. So fine tuning that existing model. That foundational model on your unique dataset. You, you know, if you are in medical instruments, it's not good enough to identify that it's a medical instrument in the picture. You got to know what type of medical instrument. So there's always a fine tuning step. And so we've created open source tools that make it easy for you to do two things at once. You can fine tune that existing foundational model, whether that's in the language space or whether that's in the vision space. You can fine tune that on your dataset. And at the same time you get an optimized model that comes out the other end. So you get kind of both things. So you, you no longer have to worry about you're, we're freeing you from worrying about the complexity of that transfer learning, if you will. And we're freeing you from worrying about, well where am I going to deploy the model? Where does it need to be? Does it need to be on a device, an edge, a data center, a cloud edge? What kind of hardware is it? Is there enough hardware there? We're liberating you from all of that. Because what you want, what you can count on is there'll always be commodity capability, commodity CPUs where you want to deploy in abundance cause that's where your application is. And so all of a sudden we're just freeing you of that, of that whole step. >> John: Okay. Let's get into deep sparse because you mentioned that earlier. What inspired the creation of deep sparse and how does it differ from any other solutions in the market that are out there? >> Brian: Sure. So, so where unique is it? It starts by, by two things. One is what the industry's pretty good at from the optimization side is they're good at like this thing called quantization, which turns like, you know, big numbers into small numbers, lower precision. So a 32 bit representation of a, of AI weight into a bit. And they're good at like cutting out layers, which also takes away accuracy. What we've figured out is to take those, the industry techniques for those that are best practice, but we combined it with unstructured varsity. So by reducing that model by 90 to 95% in size, that's great because it's made it smaller. But we've taken that when it's the deep sparse engine, when you deploy it that looks at that model and says, because it's so much smaller, I no longer have to run the part of the model that's been essentially sparsified. So what that's done is, it's meant that you no longer need a supercomputer to run models because there's not nearly as much math and processing as there was before the model was optimized. So now what happens is, every CPU platform out there has, has an enormous amount of compute because we've sparsified the rest of it away. So you can pick a, you can pick your, your laptop and you have enough compute to run state-of-the-art models. The second thing that, and you need a software engine to do that cause it ignores the parts of the models. It doesn't need to run, which is what like specialized hardware can't do. The second part is it's then turned into a memory efficiency problem. So it's really around just getting memory, getting the models loaded into the cash of the computer and keeping it there. Never having to go back out to memory. So, so our techniques are both, we reduce the model size and then we only run the part of the model that matters and then we keep it all in cash. And so what that does is it gets us to like these, these low, low latency faster and we're able to increase, you know, the CPU processing by an order magnitude. >> John: Yeah. That low latency is key. And you got developers, you know, co coding super fast. We'll get to the developer angle in a second. I want to just follow up on this, this motivation behind the, the deep sparse because you know, as we were talking earlier before we came on camera about the old days, I mean, not too long ago, virtualization and VMware abstracted away the os from, from the hardware rights and the server virtualization changed the game. >> Brian: Yeah. >> John: And that basically invented cloud computing as we know it today. So, so we see that abstraction. >> Brian: Yeah. >> John: There seems to be a motivation behind abstracting the way the machine learning models away from the hardware. And that seems to be bringing advantages to the AI growth. Can you elaborate on, is that true? And it's, what's your comment? >> Brian: It's true. I think it's true for us. I don't think the industry's there yet, honestly. Cause I think the industry still is of that mindset that if I took, if it took these expensive GPUs to train my model, then I want to run my model on those same expensive GPUs. Because there's often like not a separation between the people that are developing AI and the people that have to manage and deploy at where you need it. So the reality is, is that that's everything that we're after. Like, do we decrease the cost? Yes. Do we make the models smaller? Yes. Do we make them faster? A yes. But I think the most amazing power is that we've turned AI into a docker based microservice. And so like who in the industry wants to deploy their apps the old way on a os without virtualization, without docker, without Kubernetes, without microservices, without service mesh without serverless. You want all those tools for your apps by converting AI models. So they can be run inside a docker container with no apologies around latency and performance cause it's faster. You get the best of that whole world that you just talked about, which is, you know, what we're calling, you know, software delivered AI. So now the AI lives in the same world. Organizations that have gone through that digital cloud transformation with their app infrastructure. AI fits into that world. >> John: And this is where the abstraction concepts matter. When you have these inflection points, the convergence of compute data, machine learning that powers AI, it really becomes a developer opportunity. Because now applications and businesses, when they actually go through the digital transformation, their businesses are completely transformed. There is no IT. Developers are the application. They are the company, right? So AI will be part of whatever business or app will be out there. So there is a application developer angle here. Brian, can you explain >> Brian: Oh completely. >> John: how they're going to use this? Because you mentioned docker container microservice, I mean this really is an insane flipping of the script for developers. >> Brian: Yeah. >> John: So what's that look like? >> Brian: Well speak, it's because like AI's kind of, I mean, again, like it's come so fast. So you figure there's my app team and here's my AI team, right? And they're in different places and the AI team is dragging in specialized infrastructure in support of that as well. And that's not how app developers think. Like they've ran on fungible infrastructure that subtracted and virtualized forever, right? And so what we've done is we've, in addition to fitting into that world that they, that they like, we've also made it simple for them for they don't have to be a machine learning engineer to be able to experiment with these foundational models and transfer learning 'em. We've done that. So they can do that in a couple of commands and it has a simple API that they can either link to their application directly as a library to make difference calls or they can stand it up as a standalone, you know, scale up, scale out inference server. They get two choices. But it really fits into that, you know, you know that world that the modern developer, whether they're just using Python or C or otherwise, we made it just simple. So as opposed to like Go learn something else, they kind of don't have to. So in a way though, it's made it. It's almost made it hard because people expect when we talk to 'em for the first time to be the old way. Like, how do you look like a piece of hardware? Are you compatible with my existing hardware that runs ML? Like, no, we're, we're not. Because you don't need that stack anymore. All you need is a library called to make your prediction and that's it. That's it. >> John: Well, I mean, we were joking on Twitter the other day with someone saying, is AI a pet or a cattle? Right? Because they love their, their AI bots right now. So, so I'd say pet there. But you look at a lot of, there's going to be a lot of AI. So on a more serious note, you mentioned in microservices, will deep sparse have an API for developers? And how does that look like? What do I do? >> Brian: Yeah. >> John: tell me what my, as a developer, what's the roadmap look like? What's the >> Brian: Yeah, it, it really looks, it really can go in both modes. It can go in a standalone server mode where it handles, you know, rest API and it can scale out with ES as the workload comes up and scale back and like try to make hardware do that. Hardware may scale back, but it's just sitting there dormant, you know, so with this, it scales the same way your application needs to. And then for a developer, they basically just, they just, the PIP install de sparse, you know, has one commanded to do an install, and then they do two calls, really. The first call is a library call that the app makes to create the model. And models really already trained, but they, it's called a model create call. And the second command they do is they make a call to do a prediction. And it's as simple as that. So it's, it's AI's as simple as using any other library that the developers are already using, which I, which sounds hard to fathom because it is just so simplified. >> John: Software delivered AI. Okay, that's a cool thing. I believe in it personally. I think that's the way to go. I think there's going to be plenty of hardware options if you look at the advances of cloud players that got more silicon coming out. Yeah. More GPU. I mean, there's more instance, I mean, everything's out there right now. So the question is how does that evolve in your mind? Because that's seems to be key. You have open source projects emerging. What, what path does this take? Is there a parallel mental model that you see, Brian, that is similar? You mentioned open source earlier. Is it more like a VMware virtualization thing or is it more of a cloud thing? Is there Yeah. Is it going to evolve in a, in a trajectory that looks similar to what we might've seen in the past? >> Brian: Yeah, we're, you know, when I, when when I got involved with the company, what I, when I thought about it and I was reasoning about it, like, do you, you know, you want to, like, we all do when you want to join something full-time. I thought about it and said, where will the industry eventually get to? Right? To fully realize the value of, of deep learning and what's plausible as it evolves. And to me, like I, I know it's the old adage of, you know, you know, software, its hardware, cloudy software. But it truly was like, you know, we can solve these problems in software. Like there's nothing special that's happening at the hardware layer and the processing AI. The reality is that it's just early in the industry. So the view that that we had was like, this is eventually the best place where the industry will be, is the liberation of being able to run AI anywhere. Like you're really not democratizing, you democratize the model. But if you can't run the model anywhere you want because these models are getting bigger and bigger with these large language models, then you're kind of not democratizing. And if you got to go and like by a cluster to run this thing on. So the democratization comes by if all of a sudden that model can be consumed anywhere on demand without planning, without provisioning, wherever infrastructure is. And so I think that's with or without Neural Magic, that's where the industry will go and will get to. I think we're the leaders, leaders in getting it there. It's right because we're more advanced on these techniques. >> John: Yeah. And your background too. You've seen OpenStack, pre-cloud, you saw open source grow and still exponentially growing. And so you have the same similar dynamic with machine learning models growing. And they're also segmenting into almost a, an ML stack or foundational model as we talk about. So you're starting to see the formation of tooling inference. So a lot of components coming. It's almost a stack, it's almost a, it literally is like an operating system problem space, you know? How do you run things, how do you link things? How do you bring things together? Is that what's going on here? Is this like a data modeling operating environment kind of red hat type thing going on? Like. >> Brian: Yeah. Yeah. Like I think there is, you know, I thought about that too. And I think there is the role of like distribution, because the industrialization not happening fast enough of this. Like, can I go back to like every customers, every, every user does it in their own kind of way. Like it's not, everyone's a little bit of a snowflake. And I think that's okay. There's definitely plenty of companies that want to come in and say, well, this is the way it's going to be and we industrialize it as long as you do it our way. The reality is technology doesn't get industrialized by one company just saying, do it our way. And so that's why like we've taken the approach through open source by saying like, Hey, you haven't really industrialized it if you said. We made it simple, but you always got to run AI here. Yeah, right. You only like really industrialize it if you break it down into components that are simple to use and they work integrated in the stack the way you want them to. And so to me, that first principles was getting thing into microservices and dockers that could be run on VMware, OpenShare on the cloud in the edge. And so that's the, that's the real part that we're happening with. The other part, like I do agree, like I think it's going to quickly move into less about the model. Less about the training of the model and the transfer learning, you know, the data set of the model. We're taking away the complexity of optimization. Giving liberating deployment to be anywhere. And I think the last mile, John is going to be around the ML ops around that. Because it's easy to think of like soft now that it's just a software problem, we've turned it into a software problem. So it's easy to think of software as like kind of a point release, but that's not the reality, right? It's a life cycle. And it's, and so I think ML very much brings in the what is the lifecycle of that deployment? And, you know, you get into more interesting conversations, to be honest than like, once you've deployed in a docking container is around like model drift and accuracy and the dataset changes and the user changes is how do you become from an ML perspective of where of that sending signal back retraining. And, and that's where I think a lot of the, in more of the innovation's going to start to move there. >> John: Yeah. And software also, the software problem, the software opportunity as well is developer focused. And if you look at the cloud native landscape now, similar stacks developing a lot of components. A lot of things to, to stitch together a lot of things that are automating under the hood. A lot of developer productivity conversations. I think this is going to go down that same road. I want to get your thoughts because developers will set the pace. And this is something that's clear in this next wave developer productivity. They're the defacto standards bodies. They will decide what microservices check, API check. Now, skill gap is going to be a problem because it's relatively new. So model sprawl, model sizes, proprietary versus open. There has to be a way to kind of crunch that down into a, like a DevOps, like just make it, get the developer out of the, the muck. So what's your view? Are we early days like that? Or what's the young kid in college studying CS or whatever degree who comes into this with, with both feet? What are they doing? >> Brian: I'll probably say like the, the non-popular answer to that. A little bit is it's happening so fast that it's going to get kind of boring fast. Meaning like, yeah, you could go to school and go to MIT, right? Sorry. Like, and you could get a hold through end like becoming a model architect, like inventing the next model, right? And the layers and combining 'em and et cetera, et cetera. And then what operators and, and building a model that's bigger than the last one and trains faster, right? And there will be those people, right? That actually, like they're building the engines the same way. You know, I grew up as an infrastructure software developer. There's not a lot of companies that hire those anymore because they're all sitting inside of three big clouds. Yeah. Right? So you better be a good app developer, but I think what you're going to see is before you had to be everything, you had to be the, if you were going to use infrastructure, you had to know how to build infrastructure. And I think the same thing's true around is quickly exiting ML is to be able to use ML in your company, you better be like, great at every aspect of ML, including every intricacy inside of the model and every operation's doing, that's quickly changing. Like, you're going to start with a starting point. You know, in the future you're not going to be like cracking open these GPT models, you're going to just be pulling them off the shelf, fine tuning 'em and go. You don't have to invent it. You don't have to understand it. And I think that's going to be a pivot point, you know, in the industry between, you know, what's the future? What's, what's the future of a, a data scientist? ML engineer researcher look like? >> John: I think that's, the outcome's going to be determined. I mean, you mentioned, you know, doing it yourself what an SRE is for a Google with the servers scale's huge. So yeah, it might have to, at the beginning get boring, you get obsolete quickly, but that means it's progressing. So, The scale becomes huge. And that's where I think it's going to be interesting when we see that scale. >> Brian: Yep. Yeah, I think that's right. I think that's right. And we always, and, and what I've always said, and much the, again, the distribute into my ML team is that I want every developer to be as adept at being able take advantage of ML as non ML engineer, right? It's got to be that simple. And I think, I think it's getting there. I really do. >> John: Well, Brian, great, great to have you on theCUBE here on this cube conversation. As part of the startup showcase that's coming up. You're going to be featured. Or your company would featured on the upcoming ABRA startup showcase on making machine learning easier and more affordable as more machine learning models come in. You guys got deep sparse and some great technology. We're going to dig into that next time. I'll give you the final word right now. What do you see for the company? What are you guys looking for? Give a plug for the company right now. >> Brian: Oh, give a plug that I haven't already doubled in as the plug. >> John: You're hiring engineers, I assume from MIT and other places. >> Brian: Yep. I think like the, the biggest thing is like, like we're on the developer side. We're here to make this easy. The majority of inference today is, is on CPUs already, believe it or not, as much as kind of, we like to talk about hardware and specialized hardware. The majority is already on CPUs. We're basically bringing 95% cost savings to CPUs through this acceleration. So, but we're trying to do it in a way that makes it community first. So I think the, the shout out would be come find the Neural Magic community and engage with us and you'll find, you know, a thousand other like-minded people in Slack that are willing to help you as well as our engineers. And, and let's, let's go take on some successful AI deployments. >> John: Exciting times. This is, I think one of the pivotal moments, NextGen data, machine learning, and now starting to see AI not be that chat bot, just, you know, customer support or some basic natural language processing thing. You're starting to see real innovation. Brian Stevens, CEO of Neural Magic, bringing the magic here. Thanks for the time. Great conversation. >> Brian: Thanks John. >> John: Thanks for joining me. >> Brian: Cheers. Thank you. >> John: Okay. I'm John Furrier, host of theCUBE here in Palo Alto, California for this cube conversation with Brian Stevens. Thanks for watching.

