>>From around the globe. It's the cube with digital coverage of IBM. Think 20, 21 brought to you by IBM, >>Welcome back to the cubes coverage of IBM, think 20, 21. We're gonna talk about the edge. Like what is the edge, how it's going to evolve. And we're gonna take a look at an autonomous vessel use case, which is quite interesting with me as Rob high. He was an IBM fellow VP and CTO. IBM edge computing. Rob. Welcome. Great to see you again. Thanks Dave. Appreciate that. Yeah. So let's start with the basic question here. You know, people's like, Oh, what is the edge? Like, it's one big thing and it's not, it's it's many things, but how should we think about the edge and why should enterprises, you know, feel like it's necessary to begin to lean in? >>Well, so let's just start with the use cases. Uh, you know, what edge means is the ability to put a camera on a manufacturing floor, you know, perhaps juxtaposed with a robot monitoring the work that the robot is doing using AI visual recognition to detect whether what that robot is doing is producing high quality parts or not. And to be able to do that in real time, to be able to use that analytic thin to, you know, quickly remediate any kind of quality issues, uh, helps lower costs, it helps increase your yield and it helps increase the overall efficiency of your production processes. Or if not that then putting it in something a little bit. It's perhaps a little bit more familiar to us, the idea of an autonomous vehicle, you know, being able to, you know, drive and, and, uh, do driver assistance to drivers safety kinds of features, you know, all of that requires compute and having that compute where people are actually performing these tasks based on the data that they're receiving at the moment that they receive it, they are able to process that real time, be able to give them the feedback that allows them to make better decisions, to be able to do that. >>Not only with lower latency, but actually with better protection of their data, uh, better protection of their personal information or private information. If you're thinking about, you know, the business in which they operate, you know, be able to do that, even when the network fails, be able to do that without necessarily having to transmit tons and tons of data back to the cloud, especially if you end up not actually using that anywhere. That's what as computing really means. >>Yeah. So it sounds like the edge isn't that maybe we shouldn't think of it as a place, but the most logical place to process the data, um, depending on latency and other factors, it's a, that's a good way to look at it. So >>It's just where we do our work. >>Yeah. Well, you do the work, right? That's that makes a lot of sense. Thank you for that. So, you know, we always were talking about the pandemic changing the way we think about things. And I wonder if you can comment on, on the, the edge context as come back from, you know, work from home or remote work, um, you know, think 20, 22, we hope it's going to be face-to-face could edge play a part in that has the pandemic, uh, made you think differently about the opportunities at edge? >>Yeah. And in fact, what we've seen is the pandemic is actually beginning to accelerate digital transformation. If you think about it, you know, any store that wanted to survive the same Deming could only do so by basically introducing a digital presence, you know, the ability to buy online. And even if you're picking up at the store, picking up the curbside, you know, you can't go into a restaurant without getting that QR code that gives you, you know, your digital menu, um, trying to get workers back into both the factories, as well as the warehouses and offices, and to do so safely, be able to ensure that they're wearing the face mask and socially distancing properly. All of these things I think have driven digital transformation. And if you think about the task of, you know, buying online and picking up the store while store is better, have a pretty good idea of where their inventory is. >>Um, they need to know exactly where that product is so they can quickly pick it and get it available to the client before they arrive at the store. Um, and so that's edge computing. We need edge computing to be able to automate the processes of inventory tracking down to individual items and where they're located throughout the store to be able to do the recognition for whether people are or are not being changing their social distancing or wearing their PPE, um, to be able to ensure that our processes are as automated as possible to limit the amount of human interaction that's required in order to perform these processes. All of that I think has accelerated both digital transformation, as well as particularly the use of edge computing, uh, in, in all of our businesses. >>I think about, you know, the forced March to digital in 2020. And if you weren't a digital business, you were out of business, but to your, my big takeaway from what you just said is that digital transformation is just starting and now people really have some time to think about that, that