>> Hello everyone and welcome back to theCUBE, where we're live from Dallas, Texas here at Super computing 2022. I am joined by my cohost David Nicholson. Thank you so much for being here with me and putting up with my trashy jokes all day. >> David: Thanks for having me. >> Yeah. Yes, we are going to be talking about AI this morning and I'm very excited that our guest has has set the stage for us here quite well. Please welcome Andrea Booker. Andrea, thank you so much for being here with us. >> Absolutely. Really excited to be here. >> Savannah: How's your show going so far? >> It's been really cool. I think being able to actually see people in person but also be able to see the latest technologies and and have the live dialogue that connects us in a different way than we have been able to virtually. >> Savannah: Oh yeah. No, it's all, it's all about that human connection and that it is driving towards our first question. So as we were just chit chatting. You said you are excited about making AI real and humanizing that. >> Andrea: Absolutely. >> What does that mean to you? >> So I think when it comes down to artificial intelligence it means so many different things to different people. >> Savannah: Absolutely. >> I was talking to my father the other day for context, he's in his late seventies, right. And I'm like, oh, artificial intelligence, this or that, and he is like, machines taking over the world. Right. >> Savannah: Very much the dark side. >> A little bit Terminator. And I'm like, well, not so much. So that was a fun discussion. And then you flip it to the other side and I'm talking to my 11 year old daughter and she's like, Alexa make sure you know my song preferences. Right. And that's the other very real way in which it's kind of impacting our lives. >> Savannah: Yeah. >> Right. There's so many different use cases that I don't think everyone understands how that resonates. Right. It's the simple things from, you know, recommend Jason Engines when you're on Amazon and it suggests just a little bit more. >> Oh yeah. >> I'm a little bit to you that one, right. To stuff that's more impactful in regards to getting faster diagnoses from your doctors. Right. Such peace of mind being able to actually hear that answer faster know how to go tackle something. >> Savannah: Great point, yeah. >> You know, and, and you know, what's even more interesting is from a business perspective, you know the projections are over the next five years about 90% of customers are going to use AI applications in in some fashion, right. >> Savannah: Wow. >> And the reason why that's interesting is because if you look at it today, only about 15% of of them are doing so. Right. So we're early. So when we're talking growth and the opportunity, it's, it's amazing. >> Yeah. I can, I can imagine. So when you're talking to customers, what are are they excited? Are they nervous? Are you educating them on how to apply Dell technology to advance their AI? Where are they off at because we're so early? >> Yeah well, I think they're figuring it out what it means to them, right? >> Yeah. Because there's so many different customer applications of it, right? You have those in which, you know, are on on the highest end in which that our new XE products are targeting that when they think of it. You know, I I, I like to break it down in this fashion in which artificial intelligence can actually save human lives, right? And this is those extreme workloads that I'm talking about. We actually can develop a Covid vaccine faster, right. Pandemic tracking, you know with global warming that's going on. And we have these extreme weather events with hurricanes and tsunamis and all these things to be able to get advanced notice to people to evacuate, to move. I mean, that's a pretty profound thing. And it is, you know so it could be used in that way to save lives, right? >> Absolutely. >> Which is it's the natural outgrowth of the speeds and feeds discussions that we might have internally. It's, it's like, oh, oh, speed doubled. Okay. Didn't it double last year? Yeah. Doubled last year too. So it's four x now. What does that mean to your point? >> Andrea: Yeah, yeah. >> Savannah: Yeah. >> Being able to deliver faster insight insights that are meaningful within a timeframe when otherwise they wouldn't be meaningful. >> Andrea: Yeah. >> If I tell you, within a two month window whether it's going to rain this weekend, that doesn't help you. In hindsight, we did the calculation and we figured out it's going to be 40 degrees at night last Thursday >> Knowing it was going to completely freeze here in Dallas to our definition in Texas but we prepare better to back to bring clothes. >> We were talking to NASA about that yesterday too. I mean, I think it's, it's must be fascinating for you to see your technology deployed in so many of these different use cases as well. >> Andrea: Absolutely, absolutely. >> It's got to be a part of one of the more >> Andrea: Not all of them are extreme, right? >> Savannah: Yeah. >> There's also examples of, you know natural language processing and what it does for us you know, the fact that it can break down communication barriers because we're global, right? We're all in a global environment. So if you think about conference calls in which we can actually clearly understand each other and what the intent is, and the messaging brings us closer in different ways as well. Which, which is huge, right? You don't want things lost in translation, right? So it, it helps on so many fronts. >> You're familiar with the touring test idea of, of, you know whether or not, you know, the test is if you can't discern within a certain number of questions that you're interacting with an AI versus a real human, then it passes the touring test. I think there should be a natural language processing test where basically I say, fine >> Andrea: You see if people was mad or not. >> You tell me, you tell me. >> I love this idea, David. >> You know? >> Yeah. This is great. >> Okay. AI lady, >> You tell me what I meant. >> Yeah, am I actually okay? >> How far from, that's silly example but how far do you think we are from that? I mean, what, what do you seeing out there in terms of things where you're kind of like, whoa, they did this with technology I'm responsible for, that was impressive. Or have you heard of things that are on the horizon that, you know, again, you, you know they're the big, they're the big issues. >> Yeah. >> But any, anything kind of interesting and little >> I think we're seeing it perfected and tweaked, right? >> Yeah. >> You know, I think going back to my daughter it goes from her screaming at Alexa 'cause she did hear her right the first time to now, oh she understands and modifies, right? Because we're constantly tweaking that technology to have a better experience with it. And it's a continuum, right? The voice to text capabilities, right. You know, I I'd say early on it got most of those words, right Right now it's, it's getting pretty dialed in. Right. >> Savannah: That's a great example. >> So, you know, little things, little things. >> Yeah. I think I, I love the, the this thought of your daughter as the example of training AI. What, what sort of, you get to look into the future quite a bit, I'm sure with your role. >> Andrea: Absolutely. >> Where, what is she going to be controlling next? >> The world. >> The world. >> No, I mean if you think about it just from a generational front, you know technology when I was her age versus what she's experiencing, she lives and breathes it. I mean, that's the generational change. So as these are coming out, you have new folks growing with it that it's so natural that they are so open to adopting it in their common everyday behaviors. Right? >> Savannah: Yeah. >> But they'd they never, over time they learn, oh well how it got there is 'cause of everything we're doing now, right. >> Savannah: Yeah. >> You know, one, one fun example, you know as my dad was like machines are taking over the world is not, not quite right. Even if when you look at manufacturing, there's a difference in using AI to go build a digital simulation of a factory to be able to optimize it and design it right before you're laying the foundation that saves cost, time and money. That's not taking people's jobs in that extreme event. >> Right. >> It's really optimizing for faster outcomes and, and and helping our customers get there which is better for everyone. >> Savannah: Yeah and safer too. I mean, using the factory example, >> Totally safer. >> You're able to model out what a workplace injury might be or what could happen. Or even the ergonomics of how people are using. >> Andrea: Yeah, should it be higher so they don't have to bend over? Right. >> Exactly. >> There's so many fantastic positive ways. >> Yeah so, so for your dad, you know, I mean it's going to help us, it's going to make, it's going to take away when I. Well I'm curious what you think, David when I think about AI, I think it's going to take out a lot of the boring things in life that, that we don't like >> Andrea: Absolutely. Doing. The monotony and the repetitive and let us optimize our creative selves maybe. >> However, some of the boring things are people's jobs. So, so it is, it it it will, it will it will push a transition in our economy in the global economy, in my opinion. That would be painful for some, for some period of time. But overall beneficial, >> Savannah: Yes. But definitely as you know, definitely there will be there will be people who will be disrupted and, you know. >> Savannah: Tech's always kind of done that. >> We No, but we need, I, I think we need to make sure that the digital divide doesn't get so wide that you know that, that people might not be negative, negatively affected. And, but, but I know that like organizations like Dell I believe what you actually see is, >> Andrea: Yeah. >> No, it's, it's elevating people. It's actually taking away >> Andrea: Easier. >> Yeah. It's, it's, it's allowing people to spend their focus on things that are higher level, more interesting tasks. >> Absolutely. >> David: So a net, A net good. But definitely some people disrupted. >> Yes. >> I feel, I feel disrupted. >> I was going to say, are, are we speaking for a friend or for ourselves here today on stage? >> I'm tired of software updates. So maybe if you could, if you could just standardize. So AI and ML. >> Andrea: Yeah. >> People talk about machine learning and, and, and and artificial intelligence. How would you differentiate the two? >> Savannah: Good question. >> It it, it's, it's just the different applications and the different workloads of it, right? Because you actually have artificial intelligence you have machine learning in which the learn it's learning from itself. And then you have like the deep learning in which it's diving deeper in in its execution and, and modeling. And it really depends on the workload applications as long as well as how large the data set is that's feeding into it for those applications. Right. And that really leads into the, we have to make sure we have the versatility in our offerings to be able to meet every dimension of that. Right. You know our XE products that we announced are really targeted for that, those extreme AI HPC workloads. Right. Versus we also have our entire portfolio products that we make sure we have GPU diversity throughout for the other applications that may be more edge centric or telco centric, right? Because AI isn't just these extreme situations it's also at the edge. It's in the cloud, it's in the data center, right? So we want to make sure we have, you know versatility in our offerings and we're really meeting customers where they're at in regards to the implementation and and the AI workloads that they have. >> Savannah: Let's dig in a little bit there. So what should customers expect with the next generation acceleration trends that Dell's addressing in your team? You had three exciting product announcements here >> Andrea: We did, we did. >> Which is very exciting. So you can talk about that a little bit and give us a little peek. >> Sure. So, you know, for, for the most extreme applications we have the XE portfolio that we built upon, right? We already had the XC 85 45 and we've expanded that out in a couple ways. The first of which is our very first XC 96 88 way offering in which we have Nvidia's H 100 as well as 8 100. 'Cause we want choice, right? A choice between performance, power, what really are your needs? >> Savannah: Is that the first time you've combined? >> Andrea: It's the first time we've had an eight way offering. >> Yeah. >> Andrea: But we did so mindful that the technology is emerging so much from a thermal perspective as well as a price and and other influencers that we wanted that choice baked into our next generation of product as we entered the space. >> Savannah: Yeah, yeah. >> The other two products we have were both in the four way SXM and OAM implementation and we really focus on diversifying and not only from vendor partnerships, right. The XC 96 40 is based off Intel Status Center max. We have the XE 86 40 that is going to be in or Nvidia's NB length, their latest H 100. But the key differentiator is we have air cold and we have liquid cold, right? So depending on where you are from that data center journey, I mean, I think one of the common themes you've heard is thermals are going up, performance is going up, TBPs are going up power, right? >> Savannah: Yeah. >> So how do we kind of meet in the middle to be able to accommodate for that? >> Savannah: I think it's incredible how many different types of customers you're able to accommodate. I mean, it's really impressive. I feel lucky we've gotten to see these products you're describing. They're here on the show floor. There's millions of dollars of hardware literally sitting in your booth. >> Andrea: Oh yes. >> Which is casual only >> Pies for you. Yeah. >> Yeah. We were, we were chatting over there yesterday and, and oh, which, which, you know which one of these is more expensive? And the response was, they're both expensive. It was like, okay perfect >> But assume the big one is more. >> David: You mentioned, you mentioned thermals. One of the things I've been fascinated by walking around is all of the different liquid cooling solutions. >> Andrea: Yeah. >> And it's almost hysterical. You look, you look inside, it looks like something from it's like, what is, what is this a radiator system for a 19th century building? >> Savannah: Super industrial? >> Because it looks like Yeah, yeah, exactly. Exactly, exactly. It's exactly the way to describe it. But just the idea that you're pumping all of this liquid over this, over this very, very valuable circuitry. A lot of the pitches have to do with, you know this is how we prevent disasters from happening based on the cooling methods. >> Savannah: Quite literally >> How, I mean, you look at the power requirements of a single rack in a data center, and it's staggering. We've talked about this a lot. >> Savannah: Yeah. >> People who aren't kind of EV you know electric vehicle nerds don't appreciate just how much power 90 kilowatts of power is for an individual rack and how much heat that can generate. >> Andrea: Absolutely. >> So Dell's, Dell's view on this is air cooled water cooled figure it out fit for for function. >> Andrea: Optionality, optionality, right? Because our customers are a complete diverse set, right? You have those in which they're in a data center 10 to 15 kilowatt racks, right? You're not going to plum a liquid cool power hungry or air power hungry thing in there, right? You might get one of these systems in, in that kind of rack you know, architecture, but then you have the middle ground the 50 to 60 is a little bit of choice. And then the super extreme, that's where liquid cooling makes sense to really get optimized and have the best density and, and the most servers in that solution. So that's why it really depends, and that's why we're taking that approach of diversity, of not only vendors and, and choice but also implementation and ways to be able to address that. >> So I think, again, again, I'm, you know electric vehicle nerd. >> Yeah. >> It's hysterical when you, when you mention a 15 kilowatt rack at kind of flippantly, people don't realize that's way more power than the average house is consuming. >> Andrea: Yeah, yeah >> So it's like your entire house is likely more like five kilowatts on a given day, you know, air conditioning. >> Andrea: Maybe you have still have solar panel. >> In Austin, I'm sorry >> California, Austin >> But, but, but yeah, it's, it's staggering amounts of power staggering amounts of heat. There are very real problems that you guys are are solving for to drive all of these top line value >> Andrea: Yeah. >> Propositions. It's super interesting. >> Savannah: It is super interesting. All right, Andrea, last question. >> Yes. Yes. >> Dell has been lucky to have you for the last decade. What is the most exciting part about you for the next decade of your Dell career given the exciting stuff that you get to work on. >> I think, you know, really working on what's coming our way and working with my team on that is is just amazing. You know, I can't say it enough from a Dell perspective I have the best team. I work with the most, the smartest people which creates such a fun environment, right? So then when we're looking at all this optionality and and the different technologies and, and, and you know partners we work with, you know, it's that coming together and figuring out what's that best solution and then bringing our customers along that journey. That kind of makes it fun dynamic that over the next 10 years, I think you're going to see fantastic things. >> David: So I, before, before we close, I have to say that's awesome because this event is also a recruiting event where some of these really really smarts students that are surrounding us. There were some sirens going off. They're having competitions back here. >> Savannah: Yeah, yeah, yeah. >> So, so when they hear that. >> Andrea: Where you want to be. >> David: That's exactly right. That's exactly right. >> Savannah: Well played. >> David: That's exactly right. >> Savannah: Well played. >> Have fun. Come on over. >> Well, you've certainly proven that to us. Andrea, thank you so much for being with us This was such a treat. David Nicholson, thank you for being here with me and thank you for tuning in to theCUBE a lot from Dallas, Texas. We are all things HPC and super computing this week. My name's Savannah Peterson and we'll see you soon. >> Andrea: Awesome.