>> Announcer: Live from New Orleans, Louisiana, it's theCUBE covering .NEXT conference, 2018. Brought to you by Nutanix. >> Welcome back I'm Stu Miniman with my co-host Keith Townsend, and you're watching theCUBE, the leader in live tech coverage. We're at Nutanix NEXT 2018, happy to welcome to the program Brian Stevens, who's the CTO of Google Cloud, had on the program many times. Brian, always a pleasure to catch up with you. >> Thanks, glad to be here. >> Stu: And have a first time guest, Ricardo Jenez, who's the SVP of Development at Nutanix. Thank you so much for joining us. >> Well, thank you for being, thanks for being here. >> Alright, so Ricardo you've only been with Nutanix for three months. I believe this is probably your first .NEXT? >> Ricardo: Yes, it is. >> So give us a little bit about your role and what brings you to us today. >> So I'm responsible for some of the core data path and per some products. So, you know, a lot of it has to do with how do we end up delivering value to our customers and actually end up having predictable, scalable HCI solutions. So, that's really what I'm focused on and focusing on sort of improving our ability to deliver products more quickly. >> So Brian, last year Diane Greene was up on stage talking about the partnership and what was happening here, see Google at the show, obviously a tighter partnership for Nutanix, but give us the update on-- >> We're downgrading. >> Yeah? >> Slumming it. >> Not at all. Not at all. I wish we had enough time to get into the weeds on some of the stuff you're working on, but tell us what brings you here and what kind of stuff you're poking at these days. >> Geez, I think I met Sunil Potti a couple years ago, just at the very beginning of trying to find sort of the intersection between Google Cloud and Nutanix. I mean, Nutanix is largely redefining what IT looks like on premise. We believe we're doing that in cloud, and you really just want to eliminate the impedance between on-premise and public cloud, and so the work with Nutanix is all like what can we do to actually make it more seamless for users that want to use core cloud technology. >> Yeah Brian, you're one of those people that we would say have enterprise DNA in what they've done in their background. People on the outside will always say, Well you know, it's Google, it's Google-y. It's too smart for us. >> Brian: Enterprise DNA is still sexy. >> Yeah, I mean look, there's a lot of enterprises out there, and while yes, the other startups. Maybe we talk a little bit about what that means inside Google. >> Oh my gosh, yeah it was quite a pivot for Google, you know. It was amazing technology, but the customer that you were serving with Google Cloud was already inside of Google. You were serving Surge and YouTube and ads. So you end being up, a really technically, but close relationship. And so what enterprise is, a couple things, it's been a cultural transformation inside of Google, it's been obviously working with enterprise customers globally and building that go to market model and motion that you can sell, but we want a really technical engineered partnership with our customers. So it's not a vendor relationship. So building all that out, we thing we're unique with that. And then the other part I think you were alluding to early before we went on mic, was just around enterprise has a increased set of requirements on what we deliver them from a capabilities perspective, from a security aspect, from a telemetry aspect. And then it's all like how do we actually slipstream into their process, rather than just redefine everything. So to us, that's a big part of what our enterprise pivot's been, for the last three, four years. >> So Ricardo, you have some background at Google. What brought you to Nutanix? What appealed to you? >> Well you know, more than anything else, I think Nutanix has set themselves up, to basically take that experience it has in enterprise, and translate that into the cloud. So when I was at Google, I actually worked on the Google search appliance, which was Google's first-- >> I remember that. >> You remember that. >> I had that one. >> Little yellow boxes, sometimes blue boxes, and that was a great experience. So I'm really happy to hear that Brain talk about the transformation that has happened within Google. But you know, being at Nutanix, the ability to take that experience very close with the work loads that customers are running, and then being able to work with a partner like Google and actually be able to have hybrid clouds where internal private cloud plus having public cloud providers, that really ends up changing the game for a lot of enterprises. >> Yep. Brain, One of the things we've been struggling with as an industry is, you know, it's application mobility. Data, where it goes. Nutanix has been talking about really hybrid cloud from their standpoint. We've talked with you before about where Kubernetes fits into this. Application portability, you just made an acquisition, today was announced, Velostrata. Give us your state on where those things added, it's a big gnarly topic. >> It was just more friction, like public cloud offers great capability that's going to be used not necessarily completely instead of, but in companion to, you know, application services. But there was still that friction around in the early incarnation, it was like it's VMware in this environment or KVM in this environment, and it's a whole nother AMI kind of model here. So the ability to use it, there was a tax. And then there also wasn't that portability and that lightweight aspect that you'd want from an application containerization. I mean, you want what you have on your phone. You want that ability to install apps anywhere. And cloud and IT infrastructure should be exactly the same way. So that's a big part of our investment in containerization. You know Google, back when I was at Red Hat, was investing in cgroups back when there was a kernel, way back then to kind of build that first incarnation of containers in Linux. Along comes Docker to standardize that. I mean, it's an amazing gift to the world. And then Kubernetes is, we're just moving up the stack, on how do you orchestrate it. So sure, companies like Velostrata are really interesting because you have, you know, beyond having Kubernetes platform everywhere, yeah we'll say it's the de facto, but that doesn't mean everybody's running it. And so you're still running on existing systems, you know, largely kind of virtualized. And Velostrata is a technology leader in being virtualization of this type to Google Cloud or other clouds. And then even more so, the technology they have to bring that to containers. So they help you do that migration, transformation process. And I think that's really important for IT organizations. >> Ricardo, you want to comment on some of the hybrid cloud migration stuff? >> So we have our com product, which allows us to actually end up taking workload and moving it to, for instance, Google Cloud or eventually sciCloud and then moving that workload back. So having that sort of Nutanix inside and outside gives it maximum flexibility, and that's a lot of power for IT to have, right? Deciding where it's best to actually run their workloads and be as efficient as possible. >> So as we look at the com, we look at Google Cloud, just the overall pictures, if you're enterprise, you're looking at Google and you're saying man, Google runs at two different speeds. One is 12 factor, micro services, Kubernetes, functions. And then the other side is that, some people just want a VM. They just want a cloud instance and how to make that simple. So let's talk about this relationship. How does Nutanix come together with Google who runs at two different speeds, to make Google Cloud more consumable to the average enterprise? >> Well we're going to talk a little bit more about it later, but the fact that basically we're going to be able to deploy Xi within Google Cloud with nested AHV, and then allow our customers, that'll basically be doing standard workloads to migrate their jobs over to a Google Cloud offering. And as Brian will point out, that basically creates opportunities for them to be able to avail themselves of other capabilities that Google has. So it's not altogether an instant moving path to rewrite, reorient all your apps. It's an ability to kind of do that school migration, if you want to. But you have that capability of being able to go back and forth, in terms of what your workloads are. >> Yeah. >> Brian, want to get your viewpoint on just some of the changing roles that are happening in our industry. We were talking that some of the interviews we've been doing today, it's people talking about infrastructure and code. There was a big hackathon at this event for the first time in, they sold out with over 14 groups, and everything like that. This is a show that started out with people talking about storage, and now we're talking about individual data centers and clouds and all of those things. What are you seeing out in the marketplace? What are some of the challenges and opportunities you're hearing from customers these days? >> I mean it depends on which customers, right? Which region of the world and what their business looks like and I think we all know the holy grail. Infrastructure, as code, is an implementation, but I think what we know that what you really desire is the ability for reproduce ability. The ability to sort of not have state in the IT process. You want to be able to recreate things anywhere. Recreate a whole application, blueprint internally, on public cloud. Tear it down, recreate it. There's no other way to do that without code. So what sort of comes from that SRE model that Google invented, is that what it you didn't have an IT department? And what if you had software engineers that were responsible for IT function? What would that look like? And that's where all of the sudden you realize, everything's APIs and code. So I think that's interesting, and that's sort of where you want to get to, but it's then like, how do you bridge that because a lot of people aren't software developers in IT departments. >> So here's my follow up, 'cause when I go to the Kubernetes show and I talk to users there, 95% of them-- >> They're way over there. >> Had built their own stack, and why do they do that? Because they were ahead of all the platforms. And then I come to the Nutanix show and they're like oh, tensorflow and functions and all that stuff. We're going to put an easy button, and make it easy. I need to take all of these tools and open source and put it together, versus the platform and the easy button. Is this just the early adopters and the majority? >> I think that's okay. That's the open source world, right? I mean think about what's great about open source, is not just creating sort of a venue for collaboration and developers, it's creating access for end users. And so some of the best companies in the world have been built on a DIY model of people just taking open source and integrating it and making the recipe that they want. And so I think you get that whole sort of spectrum and you aren't forced down this model of, here's a COTS product, oh and it happens to be based on open source, but you always have to use technology this way. Open source gives them the freedom to do it as they want. We just need to make sure that we bridge it, so that there's not anybody left behind. That everybody should be able to use the power of Kubernetes, and that means making things super easy to use, and the integration with Nutanix we think is a huge part of making you use that technology stack in a way that's seamlessly operated for an audience like this. >> So a lot of the debate and questions around Kubernetes is how far should it go? Should it go as far as being an opinionated pass? Should it just be a container platform? Where does it start and end? >> Brian: You want my opinion? >> Yeah, opinion that would be awesome. >> Yeah, that was it. Well I think the way the industry started was obviously, there were no PASes, and then we built OpenShift to Red Hat and Google app engine in Roku. And what happened is, those are interesting, but you're right, they are overly opinionated. So you were left either picking a PAS, and you got to change everything to do it this way, and it's great because it delivers value of managed service, but not everything fit in that model. Or you got next to nothing. >> Keith: Right. >> You got a straight IS platform, and then you got to do all the rest. So what we've been doing at Google is tearing that apart and building that architecture from the ground up where you opt into the level that you want. If you want to be able to use IS and the features of IS you use that. If you want to step up and just use containers and IS, you can use containers and IS. If you want to step up and use Kubernetes orchestration, you can do that. If you want to step up and run managing everything in services, than that stacks on top of Kubernetes with STO. If you want to be full on and put in a developer workflow that always has you do deploys this way, then that stacks on top. So I think you're going to get away from this false dichotomy of a choice over here or here, and you're going to all of a sudden get this architectural layering cake that lets you opt into what you want and have IT consistency all the way through it. >> I mean, I used to have a startup that was focused on Hatuputu service, and you know one of the things was basically you didn't have this layering, right? It was, you take the whole stack or you take nothing. And I think the strategy that Google has employed with Kubernetes is just brilliant, to kind of work you way up and basically get people at different levels to be involved. You know, there is a do-it-yourself folks, and they should be allowed to and empowered to do the things that they want to do. And then there are other people who want to have more composed environment. And so we can actually bring that to them as well. And I think that's brilliant. Basically very early on, while Google used a lot of open source internally, it wasn't a strong sort of part of the open source environment. And so I've just enjoyed watching the evolution of Google, sort of leading the open source movement. So, it's been fantastic. I'm right there with you, you know, give them at every level. >> Ricardo, one of the questions coming into this week, people want to know the update of what's happening with Xi. Can you speak about where we are with that and the relationship with Google? What should we be looking for for the rest of this year? >> Well I can't really talk about that, but you know, we are working very closely with Google. And we'll talk a little bit about that at our talk later today. But I won't comment on anything to do with Xi. >> So that gives me the opportunity to ask another controversial question about Kubernetes and getting both of your opinions on it. There's religions and open sourced as religions, enterprise IT, one of which is DevOps. And you look at what companies like Netflix have done with containerizing Java applications and running those legacy Java applications in their container platform. Enterprises are looking at that stuff and thinking, you know what, can I containerize my monolithic application, put it on top of Kubernetes, and drive more efficiency out of my operations from portability to being able to stack up applications in public cloud, general things. Monolithic applications, is that a good thing, bad thing, indifferent? Wrong plate, wrong tool, wrong-- >> No, I think it's just that there's no like one size even for what a monolithic app looks like. Like we don't really have a really proper definition of what it is, but I think people do feel that all of a sudden Kubernetes needs a rewrite and containers needs a rewrite, and actually it doesn't. Because apps are usually sort of separated from the OS already. And so what they're doing is marrying the libraries of the OS, and containers allows them to do that, but just get a higher degree of portability and then with Kubernetes orchestration. So it really depends more around what's the machine resources that that monolithic app needs and are those machine resources still available in a containerized environment. In most cases, the answer is yes. Now the most interesting thing is, what's the escape hatch? Because you can't have a monolithic app that your company, say it's on Mainframe, say it's in the case of something that will not containerize and shouldn't because it's working as designed and there's no use touching it. But that should still participate in the application architecture of the future. And that's why SEO and services are so important. So even if you can't change your runtime stack, you still need to be able to put a services layer in an API in front of that monolithic service, and you'll have a visibility of a service mesh inside of that environment. So now IT sees it just looks like a black box IT service. It doesn't really matter to them that it's not running on the next generation stack because they can still depend on its' services. >> Yeah, I mean I would agree. I look at what Kubernetes offers and containers as sort of an on ramp to creating services, the on ramp to actually taking that monolithic application, assuming that they're resources, and take a step up in terms of the architectures that you can build around it and then be able to break apart that monolithic application. It doesn't have to happen all at once. It's sort of the stepping stones that you can take. So it's a very powerful model for enablement for people who have stuff that they haven't been able to make the most value out of because maybe the application's been around for a while. Now they can actually end up putting it in an environment where they can actually make the most of it and then work on how they're going to end up slowly pulling it apart and making it more service oriented. >> Alright, Ricardo and Brian, thank you so much for joining us. Appreciate the update and look forward to seeing more throughout the show and further in the year. Be sure to check out theCUBE.net where you'll not only find all of this information, but theCUBE is really excited to say that we will be at the Google Cloud show in July. So for Keith Townsend, and I'm Stu Miniman, getting towards the end of day one of two days of live coverage. Thanks so much for watching theCUBE. (upbeat music)

>> Narrator: Live from Boston, Massachusets. It's theCUBE, covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, Red Hat and additional ecosystem and support. >> Hi, welcome back, I'm Stu Miniman, joined by my cohost John Troyer and happy to welcome back to the program Brian Stevens who's the CTO of Google Cloud. Brian, thanks for joining us. >> I'm glad to, it's been a few years. >> All right, I wanted to bounce something off you. We always talk about, you know, it's like open source. You worked for in the past what is most considered the most successful open source company for monetizing open source, which is Red Hat. We have posited at Wikibon that it's not necessarily the company, it's not only the companies that sell a product or a solution that make money off it, but I said, if it wasn't for things like Linux in general and open source, we wouldn't have a company like Google. Do you agree with that, you look at the market cap of a Google, I said if we didn't have Linux and we didn't have open source, Google probably couldn't exist today. >> Yeah, I don't think any of the hyper scale cloud companies would exist without open source and Linux and Intel. I think it's a big part of the stack, absolutely. >> All right. You made a comment at the beginning about what it means to be an open source person working at Google. The joke we all used to make was the rest of us are using what Google did 10 years ago, it eventually goes from that whitepaper all the way down to some product that you used internally and then maybe gets spun off. We wouldn't have Hadoop if it wasn't for Google. Just some of the amazing things that have come out of those people at Google. But what does it mean to be open source at Google and with Google? >> You get both, right? 'Cause I think that's the fun part is I don't think a week goes by where I don't get to discover something coming out of a resource group somewhere. Now the latest is machine learning, you know, Spanner because they'd learned how do to distributed time synchronization across geo data centers, like who does that, right? But Google has both the people and the desire and the ability to invest in on the research side. And then you marry that innovation with everything that's happening in open source. It's a really perfect combination. And so instead of building these proprietary systems, it's all about how do we actually not just contribute to open source, but how do we actually build that interoperability framework, because you don't want cloud to be an island, you want it to be really integrated into developer tools, databases, infrastructure, et cetera. >> And a lot of that sounds like it plays into the Kubernetes story, 'cause, you know, Kubernetes is a piece that allows some similarities between wherever you place your data. Maybe give us a little bit more about what Google, you know, how do you decide what's internal, I think about like the Spanner program, which there's some other open source pieces coming up, looks like they read the whitepaper and they're trying to do some pieces. You said less whitepapers, more code coming out of people, what does that means? >> It's not that we'll do less whitepapers. 'Cause whitepapers are great for research, and Google's definitely a research strong academic oriented company. It's just that you need to go further as well. So that was, you know, what I was talking about like with GRPC, creating an Apache project I think was the first time for streaming analytics, right, was the first time that I think Google's done that. Obviously, been involved for years at the Linux kernel, compilers, et cetera. I think it's more around what do developers need, where can we actually contribute to areas, because what you don't want, what we don't want is you're on premise and you're using one type of system, then you move to Google Cloud and it feels like there's impedance. You're really trying to get rid of the impedance mismatch all the way across the stack, and one of the best ways you can do that is by contributing new system designs. There's a little bit less of that happening in the analytics space now though, I think the new ground for that is everything that's happening in machine learning with Tensor Flow et cetera. >> Yeah, absolutely. There was some mention in the keynote this morning, all of the AI and ML, I mean, Google with Tensor Flow, even Amazon themselves getting involved more with open source. You said you couldn't build the hyper scales without them, but is that the, do they start with open source, do you see, or? >> Well, I think that most people are running on a Linux backplane. It's a little bit different in Google 'cause we got an underlying provisioning system called the Borg. And that just works, so some things work, don't change them. Here is where you really want to be open source first are areas that are just under active evolution, because then you actually can join that movement of active evolution. Developer tools are kind of like that. Even machine learning. Machine learning's super strategic to just about every company out there. But what Google did by actually open sourcing Tensor Flow is now they created a canvas, that community, we talk about that here, but for data scientists to collaborate, and these are people that didn't do much in open source prior, but you've given that ability to sort of come up with the best ideas and to innovate in code. >> I wanted to ask a little bit about the enterprise, right. We can all make jokes about enterprising is what everybody should've been doing 10 years ago, and they're finally getting to. But on the other hand, Red Hat, very enterprise focused company. OpenStack, service provider and very enterprise focused. One of the things that Google Cloud is doing... Well, I guess the criticism has typically been how does Google as a company and as a culture and as a cloud focused on the enterprise, especially bringing advanced topics like machine learning and things like that, which to a traditional IT person are a little foreign. So I just am interested in kind of how you're viewing, how do we approach the needs of the enterprise, meet them where they are today, while yet giving them an access to a whole set of services and tools that are actually going to take them into a business transformation stance? >> Sure. And that's because you end up as a public cloud provider with the enterprise, you end up having multiple conversations. You certainly have one of your primary audiences, the IT team, right. And so you have to earn trust and help them understand the tools and your strategy and your commitment to enterprise. And then you have CSOs, right, and the CEO, that's worried about everything security and risk and compliance, so it's a little bit different than your IT department. And then what's happening with machine learning and some of the higher end services is now you're actually building solutions for lines of business. So you're not talking to the IT teams with machine learning and you're not talking to the CSOs, you're really talking around business transformation. And when you're actually, if you're going into healthcare, if you're going into financial, it's a whole different team when you're talking about machine learning. So what happens is Google's really got a segmented three sort of discreet conversations that happen at separate points of time, but all of which are enterprise focused, 'cause they all have to marry together. Even though there may be interest in machine learning, if you don't wrap that in an enterprise security model and a way that IT can sustain and enable and deal with identity and all the other