>> Announcer: From around the globe, it's the queue with digital coverage of DockerCon live 2020. Brought to you by Docker and its ecosystem partners. >> Welcome, welcome, welcome to DockerCon 2020. We got over 50,000 people registered so there's clearly a ton of interest in the world of Docker and Eddie's as I like to call it. And we've assembled a power panel of Open Source and cloud native experts to talk about where things stand in 2020 and where we're headed. I'm Shawn Conley, I'll be the moderator for today's panel. I'm also a proud alum of JBoss, Red Hat, SpringSource, VMware and Hortonworks and I'm broadcasting from my hometown of Philly. Our panelists include; Michelle Noorali, Senior Software Engineer at Microsoft, joining us from Atlanta, Georgia. We have Kelsey Hightower, Principal developer advocate at Google Cloud, joining us from Washington State and we have Chris Aniszczyk, CTO CIO at the CNCF, joining us from Austin, Texas. So I think we have the country pretty well covered. Thank you all for spending time with us on this power panel. Chris, I'm going to start with you, let's dive right in. You've been in the middle of the Docker netease wave since the beginning with a clear focus on building a better world through open collaboration. What are your thoughts on how the Open Source landscape has evolved over the past few years? Where are we in 2020? And where are we headed from both community and a tech perspective? Just curious to get things sized up? >> Sure, when CNCF started about roughly four, over four years ago, the technology mostly focused on just the things around Kubernetes, monitoring communities with technology like Prometheus, and I think in 2020 and the future, we definitely want to move up the stack. So there's a lot of tools being built on the periphery now. So there's a lot of tools that handle running different types of workloads on Kubernetes. So things like Uvert and Shay runs VMs on Kubernetes, which is crazy, not just containers. You have folks that, Microsoft experimenting with a project called Kruslet which is trying to run web assembly workloads natively on Kubernetes. So I think what we've seen now is more and more tools built around the periphery, while the core of Kubernetes has stabilized. So different technologies and spaces such as security and different ways to run different types of workloads. And at least that's kind of what I've seen. >> So do you have a fair amount of vendors as well as end users still submitting in projects in, is there still a pretty high volume? >> Yeah, we have 48 total projects in CNCF right now and Michelle could speak a little bit more to this being on the DOC, the pipeline for new projects is quite extensive and it covers all sorts of spaces from two service meshes to security projects and so on. So it's ever so expanding and filling in gaps in that cloud native landscape that we have. >> Awesome. Michelle, Let's head to you. But before we actually dive in, let's talk a little glory days. A rumor has it that you are the Fifth Grade Kickball Championship team captain. (Michelle laughs) Are the rumors true? >> They are, my speech at the end of the year was the first talk I ever gave. But yeah, it was really fun. I wasn't captain 'cause I wasn't really great at anything else apart from constantly cheer on the team. >> A little better than my eighth grade Spelling Champ Award so I think I'd rather have the kickball. But you've definitely, spent a lot of time leading an Open Source, you've been across many projects for many years. So how does the art and science of collaboration, inclusivity and teamwork vary? 'Cause you're involved in a variety of efforts, both in the CNCF and even outside of that. And then what are some tips for expanding the tent of Open Source projects? >> That's a good question. I think it's about transparency. Just come in and tell people what you really need to do and clearly articulate your problem, more clearly articulate your problem and why you can't solve it with any other solution, the more people are going to understand what you're trying to do and be able to collaborate with you better. What I love about Open Source is that where I've seen it succeed is where incentives of different perspectives and parties align and you're just transparent about what you want. So you can collaborate where it makes sense, even if you compete as a company with another company in the same area. So I really like that, but I just feel like transparency and honesty is what it comes down to and clearly communicating those objectives. >> Yeah, and the various foundations, I think one of the things that I've seen, particularly Apache Software Foundation and others is the notion of checking your badge at the door. Because the competition might be between companies, but in many respects, you have engineers across many companies that are just kicking butt with the tech they contribute, claiming victory in one way or the other might make for interesting marketing drama. But, I think that's a little bit of the challenge. In some of the, standards-based work you're doing I know with CNI and some other things, are they similar, are they different? How would you compare and contrast into something a little more structured like CNCF? >> Yeah, so most of what I do is in the CNCF, but there's specs and there's projects. I think what CNCF does a great job at is just iterating to make it an easier place for developers to collaborate. You can ask the CNCF for basically whatever you need, and they'll try their best to figure out how to make it happen. And we just continue to work on making the processes are clearer and more transparent. And I think in terms of specs and projects, those are such different collaboration environments. Because if you're in a project, you have to say, "Okay, I want this feature or I want this bug fixed." But when you're in a spec environment, you have to think a little outside of the box and like, what framework do you want to work in? You have to think a little farther ahead in terms of is this solution or this decision we're going to make going to last for the next how many years? You have to get more of a buy in from all of the key stakeholders and maintainers. So it's a little bit of a longer process, I think. But what's so beautiful is that you have this really solid, standard or interface that opens up an ecosystem and allows people to build things that you could never have even imagined or dreamed of so-- >> Gotcha. So I'm Kelsey, we'll head over to you as your focus is on, developer advocate, you've been in the cloud native front lines for many years. Today developers are faced with a ton of moving parts, spanning containers, functions, Cloud Service primitives, including container services, server-less platforms, lots more, right? I mean, there's just a ton of choice. How do you help developers maintain a minimalist mantra in the face of such a wealth of choice? I think minimalism I hear you talk about that periodically, I know you're a fan of that. How do you pass that on and your developer advocacy in your day to day work? >> Yeah, I think, for most developers, most of this is not really the top of mind for them, is something you may see a post on Hacker News, and you might double click into it. Maybe someone on your team brought one of these tools in and maybe it leaks up into your workflow so you're forced to think about it. But for most developers, they just really want to continue writing code like they've been doing. And the best of these projects they'll never see. They just work, they get out of the way, they help them with log in, they help them run their application. But for most people, this isn't the core idea of the job for them. For people in operations, on the other hand, maybe these components fill a gap. So they look at a lot of this stuff that you see in the CNCF and Open Source space as number one, various companies or teams sharing the way that they do things, right? So these are ideas that are put into the Open Source, some of them will turn into products, some of them will just stay as projects that had mutual benefit for multiple people. But for the most part, it's like walking through an ion like Home Depot. You pick the tools that you need, you can safely ignore the ones you don't need, and maybe something looks interesting and maybe you study it to see if that if you have a problem. And for most people, if you don't have that problem that that tool solves, you should be happy. No one needs every project and I think that's where the foundation for confusion. So my main job is to help people not get stuck and confused in LAN and just be pragmatic and just use the tools that work for 'em. >> Yeah, and you've spent the last little while in the server-less space really diving into that area, compare and contrast, I guess, what you found there, minimalist approach, who are you speaking to from a server-less perspective versus that of the broader CNCF? >> The thing that really pushed me over, I was teaching my daughter how to make a website. So she's on her Chromebook, making a website, and she's hitting 127.0.0.1, and it looks like geo cities from the 90s but look, she's making website. And she wanted her friends to take a look. So she copied and paste from her browser 127.0.0.1 and none of her friends could pull it up. So this is the point where every parent has to cross that line and say, "Hey, do I really need to sit down "and teach my daughter about Linux "and Docker and Kubernetes." That isn't her main goal, her goal was to just launch her website in a way that someone else can see it. So we got Firebase installed on her laptop, she ran one command, Firebase deploy. And our site was up in a few minutes, and she sent it over to her friend and there you go, she was off and running. The whole server-less movement has that philosophy as one of the stated goal that needs to be the workflow. So, I think server-less is starting to get closer and closer, you start to see us talk about and Chris mentioned this earlier, we're moving up the stack. Where we're going to up the stack, the North Star there is feel where you get the focus on what you're doing, and not necessarily how to do it underneath. And I think server-less is not quite there yet but every type of workload, stateless web apps check, event driven workflows check, but not necessarily for things like machine learning and some other workloads that more traditional enterprises want to run so there's still work to do there. So server-less for me, serves as the North Star for why all these Projects exists for people that may have to roll their own platform, to provide the experience. >> So, Chris, on a related note, with what we were just talking about with Kelsey, what's your perspective on the explosion of the cloud native landscape? There's, a ton of individual projects, each can be used separately, but in many cases, they're like Lego blocks and used together. So things like the surface mesh interface, standardizing interfaces, so things can snap together more easily, I think, are some of the approaches but are you doing anything specifically to encourage this cross fertilization and collaboration of bug ability, because there's just a ton of projects, not only at the CNCF but outside the CNCF that need to plug in? >> Yeah, I mean, a lot of this happens organically. CNCF really provides of the neutral home where companies, competitors, could trust each other to build interesting technology. We don't force integration or collaboration, it happens on its own. We essentially allow the market to decide what a successful project is long term or what an integration is. We have a great Technical Oversight Committee that helps shepherd the overall technical vision for the organization and sometimes steps in and tries to do the right thing when it comes to potentially integrating a project. Previously, we had this issue where there was a project called Open Tracing, and an effort called Open Census, which is basically trying to standardize how you're going to deal with metrics, on the tree and so on in a cloud native world that we're essentially competing with each other. The CNCF TC and committee came together and merged those projects into one parent ever called Open Elementary and so that to me is a case study of how our committee helps, bridges things. But we don't force things, we essentially want our community of end users and vendors to decide which technology is best in the long term, and we'll support that. >> Okay, awesome. And, Michelle, you've been focused on making distributed systems digestible, which to me is about simplifying things. And so back when Docker arrived on the scene, some people referred to it as developer dopamine, which I love that term, because it's simplified a bunch of crufty stuff for developers and actually helped them focus on doing their job, writing code, delivering code, what's happening in the community to help developers wire together multi-part modern apps in a way that's elegant, digestible, feels like a dopamine rush? >> Yeah, one of the goals of the(mumbles) project was to make it easier to deploy an application on Kubernetes so that you could see what the finished product looks like. And then dig into all of the things that that application is composed of, all the resources. So we're really passionate about this kind of stuff for a while now. And I love seeing projects that come into the space that have this same goal and just iterate and make things easier. I think we have a ways to go still, I think a lot of the iOS developers and JS developers I get to talk to don't really care that much about Kubernetes. They just want to, like Kelsey said, just focus on their code. So one of the projects that I really like working with is Tilt gives you this dashboard in your CLI, aggregates all your logs from your applications, And it kind of watches your application changes, and reconfigures those changes in Kubernetes so you can see what's going on, it'll catch errors, anything with a dashboard I love these days. So Yali is like a metrics dashboard that's integrated with STL, a service graph of your service mesh, and lets you see the metrics running there. I love that, I love that dashboard so much. Linkerd has some really good service graph