>> Hi, my name is Andy Clemenko. I'm a Senior Solutions Engineer at StackRox. Thanks for joining us today for my talk on labels, labels, labels. Obviously, you can reach me at all the socials. Before we get started, I like to point you to my GitHub repo, you can go to andyc.info/dc20, and it'll take you to my GitHub page where I've got all of this documentation, socials. Before we get started, I like to point you to my GitHub repo, you can go to andyc.info/dc20, (upbeat music) >> Hi, my name is Andy Clemenko. I'm a Senior Solutions Engineer at StackRox. Thanks for joining us today for my talk on labels, labels, labels. Obviously, you can reach me at all the socials. Before we get started, I like to point you to my GitHub repo, you can go to andyc.info/dc20, and it'll take you to my GitHub page where I've got all of this documentation, I've got the Keynote file there. YAMLs, I've got Dockerfiles, Compose files, all that good stuff. If you want to follow along, great, if not go back and review later, kind of fun. So let me tell you a little bit about myself. I am a former DOD contractor. This is my seventh DockerCon. I've spoken, I had the pleasure to speak at a few of them, one even in Europe. I was even a Docker employee for quite a number of years, providing solutions to the federal government and customers around containers and all things Docker. So I've been doing this a little while. One of the things that I always found interesting was the lack of understanding around labels. So why labels, right? Well, as a former DOD contractor, I had built out a large registry. And the question I constantly got was, where did this image come from? How did you get it? What's in it? Where did it come from? How did it get here? And one of the things we did to kind of alleviate some of those questions was we established a baseline set of labels. Labels really are designed to provide as much metadata around the image as possible. I ask everyone in attendance, when was the last time you pulled an image and had 100% confidence, you knew what was inside it, where it was built, how it was built, when it was built, you probably didn't, right? The last thing we obviously want is a container fire, like our image on the screen. And one kind of interesting way we can kind of prevent that is through the use of labels. We can use labels to address security, address some of the simplicity on how to run these images. So think of it, kind of like self documenting, Think of it also as an audit trail, image provenance, things like that. These are some interesting concepts that we can definitely mandate as we move forward. What is a label, right? Specifically what is the Schema? It's just a key-value. All right? It's any key and pretty much any value. What if we could dump in all kinds of information? What if we could encode things and store it in there? And I've got a fun little demo to show you about that. Let's start off with some of the simple keys, right? Author, date, description, version. Some of the basic information around the image. That would be pretty useful, right? What about specific labels for CI? What about a, where's the version control? Where's the source, right? Whether it's Git, whether it's GitLab, whether it's GitHub, whether it's Gitosis, right? Even SPN, who cares? Where are the source files that built, where's the Docker file that built this image? What's the commit number? That might be interesting in terms of tracking the resulting image to a person or to a commit, hopefully then to a person. How is it built? What if you wanted to play with it and do a git clone of the repo and then build the Docker file on your own? Having a label specifically dedicated on how to build this image might be interesting for development work. Where it was built, and obviously what build number, right? These kind of all, not only talk about continuous integration, CI but also start to talk about security. Specifically what server built it. The version control number, the version number, the commit number, again, how it was built. What's the specific build number? What was that job number in, say, Jenkins or GitLab? What if we could take it a step further? What if we could actually apply policy enforcement in the build pipeline, looking specifically for some of these specific labels? I've got a good example of, in my demo of a policy enforcement. So let's look at some sample labels. Now originally, this idea came out of label-schema.org. And then it was a modified to opencontainers, org.opencontainers.image. There is a link in my GitHub page that links to the full reference. But these are some of the labels that I like to use, just as kind of like a standardization. So obviously, Author's, an email address, so now the image is attributable to a person, that's always kind of good for security and reliability. Where's the source? Where's the version control that has the source, the Docker file and all the assets? How it was built, build number, build server the commit, we talked about, when it was created, a simple description. A fun one I like adding in is the healthZendpoint. Now obviously, the health check directive should be in the Docker file. But if you've got other systems that want to ping your applications, why not declare it and make it queryable? Image version, obviously, that's simple declarative And then a title. And then I've got the two fun ones. Remember, I talked about what if we could encode some fun things? Hypothetically, what if we could encode the Compose file of how to build the stack in the first image itself? And conversely the Kubernetes? Well, actually, you can and I have a demo to show you how to kind of take advantage of that. So how do we create labels? And really creating labels as a function of build time okay? You can't really add labels to an image after the fact. The way you do add labels is either through the Docker file, which I'm a big fan of, because it's declarative. It's in version control. It's kind of irrefutable, especially if you're tracking that commit number in a label. You can extend it from being a static kind of declaration to more a dynamic with build arguments. And I can show you, I'll show you in a little while how you can use a build argument at build time to pass in that variable. And then obviously, if you did it by hand, you could do a docker build--label key equals value. I'm not a big fan of the third one, I love the first one and obviously the second one. Being dynamic we can take advantage of some of the variables coming out of version control. Or I should say, some of the variables coming out of our CI system. And that way, it self documents effectively at build time, which is kind of cool. How do we view labels? Well, there's two major ways to view labels. The first one is obviously a docker pull and docker inspect. You can pull the image locally, you can inspect it, you can obviously, it's going to output as JSON. So you going to use something like JQ to crack it open and look at the individual labels. Another one which I found recently was Skopeo from Red Hat. This allows you to actually query the registry server. So you don't even have to pull the image initially. This can be really useful if you're on a really small development workstation, and you're trying to talk to a Kubernetes cluster and wanting to deploy apps kind of in a very simple manner. Okay? And this was that use case, right? Using Kubernetes, the Kubernetes demo. One of the interesting things about this is that you can base64 encode almost anything, push it in as text into a label and then base64 decode it, and then use it. So in this case, in my demo, I'll show you how we can actually use a kubectl apply piped from the base64 decode from the label itself from skopeo talking to the registry. And what's interesting about this kind of technique is you don't need to store Helm charts. You don't need to learn another language for your declarative automation, right? You don't need all this extra levels of abstraction inherently, if you use it as a label with a kubectl apply, It's just built in. It's kind of like the kiss approach to a certain extent. It does require some encoding when you actually build the image, but to me, it doesn't seem that hard. Okay, let's take a look at a demo. And what I'm going to do for my demo, before we actually get started is here's my repo. Here's a, let me actually go to the actual full repo. So here's the repo, right? And I've got my Jenkins pipeline 'cause I'm using Jenkins for this demo. And in my demo flask, I've got the Docker file. I've got my compose and my Kubernetes YAML. So let's take a look at the Docker file, right? So it's a simple Alpine image. The org statements are the build time arguments that are passed in. Label, so again, I'm using the org.opencontainers.image.blank, for most of them. There's a typo there. Let's see if you can find it, I'll show you it later. My source, build date, build number, commit. Build number and get commit are derived from the Jenkins itself, which is nice. I can just take advantage of existing URLs. I don't have to create anything crazy. And again, I've got my actual Docker build command. Now this is just a label on how to build it. And then here's my simple Python, APK upgrade, remove the package manager, kind of some security stuff, health check getting Python through, okay? Let's take a look at the Jenkins pipeline real quick. So here is my Jenkins pipeline and I have four major stages, four stages, I have built. And here in build, what I do is I actually do the Git clone. And then I do my docker build. From there, I actually tell the Jenkins StackRox plugin. So that's what I'm using for my security scanning. So go ahead and scan, basically, I'm staging it to scan the image. I'm pushing it to Hub, okay? Where I can see the, basically I'm pushing the image up to Hub so such that my StackRox security scanner can go ahead and scan the image. I'm kicking off the scan itself. And then if everything's successful, I'm pushing it to prod. Now what I'm doing is I'm just using the same image with two tags, pre-prod and prod. This is not exactly ideal, in your environment, you probably want to use separate registries and non-prod and a production registry, but for demonstration purposes, I think this is okay. So let's go over to my Jenkins and I've got a deliberate failure. And I'll show you why there's a reason for that. And let's go down. Let's look at my, so I have a StackRox report. Let's look at my report. And it says image required, required image label alert, right? Request that the maintainer, add the required label to the image, so we're missing a label, okay? One of the things we can do is let's flip over, and let's look at Skopeo. Right? I'm going to do this just the easy way. So instead of looking at org.zdocker, opencontainers.image.authors. Okay, see here it says build signature? That was the typo, we didn't actually pass in. So if we go back to our repo, we didn't pass in the the build time argument, we just passed in the word. So let's fix that real quick. That's the Docker file. Let's go ahead and put our dollar sign in their. First day with the fingers you going to love it. And let's go ahead and commit that. Okay? So now that that's committed, we can go back to Jenkins, and we can actually do another build. And there's number 12. And as you can see, I've been playing with this for a little bit today. And while that's running, come on, we can go ahead and look at the Console output. Okay, so there's our image. And again, look at all the build arguments that we're passing into the build statement. So we're passing in the date and the date gets derived on the command line. With the build arguments, there's the base64 encoded of the Compose file. Here's the base64 encoding of the Kubernetes YAML. We do the build. And then let's go down to the bottom layer exists and successful. So here's where we can see no system policy violations profound marking stack regimes security plugin, build step as successful, okay? So we're actually able to do policy enforcement that that image exists, that that label sorry, exists in the image. And again, we can look at the security report and there's no policy violations and no vulnerabilities. So that's pretty good for security, right? We can now enforce and mandate use of certain labels within our images. And let's flip back over to Skopeo, and let's go ahead and look at it. So we're looking at the prod version again. And there's it is in my email address. And that validated that that was valid for that policy. So that's kind of cool. Now, let's take it a step further. What if, let's go ahead and take a look at all of the image, all the labels for a second, let me remove the dash org, make it pretty. Okay? So we have all of our image labels. Again, author's build, commit number, look at the commit number. It was built today build number 12. We saw that right? Delete, build 12. So that's kind of cool dynamic labels. Name, healthz, right? But what we're looking for is we're going to look at the org.zdockerketers label. So let's go look at the label real quick. Okay, well that doesn't really help us because it's encoded but let's base64 dash D, let's decode it. And I need to put the dash r in there 'cause it doesn't like, there we go. So there's my Kubernetes YAML. So why can't we simply kubectl apply dash f? Let's just apply it from standard end. So now we've actually used that label. From the image that we've queried with skopeo, from a remote registry to deploy locally to our Kubernetes cluster. So let's go ahead and look everything's up and running, perfect. So what does that look like, right? So luckily, I'm using traefik for Ingress 'cause I love it. And I've got an object in my Kubernetes YAML called flask.doctor.life. That's my Ingress object for traefik. I can go to flask.docker.life. And I can hit refresh. Obviously, I'm not a very good web designer 'cause the background image in the text. We can go ahead and refresh it a couple times we've got Redis storing a hit counter. We can see that our server name is roundrobing. Okay? That's kind of cool. So let's kind of recap a little bit about my demo environment. So my demo environment, I'm using DigitalOcean, Ubuntu 19.10 Vms. I'm using K3s instead of full Kubernetes either full Rancher, full Open Shift or Docker Enterprise. I think K3s has some really interesting advantages on the development side and it's kind of intended for IoT but it works really well and it deploys super easy. I'm using traefik for Ingress. I love traefik. I may or may not be a traefik ambassador. I'm using Jenkins for CI. And I'm using StackRox for image scanning and policy enforcement. One of the things to think about though, especially in terms of labels is none of this demo stack is required. You can be in any cloud, you can be in CentOs, you can be in any Kubernetes. You can even be in swarm, if you wanted to, or Docker compose. Any Ingress, any CI system, Jenkins, circle, GitLab, it doesn't matter. And pretty much any scanning. One of the things that I think is kind of nice about at least StackRox is that we do a lot more than just image scanning, right? With the policy enforcement things like that. I guess that's kind of a shameless plug. But again, any of this stack is completely replaceable, with any comparative product in that category. So I'd like to, again, point you guys to the andyc.infodc20, that's take you right to the GitHub repo. You can reach out to me at any of the socials @clemenko or andy@stackrox.com. And thank you for attending. I hope you learned something fun about labels. And hopefully you guys can standardize labels in your organization and really kind of take your images and the image provenance to a new level. Thanks for watching. (upbeat music) >> Narrator: Live from Las Vegas It's theCUBE. Covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel along with it's ecosystem partners. >> Okay, welcome back everyone theCUBE's live coverage of AWS re:Invent 2019. This is theCUBE's 7th year covering Amazon re:Invent. It's their 8th year of the conference. I want to just shout out to Intel for their sponsorship for these two amazing sets. Without their support we wouldn't be able to bring our mission of great content to you. I'm John Furrier. Stu Miniman. We're here with the chief of AWS, the chief executive officer Andy Jassy. Tech athlete in and of himself three hour Keynotes. Welcome to theCUBE again, great to see you. >> Great to be here, thanks for having me guys. >> Congratulations on a great show a lot of great buzz. >> Andy: Thank you. >> A lot of good stuff. Your Keynote was phenomenal. You get right into it, you giddy up right into it as you say, three hours, thirty announcements. You guys do a lot, but what I liked, the new addition, the last year and this year is the band; house band. They're pretty good. >> Andy: They're good right? >> They hit the queen notes, so that keeps it balanced. So we're going to work on getting a band for theCUBE. >> Awesome. >> So if I have to ask you, what's your walk up song, what would it be? >> There's so many choices, it depends on what kind of mood I'm in. But, uh, maybe Times Like These by the Foo Fighters. >> John: Alright. >> These are unusual times right now. >> Foo Fighters playing at the Amazon Intersect Show. >> Yes they are. >> Good plug Andy. >> Headlining. >> Very clever >> Always getting a good plug in there. >> My very favorite band. Well congratulations on the Intersect you got a lot going on. Intersect is a music festival, I'll get to that in a second But, I think the big news for me is two things, obviously we had a one-on-one exclusive interview and you laid out, essentially what looks like was going to be your Keynote, and it was. Transformation- >> Andy: Thank you for the practice. (Laughter) >> John: I'm glad to practice, use me anytime. >> Yeah. >> And I like to appreciate the comments on Jedi on the record, that was great. But I think the transformation story's a very real one, but the NFL news you guys just announced, to me, was so much fun and relevant. You had the Commissioner of NFL on stage with you talking about a strategic partnership. That is as top down, aggressive goal as you could get to have Rodger Goodell fly to a tech conference to sit with you and then bring his team talk about the deal. >> Well, ya know, we've been partners with the NFL for a while with the Next Gen Stats that they use on all their telecasts and one of the things I