aspects, then you'll come up short. >> Yeah. Building on that. One of the critiques of OpenStack for years has been it's tough. I think about one of the critiques of Google is like, oh well, Google build stuff for Google engineers, we're not Google engineers, you know, Google's got the smartest people and therefore we're not worthy to be able to handle some of that. What's your response to that? How do you put some of those together? >> Of course, Google's really smart, but there's smart people everywhere. And I don't think that's it. I think the issue is, you know, Google had to build it for themselves, right, they'd build it for search and build it for apps and build it for YouTube. And OpenStack's got a harder problem in a way, when you think about it, 'cause they're building it for everybody. And that was the Red Hat model as well, it's not just about building it for Goldman Sachs, it's building it for every vertical. And so it's supposed to be hard. This isn't just about building a technology stack and saying we're done, we're going to move on. This community has to make sure that it works across the industry. And that doesn't happen in six years, it takes a longer period of time to do that, and it just means keeping your focus on it. And then you deal with all the use cases over time and then you build, that's what getting to a unified commoditized platform delivers. >> I love that, absolutely. We tend to oversimplify things and, right, building from the ground up some infrastructure stack that can live in any data center is a big challenge. I wrote an article years ago about Amazon hyperoptimizes. They only have to build for one data center, it's theirs. At Google, you understand what set of applications you're going to be running, you build your applications and the infrastructure supports it underneath that. What are some of the big challenges you're working on, some of the meaty things that are exciting you in the technology space today? >> In a way, it's similar. In a way, it's similar, it's just that at least our stack's our stack, but what happens is then we have to marry that into the operational environments, not just for a niche of customers, but for every enterprise segment that's out there. What you end up realizing is that it ends up becoming more of a competency challenge than a technology issue because cloud is still, you know, public cloud is still really new. It's consolidating but it's still relatively new when you start to think about these journeys that happen in the IT world. So a lot of it for us is really that technical enablement of customers that want to get to Google Cloud, but how do you actually help them? And so it's really a people and processes kind of conversation over how fast is your virtual machine. >> One of the things I think is interesting about that Google Cloud that has developed is the role of the SRE. And Google has been, has invented that, wrote the book on it, literally, is training others, has partnerships to help train others with their SREs and the CRE program. So much of the people formerly known as sysadmins, in this new cloud world, some of them are architects, but some of them will end up being operators and SREs. How do you see the balance in this upscaling of kind of the architecture and the traditional infrastructure and capacities and app dev versus operations, how important is operations in our new world? >> It's everything. And that's why I think people, you know... What's funny is that if you do this code handoff where the software developers build code and then they hand it to a team to run and deploy. Developers never become great at building systems that can be operationally managed and maintained. And so I think that was sort of the aha moment, as the best I understand the SRE model at Google is that until you can actually deliver code that can be maintained or alive, well then the software developer owns that problem. The SRE organization only comes in at that point in time where they hand up their, and they're software developers. They're every bit as skilled software developers as the engineers are that are building the code, it's just that's the problem they want to decode, which I think is actually a harder problem than writing the code. 'Cause when you think about it for a public cloud, its like, how do you actually make change, right, but keep the plane flying? And to make sure that it works with everything in an ecosystem. At a period of time where you never really had a validation stage, because in the land of delivering ISV software, you always have the six month, nine month evaluation phase to bring in a new operating system or something else, or all the ecosystem tests around that. Cloud's harder, the magic of cloud is you don't have that window, but you still have to guarantee the same results. One of the things that we did around that was we took the page out of the SRE playbook, which is how does Google do it, and what we realized is that, even though public cloud's moved the layers up, enterprises still have the same issue. Because they're deploying critical applications and workloads on top. How do they do that and how do they keep those workloads running and what are their mechanisms for managing availability, service level objectives, share a few dashboards, and that's why we created the CRE team, which is customer reliability engineering, which is a playbook of SRE, but they work directly with end users. And that's part of the how do we help them get to Google Cloud, part of it's like really understanding their application stacks and helping them build those operational procedures, so they become SREs if you will. >> Brian, one of the things I, if you look at OpenStack, it's really, it's the infrastructure layer that it handles, when I think about Google Cloud, the area that you're strongest and, you know, you're welcome to correct me, but it's really when we talk about data, how you use data, how analytics, your leadership you're taking in the machine learning space. Is it okay for OpenStack to just handle those lower levels and let other projects sit on top of it? And curious as to the developing or where Google Cloud sits. >> I think that was a lower level aha moment for me, even prior to Google, was it was, I did have a lens and it was all about infrastructure. And I think the infrastructure is every bit as important as it ever was. But the fact that some of these services that don't exist in the on-premise world that live in Google Cloud are the ones that are transformative change, as opposed to just giving you operational, easing the operational burden, easing the security burden. But it's some of these add-on services that are the ones that really changed here, bring around business transformation. The reason we have been moving away from Hadoop as an example, not entirely but just because Hadoop's a batch oriented application. >> Could go to Spark, Flink, everything beyond that. >> Sure, and also now when you get to real time and streaming image, you can have adjusted data pipelines, data come from multiple sources. But then you can action on that data instantly, and a lot of businesses require, or ours certainly does and I think a lot of our customers' businesses do, the time to action really matters, and those are the types of services that, at least at scale, don't really exist anywhere else and machine learning, the ability of our custom ASICs to support machine learning. But I don't think it's a one versus the other, I think that brings about how do you allow enterprises to have both. And not have to choose between public cloud and on premise, or doing (mumbles) services or (mumbles) services, because if you ask them, the best thing they can have is actually how do you marry the two environments together so they don't look, again, back to that impedance differences. >> Yeah, and I think that's a great point, we've talked OpenStack is fitting into that hybrid or multi-cloud world a bunch. The challenge I guess we look at is some of those really cool features that are game changers that I have in public cloud that I can't do in my own data center, how do we bridge that? Started to see the reach or the APIs that do that, but how do you see that playing out? >> Because you don't have to bring them in. Because if you think about the fabric of IT, the fabric of IT is that Google's data center in that way just becomes an extension of the data center that a large enterprise is already using anyway. So it's through us. So they aren't going to the lines of distinction, only we and sort of the IT side see that. There isn't going to be seen, as long as they have an existing platform and they can take advantage of those services, and it doesn't mean that their workload has to be portable and the services have to exist in both places, it's just a data extension with some pretty compelling services. >> I think back, you know, Hadoop was let me bring the compute to the data 'cause the data's big and can't be moved. Look at edge computing now, I'm not going to be able to move all that data from the edge, I don't have the networking connectivity. There's certain pieces which we'll come back to, you know, a core public cloud, but I wonder if you can comment on some of those edge pieces, how you see that fitting in? We've talked a little bit about it here at OpenStack, but 'cause you're Google. I think it's the evolution. When we look at, we just even see the edge of our network, the edge of our network is in, it's 173 countries and regions globally. And so that edge of the network is full compute and cashing. And so even for us, we're looking at what sort of compute services do you bring to the edge of the network. We're like, low latency really matters and proximity matters. The easiest obvious examples are gaming, but there's other ones as well, trading. But still though, if you want to take advantage of that foundation, it shouldn't be one that you have to dive into the specificities of a single provider, you'd really want that abstraction layer across the edge, whether that's Docker and a defined set of APIs around data management and delivery and security, that probably gives you that edge computing sell, and then you really want to build around that on Google's edge, you want to build around that on a telco's edge. So I don't think it really becomes necessarily around whether it's centralized or it's the edge, it's really what's that architecture to deliver. >> All right. Brian, I want to give you the opportunity, final world, things either from OpenStack, retrospectively or Google looking forward that you'd like to leave our audience with. >> Wow, closing remarks. You know, I think the continuity here is open source. And I know the backdrop of this is OpenStack, but it's really around open source is the accepted foundation and substrate for IT computing up the stack, so I think that's not changing, the faces may change and what we call these projects may change, but that's the evolution and I think there's really no turning back on that now. >> Brian Stevens, always a pleasure to catch up with you, we'll be back with lots more coverage here with theCUBE, thanks for watching. (energetic music)

>> From the SiliconANGLE Media Office in Boston, Massachusetts, it's theCube. (techno music) Now here's your host, Dave Vellante. >> Hi everybody, this is Dave Vellante and welcome to this special Cube Insights, powered by ETR. We've been running these Breaking Analysis Segments and today we're going to talk about some spending data that shows that there's continued interest in hyperconverged infrastructure. So we've been running these segments over the last several weeks with our partner ETR. They've got a database of about 4,500 IT Practitioners and CIOs. They go out quarterly and ask spending intentions. So we've been sharing that, along with our opinions. These are completely independent segments. I want to disclose that a number of the companies that we're talking about today: Nutanix, VMware, Dell EMC, Cisco, HPE. They sponsor theCube, but they have absolutely no input into editorial. They don't affect our opinion in any way, shape or form. So let's get into it. I'm here with Stu Miniman. Stu is an expert in this field. He's covered the space. Stu, let's look at some of the fundamentals. What do people need to know... Alex, if ya put up the slide, Stu, maybe you could talk to it. >> Yeah. Dave, thanks. I've been watching you have some fun with this. I enjoyed swimming in some of the data here and as you know, Dave, we've been watching since before hyperconverged infrastructure, or HCI, was a term that everybody talked about. We've been looking at how these hyperscale trends are going to impact the Enterprise. We put out our server SAN research years and years ago, so we know all these companies really well. And despite the latest AI and cloud and everything, the data shows, HCI, the simplification of the data center, building out what we would call True Private Cloud is important today. So right, we wanted to know when you look at the data, first of all, how are the vendors doing? Who are the leaders in this space here? There were a whole number of startups that came in this space. When we first analyzed the market it was companies like Microsoft and VMware that owned the operating system we thought would be hugely important. If you look in the big names this environment: Dell partnered with everyone, of course they bought Dell, bought EMC, which included a stake in VMware. What's that relationship with Nutanix? How is that shaping the market? As well as how is cloud impacting things? Both from a spending standpoint, has cloud sucked away revenue from HCI as that specter has overhung everybody in the IT space? And also, how does HCI fit into multicloud and how does that fit? >> Okay, great. So thanks for that setup, Stu, now let's get into some of the data. Alex, if you bring up the slide, the next slide. This is spending intentions for Nutanix, VMware and some other vendors. I'll go through that. But it's basically showing Nutanix and VMware are fighting it out. You know they're in this internecine battle and in social, and (chuckles) there's a war goin' on, because there's big money to be made here. So for those of you who are familiar with these segments, this is data from Enterprise Technology Research, from their July 2019 Spending Intentions Survey. So they're asking about spending intentions for the second half of 2019. The end of the survey, out of the 4,500 people in the panel, 1,068 responded to this survey. So on the left hand side you see the vendors: Nutanix, VMware with vSAN, Dell EMC with VxRail, specifically. Then SimpliVity, and then Springpath, or Cisco. So what the chart shows is what we call, Net Score. And net score is calculated by taking the red, on the bar, which is, we're going to leave the platform, that's the dark red. The lighter red, which is, we're going to spend less in the second half. The gray, which their spending's going to be flat. The dark green, or the evergreen, which says, we're going to increase spending. And the lime green, which I'm going to add to the platform. You take the green, minus the red, you get net score. Higher the net score, the better. You can see, Nutanix and VMware with vSAN are leading the pack. And then we'll go through that. But then you see, Shared Accounts. That's the number of indications for spending that they received out of those 1068. So Stu, what is this data telling you? >> So first of all, Dave, it confirmed kind of the general market share numbers that we hear out there. The vendors that track that on quarterly. VMware has the most customers, has the largest revenue, and their largest partner for that, of course, is Dell. VMware and Dell go to market, joint product development, joint engineering, joint go to market and it's the biggest piece of vSAN, so that's where we specifically wanted to look at the VxRail. And vSAN and VxRail, doing very well. They're adding new customers; was interesting to me that you saw VxRail kind of ramping up a little more on the, attracting new companies, but also looked to be losing some on the tail end of the dark red. As opposed to vSAN in general, is a little bit more stable. We know how many thousands of customers they have out there, and Vmware's a software story as opposed to VxRail is that full appliance. Nutanix is the second horse in this two-horse race that we're really talking about here, from HCI. There's some discussion in the marketplace after two quarters being down, is Nutanix showing weakness? What's happening there? The most recent quarter announcement was that Nutanix is doing well, seems to... They had a little bit of change as they're going through their move to a software model and sorting things out with sales and marketing in their channel. The data here shows that the second half of the year looks good for Nutanix. So to some of the questions I asked in the first slide, Dave, Nutanix and VMware, of course the clear leaders in this space. SimpliVity, which was of course bought be HP, Springpath which is the hyperflex from Cisco, are far behind those two out there. And it seems that even though Dell and VMware are fighting, very much with Nutanix, that is not heavily dampening Nutanix's from the respondents in this survey. >> Okay, and just a word on the data, so you see 184 shared accounts for Nutanix, 174 for VMware and down the line. Only 42 for SimpliVity and only 18 for Springpath, and Cisco. It's an indication of the size of the install base, obviously the more shared accounts, the more mentions, the larger the install base. Again, they're statistically significant; ETR does a very good job of that. Let's look Stu, at... Oh, actually I want to make another point here. So how are these net scores? Well let's put 'em in context. The hottest net scores we've seen recently are: Snowflake, and UiPath, with 80% plus, net score. Okay, so that's really, they're off the charts, they're growing like crazy. We saw Salesforce with 55%, so, and Workday sort of in there as well. Companies that are growing share. So SAP in the 30% range, and so you see the Dell EMC, VxRail, that's kind of holding serve. It's not like, dramatically gaining share, but they're growing a little bit and then-- >> And I think it's a lot, Dave, it shows to the maturity of this market. HCI is not new, both Nutanix and VMware have thousands of customers, specifically with V's then we're talking VMware. So it was more, when I saw some of your charts, Microsoft has a similar net score. >> Right >> Well liked, good install based, still growing and the like. And brings in the discussion of when we did some cross section of the analysis looking at cloud companies and how does this impact their public cloud spend; is this detracting if this customer's also doing public cloud? And the long and the short of it is VMware and Nutanix are pretty much the same if not actually a little bit better when you talk about a customer that's looking at their overall cloud spend. So to me that really signals that both VMware and Nutanix are doing a good job into how their solution fits into the customer's overall hybrid cloud strategy. >> All right, let's take a look at the next slide, which talks to time series. So this is hyperconverged infrastructure spending intentions again, for the second half of 2019, over time. So the July '19 Survey you can see is the most recent one. We go all the way back to January '17 and you can see Nutanix on the top, VMware or vSAN on the bottom. We just selected those two. We're just repeating the net score and the shared accounts. And you can see these things tend to bounce around a little bit. You can see Nutanix maintains a lead, but the market's startin' to converge. These two companies are coming together. We hear a lot about vSAN doing very well, it's kind of held on. You can see a slight downward pressure in July, in the July survey. It's unclear what that means. That could be an indication of just some uncertainty in the marketplace. Some economic macro concerns. Tariffs, potential headwinds there, so there could be some uncertainty there. But what do you takeaway from this slide, Stu? >> Yeah, first of all right. As you show, Dave, VMware is a bit more steady, Nutanix gone up for bit and come down. Both of them stayed relatively stable. Somewhere between kind of the 45 and 55 lately. A little bit, if you look at the overall trend, Nutanix is down. VMware could surpass them from the net score in the future, if this trend holds. But both of them doing quite well. When you looked at all the other vendors in there, of course the scale is just showing 40-70%, if you put all the others, which are down much lower, you can see once again, that kind of the clear leadership. These two companies, just strong lead. Does not look like there any challengers in this space that are ready to be a clear number three yet, in the market. >> But Nutanix at one point had no competition. >> Yeah. >> Okay, now vSAN comes in and of course-- >> Oh no, absolutely. So no, SimpliVity and Scale Computing, and there were a whole host of startups. There's all the brand new startups in the space. Everything from little companies like Diamante, Pivot3, who was around doing this before it came. So there's always been a lot there, but Nutanix is the one that separated from the pack. The only one in this space that's gone IPO. But VMware's there, Microsoft won that, they rebranded their Azure Stack HCI for what they put in the data center last year. So expect Microsoft partnering with all of the big server manufacturers to push farther into HCI, but really has not directly impacted this market too much, just yet. >> But there's definitely been some pressure on Nutanix from an earning standpoint, the stock's been hit. You've had some executive departures. There's some rumors about acquisition with Google. Your thoughts on-- >> Yeah, definitely. So John Furrier just had Dheeraj Pandey, the CEO of Nutanix, in our Palo Alto studio, leading up to the Copenhagen show for Nutanix that I will be at. Sure. Sunil Potti who was basically the number two at Nutanix, is now working for Thomas Kurian, TK, over at Google Cloud. My indication from what I hear, he is not over there to help broker a deal. Sunil had a great run at Nutanix, there was a clean break there, but there is a mostly new executive team at Nutanix. Now a couple of years past the IPO and the team at Nutanix, they have their platform. The have a bunch of SaaS offerings that they're doing there. Do they have a relationship with Google? Absolutely! They had Diane Greene at one of their events a couple of years ago. They did joint engineering. But I actually saw that engineering effort cool off a little bit in the last year or so since the new regime came on in Google Cloud. So does Nutanix have a lot of Enterprise accounts and know how to work with the Enterprise and could that be a boon to Google? Absolutely! But the personnel of a Nutanix executive over at Google, and Brian Stevens who's the CTO of Google Cloud being on the Board of Nutanix? I do not think that that is telegraphing that an acquisition is going to happen. It could. We see lots of big acquisitions. Nine or 10 billion dollars from Nutanix could be interesting for Nutanix and help them get in a lot of places and help Google. But Dave, I goin' on record say, I don't think it's going to happen. I don't think Cisco is going to buy Nutanix. Infrastructure's not the real push for Chuck Robbins and that team. And at the Google Cloud event, Dave, that we were at, we saw Sanjay Poonen from VMware up on stage touting how deeply VMware was going to partner. So both VMware and Nutanix are partnering with all of the clouds. VMware of course has a very deep relationship with VMware. They're going deeper with Google, they are even partnering with the old enemy of Microsoft, so I would give VMware definitely has a deeper and more public relationship with all the public cloud providers but Nutanix is also partnering and expanding their portfolio to give themselves good growth beyond just the core HCI market. >> HP's another one. So Nutanix and HPE are workin' together. Kind of the enemy of my enemy is my friend. Nutanix was not at VMworld this year; they're kind of booted out. So they belly up to HP. >> Yeah, HP loves having, they have their, "As a service offerings," and Nutanix is one of those as well as Nutanix can sell the HP. So as the, right, the Dell relationship is likely going to die down over time, as Michael Dell on the team, want to sell more Dell hardware with VMware software. HPE is another... And they also partner with Lenovo on the Nutanix side. >> All right, Stu, bring it home. What are the key takeaways on this cube Insights. >> Okay, so HCI, who is a two-horse race right now. There are interesting companies to look at beyond the two, but if you want to understand who the leaders are in the space it is: VMware, especially with their VxRail and Nutanix, are the two leaders in that space. Really looking and understanding how they're expanding into multicloud and hybrid cloud solutions. VMware very much with their VCF offering, which packages vSAN to go into the VMware cloud offerings. And Nutanix with an interesting strategy, both with how they really spread some of their services like what they're doing with Xi Cloud, as well as some SaaS offerings, which some of them really have a disconnect. Not in a bad way, but just are not tied directly to the hardware. What the infrastructure companies have tried to do for years. Both of them, VMware's done tons of acquisitions. Nutanix has done quite a few acquisitions too. >> So your second point here, what's the impact of Dell VMware versus the Nutanix battle? You say not a significant impact on spending intentions yet. I mean there's clearly some evidence that those two markets are comin' together, that VMware's pressuring Nutanix. But why do you say, yet? What do you expect? I mean is it the OEM deal with Dell? >> It's the OAM relationship. There is huge pipeline of Dell hardware with Nutanix software and they're at loggerheads. So