digital strategy. And as we think about doing things more safely, maybe with less human intervention, we love autonomous vehicles. Examples just cause because there's a technically they're challenging, but, but I wonder if you could tell us the story of the Mayflower autonomous ship it's it's upcoming journey, it's going to be cruelest across the Atlantic, unbelievable collecting data, you know, talk about how edge relates to that story. What can you tell us? >>Well, first of all, this is simply talk about the task of navigating a ship from one port on one side of the world to another port across the ocean, across the Atlantic. Um, you know, the ocean is a dangerous place. Uh, yes, it's wide open it's, you know, lots of water, but the reality is it's full of barriers. Of course, you've got land barriers, you've got other ships, you've got Marine life, you've got debris that gets stuck dropped in the ocean. And so the task of navigating is actually quite difficult. And again, to the same point that we've made earlier, you have to have local compute in order to really be able to make those decisions fast enough with enough acuity, with enough clarity, to be able to, um, to be able to safely safely navigate around those kinds of obstacles. So we have to put compute in the ship. >>So the Mayflower ship is as I sort of implied, uh, a, a ship that will be autonomous. There are no human beings involved in the, in operating the ship. It has to be able to on its own, both recognize these obstacles, recognize on the ship, recognize about recognized, um, you know, that cargo container that happened to fallen off, uh, some other ship and floating through the ocean, uh, recognize, you know, uh, rain life, uh, whales and other, other, uh, fish and birds that might be, uh, uh, on, in the way. Um, and, and, and to be able to, um, do all that, you know, entirely without any human intervention. So that compute power is really a prime example of an edge computer. It is compute in the, in the business of navigation, uh, making decisions about, um, the things that it sees and, and making decisions about how best to circumvent those issues. >>Um, now along the way, I should also say part of what the med flagship is going to do is not only exercise the task of navigation and prove that, um, these algorithms can efficiently and effectively, uh, bring that shift from one side of the world to be upside safe, but along the way, it's going to conduct science is going to, um, collect water samples for the, um, chemical makeup of, of the oceans at various points along the way, it's going to be sampling for microplastics or, uh, examining phytoplankton for its health and life. Uh, it's going to be the detecting wave motions and the wave energy that might be indicative of how the world is transforming in the presence of global climate change. Um, these science packages that are going to be formed are also being performed autonomously without human intervention. And that actually opens up a very exciting potential future, which is the idea of these autonomous ships navigating the oceans, collecting data that can then be brought back for the scientists to examine so that they, the scientists are not having to go out and spend weeks and months at a time in perilous conditions. >>These potentially the only conditions, um, collected that data, but rather they can remain safely at land. The ship will collect the data and they can analyze that data from their home labs. So this is actually a really exciting project, but one that I think would demonstrate not only the idea of edge computing, but also the advances in navigation and Marine science. >>Yeah, because I mean, the ship has to navigate itself. Not only is it bringing back data, but there's a great, great example. I met a lot of the work in machine intelligence today is done in the modeling side. This is, this, this is inference going on in near real time. Uh, which we think is where, where the, the, the action is. That's why we love the autonomous, because there's a lot of IBM tech involved in here as well. Is there not, I mean, you've got to have software and you've got your edge devices. You've got, you know, automation capabilities. I mean, it's not right. That this is like serious technical challenge. >>Yeah. Well, we were approached by the primary team on this project and it didn't take us long to realize the utility that some of our technology would have to advancing their project. And so you're right. I mean, we have things like operational decision manager, ODM, which typically is used in the financial services industry, but now it's being applied to the rules of navigation. We've called the Culver over cold rags. Um, we've got, uh, our AI services that do visual recognition because obviously we've got to be able to detect and identify, um, the things that, that the ship is seeing along the way and be able to distinguish what those things are. Uh, we have our IBM edge application manager, which is being used to manage deployment of these kinds of workloads, and frankly, all of the workloads that are hosted in the ship, getting