really like about Roger is that he's very curious and very interested in technology and the first couple times I spoke with him he asked me so many questions about ways the NFL might be able to use the Cloud and digital transformation to transform their various experiences and he's always said if you have a creative idea or something you think that could change the world for us, just call me he said or text me or email me and I'll call you back within 24 hours. And so, we've spent the better part of the last year talking about a lot of really interesting, strategic ways that they can evolve their experience both for fans, as well as their players and the Player Health and Safety Initiative, it's so important in sports and particularly important with the NFL given the nature of the sport and they've always had a focus on it, but what you can do with computer vision and machine learning algorithms and then building a digital athlete which is really like a digital twin of each athlete so you understand, what does it look like when they're healthy and compare that when it looks like they may not be healthy and be able to simulate all kinds of different combinations of player hits and angles and different plays so that you could try to predict injuries and predict the right equipment you need before there's a problem can be really transformational so we're super excited about it. >> Did you guys come up with the idea or was it a collaboration between them? >> It was really a collaboration. I mean they, look, they are very focused on players safety and health and it's a big deal for their- you know, they have two main constituents the players and fans and they care deeply about the players and it's a-it's a hard problem in a sport like Football, I mean, you watch it. >> Yeah, and I got to say it does point out the use cases of what you guys are promoting heavily at the show here of the SageMaker Studio, which was a big part of your Keynote, where they have all this data. >> Andy: Right. >> And they're data hoarders, they hoard data but the manual process of going through the data was a killer problem. This is consistent with a lot of the enterprises that are out there, they have more data than they even know. So this seems to be a big part of the strategy. How do you get the customers to actually wake up to the fact that they got all this data and how do you tie that together? >> I think in almost every company they know they have a lot of data. And there are always pockets of people who want to do something with it. But, when you're going to make these really big leaps forward; these transformations, the things like Volkswagen is doing where they're reinventing their factories and their manufacturing process or the NFL where they're going to radically transform how they do players uh, health and safety. It starts top down and if the senior leader isn't convicted about wanting to take that leap forward and trying something different and organizing the data differently and organizing the team differently and using machine learning and getting help from us and building algorithms and building some muscle inside the company it just doesn't happen because it's not in the normal machinery of what most companies do. And so it always, almost always, starts top down. Sometimes it can be the Commissioner or CEO sometimes it can be the CIO but it has to be senior level conviction or it doesn't get off the ground. >> And the business model impact has to be real. For NFL, they know concussions, hurting their youth pipe-lining, this is a huge issue for them. This is their business model. >> They lose even more players to lower extremity injuries. And so just the notion of trying to be able to predict injuries and, you know, the impact it can have on rules and the impact it can have on the equipment they use, it's a huge game changer when they look at the next 10 to 20 years. >> Alright, love geeking out on the NFL but Andy, you know- >> No more NFL talk? >> Off camera how about we talk? >> Nobody talks about the Giants being 2 and 10. >> Stu: We're both Patriots fans here. >> People bring up the undefeated season. >> So Andy- >> Everybody's a Patriot's fan now. (Laughter) >> It's fascinating to watch uh, you and your three hour uh, Keynote, uh Werner in his you know, architectural discussion, really showed how AWS is really extending its reach, you know, it's not just a place. For a few years people have been talking about you know, Cloud is an operational model its not a destination or a location but, I felt it really was laid out is you talked about Breadth and Depth and Werner really talked about you know, Architectural differentiation. People talk about Cloud, but there are very-there are a lot of differences between the vision for where things are going. Help us understand why, I mean, Amazon's vision is still a bit different from what other people talk about where this whole Cloud expansion, journey, put ever what tag or label you want on it but you know, the control plane and the technology that you're building and where you see that going. >> Well I think that, we've talked about this a couple times we have two macro types of customers. We have those that really want to get at the low level building blocks and stitch them together creatively however they see fit to create whatever's in their-in their heads. And then we have the second segment of customers that say look, I'm willing to give up some of that flexibility in exchange for getting 80% of the way there much faster. In an abstraction that's different from those low level building blocks. And both segments of builders we want to serve and serve well and so we've built very significant offerings in both areas. I think when you look at microservices um, you know, some of it has to do with the fact that we have this very strongly held belief born out of several years of Amazon where you know, the first 7 or 8 years of Amazon's consumer business we basically jumbled together all of the parts of our technology in moving really quickly and when we wanted to move quickly where you had to impact multiple internal development teams it was so long because it was this big ball, this big monolithic piece. And we got religion about that in trying to move faster in the consumer business and having to tease those pieces apart. And it really was a lot of impetus behind conceiving AWS where it was these low level, very flexible building blocks that6 don't try and make all the decisions for customers they get to make them themselves. And some of the microservices that you saw Werner talking about just, you know, for instance, what we-what we did with Nitro or even what we did with Firecracker those are very much about us relentlessly working to continue to uh, tease apart the different components. And even things that look like low level building blocks over time, you build more and more features and all of the sudden you realize they have a lot of things that are combined together that you wished weren't that slow you down and so, Nitro was a completely re imagining of our Hypervisor and Virtualization layer to allow us, both to let customers have better performance but also to let us move faster and have a better security story for our customers. >> I got to ask you the question around transformation because I think that all points, all the data points, you got all the references, Goldman Sachs on stage at the Keynote, Cerner, I mean healthcare just is an amazing example because I mean, that's demonstrating real value there there's no excuse. I talked to someone who wouldn't be named last night, in and around the area said, the CIA has a cost bar like this a cost-a budget like this but the demand for mission based apps is going up exponentially, so there's need for the Cloud. And so, you see more and more of that. What is your top down, aggressive goals to fill that solution base because you're also a very transformational thinker; what is your-what is your aggressive top down goals for your organization because you're serving a market with trillions of dollars of spend that's shifting, that's on the table. >> Yeah. >> A lot of competition now sees it too, they're going to go after it. But at the end of the day you have customers that have a demand for things, apps. >> Andy: Yeah. >> And not a lot of budget increase at the same time. This is a huge dynamic. >> Yeah. >> John: What's your goals? >> You know I think that at a high level our top down aggressive goals are that we want every single customer who uses our platform to have an outstanding customer experience. And we want that outstanding customer experience in part is that their operational performance and their security are outstanding, but also that it allows them to build, uh, build projects and initiatives that change their customer experience and allow them to be a sustainable successful business over a long period of time. And then, we also really want to be the technology infrastructure platform under all the applications that people build. And we're realistic, we know that you know, the market segments we address with infrastructure, software, hardware, and data center services globally are trillions of dollars in the long term and it won't only be us, but we have that goal of wanting to serve every application and that requires not just the security operational premise but also a lot of functionality and a lot of capability. We have by far the most amount of capability out there and yet I would tell you, we have 3 to 5 years of items on our roadmap that customers want us to add. And that's just what we know today. >> And Andy, underneath the covers you've been going through some transformation. When we talked a couple of years ago, about how serverless is impacting things I've heard that that's actually, in many ways, glue behind the two pizza teams to work between organizations. Talk about how the internal transformations are happening. How that impacts your discussions with customers that are going through that transformation. >> Well, I mean, there's a lot of- a lot of the technology we build comes from things that we're doing ourselves you know? And that we're learning ourselves. It's kind of how we started thinking about microservices, serverless too, we saw the need, you know, we would have we would build all these functions that when some kind of object came into an object store we would spin up, compute, all those tasks would take like, 3 or 4 hundred milliseconds then we'd spin it back down and yet, we'd have to keep a cluster up in multiple availability zones because we needed that fault tolerance and it was- we just said this is wasteful and, that's part of how we came up with Lambda and you know, when we were thinking about Lambda people understandably said, well if we build Lambda and we build this serverless adventure in computing a lot of people were keeping clusters of instances aren't going to use them anymore it's going to lead to less absolute revenue for us. But we, we have learned this lesson over the last 20 years at Amazon which is, if it's something that's good for customers you're much better off cannibalizing yourself and doing the right thing for customers and being part of shaping something. And I think if you look at the history of technology you always build things and people say well, that's going to cannibalize this and people are going to spend less money, what really ends up happening is they spend less money per unit of compute but it allows them to do so much more that they ultimately, long term, end up being more significant customers. >> I mean, you are like beating the drum all the time. Customers, what they say, we encompass the roadmap, I got that you guys have that playbook down, that's been really successful for you. >> Andy: Yeah. >> Two years ago you told me machine learning was really important to you because your customers told you. What's the next traunch of importance for customers? What's on top of mind now, as you, look at- >> Andy: Yeah. >> This re:Invent kind of coming to a close, Replay's tonight, you had conversations, you're a tech athlete, you're running around, doing speeches, talking to customers. What's that next hill from if it's machine learning today- >> There's so much I mean, (weird background noise) >> It's not a soup question (Laughter) And I think we're still in the very early days of machine learning it's not like most companies have mastered it yet even though they're using it much more then they did in the past. But, you know, I think machine learning for sure I think the Edge for sure, I think that um, we're optimistic about Quantum Computing even though I think it'll be a few years before it's really broadly useful. We're very um, enthusiastic about robotics. I think the amount of functions that are going to be done by these- >> Yeah. >> robotic applications are much more expansive than people realize. It doesn't mean humans won't have jobs, they're just going to work on things that are more value added. We're believers in augmented virtual reality, we're big believers in what's going to happen with Voice. And I'm also uh, I think sometimes people get bored you know, I think you're even bored with machine learning already >> Not yet. >> People get bored with the things you've heard about but, I think just what we've done with the Chips you know, in terms of giving people 40% better price performance in the latest generation of X86 processors. It's pretty unbelievable in the difference in what people are going to be able to do. Or just look at big data I mean, big data, we haven't gotten through big data where people have totally solved it. The amount of data that companies want to store, process, analyze, is exponentially larger than it was a few years ago and it will, I think, exponentially increase again in the next few years. You need different tools and services. >> Well I think we're not bored with machine learning we're excited to get started because we have all this data from the video and you guys got SageMaker. >> Andy: Yeah. >> We call it the stairway to machine learning heaven. >> Andy: Yeah. >> You start with the data, move up, knock- >> You guys are very sophisticated with what you do with technology and machine learning and there's so much I mean, we're just kind of, again, in such early innings. And I think that, it was so- before SageMaker, it was so hard for everyday developers and data scientists to build models but the combination of SageMaker and what's happened with thousands of companies standardizing on it the last two years, plus now SageMaker studio, giant leap forward. >> Well, we hope to use the data to transform our experience with our audience. And we're on Amazon Cloud so we really appreciate that. >> Andy: Yeah. >> And appreciate your support- >> Andy: Yeah, of course. >> John: With Amazon and get that machine learning going a little faster for us, that would be better. >> If you have requests I'm interested, yeah. >> So Andy, you talked about that you've got the customers that are builders and the customers that need simplification. Traditionally when you get into the, you know, the heart of the majority of adoption of something you really need to simplify that environment. But when I think about the successful enterprise of the future, they need to be builders. how'l I normally would've said enterprise want to pay for solutions because they don't have the skill set but, if they're going to succeed in this new economy they need to go through that transformation >> Andy: Yeah. >> That you talk to, so, I mean, are we in just a total new era when we look back will this be different than some of these previous waves? >> It's a really good question Stu, and I don't think there's a simple answer to it. I think that a lot of enterprises in some ways, I think wish that they could just skip the low level building blocks and only operate at that higher level abstraction. That's why people were so excited by things like, SageMaker, or CodeGuru, or Kendra, or Contact Lens, these are all services that allow them to just send us data and then run it on our models and get back the answers. But I think one of the big trends that we see with enterprises is that they are taking more and more of their development in house and they are wanting to operate more and more like startups. I think that they admire what companies like AirBnB and Pintrest and Slack and Robinhood and a whole bunch of those companies, Stripe, have done and so when, you know, I think you go through these phases and eras where there are waves of success at different companies and then others want to follow that success and replicate it. And so, we see more and more enterprises saying we need to take back a lot of that development in house. And as they do that, and as they add more developers those developers in most cases like to deal with the building blocks. And they have a lot of ideas on how they can creatively stich them together. >> Yeah, on that point, I want to just quickly ask you on Amazon versus other Clouds because you made a comment to me in our interview about how hard it is to provide a service to other people. And it's hard to have a service that you're using yourself and turn that around and the most quoted line of my story was, the compression algorithm- there's no compression algorithm for experience. Which to me, is the diseconomies of scale for taking shortcuts. >> Andy: Yeah. And so I think this is a really interesting point, just add some color commentary because I think this is a fundamental difference between AWS and others because you guys have a trajectory over the years of serving, at scale, customers wherever they are, whatever they want to do, now you got microservices. >> Yeah. >> John: It's even more complex. That's hard. >> Yeah. >> John: Talk about that. >> I think there are a few elements to that notion of there's no compression algorithm for experience and I think the first thing to know about AWS which is different is, we just come from a different heritage and a different background. We ran a business for a long time that was our sole business that was a consumer retail business that was very low margin. And so, we had to operate at very large scale given how many people were using us but also, we had to run infrastructure services deep in the stack, compute storage and database, and reliable scalable data centers at very low cost and margins. And so, when you look at our business it actually, today, I