absolutely, the Dell family: Dell, EMC and VMware are doing all they can to dial that down. So they put pressure on the channel. And even some of the most loyal Nutanix channel partners that work with Dell, have had pressure to do more and more VxRail. So I expect it to have impact, but just as, Dave, I'll dial back the clock. You probably remember when EMC had a relationship with HP and HP killed the OEM of EMC storage. EMC stormed back and got a lot of those accounts. Same thing happened when EMC and Dell broke up a couple of years before the acquisition. So Nutanix is storming to go with HPE as one of their server partners, and (mumbles). So can Nutanix keep their growth and momentum going as Dell is no longer their biggest partner? >> Well, they're fighting a two-front war. They've got one with Dell VMware and they're also fighting the war with the public cloud guys, even though they're partnering with the public cloud guys. All right, they're sort of taking that cloud model but of course it's on prim. So you say how this public cloud affects HCI spending; not a significant impact on spending intentions yet. Can I infer from that that you do expect there to be pressure on that second front? >> Yeah, so as I've talked about before Dave, when we look at VMware and VMware gives the VMware cloud in AWS. Some say, "Great, that gives me a nice path to be able to use public cloud. But maybe I don't need some of this VMware licensing and software in there." The question for Nutanix is very similar. What services do they have? How do they become more sticky in customer environments? And absolutely, they're driving a roadmap for that in working with their customers. >> Well the thing about Nutanix is that customer's really happy. The customer's really like Nutanix. They like the simplicity. I've talked to a number of Nutanix customers that are very happy in that regard. And they have a leading product in that regard. But they're aiming at the multicloud space and can they play there? >> And Dave, you make a really good point. The killer use case, what did HCI deliver? It delivered simplicity. Today, if you talk about public cloud in general or even hybrid or multicloud, (chuckles) simplicity is not how you would describe this. So can the customers, the companies that did HCI, so, VMware, Nutanix, HPE and Cisco, they're all fighting for that hybrid and multicloud environment. And if they can help deliver simplicity of management, simplicity of leveraging my data, they can be successful in that space. >> Okay, so you're sort of positive on the multicloud, their position in multicloud. Even though they're not one of the big five. >> Yeah, and the good news for a Nutanix is that they're growing off of a much smaller base then say VMware, when you say they have five or 600,000 customers. Hey, how big of an impact will public cloud have on them? >> All right, so we don't pick stocks. We're not making recommendations. (laughs) But, do you feel like it's overdone, that it's undervalued? Independent of the macro. Do you feel like the pressure on Nutanix is warranted, or do you feel like it's got legs? >> So I feel Wall Street tends to over adjust when they go through things. When I talk to my friends on the Wall Street stuff. Definitely Nutanix took more of a beating probably then they should have. But they had two quarters that weren't great. And some of that was the management changes, they blamed that they couldn't hire sales and marketing fast enough. Something we'd asked, if you're a company in the Valley and you've gone from a few hundred people to a few thousand people. How do you keep adding good quality people? That's challenging. So yes, I think we've actually seen Dave, in the last week, or so Nutanix has been one of the fastest growing stocks in the tech market. So they're adjusting some. So I still think Nutanix has plenty of room for growth. The question is, what's their path to say, two billion dollars? Or is it an exit for 9-10 billion dollars down the road? >> All right, Stu, some great stuff. Thank you for that analysis. And thank you for watching this episode of theCube Insights, powered by ETR. This is Dave Vellante, for Stu Miniman, we'll see ya next time. (techno music)

>> Narrator: Live, from New Orleans, Louisiana, it's theCube, covering .NEXT conference 2018. Brought to you by Nutanix. >> It's not the critic who counts. Not the man who points out how the strong man stumbles. Or where the doer of deeds, could have done them better. The credit belongs to the man who is actually in the arena. Whose face is marked by dust, and sweat and blood. Who strives valiantly, who errors, who comes short again and again, because there is no effort without error in shortcoming. But who does actually strive to do the deeds? Who knows great enthusiasms, the great devotions, who spends himself in a worthy cause. Who, at the best, knows in the end of the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly. So that his place shall never be with those cold and timid souls who neither know victory nor defeat. Those words by Theodore Roosevelt were in this morning's keynote by Dr. Brene Brown. Welcome to theCube's coverage of Nutanix.NEXT 2018. I'm Stu Miniman, with Keith Townsend here to break down, give our critiques as well as understand that Nutanix, while they are a public company, been striving and succeeding greatly. 5500 people here at this conference, very enthusiastic, great party last night, so Keith, we talked about it, our show opened yesterday, been your first show, got to talk to a bunch of customers, talked to a bunch of partners. Give us impressions and overall experience. >> So you know, you can't go to a show like this and not get hero numbers. 70,000 people in the Nutanix community program. 61,000 certified individuals. Customers making statements such as, Nutanix, humble company, Nutanix, not feeling entitled to the sale. Needing to work for the dollar. Customers extremely excited about the announcements, the direction of the company for key core areas I saw from a technology perspective, in which they made some really aggressive announcements and bets. So you know what, this has been a very high energy conference. >> Yeah, absolutely, talk about, from a financial standpoint, they're doin' well. Wall Street's been rewarding them greatly for the move to move to software only. Company's over nine billion dollars in market cap. Amazing. Had to go for a thousand customers a quarter. Very good for the space that they're playing in. Things like their file system, AFS, their fastest growing products. Building on that base infrastructure, but then yes, as you said, bold direction, they've got the kind of three axises that they're trying to build on. Build out HyperVage's support, build out cloud support. They're going to talk about how we think, where Nutanix fits in this cloud world. Building out their software portfolio. Where do they have IP, where are they growing? They've done four acquisitions so far in the software space. Some of those are starting to show through. We did interviews with the former CEO of Minjar and it NetSill, and- >> Bot Metric. >> Yeah, yeah that's the Netsill Bot Metric piece there. So products that are now, some of them are shipping. And as well as getting some vision. They had their first SAS product in Beam. Really interesting, something that really was targeted at AWS and Azure. Not the data center, but they're trying to make that hybrid-hybrid message as well as giving some of the vision. Nutanix Era is a big directional piece. Project Sherlock. Of course the big brains here working on that. Really interested in Edge and IOT. So a lot of pieces there, what's your take? >> You know what? I think I'm a bit overwhelmed actually. Which is a great thing, you look at COM was over the past couple of months, their Com platform was evened out by adding micro-segmentation. Which, against their biggest competitor VMware was a essential piece. They've been unabashful with going after it. You know what, AHV can now compete head-to-head with VMware just as long as you don't need memory over commit, and metro clustering that AHV, the term that they use in "game on." So Nutanix is, you know we talked to Duraj, a couple of years on theCube, asked him, you know what, is Nutanix a platform company? He say, you know what, no, (mumbles) too humble to accept that mantle of being a platform company, there's a lot of work to do. You look out onto the show floor, 80 partners and sponsors, who are all offering solutions tied to AHV. Which we talked about a little bit. A lot of adoption, but it doesn't seem like there's much VMware. Market penetration and stealing customers from VMware as much as HyperV. There're a lot of customers we talked to we said, you know we tried HyperV on Nutanix, not so much so we went to AHV. >> Quick point, and I felt a few years ago, the conversation wasn't about HyperV when you talked about Microsoft. It wasn't the, for years it was, when will it catch up to what VMware's doing? VMware's still dominant in the space, customers here, and lots of 'em are usin' Vmware. Yes, there's that tension between Vmware and Nutanix, but Nutanix, do they poke and prod a little bit at some things? Yes, but at the show, very much focusing on what they're doing, and focusing on their customers, not sending pot shots or anything like that. But when it comes to Microsoft, you're right Keith, there were a number of customers I talked to that were like, well in a Microsoft shop, and we know what applications used to live on VMware. Number one thing was always Microsoft. Many of them, I tried HyperV, didn't really like the experience. And therefore it was a smooth path to go over to AHV. Lot's of customers that are doing both VMware and AHV and sorting that out. And it's like oh, well over time, if Nutanix becomes 80, 90, even some of them gettin' towards 100% of heir deployment, AHV becomes a bigger piece of the portfolio. >> And you know, we thought that this whole multi-HyperVisor argument was over. Like, you know what, just go to one HyperVisor. A lot of Nutanix customers are showing that multi-HyperVisor is a legit way to go that we haven't ran with anyone who said, No, we're having management pains, running AHV side-by-side with VM or Vspare. >> I would like to see from Nutanix, more partnerships with Microsoft though. You talk Azure, absolutely huge growth, number two out there. Yes, they support it, but you know, of course they have much more showing at the Amazon show. They've got a strong partnership with Google. Got to highlight that with the Brian Stevens interview. And know that later this year, as Zai really starts to roll out, that we will see much more of that. But Azure, not only in the public cloud piece, but Azure's stack is starting to grow. I've been talking to Lenovo, HP, Adele, Cisco, all of them have pent-up demands, service writers that are starting to roll at Azure's stack. And while Azure's stack really is kind of a closed ecosystem there, I think there is opportunity for Nutanix to play in there, I expect them to hear from the customers who'd love them to do more with Microsoft. We heard from customers that they'd actually love to hear Nutanix do more with Redhat, and in general be a deletega system, yes, show floor, it's growing, it's vibrant but absolutely, it's always, what more? >> OF course, we always, and I think we get our friends at Nutanix always pokes us about staying positive. But it is a positive, they're a software company now. And as a software company, you have to integrate with other software company services. The Azure stack thing, while it's mainly a hardware play for companies like Dale, Lenovo, Fujitsu, there has to be software integration. The folks with the Google and Nutanix partnership, did a really great job of doing push-button, at least showin' us on stage, push-button deployments of VM's, from Zai to Nutanix instances in the cloud. This is Nutanix in the cloud. That won't probably play with Azure and Azure Stack. So Nutanix really needs to figure out a way to get into that relationship with Microsoft. >> Yeah, true simplicity takes genius, is a quote that I had out of this show in the early years. And Nutanix will make a bold claim. Oh, database migration, we're going to make that really easy. Well, show me (laughs) Anybody that's worked with databases- >> That's like sayin' DR is easy. Yeah, gettin' the stores from one point to another one is easy. Processes, not so much. >> Some of that Project Sherlock, oh yeah all that tensor flow, cumbrineties, functions of the service, we're going to make it push-button easy so that we'll make that invisible. How much is a distraction, what's in the weeds? You know, the networking, there's so many pieces in there that love the vision. Of course customers want it simplified, but we want to talk to the customers, and understand what works, what still needs to be tweaked, where do they have to build out some services, partnerships, even more than they've done today to go further, what have you been seeing and hearing? >> So, Nutanix, the enterprise cloud company. I've poked at the whole cloud marketing term. Matter of fact, on Twitter, one of the, I'll read this. Cloud really, no AI, no databases or severs. No server-less, does that even, doesn't even have a presence at Cubrineties events. Fake cloud story for IT, ah! So you know what, let's pick that apart a little bit. DV as a service, they announced basically yesterday, that's there. AI, Satium Gatupum said a really nice story with Sherlock there, absolutely looking at it. Cubrineties integration, ACS, 2.0 will come out the gate as a Cubrineties manage distribution. They announced Zai integration with Cubrineties and push-button. Now you may pick on the cloud part. Nutanix still very much talks to the infrastructure group. Their customers are the infrastructure group, and you can't talk cloud without having a relationship with application developers. So I think the next step as Nutanix matures, these offerings on, their cloud offerings, is that they have to start to have a deeper relationship. They have to go side-by-side with their IT sponsors and organizations to start to have conversations with application developers. >> Yeah, and I love the online, the cloud-eraderie if you will, out there. Well, we understand, this is the architecture of the future. Where it should go, I love hangin' out with the cloud native crew. But for me, it goes back to talking to their customers. And when the customers, if they're like here's what we've done, here's the proof as to how I get faster time to market, how I'm accelerating my development teams insight. I'm creating, one of the interviews we did, IT as business, is how we run things. These are real digital transformation stories. Impressive stuff, and it's cloud. And it's not virtualization with a little layer on top. It's real change inside customers, and Nutanix, I'll say, as a platform to help us get from where I've been, to where I'm going. >> Yeah, absolutely. Obviously, Nutanix customers are not listening to the cloud-eraderie. They absolutely love the platform. You know Stu, I don't think I've run into a negative customer at the show. I haven't run into a customer that says, you know what, Nutanix isn't meeting my need in X or Y area. Home Depot won the innovation award at the show. Then Home Depot is a forward thinking customer, truly embracing parts of the platform. I'm sure there's some cloud native pieces. >> They're a big Google cloud platform customer. One of Pivotal's big one on GCP. So absolutely, and we have, I've talked to a number of customers big on Amazon, developer shops, absolutely public cloud to piece of it. Yeah, if the criticism I should have, I always look and say, if I said public cloud and private cloud, where's your center of gravity? Of course Nutanix is going to go, leaning a little bit more towards the data centers, hosted service providers. That's where they live today. But they're not blind to it, they're embracing it. They have a full SAS product, they're going to be expanding that. They are software at their core, distributed architectures where they're going. >> You know Stu, one of our favorite comments is that, company X likes to move, moves at the pace of the CIO. I think it's safe to say, Nutanix is a little bit faster than the CIO. And they're enabling the old stuff. You know what, let's make that push-button easy, and as we're looking, have a eye to the future, looking at the new stuff, let's see how we can get there, push-button easy. There's a lot of work to do. But I think they're making some really interesting and probably the right moves for their customer base. >> Aright well, Keith, first of all, I want to thank you for all of your help here this week. The CTO advisor, always great to dig in with customers. Really get in, it's been exciting to watch you kind of get to know a little bit more about this. I've had the pleasure of tracking Nutanix in the really early days, been at every one of these shows. It is a great community, kudos to Nutanix. Thank you for sponsoring us, and if not familiar, if you look at the bottom of the videos we're playin' right now, we mention who sponsors, we're tryin' to be transparent. Keith and I though, we're out here in the field. If you have questions for us, or you know, want us to ask something, or question what we're doing, hit us up, we're really easy to reach on Twitter. Always happy for feedback from the community. And as always, check out thecube.net for all the upcoming shows, everywhere we're going. For Keith Townsend, I'm Stu Miniman, thank you so much for watchin' theCube's presentation from Nutanix.NEXT 2018 in New Orleans, and see you at lots more shows. (futuristic music)

[Music] and y'all know that these [Music] ladies and gentlemen please take your seats and silence your cellphone's our program will begin shortly ladies and gentlemen please welcome Red Hat executive vice president and chief people officer dallisa Alexander an executive vice president and chief marketing officer Tim Layton [Music] hi everyone we're so excited to kick off this afternoon day 2 at the Red Hat summit we've got a stage full of stories about people making amazing contributions with open source well you know dallisa you and I both been coming to this event for a long long time so what keeps you coming back well you know the summit started as a tech conference an amazing tech conference but now it's expanded to be so much more this year I'm really thrilled that we're able to showcase the power of open source going way beyond the data center and beyond the cloud and I'm here also on a secret mission oh yes I'm here to make sure you don't make too many bad dad jokes so there's no such thing as a bad dad they're just dad jokes are supposed to be bad but I promise to keep it to my limit but I do have one okay I may appeal to the geeks in the audience okay so what do you call a serving tray full of empty beer cans yeah we container platform well that is your one just the one that's what I only got a budget of one all right well you know I have to say though in all seriousness I'm with you yeah I've been coming to the summit since its first one and I always love to hear what new directions people are scoring what ideas they're pursuing and the perspectives they bring and this afternoon for example you're gonna hear a host of different perspectives from a lot of voices you wouldn't often see on a technology mainstage in our industry and it's all part of our open source series live and I have to say there's been a lot of good buzz about this session all week and I'm truly honored and inspired to be able to introduce them all later this afternoon I can tell you over the course the last few weeks I've spent time with all of them and every single one of them is brilliant they're an innovator they're fearless and they will restore your faith in the next generation you know I can't wait to see all these stories all of that and we've got some special guests that are surprised in store for us you know one of the things that I love about the people that are coming on the stage today with us is that so many of them teach others how to code and they're also bringing more people that are very different in to our open-source communities helping our community is more innovative and impactful and speaking of innovative and impactful that's the purpose of our open brand project right that's right we're actually in the process of exploring a refresh of our mark and we'd really like your help as well because we're doing this all in the open we've we've been doing it already in the open and so please join us in our feedback zone booth at the summit to tell us what you think now it's probably obvious but I'm big into Red Hat swag I've got the shirt I've got my pen I've got the socks so this is really important to me personally especially that when my 15 year old daughter sees me in my full regalia she calls me adorable okay that joke was fed horrible as you're done it wasn't it wasn't like I got way more well Tim thanks for helping us at this stage for today it's time to get started with our first guest all right I'll be back soon thank you the people I'm about to bring on the stage are making outstanding contributions to open source in new and brave ways they are the winners of the 2018 women and open source Awards the women in open source awards was created to highlight the contributions that women are making to open source and to inspire new generations to join the movement our judges narrowed down the panel a very long list just ten finalists and then the community selected our two winners that were honoring today let's learn a little bit more about them [Music] a lot of people assume because of my work that I must be a programmer engineer when in fact I specifically chose and communications paths for my career but what's fascinating to me is I was able to combine my love of Communications and helping people with technology and interesting ways I'm able to not be bound by the assumptions that everybody has about what the technology can and should be doing and can really ask the question of what if it could be different I always knew I wanted to be in healthcare just because I feel like has the most impact in helping people a lot of what I've been working on is geared towards developing technology and the health space towards developing world one of the coolest things about open-source is bringing people together working with other people to accomplish amazing things there's so many different projects that you could get involved in you don't even have to be the smartest person to be able to make impact when you're actually developing for someone I think it's really important to understand the need when you're pushing innovation forward sometimes the cooler thing is not [Music] for both of us to have kind of a health care focus I think it's cool because so many people don't think about health care as being something that open-source can contribute to it took a while for it to even get to the stage where it is now where people can open-source develop on concepts and health and it's an untapped potential to moving the world for this award is really about highlighting the work of dozens of women and men in this open source community that have made this project possible so I'm excited for more people to kind of turn their open-source interest in healthcare exciting here is just so much [Music] I am so honored to be able to welcome to the stage some brilliant women and opensource first one of our esteemed judges Denise Dumas VP of software engineering at Red Hat she's going to come up and share her insights on the judging process Denise so you've been judging since the very beginning 2015 what does this judge this being a judge represents you what does the award mean to you you know every year it becomes more and more challenging to select the women an opensource winner because every year we get more nominees and the quality of the submissions well there are women involved in so many fabulous projects so the things that I look for are the things that I value an open source initiative using technology to solve real world problems a work ethic that includes sin patches and altruism and I think that you'll see that this year's nominees this year's winners really epitomize those qualities totally agree shall we bring them on let's bring them on let's welcome to the stage Zoe de gay and Dana Lewis [Music] [Applause] [Applause] [Music] alright let's take a seat [Applause] well you both have had an interesting path to open-source zuy you're a biomedical engineering student any of it you have a degree in public relations tell us what led to your involvement and open source yeah so coming to college I was new I was interested in science but I didn't want to be a medical doctor and I didn't want to get involved in wet lab research so through classes I was taking oh that's why I did biomedical engineering and through classes I was taking I found the classroom to be very dry and I didn't know how how can I apply what I'm learning and so I got involved in a lot of entrepreneurship on campus and through one of the projects I was asked to build a front end and I had no idea how to go about doing that and I had some basic rudimentary coding knowledge and what happened was I got and was digging deep and then found an open source library that was basically building a similar thing that I needed and that was where I learned about open source and I went from there now I'm really excited to be able to contribute to many communities and work on a variety of projects amazing contributions Dana tell us about your journey well I come from a non-traditional background but I was diagnosed with type 1 diabetes at the age of 14 and over the next couple years got really frustrated with the limitations of my own diabetes devices but felt like I couldn't change them because that wasn't my job as a patient but it was actually through social media I discovered someone who had solved one of the problems that I had been found having which