that managed and deployed onto the ship. Uh, and, and of course, you know, all these things have to be integrated. And so that's just a small sampling of the kinds of technologies, but it's a good example of where I think the edge kind of represents the combination of what we have all been working with in this industry, which is how do we bring technologies together, the solver problem as an integrated solution, >>You mentioned financial services. So I wonder if we could, you know, think beyond shipping maybe, uh, what, what are you seeing in other industries? Are there any patterns that are developing where clients are saying, Hey, we need this sort of this capability. What can you tell us? >>So edge computing is it's probably greatest demand right now in manufacturing, uh, in industrial four dash zero, uh, kinds of, uh, environments where, you know, most of the industry, the industrial industry, the markets have grown up largely dependent upon operations, technology, OT, but one of the things that people need in these kinds of environments is the additional benefits that come from AI. And we've talked about, you know, using AI to do visual recognition on manufacturing processes, looking at quality inspection, for example, but you know, there's other aspects of production optimization of worker safety. We talked a little bit about that, um, around, uh, you know, predictive maintenance and asset management, uh, you know, these kinds of additional things that are necessary to really run your factory efficiently, or you're, you know, you're a drilling rig or your energy production systems. All these kinds of industrial processes can benefit from the advances that are occurring in analytics in, um, in, and then of course, having localized compute to do that with, to both do those kinds of decisions in real time, but also to offload the amount of transmission, the data that we have the transmitting back to the cloud. >>So industry four O or manufacturing is one big area retail. We talked a little bit about that, but you think about, you know, point of sale terminals, and the idea of being able to brute two offers at point of sale, to be able to do price checking to help you navigate the store is digital signage. Um, you know, all the user experiences, spillage and spoilage and loss prevention, these are all kinds of use cases that will benefit retail retailers, um, lot of demand. And of course, again, the need to be able to do that locally within the store, we talked to touch a little bit on automotive. The whole automotive industry right now is going through a really fundamental transformation where virtually every automobile now is being imbued with more and more compute capacity and localized processing for doing driver's safety and, and car maintenance and, and, and even short of, you know, full autonomy, which is of course is another topic in its own, right? Uh, lots of experiences that can be brought there as well. So lots of opportunity in distribution, manufacturing, retail banking, uh, uh, virtually every industry that we've looked at has some opportunity for, um, leveraging the benefit that does computing. >>It's hard to get cars right now because the chip short is. But, um, I wonder real quick, if you could talk about 5g, you hear a lot about 5g, there's a ton tons of hype there. Uh, how should we be thinking about 5g? How real is it? What's your take in terms of its impact on the edge? >>So a couple of thoughts here. One is 5g obviously is accelerating, and it has the effect of accelerating edge computing, because one of the benefits of 5g of course, is lower latency and higher bandwidth. And that kind of opens people's minds, the potential to leverage the network connectivity of equipment that otherwise, you know, is hard to connect. If you think about the factory floor for a moment in all the kinds of equipment you have on the factory floor, if you had to hard wire, all that equipment to get access to the compute power on that, that could be a very expensive proposition. You'd like to kind of wirelessly connect that equipment. And that's one of the things that 5g brings to the table, because some of the spectrum that five peak uses has less potential to interfere with that equipment then than you would otherwise. So I think that what we're going to see is 5g will sort of disproportionately benefit I'll call them industrial or commercial unit use cases as compared to 4g and LTE, which were very much centered on consumer use cases. 5g is accelerating as competing in a many ways. 5g actually depends on edge computing. It doesn't mean that we can't do educated beginning without 5g. We can, we can certainly do it for DLP than wireline. Uh, but I think 5g is going to have a very symbiotic effect on, on edge computing, >>Just like wifi was enabler on mobile, but this is a, you know, much, much, much larger potential. Rob. We got to go, thanks so much for coming on and sharing your insights. Love to have you back. Awesome. All right. Appreciate it. Thank you for watching everybody. This is Dave Volante for the cubes coverage of IBM. Think 2020, 21, 2021. We'll be right back.