images, too. So anything that helps me as an end user, which I'm not technically an end user, but me as a person who's just trying to get stuff up and running and working, see the state of the world easily and digest them has been really exciting to see. And I'm seeing more and more dashboards come to light and I'm very excited about that. >> Yeah, as part of the DockerCon just as a person who will be attending some of the sessions, I'm really looking forward to see where DockerCompose is going, I know they opened up the spec to broader input. I think your point, the good one, is there's a bit more work to really embrace the wealth of application artifacts that compose a larger application. So there's definitely work the broader community needs to lean in on, I think. >> I'm glad you brought that up, actually. Compose is something that I should have mentioned and I'm glad you bring that up. I want to see programming language libraries, integrate with the Compose spec. I really want to see what happens with that I think is great that they open that up and made that a spec because obviously people really like using Compose. >> Excellent. So Kelsey, I'd be remiss if I didn't touch on your January post on changelog entitled, "Monoliths are the Future." Your post actually really resonated with me. My son works for a software company in Austin, Texas. So your hometown there, Chris. >> Yeah. >> Shout out to Will and the chorus team. His development work focuses on adding modern features via micro services as extensions to the core monolith that the company was founded on. So just share some thoughts on monoliths, micro services. And also, what's deliverance dopamine from your perspective more broadly, but people usually phrase as monoliths versus micro services, but I get the sense you don't believe it's either or. >> Yeah, I think most companies from the pragmatic so one of their argument is one of pragmatism. Most companies have trouble designing any app, monolith, deployable or microservices architecture. And then these things evolve over time. Unless you're really careful, it's really hard to know how to slice these things. So taking an idea or a problem and just knowing how to perfectly compartmentalize it into individual deployable component, that's hard for even the best people to do. And double down knowing the actual solution to the particular problem. A lot of problems people are solving they're solving for the first time. It's really interesting, our industry in general, a lot of people who work in it have never solved the particular problem that they're trying to solve for the first time. So that's interesting. The other part there is that most of these tools that are here to help are really only at the infrastructure layer. We're talking freeways and bridges and toll bridges, but there's nothing that happens in the actual developer space right there in memory. So the libraries that interface to the structure logging, the libraries that deal with rate limiting, the libraries that deal with authorization, can this person make this query with this user ID? A lot of those things are still left for developers to figure out on their own. So while we have things like the brunettes and fluid D, we have all of these tools to deploy apps into those target, most developers still have the problem of everything you do above that line. And to be honest, the majority of the complexity has to be resolved right there in the app. That's the thing that's taking requests directly from the user. And this is where maybe as an industry, we're over-correcting. So we had, you said you come from the JBoss world, I started a lot of my Cisco administration, there's where we focus a little bit more on the actual application needs, maybe from a router that as well. But now what we're seeing is things like Spring Boot, start to offer a little bit more integration points in the application space itself. So I think the biggest parts that are missing now are what are the frameworks people will use for authorization? So you have projects like OPA, Open Policy Agent for those that are new to that, it gives you this very low level framework, but you still have to understand the concepts around, what does it mean to allow someone to do something and one missed configuration, all your security goes out of the window. So I think for most developers this is where the next set of challenges lie, if not actually the original challenge. So for some people, they were able to solve most of these problems with virtualization, run some scripts, virtualize everything and be fine. And monoliths were okay for that. For some reason, we've thrown pragmatism out of the window and some people are saying the only way to solve these problems is by breaking the app into 1000 pieces. Forget the fact that you had trouble managing one piece, you're going to somehow find the ability to manage 1000 pieces with these tools underneath but still not solving the actual developer problems. So this is where you've seen it already with a couple of popular blog posts from other companies. They cut too deep. They're going from 2000, 3000 microservices back to maybe 100 or 200. So to my world, it's going to be not just one monolith, but end up maybe having 10 or 20 monoliths that maybe reflect the organization that you have versus the architectural pattern that you're at. >> I view it as like a constellation of stars and planets, et cetera. Where you you might have a star that has a variety of, which is a monolith, and you have a variety of sort of planetary microservices that float around it. But that's reality, that's the reality of modern applications, particularly if you're not starting from a clean slate. I mean your points, a good one is, in many respects, I think the infrastructure is code movement has helped automate a bit of the deployment of the platform. I've been personally focused on app development JBoss as well as springsSource. The Spring team I know that tech pretty well over the years 'cause I was involved with that. So I find that James Governor's discussion of progressive delivery really resonates with me, as a developer, not so much as an infrastructure Deployer. So continuous delivery is more of infrastructure notice notion, progressive delivery, feature flags, those types of things, or app level, concepts, minimizing the blast radius of your, the new features you're deploying, that type of stuff, I think begins to speak to the pain of application delivery. So I'll guess I'll put this up. Michelle, I might aim it to you, and then we'll go around the horn, what are your thoughts on the progressive delivery area? How could that potentially begin to impact cloud native over 2020? I'm looking for some rallying cries that move up the stack and give a set of best practices, if you will. And I think James Governor of RedMonk opened on something that's pretty important. >> Yeah, I think it's all about automating all that stuff that you don't really know about. Like Flagger is an awesome progressive delivery tool, you can just deploy something, and people have been asking for so many years, ever since I've been in this space, it's like, "How do I do AB deployment?" "How do I do Canary?" "How do I execute these different deployment strategies?" And Flagger is a really good example, for example, it's a really good way to execute these deployment strategies but then, make sure that everything's happening correctly via observing metrics, rollback if you need to, so you don't just throw your whole system. I think it solves the problem and allows you to take risks but also keeps you safe in that you can be confident as you roll out your changes that it all works, it's metrics driven. So I'm just really looking forward to seeing more tools like that. And dashboards, enable that kind of functionality. >> Chris, what are your thoughts in that progressive delivery area? >> I mean, CNCF alone has a lot of projects in that space, things like Argo that are tackling it. But I want to go back a little bit to your point around developer dopamine, as someone that probably spent about a decade of his career focused on developer tooling and in fact, if you remember the Eclipse IDE and that whole integrated experience, I was blown away recently by a demo from GitHub. They have something called code spaces, which a long time ago, I was trying to build development environments that essentially if you were an engineer that joined a team recently, you could basically get an environment quickly start it with everything configured, source code checked out, environment properly set up. And that was a very hard problem. This was like before container days and so on and to see something like code spaces where you'd go to a repo or project, open it up, behind the scenes they have a container that is set up for the environment that you need to build and just have a VS code ID integrated experience, to me is completely magical. It hits like developer dopamine immediately for me, 'cause a lot of problems when you're going to work with a project attribute, that whole initial bootstrap of, "Oh you need to make sure you have this library, this install," it's so incredibly painful on top of just setting up your developer environment. So as we continue to move up the stack, I think you're going to see an incredible amount of improvements around the developer tooling and developer experience that people have powered by a lot of this cloud native technology behind the scenes that people may not know about. >> Yeah, 'cause I've been talking with the team over at Docker, the work they're doing with that desktop, enable the aim local environment, make sure it matches as closely as possible as your deployed environments that you might be targeting. These are some of the pains, that I see. It's hard for developers to get bootstrapped up, it might take him a day or two to actually just set up their local laptop and development environment, and particularly if they change teams. So that complexity really corralling that down and not necessarily being overly prescriptive as to what tool you use. So if you're visual code, great, it should feel integrated into that environment, use a different environment or if you feel more comfortable at the command line, you should be able to opt into that. That's some of the stuff I get excited to potentially see over 2020 as things progress up the stack, as you said. So, Michelle, just from an innovation train perspective, and we've covered a little bit, what's the best way for people to get started? I think Kelsey covered a little bit of that, being very pragmatic, but all this innovation is pretty intimidating, you can get mowed over by the train, so to speak. So what's your advice for how people get started, how they get involved, et cetera. >> Yeah, it really depends on what you're looking for and what you want to learn. So, if you're someone who's new to the space, honestly, check out the case studies on cncf.io, those are incredible. You might find environments that are similar to your organization's environments, and read about what worked for them, how they set things up, any hiccups they crossed. It'll give you a broad overview of the challenges that people are trying to solve with the technology in this space. And you can use that drill into the areas that you want to learn more about, just depending on where you're coming from. I find myself watching old KubeCon talks on the cloud native computing foundations YouTube channel, so they have like playlists for all of the conferences and the special interest groups in CNCF. And I really enjoy talking, I really enjoy watching excuse me, older talks, just because they explain why things were done, the way they were done, and that helps me build the tools I built. And if you're looking to get involved, if you're building projects or tools or specs and want to contribute, we have special interest groups in the CNCF. So you can find that in the CNCF Technical Oversight Committee, TOC GitHub repo. And so for that, if you want to get involved there, choose a vertical. Do you want to learn about observability? Do you want to drill into networking? Do you care about how to deliver your app? So we have a cig called app delivery, there's a cig for each major vertical, and you can go there to see what is happening on the edge. Really, these are conversations about, okay, what's working, what's not working and what are the next changes we want to see in the next months. So if you want that kind of granularity and discussion on what's happening like that, then definitely join those those meetings. Check out those meeting notes and recordings. >> Gotcha. So on Kelsey, as you look at 2020 and beyond, I know, you've been really involved in some of the earlier emerging tech spaces, what gets you excited when you look forward? What gets your own level of dopamine up versus the broader community? What do you see coming that we should start thinking about now? >> I don't think any of the raw technology pieces get me super excited anymore. Like, I've seen the circle of around three or four times, in five years, there's going to be a new thing, there might be a new foundation, there'll be a new set of conferences, and we'll all rally up and probably do this again. So what's interesting now is what people are actually using the technology for. Some people are launching new things that maybe weren't possible because infrastructure costs were too high. People able to jump into new business segments. You start to see these channels on YouTube where everyone can buy a mic and a B app and have their own podcasts and be broadcast to the globe, just for a few bucks, if not for free. Those revolutionary things are the big deal and they're hard to come by. So I think we've done a good job democratizing these ideas, distributed systems, one company got really good at packaging applications to share with each other, I think that's great, and never going to reset again. And now what's going to be interesting is, what will people build with this stuff? If we end up building the same things we were building before, and then we're talking about another digital transformation 10 years from now because it's going to be funny but Kubernetes will be the new legacy. It's going to be the things that, "Oh, man, I