was getting date off my diabetes device and that's how I learned about open source was when he was willing to share his code with me so when we turned around and made this hybrid closed-loop artificial pancreas system it was a no brainer to make our work open source as well that's right absolutely and we see using the hash tag we are not waiting can you tell us about that yeah so this hash tag was created actually before I even discovered the open source diabetes world but I loved it because it really illustrates exactly the fact that we have this amazing technology in our hands in our pockets and we can solve some of our most common problems so yes you could wait but waiting is now a choice with open source we have the ability to solve some of our hardest problems even problems dealing with life and death that's great so zuy with the vaccine carrier system that you helped to build how were you able to identify the need and where did you build it yes so I think before you even build anything first need to understand what is the problem that you're trying to solve and that really was the case when starting this project I got to collaborate with engineers in Kampala Uganda and travel there and actually interview stakeholders in the medical field medical doctors as well as pharmaceutical companies and from there I really got to understand the health system there as well as what is how do vaccines enter the country and how can we solve this problem and that's how we came up with the solution for an IOT based vaccine carrier tracking system I think it's really important especially today when products might be flashy to also understand what is the need behind it and how do we solve problems with these products yeah yeah it's so interesting how both of you have this interest in health care Dana how do you see open-source playing a role in healthcare but first before you answer that tell us about your shirt so this shirt has the code of my artificial pancreas on it and I love it as an illustration of no thank you I love it as an illustration of how open-source is more than we think it is I've just been blown away by the contributions of people in my open-source communities and I think that that is what we should apply to all of healthcare there's a lot of tools and technologies that are solving real world problems and I think if we take what we know in technology and apply it to healthcare we'll solve a lot of problems more quickly but it really needs to be recognizing everything an open source it's the documentation it's the collaboration it's the problem-solving it's working together to take technologies that we didn't previously think we're applicable and finding new ways to apply it it's a great answer Sooey yeah I think especially where healthcare is related to people and open-source is the right way to collaborate with people all over the world especially in the project I've been working on we're looking at vaccines in Uganda but the same system can be applied in any other country and then you can look at cross countries health systems there and from there it becomes bigger and bigger and I think it's really important for people who have an idea and want to take it further to know that open-source is a way that you could actually take your idea further whether you have a technical background or not so yeah stories are amazing you're just an inspiration for everyone in open-source I want to thank you so much for joining us here today let's give another round of applause to our winners [Applause] [Music] you know the tagline for the award is honor celebrate inspire and I feel like we've been doing that today very very well and I know that so many people have been inspired today especially the next generation who go on to do things we can't even dream of yet [Music] I think collabs important because we need to make sure we get younger children interested in technology so that they understand the value of it but also that there are a lot of powerful women in technology and they can be one of them I hope after this experience maybe we'll get some engineers and some girls working our hot so cool right well we have some special guests convite for the club stage now I'd like to invite Tim back and also introduce Red Hat's own Jamie Chappell along with our collab students please welcome Gabby tenzen Sofia lyric Camila and a Volyn [Applause] you've been waiting for this moment for a while we're so excited hear all about your experiences but Jamie first tell us about collab sure so collab is red hats way of teaching students about the power of open source and collaboration we kicked off a little over a year ago in Boston and that was so successful that we decided to embark on an East Coast tour so in October we made stops at middle schools in New York DC and Raleigh and these amazing people over here are from that tour and this week they have gone from student to teacher so they've hosted two workshops where they have taught Red Hat summit attendees how to turn raspberry pies into digital cameras they assigned a poem song of the open road by Walt Whitman and they've been working at the open source stories booth helping to curate photos for an installation we're excited to finish up tomorrow so amazing and welcome future women in open source we want to know all about your experiences getting involved can you tell us tenzen tell us about something you've learned so during my experience with collab I learned many things but though however the ones that I valued the most were open source and women empowerment I just I was just so fascinated about how woman were creating and inventing things for the development of Technology which was really cool and I also learned about how open source OH was free and how anyone could access it and so I also learned that many people could you know add information to it so that other people could you learn from it and use it as well and during Monday's dinner I got this card saying that the world needed more people like you and I realized through my experience with collab that the world does not only need people like me but also everyone else to create great technology so ladies you know as you were working on your cameras and the coding was there a moment in time that you had an AHA experience and I'm really getting this and I can do this yes there was an aha moment because midway through I kind of figured out well this piece of the camera went this way and this piece of the camera did it go that way and I also figured out different features that were on the camera during the camera build I had to aha moments while I was making my camera the first one was during the process of making my camera where I realized I was doing something wrong and I had to collaborate with my peers in order to troubleshoot and we realize I was doing something wrong multiple times and I had to redo it and redo it but finally I felt accomplished because I finished something I worked hard on and my second aha moment was after I finished building my camera I just stared at it and I was in shock because I built something great and it was so such a nice feeling so we talked a lot about collaboration when we were at the lab tell us about how learning about collaboration in the lab is different than in school so in school collaboration is usually few and far between so when we went to collab it allowed us to develop new skills of creativity and joining our ideas with others to make something bigger and better and also allowed us to practice lots of cooperation an example of this is in my group everybody had a different problem with their pie camera and we had to use our different strengths to like help each other out and everybody ended up assembling and working PI camera great great awesome collaboration in collab and the school is very different because in collab we were more interactive more hands-on and we had to work closer together to achieve our own goals and collaboration isn't just about working together but also combining different ideas from different people to get a product that is so much better than some of its parts so girls one other interesting observation this actually may be for the benefit of the folks in our audience but out here we have represented literally hundreds and hundreds of companies all of whom are going to be actually looking for you to come to work for them after today we get first dibs that's right but um you know if you were to have a chance to speak to these companies and say what is it that they could do to help inspire you know your your friends and peers and get them excited about open source what would you say to them well I'm pretty sure we all have app store and I'm pretty sure we've all downloaded an app on that App Store well instead of us downloading app State well the computer companies or the phone companies they could give us the opportunity to program our own app and we could put it on the App Store great idea absolutely I've got to tell you I have a 15 year old daughter and I think you're all going to be an inspiration to her for the same absolutely so much so I see you brought some cameras why don't we go down and take a picture let's do it [Applause] all right I will play my very proud collab moderator role all right so one two three collab okay one two three [Applause] yeah so we're gonna let leave you and let you tell us more open source stories all right well thank you great job thank you all and enjoy the rest of your time at Summit so appreciate it thanks thank you everyone pretty awesome pretty awesome and I would just like to say they truly are fedorable that's just um so if you would like to learn more as you heard the girls say they're actually Manning our open-source stories booth at the summit you know please come down and say hello the stories you've seen thus far from our women and open-source winners as well as our co-op students are really bringing to life the theme of this year's summit the theme of ideas worth exploring and in that spirit what we'd like to do is explore another one today and that is how open-source concepts thrive and expand in the neverending organic way that they do much like the universe metaphor that you see us using here it's expanding in new perspectives and new ideas with voices beyond their traditional all starting to make open-source much bigger than what it was originally started as fact open-source goes back a long way long before actually the term existed in those early days you know in the early 80s and the like most open-source projects were sort of loosely organized collections of self-interested developers who are really trying to build low-cost more accessible replicas of commercial software yet here we are 2018 the world is completely different the open-source collaborative development model is the font of almost all original new innovation in software and they're driven from communities communities of innovation RedHat of course has been very fortunate to have been able to build an extraordinary company you know whose development model is harnessing these open-source innovations and in turning them into technologies consumable by companies even for their most mission-critical applications the theme for today though is we see open-source this open source style collaboration and innovation moving beyond just software this collaborative community innovation is starting to impact many facets of society and you're starting to see that even with the talks we've had already too and this explosion of community driven innovation you know is again akin to this universe metaphor it expands in all directions in a very organic way so for red hat you know being both beneficiaries of this approach and stewards of the open collaboration model we see it important for us to give voice to this broader view of open source stories now when we say open source in this context of course will meaning much more than just technology it's the style of collaboration the style of interaction it's the application of open source style methods to the innovation process it's all about accelerating innovation and expanding knowledge and this can be applied to a whole range of human endeavors of course in education as we just saw today on stage in agriculture in AI as the open source stories we shared at last year's summit in emerging industries like healthcare as we just saw in manufacturing even the arts all these are areas that are now starting to benefit from collaboration in driving innovation but do we see this potentially applying to almost any area of human endeavor and it expands again organically expanding existing communities with the addition of new voices and new participants catalyzing new communities and new innovations in new areas as we were talking about and even being applied inside organizations so that individual companies and teams can get the same collaborative innovation effects and most profound certainly in my perspective is so the limitless bounds that exist for how this open collaboration can start to impact some of humankind's most fundamental challenges we saw a couple of examples in fact with our women and open-source winners you know that's amazing but it also potentially is just the tip of the iceberg so we think it's important that these ideas you know as they continue to expand our best told through storytelling because it's a way that you can embrace them and find your own inspirations and that's fundamentally the vision behind our open-source stories and it's all about you know building on what's come before you know the term we use often is stay the shoulders are giants for a lot of the young people that you've seen on this stage and you're about to see on this stage you all are those giants you're the reason and an hour appears around the world are the reasons that open-source continues to expand for them you are those giants the other thing is we all particularly in this room those of us have been around open-source we have an open-source story of our own you know how were you introduced the power of open-source how did you engage a community who inspired you to participate those are all interesting elements of our personal open-source stories and in most cases each of them are punctuated by you here my question to the girls on stage an aha moment or aha moments you know that that moment of realization that enlightens you and causes you to think differently and to illustrate I'm going to spend just a few minutes sharing my open-source story for for one fundamental reason I've been in this industry for 38 years I am a living witness to the entire life of open-source going back to the early 80s I've been doing this in the open-source corner of the industry since the beginning if you've listened to Sirhan's command-line heroes podcasts my personal open story will actually be quite familiar with you because my arc is the same as the first several podcast as she talked about I'm sort of a walking history lesson in fact of open source I wound up at most of the defining moments that should have changed how we did this not that I was particularly part of the catalyst I was just there you know sort of like the Forrest Gump of open-source I was at all these historical things but I was never really sure how it went up there but it sure was interesting so with that as a little bit of context I'm just gonna share my aha moment how did I come to be you know a 59 year old in this industry for 38 years totally passionate about not just open source driving software innovation but what open source collaboration can do for Humanity so in my experience I had three aha moments I just like to share with you the first was in the early 80s and it was when I was introduced to the UNIX operating system and by the way if you have a ha moment in the 80s this is what it looks like so 1982 mustache 19 where were you 2018 beard that took a long time to do all right so as I said my first aha moment was about the technology itself in those early days of the 80s I became a product manager and what at the time was digital equipment corporation's workstation group and I was immediately drawn to UNIX I mean certainly these this is the early UNIX workstation so the user interface was cool but what I really loved was the ability to do interactive programming via the shell but by a--basically the command line and because it was my day job to help figure out where we took these technologies I was able to both work and learn and play all from the same platform so that alone was was really cool it was a very accessible platform the other thing that was interesting about UNIX is it was built with networking and and engagement in mind had its own networking stack built in tcp/ip of course and actually built in a set of services for those who've been around for a while think back to things like news groups and email lists those were the first enablers for cross internet collaboration and that was really the the elements that really spoke to me he said AHA to me that you know this technology is accessible and it lets people engage so that was my first aha moment my second aha moment came a little bit later at this point I was an executive actually running Digital Equipment Corporation UNIX systems division and it was at a time where the UNIX wars were raging right all these companies we all compartmentalized Trump those of the community and in the end it became an existential threat to the platform itself and we came to the point where we realized we needed to actually do something we needed to get ahead of this or UNIX would be doomed the particular way we came together was something called cozy but most importantly the the technique we learned was right under our noses and it was in the area of distributed computing distributed client-server computing inherently heterogenous and all these same companies that were fierce competitors at the operating system level were collaborating incredibly well around defining the generation of client-server and distributed computing technologies and it was all being done in open source under actually a BSD license initially and Microsoft was a participant Microsoft joined the open group which was the converged standards body that was driving this and they participated to ensure there was interoperability with Windows and and.net at the time now it's no spoiler alert that UNIX lost right we did but two really important things came out of that that sort of formed the basis of my second aha moment the first is as an industry we were learning how to collaborate right we were leveraging open source licenses we realized that you know these complex technologies are best done together and that was a huge epiphany for the industry at that time and the second of course is that event is what opened the door for Linux to actually solve that problem so my second aha was all about the open collaboration model works now at this point to be perfectly candidates late 1998 well we've been acquired by compacts when I'm doing the basically same role at Compaq and I really had embraced what the potential impact of this was going to be to the industry Linux was gaining traction there were a lot of open source projects emerging in distributed computing in other areas so it was pretty clear to me that the in business impact was going to be significant and and that register for me but there was seem to be a lot more to it that I hadn't really dropped yet and that's when I had my third aha moment and that was about the passion of open-source advocates the people so you know at this time I'm running a big UNIX group but we had a lot of those employees who were incredibly passionate about about Linux and open source they're actively participating so outside of working a lot of things and they were lobbying more and more for the leadership to embrace open source more directly and I have to say their passion was contagious and it eventually spread to me you know they were they were the catalyst for my personal passion and it also led me to rethink what it is we needed to go do and that's a passion that I carry forward to this day the one driven by the people and I'll tell you some interesting things many of those folks that were with us at Compaq at the time have gone on to be icons and leaders in open-source today and many of them actually are involved with with Red Hat so I'll give you a couple of names that some of whom you will know so John and Mad Dog Hall work for me at the time he was the person who wrote the first edition of Linux for dummies he did that on his own time when he was working for us he he coined he was part of the small team that coined the term open source' some other on that team that inspired me Brian Stevens and Tim Burke who wrote the first version to rent out Enterprise Linux actually they did that in Tim Burke's garage and cost Tim's still with Red Hat today two other people you've already seen him on stage today Denise Dumas and Marko bill Peter so it was those people that I was fortunate enough to work with early on who had passion for open-source and much like me they carry it forward to this day so the punchline there is they ultimately convinced us to you know embrace open-source aggressively in our strategy and one of the interesting things that we did as a company we made an equity investment in Red Hat pre-ipo and a little funny sidebar here I had to present this proposal to the compact board on investing in Red Hat which was at that time losing money hand over fist and they said well Tim how you think they're gonna make money selling free software and I said well you know I don't really know but their customers seem to love them and we need to do this and they approve the investment on the spot so you know how high do your faith and now here we are at a three billion dollar run rate of this company pretty extraordinary so from me the third and final ha was the passion of the people in the way it was contagious so so my journey my curiosity led me first to open source and then to Red Hat and it's been you know the devotion of my career for over the last thirty years and you know I think of myself as pretty literate when it comes to open source and software but I'd be the first one to admit I would have never envisioned the extent to which open source style collaboration is now being brought to bear on some of the most interesting challenges in society so the broader realization is that open source and open can really unlock the world's potential when applied in the collaborative innovative way so what about you you know you many of you particular those have been around for a while you probably have an open source story of your own for those that maybe don't or they're new to open source are new to Red Hat your open source story may be a single inspiration away it may happen here at the summit we certainly hope so it's how we build the summit to engage you you may actually find it on this stage when I bring up some of the people who are about to follow me but this is why we tell open-source stories and open source stories live so each of you hopefully has a chance to think about you know your story and how it relates over source so please take advantage of all the things that are here at the summit and and find your inspiration if you if you haven't already so next thing is you know in a spirit of our telling open source stories today we're introducing our new documentary film the science of collective discovery it's really about citizen scientists using open systems to do serious science in their backyards and environmental areas and the like we're going to preview that I'm gonna prove it preview it today and then please come see it tonight later on when we preview the whole video so let's take a look I may not have a technical scientific background but I have one thing that the scientists don't have which is I know my backyard so conventional science happens outside of public view so it's kind of in this black box so most are up in the ivory tower and what's exciting about citizen science is that it brings it out into the open we as an environmental community are engaging with the physical world every day and you need tools to do that we needed to democratize that technology we need to make it lightweight we need to make it low-cost we needed to make it open source so that we could put that technology in the hands of everyday people so they go out and make those measurements where they live and where they breathe when you first hear about an environmental organization you mostly hear about planting trees gardens things like that you don't really think about things that are really going to affect you hey we're the air be more they'd hold it in their hand making sure not to cover the intake or the exhaust I just stand here we look at the world with forensic eyes and then we build what you can't see so the approach that we're really centered on puts humans and real issues at the center of the work and I think that's the really at the core of what open source is social value that underlies all of it it really refers to sort of the rights and responsibilities that anyone on the planet has to participate in making new discoveries so really awesome and a great story and you know please come enjoy the full video so now let's get on with our open stories live speakers you're going to really love the rest of the afternoon we have three keynotes and a demo built in and I can tell you without exaggeration that when you see and hear from the young people we're about to bring forward you know it's truly inspirational and it's gonna restore totally your enthusiasm for the future because you're gonna see some of the future leaders so please enjoy our open source stories live presentation is coming and I'll be back to join you in a little bit thanks very much please welcome code newbie founder Saran yep Eric good afternoon how y'all doing today oh that was pretty weak I think you could do better than that how y'all doing today wonderful much better I'm Saran I am the founder of code newbie we have the most supportive community of programmers and people learning to code this