mean its, its a higher margin business in our retail business, its a lower margin business in software companies but at real scale, it's a high volume, relatively low margin business. And the way that you have to operate to be successful with those businesses and the things you have to think about and that DNA come from the type of operators we have to be in our consumer retail business. And there's nobody else in our space that does that. So, you know, the way that we think about costs, the way we think about innovation in the data center, um, and I also think the way that we operate services and how long we've been operating services as a company its a very different mindset than operating package software. Then you look at when uh, you think about some of the uh, issues in very large scale Cloud, you can't learn some of those lessons until you get to different elbows of the curve and scale. And so what I was telling you is, its really different to run your own platform for your own users where you get to tell them exactly how its going to be done. But that's not the way the real world works. I mean, we have millions of external customers who use us from every imaginable country and location whenever they want, without any warning, for lots of different use cases, and they have lots of design patterns and we don't get to tell them what to do. And so operating a Cloud like that, at a scale that's several times larger than the next few providers combined is a very different endeavor and a very different operating rigor. >> Well you got to keep raising the bar you guys do a great job, really impressed again. Another tsunami of announcements. In fact, you had to spill the beans earlier with Quantum the day before the event. Tight schedule. I got to ask you about the musical festival because, I think this is a very cool innovation. It's the inaugural Intersect conference. >> Yes. >> John: Which is not part of Replay, >> Yes. >> John: Which is the concert tonight. Its a whole new thing, big music act, you're a big music buff, your daughter's an artist. Why did you do this? What's the purpose? What's your goal? >> Yeah, it's an experiment. I think that what's happened is that re:Invent has gotten so big, we have 65 thousand people here, that to do the party, which we do every year, its like a 35-40 thousand person concert now. Which means you have to have a location that has multiple stages and, you know, we thought about it last year and when we were watching it and we said, we're kind of throwing, like, a 4 hour music festival right now. There's multiple stages, and its quite expensive to set up that set for a party and we said well, maybe we don't have to spend all that money for 4 hours and then rip it apart because actually the rent to keep those locations for another two days is much smaller than the cost of actually building multiple stages and so we thought we would try it this year. We're very passionate about music as a business and I think we-I think our customers feel like we've thrown a pretty good music party the last few years and we thought we would try it at a larger scale as an experiment. And if you look at the economics- >> At the headliners real quick. >> The Foo Fighters are headlining on Saturday night, Anderson Paak and the Free Nationals, Brandi Carlile, Shawn Mullins, um, Willy Porter, its a good set. Friday night its Beck and Kacey Musgraves so it's a really great set of um, about thirty artists and we're hopeful that if we can build a great experience that people will want to attend that we can do it at scale and it might be something that both pays for itself and maybe, helps pay for re:Invent too overtime and you know, I think that we're also thinking about it as not just a music concert and festival the reason we named it Intersect is that we want an intersection of music genres and people and ethnicities and age groups and art and technology all there together and this will be the first year we try it, its an experiment and we're really excited about it. >> Well I'm gone, congratulations on all your success and I want to thank you we've been 7 years here at re:Invent we've been documenting the history. You got two sets now, one set upstairs. So appreciate you. >> theCUBE is part of re:Invent, you know, you guys really are apart of the event and we really appreciate your coming here and I know people appreciate the content you create as well. >> And we just launched CUBE365 on Amazon Marketplace built on AWS so thanks for letting us- >> Very cool >> John: Build on the platform. appreciate it. >> Thanks for having me guys, I appreciate it. >> Andy Jassy the CEO of AWS here inside theCUBE, it's our 7th year covering and documenting the thunderous innovation that Amazon's doing they're really doing amazing work building out the new technologies here in the Cloud computing world. I'm John Furrier, Stu Miniman, be right back with more after this short break. (Outro music)

>> Hi, my name is Andy Clemenko. I'm a Senior Solutions Engineer at StackRox. Thanks for joining us today for my talk on labels, labels, labels. Obviously, you can reach me at all the socials. Before we get started, I like to point you to my GitHub repo, you can go to andyc.info/dc20, and it'll take you to my GitHub page where I've got all of this documentation, I've got the Keynote file there. YAMLs, I've got Dockerfiles, Compose files, all that good stuff. If you want to follow along, great, if not go back and review later, kind of fun. So let me tell you a little bit about myself. I am a former DOD contractor. This is my seventh DockerCon. I've spoken, I had the pleasure to speak at a few of them, one even in Europe. I was even a Docker employee for quite a number of years, providing solutions to the federal government and customers around containers and all things Docker. So I've been doing this a little while. One of the things that I always found interesting was the lack of understanding around labels. So why labels, right? Well, as a former DOD contractor, I had built out a large registry. And the question I constantly got was, where did this image come from? How did you get it? What's in it? Where did it come from? How did it get here? And one of the things we did to kind of alleviate some of those questions was we established a baseline set of labels. Labels really are designed to provide as much metadata around the image as possible. I ask everyone in attendance, when was the last time you pulled an image and had 100% confidence, you knew what was inside it, where it was built, how it was built, when it was built, you probably didn't, right? The last thing we obviously want is a container fire, like our image on the screen. And one kind of interesting way we can kind of prevent that is through the use of labels. We can use labels to address security, address some of the simplicity on how to run these images. So think of it, kind of like self documenting, Think of it also as an audit trail, image provenance, things like that. These are some interesting concepts that we can definitely mandate as we move forward. What is a label, right? Specifically what is the Schema? It's just a key-value. All right? It's any key and pretty much any value. What if we could dump in all kinds of information? What if we could encode things and store it in there? And I've got a fun little demo to show you about that. Let's start off with some of the simple keys, right? Author, date, description, version. Some of the basic information around the image. That would be pretty useful, right? What about specific labels for CI? What about a, where's the version control? Where's the source, right? Whether it's Git, whether it's GitLab, whether it's GitHub, whether it's Gitosis, right? Even SPN, who cares? Where are the source files that built, where's the Docker file that built this image? What's the commit number? That might be interesting in terms of tracking the resulting image to a person or to a commit, hopefully then to a person. How is it built? What if you wanted to play with it and do a git clone of the repo and then build the Docker file on your own? Having a label specifically dedicated on how to build this image might be interesting for development work. Where it was built, and obviously what build number, right? These kind of all, not only talk about continuous integration, CI but also start to talk about security. Specifically what server built it. The version control number, the version number, the commit number, again, how it was built. What's the specific build number? What was that job number in, say, Jenkins or GitLab? What if we could take it a step further? What if we could actually apply policy enforcement in the build pipeline, looking specifically for some of these specific labels? I've got a good example of, in my demo of a policy enforcement. So let's look at some sample labels. Now originally, this idea came out of label-schema.org. And then it was a modified to opencontainers, org.opencontainers.image. There is a link in my GitHub page that links to the full reference. But these are some of the labels that I like to use, just as kind of like a standardization. So obviously, Author's, an email address, so now the image is attributable to a person, that's always kind of good for security and reliability. Where's the source? Where's the version control that has the source, the Docker file and all the assets? How it was built, build number, build server the commit, we talked about, when it was created, a simple description. A fun one I like adding in is the healthZendpoint. Now obviously, the health check directive should be in the Docker file. But if you've got other systems that want to ping your applications, why not declare it and make it queryable? Image version, obviously, that's simple declarative And then a title. And then I've got the two fun ones. Remember, I talked about what if we could encode some fun things? Hypothetically, what if we could encode the Compose file of how to build the stack in the first image itself? And conversely the Kubernetes? Well, actually, you can and I have a demo to show you how to kind of take advantage of that. So how do we create labels? And really creating labels as a function of build time okay? You can't really add labels to an image after the fact. The way you do add labels is either through the Docker file, which I'm a big fan of, because it's declarative. It's in version control. It's kind of irrefutable, especially if you're tracking that commit number in a label. You can extend it from being a static kind of declaration to more a dynamic with build arguments. And I can show you, I'll show you in a little while how you can use a build argument at build time to pass in that variable. And then obviously, if you did it by hand, you could do a docker build--label key equals value. I'm not a big fan of the third one, I love the first one and obviously the second one. Being dynamic we can take advantage of some of the variables coming out of version control. Or I should say, some of the variables coming out of our CI system. And that way, it self documents effectively at build time, which is kind of cool. How do we view labels? Well, there's two major ways to view labels. The first one is obviously a docker pull and docker inspect. You can pull the image locally, you can inspect it, you can obviously, it's going to output as JSON. So you going to use something like JQ to crack it open and look at the individual labels. Another one which I found recently was Skopeo from Red Hat. This allows you to actually query the registry server. So you don't even have to pull the image initially. This can be really useful if you're on a really small development workstation, and you're trying to talk to a Kubernetes cluster and wanting to deploy apps kind of in a very simple manner. Okay? And this was that use case, right? Using Kubernetes, the Kubernetes demo. One of the interesting things about this is that you can base64 encode almost anything, push it in as text into a label and then base64 decode it, and then use it. So in this case, in my demo, I'll show you how we can actually use a kubectl apply piped from the base64 decode from the label itself from skopeo talking to the registry. And what's interesting about this kind of technique is you don't need to store Helm charts. You don't need to learn another language for your declarative automation, right? You don't need all this extra levels of abstraction inherently, if you use it as a label with a kubectl apply, It's just built in. It's kind of like the kiss approach to a certain extent. It does require some encoding when you actually build the image, but to me, it doesn't seem that hard. Okay, let's take a look at a demo. And what I'm going to do for my demo, before we actually get started is here's my repo. Here's a, let me actually go to the actual full repo. So here's the repo, right? And I've got my Jenkins pipeline 'cause I'm using Jenkins for this demo. And in my demo flask, I've got the Docker file. I've got my compose and my Kubernetes YAML. So let's take a look at the Docker file, right? So it's a simple Alpine image. The org statements are the build time arguments that are passed in. Label, so again, I'm using the org.opencontainers.image.blank, for most of them. There's a typo there. Let's see if you can find it, I'll show you it later. My source, build date, build number, commit. Build number and get commit are derived from the Jenkins itself, which is nice. I can just take advantage of existing URLs. I don't have to create anything crazy. And again, I've got my actual Docker build command. Now this is just a label on how to build it. And then here's my simple Python, APK upgrade, remove the package manager, kind of some security stuff, health check getting Python through, okay? Let's take a look at the Jenkins pipeline real quick. So here is my Jenkins pipeline and I have four major stages, four stages, I have built. And here in build, what I do is I actually do the Git clone. And then I do my docker build. From there, I actually tell the Jenkins StackRox plugin. So that's what I'm using for my security scanning. So go ahead and scan, basically, I'm staging it to scan the image. I'm pushing it to Hub, okay? Where I can see the, basically I'm pushing the image up to Hub so such that my StackRox security scanner can go ahead and scan the image. I'm kicking off the scan itself. And then if everything's successful, I'm pushing it to prod. Now what I'm doing is I'm just using the same image with two tags, pre-prod and prod. This is not exactly ideal, in your environment, you probably want to use separate registries and non-prod and a production registry, but for demonstration purposes, I think this is okay. So let's go over to my Jenkins and I've got a deliberate failure. And I'll show you why there's a reason for that. And let's go down. Let's look at my, so I have a StackRox report. Let's look at my report. And it says image required, required image label alert, right? Request that the maintainer, add the required label to the image, so we're missing a label, okay? One of the things we can do is let's flip over, and let's look at Skopeo. Right? I'm going to do this just the easy way. So instead of looking at org.zdocker, opencontainers.image.authors. Okay, see here it says build signature? That was the typo, we didn't actually pass in. So if we go back to our repo, we didn't pass in the the build time argument, we just passed in the word. So let's fix that real quick. That's the Docker file. Let's go ahead and put our dollar sign in their. First day with the fingers you going to love it. And let's go ahead and commit that. Okay? So now that that's committed, we can go back to Jenkins, and we can actually do another build. And there's number 12. And as you can see, I've been playing with this for a little bit today. And while that's running, come on, we can go ahead and look at the Console output. Okay, so there's our image. And again, look at all the build arguments that we're passing into the build statement. So we're passing in the date and the date gets derived on the command line. With the build arguments, there's the base64 encoded of the Compose file. Here's the base64 encoding of the Kubernetes YAML. We do the build. And then let's go down to the bottom layer exists and successful. So here's where we can see no system policy violations profound marking stack regimes security plugin, build step as successful, okay? So we're actually able to do policy enforcement that that image exists, that that label sorry, exists in the image. And again, we can look at the security report and there's no policy violations and no vulnerabilities. So that's pretty good for security, right? We can now enforce and mandate use of certain labels within our images. And let's flip back over to Skopeo, and let's go ahead and look at it. So we're looking at the prod version again. And there's it is in my email address. And that validated that that was valid for that policy. So that's kind of cool. Now, let's take it a step further. What if, let's go ahead and take a look at all of the image, all the labels for a second, let me remove the dash org, make it pretty. Okay? So we have all of our image labels. Again, author's build, commit number, look at the commit number. It was built today build number 12. We saw that right? Delete, build 12. So that's kind of cool dynamic labels. Name, healthz, right? But what we're looking for is we're going to look at the org.zdockerketers label. So let's go look at the label real quick. Okay, well that doesn't really help us because it's encoded but let's base64 dash D, let's decode it. And I need to put the dash r in there 'cause it doesn't like, there we go. So there's my Kubernetes YAML. So why can't we simply kubectl apply dash f? Let's just apply it from standard end. So now we've actually used that label. From the image that we've queried with skopeo, from a remote registry to deploy locally to our Kubernetes cluster. So let's go ahead and look everything's up and running, perfect. So what does that look like, right? So luckily, I'm using traefik for Ingress 'cause I love it. And I've got an object in my Kubernetes YAML called flask.doctor.life. That's my Ingress object for traefik. I can go to flask.docker.life. And I can hit refresh. Obviously, I'm not a very good web designer 'cause the background image in the text. We can go ahead and refresh it a couple times we've got Redis storing a hit counter. We can see that our server name is roundrobing. Okay? That's kind of cool. So let's kind of recap a little bit about my demo environment. So my demo environment, I'm using DigitalOcean, Ubuntu 19.10 Vms. I'm using K3s instead of full Kubernetes either full Rancher, full Open Shift or Docker Enterprise. I think K3s has some really interesting advantages on the development side and it's kind of intended for IoT but it works really well and it deploys super easy. I'm using traefik for Ingress. I love traefik. I may or may not be a traefik ambassador. I'm using Jenkins for CI. And I'm using StackRox for image scanning and policy enforcement. One of the things to think about though, especially in terms of labels is none of this demo stack is required. You can be in any cloud, you can be in CentOs, you can be in any Kubernetes. You can even be in swarm, if you wanted to, or Docker compose. Any Ingress, any CI system, Jenkins, circle, GitLab, it doesn't matter. And pretty much any scanning. One of the things that I think is kind of nice about at least StackRox is that we do a lot more than just image scanning, right? With the policy enforcement things like that. I guess that's kind of a shameless plug. But again, any of this stack is completely replaceable, with any comparative product in that category. So I'd like to, again, point you guys to the andyc.infodc20, that's take you right to the GitHub repo. You can reach out to me at any of the socials @clemenko or andy@stackrox.com. And thank you for attending. I hope you learned something fun about labels. And hopefully you guys can standardize labels in your organization and really kind of take your images and the image provenance to a new level. Thanks for watching. (upbeat music)