>> Announcer: Live from San Francisco, it's theCUBE, covering DevNet Create 2017, brought to you by Cisco. >> Welcome back everyone, we're here live in San Francisco for theCUBE's special exclusive coverage of Cisco's inaugural event, DevNet Create, a foray into the developer opensource world as they extend their classic DevNet core developer program, three years old now, going into the opensource world, this is theCUBE, I'm John Furrier with my cohost, Peter Burris, our next guest is Matt Howard, EVP and CMO of Sonatype, knows something about opensource, Matt, great to have you on theCUBE, thanks for joining us. >> Thanks for having me. >> So first, talk about Sonatype, what do you guys do? Give a quick minute to describe the company, then I got some pointed questions for you. >> Well, we provide tools and intelligence to modern development organizations to basically reinvent how opensource components are flowing through the pipeline, through the value chain, through the development lifecycle. >> You guys are a service, SaaS service, are you guys a subscription? >> It's a subscription service, and we provide two products, there's a product which is a repository manager called Nexus where you store, organize, and distribute software binaries into the development lifecycle, and then there's a second server product called Nexus IQ, which provides intelligence on top of those binary, so think of it as like FDA food labeling database, so if you're looking at a bag of potato chips as a consumer, you can see that there's calories, sugar, salt, it's gluten-free. If you're looking at a software binary, you're able to see metadata that we provide, which allows you as a developer to make intelligent decisions with respect to, this component's good for my application 'cause it's properly licensed, or this component's good for my application because it doesn't have any-- >> So you're a verifying code, basically, in a way. >> Yeah, absolutely. Verifying and qualifying the opensource-- >> John: And the problem you solve for the customer as well. >> The customer basically gets to build applications at scale, at speed, with quality opensource components. >> So you take the worries off, like, with the licensing, does it work well, you're like Yelp for software? There're comments? >> Sort of, more like Amazon reviews for opensource binaries. >> Okay, great, cool, thanks for taking the time. So we was just talking in our intro, opensource, I'm old enough to know when we used to pirate software, and then opensource, woo, this is great, and then it became a tier two in the enterprise player, Red Hat brought it to tier one. It's booming. Communities are changing. You're in the middle of it, what's happening? Give us your take on how opensource is evolving, because it's the classic case of cliche, opensource, I'm standing on the shoulders of giants before me, and now the next generation is standing on the current generations of shoulders, a new generation's happening, what's going on? >> So, just think of supply and demand, simple supply. We live in a world right now where development organizations are facing an infinite supply of opensource, there's a thousand new opensource projects a day, 10,000 new versions and 14 releases per year. The supply is massive. And in a world where supply is incredible, consumption is equally incredible, last year alone, there were 52 billion download requests from Maven Central for Java binaries, 50 billion-plus requests for NPM packages in the JavaScript ecosystem, so we are basically dealing with a world where software is no longer a marginal cost to doing business, it is the business. Developers are king, developers are the lifeblood that's flowing through every great enterprise today, because innovation is ultimately the thing that will allow companies to compete and win on a global playing field! >> I mean, it's almost intoxicating for these guys who are just drinking from the trough of free software, because if you compound the new projects with the fact that Google and these guys are donating awesome libraries, Amazons, machine-learning stuff, it's not something to shake a stick at, it's great software! >> Yeah! >> TensorFlow, Spanner, I mean, all this stuff-- >> It's great software, and just think, in a world of infinite choice, which is the world we're living in, how do you make the best choice? >> So where's the growth coming from? Peter and I were speculating that, in talking to Abby Kearns yesterday from Cloud Foundry, and then with the Cloud Native Foundation, a lot of money's coming in so the business model for players and vendors are coming in, and suppliers now helping out and donating software, but we're speculating that there's a whole growth area that's different than we've seen before. Are we on that? Your comment to that, your thoughts on where this evolution's coming from, the next wave, is it horizontal? >> Our view is that the devops transformation from waterfall-native development to devops-native software development is happening and it's real, and it's arguably in the early days, but it's