is my very first Red Hat summits I'm super pumped super excited to be here today I'm gonna give you a talk and I'm going to share with you the key to coding progress yes and in order to do that I'm gonna have to tell you a story so two years ago I was sitting in my hotel room and I was preparing for a big talk the next morning and usually the night before I give a big talk I'm super nervous I'm anxious I'm nauseous I'm wondering why I keep doing this to myself all the speakers backstage know exactly what I'm what I'm talking about and the night before my mom knows this so she almost always calls just to check in to see how I'm doing to see how I'm feeling and she called about midnight the night before and she said how are you how are you doing are you ready and I said you know what this time I feel really good I feel confident I think I'm gonna do a great job and the reason was because two months ago I'd already given that talk in fact just a few days prior they had published the video of that talk on YouTube and I got some really really good positive feedback I got feedback from emails and DMS and Twitter and I said man I know people really like this it's gonna be great in fact that video was the most viewed video of that conference and I said to my office said you know what let's see how many people loved my talk and still the good news is that 14 people liked it and a lot more people didn't and I saw this 8 hours before I'm supposed to give that exact same talk and I said mom I gotta call you back do you like how I did that to hang up the phone as if that's how cellphones work yeah and so I looked at this and I said oh my goodness clearly there's a huge disconnect I thought they were really liked they were I thought they were into it and this showed me that something was wrong what do you do what do you do when you're about to give that same talk in 8 hours how do you begin finding out what the problem is so you can fix it I have an idea let's read the comments you got to believe you gotta have some optimism come on I said let's read the comments because I'm sure we'll find some helpful feedback some constructive criticism some insights to help me figure out how to make this talk great so that didn't happen but I did find some really colorful language and some very creative ideas of what I could do with myself now there are some kids in the audience so I will not grace you with these comments but there was this one comment that did a really great job of capturing the sentiment of what everyone else was saying I can only show you the first part because the rest is not very family-friendly but it reads like this how do you talk about coding and not fake societal issues see the thing about that talk is it wasn't just a code talk it was a code and talk is about code and something else that talked touched on code and social justice I talked a lot about how the things that we build the way we build them affect real people and their problems and their struggles and that was absolutely not okay not okay we talk about code and code only not the social justice stuff it also talked about code and diversity yeah I think we all know the diversity is really about lowering the bar it forces us to talk about people and their issues and their problems in their history and we just don't do that okay absolutely inappropriate when it comes to a Tech Talk That Talk touched on code and feelings and feelings are squishy they're messy they're icky and a lot of us feel uncomfortable with feelings feelings have no place in technology no place in code we want to talk about code and code I want you to show me that API and when you show me that new framework that new tool that's gonna solve my problems that's all I care about I want to talk about code and give me some more code with it now I host a podcast called command line heroes it's an original podcast from Red Hat super excited about it if you haven't checked it out and totally should and what I love about this show as we talk about these really important moments and open swords these inflection points moments where we see progress we move forward and what I realized looking back at those episodes is all of those episodes have a code and something let's look at a few of those the first two episodes focused on the history of operating systems as a two-part episode part 1 and part 2 and there's lots of different ways we can talk about operating systems for these two episodes we started by talking about Windows and Mac OS and how these were two very powerful very popular operating systems but a lot of a lot of developers were frustrated with them they were closed you couldn't see inside you can see what it was doing and I the developer want to know what it's doing on my machine so we kind of had a little bit of a war one such developer who was very frustrated said I'm gonna go off and do my own thing my name is Linus this thing is Linux and I'm gonna rally all these other developers all these other people from all over the old to come together and build this new thing with me that is a code and moment in that case it was code and frustration it was a team of developers a world of developers literally old world of developers who said I'm frustrated I'm fed up I want something different and I'm gonna do something about it and what's really beautiful about frustration is it the sign of passion we're frustrated because we care because we care so much we love so deeply then we want to do something better next episode is the agile revolution this one was episode three now the agile revolution is a very very important moment in open-source and technology in general and this was in response to the way that we used to create products we used to give this huge stack of specs all these docs from the higher-ups and we'd take it and we go to our little corner and we lightly code and build and then a year with Pastor here's a pass a few years have passed and we'd finally burst forth with this new product and hope that users liked it and loved it and used it and I know something else will do that today it's okay no judgment now sometimes that worked and a lot of times it didn't but whether or not it actually worked it hurt it was painful these developers not enjoy this process so what happened a dozen developers got together and literally went off into their own and created something called the agile manifesto now this was another code and moment here it's code and anger these developers were so angry that they literally left civilization went off into a mountain to write the agile manifesto and what I love about this example is these developers did not work at the same company we're not on the same team they knew each other from different conferences and such but they really came from different survive and they agreed that they were so angry they were going to literally rewrite the way we created products next as an example DevOps tear down the wall this one is Episode four now this is a bit different because we're not talking about a piece of technology or even the way we code here we're talking about the way we work together the way that we collaborate and here we have our operations folks and our developers and we've created this new kind of weird place thing called DevOps and DevOps is interesting because we've gotten to a point where we have new tools new toys so that our developers can do a lot of the stuff that only the operations folks used to be able to do that thing that took days weeks months to set up I can do it with a slider it's kind of scary I can do it with a few buttons and here we have another code and moment and here that blink is fear for two reasons the operations focus is looking over the developer folks and thinking that was my job I used to be able to do that am I still valuable do I have a place in this future do I need to retrain there's also another fear which is those developers know what they're doing do they understand the security implications they appreciate how hard it is or something to scale and how to do that properly and I'm really interested in excited to see where we go with that where we take that emotion if we look at all of season one of the podcast we see that there's always a code and whether it's a code and frustration a code and anger or a code and fear it always boils down to code and feelings feelings are powerful in almost every single episode we see that that movement forward that progress is tied back to some type of Oshin and for a lot of us this is uncomfortable feelings make us feel weird and a lot of those YouTube commenters definitely do not like this whole feeling stuff don't be like those YouTube commenters there's one thing you take away from this whole talk let it be that don't be like these YouTube commenters feelings are incredibly powerful so the next time that you're working on a project you're having a conversation about a piece of software or a new piece of technology and you start to get it worked up you get angry you get frustrated maybe you get worried you get anxious you get scared I hope you recognize that feeling as a source of energy I hope you take that energy and you help us move forward I would take that to create the next inflection point that next step in the right direction feelings are your superpowers and I hope you use your powers for good thank you so much [Applause] please welcome jewel-box chief technology officer Sara Chipps [Music] Wow there's a lot of you out here how's it going I know there's a lot of you East Coasters here as well and I'm still catching up on that sleep so I hope you guys are having a great experience also my name is Sarah I'm here from New York I have been a software developer for 17 years it's longer than some of the people on stage today I've been alive big thanks to the folks at Red Hat for letting us come and tell you a little bit about jewel box so without further ado I'm gonna do exactly that okay so today we're gonna do a few things first I'm gonna tell you why we built jewel BOTS and why we think it's a really important technology I'm gonna show you some amazing magic and then we're gonna have one of the jewel bus experts come as a special guest and talk to you more about the deep technology behind what we're building so show hands in the audience who here was under 18 years old when they started coding it's hard for me to see you guys yep look around I'd have to say at least 50% of you have your hands up all right keep your hand up if you were under 15 when you started coding I think more hands up just what is it I don't know how that mouth works but awesome okay great yeah a little of I think about half of you half of you have your hands up that's really neat I've done a bunch of informal polls on the internet about this I found that probably about two-thirds of professional coders were under 18 when they started coding I myself was 11 I was a homeschooled kid so a little weird I'm part of the generation and some of you maybe as well is the reason we became coders is because we were lonely not because we made a lot of money so I was 11 this is before the internet was a thing and we had these things called BBS's and you would call up someone else's computer in your town and you would hang out with people and chat with them and play role-playing games with them it didn't have to be your town but if it wasn't your mom would yell at you for a long distance fees and I got really excited about computers and coding because of the community that I found online okay so this is sometimes the most controversial part of this presentation I promised you that they dominate our lives in many ways even if you don't even if you don't even know a 9 to 14 year old girl even if you just see them on the street sometimes they are deciding what you and I do on a regular basis hear me out for a second here so who here knows who this guy is okay you don't have to raise your hands but I think most people know who this guy is right so this guy used to be this guy and then teenage girls were like I think this guy has some talent to him I think that he's got a future and now he's a huge celebrity today what about this guy just got his first Oscar you know just kind of starting out well this guy used to be this guy and I'm proud to tell you that I am one of the many girls that discovered him and decided this guy has a future all right raise your hand if you listen to Taylor Swift just kidding I won't make you do it but awesome that's great so Taylor Swift we listen to Taylor Swift because these girls discovered Taylor Swift it wasn't a 35 year old that was like this Taylor Swift is pretty neat no one cares what we think but even bigger than that these huge unicorns that all of us some of us work for some of us wish we invented these were discovered by young teenage girls no one is checking to see what apps were using they're finding new communities in these thin in these platforms and saying this is how I want to commune with my friends things like Instagram snapchat and musically all start with this demographic and then we get our cues from them if you don't know what musically is I promise you ask your nearest 9 to 14 year old friend if you don't do that you'll hear about it in a few years but this demographic their futures are all at risk everyone here knows how much the field of software development is growing and how important technical literacy is to the future of our youth however just 18% of computer science graduates are girls just 19% of AP computer science test takers and just 15% of Google's tech force identify as female so we decided to do something about that we were inspired by platforms like MySpace and Geocities things like Neopets and minecraft all places where kids find something they love and they're like okay to make this better all I have to do is learn how to code I can totally do that and so we wanted to do that so we talked to 200 girls we went to schools we sat down with them and we were like what makes you tick what are you excited about and what we heard from them over and over again is their friends their friends and their community are pivotal to them and this time in their lives so when we started talking to them about a smart friendship bracelet that's when they started really freaking out so we built Jewel BOTS and Jewel BOTS has an active online community where girls can work together share code that they've built and learn from each other help each other troubleshoot sometimes the way they work is when you are near your friends your bracelets light up the same color and you can use them to send secret messages to each other and you can also code them so you can say things like when all my swimming friends are together in the same room all of our bracelets should go rainbow colors which is really fun you can even build games jewel BOTS started shipping about a year and a half ago about after a lot of work and we are about to ship our 12,000 jewel bot we're in 38 city sorry 38 countries and we're just getting started okay so now it's time for the magic and I have an important question does anyone here want to be my friend pick me all right someone today Gary oh I don't have many friends that's awesome I'm so glad that we'll be friends okay it's awesome so we just need to pair our jewel BA okay okay and in order to do that we're gonna hold the magic button in the middle down for two seconds so one locomotive two locomotive great and then we got a white flashing I'm gonna do yours again I did it wrong locomotive two locomotive it's we're adults we can't do it okay it's a good that are smart alright so now we get to pick our friendship color I'm gonna pick red hat red does that work for you sure okay great so now I just picked a red hat red and my jewel bot is saying alright Tim's jewel bot do you want to be my friend and imageable about it's like I'm thinking about it I think so okay now we're ready okay great so now we're red friends when we're together our bracelets are going to be red and I will send you a secret message when it's time for you to come out and trip and introduce the next guest awesome well thank you so much thank you tailor gun so glad we could be friends and if only people would start following me on Twitter it'd be a great day awesome alright so now you can see the not so technical part of jewel box they use bluetooth to sense when your friends are nearby so they would work in about a 30 meter hundred foot range but to tell you about the actual technology part I'm going to introduce is someone much more qualified than I am so Ellie is one of our jewel box ambassadors she's an amazing YouTube channel that I would please ask you to check out and subscribe she's le G Joel BOTS on YouTube she's an amazing coder and I'm really excited to introduce you today to Ellie Galloway come on out Ellie [Applause] hello my name is le gallais I'm gonna show you how I got coding and then show you some coding in action I first started coding at a6 when my dad helped me code a game soon after I program form a code for Minecraft then my dad had shown me jo bot I keep coding because it helps people for instance for instance you could code auto crack to make it a lot smarter so it can help make people stay run faster but what about something more serious what if you could help answer 911 calls and give alerts before we start I have three main steps to share with you I often use these steps to encoding my jaw bot and continue to use some of these now step one read the instructions and in other words this means for Jabba to memorize the colors and positions a way to memorize these because it's tricky is to remember all the colors and positions you O type will be capital and remember that the positions are either short for north west south west north east and south east step to learn the basic codes when it comes to coding you need to work your way up step 3 discover feel free to discover once you mastered everything now let's get to coding let's use or let's first use combining lights so under void loop I'm going to put LED turn on single s/w and blue and before we make sure that this works we got to put LED LED okay now let's type this again LED dot turn on single now let's do SW green now we have our first sketch so let's explain what this means led LED is a function that to control the LED lights LED turn on single SW blue tells that SW light to turn blue and green flashes so quickly with the blue it creates aqua now let's do another code lets you i'm going to use a more advanced command to make a custom color using RGB let's use a soft pink using 255 105 and 180 now let's type this in the button press function so let's do LED led LED dot set light and now we can do let's do position 3 255 105 and 180 now let's explain what this means the first one stands for the position the three others stand for red green and blue our GPS can only go up to 255 but there are 256 levels but if you count the first one as zero then get 255 so let's first before we move on let's show how this works so this is it before and now let's turn it on to see how our aqua turned out now let's see how our RGB light turned out so we are looking for a soft pink so let's see how it looks think about how much the code you write can help people all around the world these are ideas are just the beginning of opening a new world in technology a fresh start is right around the corner I hope this helped you learn a little bit about coding and even made you want to try it out for yourself thank you [Applause] alright alright alright I need your help for a second guys alright one second really really fascinating we're short on time today is Ellie's 11th birthday and I think we should give her the biggest present that she's gonna get today and it's something none of us have experienced and that is thousands of people saying happy birthday Elliott wants so when I say three can I get a happy birthday Elly one two three happy birthday Elly great job that's the best part of my job okay so those are that's two of us we're just getting started this numbers out Dana would almost shipped 12,000 jewel BOTS and what I'm really excited to tell you about is that 44% of our users don't just play with their jewel bots they code them and they're coding C do you even code C I don't know that you do but we have 8 to 14 year olds coding C for their jewel box we also have hundreds of events where kids come and they learn how to code for the first time here's how you can help we're open source so check out our github get involved our communities online you can see the different features that people's are asking for we're also doing events all over the world a lot of people are hosting them at their companies if you're interested in doing so reach out to us thank you so much for coming and learning about jewel box today enjoy the rest of your summit [Music] ladies and gentlemen please welcome hacker femme au founder Femi who Bois de Kunz [Music] good afternoon red hat summit 2018 i'm femi holiday combs founder of hacker femme Oh I started coding when I was 8 when I was 9 I set up South London raspberry jam through crowdfunding to share my passion for coding with other young people who might not otherwise be exposed to tech since then I've run hundreds of coding and robot workshops across the UK and globally in 2017 I was awarded an inaugural legacy Diana award by their Royal Highnesses Prince William and Prince Harry my service and community we welcome young people who have autism or like me tract syndrome because coding linked me up to a wider community of like-minded people and I'm trying to do the same for those who might also benefit from this I also deliver workshops to corporate companies and public organizations whilst feeding back ideas and resources into my community work we like to cascade our knowledge and experience to other young coders so that they can benefit too we're learning new tech every day we're starting to use github to document and manage our coding projects we've no dread we're using the terminal and beginning to really appreciate Linux as we explore cybersecurity and blockchain it's been quite a journey from South London to the world-famous Tate Modern museum to Bangladesh to this my first trip to the States and soon to China where I hope to translate my microwave workshops into Mandarin on this journey I'm noticed it is increasingly important for young coders to have collaborative and community led initiatives and enterprise and career ready skills so my vision now is to run monthly meetups and in collaboration with business partners help a hundred young disadvantaged people to get jobs in the digital services in fact out of all the lessons I've learned from teaching young coders they all have one thing in common the power of open source and the importance of developing community and today I want to talk about three of those lessons the value of reaching out and collaborating the importance of partnering event price and the ability to self organize and persist which translated into English means having a can-do attitude getting stuff done when you reach out when you show curiosity you realize you're not alone in this diverse community no matter who you are and where you're from from coding with minecraft to meeting other young people with jams I found there are people like me doing things I like doing I get to connect with them that's where open-source comes to the fourth second the open source community is so vast then it crosses continents it's so immersed perspectives that it can take you to amazing places out of space even that's my code running on the International Space Station's Columbus module let's take a lesson and playing was an audio representation for the frequencies recorded in space my team developed Python code to measure and store frequency readings from the space station and that was down linked back to earth to my email box Thomas who's 10 developed an audio file using audacity and importing it back into Python how cool is that Trulli collaboration can take you places you never thought possible because that's how the community works when you throw a dilemma a problem a tip the open source community comes back with answers when you give the community gives back tenfold that's how open source expands but in that vast starscape how do you know what to focus on there are so many problems to solve where do I start your world enterprice enterprise software is very good at solving problems what's the big problem how about helping the next generation be ready for the future I want to do more for the young coding community so I'm developing entrepreneurial business links to get that done this is a way to promote pathways to deal with future business problems whether in FinTech healthcare or supply chains a meeting the skill shortage it is a case for emerging in it's a case for investing in emerging communities and young change enablers throwing a wider net equates to being fully inclusive with a good representation of diversity you know under the shadow of the iconic show back in London there are pockets of deprivation where young people can't even get a job in a supermarket many of them are interested in tech in some way so my goal for the next three years is to encourage young people to become an active part of the coding community with open source we have the keys to unlock the potential for future innovation and technological development with young coders we have the people who have to face these problems working on them now troubleshooting being creative connecting with each other finding a community discovering their strengths along the way for me after running workshops in the community for a number of years when I returned from introducing coding to young street kids in Bangladesh I realized I had skills and experience so I set up my business hacker Famicom my first monetized fehmi's coding boot camp at Rice London Barclays Bank it was a sellout and a few weeks later shows my second I haven't looked back since but it works the opposite way - all the money raised enable me to buy robots for my community events and I was able to cascade my end price knowledge across to other young coders - when you focus on business problems you get active enthusiastic support from enterprise and then you can take on anything the support is great and we have tons of ideas but what does it really take to execute on those ideas to get things done can-do attitudes what open source needs you've seen it all this week we're all explorers ideator z' thinkers and doers open source needs people who can make the ideas happen get out there and see them through like I did setting up Safford and raspberry jam as an inclusive space to collaborate and learn together and that that led to organizing the young coders conference this was about organizing our own two-day event for our partners in industry to show they value young people and wanted to invest in our growth it doesn't stop there oh nice now I'm setting up monthly coding meetups and looking at ways to help other young people to access job opportunities in end price and digital services the underlying ethos remains the same in all I do promoting young people with the desire to explore collaborative problem-solving when coding digital making and building enterprise you fled having the confidence to define our journey and pathways always being inclusive always encouraging innovation and creativity being doers does more than get projects done makes us a pioneering force in the community dreaming and doing is how we will make exponential leaps my generation is standing on the shoulders of giants you the open-source pioneers and the technology you will built so I'd love to hear about your experiences who brought you into the open-source community who taught you as we go to upscale our efforts we encounter difficulties have you and how did you overcome them please do come to talk to me I'll be in the open-source stories booth both today and tomorrow giving workshops or visit the Red Hat page of my website hack Famicom I really value your insights in conclusion I'd like I'd like to ask you to challenge yourself you can do this by supporting young coders find the crowdfunding campaign kick-start their ideas into reality I'm proof that it works it's so awesome to be an active part of the next exponential leap together thank you [Applause] so unbelievable huh you know he reminds me of be at that age not even close and I can tell you I've spent a lot of time with Femi and his mom grace I mean what you see is what you get I mean he's incredibly passionate committed and all that stuff he's doing that long list of things he's doing he's going to do so hopefully today you get a sense of what's coming in the next generation the amazing things that people are doing with collaboration I'd also like to thank in addition to femi I'd like to thank Sauron Sarah and Ellie for equally compelling talks around the open source stories and again as I mentioned before any one of you can have an open source story that can be up here inspiring others and that's really our goal in telling these stories and giving voice to the things that you've seen today absolutely extraordinary things are happening out there and I encourage you to take every advantage you can hear this week and as is our theme for the summit please keep exploring thank you very much [Applause] [Music]