>> From the Salesforce tower in downtown San Francisco, it's theCUBE, covering Accenture Tech Vision 2019 brought to you by Silicon Angle Media. (upbeat music) >> Hey welcome back, everybody. Jeff Frick here with theCUBE. We are in an exciting new location. Last year we covered the Accenture technology vision release 2018. It was at Minna Gallery, cool event. But this year the venue is off the hook and 33 stories high and we're really excited to be in the brand-new Accenture Innovation Hub and joining me here our first guest, John Del Santo, he is the senior managing director for the West region for Accenture and he is responsible for this beautiful five-story. So John, first off congratulations to you and the team. >> Thanks, it's been a big project opening up this place over the last year, but it's come together great. >> Yeah and this morning they had a nice ribbon cutting, all kinds of dignitaries so, you know, what does this mean in terms of kind of, you've been with the center a long time. Your presence in the Bay Area specifically, but also as part of more of this global innovation effort. >> Well I think it's this, this is bringing together all the best of Accenture that we already had in the Bay Area. We're putting it all under one roof. We're relocating everybody and we're expanding the team. So we announced 500 new technology jobs here in this location over the next year and expanding our apprentice program. But basically, it's all about bringing more talent to this location in San Francisco to do more projects with clients in this space. >> Right. So we'll get into it with some of the other folks that we have scheduled, but it's both a coworking space for the Accenture people in town and three solid floors of all kinds of labs and innovation, kind of hands-on spaces, if you will, to do this work with your clients. >> Absolutely, that co-creation, we think, is what is really differentiating us from our competitors and it's really allowing our clients to work with us and our experts, our technology experts, and the ecosystem partners that we do a ton of work with, real time to solve a problem. Brainstorm a problem, prototype it, solve it over a very short period of time. >> Yeah, I think it's a pretty unique approach that you guys have, which is imagine the future and then create the future. >> Yeah >> As opposed to just reacting to the future. And you made an interesting comment this morning about, you know, be the disrupter, not the disruptee. And my question is really, as you see the leadership at these traditional companies that are afraid of being disrupted, how are they kind of changing the way that they do things, knowing that the digital natives and the threats that they don't even see coming from a completely different direction are now bearing down, and they have to get with the program. >> Well they do have to. And then it's really our job, our purpose, you know, the talent that we have in this company's purpose is to make our clients succeed and be disrupters. Because if they're not, they will be disrupted. And so it's in our best interest to make sure we're bringin' in the best talent, pushing their thinking on ideas, and actually getting to a solution that can actually allow them to differentiate and serve their customers better. >> Right. >> So that's what we're all about, is making sure our clients are successful. >> And draggin' 'em kicking and screaming? Or are they, are they seeing-- >> Absolutely not. >> Are they seeing it in their competition? I mean, in terms of kind of that board-level discussion, where, you know, it's passe that everybody's a technology company, and everybody's doing digital disruption, but you're down in the weeds helping these people actually execute the detail. >> Yeah, well it's funny, you say everyone's a digital company, that was our big theme a few years ago at this exact event. >> Right, right. >> Absolutely, not kicking and screaming. Most executive teams, most business teams that we work with understand that they need to change. The pace of change at their business is rapid, it's faster and faster, and every year it gets faster, and so they need to actually be a lot more agile in that >> Right. >> And move quickly. >> So one of the big things in like the singularity and accelerating pace of change. And some of these big kind of macro trends that we're experiencing is that there's no single person that sees all the innovation change across this broad front, by industry, by role, etc. You guys are in a pretty unique position 'cause you actually get to see the technology innovation and the disruption and the digitization across a number of industries as well as a number of roles. So you can kind of see this big huge glacier that's moving down the valley. >> That's one of the really cool things about this particular geography and location is that literally steps from our door here on Mission Street in San Francisco, we've got clients from ten, fifteen different industries that we serve, and we can bring talent from ten or fifteen plus different industries plus the technology skills to make sure they're looking at the problem from all angles. So if it's a retailer, are they really thinking about financial services, 'cause we've got both skills here. If it's a retailer, are they thinking about platform-based selling? Do they have an omnichannel strategy? We've got the skills in this location cross-industry to help serve banks, retailers, products companies, software platform companies, etc. And I don't think you can find that anywhere else, at least in the Continental United States, given kind of where we are in our geography. >> Right. So you had a couple of special guests this morning at the ribbon cutting. You had a customer, which is great, but you also had a representative from City of San Francisco and I just want to shift gears and talk about, you know, what it is to be kind of an active member of the community. You know, the responsibility of companies we're seeing, with kind of this backlash, if you will, against some of the mega-companies out there. It's more than just taking care of your customers. It's more than just taking care of your employees and even your stockholders. But now companies are being asked to be more kind of responsible and active participants in their local community. That's always been sort of part of our ethos. It's always been part of our vision to help our clients succeed, but also to change the way the world works and lives. And therefore, we have to be really active in our communities. We're being a little bit more explicit about it lately. But it's our view that we need to be able to improve where we're working and living, 'cause our people are active and it's important that we help serve 'em. We have a very strong public service business. We serve the State of California, we serve the City and County of San Francisco as well as well as other entities in California. And it's critical for us to help improve California as we improve the businesses in California. And so it's clearly part of our mission. >> Right. The other thing I think it's interesting is kind of companies' roles with higher education. We've seen a lot of work that Accenture's doing with community colleges and, you know, it's more than just helping so that you get good talent to feed your own system, >> Right. >> But it's really, as the pace of change just continues to accelerate, you know, historical institutions aren't necessarily best-equipped to move that fast. So again, you guys are taking a much more active, you probably done it before, but more active vocal role in the local academic institutions as well. >> Absolutely, I mean, our university relationships are really, really strong, always have been. But it's always been a little selfish on our end. We're always trying to get the best talent out of the universities locally here and there's obviously great schools in the Bay Area. We want to be more engaged with those universities on projects together as well. We want more of a 360-degree relationship. We've got great examples of where we've done research with some of the universities here locally, where we've co-innovated with some of them and we want to do more of that so that there's more of a solid relationship. It's not just about us, you know, helping them find the best students to work here, >> Right. >> Which we want, (laughs) and we do every year, but making sure that we're actually involvin' them from a research perspective and any other kind of, you know, philanthropic idea that we might have together. >> Right. So big event tonight, big event this morning, >> Yeah. >> So before I let you go, it's a brand-new space, I wonder if you could share a couple fun facts for the people who haven't come to visit yet, but hopefully will come as part of a project and a co-creation about some of the cool unique features that you guys have-- >> Well some >> Built in this thing. >> Unique features in the building. First of all, there's unique features with the talent. So we have researchers here, labbers, we call 'em, from our labs, that have, you know, Accenture has thousands of patents. More than 10% of them have been actually invented here. So our inventors are a secret that we've had in Northern California for a long time and they're all based here now. We've got some really cool spaces. We've got an augmented reality room, which is basically a 360-degree room where you can, rather than having to wear virtual-reality goggles, you can actually go inside of a computer, go inside of a lab, go inside of a hospital, and get an experience that's much more hands-on and a lot more immersive, if you will, than you could any other way. We've got a maker lab where we actually are makin' stuff. So we've got a design business here where we've helped physically make not only software, we make a lot of software, everyone knows that, but we've actually made products that have embedded software in them and so there's that fabrication capability we actually have in this building as well, which is pretty unique for a high-rise. (laughs) so >> Right. No, we saw all the machines back there, >> Yup. >> Had a good tour earlier today so-- >> Oh lots of robots and toys and all that good stuff, too. >> Yeah, that's right, it's all the robot room. All right, well, John, thanks for taking a few minutes of your time. Really exciting day for you and the team, >> Yeah. >> And nothing but congratulations. >> Thank you so much. >> All right. >> Thank you, thanks for coming. >> He's John, I'm Jeff, you're watching theCUBE. We're at the brand-new Accenture Innovation Hub in downtown San Francisco in the Salesforce tower. Thanks for watching. (upbeat music)

>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon web services, Intel, and their ecosystem partners. >> Hey welcome back everyone, here at AWS re:Invent 2018, their sixth year of theCUBE coverage, two sets wall-to-wall coverage here, two more sets in other locations, getting all the content, bringing it in, ingesting it into our video cloud service on AWS, ah, Dave, >> Lot of content, John. >> Lot of people don't know that we have that video cloud service, but we're going to have a lot of fun, ton of content, ton of stories, and a special analyst segment, Jerry Chen, guest here today, CUBE alumni, famous Venture Capitalist and Greylock partners, partnering with Reid Hoffman, the founder of LinkedIn, great set of partners at Greylock , great firm, tier one, doing a lot of great deals, Rockset, recent one. >> Thanks, yeah. >> You're also, on the record, these six years ago, calling the shot of Babe Ruth predicting the future. You've got a good handle on, you've got VM where you have the cloud business, now you're making investments, you're seeing a lot of stuff on the landscape, certainly, as a Venture Capitalist, you're funding projects, what better time now of innovation to actually put money to work, to hit market share, and then the big guys are getting bigger, they're creating more robust platforms, game is changing big-time, want to get your perspective, Dave, so, Jerry, what's your take on the announcements, slew of announcements, which ones jumped out at you? >> I think there's kind of two or three areas, there's definitely the hybrid cloud story with the Outpost, there's a bunch of stuff around ML and AI services, and a bunch of stuff on data and storage, and for me I think what they're doing around the ML services, the prediction, the personalization, the text OCR, what Amazon's doing at that app layer is now creating AI building blocks for modern application, so you want to do forecasts, you want to do personalization, you want to do text analysis, you have a simple API to basically build these modern apowered apps, he's doing to the app infrastructure layer what he's done to the cloud infrastructure layer, by deconstructing these services. >> And API is also the center, that's what web services are, so question for you is, do you see that the core cloud players, Aussie, Amazon, Bigly, Google, Microsoft, others, it's a winner take most, you called that six years ago, and that's true, but as they grow there's going to be now a new cloudification going on for business apps, new entrepreneurs coming to market, who's vulnerable, who wins, who loses, as this evolution continues because it's going to enable a lot of opportunity. >> Yeah, well I mean Amazon in cloud in general is going to create a lot of winners and losers, like you said, so I think you have a shift of dollars from on prem and old legacy vendors, databay storage, compute, to the cloud, so I think there's a shift of dollars, there are winner and losers, but I think what's going to happen is, with all these services around AI, ML, and Cloud as a distribution model, a lot of applications are going to be rebuilt. So I think that the entire application stack from all the big SaaS players to small SaaS companies, you're going to see this kind of a long tale of new SaaS applications being built on top of the Cloud that you didn't see in the past. >> And the ability to get to markets faster, so the question I have for you is, if you're an entrepreneur out there, looking for funding and I can to market quicker, what's the playbook, and two, Jassie talked on stage about a new persona, a new kind of developer, one that can rethink and reimagine and reinvent something that someone else has already done, so if you're an entrepreneur, you got to think to take someone else's territory, so how does an entrepreneur go out and identify whose lunch to eat, so if I want to take down a company, I got to have a strategy, how do I use the cloud to >> I think it's always a combination when a founder in a thing attacks your market it's a combination of where are the dollars, where can I create some advantage IP or advantage angle, and thirdly where do I have a distribution advantage, how can I actually get my product in the hands of the users differently? And so I think those are the three things, you find intersection of a great market, you have a unique angle, and you have a unique route to market, then you have a powerful story. So, you think about cloud changing the game, think about the mobile app you can consist of, for consumers, that is also a new platform, a new distribution method, the mobile app stores, and so what happened, you had a new category of developers, mode developers, creating this long tale, a thousand thousand apps, for everything from groceries to cars to your Fantasy Football score. So I think you're going to see distribution in the cloud, making it easy to get your apps out there, going to see a bunch of new markets open up, because we're seeing verticals like healthcare, construction, financial services, that didn't have special apps beforehand, be disrupted with technology. Autodesk just bought PlanGrid for 800 million dollars, I mean that's unheard of, construction software company. So you can see a bunch of new inverdics like that be opened up, and then I think with this cloud technology, with compute storage network becomes free and you have this AI layer on top of it, you can power these new applications using AI, that I think is pretty damn exciting. >> Yes, you described this sort of, we went from client server to the cloud, brought a whole bunch of new app providers, obviously Salesforce was there but Workday, Service Now, what you described is a set of composeable digital services running on top of a cloud, so that's ripe for disruption, so do I have to own my own data centers if I'm big SaaS company, what happens to those big guys? >> I don't think you have to, well, you don't have to own your own data center as a company, but you could if you wanted