got stuck in this Kubernetes thing," and there'll be some governor on TV, looking for old school Kubernetes engineers to migrate them to some new thing, that's going to happen. You got to know that. So at some point merry go round will stop. And we're going to be focused on what you do with this. So the internet is there, most people have no idea of the complexities of underwater sea cables. It's beyond one or two people, or even one or two companies to comprehend. You're at the point now, where most people that jump on the internet are talking about what you do with the internet. You can have Netflix, you can do meetings like this one, it's about what you do with it. So that's going to be interesting. And we're just not there yet with tech, tech is so, infrastructure stuff. We're so in the weeds, that most people almost burn out what's just getting to the point where you can start to look at what you do with this stuff. So that's what I keep in my eye on, is when do we get to the point when people just ship things and build things? And I think the closest I've seen so far is in the mobile space. If you're iOS developer, Android developer, you use the SDK that they gave you, every year there's some new device that enables some new things speech to text, VR, AR and you import an STK, and it just worked. And you can put it in one place and 100 million people can download it at the same time with no DevOps team, that's amazing. When can we do that for server side applications? That's going to be something I'm going to find really innovative. >> Excellent. Yeah, I mean, I could definitely relate. I was Hortonworks in 2011, so, Hadoop, in many respects, was sort of the precursor to the Kubernetes area, in that it was, as I like to refer to, it was a bunch of animals in the zoo, wasn't just the yellow elephant. And when things mature beyond it's basically talking about what kind of analytics are driving, what type of machine learning algorithms and applications are they delivering? You know that's when things tip over into a real solution space. So I definitely see that. I think the other cool thing even just outside of the container and container space, is there's just such a wealth of data related services. And I think how those two worlds come together, you brought up the fact that, in many respects, server-less is great, it's stateless, but there's just a ton of stateful patterns out there that I think also need to be addressed as these richer applications to be from a data processing and actionable insights perspective. >> I also want to be clear on one thing. So some people confuse two things here, what Michelle said earlier about, for the first time, a whole group of people get to learn about distributed systems and things that were reserved to white papers, PhDs, CF site, this stuff is now super accessible. You go to the CNCF site, all the things that you read about or we used to read about, you can actually download, see how it's implemented and actually change how it work. That is something we should never say is a waste of time. Learning is always good because someone has to build these type of systems and whether they sell it under the guise of server-less or not, this will always be important. Now the other side of this is, that there are people who are not looking to learn that stuff, the majority of the world isn't looking. And in parallel, we should also make this accessible, which should enable people that don't need to learn all of that before they can be productive. So that's two sides of the argument that can be true at the same time, a lot of people get caught up. And everything should just be server-less and everyone learning about distributed systems, and contributing and collaborating is wasting time. We can't have a world where there's only one or two companies providing all infrastructure for everyone else, and then it's a black box. We don't need that. So we need to do both of these things in parallel so I just want to make sure I'm clear that it's not one of these or the other. >> Yeah, makes sense, makes sense. So we'll just hit the final topic. Chris, I think I'll ask you to help close this out. COVID-19 clearly has changed how people work and collaborate. I figured we'd end on how do you see, so DockerCon is going to virtual events, inherently the Open Source community is distributed and is used to not face to face collaboration. But there's a lot of value that comes together by assembling a tent where people can meet, what's the best way? How do you see things playing out? What's the best way for this to evolve in the face of the new normal? >> I think in the short term, you're definitely going to see a lot of virtual events cropping up all over the place. Different themes, verticals, I've already attended a handful of virtual events the last few weeks from Red Hat summit to Open Compute summit to Cloud Native summit, you'll see more and more of these. I think, in the long term, once the world either get past COVID or there's a vaccine or something, I think the innate nature for people to want to get together and meet face to face and deal with all the serendipitous activities you would see in a conference will come back, but I think virtual events will augment these things in the short term. One benefit we've seen, like you mentioned before, DockerCon, can have 50,000 people at it. I don't remember what the last physical DockerCon had but that's definitely an order of magnitude more. So being able to do these virtual events to augment potential of physical events in the future so you can build a more inclusive community so people who cannot travel to your event or weren't lucky enough to win a scholarship could still somehow interact during the course of event to me is awesome and I hope something that we take away when we start all doing these virtual events when we get back to physical events, we find a way to ensure that these things are inclusive for everyone and not just folks that can physically make it there. So those are my thoughts on on the topic. And I wish you the best of luck planning of DockerCon and so on. So I'm excited to see how it turns out. 50,000 is a lot of people and that just terrifies me from a cloud native coupon point of view, because we'll probably be somewhere. >> Yeah, get ready. Excellent, all right. So that is a wrap on the DockerCon 2020 Open Source Power Panel. I think we covered a ton of ground. I'd like to thank Chris, Kelsey and Michelle, for sharing their perspectives on this continuing wave of Docker and cloud native innovation. I'd like to thank the DockerCon attendees for tuning in. And I hope everybody enjoys the rest of the conference. (upbeat music)

>> live from Las Vegas it's the cube, covering Magento Imagine 2019. Brought to you by Adobe. >> Hey welcome back to the cube, Lisa Martin with Jeff Frick live at The Wynn Las Vegas for Magento Imagine 2019, with about 3500 people here give or take a few. We're very pleased to welcome Magento evangelist Ben Marks to the Cube, Ben welcome >> Thank you for having me, I appreciate you making time. >> And thanks for bringing the flair to our set. >> I've got to let people know where my allegiances lie, right? >> So this is the first Magento Imagine post adobe acquisition, that was announced about a year ago completed about six or seven months ago. You have a very strong history with Magento the last 10 years, Magento is very much known for their developer community, their open source history and DNA. Talk to us about, how things are now with the community and really the influence that the developers have. >> Well if it's up to me we retain this really strong influence in the business. I mean at the the core of Magento since its inception the very humble beginnings that it had back in back in 2007 has been this this developer ecosystem. And that is what takes the software basically all the output and all of the expertise and intuition that we have that we put into our products and our services, it only goes so far. Now it is a platform that tends to fit in a lot of places but it only goes so far and we have that last mile, that is the most important distance that we cross and we cannot do it without this ecosystem. They are the ones that they know, they understand the merchant requirements, they understand the vertical, they understand the region, they understand cross border concerns, whatever it may be they know our product from an expert perspective and then they take that and they make it make sense. That being the case, Adobe I think so far has shown excellent stewardship in terms of recognizing the value. A big part of that 1.7 billion price tag, they paid for the community. They knew this ecosystem was the real, has always been the x-factor in Magento and so they've been very diligent, well now that I'm an employee we've been very introspective about what that means as part of adobe, is part of this this massive set of opportunities and new addressable market that we have. And we're just all trying to make sure that we look after all of these people who are at the end of the day probably our biggest champions. >> Just curious how you've been able to maintain that culture because to be kind of open source and open source first timer, first isn't the right word but open source neutral or pro, along with your proprietary stuff and to really engage developers it's such a special town and as a special culture because by rule you're saying that there's more smart people outside of our walls than inside of our walls and embracing and loving that. But you guys have gone through all kinds of interesting kind of evolutions on the business side in terms of ownership and management. How've you been able to maintain that? And what is kind of the secret sauce? Why are the developers so passionate to continue to develop a Magento? Because let me tell you we go to a lot of conferences and a lot of people are trying really hard to get that developer to spend that next time working on their platform versus a different one. >> Yeah, well you know it's endemic to our culture that whether it's a developer, someone who's working who's an expert in administering Magento stores, just whatever someone's focus is in this ecosystem, it is interesting we've always had at the underpinning everything has been this open source ethos. So from the very beginnings of Magento, the creators Roy Rubin and Yoav Kutner, they sought out as they announced this Magento thing back in the day. They intentionally made it open-source because they knew that, that had been proved by a previous open-source commerce software and they knew that that was really where they were going to win that was the force multiplier. Again the thing that would get them into markets that they couldn't address with their very small agency that they were walking out of. So through the years that grew and in large part we can thank the Doc community, especially in Germany, the Dutch community, there's just the general open source ethos there. But I learned about open source from Magento, I had someone help me out when I was first starting at my first week working with Magento as a developer there was no documentation, I had to go into a chatroom and ask for help and this guy he actually spent about a couple of hours helping me and we remain close friends to this day. But at the end of it I'm like so should I pay you? And he was this guy this guy from outside of Heidelberg he's just no this is open source, is like just as you learn give it back. And that's a perfect summation for a big part of the spirit here. It helps who are in commerce, there's money kind of flowing all around but at the end of the day we provide options, we provide flexibility where there's nothing wrong with the sass platforms there's nothing wrong with some of the the larger like API driven platforms, it's just at some point if you have a custom requirement that they can't satisfy and that happens regularly, guess what? You got to go with the platform that gives you the extensibility. So they feel a sense of ownership I think because of that and they're sort of proud to take this wherever they can. >> So with the Adobe acquisition being complete around six eight months you mentioned Adobe doing a good job of welcoming this community but you also talked about this core ethos that Magento brings. I believe in the press release, announcing the acquisition last year, Adobe said open source is in our DNA. Have you found that one to be true? And two how much has the Magento open source community been able to sort of open the eyes and maybe open the door to Adobe's ethos of embracing it? >> Let's see how much trouble can I get in to today? >> So I have a good counterpart over Alberto Dobby and it's a stretch for me to call him a counterpart. He's got his JD,he's been big in the open source world for since forever but, Matt Asay probably... >> CUBE alum >> ...if you follow tech online, you've seen this post, you've seen him as an postulating on open source and it was interesting a lot of us were asking the same question from Magento world because a lot of us remembere the eBay days and an eBay had a sort of a different plan and vision for Magento that ultimately, that whole thing they were trying to create just didn't work out. Magento survived, but we're a bit wary we all knew it was coming it's the natural progression from private equity ownership but really, where is this open source that we were told about? And Matt is a kind of a big a piece there but as it turns out he jumped on Twitter immediately when none of us was supposed to be talking about anything of course but that's in Matt's nature. Because there is a lot of open source at Adobe in fact there's a lot of open source technology that underpins even these Enterprise Solutions that they offer. I visited with with several of our team members in the Basel office and there are Apache Software Foundation board members. I mean you want to to talk about the beginnings of open source and the impact its had on the world? These are some of these people and so yes it's there I think it's not a secret to say that Adobe really hasn't done a great job of telling that story. So as I've met and kind of toured around with some of the Adobe vice presidents who've been visiting here and I love