>> Announcer: Live, from Boston, Massachusetts, it's theCUBE, covering OpenStack Summit 2017. Brought to you by The OpenStack Foundation, Red Hat, and additional ecosystems support. >> Hi, I'm Stu Miniman, and my cohost this week has been John Troyer. This is SiliconANGLE Media's production of theCUBE, worldwide leader in live tech coverage. And this has been OpenStack Summit 2017 in Boston, Massachusetts. John, we came in with a lot of questions. One of my premises, coming into the event was that we needed to reset expectations, a little bit. I know I learned a lot this week. Still one of my favorite communities. A lot of really smart people. Really interesting things going on. Open source infrastructure is really the focus here. Start with you, big meta takeaways from the show so far. >> Big picture, my first summit, my first summit here. Didn't quite know what to expect. I love the community, a lot of activity. A lot of real world activity going on. People building clouds today. So that was very insightful and very, that's a great data point. As far as the ecosystem goes, a lot more talk about integrating with the rest of the open source ecosystem, about integrating with other public and private clouds. So I thought that there was also a lot of self awareness here about where OpenStack is on it's journey and how it might proceed into the future. So overall, I think, you know, a really practical, focused, and grounded week. >> Yeah, came in with the whole concept of big tent. I think which we said, there's a big hole poked in that. There's the core is doing well, there's a number of projects, I forget the user survey, whether you know, there's the kind of the six core pieces and then there's like 9 or 10 in the average configuration. So there's more than the core, there's interesting things going into it and last year I felt that OpenStack kind of understood where it fit into that hybrid cloud environment. As you pointed out this year, some of those upper layer things, I feel like I understand them a little more. So, of course, containers and Kubernetes, a big piece of the discussion this week. Containers definitely transforming the way we build our applications. It seems a given now, that containers will be a big part of the future and OpenStack's ready for it. We had yesterday, we had the people that did the demo in the keynote, but containers doing well. Kubernetes fits in pretty well, even though, I think it was Randy Bias that said, "Well, OpenStack needs Kubernetes." My paraphrase is Kubernetes doesn't need OpenStack. KubeCon is going to be in Austin at the end of the year and that show could be bigger than this show was here in Boston. Year over year, for the North American show, attendance is down a little bit, but still robust attendance, lots of different pieces. Containers, Kubernetes, you mentioned some of the other pieces, any other add-ons on that? >> Well now, I mean other than its worth saying that these are not either or, this is all and. If you look at the total addressable market, every place that containers and Kubernetes can play, that's every cloud in the world, right? It's up there at the application layer. If you look at where OpenStack belongs, it is in these private clouds that have special needs, that have, either from privacy, security or functionality latency, just data gravity, right. There's all these reasons why you might want to build out a public cloud and we see that with Telco. Telecomm is building out their own infrastructure, because they need it, because they run the network core. So that's not going away. As far as containers go, again the story was not either or, it's and. You can containerize the infrastructure. That's super useful. Sometimes being bare metal is useful. Separately, you can put containers on top, because that's increasingly becoming the application packaging and interface format. So, I didn't see a lot of ideology here, Stu, and that was refreshing to me. People were not saying there is one true way. This is a modular system that, at this point in it's life cycle, it has to become very pragmatic. >> John, I think that's a great point, because we knock on, and everybody knocks on, OpenStack's not simple and the reason is because IT is not simple. Everybody has different challenges, therefore, it's not a Lego brick, it's lots of ways we put it together. Had some really interesting deep dives with a customer, couple of users today. The Adobe advertising cloud, Paddy Power Betfair, both of those gave us real concrete examples of how and why they build things the way they do. How OpenStack and Kubernetes go together. How acquiring another company, or switching your storage vendors is made easier by OpenStack. So, we've talked to a number of practitioners, they like OpenStack, reminds me of VMware. People like being able to build it and tweak it. Very different scale for some of these environments, but people are building clouds. The Telecom's are doing some good things. All the Linux companies are super excited about the future, that it helps them kind of move up the stack and become more critical environments and how it all ties into this multi-hybrid cloud world. Digital transformation, many of these pieces, I need that modern infrastructure and the open infrastructure coming from OpenStack and related pieces pull it all together. >> Well, where is the innovation going to come from in this next generation of cloud? I thought our segment with Orran, talking about the Massachusetts open cloud, was great, because he's there as a computer science professor, somebody who's been intimately involved with virtualization, with IBM, with VMware, saying, "Okay, we need to build this next generation. "Where can we innovate? We have to own the stack "and OpenStack is a great way for us to innovate "with those different components." One of the challenges, because OpenStack as a set of technologies, is so modular, is where's the knowledge come from? Where's the knowledge transfer? Can you find an OpenStack expert? Do you have to grow them? So, I see that as one challenge going forward for the OpenStack community, is how do we grow the knowledge base? How do we make sure that people are trained up and able to architect and operate OpenStack based clouds? >> Yeah, John, how about the individuals themselves? We talked to Lisa-Marie Namphy about the Ambassadors Program. We talked to a number of our guests throughout the week about training everything, from Orran Krieger, talking about how his students are helping to build this, to engagement contribution. I mean it's nuance, when I look at the future of jobs. A lot of companies here are hiring. Which is always heartening to me. What's your take on that aspect? >> Well, it's still a very vibrant community. You look at these different camps, a lot of them are vendor affiliated these days. There are very few communities that are outside of a vendor and these open source foundations are one source of those. I think, look there's still 5 or 6,000 people here, right? This is not a small event and these people are active, hands on operators, for the most part. So-- >> Yeah and the thing I'd point out, there are lots of companies that have contributors here. The other category is still really big here. A point Lisa-Marie made, many of the people that have contributed here have switched jobs a number of times. NASA helped start it. They kind of left, they came back. Some of the big Telecom companies, they're not selling OpenStack, they're using it to help build their services. So, it's like wait, which are vendors, which are providers? I think we know everybody's becoming a software company. Wait John, TechReckoning, are you a software company yet? >> We use a lot of soft, we use a lot of cloud, mostly on SaaS side. >> At SiliconANGLE Media we actually have a part of our business that is software. We've got a full development team, you know open source plays into somewhat we do, but I guess what I'm saying is, the traditional demarcation between the vendor and the consumer in open source tends to be blurring. I don't remember in the keynote if they had, hey how many people have contributed to the code. That's something that we used to get, partially because we have splintered out this event a little as to, the goals, it's no longer the people building it. They've got lots of ways to do that and a lot of the drama's gone. We had for many years in OpenStack, it was who's going to own what distribution and who's driving what project and a lot of that's come out. We talked about the last couple of years, has it become boring in certain ways? But it's important, it's driving a lot of pieces and OpenStack should be here to stay for awhile. >> Yeah, it's part of the conversation. I love the term open infrastructure. We heard it once or twice. We'll see if that becomes a topic of conversation. Going back to Lisa-Marie Namphy's segment, I encourage people to check out your local OpenStack meet-up right? You'll find that other conversations are going on there, other than just OpenStack. This is an ecosystem, it interacts with the rest of the world. >> Yeah, and talk about that next generation, edge is really interesting, the conversation we had with Beth Cohen. Also talked to Lee Doyle from the analysts perspective. Lots of cool things happening with that next generation of technology. 5G's going to play into it. So, there's always the next next thing and OpenStack's doing a good job to, as a community, to be open, working with it and understanding that they don't need to be all things to all people, certain other pieces will pull in and we have that broad diverse ecosystem. >> Looks a, I'll go out and make a prediction, I think in five years, we're going to look back and we're going to say, actually, OpenStack driven plumbing is going to be driving a lot of the next generation to the internet. >> Yeah, I love that, actually I forget if it's two or three years ago, what I said was that, as Linux took a long time to kind of work its way into all the environments, OpenStack pieces will find its way there. Brian Stevens from Google said, "If it wasn't for open source, in general, "Linux specifically, we wouldn't have "any of the hyperscale guys today." All those companies leverage open source a bunch. We've heard whisperings that, not just the telecommunications, some very large global companies that are trying to figure out how OpenStack fit into it. Coming into the show, it was all the talk about, oh, Intel stopped its joint lab with Rackspace, HPE pulled its cloud out, there's some other hyperscale companies that are looking at OpenStack. It's reached a certain maturity and it will fit in a number of places. All right, well, hey John, we started the beginning of the week, it was cloudy and overcast, a little cool in Boston. The skies opened up, it's blue. I've loved having two weeks here in Boston. Really appreciate you joining me for the journey here. Here for the OpenStack Summit. >> Thanks for having me, it was fascinating. >> Thank you John. Want to thank our audience, and thank the whole team here in Boston, and the broad SiliconANGLE media team. This is our biggest week that we've ever had, as to how much content we're creating. So, thanks so much to everyone. Thanks for our community for watching. As anything, when they scale, let us know if there's things we need to fix or feedback that you have for us. For Stu Miniman, John Troyer, the whole team here in Boston and beyond, I want to thank you so much for watching theCUBE. Be sure to check out SiliconANGLE TV for all the upcoming events. Let us know where we should be at and feel free to reach to us with any comments, and thank you for watching theCUBE. (light techno music)

>> Announcer: Live from Boston, Massachusetts, it's the CUBE covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, Red Hat, and additional ecosystem support. >> Welcome back, I'm Stu Miniman. And if I'm sitting on this side of the table with the long hallways behind me, it means we're here for the wrap of the second day. John Troyer's here, day two of three days, theCUBE here at OpenStack Summit. John, I feel like you're building energy as the show goes on, kind of like the show itself. >> Yeah, yeah, getting my footing here. Again, my first summit. It was a good second day, Stu, I think we made it through. We had some fascinating stuff. >> Yeah, fascinating stuff. Before we jump into some of the analysis here, I do want to say you know, first and foremost, big thanks to the foundation. Foundations themselves tend to get, they get beat up some, they get loved some, without the OpenStack Foundation, we would not be here. Their support for a number of years, our fifth year here at the show, as well as the ecosystem here, really interesting and diverse and ever-changing ecosystem, and that fits into our sponsors too. So Red Hat's our headline sponsor here. We had Red Hat Summit last week and two weeks, lots of Red Haters, and now lots of Stackers here. Additional support brought to us by Cisco, by Netronome, and by Canonical. By the way, no secret, we try to be transparent as to how we make our money. If it's a sponsored segment, it lists "sponsored by" that guest here, and otherwise it is editorial. Day three actually has a lot of editorial, it means we have a lot of endusers on the program. We do have vendors, cool startups, interesting people, people like Brian Stevens from Google. When I can get access to them, love to have it here. So big shout out as always. Content, we put it out there, the community, try to have it. Back to the wrap. John, you know we've kind of looked at some of the pieces here, the maturity, you know where it fits in the hybrid and multi cloud world. What jumped out at you as you've been chewing on day two? >> Well, my favorite thing from today, and we talked about it a couple times just in passing it keep coming up, is OpenStack on the edge. So the concept of, that the economics works today, that you can have a device, a box, maybe it's in your closet somewhere, maybe it's bolted to a lamppost or something, but in the old days it would have run on some sort of proprietary chip, maybe an embedded Linux. You can put a whole OpenStack distribution on there, and when you do that, it becomes controllable, it becomes a service layer, you can upgrade it, you can launch more services from there, all from a central location. That kind of blew my mind. So that's my favorite thing from today. I finally got my arms around that I think. >> Okay, great, and we saw Beth Cohen from Verizon was in the day one keynote. We're actually going to have her on our program for the third day. And right, teasing out that edge, most of it, telecommunications is a big discussion point here. I understand why. Telcos spend a lot of money, they are at large scale, and that NFV use case has driven a lot of adoption. So Deutsche Telekom is a headline sponsor of the OpenStack Foundation, did a big keynote this morning. AT&T's up on the main stage, Verizon's up on the main stage, you know Red Hat and Canonical all talk about their customers that are using it. You know, we just talked to Netronome about telecommunications. Everybody here, if you're doing OpenStack, you probably have a telco place because that's where the early money is and it tends to be, there's the network edge, then there's the IoT edge, and some of the devices there. So it was was one of the buzzy things going in and definitely is one of the big takeaways from the show so far. >> Well, Stu, I also think it's a major prove point for OpenStack, right. Bandwidth needs are not going down, that's pretty clear, with all the things you mentioned. Throughput is going to have to go up, services are going to have to be more powerful, and so all these different connected devices and qualities of service and streaming video to your car. So if OpenStack can build a back plan, a data plan for OpenStack that can do that, which it looks like they are doing, right, that's a huge prove point downstream from the needs of a telco, so I think that's super important for OpenStack that it's usable enough and robust enough to do that and that's one of the reasons I think it gets talked about so much. The nice thing is this year compared to my comparisons of previous years of OpenStack Summit, telco is not the only game in town, right. Enterprise also got a lot of play and there's a lot of use cases there too. >> And just to close out on that edge piece, really enjoyed the conversation we had with John and Kendall who had worked on the container space. Talking about the maturation of where Cinder had gone, how we went from virtualized environments to containerized environments. And even we teased out a little bit that edge use case. I can have a really small OpenStack deployment to put it at that edge. Maybe that's where some of the serverless stuff fits in. I know I've been, I tell my team, every time I get a good quote on serverless, let's make a gem out of that, put it out there, 'cause it's early days, but that is one of those deployments where I need at the edge environments, I need something lightweight, I need something that's going to be less expensive, can do some task processing, and both containers and potentially serverless can be interesting there. >> Yeah, I mean, even in our Canonical discussion with the product manager for their OpenStack distribution, right, containers are all over that, right, containers are just a way of packaging, there are some really interesting development pipelines that are now very popular and being talked about and built on in the container space. But containerization actually can come into play multiple points in the stack. Like you said, the Canonical distribution gets containerized and pushed out, it's a great way of compartmentalizing and upgrading, that's what the demo on stage today was about. Also, just with a couple of very short scripts, containerizing and pulling down components. So I think again, my second favorite thing after the edge today was just showing that actually containers and OpenStack mix pretty well. They're really not two separate things. >> Right, and I think containerization is one of those things that enables that multi cloud world. We talked in a number of segments today, everything from Kubernetes with Brian Stevens as to how that enables that. Reminds me at Red Hat Summit last week we talked a lot about OpenShift. OpenShift's that layer on top of OpenStack and sits at that application level layer to allow be to be able to span between public or private clouds and we need that kind of you know that to be able to enable some real multi or hybrid cloud environments. >> Yeah I mean, containers and in fact that Kubernetes layer may end up being the thing that drives more OpenStack adoption. >> Yeah, and the other thing that's been interesting, just hallway conversations, bumping into people we know, you know trying to walk around the show a little bit, as to people that are finally getting their arms around, okay, OpenStack from a technology standpoint has matured and you know they either need it to clean up what was their internal cloud or building something out, so real deployments. We talked about it yesterday in the close though. They're real customers doing real deployments. It's heartening to hear. >> Yeah I mean, one of those conversations, I ran into somebody at a hyperscale company, a friend of mine, and you know they are building out, internal OpenStack clouds to use for real stuff, right. >> But wait, hyperscale, come on, John, we can give away. Is this something we have on our phone or something we, I'll buy and use? >> One of those big folks. >> There's a large Chinese company that anybody in tech knows that's supposed to be doing a lot with OpenStack. We heard definitely Asia, very broad use of OpenStack. Been a theme of the whole show, right, is that outside the US where we tend to talk a lot about the public cloud, OpenStack's being used. An undertone I've heard is certain companies that start here in the United States, it's sometimes challenging for a foreign company to say I'm going to buy and use that, absolutely that is a headwind against a company like Amazon. Ties back to we had a keynote this morning with Edward Snowden and some of those things. What is the relationship between government and global companies that have a headquarters in the US and beyond. >> Yeah I think it's too soon to say where the pendulum, how the far the pendulum is going to swing. I'll be very interested in the commentary for next year to see have we moved away from more of the centralized services dominating the entire marketplace and workload into more distributed, more private, more customizable. For all those reasons, there's a lot of dynamics that might be pushing the pendulum in that direction. >> And one of the things I've liked hearing is infrastructure needs to be more agile, it needs to be more distributed, more modularized, especially as the applications are changing. So I feel like more than previous summits I've been at, we're at least talking about how those things fit together. With everything that's happening with the OpenStack Days, the Kubernetes, Cloud Foundry, Ceph, other open source projects, how those all fit together. It feels like a more robust, full position as opposed to , we were just building a software version of what we were doing in the data center before. >> My impression was the conversation at times had been a little more internally focused, right, it's a world unto its own. Here at this summit, they're definitely acknowledging there's an ecosystem, there's a landscape, it all has to interoperate. Usability's a part of that, and then interoperability and componentization is a part of that as well. >> The changing world of applications. We understand the whole reason we have infrastructure is to run those applications, so if we're not getting ready for that, what are we doing? >> I don't want to put words in their mouth, but I think the OpenStack community as a whole, one of their goals, you know, OpenStack needs to be as easy to run as a public cloud. The infrastructure needs to be boring. We heard the word boring a lot actually today. >> Yeah and what we say is, first of all, the public cloud is the bar that you were measured against. Whether it is easier or cheaper, your mileage may vary, because public cloud was supposed to be simple. They're adding like a thousand new features every year, and it seems to get more complicated over time. It's wonderful if we could architect everything and make it simple. Unfortunately, you know, that's why we have technology. I know every time I go home and have some interaction with a financial institution or a healthcare institution, boy, you wish we could make everything simpler, but the world's a complicated place and that's why we need really smart people like we've gotten to interview here at the show. So any final comments, John? >> No, I think that sums it up. Those are my favorite things for today. I'm looking forward to talking to a lot of customers tomorrow. >> Yeah, I'm really excited about that. John, appreciate your help here. So there's a big party here at the show. They're taking everyone to Fenway Park for the Stacker party. Last year it was an epic party in Austin. Boston's fun, Fenway's a great venue. Looks like the rain's going to hold off, which is good, but it'll be a little chillier than normal, but we will be back here with a third day of programming as John and I talked about. Got a lot of users on the program. Really great lineup, two days in the bag. Check out all the videos, go to SiliconANGLE.tv to check it all out. Big shout out to the rest of the team that's at the Dell EMC World and ServiceNOW shows, be able to check those out and all our upcoming shows. And thank you, everyone, for watching theCUBE. (technical beat)