to, right, so at some point in scale, a lot of big players build their own data centers, like AirBNB is on Amazon, but Dropbox built their own storage on Amazon early, then their own data center later. Uber has their own data center, right, so you can argue that at some point of scale it makes sense to build your own, so you don't need to be on Amazon or Google as your start, but it does give you a head start. Now the question is, in the future, can you build a SaaS application entirely on Amazon, Azure, or Google, without any custom code, right, can you hide read write call private SaaS, like a single instance of my SaaS application for you, John, or for you, Dave, that's your data, your workflow, your information personalized for you, so instead of this multi-tenet CRM system like Salesforce, I have a custom CRM system just for Dave, just for Jeff, just for Jerry, just for theCUBE, right? >> I think yes, for that, I think that's definitely a trend I would see happening. >> It's what Infor is trying to do, right, Charles Phillips says "Friends don't let friends "build data centers," but they've still got a big loss in legacy there, but it's an interesting model, focused on verticals or microverticals or like the healthcare example that you're giving, and lot of potential for something. >> Well here's why I think I like this because, I think, and I said this before in theCUBE maybe it's not the best way to say it is that, if you look at the benefit of AI, data-driven, the quality of the data and the power of the compute has to be there. AI will work well with all that stuff, but it's also specialized around the application's use case. So you have specialism around the application, but you don't have to build a full stack to do that, you could use a horizontally scalable cloud distribution system in your word, and then only create custom unique workloads for the app, where machine learning's involved, and AI, that's unique to the app, that's differentiation, that could be the business model, or the utility. So, multitenancy could exist in theory, at the scalable level, but unique at the top of the level so yes I would say I'd want that hosted in the most customized, agile, flexible way. So I would argue that that's the scenario. >> I think that's the future, I mean one of my, I think you were saying, Dave, friends don't let friends build data centers anymore, it's you probably don't need to build a data center anymore because you can actually build your own application on top of one of the two or three large cloud providers. So it's interesting to see what happens the next three, four years, we're going to see kind of a thousand flowers bloom of different apps, not everyone's going to make it, not everyone's going to be a huge Salesforce-like outcome, but there'll be a bunch of applications out there. >> And the IoT stuff is interesting to me, so observing a lot of what the IT guys are doing, it reminds me of people trying to make the Windows mobile phone, they're just trying to force IT standards down the IoT, what I've seen from AWS today is more of a bottoms up approach, build applications for operations technology people, which I think is the right way to go, what do you see in an IoT, IoT apps, what's the formula there? >> I think what Amazon announced today with their time series database, right, their Timestream prediction engine, plus their Outpost offering with the Vmware themselves, you're really seeing a combination of IoT and Edge, right, it's the whole idea is, one, there's a bunch of use cases for time series in IoT, because sentry data, cameras, self-driving cars, drones, et cetera, there's more data coming at you, it adds all of that. >> And Splunk has proven that big-time. >> Correct, Splunk's let 18 billion Marcap company, all on time series data, but number two, what's happening is, it's not necessarily centralized data, right, it's happening at the edge, your self-driving car, your cell phone, et cetera, so Outpost is really a way for Amazon to get closer to the edge, by pushing their compute towards your data center, towards remote office, branch office, and get closer to where the data is, so I think that'll be super interesting. >> Well the Elastic Inference engine is critical, now we got elasticity around inference, and then they got the chip set that worked Inferentia, that can work with the elastic service. That's a powerful combination. >> The AI plumbing war between Google and TetraFlow as technology there's like PyTorch, Google TPUs versus what Amazon is doing with inference chips today, versus what I'm sure Microsoft and else is doing, is fascinating to watch in terms of how you had a kind of a Intel Nvidia duopoly for a long time, and now you have Intel, Nvidia, and then everyone from Amazon, Google, Microsoft doing their own soul again, it's pretty fascinating to watch. >> What was the stat, he said 85% of the TensorFlow, cloud TensorFlow's running on AWS? >> Makes a lot of sense, I think he said Aurora's customers logoslide doubled, but let's break down real quick, to end the segment with the key areas that we see going on, at least my perspective, I want to get your reaction. Storage, major disruption, he emphasized a lot of that in the keynote, spent a lot of time on stores, actually I think more than EC2 if you look at it, two, databases, database war, storage rate configuration, and a holy trinity of networking, storage, and compute, that's evolving, databases, SageMaker, machine learning. All there and then over the top, yesterday's announcement of satellite as a service, that essentially kills the edge of the network, cause there is no edge if we have space satellites shooting connectivity to any device the world is now, there's no more edge, it's everywhere. So, your thoughts, those areas. Which one pops out as the most surprising or most relevant? >> I think it's consistent Amazon strategy, on the lowest layer they're trying to draw the cost to zero, so on storage, cheaper cheaper cheaper, they're driving the bottom layer to zero to get all your data. I think the second thing, the database layer, it makes sense, it's not open-source, right, time scale or time series, it's not, Timestream's not their open-source database, it's their own, so open-source, low cost, the lowest layer, their database stuff is mostly their own, Aurora, Dynamo, Timestream, right, because there's some level lock in there, which I think customers are worried about, so that's clever, it's not by accident, that's all proprietary, and then ML Services, on top of that, that's all cares with developers, and it's API locking, so clearly low-cost open-source for the bottom, proprietary data services that they're trying to own, and then API's on top of it. And so the higher up in the stack, the more and more Amazon, you look, the more and more Amazon you have to adopt as kind of a lock in stack, so it's a brilliant strategy the guys have been executing for the past six, seven years as you guys have seen firsthand, I think the most exciting thing, and the most shocking thing to me is this move towards this battle for the AI front, this ML AI front, I think we saw ML's the new sequel, right, that's the new war, right, against Amazon, Google, and Microsoft. >> And that's the future of applications, cause this is >> But you're right on, it's a knife fight for the data, and then you layer on machine intelligence on top of that, and you get cloud scale, and that's the innovation engine for the next 10 years. >> Alright Jerry Chen just unpacked the State of the Union of cloud, of course as an investor I got to ask the final question, how are you investing to take advantage of this wave, versus being on the wrong side of history? >> I have framers for everything, there's a framer on how to attack the cloud vendors, and so I'm looking at a couple things, one, a seams in between the clouds, right, or in between services, because they can't do everything well, and there were kind of these large continents, Amazon, Google, Azure, so I'm looking for seams between the three of them, I'm looking for two, deep areas of IP that they're not going into that you actually have proprietary tap, and then verticals of data, like source of the data, or workflows that these guys aren't great, and then finally kind of cross-data cross-cloud solution, so, something that gives you the ability to run on prem, off prem, Microsoft, Google, Azure. >> Yeah, fill in the white spaces, there are big white spaces, and then hope that could develop into, good. Jerry Chen, partner in Greylock , partners formerly Vmware part of the V Mafia, friend of theCUBE, great guest analysis here, with Dave Vellante and John Furrier, thanks for watching us, stay with us, more live coverage, day two of three days of wall-to-wall coverage at re:Invent, 52,000 people, the whole industry's here, you can see the formations, we're getting all of the data, we're bringing it to you, stay with us.

>> Live from Toronto, Canada, it's theCUBE! Covering Blockchain Futurist Conference 2018. Brought to you by theCUBE! >> Hey, welcome back, everyone, we're live here in Toronto for the Blockchain Futurist Conference put on by Untraceable, Tracy and her team doing a fantastic job, so shout out to the team at Untraceable for another great event. I'm John Furrier with theCUBE, my cohost's Dave Vellante, and we're here with CUBE's friend, CUBE alumni, from the CryptoChicks, Nataliya Hearn, director, good to see you, great to have you back. >> Thank you. (laughs) >> Okay, good to see you, we're laughing, we've got some great funny stories we've been telling, since PolyCon, but really, some great things going on, so give us the update, you had a hackathon recently, you got new things happening here in your organization, take a quick minute to explain what it is for the folks that don't know, what do you guys do, and what's going on? >> Good, well, CryptoChicks is a organization focused on educating women in blockchain and cryptospace. We started because at meetups there would be one or two women out of hundreds of men, who would be afraid to ask stupid questions, so we said, Oh, okay, there's no stupid questions, come and join us, and we'll show you how to open a wallet, what blockchain is all about, so we've been doing that. We've actually grew quite a bit, we are now have chapters in all over the world, in Pakistan, in Bahamas, in Moscow, we just teamed up with She Codes in Israel, which is 50,000 women, so, we're doing really well. >> Congratulations, a great mission, we totally support it, and, you know, I'm proud to say that I love my shirt that says, Satoshi is Female, thanks to Nyla Rodgers, who gave it to me, at Consensus in Blockchain Week in New York, but this is really beyond women in tech, it's beyond that, it's a really, you're doing some innovative things around onboarding, new talent and education, this is a really important, because the Internet is bounded on discovery, learning. >> Absolutely. >> What's the new thing? >> Well, you know when you hear, when you go to the blockchain conference and events, and we hear again and again about the chasm. How do we bridge the chasm, right? That's just the, like, big word that you hear like every third presentation, because the blockchain community needs it. But I think globally, blockchain represents something that's quite unique, and it's an opportunity not just to make money and speculate, or to develop new technology, it's technology that can liberate. But how do we get that message across? And I think we have to start with kids. Kids are our future, but they're also the ones who spend most of their time on social media, so that's a good thing, but if you ask their parents, that's not such a good thing necessarily. So how do we convert them, some of their time from social media to learning? So we've put, we're putting together this program that focuses on children to earn to learn. >> Earn to learn, like they earn coins or money, or? >> That's right, basically they can earn swag, so basically we're creating the marketplace that rewards children for learning. >> All kids, right? >> All kids, well we're focusing on -- >> On girls. >> No, not on girls, we're going to high schools, so immediate next generation. >> So girls, boys, everybody's welcome? >> Absolutely. Yep. >> Awesome. >> Next generation, and they're the next generation that has to solve the problems that we, and opportunities that can be captured, that's coming right to their front door. >> Absolutely, we have a lot of question marks in the blockchain community. Which blockchain, how do we do it, there is going to be multi-chain tokens, we're talking about, next generation is the one who's going to provide solutions for us. So we got to open their minds, and to show that blockchain is a tool like potentially calculus is a tool. To create something that hasn't been there before. >> You know, I have a lot of conversations in Silicon Valley and Nataliya, recently at the Google Cloud event, Google's been very much a great change agent, especially with women in tech and underrepresented minorities, but Aparna Sinha, who's one of the senior people there, dual degrees from Stanford, she's got a PhD, she said we're losing the girls early, and what came out of it was a conversation that, when you have these new market movements like blockchain, AI, these are new skills that you can level up, so the ability to come from behind and level up is an opportunity for people who have traditionally been behind, whether it's women or other minorities, to level up. So it's a huge opportunity now to put the naysayers down to rest, and saying, Screw you, we're going to level up and learn. >> Absolutely, and it's global, the thing is -- >> There's nothing stopping anyone from learning. >> Absolutely, and trust, and the borderless system that blockchain potentially can provide is at a global advantage. As long as you have a cell phone, you can be in a village, an old village, like at our last hackathon, we actually were streaming women hackers from Zimbabwe. So there you go, it's doable. >> So how are you, how are you scaling your message globally? >> So we're starting, one thing is that education today, is basically the bill is being paid either by the government or by parents. The reason I would call that a marketplace, I would like companies to be involved. And it could be local companies, or it could be global. What about creating ARVR classrooms, and providing the information to kids, via a completely new way that they would actually move away from swiping or just looking on some random YouTube videos, to something that they can get a phone, some shoes, mascara, focusing on girls, right? And to understand what that borderless economy really means by experiencing, what does it mean to have tokens that you can trade globally? You are used to your parents giving you some dollars, you go to a corner store. What about if you learn something, you go to a bakery, in Kenya, and for the work that you've done, you get a bun, right, or a meal? >> So this democratizing access, it's bringing education to the masses? >> And it's also uniting the blockchain community, 'cause we would be building this governance platform on blockchain, we would tokenize it, and there will be many elements of it, reward programs, smart contracts that reward content, some level of AI in terms of analysis of what we're doing, so I think this is why I was looking at multi-chain tokens. Maybe that would be a solution to kind of, to deal with -- >> Explain that, what does that mean? >> Well, we've got different chains right now, right? You've got Hyperledger, you've got Ethereum, and all this good stuff. How do you bridge all this, right, instead of having to choose one, you're now saying, I can work in all of them, because each one potentially can offer something unique. Maybe you don't have to choose one. We don't know. Only time will tell, as this, this is such a young industry, and this is why it's so exciting. >> Well, Nataliya -- >> It -- >> Oh, go ahead. >> No, I was going to say, and you're giving the kids examples, so a lot of times kids ask me, Well, what's the difference between crypto and Venmo? I'm like, okay, you know, let's talk about the different things you can do with crypto that you can't do, but they're closer than the older generations are to transferring, you know, money, at least, so now you're applying different use cases and expanding their minds in ways that, perhaps -- >> Absolutely, and I'll give you my example. I mean, I got into blockchain early before Ethereum was launched, and partly I was into public markets, and then I kind of stopped because that project ended, or I stopped and I actually reentered it, because my fifteen-year-old who started mining. But he started mining because I was in that field already, so there you go, it kind of, you know, what comes around. >> Good job. I hope he gets all his Bitcoin. >> Yeah, he did. (laughs) >> So, I want you to tell a story, of what you've seen that's been high impact from your work you've done. You had, again, that whole Pakistan thing going on, you've got all these hackathons, what is a good story you could share? >> You know, the good story we can share, I think the part that we were able to do, the hackathons that we are doing are local, but they're also global, it really is, there's this sense of empowerment, and you know what I think the best story, this is the best story: best story was, at the hackathon that we ran, it was women, over 100 women, that participated. But all our mentors were young, geeky programming guys. Sorry guys. But you really knew they really knew their stuff, so there was technology transfer, and we had a 48 hour hackathon, these guys stayed 48 hours, they didn't go to sleep, they didn't have to as mentors, and there was this amazing technology transfer that happened, and I think some relationships were formed too. >> Yeah, some serious bonding went on, right? >> Yeah, absolutely. >> It's actually a good thing that you're including people. It's not just a certain thing, you got this inclusion. >> Absolutely, and actually all it is is about inclusion, all it is is we are giving a platform for women not to be afraid, I mean, I'm an engineer, so I've been working with men all my life, so for me to ask difficult questions, or stupid questions, it's like natural now, because it's been what my life, but for women, for many, it isn't. So we just wanted to kind of cross that divide, it's not a chasm, it's just a little divide that we're bridged. >> So when you say stupid questions, do you mean like, Why do you do it that way? (laughs) Why don't you do it this way? >> Or, what's a wallet? Like, what's a private key? What's a public key? And asking that not once, but twenty times until you got it. That's okay too. >> That's called learning. >> Yeah. >> Last question, okay I got to ask you, the most important question is, how do someone get a CryptoChicks shirt? >> I think you can order it on our website, sizes are a problem, I know we've discussed this, so we need to -- >> Extra-large. >> Well, CryptoChicks is a not-for-profit organization so there are, we'll have to order this in bunches, so I'll figure this out, but what I wanted to say is that we have another hackathon that's coming up. And the hackathon is in New York, October 5th to 8th, and we have three streams, so if you're a developer, and this is for women, so if you're a developer, we have a stream. If you're not a developer, or you've never coded in your life, but you have a business mind, and you think you have a really good idea that you can put on blockchain, you're welcome to join as well, and now with all the news and regulations, we also have a regulatory stream. >> So for entrepreneurs and for business-minded people, that want to get involved, that they can come too? >> Absolutely. >> Okay, and their website is cryptochicks.ca, that's where you can get access to the information, that's great. >> October 5th to 8th, you said, right? >> That's right. >> And anybody can go? >> Anybody can register. >> And where in New York? >> It's going to be at University of New York, and at their School of Law. >> Great. >> Blockchain Educational Fun Hub. That's what it says on the website, love your website. Looking forward to getting some shirts, and putting it out there, and promoting your mission. Great job, good to see you again. >> You guys are awesome. Thank you so much. >> Thank you. >> Thank you, Nataliya. >> Thank you. >> This is crypto for good, a lot of education, and this opportunity, and our role is to share that, as a community, and I think this is a great example of the kind of community that crypto is. Education people can level up and move fast through and get proficiency, and change their lives. This is what this is all about, glad to bring us this CUBE coverage live, stay with us! Day One continues, I'm John Furrier with Dave Vellante, we'll be right back from Toronto Blockchain Futurist Summit. Thank you. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and it's ecosystem partners. >> Welcome back to Las Vegas everybody. You're watching theCUBE, the leader in live tech coverage and this is day three of our coverage of the inaugural Dell Technologies World. We're in the home stretch. Stu Miniman and Dave Vellante joining you, with Alison Dew, the newly minted CMO of Dell. Great to see you, thanks for coming on. >> Thanks for having me, good to be here. >> So, you've been with Dell for a long time. >> 10 years >> You know the drill, you know the culture. But, 23 days as CMO? >> Yes >> Well congratulations. You were on stage today, awesome show. >> Thank you, I couldn't be more delighted. Great experience for me personally. Great show for our customers. >> Yeah, I'll bet. I mean, and you brought in some outside speakers this year, which has not been typical of this show, at least the legacy EMC world, and certainly Dell World did that. >> Stu: Dell World did, definitely. >> Alison: Dell World did do it more, you know. >> Yep, Bill Clinton, we saw some other amazing speakers. >> Elon Musk >> Elon Musk, I remember the year Elon came. >> So that's good, and you got to interview Ashton Kutcher >> Yeah >> Which was quite amazing. He's an unbelievable-- people don't know, he's an investor, he's kind of a geek. >> Alison: Yep >> Even though he's, you know >> An engineer by training? >> Right, so what'd you think of his discussion? >> I mean, I thought it was fantastic and, as you said, I think people don't quite realize how involved in technology he actually is. And also, how well and successful his businesses have been. And then, equally important, the work that he's doing with his foundation and the way he's using technology for really important human causes. I don't think he gets enough credit for that, so it was great to sit on stage and have that conversation. It was super fun. >> Yeah, cause we know him from That 70's Show. >> I know, I like That 70's Show. >> And he's a goofball, and he comes across He's a great actor, lot of fun. >> Yeah, there was one of the lines I actually really loved from the presentation. It's that he looks for companies that have counter-intuitive thesis because if you're doing something that everybody else is, then chances are somebody is going to catch you and everything else like that. You also had to talk about geeks. You know, John Rose and Ray O'Farrell, up there. Share a little bit about some commonalities you saw between these speakers, and some of the unconventional things they're doing. >> So, I completely agree. I love the point of talking, there's so much hype in the space. And that's why I think that line is so important. And so, the big commonality that we're really seeing and talking about this year in particular is we've been talking for years about data as the rocket fuel of the economy and of business transformation, and now we're really talking about data combined with those emerging technologies. So, things like AI, IOT, Blockchain, which are really taking that data and unlocking the business value because for years, there's been this hype about big data, but I don't think the reality has quite been there. And now as those technologies catch up, we're really starting to see some practical applications and use cases and that's why I thought, in particular, John Rose's section on AI and how we're seeing some of those really emerging practical applications was so interesting and fun and tied really well to Ashton's talk track. >> You know, that's a good point. I mean, I feel like we started covering the big data trend really early on. And I feel like big data was like the warm up. It's cheaper now to collect all this data. Now that we have all this data, we're going to apply machine intelligence to that data. We're going to scale it, with cloud economics and that's really what's going to drive value and innovation. What are your thoughts on that? >> Absolutely. We talked this morning on the stage even about some of the companies, large and small, who are really doing that. I think one of the examples that's really interesting Wal-Mart using Blockchain technology to decrease the amount of time from seven days to mere seconds that it takes them to identify the source of food contamination. Really interesting things where, a couple of years ago even, frankly even 18, 20 months ago, that would have been a promise, but maybe not a reality. And so that's what I think is really exciting. Finally. >> It's something that's actually resonated with me this week. We've talked for my entire career, there's the journeys. And it was like, a lot of times it's the journey of the technology. A couple of years ago, digital transformation was "Okay, is it real? Isn't it?" Every customer I talk to, they understand making it real as you said in the keynote, where they're going. What kind of feedback are you getting from people at the show? >> So one of the things I talked about briefly on Monday, but I think is really important, is this promise and the hope and the optimism of digital transformation. And yet also, the fear behind it as well. Through some of the work that we've done in our own research for Realizing 2030, we're really seeing that about 50% of our respondents say they believe in the power of the human machine partnership, which means that 50% don't. And all of the data questions are really divided and polarizing like that. And as a lifelong researcher, that's really interesting to me because it says that there's something going on there. And yet, at the same time, we're seeing over 85% of the respondents that we talk to who say they're committed to becoming a software defined company in five years. So this idea of "I know what I want to do "I know what it means to transform an industry, "And yet, I'm still not really sure that's going to "do me or my business good. "I'm not really sure what that means for "myself or my employees, getting really practical. "Obviously about the technologies, "that's what we do, "but the examples of how people can do "that better from a business perspective." That's a lot of the customer conversation that I've had over this week. >> But you're an optimist. You believe the world would be a better place as a result of machines. >> Yes, I do and we do. Are you an optimist? >> I am, I think there's some obviously some challenges but there's no question. Stu and I talk about this all the time, on theCUBE, that machines have always replaced humans throughout history. For the first time now, it's on cognitive functions, but the gap is creativity and eduction. So I am an optimist if we invest in the right places and I think there's an opportunity for public policy to really get involved. Leadership from companies like yours and others, politicians, of course. >> Dave and I did an event a couple of years ago with Andy McAfee and Erik Brynjolfssono, you had Andy here. Cause it's really it's not just the technology, it's technology and people, and those have to go together. And Dave said, there's policy and there's so many different layers of this that have to go into it. >> And I think we're just starting to really enter into that. On that optimist versus the robots are coming to get us spectrum, obviously there are things that we have to look out for as leaders, as society, as businesses. And yet, even if you look at the example from this morning, where Ashton is talking about minimizing child sexual trafficking and using AI and machine learning to one, arrest many of the perpetrators of these crimes, as well as free thousands of children from sexual slavery. I mean, you hear those examples, and it's hard not to be an optimist. >> I want to ask you about your digital transformation and how that's being led inside of Dell, what it means to you. >> So, obviously, we are two huge companies that came together. So when we talk about digital transformation, and what that really means, have a very different way of operating and working with IT and being in a different business model, we know that really well. One of the things that's really interesting for me personally, as the CMO for 23 days, is one of the biggest line items in my budget is actually for our own marketing digital transformation. Obviously, Dell in particular, had many, many years starting in the consumer and small business, and then growing up to larger businesses, of direct marketing. And we have a great relationship with our customers, but we also have all of these legacy systems and processes and way that work is done and now as we come together with EMC and we start to build Dell Technologies, the idea of what a data driven marketing engine can be, that possibility is something that we're also working to build ourselves. And so, everything from "how do we build our "own data lake to actually bring all "of these sources of data together? "How do we clean up that data?" is something that I'm pretty deeply into myself. There's a lot of that work going on across the company, and then for me personally, as CMO. Big initiative. >> So it's customer experience as part of it, but it's also a new way to work. >> Exactly. And it sounds so trite in a way to say the technology is the easy part, but the really hard part begins when the technology is finished. And I really believe that because if I look at my own team and my own teams experience, there's so many places where they've been doing marketing one way for a very long time. And if you come in and you ask them to do something differently, that's actually a pretty hard thing to do. And the only way to unlock the power of the data and the power of the new technologies, is to actually change how work is done. And I know it's an analogy that's overused, but if you'd ask the taxi dispatch "Are you important to the taxi business?" they would have said "Yes, of course "I'm the most important person in this chain." That's how taxis get to customers. And then along comes Uber, and suddenly you don't need that. You have to really think differently about that and as a leader, that's exciting and also really hard. >> I don't know if you've ever heard Sanjay Poonen talk about change, he says there's three reactions to change. Either run from it, fight it, or you embrace it. That's it. And the third is the only way to go. >> It's the only way. >> How about messaging? I'm sensing different messaging. Much more around the business, maybe a little bit less on the products. Plenty of product stuff here, but the high level stuff. What's your philosophy on messaging? >> I used to say "I'm a person that "believes in shades of gray" and about seven years ago I had to stop saying that. (laughs) >> But the truth is, I am a person who believes in shades of gray and I almost always believe that the answer is somewhere in the middle. So you get in marketing into these debates about is it these thought leadership and high level conversations or is it about product messaging and selling what's on the truck? And the honest truth is, you have to do both. You have to set a vision, you have to build the brand, you have to talk about the business and where we're going from a business perspective. As we talk about things like 2030, that's a really lean into the future conversation. At the same time, we also want to sell you some PCs and some servers and some storage and some data protection, so we need to do that well, too. And frankly, we need to get better as a marketing machine, as a company, and as salespeople, in terms of talking to customers. The right conversation at the right time. Again, sounds like marketing 101, but it's actually quite hard to do. When do you want to have a connected cities conversation? When do you want to just talk about how to modernize your data center? >> It's true, we always talk about above the line and below the line. When you're talking above the line, you might be speaking one language and below the line, another language. You try to mix the two, it doesn't work. >> Right, exactly. >> You have to target the appropriate audience. >> The conversation one of the women on my team started talking about this and I thought it really made sense was macro-conversations, micro-conversations. So to get out of this advertising vernacular, and I grew up in the ad industry, sort of above the line, below the line, and those were always two departments who didn't even talk to each other and usually hated each other. Instead of above the line, below the line, what's the macro-conversation? How are we talking about Realizing 2030? How are we talking about digital transformation? And then what are some of those micro-conversations where I'm going to talk to you about what are the personas that you have in your work force? And lets talk about some in user compute technology together with something really simple, like a monitor, that's going to help them be more productive. Those things don't have to fight with each other, you just have to be honest about when you're doing each one. >> Target them in the right place. >> Alison, we're getting to the end of the show here. >> Yeah, I can talk a lot. >> First of all, New Media Row here gave us the biggest set. We've done this show for nine years, we're super excited. The therapy dogs next door-- >> I love the therapy dogs. >> Are really fun to see, but every once in a while, give a little bit of color in the background here. For people that didn't get to come and experience in person, I know the sessions are online, but give us some of the flavors and some of the fun things you've seen and what would we expect from you in the future? >> I think this is just one of the most fun shows. I mean, obviously it's important for us to set our vision, it's important for people to come into the hands on labs, and the training, and the breakouts, and to learn and to engage. But, you see things like the beanbags and sitting out there, the therapy dogs, and my team does want me to say that every year we get new beanbag covers so we don't recycle those. And then really experience the fun in the Solutions Expo and talking about the way that we're taking trash, plastic trash, out of oceans and making art with it, so we can talk about our sustainable supply chain in an interesting way. I think, I'm biased, but I think this is the best show in terms of actual education and vision, but also some fun. Hopefully you guys think so too. >> Well, Sting. >> And Walk the Moon. Do you guys know who Walk the Moon is? >> Yes. >> I don't. >> Me neither. (laughs) >> Come on and dance with me. >> Oh, okay. Alright, great. >> I'm a child of the 80's, what can I say? >> Alright, so 23 days on the job, what should we be watching from you, your team, and Dell? >> So, as we talked about in the very beginning, this is our first Dell Technologies World, so obviously, we have just gone through some of the biggest integration of large tech companies in the history. And we're really proud of how successful that integration has been, and yet we also still have so much work to do around telling that integrated story. Yes, Dell and Dell EMC, but also together with VM, we're a pivotal RSA Secureworks, and the extend is strategically aligned businesses. And so that's what you'll see us really lean into is "How do we tell "that story more effectively?" We're continuing to invest in the brand, so a lot of the work that you've seen with Jeffrey Wright and those TV spots we launched again in March, and just making sure that people understand what the Dell Technologies family actually is. >> So really a more integrated story. But something that Dell always tried to tell, but you didn't have the portfolio to tell it. Now you do, so that's got to be exciting for you. >> It is exciting, yeah. >> Great. Alison, thanks so much for coming on theCUBE. It was great to have you. >> My pleasure. Cheers, thanks. >> Alright, keep it right there, buddy. We'll be back with our next guest. You're watching theCUBE live from Dell Technologies World in Vegas. We'll be right back.