that they're engaged. They get this, they want this to expand. It's been it's been really interesting watching them and encounter this and then start to be inspired by us as much as we are inspired by again the opportunities that exist as we all come together. >> It's great, yeah and Matt's been on his Trevi a week cover, CNCF and will be a cube con I think next week and in Barcelona so we're huge advocates, but so it's such a different way of looking at the world again accepting that there's more smart people outside your four walls than are inside your four walls. Which just by rule is the way that it has to be, you can't hire all the smart people. So to use that leverage and really build this develop wrapped advocacy is a really tremendous asset. >> Better together, is what we say, and it could not be true. I mean there there is no way we could know at all, we can't hope to. So what we've done actually in the last couple of years really under some brilliant leadership by Jason Woosley we've been able to double down on our open-source investment and I'd say that was a moment when we truly became an open-source company with through and through because we spun up and we took our best architects and just put them on a project called community engineering that they're dedicated to enabling contribution of fixes improvements and features from our ecosystem. So by doing that we all of a sudden we now have worldwide engineering that is that they're all experts in their individual domains so that line of code that some contributor from somewhere is contributing, he or she has become an expert let's say in something as glamorous like totals calculation like the logic that has to go into that. Because of their real-world experience we get the highest quality code that's just backed up by a lot of trial and tribulation. And from that we basically get to cover all of our bases and they tend to write things in a way that's way more extensible than probably we could ever envision. I don't know of a better formula for having a product that satisfies something so varied and challenging and just constantly evolving as e-commerce. >> Well and I think Jason mentioned this morning that the community engineering program was only launched a couple of years ago. >> Literally a two years ago February. >> So significant impacts in a very short period of time. >> Yeah we were fascinated to see that while we'd had this kind of haphazard almost ad hoc open source engagement up to that point, once we really built machinery around it We've we've managed to build something that is a model for any other company that wants to try to do this. Once we did that we very quickly got to some of our big releases where over 50% of the new lines of code were written externally. And that was cool for about a week and then we realized that that's not even the story the story is everything else I talked about which is just that degree of ownership that degree of informed engineering that we would never come up with on our own. And it was a real signal to this very patient and resilient ecosystem that hey, we're all in this together. And of course we've done that also, we've replicated that with our developer documentation, it's all open source and able to be contributed to and we sort of look at how that can expand and even to the point where our core architecture team now all of their discussions so you can go to github.com/magento, you can see our backlog, you could see where we're discussing features and kind of planning what's coming next. You can also go to our architecture repository and you see all of our core architects having their dialogue with each other in public so that the public is informed and they can be involved and that is literally the highest stage I believe of open source evolution. >> That's a great story now the other great thing though that it don't be brought to you is some really sophisticated marketing tools to drive the commerce in your engine, so I'm just curious your perspective. You've been playing in this for a long time but you guys are really kind of taken over at the transactional level now to have that front-end engagement tools, partners, methodologies, I mean you got to be excited. >> Well really so going back to my, I remember my agency days I remember why some of the Google Analytics code looks the way it does because I remember the product that it was before. Urgent analytics right and I remember when we could first do split tests and one of the first cool projects I ever worked on in Magento 1.1 was sort of parsing Google's cookies to be able to sort of change the interface of Magento and test that for conversion rights. And to think of how far we've come, now we have the power and the mandate really to absolutely know everything about the customer experience, the customer journey and then I'm sitting there in our keynotes you know in the general session yesterday, looking up and I'm looking at the slide and I'm seeing like 14 trillion transactions that are captured in our various apparatus and I think that it's tremendous responsibility, it's tremendous power. And if we if we combine, if we use this insight responsibly, what we do is we continue to do what I think Magento has done all along which has allowed us to be at not just at the forefront of where commerce evolves but really to set the standard that consumers begin to expect. And I know we've all felt it, when you have when you have that experience and it feels very full of friction I know we can do better and I will immediately go away from any website that makes it hard for me to do what I want to do any website that seems like they are kind of a partner on my journey that's where I mean that's we're going to spend my time and my money and that's really what we're trying to really lean into here. >> Which is essential, because as you mentioned if I'm doing something on my phone I expect a really fast transaction and there's friction points, I'm gone. I will be able to find another service or product that meets my need because there is so much choice and there's so much competition for almost every product and service. So being able to leverage the power of advertising, analytics, marketing and commerce to really deliver the fundamentals of the business needs to truly manage the customer experience is a game changer. >> Yap it is so what we're what we're looking to these days you know Magento, just before the acquisition was announced made a tremendous investment to start up it's completely independent trade association called the Magento Association. It's a place for our community to collect under. And and when we're here and Magento is still a big champion of ours a big source of investment and we are you know we are looking and I kind of wear both hats right because I'm a board member of that group as well as being a Magento Adobe employee. But one of the focus that we have is still that collaborative spirit where we start to carry the message and the capabilities of this tooling so that we can ensure that this ecosystem remains and powered to deliver the experiences that our customers and their customers expect. >> Absolutely, well Ben thank you so much for sharing your knowledge and your enthusiasm and passion >> Yeah did that come through I was hoping. >> You could next time dial it up a little bit more. >> Okay good. >> Awesome and bring more flair. >> I'll bring more flair next time. [Lisa Mumbling] >> I'm still wondering what happened to the capes? >> The magician master capes yes. >> I can I can probably go grab you a couple. >> That would be awesome orange is my favorite color. >> Good to know. >> Ben it's been a pleasure having you on the program we look forward to next year. >> Likewise thank you both. >> Our pleasure. For Jeff Rick, I'm Lisa Martin and you are watching theCube live at Magento imagine 2019 from Vegas. Thanks for watching. (upbeatmusic)

>> Announcer: Live, from Vancouver, Canada it's the CUBE, covering OpenStack Summit North America 2018, brought to you by Red Hat, the Open Stack Foundation, and it's ecosystem partners. >> Welcome back, I'm Stu Miniman and my cohost John Troyer and you're watching the CUBE, the worldwide leader in tech coverage. Happy to welcome back to the program long time friend of the CUBE back from the earliest days, Randy Bias, Vice President with Juniper, Randy, great to see you. >> Absolutely, great to be back with you guys. >> All right, so Randy, we've been talking about, you know, community, and everything's going good and attendance might be down a little bit but how we fit in with containers and kubernetes, and everything, so we expect you to tear everything up for us and tell us the reality of what's happening in this community. >> I'll do my best (laughing). >> All right, so before we get to the kubernetic stuff, you're working on, we used to call it OpenContrail? Which you were involved in before Juniper acquired it, went through a rebranding recently, Tungsten, which I was looking up, came from the word heavy stone, give us the update from the networking side. >> Yeah, so the short history is that there was a company called Contrail, and they created a software defined networking controller, it was acquired by Juniper in 2012, 2013, and then that was open sourced, so Juniper for a long time was running with sort of two editions, Contrail which was the commercial offering, and OpenContrail which was the open source, and then shortly after I joined Juniper, identified that, you know, we really needed to go back to the drawing board on the way that we had organized the community, and transition it from being Juniper-led to community led, and so over the past year, I spearheaded that effort, and then that culminated in us announcing at the end of March at ONS that, you know, OpenContrail was now Tungsten Fabric. We renamed it, we moved it into the Linux foundation, under its governance, and now Juniper is one of many people of the community that have a seat at the table for the management, both from a business and technical perspective, and we're moving forward with a new reinvigorated community. >> Yeah, so networking sits at really the intersection of this multi-cloud world that we're living in. There's so many players trying to be there, you know Cisco, really moving to become more of a software company, when I interviewed their number two guy at their show, he's like, when you think of Cisco in the future, we're not even going to be a networking company, we'll be a software company. VMware, of course, pushed heavy through, then the Nicira acquisition, where does Tungsten fit, kind of compare and contrast for us, where it fits among some of these other offerings out there in the marketplace. >> Yeah, I mean, I think most enterprise vendors are in a similar transition from being a hardware to software companies. We're no different than any of the rest. I think we have a pretty significant advantage in that we have a lot of growth in the cloud sector, so a lot of the large public clouds are our customers and we're selling a tremendous amount of hardwaring to them, so I think we've got a lot longer runway. But, you know, we just recently hired CTO, Bikash Koley, out of Google, and we're starting to see some additional folks out of Google, like my new boss, Morgan, and what that's bringing with it is a very much a software first type perspective. So Bikash and Morgan really built everything for the Google network from the topper rack all the way out to the win and it's almost all software-based, disaggregated, hardware, software, opensource software running on top of white boxes, and so that kind of perspective is now really deep, start beginning to become embedded in Juniper. And at the head of that is Tungsten. So we see Tungsten Fabric as being sort of a tool that we use to create, you know, a global ubiquitous network fabric, that anybody can use anywhere, without talking to Juniper at all, without knowing that Juniper's part of Tungsten, and then as they grow up and they get to a point where they need multi-cloud, they need federation, or they need kind of day two enterprise operations, you know, we have a commercial version and a commercial distribution that they can use. >> Randy, we talked a little bit about OpenContrail and last year, at OpenStack Summit and moving it to a more of a community based governance model, and now that's happened with the Linux Foundation, can you talk a little bit about the role of opensource governance, and corporate governance, and then foundations, and just going forward, you know, what's an effective model for 2018 going forward, for a foundation-led project and maybe in the context of Tungsten Fabric, and how is that looking? >> Yeah, so again, OpenContrail's now Tungsten Fabrics, might be new for some of the viewers, lot of people still coming to terms with that. And so one of the things that we noticed is that, and when many people go and they say, hey, we want opensource first, the AT&T's of this world, part of what they're saying, one of the aspects of being opensource versus we want to be one of many around the table, we want to have a seat at the table, we want to have the option to contribute code back, and we want to feel like it's a group effort. And so that was a big factor, right? It was an opensource project, but it was largely the governance was carried by Juniper, all the testing infrastructure was Juniper, you know, all of the people who made architectural decisions were Juniper, all of the lead contributors were Juniper, and so, going to Linux Foundation was critical to us having a legal framework, for the trademarks, the code, the licenses, the contributor license agreements, are all owned and operated by the Linux Foundation and not by Juniper, so we basically have a trusted third party who can mediate all those things and create a structure, a governance small structure where Juniper has one seat at the table, and all the other community members do as well. So it was really key to getting, to moving to that model to increase people's interest in the project and to really go the next level. There just wasn't any way to do it without doing this. >> All right, so, Randy, let's talk about OpenStack. You were watching the keynote yesterday, you were, you know, in the Twitter