(energetic music) >> Narrator: Live from Boston, Massachusetts it's the Cube, covering OpenStack Summit 2017 brought to you by the OpenStack Foundation, Red Hat, and additional ecosystem support. >> Hi and welcome back to SiliconANGLE TV's production of the Cube here at OpenStack Summit 2017 in Boston. I'm Stu Miniman joined with my co-host for the week, John Troyer. As you can see behind us, the day 2 keynotes letting out. John, it's always interesting to look at these shows. They had some demos that were awesome, a couple of demos were the demo gods were not smiling on them. They had Edward Snowden live via Q&A. They had Brian Stevens, who we're going to be talking with in a little bit, the CTO of Google, who was on The Early Start. For me, they're a little up and down. There's some of the vendor pitches in there, people are like, "Oh I have a great demo," and then you say, "Come to my booth "and see a bunch of my sessions." So, a little bit uneven and disjointed, which has been a some of the feedback you get about OpenStack in general over the last few years as to all those pieces come together. But yeah, what are your early thoughts coming out of the day 2 keynote? >> Well, it was definitely a keynote focused at the OpenStack community. We started off with open source and talking about the importance of open source, which is a little bit odd, because everyone here know that. I did like the message that OpenStack was composed of different projects, that it was a piece of the puzzle, not the whole puzzle. You and I both noted VMware's Scott Lowe tweeted, "It's good to the OpenStack Foundation talking about being a part of the overall solution, not the overall solution." I mean, as one example, they mentioned using etcd, which is a distributed key value store, instead of writing their own. Etcd powers Kubernetes. Your would be insane in 2017 to rewrite or distribute a key value pair, sorb at this point. Because, it's just out there, it's mature. You know, OpenStack has been around for seven years. There's been a lot of ecosystem grown up around them. >> Yeah, yeah. A couple of pieces on that. One is, there was a message about like, oh I can now take the individual components of OpenStack. I could actually do that before. I've noted, I've talked to a number of software companies, that when you did down into what they're doing, oh what do you know, there's, you know, there's Syndrr. Or, there's, you know, something in there, just as when I use AWS, I can use some of the individual components, same thing with OpenStack. It's not a monolith. There are the individual pieces. But, they're highlighting that a little bit more. They're saying use some of the pieces. The other thing, on the open source in general, they noted that like, in the artificial intelligence machine learning space, like, everyone that you see is using open source. Everything from Google and TensorFlow, is one that gets highlighted a lot. Amazon made a big push at their show about what they're doing with, you know, some of the machine learning. I can't remember right now, the program on there. But, right, in some of these emerging spaces, open source is the defacto way to do that. We had, in one of the conversations we had yesterday with one of the Cysco Distinguished Engineers, you know, it used to be standards. Now, open source really drives a lot of that. I actually got a quick conversation with Martin Casado, who had, you know, worked on a lot of open source things before Vmware acquired him. And, now he's at Andreessen Horowitz looking at all the open source models. So, unfortunately Martin didn't have enough time to come on the program, but we've had him on many times. Yeah, so sometime he's going to do that. >> Stu, I have a question. >> Stu: Yeah. >> The message today of being part of an ecosystem and being a componentized, open source set of projects, does that detract or add to this conversation around OpenStack Core versus Big Tent? >> I think Big Tent is dying. We talked to a number of the participants yesterday and said it was a little overblown. It does not mean that some pieces might still get worked on, but it's the core components. And you know, when dug into the survey, how many of the pieces do we really need? We want to make sure the Core works. I can have that distribution if I want to do what is OpenStack. When they highlighted those components, it wasn't 27 different projects there. You know, I think it was a handful of like six. >> Yeah. >> That were there. So, you know Swift and Syndrr, some interesting, cool little graphics. It was ironic, I tell you. The little graphic there, that was like a scary looking bear. It's like, I wouldn't want to run into him in a cartoon alley. Uh, but (laughs). >> Yeah, I did tweet. Yeah, there was an angry bear, kind of a poisonous spider, and a horse's behind. So, I'm not quite sure about the marketing there. But (laughs). >> What is the message you're sending? But, there's some fun. We've got, you know, Mark Collier and Jonathan Bryce coming on soon. We can ask them, you know, was this the community? And are there just some people that have a funny sense of humor, and this is how they show it? >> I did love the demos in today's talk, Stu. I especially liked, they spun up, live on stage, 15 from scratch, OpenStack clouds. And then, had them all join a CockroachDB cluster. I thought that was kind of cool and amazing. >> Yeah, absolutely. You talk about that hybrid, multi cloud world, showing it, you know, in reality, how that works. Pretty neat, and you know, you can actually see some applicability as to how that would fit into a customer environment. And, kudos to all the people. I mean, these were live, no net demos, not Camtasia, not some prerecorded things. Because like, oh wait, this thing's not quite ready to be able to be bootable, or you know, let me come in. I mean, they're up there on stage doing it. The wifi all seemed to work fine. That wasn't a challenge, but yeah, it was pretty cool. >> Well again, trying to give the message that OpenStack is indeed not a science project. That it's live, that it's configurable, that it's stable, that it's installable. And, I think that kind of message of stability, and configurability, and simplicity maybe is one of the ones they're trying to hit here today. >> Yeah, last thing I want to hit on, John, is I want to get your opinion. We throw out the term "open" a bunch. And, I'm watching some of the other industry things, and they say "open" when they mean "choice," as opposed to "open" as in "open source." So, you know, we see Google here, and Google talks about open. So many things that are now open source, a lot of times started out as a Google white paper or something. As we all say, we're all using open source which Google was using 10 years ago, right? You know, MapReduce, and Borg, and Spanner, and some of those things eventually get their way out. I've got some view points on this, but love to get your take first, yeah. >> Well, I mean, definitely it was an homage to open source this morning. In some ways, it was kind of a dig at AWS and Amazon, which uses a lot of open source tools, but does not share back. You know, OpenStack is clearly open source, and they were emphasizing that. I don't know. What are your thoughts, Stu? >> Yeah, it's, customers now, it used to be if you said open source, you know, go back 10, 15 years, and it was like, ooh, no. Now, open source is, a lot of times, a plus, something that they're asking for. Many companies are contributing and engaging in that. OpenStack is a great example of companies that have participated, you know, in helping to build OpenStack. That being said, you know, I always go to, you know, what's the problem to be solved, what's the solution that solves it. And, if it happens to be a little bit pre standard, or not 100% open source, most companies are fine with that. We were at Red Hat Summit last week with the Cube though, and everything they do is 100% open source. They're building their business. Their customers are really happy. So, you know, open source still has a little bit of a double edged sword as to how you do it. But, you know, open source absolutely, there's no question of if open source, it's how much, and to what extent, and where it fits. >> Sure, there is an ecosystem of providers here. There's always lock-in when you make a technical choice. But, in this case, I think they've successfully were trying to show off that there is a choice of clouds. There is an open, a set of open source components that you can mix and match. And so, that actually ties in very well to the interview with Edward Snowden. >> Yeah, absolutely, yeah. It was, and last point. Edward Snowden, towards the end he said fear is, I think the quote was, "the most powerful weapon in the world today." From a political statement, is what he's doing. Fear in IT is a powerful weapon. We know that, you know, enterprise and inertia, you know, tend to go together. With my background in networking, I used to draw these timelines. And, say, from when the time the standard was done to when, you know, the early majority adopt, is often times a decade. So, the technology adoption, moving the operational, we know the people piece is always tough to do, moving my applications. We think people are definitely moving faster, but fear is definitely something that holds them back. What do you see, john? >> Sure, I think the through line of the whole morning was about choice and diversity. Edward Snowden talked about the centralization of information services like Facebook, Google, and Twitter. And I think, and I think by implication, Amazon. And, I think the message that he was giving to the OpenStack crowd was look, you are enabling a multitude of services and a multitude of clouds, and that actually is a lever, a cultural lever against the over centralization of commercial forces, which are a little bit outside people's control. >> Yeah, so John, thanks for helping me wrap up day one. As always, we welcome our audience to please send us feedback. John and I are both pretty active on Twitter, very easy to get in touch with. We are at so many shows. You can check out SiliconANGLE TV. See where we're at. If we're not at a show that you think we should be at, reach, there's contact information at the top. If there's guests that we should have on our program, we're always looking for feedback. Love to get, especially those end user stories, talking about with interesting startups. So, we've got two more days of live coverage. So, for John and myself, stay with us. And, thanks, as always, for watching The Cube. (exciting music)

>> Announcer: Live, from Silicon Valley, it's theCUBE, covering Google Cloud Next '17. (funky techno music) >> Welcome back to our live coverage here of Google Next 2017, an event that last year was focused only on Google Cloud. They've actually expanded a bit, they're talking about G Suite, talking about some of the devices, and they bring in a really broad and diverse community, so when I talk to the Google people, it's not one show, it's a handful of shows. I went to the analyst event. My guest for this segment is Chris Wahl, who came in through the community event. So, excited to get that angle. Chris, thanks so much for doing the drive with me from San Francisco down to Palo Alto. For those of us not in the area, it's a 45 minute drive, it's not too bad. It's a beautiful, sunny day. It's great to catch up with you and thanks for coming. >> Always glad to be on, love being a CUBE Alumni, so, I think it's my third time. >> Wow, a three-time Alumni. It's like if you've been a host of Saturday Night Live for like seven times, you know you get the special jacket. - Automatically. >> Things like that. You're getting up there. Three times. It's like, you're not quite in Pak Elsinger area, but you have passed, you've been on more than Andy Jassey now. >> Wow, cool. >> I think that that's pretty impressive. >> Bucket list, accomplished. >> Exactly, so, what brings you to the Google event and tell us a little bit about the community event. >> Yeah, to be honest, I thought it was a spam email at first. I just got an invite saying, hey, we have this Google event going on, and I'm not really plugged in to the Google Universe too much. So I said, cool, I'm interested, I'll take a look. Got invited out by Sarah Novotny to a community focus day. >> Host: Sarah's awesome. Also a CUBE Alum, of course. >> Yeah, Alum, and ran OSCON I think, as a boarder or some kind of management facility for quite a while. So yeah, the Google Cloud Next is this week but on Tuesday. They actually had a bunch of influencers, evangelists, community members, out to spend time with all sorts of Google-y Google-ers, talking around what their vision is around kind of bridging the gap to the enterprise, what their thought around Kubernetes, and just really the community in general were. Which was kind of cool because it was all fresh and clean and new for me. So, it was really great to taste the Kool-Aid, and see how delicious it could be. >> Yeah, so I'm curious what your take is. I remember I did a panel at Interop a couple of years ago, and it was like, basically, hyper-scale, you're-not-Google, so what do you need to do, how do you do it, do you just use Google stuff, can you code like Google, can you act like Google, or are you just an enterprise and you're forced to live in the past. >> I think over the last couple of years, the idea of the Sight Reliability Engineers come out and been more focused on the enterprise and kind of dovetailed into the Dev-Op story. So, it was really interesting to hear, not only trying to talk to the enterprise, but also how they're trying to get the enterprise to kind of stop being the traditional enterprise that it's been. Which I think entirely, it's something that we practitioners have always been trying to do. No one wants to be on-call all the time and fixing these flaming disasters and things like that. But at the same time, you have to recognize that moving that much intrinsic culture poison from one side to the next is hard. They're admitting that too, it's like, we wold love for you guys to be more Google-y, and to use the tools that we have here, but we're not sure you even know what the tools are or how to use them, or what kind of documentation is necessary, or what meet-ups we can go to find my people, you know, the practitioners. >> I want to channel our friends, the Geek Whisperers, and alright Chris, so how did you transition out of being a VMware guy to someone that does cool and interesting things now, because VMware is no longer the coolness. >> That's been the vibe, yeah. It's something I personally have been trying to, I don't think in any technology you want to be that technology specific. VMware, love it, have been doing it for 12 something years, but you don't just want to be pigeon-holed in that kind of silo. Which is actually why I wanted to come out and talk with the folks at Google around what they're doing to build a community. I think it was Sam something-or-other-- >> Host: Sam Ramji. >> Sam Ramji actually came up and said, you know, as long as we're going to exist as a company, we're going to have this community day. It's the first one they've done, and they plan to do it basically infinitely forever, because they realized they had the analysts, and things like that out there, they had all the engineers and developers, but what were they missing? The folk in the trenches that are trying to adopt and use this sort of technology. I like that aspect of it. There weren't any huge, mind-shattering results that were out there, except for I think, me personally, I like that Google kind of admitted that yeah, they hadn't been doing the best job around interfacing with the community and getting IT practitioners and operation-centric folks into the fold, welcoming into the bosom of Google, and that they were trying to work on that. And it's like, okay, awesome. Let's have a conversation, which the other half of the day was an un-conference, where we literally broke up into groups, that we decided ourselves as like a democracy of Google decision-making. We formed eight different groups. Some focused on containers, I actually sat in in a two hour session where we just kind of riffed on abstraction layers and where we should we start working. Is it at the container level, is it at the hypervisor level, is it at the virtual machine level? And it was neat because everyone had a completely different idea and background around that. I felt like I was an alien in that conversation for a lot of it 'cause they're working on solving problems that are totally alien to my world. So I liked all that. >> It's an interesting crowd when the server-less stuff got talked about in the keynote today-- >> Yes! >> There was a big clap and I loved Brian Stevens. He's like, functions are just fragments of code, and they get applause, you know, he's kind of like-- (Chris laughs) >> It's like either remark, I got applause for that. >> Yeah, yeah, it's pretty funny. But you know, that's the kind of people that come to this show, right? So, you checked out a thing called, what was it, Code Labs or something like that? Maybe you could talk a little bit about that. >> Yeah, yeah, there was, I had some notes there that I'd written down. Certification in Code Labs, specifically. So Code Labs was interesting 'cause it's a place that you can, you have to book it in advance, like a day in advance, and from about 11 to seven each day, they just have Google-y Google-ers, you know, very Google-y people out there that say alright, here's all our various APIs, such as the new one where you can query a video and say I'm looking for, I think in the keynote, they had "find me baseball" in this video, and it actually shows you in the timeline where baseball occurs. There's also things to do image tagging and things like that. And, I don't know, it might be difficult to grasp that API interaction at first. And so you can sit down, and they'll show you how to write code in the languages of your choice. Obviously Go is very prominent. I'm a PowerShell developer, so it's like, alright, how would you write that in Curl, and that's maybe our bridge to one another, since I don't know Go and they don't know PowerShell, or the person I was working with. So that was cool, to hear how they approach those things, because I've typically done it as an Ops person. I'm typically looking at it from the perspective of I'm trying to automate some task and feed it into an orchestration engine. And I'm not super deep on APIs in general, I like them, but ... That was cool, I liked that you're basically getting to meet with really, really awesome engineers and SREs to pick their brain and their vast decades of experience on writing code. To work with APIs and things that are Google-centric. So that was awesome. >> So it sounds like you didn't feel like this was a marketing show, right, - [Chris] No! >> that they bring in the engineers, the technical people, I mean it's not far being from San Franscisco from the Google-Plex, the Mothership is nearby. >> Thats's a good point because a lot of these shows have just become a sales pitch in a wolf's clothing or a conference clothing, and this was ... I've never met so many really, really talented engineers all concentrated in one spot. I mean, you've got the rock stars that I think everybody knows, like Sarah, and Kelsey, that are very available and personable, but you also have a whole army of people that have a huge amount of passion around writing code and understand what your problems are and wanting to talk to you. I felt like a person, which I've been a Google customer since, I guess, Google came out, you know, Google apps and things like that. This is really the first time I really started putting faces to the technical practitioners that work there, and they're really interested and excited with what my mundane kind of problems. So, that's kind of cool. >> Yeah, I found they're definitely, they're listening, they're talking, it's really good, because right, we at our firm, we've used Google for a while and it's like, oh wait I have a challenge. Who do I call, who do I email? Nope, you should just watch the YouTube video and use it. C'mon, aren't you smart enough to use these things right? You know, was kind of how we all felt for a while. Interesting. Kinder, gentler Google than we've knew in the past? >> They had the Google leaders circle and the various groups that you could join online, but it was just, you can't fake that kind of raw passion, and I sat down with some of the SREs at the community day, and it was really just, talk to me about what you do, and why, and what tools you use, and what can we do to be better? More specifically, the Dev Rel, the developer relations folks were just awesome. And they're like, is our title threatening? What meet-up should we go to? What can we do to make your life better? And I just kind of, at first, said a few comments and realized, no, this is real. They want to know my day one and day two operations, so that they can find the right tools, or if there isn't one, build one. And I don't know, that's great. I've never seen that at a conference before. So I'm hooked. I definitely plan to go again. >> Alright, so anything you didn't see that you were hoping to see, follow-up that you want to have, other cool stuff going on that you want to share? >> I almost want to do like a plea to Google that throughout the community today and at the conference, there's been a lot of commentary and some, kind of some references to, oh we don't want to tell you how to do things, we don't want to tell you how to build architecture in a certain way. Please do tell me how to do those things. At least give me a reference architecture, or some example environments, because I feel like a lot of it is just, here's some cool things you can do, kind of in isolation. Or here are some things with Kubernetes that kind of exist outside of reality. I'm looking for, alright, I don't have any of that stuff, how do I onboard into that? Here's a white paper, and that kind of jazz. >> Yeah, and we saw, you know, I hate to always bring up AWS, but AWS went from here's this giant toolbox with all these things to right, here's some services, here are some tracks, here are some, not wizards, but you know, templates you can follow for certain things. Here are people that are probably similar to you and, boy, with Google with their AI and ML and all their things that they can do to help us sort out all the TLAs that they've got to. (Chris laughs) You know, they should be able to help going forward because, yeah, Google should be able to personalize all that to be able to work a little bit better for us as opposed to us having to just kind of figure it out a little bit. I know you played with the Google Cloud a little bit yourself-- - Yeah. >> And it wasn't as simple as you were hoping, right? >> It was hard. (both laugh) I mean-- >> Host: C'mon, if you can't figure it out, you know-- >> I don't feel like I'm the sharpest tool in the shed, but I was like, I'm kind of the representative layman ops person, and it felt very convoluted, complex, the documentation was fragmented. I'm like, just give me the wizard so that I can start fishing for myself. I just do that first hit for free, and then I'll take care of it beyond that. So, that would be my one ask to Google as a whole, but otherwise I think the tooling and the people, and the culture are all there, it's just build a few more things and I think we've got some interesting entanglements at the enterprise level once that's done. >> Okay, want to give me the final word, what's going on with you other than, your hometown, your new hometown of Austin, Texas. South By coming, so I know there's a lot of music and fun going on but, what's happening in your world, what's happening with Rubrik? >> Oh yeah, I'll mention South By, definitely will be there, I will not be available online or anything. I'm going to be going into sequester mode and just listen to music with my co-host actually. If you listen to the Datanauts podcast, with Ethan Banks, he's going to come by. So, we'll be at the show I guess if you want to hang out with us, hit us up. Otherwise, Rubrik's been awesome. It's definitely a rocket ship ride and it was actually dove-tailed into quite a few conversations I had while at Google Next. Because movement of data into and around clouds is non-trivial, so that's where the Cloud Data Management world that we're in, kind of fits into that equation, and why I personally wanted to go to this show, but also professionally I thought that there'd be some inroads there to discuss with the other practitioners. >> Absolutely, the whole infrastructure side and how that plays in the public cloud, how it plays with Sass, there's a lot of those discussions going on. Congrats, you guys have been growing some good buzz. You guys have been hiring, too, so check Chris out for all that. We'll be back, lots more coverage here of the Google Cloud Next 2017, you're watching theCUBE. (funky techno music)