no stopping that train now. As organizations continue to reconcile demand from board members and shareholders and CEOs, how do you remain relevant, how do you be, put yourself into a position where you're innovating with software fast enough to remain competitive? And that's a tremendous pressure, and it's driving transformational change like devops, and so as that demand for speed continues to grow, we think it only increases the appetite for opensource, and it creates opportunities for organizations like ours to basically automate how that opensource innovation happens. >> We do a lot of crowd chats, to surface the landscape and the common theme that comes up is, oh, your organizational mindset has to change, and were commenting, Peter and I were talking yesterday about, if your org's not set up, you'll have, what's the law? >> Conway's law. >> Conway's law, where the output matches the organization, but the bigger question is, Ford CEO got fired, he's been in the job for less than four years, he didn't have time to transform, so the question is, how does opensource help people transform faster, do you have any observations around that? Because that's the number one question we get is, okay, I need to configure resources to do that, and then the other theme that we're hearing, I'd love to get your reaction on is, "Oh my God, I'm going to lose my job through automation." And certainly Cisco has networking guys who are looking down the barrel of potentially being irrelevant if they don't make the network programmable, so this is, we've lived through cycles, is it the mainframe guys who kind of lose their jobs, kind of thing going on? Or is it a transformative opportunity for the people as well? >> Yeah, it's a great question, there's a lot there, but I think the notion that they say software eats the world, a different way of viewing is automation eats the world, and if you look at, we refer to the 100-10-1 rule, today, in every large IT organization, you got 100 developers for every 10 IT operations professionals for every one security professional. It's impossible for the application security professionals to maintain governance over 100 software developers. If the old way of doing something like application security in this world where we're talking about infinite supply of opensource, needs to be automated with machine intelligence, it needs to be scalable early, everywhere, and throughout the entire development lifecycle, and unless it's not, you're going to basically get some of the benefit of opensource, but not all of the benefit of opensource. >> I want to push you a little bit in this, Matt, because, one might argue, and I'm going to be a little bit apocryphal here for a second, but one might argue that we also have an infinite supply of different types of bubblegum. And at the end of the day, one can say, "Well, do we need another bubblegum?" And we may or may not, and yet we do. So the reason why I'm bringing that up is I want to square the infinite supply, which I don't disagree with, with the idea that, certainly our clients, especially the big data side, are still concerned about the fact that they can't find tooling, or combinations of opensource tooling, that can help them with their use case. And so as you think about, one of the things that intrigued me about what your company does is the idea of to what degree can you start with a business problem, use that business problem to do some design work, and then based on that, start finding the tooling that will be most appropriate for solving the problem. >> Yeah, it's a great question, and I think it goes back to this idea of automation, let's just give a real world use case, this is one of many, but if the demand for speed and innovation is what shareholders, boards, and CEOs are looking for out of their IT organizations and their development teams, then the first thing you do, in the theory of constraints is you look for where is the friction, right? So theory of constraints basically points to something like the process inside of a large financial organization that involves a developer requesting approval for using an opensource component. How long does that take? How many people are involved in that process? How many hours, how many dollars? Does it have to be that hard? Or can you basically create policy, and define policy, and build, effectively, a firewall that then automatically governs the flow of opensource, healthy opensource components, into the development lifecycle? With no human intervention at pace, right? And that's the idea of what we're doing when we talk about scaling opensource innovation early, everywhere, and across the entire development lifecycle, it starts at the perimeter, the moment the development requests the opensource component for use, it has to be automated, you can't afford to take three months to approve it, he needs it now! >> So let me turn that around, and see if this is a service that you are providing, or actually could provide. Given that you probably visibility into a lot of the problems that the developer's trying to solve, and therefore, their