(click) >> Hey, Lisa Martin on the ground with theCUBE at Google for the Sixth Annual CloudNOW Top Women in Cloud Awards Event, our second year covering this, very excited to be joined by tonight's emcee, Becky Wanta, the founder of RSW1C. Welcome to theCUBE. >> Thank you. >> It's great to have you here. So tell us a little bit about what you do and your background as a technology leader. >> So, I've been in technology for close to 40 years. I started out as a software. >> Sorry, I don't even, what? (laughing) >> Ha, ha, ha, it's a long time ago, yeah. So I started out as a developer back in the Department of Defense. So it wasn't rocket science in the early days when I began because it was back when computers took up whole rooms and I realized I had an affinity for that. So, I leveraged that, but then I got into, at that time, and I'm from northern California, if you remember right, the Department of Defense was drawing down. And so I decided I was going to leverage my experience in IT to get into either integrative financial services or healthcare, right. So I took over running all of tech for the Money Store at the time which you would have no idea who that is. And then that got acquired by Wells Fargo First Union, so I took over as their Global CTO for Wells Fargo. And what you'll see is, so let me just tell you about RSW1C because what it is is it's a technology consulting firm that's me. And the reason I have it is because tech changes so much that it's easy to stay current. And when I get brought into companies, and you'll look at me, so I've been the executive officer for tiny little companies like PepsiCo, Wells Fargo, Southwest Airlines. >> The small ones. >> Yeah, tiny, not really, MGM Resorts International, the largest worker's comp company in California, a company that, unborn midsize SMB in southern California that just wrapped up last year. And when I get brought into these companies, I get brought in to transform them. It's at a time in the maturation of these companies, these tiny little brands we've mentioned, where they're ready to jettison IT. So I take that very seriously because I know technology is that gateway to keep that competitive advantage. And the beauty is of that the companies I've mentioned, they're all number one in their markets. And when you're number one, there's only one direction to go, so they take that very seriously. >> How do you come in there and help an MGM Grand Resorts transform? >> So what happened in MGM's case and probably in the last five CIO positions that I've taken, they've met me as a consultant, again, from RSW1C. And then when I look into what needs to happen and I have the conversation, because everybody thinks they want to do digital transformation, and it's not an easy journey and if you don't have the executive sponsorship, don't even try it at home, right? And so, in MGM's case, they had been talking. MGM's the largest taxpayer in Nevada. People think about it as MGM Grand. It's 19 brands on The Strip. >> Is that right? >> It's Bellagio, MGM, so it's the largest taxpayer in Nevada. So it owns 44,860 rooms on The Strip. So if I just counted now, you have Circa Circa, Slots of Fun, Mirage, Bellagio, Monte Carlo, New York, New York, um, MGM Grand Las Vegas, MGM Grand Detroit. They're in the countries and so forth. So it's huge. And that includes Mandalay, ARIA, and all those, so it's huge, right? And so in MGM's case, they knew they wanted to do M life, so M life game changes their industry. And I put that in. This will be our nine year anniversary coming up on Valentine's Day. Thirty years they talked about it, and I put in with a great team And that was part of the transformation into a new way of running their business. >> Wow, we have a couple of minutes left. I'd love to get your perspective on being a female leader in tech. Who were your mentors back in the day? And who are your mentors now? >> So, I don't have any mentors. I never did. Because when I started in the industry, there wasn't a lot of women. And obviously, technology was fairly new which is why one of my passions is around helping the next generation be hugely successful. And one of the things that's important is in the space of tech, I like this mantra, this mantra that says, "How about brains "and beauty that gets you in the door? "How about having the confidence in yourself?" So I want to help a lot of the next generation be hugely successful. And that's what Jocelyn has built with CloudNow, her and Susan. And I'm a big proponent of this because I think it's a chance for us to give back and help the next generation of leaders in a non-traditional way be hugely successful in brands, in companies that are going to unleash their passion and show them how to do that. Because, the good news is that I'm a total bum, Lisa. I've never had a job. I love what I do, and I do it around the clock, so. >> Oh, if only more people could say that. That's so cool. But what we've seen with CloudNow, this is our second year covering it, I love talking to the winners and even the folks that are keynoting or helping to sponsor scholarships. There's so much opportunity. >> There really is. >> And it's so exciting when you can see someone whose life is changing as a result of finding a mentor or having enough conviction to say, "You know what? "I am interested in a STEM field. "I'm going to pursue that." >> Right. >> So, we thank you so much Becky for stopping by theCUBE. And your career is amazing. >> Thanks. >> And I'm sure you probably are mentors to countless, countless men and women out there. >> Absolutely. >> Well, thanks again for stopping by. >> Thank you, Lisa. >> Thank you for watching theCUBE. I'm Lisa Martin on the ground at Google with the CloudNow Sixth Annual Top Women in Cloud Awards Event. Stick around, we'll be right back.

(electronic music) >> Announcer: Live from Austin, Texas, it's theCUBE, covering DockercCon 2017. Brought to you by Docker and support from Asseco System Partners. >> Welcome back to theCUBE, I'm Stu Mittleman, with my co-host, Jim Kobielus. Happy to have on the program, I'm shocked to say a first time guest. Someone that I've known in the community here for many years, but Michael Ducy, who is Director of Product Marketing at Chef Software. Not a chef. Maybe you might-- >> Not a chef, although I do cook at home (laughing). >> Maybe in Chef. Not a puppeteer. >> Not a puppeteer. >> But you work for Chef Software. So thank you so much for joining us. >> Yes, thanks for having me. >> Alright, so Michael, for the audience that doesn't know you... I think a lot of people here in the community would know you. I've known you through Twitter for many years. What's your role at Chef? What do you work on? What's your passion? >> Sure, so right now I do product marketing for our open source projects. So Chef Software actually has a commercial product, and then we also have three open source projects that we maintain. The first was the original one that we're named after, which is Chef, which is open source automation or configuration management. The second one being Inspect, which is all about how do you basically write compliance rules as code. And then third one, as you can see from my shirt, is called Habitat. So Habitat is a new way of thinking about how do you package up automation for your application. And then how can you easily export that application and the automation into something like a container. I've had various roles at Chef though over the four years that I've worked for them. My passion's always kind of been open source communities, an involvement in open source communities and helping grow those communities. >> Yeah, and people send you lots of stuff about goats. >> People send me lots of stuff about goats (laughing). There was a joke that was made at a conference about waking up next to a goat. This was a conference in Amsterdam, which is I'm sure I wouldn't be the first one that woke up next to a goat in Amsterdam (laughing). But since then, the whole goat thing kind of took off after that. >> Yeah, so, Chef, you understand many things about Docker. So one of the things, we come in and we talk about there's Docker, the company, there's Docker, the community. A lot of what was talked about in the keynote today was about open source. >> Umm-hmm. >> So how's Docker doing? What interested you in the keynote? How do you as an individual in Chef see what's going on in the Docker ecosystem? And what do you think? >> Yeah. >> Yeah. >> So we've been put in a little bit of an interesting position as Chef, the company. And not only has Chef, the company, been put in this position, but all of our competitors have as well. So there's been a movement as Docker and containers got more popular that the idea that configuration management is no longer needed. And from a inside the container perspective, configuration management really isn't needed. But what you do end up realizing is that there's this whole idea of what you need to actually run a container in production effectively, that still needs to go into that container. And we kind of call it The Learning Cliff of Containers. And I tweeted out an image about... that why co-worker draw on a whiteboard. That shows in development you just have Docker and it's really easy, but then when you move it to production there's this whole other stack of concerns. And Docker or your container runtime is just one of them. And so, we've been focusing more on kind of shifting into those ideas of how do you actually run containers effectively in production. What we saw in the keynote today is more of an emphasis on things like security, right. That's definitely been an area that we're interested in, especially from a compliance perspective, and doing work around having our open source projects, being able to scan containers for compliance. >> Yeah, it's funny before the keynote they have this fun little thing. They have this 8-bit video game playing. >> Right. >> And it was like they were collecting coins and they were leveling up, but they kept hitting lots of bombs (laughing) and things were exploding all the time. And everybody was joking online. It was like, Oh, it's like putting Docker in production. I will level up (laughing) and I will get past everything, but, Boy, I'm going to have lots of bombs going off and things-- >> Sure. >> And things that I'll have to deal with, and there were lots of fun little comments that they threw out there. It's like, Checking documentation. Oh, documentation says you don't have documentation. (laughing) So just fun stuff like that. But it's challenging. Solomon says, We want this put in deployment, but as we know it's not quite there yet. There's lots of things, that's where you guys fit in. >> Umm-hmm. >> A lot of the ecosystem helps to solidify that about you here. >> Michael, what are those concerns that you allude to? There's security, and what other concerns are there for containers in production that need to be represented in the configuration management portfolio or profile you're describing? >> Sure, so there's the security aspects of it is focused on what vulnerabilities are in your container. >> Yeah. >> And there's been some interesting studies recently that showed 24% of the official images are shipping with some sort of a vulnerability. Some of that you have to accept, and then also realize can you do risk mitigation around that vulnerability. There's concerns about how the application is actually configured when you ship it as well. So am I doing things like storing secrets in config files. Am I disabling versions of ISOCELL that's no longer a best practice anymore because it's actually broken. And then there's other aspects around how do you things like service discovery, how do you do credentials or secrets. And how do you get them into the container securely. There's networking aspects. There's last malconfiguration of the application, so-- >> Right. >> If you take a container from one environment to another environment and kind of work it through a lifecycle. There are things at runtime that you have to change in its configuration to make it run in that particular environment. >> Right. >> So it's all of those little knobs that you still have to turn. And that's why-- >> The entire DevOps lifecycle essentially there's all those little knobs and... >> There's all these little knobs and this has always been a little bit of a frustration for me, in that PaaS sounds great, platform as a service sounds great. And this idea that you can just take this blob and go run it. But What people don't realize is there still are tons of knobs that you have to turn, and there are tons of concerns that you have to worry about as an operations person or as a DevOps person or as a developer when you actually are taking that code into production. >> Right. >> Michael, we've seen the cloud providers and some of the other open source providers kind of chipping away. Red Hat bought Ansible, every time I go to Amazon re:Invent or Google, it seems like they're trying to build more things up the stack and into their platforms. >> Umm-hmm. >> So what is Chef's position here? How do you guys play across all these environments and kind of maintain and grow what you're doing? >> Yeah, so we've started to take a little bit more of a different focus and... Well, not a different focus... A different focus for us. Traditionally, we focus on infrastructure and operations people and then as we moved up the stack and DevOps became more popular. We definitely focused on that because that's kind of our bread and butter. But what we started to do with Habitat is focus more on building a developer experience. So how can a developer take their code-- >> Yeah. >> Easily wrap automation around it, and then ship it out into production. And this is the new world for us, as coming from the operations side of things. And really starting to think about what does the developer tooling look like and the developer experience look like. We're taking source code, building that source code, and then deploying that source code to production. >> Yeah, and it's interesting, it sounds... We talk about Docker. They very much started out in the developer world, and then they're kind of moving to kind of the Op side more. >> Umm-hmm. >> And to the enterprise side more. You're almost going-- >> Michael: And we're kind of-- >> A little bit in reverse, huh. >> Yeah, going a little bit in reverse, yeah. >> Yeah, it's interesting because usually it's like, Okay, I start with developers, get them excited and then figure out to monetize. So, yeah, what are you seeing in your customer base? >> Sure. >> Who do you sell to in that aspect? Yeah, I'm just curiosity at some of the buyers. >> Well, so, traditionally, a tool like Chef or, even some of our competitors would be bought by what's called the Shared Services Team, right. And that Shared Services Team is going to take that and try and work economies of scale, right. And try and deploy that across all of the different BMs or machines that they have to manage, right. And we've seen this shift as we moved more up the stack and as the industry's shifted more up the stack. Of what the Shared Services Team actually needs to transform themselves into is more of a developer services team. So how can I offer the services that a developer can get via an API, to quickly deploy the application services that they need. And when I say application services, I'm thinking about all of the things that you need to actually go and persist the data. The business logic side of things are very easy to do in containers or PaaS. But when you're actually having to go and persist data in something like Red-S are Mongo or MySQL, that's a whole other area of concern that you have to worry about. So what we've actually had started to do is the core team that actually works on Habitat has a very, very big background in distributive systems. So what we've started to do is bake a lot of that foundational ideas about how you effectively run large-scale distributive systems into Habitat, which makes it very easy to then go and take that developer, take their source code, and deploy it using Habitat, using this knowledge that we have from distributive systems. So we actually see it as a benefit that we come from this infrastructure background because we have experience of actually running things in production, right. >> Umm-hmm, what do you see as some of the challenges that we still need to face in this kind of container ecosystem? I know one of the questions I have coming in is you talked about stateful applications. We know storage still needs some time to mature. Networking seems to be a little bit further along in what they're doing. >> Umm-hmm. >> What's your take as to what's doing well? What still needs some more work? >> Yeah, storage is one of those areas that... And persisting data is one of those areas that we're not able to get around, right. And if you look at some people's recommendations, so Pivotal, for example, recommends running persistent services on BMs, right. If you look at the Google approach or the Cuber-netee's approach, they actually recommend that you use a cloud provider services to go and run those data services for you, until you think you're good enough to actually go and run it like Google. (laughing) And they're also hedging on the fact that you'll probably never be good enough to run it like Google. >> Yeah, yeah. >> So, kind of building that expertise of running those distributive systems in an effective way is kind of the area in running those persistent data services in a highly scalable way is kind of the big challenge that operations still hasn't figured out. And developers also need work to... Need help to help figure that out as well. >> Yeah, the big theme this morning was really about scalability. When you talked to customers, what does scale mean to them? What are the limitations they're having? I loved when you talked about what you're doing with Habitat. Helping customers, so that they don't have to have the expertise to build distributive systems because that's the software challenge of our time-- >> Yeah. >> Is moving to that. What we talk at Wicky-bon, it's moving from the old enterprise where it was like kind of baked in the hardware to a distributive, where the software model, anything had failed, there's no single point of failure, I can scale. >> Yeah. >> What do you think? >> Well, to kind of paraphrase our CTO, Adam Jacob, he always likes to say ignore scaling problems because you don't have a scaling problem. (laughing) And you don't have a scaling problem until you have a scaling problem, right. So if you kind of look at where your time's most effectively spent, your time is more effectively spent at actually building an application that people want to use, and worry about the scaling problem when the scaling problem comes up, right. And the other thing is that you might never hit that scaling problem, so everyone wants to be the next Uber, everyone wants to be the next Netflix, and so forth. And so, if you go in as a startup or, even a startup inside of a large enterprise trying to do a new application. If you start by trying to solve the scaling problem out the door, then what you end up losing is a lot of development cycles that you could actually be spending on building something that people actually want to use. And then worrying about the scaling problem when you hit the scaling problem. >> So, Mike, last question I have for you. A month from now, you're going to be back in Austin. >> A month from now, I'm going to be back in Austin. >> So tell us about ChefConf. >> Yes. >> What can people expect? Give us a compare and contrast to kind of the communities, the type of people that attend. I expect we'll see more shorts because it's going to be a little bit warmer and more humid here in Austin (laughing). >> Yes, so we're back at Austin for the second ChefConf in Austin. We were here also last year. We were in Austin in July last year. >> Ooooh. >> Which was not a fun experience (laughing). The air conditioning was very nice. The pool was also very nice. (laughing) But what you can expect is more practical advice to how to actually run these things in production. We have a lot of talks about Habitat. I think we're going to have a lot... Nine talks on Habitat. We have a lot of talks from the Chef community about running actual systems in production in a lot of real world experience, which is something that we always try and hover into our conferences. We also have a day that's going to be focused on our open source community as well, so where our open source and contributors can get together to talk about problems that they're trying to solve in our open source communities as well. And then on the last day, of course, as every conference does we're going to have a hack day, where you can contribute to open source, our open source, or we can help you get started solving a problem that you have, but there'll be a lot of people there that can answer questions for you about the problems that you're trying to solve in running distributive systems. >> Alright, well, Michael Ducy, happy to welcoming you into the ranks of theCUBE alumni, finally. >> Yes, finally, thank you very much. >> And thank you for sharing all the updates with us. And thank you for watching theCUBE. (electronic music) >> I remember...