stream, >> Randy: I don't usually watch keynotes, man. >> Stu: But you know this community, so-- >> I do know this community (laughing). >> Give us kind of the good, the bad, and the ugly from your standpoint as to, you know, where we've gone, you know, what's doing well, and what you're frustrated as heck that we still haven't fixed yet. >> Well, I mean, it's great that we have so much inroads amongst the carriers, it's great that, you know, that there's a segment that OpenStack has been able to land in. I mean, at some points when I was feeling particularly pessimistic on some days, I was like, oh man, this thing's never going to go anywhere, so that's great. On the other hand, you know, the promise that we had of sort of being the Linux operating center, operating system of the data center, and you know, really gaining inroads into private cloud and enterprise, that just hasn't materialized and I don't see a path to that. A lot of that has to do with history, I'm not sure how much of that I want to go into here, but I see those as being bright lights. I see the Ocata containers effort and sort of having this alternative structure that's more or less like the umbrella structure that I lobbied for while I was on the board. So for several years on the board, I said we need to really look more like the Apache Software Foundation, we need to look less like the Linux Operating System in terms of how we think about things. Not this big integrated monolithic release, you need more competition between projects and that just wasn't really embraced. And I think that that, in a way, that was one of several things that really kind of limited our ability to capture the market that we really wanted, which is the enterprise market. >> Yeah, well, I know, and one of those sticking points there that I've talked to you many times over the years about is how do I actually deploy this? You know, getting a base configuration and scaling this out, simplicity is tough, getting to those environments, you know, getting it up in two weeks, is good for some environments, but maybe not for others. >> Yeah, I mean I think there's sort of a spectrum, right? At one end of the spectrum, you say hey, I'm going to have a very opinionated approach like kubernetes does, and we're going to limit what we say we can do, you know, we're not all things to all people. And I think that opinionated approach, like the Linux operating system worked very, very well. And then other end of the spectrum is we've got no opinion like the Apache Software Foundation, and then it's up to vendors to go and cherry pick the pieces they want and turn that into some kind of commercial offering, whether it's Hortonworks, or Thi-dare or Du-per or whatever it is, the problem is that OpenStack wound up in the middle where it had the sort of integrated monolithic release cycle which it still does, which started to be all things to all people, and it was never as great as it could be, so it's like we got to support Hyper-V, we got to support VMware, and as the laundry list of all things we have to support grew longer, it became more and more difficult to have a compelling, easy to use, easy to scale offering that any enterprise could consume. >> Randy, a lot of talk this week about edge computing, with several different definitions, right? But it does strike me that, you know, there's a certain set of apps, that you write 'em and that they live fine in a big public cloud, and a big data center somewhere. But there's a lot of hardware that's going to be living out in the world, whether that's at the base of a radio tower, or in a wall, or in my shoe, that is going to be running hardware, and is going to be running something, and sometimes that something can be OpenStack, and we're seeing some examples of it, many examples of that already. Is that an area of growth for OpenStack? Is that an interesting part of how this fabric is going to expand? >> Well, I probably have a contrarian view here. So, I spent a bunch of time at Juniper, one of the things I worked on for a while was edge computing and we're still trying to decide what we want to do there and you know, kind of to the first point you made is everybody's edge is different, right? Is it on the mobile phone, is it back in the data center, the difference is that the real estate gets more expensive as you move out, right? And it's in terms of latency, and it's in terms of bandwidth and it's also in terms of cost of storage and compute. There's a move closer to the mobile device that becomes progressively more expensive, and so that's why a lot of people sort of look and say hey, wouldn't it be nice if we can get you out the closer lower latency and bandwidth and so on but as we looked at it, a lot of the different use cases it became really interesting in that, it wasn't clear if there was that much value between 5 milliseconds and 20 milliseconds, right? I mean, that's pretty, either one's pretty close, sure there's a lot of difference between 20 and a 100, but maybe not so much between 5 and 20. And so we kind of came to the conclusion that at least for right now, probably, the bulk of use cases are fine with 20 milliseconds, and what that means is that regional systems like AWS's Lambda at the Edge, they're in metro, those are probably good for most cases. I don't know that you need to be on the tower, I don't know that you need to be in the central office, so I think edge computing is still nascent, we don't know exactly what all those use cases are, but I think you might be able to service most of them from regional data centers, and then the question really becomes what does that stack need to be and if you have a regional data center that's got plenty of power, plenty of space, then it might be that OpenStack is a good solution, but if you're trying to scale down onto the tower, I got to have some doubts about whether OpenStack can really scale down that far. >> Randy, analytics is something we've been seeing, the networking people used for many years, at this show, starting to hear a lot of discussion about AI and ML, would love your view point as to what you're seeing in that space. >> You know I have some friends who started off in AI in very early days and he had a very pessimistic view. He said, you know this stuff comes and goes, but I'm actually very positive and optimistic about it because the way I look at this is there's a renaissance happening which is that, you know, now ML is really available to masses and you're seeing people do really interesting things like, we have a product called AppFormix, and what they do is they take ML and they apply it to operations and I love this because as an operations guy, you know, I used to have these problems in production where something would go out and the first thing I'd do, is I'm trying to do correlation and then root cause analysis, like, what was the actual failure? Like I can see the symptom on this end and now I have to get all the way back to what caused it, and the reality is that machine learning, AI techniques and protocols can do all the heavy lifting for operators very, very quickly and basically surface a problem for somebody to do the final analysis on. And so I do think that ML and AI apply to very specific vertical problems, it is just a place where we're going to see a tremendous amount of revolution in the next couple years. >> All right, and that hits right at really that intersection between kind of the developers and the operators there-- >> Absolutely. >> What are you seeing from an organizational standpoint, companies you're talking to these days, how are they doing adopting that change, dealing with that, you know, often schism or are they bringing those groups together? >> Well, I think you remember that like in the early days, I used bring my deck along and I would talk about assembly line IT versus the robotics spectrum all of IT and I would sort of make that sort of analogy to sort of the car manufacturing process, and I think what machine learning is really going to do is take us to that next level past that right? So we had the assembly line where we have all the specialists, we had the robotics factory where we had people who know how to build a robots and software, and it's really sort of like, just churning out with a lot of people on the line, and I think the next level after that is, you know, completely fully automated applications driving themselves, you know, self-driving applications, and I think that's when things get really interesting, and maybe we start to remove the traditional operator out of the equation and it really becomes about empowering developers with tools that are comfortable and that leverage all the cloud era and stuff that we built. >> All right, so Randy, you're credited with the pets versus cattle analogy, what's the latest, you were talking about some of the previous slide decks, what's Randy Bias looking on down the road? >> I mean, the stuff just comes to me, man. I can't like predict, but the thing I've been talking about a lot lately is services of platform, I think we might've talked about that last time, which is just this notion that if we look at where Amazon's invested and what's interesting, it's certainly not at the infrastructure layer and it's really not at the PAS layer, it's that thick layer in between with like database as a service and NoSQL as a service, and messaging service, and DNS and so on, where you can kind of cherry pick those things as you're assembling your own PAS for your application, and I still think that's the area that is under-discussed, and the reason is is the people back into basically doing that, building kind of the service as a platform system, but they're not like going into it, kind of like eyes wide open. >> Yeah, so just following up on that last piece, one of the criticisms I have this week is when you talk about multi-cloud, most of the people talk about, oh well people are clawing things back to their data centers. Juniper plays across the board, strong partnership with Amazon, yet you're here, what are you hearing from customers, you know, what do you see as kind of the balance there and, you know, the public cloud's role in the world? >> I mean, they're still winning, right? I don't think there's any doubt, I haven't seen a decline back here talking about, but we are starting to enter into the era of, okay, this stuff is out there, and it's running, but I need to find my governance model, I need to understand who's using what, I need to understand what it's costing me, and that's the sign of the maturation process. And so I think that, you know, we saw in the early days of cloud, people jumping the gun, creating compliance services, and you know, SAS products that would basically measure how much you're spending and think that it's time for that stuff to come back in vogue again, because the tool needs to be there for people to manage these extended supply chain of IT vendors which include the public cloud. And I think that the idea that would claw them back as opposed to like just see that as holistic part of what we're trying to accomplish doesn't make any sense. >> Well learned. Well, Randy Bias, always a pleasure to catch up with you. >> John. >> John Troyer, I'm Stu Miniman, getting towards the end of two days of three days of live coverage. Thanks for staying with the CUBE. (bubbly electronic music)

(upbeat music) >> Narrator: Live from the Seattle, Washington, it's the Cube on the ground, covering KubeCon 2016. Brought to you by the Linux Foundation and Red Hat. Here's your host, John furrier. >> Hello, everyone. Welcome to the Cube special on the ground coverage of KubeCon or CloudNativeCon, this is an event. Seattle booming with attendance, great growth from last year, and we are here in Seattle covering it all. And my next guest is Dan Kohn, who's the executive director of the CNCF, which stands for the Cloud Native Computing Foundation. It's a mouthful, but it's super important part of the Linux foundation. Welcome. >> Thanks so much, really glad to be here. >> Yeah, so big fan of what's happening here. One, the event's awesome. Great uptake from last attendance from last year. >> Yeah, unfortunately, maybe a little too much. We're a little crowded in the foyer and a little bumping on the way into getting in the restroom and everything, but it's one of the challenges of fast growing technology space is trying to figure out a year ahead of time, what size space to get? >> And how many people to squeeze in without getting the fire marshal on your back. >> Exactly. >> Certainly this is going to be a great one because the hallway conversation has been spectacular, and normally the excitement's pretty strong at tech events like this because they're developers, so there's a lot of collaboration going on. But you have a kind of an air of really forward-thinking entrepreneurial kind of thinking going on here. And I haven't seen that in a while and I think that's one of the main things that we're seeing that came out of the containers, Kubernetes. I would say the unveiling and the clarity of at least a path. >> Yes, absolutely. >> And the importance of that. So that's been super important to (indistinct) community. Now making that a part of a foundation, an open source, has challenges. So that's what you're doing. So give us the plan, what's the strategy? >> Sure, so I'm actually relatively new to the space. I just became an executive director five months ago, and this is somewhat of a coming out party. This is the first big event that we've run as the first CloudNativeCon. And it's really just been extraordinary. I'm thrilled to see the range where we're getting some of the biggest companies in the world of the Cisco's, and Wallway's, and IBM's, Red Hat's and such. And then tons of startups, and a lot of real diversity in the end-users as well. Of startups looking at Kubernetes, massive companies, just saw a great presentation from Ticketmaster, about them having 50 year old technology that they're moving forward and putting into containers. >> So in the growth of the market, one of the challenges is to kind of, you know, not so much be a chess player, but be a gardener if you will, kind of like let the flowers bloom, if you will. And that's a challenge cause opensource is very opinionated, but there's