 Live from Las Vegas, it's theCUBE, covering AWS re-invent 2017, presented by AWS, Intel, and our ecosystem of partners. And we are live back here in Las Vegas, the sand's exposed, we continue our coverage here on theCUBE of re-invent. AWS here on the fourth day of what has been a very successful show. Still fair, a lot of buzz, a lot of activity on the show for certainly indicative of what's happened here in terms of bringing this community together in a very positive way. I'm with Justin Warren, I'm John Walls, we go from Justin to Dustin, Dustin Kirkland, who's the Vice President of Product Development for Ubuntu on the Canonical, and Dustin, good to see you again. Likewise, John. I should let the two of you probably chat about Australia. We heard these great diving stories about your adventures, your home, your native country. Maybe afterwards you get a little photos travel thing going on. Yeah, that's right. All right, so you said 17 years, you've been diving. We got to get into that a little bit later on. First off, let's talk about Ubuntu and maybe like the footprint with NAWS. Not only what brings you here, but what gets you there? What are you doing there? Yeah, first of all, this fantastic conference. I mean, hundreds of these organizations here are involved in Ubuntu, using Ubuntu, NAWS, taking advantage of open source, using it for lots of scale-out services. To date this year in 2017, over 125 million instances of Ubuntu have launched in NAWS alone, just this year. And the year's not even over yet. We see anything from media and entertainment. Netflix is here, I spent some time with them. One of Netflix's performance engineers gave a talk yesterday about how Netflix tunes their Ubuntu instances in Amazon to the tune of 100,000 instances of Ubuntu running in Amazon to deliver the Netflix experience that I'm sure all of us have. 100,000? Yeah, that's amazing. It's crazy. Yeah, I'm a big fan of Ubuntu because I am a mad person. I've been running it as my primary desktop for something like 10 years. Oh, right. I run it on a laptop. Okay. Love it, it's great. Good, so what, I mean, people use Ubuntu all the time. It's like, it just became the de facto, seems like overnight of pretty much, hey, if you want to run Linux in cloud, you just, hey, spin up in Ubuntu. Sure. Run it up. So what is it about Ubuntu itself that where are you taking the product for people who are using it in cloud? I mean, we're hearing a lot about all these different services and we're hearing about serverless. So how does Ubuntu fit into that AWS world? That's a great question. First of all, it's not overnight. We've been doing this since 2004. So we're going on 14 years of building the thing that is Ubuntu. We brought Ubuntu into Amazon in about 2008, which is right when I got involved at Canonical. I was working on Ubuntu before that, but working for Canonical. And that was relatively early in the entire Amazon adventure. You said Ubuntu on the desktop. That's certainly where Ubuntu got its start. But it was Amazon that really busted Ubuntu out into the server space. And so now, as you said, if you're starting a new company or new technology, you almost by default start on Ubuntu, right? Now, where are we taking that, right? Here we're talking about cloud, but the other half of cloud is the edge. The edge being embedded devices, embedded IoT connected devices. The thing about every IoT device, right? The I in IoT is internet, right? The connected part of a connected device means it has to be connected to something. And what's it going to be connected to? The cloud. So every smart autonomous driving vehicle, every oil rig out in West Texas, every airplane, every boat, every ship, every place where you're going to find compute in these next couple of years as we move into the 5G revolution are connected to services on the back end. The majority of those hosted in Amazon and the majority of those running Ubuntu. So when you're talking about IoT though, I mean, what kind of challenges now does that bring into your world? Because you're talking about this, I mean, I can't even think about the order. Right, billions, literally billions. I mean, just a massive connectivity and in a mobile environment, throw that on top of that. So what does that do for you then, in terms of what you're looking at down the road and the kind of capabilities you got to build in? Security, I mean, it starts with security. When we think about devices in our homes, accompanying our kids to school, devices that are inside of buses and hospitals, it's all about security and security is first and foremost. We put a lot of effort into securing Ubuntu. We've created new features, part of where we're taking Ubuntu. Many of the new features we've created around Ubuntu are about updates, security updates, being able to make those updates active without rebooting the system. So zero downtime kernel updates is something we call the live patch service which we deliver in Amazon for Ubuntu Amazon users. Extended security maintenance, security for Ubuntu after end of life. So you said you've been using Ubuntu for a long time. Each Ubuntu release has basically a five year life cycle, right? But some enterprises actually need to run Ubuntu for much longer than five years. And for those enterprises, we provide security updates after the end of life, after that five year end of life. And in many cases that helps them bridge that gap until the next release of Ubuntu. We've also worked with IBM and the US government to provide FIPS certified cryptography for Ubuntu, also available in Amazon. So department of defense contractors, many federal contractors are required to use FIPS bits. And this actually allows them to bring their Ubuntu usage into compliance with what's required for government regulations. I am so glad that you went from IoT to security in like a nanosecond, because that was going to be my next question. That's the only answer to that. I mean, that's the only right answer to that question in my mind. One of the companies put that much focus on security and that you follow it up with specific concrete examples of things that are going to work, like the live kernel patching without rebooting things so that you can have the, I mean, services in the cloud, it has to be always on. You can't take a maintenance window where something is down for hours or a weekend. That's just not acceptable in the cloud world anymore. Especially in the retail season. We're just now getting into the recent, Black Friday was last