also a lot of passion involved. So how do you look at, what's your philosophy on establishing kind of a rules of engagement? How do you foster the innovation? Certainly the market drivers are for more growth, but people have inhibitors on the enterprise that we hear about, support and these things of that nature. So how do you enable that? What's your strategy and what's your view? >> Sure, so CNCF is a very new organization. And my goal on it is to look at a lot of the giants that have come before us of like the Internet Engineering Task Force and the Apache Software Foundation and OpenStack. And my goal is to try and learn from them and ideally to try and make entirely new and different mistakes as opposed to the ones that they may have made in the past. So one of the things that's a little unusual in our setup is that we very much separate all of the technology decisions from the business decisions. We have a governing board of a bunch of the biggest technology companies in the world, the ones I mentioned, plus Google and Samsung just joined, which we're very excited about, a number of others. But they can't actually adopt projects in. So we have a separate group called the technical oversight committee, which is some of the top architects in the cloud space. So we have folks like Ben Hindman of Mesosphere, and Solomon Hykes of Docker, Brian Gantt of Google, and six others, and that's the group that looks at new projects and evaluates them and talks to them and decides whether to adopt them into CNCF or not. And we feel that that separation is really critical so that the technology decisions are not being biased by the business one. >> Yeah, it's always hard to foster growth in the innovation around business models, conflicting with the technology enablement, that's really key. Great to see that decoupling. So on the business model side, thoughts on things that you've learned and observed, learnings that you've had in your past career and applying that now, I mean, the Bait, the rage is on, Open Core to Apache, GPL, you saw some things going on there. So there's like all kinds of different approaches. Are there any thoughts of the winds blowing any which way or the other? >> Sure, I was previously the chief operating officer at the Linux Foundation between '06 and '10, and I definitely think you can, CNCF as part of the Linux Foundation, we took that model of saying, "the technology decisions "need to be separate from business ones." One thing that's interesting to me is that when I was last in this space 10 years ago, people were perfectly fine. Linux Journals, GPL, people were fine with free licenses like MIT and BSD. Since then, and for this group, there is an enormous focus on the Apache license. And the reason why, is the fear of submarine patents. And so the whole goal of CNCF is for us to be an intellectual property no fly zone. That you can have all of these companies that compete very hard in the marketplace, but they can come together and collaborate and share their ideas and their technology without the belief that a couple years later, someone's going to be able to trick someone else in with a lawsuit, and win that. And the Apache license is really the industry consensus right now for best practices. >> It's interesting cause that no fly zone gives the freedom for the creation and the invention side of it. The patent thing is always worrisome, but in general, there's also the business model down the road kind of approach. Which is, "let's go innovate." Apache has done great on packaging. Have someone get some traction. It fosters the community aspect as well as a startup. Maybe not thinking about packaging. >> No, we have an advantage that we're not, unlike OpenStack as an example, we're not trying to come up with the projects ourself. What we're actually doing is scouring the Cloud Native landscape, talking to different groups and saying, "Oh, what do we think is "the best in class project out there?" And in some cases it's more than one, but today we just announced the fourth project that's added to the CNCF. So we have Kubernetes, we have Prometheus, which is a monitoring application. OpenTracing is a tracing, and then today we just added Fluentd, which is a logging solution. And this is the idea that if you have dozens or hundreds of different applications and projects that are each producing a log stream, and then you have a perhaps dozens of other applications that are consuming it, you don't want to have an M times N problem of creating adapters for all of them. Instead, you can plug them all into Fluentd, it has over 300 adapters for different solutions out there. And that provides one comprehensive approach. But what's interesting is that we don't need to win over the community and say, "Oh, here's this project you may not have heard of." There's actually over 2000 users of that today. But by having them here at CNCF, showing how it plugs into other technologies of ours, we think we can hope-- >> You're cross-pollinating? >> Dan: Exactly. >> You're letting it bubble up and you're not being a-- >> Dan: That's exactly the metaphor. >> (laughs) A dictator. Okay, and back to the project side, this is awesome. So you have some gravity around these projects. Is there any cadence or expectation, or is it free for all in terms of the velocity of adoption of projects that the technical committee will oversight? >> We would love to be at the pace of one a month. And I don't know that we'll quite get that fast. One big change that we're hoping to make in the next month or two. When our first two projects were Kubernetes and Prometheus, those are two of the fastest growing best respected projects on GitHub right now. We didn't want to have such a high milestone for every other project we considered. So we're adopting what we think we're going to call an inception stage of earlier projects that we're going to sort of try out, but they have to essentially prove themselves within 12 months. And hopefully that'll allow us to keep a pretty good velocity where we think there's a fantastic number of projects, we think as a community, we can-- >> Yeah, let people fight it out, surface stuff and let people kick the tires, right? That's the incubation period basically. What about the forking and all the battle cage matches that go on, how do you want to handle that or you just let nature take its course? Is that philosophy there? >> Thankfully, when we look at the space and this is really coming out of the Linux Space as well, anyone can fork, and of course it has a slightly different connotation now with GitHub, where when you make a change, you fork it, but there's also just a massive centripetal force pushing people together. And when you have a really high velocity of changes, the idea of forking and you would lose out on that, becomes a lot less appealing. And so, so far thankfully, all of our members and everyone in the community has really been on board on having a single head on working together to have that consultation. >> We just had Richard Kaufman on from, I think Robert Kaufman, I mean, from Samsung, he was talking about that the number two contributor is other. >> Dan: Yes. >> Which is a nice balance to the whole critical mass. >> It's an incredible accomplishment cause for Google to pull in enough people that they're no longer the majority contributor, is something that we're thrilled with. >> Yeah, it's great to see you have Richard Kaufman. Google is the number one contributor, are you worried about that? Maybe, they've been certainly good actors in the community. I mean, they had MapReduce and let Cloudera run with it, look at what happened with that? So, we kind of all know this backstory of Kubernetes, they're kind of letting it bloom on its own. That's consistent with their current posturing? >> Well, I don't think they want to have another Cloudera. >> Which is why they embraced Kubernetes. >> But I definitely don't think it's fair to say that they're doing it on their own. They're still the largest contributor of any one company and they have a massive amount of resources, and I think they see it as a really key technology, it's something they mentioned-- >> What I was referring to is that Cloudera kind of took MapReduce under their wing and made a commercial venture out. >> Dan: Oh yeah, absolutely. >> I think Google didn't want that. >> No, and they, I mean, the way I think about it is, they had this technology a few years ago. This is definitely oversimplified. They could have kept it as a proprietary in the house thing, like Amazon Elastic Container Service. They could have made it an internal open source project, like Go, or they could have just created a Kubernetes foundation that allowed other people in, but they still controlled it. But instead they were really interested in working with the Linux Foundation and creating this Cloud Native Computing Foundation that was always designed to be much more than just Kubernetes. And that really was about trying to push the project out of the nest. But I will say that my understanding is they're still see that as an absolutely core for their business. >> Yeah, I got to give Google props out there for that because they did do the right thing there. they put it out in the open, they did a line, and they could have land grabbed that, in a different way, I mean, certainly not the way that one was above. Final question on this event, KubeCon or KubernetesCon, KubeCon, it's KubeCon, however people call it. Not to confuse with the Cube, this Cube product which is seven years and might be trademark infringement but yeah, we'll get that later. >> Dan: With a K. (both laughing) >> It's still causing a lot of confusion. But that aside, CloudNativeCon also is in conjunction, this is part of the expansion you were mentioning. Talk about the vision for the events, you got one in Berlin coming up, and certainly you could have had probably at least a few more thousand people here for sure. >> Oh well, certainly a few more hundred. And we do feel a little bad that we didn't quite aim high enough. So our vision going forward is that we have CloudNativeCon that represents all of our projects, and that KubeCon represents the biggest part of CloudNativeCon. So it's multiple tracks. It's what a ton of folks go for but we think that it also gives us a chance to expose those people to our other projects, and by the time we get to Berlin, we're certainly hoping that we have another two or three or more projects-- >> And the date on Berlin? >> It's March 29th and 30th. And then we also announced that we're going to be in Austin, in early December. And I'll say that for both of those events, we're tripling the capacity from what we had last year. So we're hoping not to be so crowded. >> I was talking to Andy Jassy last night, we had a one-on-one with him and he's talking about the first Reinvent, he didn't think he can get 4,000 people there as packed. I think you might be, having to look at more capacity potentially. I mean, at this pace. >> It's the hard question is we'd actually like to be signing contracts for 2018, and it's just really hard to predict what the right size is to get for that, because I feel terrible about the fact that we did turn people away, especially end-users that we'd like to be introducing to this space. >> Yeah, well, I can attest people watching this, definitely a fire marshal issue, because it's really packed. That's why we're in a separate room here. There was sunlight in the background earlier. Normally, we're on the show floor with the Cube, but yeah, every space is taken, hallways are jamming. >> The other thing I'll mention though, is that we are also interested in going out and reaching customers and vendors where they are. So we're going to have a booth at AWS Reinvent, and we're looking at other conferences that we can be at to help spread the Cloud Native word. >> We're certainly going to be able to have a hundred events this year, so let us know where you're at, we'll certainly bring you guys on. Let me give you the final word. Tell the folks why Kubernetes is so important. Why is this movement, why are people so excited here? For the folks that couldn't make it, what's the vibe, why is it important, and what's the impact to customers in the industry? >> So the belief is that if you're deploying a new modern software application that, putting into containers, using an orchestration platform like Kubernetes, dividing your app up into microservices is a really such a benefit in terms of optimizing your resources, and tying into a whole rapid development process, continuous integration, continuous deployment, that not doing it almost makes it impossible to compete. And so we think there's just a ton of momentum around containerization and orchestration. >> And the speed of the innovation is one of those things if you're not on it, you fall further behind and it takes more energy to catch up if you try to do it by yourself. That's the benefit of the collective communities and it highlights open source. >> Right. >> Big time in terms of successes. Dan, thanks so much for coming on, sharing the perspective, congratulations and sorry for the folks who couldn't make it, hopefully this video will help. This is the Cube here in Seattle for special coverage of CloudNativeCon and KubeCon, here in Seattle. Thanks for watching, I'm John furrier. >> Dan: Thanks. (upbeat music)

>> Narrator: Live from New York, it's the CUBE from Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, Nvidia. And our ecosystem sponsors. Now, here are your hosts: Dave Vellante and Peter Burris. >> Welcome back to New York City, everybody. This is the CUBE, the worldwide leader in live tech coverage. Holden Karau is here, principle software engineer with IBM. Welcome to the CUBE. >> Thank you for having me. It's nice to be back. >> So, what's with Boo? >> So, Boo is my stuffed dog that I bring-- >> You've got to hold Boo up. >> Okay, yeah. >> Can't see Boo. >> So, this is Boo. Boo comes with me to all of my conferences in case I get stressed out. And she also hangs out normally on the podium while I'm giving the talk as well, just in case people get bored. You know, they can look at Boo. >> So, Boo is not some new open source project. >> No, no, Boo is not an open source project. But Boo is really cute. So, that counts for something. >> All right, so, what's new in your world of spark and machinery? >> So, there's a lot of really exciting things, right. Spark 2.0.0 came out, and that's really exciting because we finally got to get rid of some of the chunkier APIs. And data sets are just becoming sort of the core base of everything going forward in Spark. This is bringing the Spark Sequel engine to all sorts of places, right. So, the machine learning APIs are built on top of the data set API now. The streaming APIs are being built on top of the data set APIs. And this is starting to actually make it a lot easier for people to work together, I think. And that's one of the things that I really enjoy is when we can have people from different sort of profiles or roles work together. And so this support of data sets being everywhere in Spark now lets people with more of like a Sequel background still write stuff that's going to be used directly in sort of a production pipeline. And the engineers can build whatever, you know, production ready stuff they need on top of the Sequel expressions from the analysts and do some really cool stuff there. >> So, chunky API, what does that mean to a layperson? >> Sure, um, it means like, for example, there's this thing in Spark where one of the things you want to do is shuffle a whole bunch of data around and then look at all of the records associated with a given key, right? But, you know, when the APIs were first made, right, it was made by university students. Very smart university students, but you know, it started out as like a grad school project, right? And like, um, so finally with 2.0, we were about to get rid of things like places where we use traits like iterables rather than iterators. And because like these minor little drunky things it's like we had to keep supporting this old API, because you can't break people's code in a minor release, but when you do a big release like Spark 2.0, you can actually go, okay, you need to change your stuff now to start using Spark 2.0. But as a result of changing that in this one place, we're actually able to better support spilling to disk. And this is for people who have too much data to fit in memory even on the individual executors. So, being able to spill to disk more effectively is really important from a performance point of view. So, there's a lot of clean up of getting rid of things, which were sort of holding us back performance-wise. >> So, the value is there. Enough value to break the-- >> Yeah, enough value to break the APIs. And 1.6 will continue to be updated for people that are not ready to migrate right today. But for the people that are looking at it, it's definitely worth it, right? You get a bunch of real cool optimizations. >> One of the themes of this event of the last couple of years has been complexity. You guys wrote an article recently in SiliconANGLE some of the broken promises of open source, really the route of it, being complexity. So, Spark addresses that to a large degree. >> I think so. >> Maybe you could talk about that and explain to us sort of how and what the impact could be for businesses. >> So, I think Spark does a really good job of being really user-friendly, right? It has a Sequel engine for people that aren't comfortable with writing, you know, Scala or Java or Python code. But then on top of that, right, there's a lot of analysts that are really familiar with Python. And Spark actually exposes Python APIs and is working on exposing R APIs. And this is making it so that if you're working on Spark, you don't have to understand the internals in a lot of depth, right? There's some other streaming systems where to make them perform really well, you have to have a really deep mental model of what you're doing. But with Spark, it's much simpler and the APIs are cleaner, and they're exposed in the ways that people are already used to working with their data. And because it's exposed in ways that people are used to working with their data, they don't have to relearn large amounts of complexity. They just have to learn it in the few cases where they run into problems, right? Because it will work most of the time just with the sort of techniques that they're used to doing. So, I think that it's really cool. Especially structured streaming, which is new in Spark 2.0. And structured streaming makes it so that you can write sort of arbitrary Sequel expressions on streaming data, which is really awesome. Like, you can do aggregations without having to sit around and think about how to effectively do an aggregation over different microbatches. That's not a problem for you to worry about. That's a problem for the Spark developers to worry about. Which, unfortunately, is sometimes a problem for me to worry about, but you know, not too often. Boo helps out whenever it gets too stressful. >> First of all, a lot to learn. But there's been some great research done in places like Cornell and Penn and others about how the open source community collaborates and works together. And I'm wondering is the open source community that's building things like Spark, especially in a domain like Big Data, which the use cases themselves are so complex and so important. Are we starting to take some of the knowledge in the contributors, or developing, on how to collaborate and how to work together. And starting to find that way into the tools so that the whole thing starts to collaborate better? >> Yeah, I think, actually, if you look at Spark, you can see that there's a lot of sort of tools that are being built on top of Spark, which are also being built in similar models. I mean, the Apache Software Foundation is a really good tool for managing projects of a certain scale. You can see a lot of Spark-related projects that have also decided that become part of Apache Foundation is a good way to manage their governance and collaborate with different people. But then there's people that look at Spark and go like wow, there's a lot of overhead here. I don't think I'm going to have 500 people working on this project. I'm going to go and model my project after something a bit simpler, right? And I think that both of those are really valid ways of building open source tools on Spark. But it's really interesting seeing there's a Spark components page, essentially, a Spark packages list, for community to publish the work that they're doing on top of Spark. And it's really interesting to see all of the collaborations that are happening there. Especially even between vendors sometimes. You'll see people make tools, which help everyone's data access go faster. And it's open source. so you'll see it start to get contributed into other people's data access layers as well. >> So, pedagogy of how the open source community's work starting to find a way into the tools, so people who aren't in the community, but are focused on the outcomes are now able to not only gain the experience about how the big data works, but also how people on complex outcomes need to work. >> I think that's definitely happening. And you can see that a lot with, like, the collaboration layers that different people are building on top of Spark, like the different notebook solutions, are all very focused on ableing collaboration, right? Because if you're an analyst and you're writing some python code on your local machine, you're not going to, like, probably set up a get up recode to share that with everyone, right? But if you have a notebook and you can just send the link to your friends and be like hey, what's up, can you take a look at this? You can share your results more easily and you can also work together a lot more, more collaboratively. And then so data bricks is doing some great things. IBM as well. I'm sure there's other companies building great notebook solutions who I'm forgetting. But the notebooks, I think, are really empowering people to collaborate in ways that we haven't traditionally seen in the big data space before. >> So, collaboration, to stay on that theme. So, we had eight data scientists on a panel the other night and just talking about, collaboration came up, and the question is specifically from an application developer standpoint. As data becomes, you know, the new development kit, how much of a data scientist do you have to become or are you becoming as a developer? >> Right, so, my role is very different, right? Because I focus just on tools, mostly. So, my data science is mostly to make sure that what I'm doing is actually useful to other people. Because a lot of the people that consume my stuff are data scientists. So, for me, personally, like the answer is not a whole lot. But for a lot of my friends that are working in more traditional sort of data engineering roles where they're empowering specific use cases, they find themselves either working really closely with data scientists often to be like, okay, what are your requirements? What data do I need to be able to get to you so you can do your job? And, you know, sometimes if they find themselves blocking on the data scientists, they're like, how hard could it be? And it turns out, you know, statistics is actually pretty complicated. But sometimes, you know, they go ahead and pick up some of the tools on their own. And we get to see really cool things with really, really ugly graphs. 'Cause they do not know how to use graphing libraries. But, you know, it's really exciting. >> Machine learning is another big theme in this conference. Maybe you could share with us your perspectives on ML and what's happening there. >> So, I really thing machine learning is very powerful. And I think machine learning in Spark is also super powerful. And especially just like the traditional things is you down-sample your data. And you train a bunch of your models. And then, eventually, you're like okay, I think this is like the model that I want to like build for real. And then you go and you get your engineer to help you train it on your giant data set. But Spark and the notebooks that are built on top of it actually mean that it's entirely reasonable for data scientists to take the tools which are traditionally used by the data engineering roles, and just start directly applying them during their exploration phase. And so we're seeing a lot of really more interesting models come to life, right? Because if you're always working with down-sampled data, it's okay, right? Like you can do reasonable exploration on down-sampled data. But you can find some really cool sort of features that you wouldn't normally find once you're working with your full data set, right? 'Cause you're just not going to have that show up in your down-sampled data. And I think also streaming machine learning is a really interesting thing, right? Because we see there's a lot of IOT devices and stuff like that. And like the traditional machine learning thing is I'm going to build a model and then I'm going to deploy it. And then like a week later, I'll maybe consider building a new model. And then I'll deploy it. And then so very much it looks like the old software release processes as opposed to the more agile software release processes. And I think that streaming machine learning can look a lot more like, sort of the agile software development processes where it's like cool, I've got a bunch of labeled data from our contractors. I'm going to integrate that right away. And if I don't see any regression on my cross-validation set, we're just going to go ahead and deploy that today. And I think it's really exciting. I'm obviously a little biased, because some of my work right now is on enabling machine learning with structured streaming in Spark. So, I obviously think my work is useful. Otherwise I would be doing something else. But it's entirely possible. You know, everyone will be like Holden, your work is terrible. But I hope not. I hope people find it useful. >> Talking about sampling. In our first at Dupe World 2010, Albi Meta, he stopped by again today, of course, and he made the statement then. Sampling's dead. It's dead. Is sampling dead? >> Sampling didn't quite die. I think we're getting really close to killing sampling. Sampling will only be data once all of the data scientists in the organization have access to the same tools that the data engineers have been using, right? 'Cause otherwise you'll still be sampling. You'll still be implicitly doing your model selection on down-sampled data. And we'll still probably always find an excuse to sample data, because I'm lazy and sometimes I just want to develop on my laptop. But, you know, I think we're getting close to killing a lot more of sampling. >> Do you see an opportunity to start utilizing many of these tools to actually improve the process of building models, finding data sources, identifying individuals that need access to the data? Are we going to start turning big data on the problem of big data? >> No, that's really exciting. And so, okay, so this is something that I find really enjoyable. So, one of the things that traditionally, when everyone's doing their development on their laptop, right? You don't get to collect a lot of metrics about what they're doing, right? But once you start moving everyone into a sort of more integrated notebook environment, you can be like, okay, like, these are data sets that these different people are accessing. Like these are the things that I know about them. And you can actually train a recommendation algorithm on the data sets to recommend other data sets to people. And there are people that are starting to do this. And I think it's really powerful, right? Because it's like in small companies, maybe not super important, right? Because I'll just go an ask my coworker like hey, what data sets do I want to use? But if you're at a company like Google or IBM scale or even like a 500 person company, you're not going to know all of the data sets that are available for you to work with. And the machine will actually be able to make some really interesting recommendations there. >> All right, we have to leave it there. We're out of time. Holden, thanks very much. >> Thank you so much for having me and having Boo. >> Pleasure. All right, any time. Keep right there everybody. We'll be back with our next guest. This is the CUBE. We're live from New York City. We'll be right back.