week, Cyber Monday, this week we're in the roll up all the way to Christmas. Canonical works quite a bit with many of the largest retailers in the world, right? Walmart, Best Buy, other ones like that, and downtime is just not acceptable, right? At the same time, security is of the utmost importance when you're taking people's credit cards, you're placing a large amounts of money on the line every time these transactions take place, security has to be utmost. And being able to do that without impacting the downtime, downtime is seriously hundreds of thousands of dollars per second on some of these sites during the major holiday rush. And you were just talking about some of the big names that you're working with, so what kind of assurance can you give them that you can sleep with both eyes closed, right? You have to keep that one eye open, don't worry that if there is an incident of some kind, we're going to take care of it. You have a problem, rest assured, we're going to be there, because as you pointed out with the volume involved and the other issues of security infiltrations be what they are today, it's hard to rest. Right, now the return on value, the return on investment of the live patch is easily apparent. Anytime someone does the math and realizes, let's actually look at how much it costs us to reboot a data center, or how much it costs us to wake up the DevOps team on a Saturday, have them work through a weekend to roll out this update, whereas with the live patch, at least the patch is applied in milliseconds without downtime, and then we get back on Monday and we roll out a comprehensive plan as to, okay, now what do we actually need to do about this going forward? That's for the kernel side of things. The other half of it is the user space side of Ubuntu. In the user space side of Ubuntu, we continue to make Ubuntu smaller, smaller and smaller. That might have been one of the reasons you were attracted to Ubuntu on your laptop early on is because we really did a good job of making a Linux that was consumable, usable, but also very small and secure. We've actually taken that same approach in the cloud where we continue to minimize the footprint of Ubuntu. That has a security impact in that if you simply leave software out of the default image, you're not vulnerable to problems in that software. So we've heard that quite a bit around the container space, the work we do in the container space. We'll be in Austin next week for KubeCon talking about containers, so I'll save the container talk for next week, but minimizing Ubuntu is an important part of that security story as well. All right, just reducing that attack surface is fabulous. It also means that when you're actually doing this patching and it's less things to patch, there's less opportunities for downtime, there's less things that can go wrong and cause outages in the rest of the place. Simple is better. That's right. Exactly right. Yeah, so what else are you doing? So we've talked about security a lot here, and what are some of the other things that you're doing around supporting the services that we're hearing here at AWS? We've heard a lot about things like serverless. We've heard a lot about high-performance computing. We've had guests here on theCUBE. We're talking about what they're doing around data and analytics and machine learning. So maybe you could give us a bit of color around that. Let's start with that last point, machine learning and data analytics. So we worked very closely with both Amazon and NVIDIA to enable the GP GPUs, the general-purpose graphic processing units that NVIDIA produces, which go into servers, and Amazon exposes in some of their largest machine learning-type instances, okay? Those instances powered by Ubuntu are working directly with that GPU out of the box, by default. And that's something that we've worked very hard on and closely with both Amazon and NVIDIA to ensure that the Ubuntu experience when using the graphics-accelerated instance types just work and just work out of the box. Those are important for the machine learning and the data analytics because many of those algorithms take advantage of CUDA. CUDA is a set of libraries that allows developers to write applications that scale very, very wide across the CUDA cores. So given NVIDIA GPU may have several thousand NVIDIA CUDA cores, each of those are running little process bits and then the answers are summed up basically at the end. That is at the heart of everything that's happening in the AI space. And then I'll tie that back to our IoT space in that for those connected devices where memory disk CPU power are very constrained, part of the important point of that connection is that they're talking to a cloud that has essentially infinite resources, infinite data at its disposal, enough memory to load those entire data sets and crunch those. The fastest CPUs and the fastest GPUs, that can crunch that data. So to really take that and make that real, that's exactly what's powering every autonomous vehicle in the world essentially is a little unit inside of the car. The majority of those autonomous vehicles are running Ubuntu on the auto driving unit, Tesla, Google, Uber, all running the Ubuntu on inside of that car. Now every one of those cards are talking to a cloud. Some clouds are Amazon, other in Google's case, certainly the Google cloud, but they're talking to GPU, Nvidia powered AI instances that are crunching all the data that these Tesla cars and GM and Ford cars are sending to the cloud and constantly making the inference engine better. What gets downloaded to the car is an updated inference engine. That inference engine comes down to the car and that's how that car decides is it safe to change lanes right now or not. That answer has to be determined inside of the car, not in the cloud, but you can understand why data training and modeling in the cloud is powerful, far more powerful than what could happen inside of a little CPU in a car. Let's just keep it on the right side of the road. Can we do that? Well, you need to talk to this gentleman about that. I don't know what the right side, or the left side of the road. Don't cross the streams. How about the correct side of the road? Don't cross the streams. Dustin, thanks for the time. Thank you, John. Always good seeing you. And we'll see you next week as well. Down in your hometown, little barbecue at Austin. Sounds good then. All right, back with more here from ReInvent. We're live in Las Vegas, back with more on theCUBE in just a bit.