(upbeat electronic music) >> Male Voiceover: Live from New York, it's the Cube, covering big data New York City 2016. Brought to you by headline sponsors Sisco, IBM, Nvidia, and our ecosystem sponsors. Now, here are your hosts. Dave Vellante and Peter Burress. >> We're back in the Big Apple. This is the Cube, the worldwide leader in live tech coverage, we're here at Big Data NYC, Big Data week is part of strata plus dupe world. Shaun Connolly is here as the vice president of strategy at Horton Works, long time friend and Cube alum, great to see you again. >> Thanks for having me, were back at the same venue last year, always a pleasure. >> Yeah, it's good, we're growing, I guess the event's growing, we haven't been over there yet, but some of our guys have, but what's it like over there? >> You know, it feels the same, some of the different use cases, I think last year was streaming, we're hearing more machine learning and things like that as far as use cases, so similar vibe. >> Yeah, so things are evolving, right? How's Hortonworks evolving? >> We're continuing to report our quarterly earnings as the only publicly traded company in this space, things from a business perspective are doing well. Our connected data platforms strategy which we unveiled at the beginning of this year, which is written data in motion and data at rest and enabling these new gen transformational applications continues to play out. The data in motion piece is sort of decoupled and unrelated to a hadou platform, it's really about acquiring and handling the FedEx for data delivery type notions, data logistics, secure transmission. That's based on the Apache Ni-Fi tech that was originally built sort of at the NSA over the past eight years, so. Really a nice robust piece of technology that we've pushed out to the edge in our latest release so you can really skin these down into a secure site to site transmission. A lot of sophisticated capabilities there, so we're seeing a lot of uptake in that sort of architectural vision, the products are maturing, both on prem and in the cloud, things are pretty exciting. >> Well this cloud thing seems pretty real. (Shaun laughing) You can get a lot of traction, right? Everybody kind of knew it was coming, but what are you seeing? >> Yeah so it was, I guess I started the journey back in 2009, when I was at Springsource in Paul Moretz was CEO of Vmware, and that was pre sort of cloud at that time. We were talking about this notion of platform as a service, and things like that. And that resonated really well with folks back then, but their main ask was how do you solve the data problem, how do actually get the data to the apps that need it. Fast forward to 2016, I think it's been a lot of open source innovation, you know a lot of commercial innovation, the rise of cloud for providing a fast path to value, booting up these used cases, it's a fascinating transition to watch. Many of our customers are, people use the word hybrid. What that means to me is they'll have data center workloads, or multi data center workloads, but they also have cloud workloads, sometimes even multi cloud workloads, and that inherent nature of the beast is why I use sort of the term of connected data architecture, is y%ou need an architecture that inherently is built to span that fact. And that's just increasing, that's just the world we live in today. >> But the fact is because there speed of light issues, there's data fidelity issues. >> Shaun: Yup. >> There's other types of things, how are you starting to see those practical and very physical realities start to impact the whole concept of design as it pertains to data, as it pertains to analytics, as it pertains to the infrastructure associated with the two? >> Yup, so at Hoop Summit that we had last June, there were really some really good sessions that were there. Folks like Comcast, Ford, Schlumberger talked about this connected data architecture reality, right. If you look at like, I like to use the connected car ecosystem as a good example, cause there were insurance providers and others that were sort of speaking on behalf of that, where you have the cars and other data that's inherently born up there, and there's a slug of use cases that are around edge analytics, streaming analytics, time series analytics, and we're seeing that, and I think the cloud lends itself really well for those types of use cases. But we also see manufacturing line data for the cars, where you want to get a 360 degree view of operational issues, and dovetail that with manufacturing line elements, and that's inherently what we've seen is, what your classic sort of on prem data wake, in quotes has been used for so you can get that 360 degree operational intelligence type of analytics to come out of that, right? So that type of use case, whether you apply it to oil and gas and having the sensors on the oil rigs, in the Schlumberger example, that pattern is repeating itself across different industries. British Gas, in Europe talks about how they're fundamentally changing the nature of the relationship with their customer because of the smart meters, and their connectivity in the homes and they can deliver a better value there. So that's inherently connected data realm, there's cloud use cases, and in the data center use cases. So I see these use cases, you know, they'll be use case specific in applications that are sprinkled across that fabric, if you will. And that's really what we're seeing. >> At our panel last year here in this venue, we would talk about a lot of things, one was the market, the sort of ebbs and flows you just mentioned, you guys are the only public player, Talon's joining that crew. >> Shaun: Yeah. Excellent. >> You've seen some. >> Shaun: We need more. >> We need more, we've seen some MNA, Plat 4 taken out, I don't know if that was, I don't know the specifics of that deal. Might have been an acu hire, might not, I don't know. And Data Mere did a raise, so you're seeing these rip currents, in all directions. What are you seeing in the marketplace, lot of funding early on, lot of players, lot of innovation, and now it's like, okay, the music at some point's going to stop, but. >> Yeah. >> What's your take? >> So in our last call, and I think we repeated it on our prior earnings call, you know, our focus and then we put out there in our earnings, in our Q3 earnings will sort of reiterate where we stand is, we basically said Q4 is when we look to go adjust to even or break even. >> Right. >> And then 2017 we'll go from there. We reiterated that guidance, we had a little over 62 million in billings for the quarter, so the business is pretty robust and growing, it's a. We're only five years into this, I mean we're just five years old, so it's a very fast pace of billings growth, right? That's almost a 250 million run rate, right? For exiting that quarter. You know, annual run rate. So we see a lot of the use cases really continuing to move on. I think what I and what our customers ask us is, they're on a digital transformation journey, and they want the industry to start talking about those types of business value drivers, right? So I think we should expect to see a transition from the piece parts animals in the zoo and what's the right open source piece of technology, and more why should you care, right? As a business, how is this transforming what you do? How does this open up new lines of business? We started seeing that at Hadoop Summit when I think about two dozen customers were sharing, very rich stories, right? So that's where things are. But I think running a company is, you have to run it with a certain sense of rigor and that was one of the reasons why we chose to go public, right? >> So, we by the way, we totally agree that customers want to stop talking about digital business in platitudes and start actually identifying specifically what is it about it that's new and different, and find ways of doing it. >> Shaun: Sure. >> Coming back to the issue, however, of how you go about making some of those transformations relevant. There is clearly a knowledge gap about what digital business is, what it isn't, certainly. But there's also a fair amount of skills that have yet to be developed, that are required for a lot of the use cases that companies are pursuing. Not just in terms of implementing the technology appropriately, but actually constructing and conceptualizing the use cases. >> Shaun: Sure. >> So that suggests that there's two paths forward. There's a path forward where we can do a better job of diffusing knowledge through people, and there's a path for where we can do a better job of building software that's easier to use. >> Shaun: Mm hmm. >> And there's both. How do you see this playing out over the course of the next few years? >> Yep, and I think in any new area as technology's emerging, like one of the things I use is Apache Software Foundation. Literally every other week there's a new data related Apache project that lands, so it's. It can be really confusing, but it's exhilarating from the fact of I participate in that, and I try and figure out what ones we can harness in a consumable platform, whether it's one prem or a cloud or what have you. What use cases can it light up? So I think you have both of those vectors, and it really depends on, I like to use the classic software adoption curve, you have a lot of the left side of the chasm folks, where a lot of this new stuff is going to be sharper edges, and they're always going to be trailblazers, right? But we are also seeing a lot of some of these advanced analytics. Some of these new solutions are automating the pipeline, so you can actually let the infrastructure and these engines do more of the thinking for you, so you get your model's output. Even to the point where you run multi model simulation in parallel, and out pops the best fit. That's where things will head, right? I think it's just a matter of the technology maturing, making sure we address things like security, metadata management, governance, and those illities that the enterprise expects, and then really forcing ourselves to simplify and automate as much as possible, right. And that was one of the reasons on that last one why in October 2011 we basically chose Teradata and Microsoft as key partners. Teradata because in 2011, clearly, right? >> Peter: Teradata. >> They're Teradata, right? Microsoft because it simplifies technologies and brings them to billions of users, right? And so we need to do both, you need to harden it, right? For the most rigorous large enterprises, but you need to simplify it for the meat of the market adopters, right? The early majority and late majority. You have to do both. >> Shaun, you're sitting across from a CEO, and you have to say these are the three things you need to do to enact this digital transformation. >> Shaun: Yup. >> What are the three things you're telling him? >> So, I think they need as a business to identify how do they want to leverage data as capital, and what pockets of value do they want to go chase, number one. Number two, how is their business being impacted by the fact that you have the rise of IOT and inherently increasing connected society and infrastructure. How is that impacting them? And number three is, how do they evolve what they're used to doing, right? You have to align it, exactly. >> Because that's really many respects of, I like to say there's a difference between invention and innovation. Invention is the engineering act, innovation's a social act, it's adopting those new practices >> Shaun: Exactly. >> That actually allow you to enact the invention and generate revenue. >> Exactly. Now in our space, I think we have a very compelling renovate value prop which is a cost savings where you can drive cost out, but the innovate use cases are the ones. Like if all you're going to do is renovate, then you will fail, you will stall, right? Because it's not a balance of cost savings. It's about how do you actually transform your business. And in the case of like the British Gas example, I used that as how they engaged that end consumer is fundamentally changing. So that's the question I put back in those conversations is how do you want to evolve your business and how do you leverage data as capital? Because the beauty of data as capital is you can actually generate multiple lines of interest off of a single data set, cause you can derive different insights off of that, so it's not like a dollar, right? And single compound, it's multiple compound annual interest rate on that. But they have to chase the right use cases. >> Although, we've also learned from great design that if you do the right thing better, you get rid of a lot waste and so coming back to your point, doing the right thing better often leads to cost savings. >> Yes. Exactly. One inherently can drive the other, but if you're just driving it then >> Peter: Just doing cost. >> You're not going to transform your buisiness. >> Peter: You're just going to continue to do the same or wrong things worse. >> Shaun: Exactly. >> Or wrong things cheaper. >> And that's difficult for enterprises. Because there's a certain way to do data management inherently inside in a highly structured manner, but I do think the rise of like IOT, I don't see as a market, I see it as infinite slices of prosciutto, right? (laughter) It's a very thinly sliced set of market opportunities, right? But it's forcing people to think about different use cases and how that might impact their business. >> We see those set of capabilities. >> Yup. >> Which leads to the prosciutto. >> Exactly. >> So you, and come up with a really nice sandwich. (laughter) >> It's my Italian. >> Let's keep going. >> I'm loving it. >> I'm getting a little hungry. >> You have always made a big deal out of your partnerships not being barney deals but being deep integration relationships. So you mentioned two here, Teradata and Microsoft. As the cloud becomes more prevalent, as things evolve and machine learning becomes the hot buzzword, et cetera. How have you evolved those relationships specifically in terms of the integration work that you've done? Have you kept up that engineering ethos, or? >> And that was the thing. With Microsoft, we clearly spent a lot of sweat equity on the Azure HDInsight service, but if you look at that ecosystem, they have Azure machine learning, right? They have a whole raft of services, right, that you can apply to the data when it's in the cloud, right? So how that piece integrates with the broader ecosystem of services is a lot of engineering work as well. I've always said, there's work to be done in our green box, but the other half of the work is how it plumbs into the rest. And so if you look at the AWS ecosystem, how do you optimize for S3 as a storage tier, and ephemeral workloads where HDFS is maybe a caching mechanism but it's not your primary storage, right? It brings up really interesting integration modes and how you actually bring your value out into really interesting use cases, right? So I think it's opened up a lot of areas where we can drive a lot more integration, drive the open source tech in a way that's relevant for those use cases. >> Alright, we got to go but, summit in Tokyo, is it next month? >> Yes, end of October. >> End of October. >> It's our first time, so primarily summits have been US and Europe. We had Melbourne end of August, and we have Tokyo end of October. I'll be, they're bringing the right hander out of retirement, so I'll be onstage in Tokyo. (laughing) I've usually been behind the scenes. >> Throwing the slurve? (laughter) >> Yeah, exactly. So I'm looking forward to it, it'll be exciting. >> Alright, good, and then 17, you're going to start again in the spring. >> Shaun: Yup. >> You're in Munich. >> Shaun: Yup. Munich. >> You were in Dublin last year, you're moving to Munich this year. >> Shaun: Exactly. >> Hopefully the Cube will be back, in Munich, alright? >> We love you guys, you guys do a good job. >> Let's make it happen, do good stuff in Europe, so thanks again for coming out. >> Shaun: Thanks for having me. >> Always a pleasure. Alright, keep it right there, we'll be back right after this short break. This is the Cube, we're live from New York City. ( upbeat electronic music)