ability to check opensource in and out from a variety of different sources, are you also gaining visibility in the types of stuff that people can't find, and making that information available to the world about, here's some of the places where the opensource world could step up and do perhaps a better job of delivering that software? And I'm specifically thinking of the big data universe, because there's so many, for example, I got a client, big financial institution, who is tearing his hair out right now trying to come up with some standard components for complex machine-learning pipelines. Real, real hard job, a lot of different tools, they work together at some level, but they're not solving the problem, 'cause they're more focused on solving each other project's problem. Am I making this? >> You are making a lot of sense, and you should introduce us to your friend, because we would love to have a conversation and talk exactly how it is that you can create prescriptive architectures with opensource components to remove friction back to the theory of constraints concept, I mean, this process of innovation has to flatten out, and we are very narrowly focused on one particular piece of that pipeline, and it is the making sure that the development organization is benefiting from all of the greatness that opensource has to offer, but none of the bad, and you have to do that with automation. >> So just really quick, John, for those of you who don't know, the theory of constraints, to a computer science person, looks like Amdahl's law. Speed up that which you do most frequently, for those of you who've ever done computer design. >> Herbie the Boy Scout. >> Exactly, so it's speed up the thing that is causing the most pain. >> Right, right, right. >> So the question I have for you this, okay, given what you guys do, which is a great service, cutting edge, it's in the devops wheelhouse, so, what is, in your opinion, the most important metric for your customer's success, vis a vis devops, okay, I'm in, I've been hearing about this cloud native thing and devops, we've got to change to Agile, we wrote a manifesto, we changed the organization, what is the important metric that you think they should look for for success? >> You know, there's a lot of metrics, there's no one answer, but I'll give you a really great one, since you mentioned Red Hat earlier. Red Hat is an amazing company that has probably done more for the evolution of opensource than anyone. They have a phenomenal track record of managing RHEL, the Red Hat Enterprise Linux stack, upstream and downstream, to the point where today, they publicly tell that the Red Hat Summit just recently in Boston, I think it's a day or two meantime to repair for a zero-day vulnerability. They understand the supply chain for RHEL extremely well, and from our perspective, we are trying to create the same type of hygiene for custom software development that RHEL has long practiced in support of Red Hat, Red Hat has long practiced in support of RHEL, and so meantime to repair, for example. If a zero-day vulnerability hits, do you have a software bill of materials? Are you wondering where that particular component is? Do you even have the component? How many applications in production are affected? I mean, this is a real-world scenario, just two weeks ago, with Struts 2, how many organizations are still working today to figure out the answer to that question? You'd be surprised, it takes organizations months-- >> Peter: But this is more than a library. >> This is more than a library. >> So explain why it's more than a library. >> Struts 2? >> No, what you're doing. >> What we're basically doing is imagining a software supply chain, so step back and imagine a world where you could build software applications the same way that Toyota builds cars. You have Deming's principles, which says you basically take and source the components or the parts from the fewer suppliers, and you source the absolute best parts, and you track and trace the location of those parts to every step of the supply chain all the way into production, so that Toyota recently had to conduct an orderly and effective recall for four million Takata airbags. Right? In software terms, the next time you're basically sitting on top of a zero day, you need the equivalent of that orderly effective recall so you can in a matter of minutes, not months, patch that vulnerability. >> Hence why you use Goldratt's theory of constraints, so in many respects, this is a digital supply chain tool? >> We believe it's software supply chain automation. >> What about digital? Can I also think about how digital objects can be included in that? Again, going back-- >> Containers? >> Going back to the big data notion? >> Yeah, absolutely, this is, supply chain theory is well understood in a physical goods world, certainly, if you look at how physical goods move through a supply chain, and you come to grips with what's happening in digital transformation today and the evolution of devops and the proliferation of opensource, continuous integration, continuous delivery, speed is king, it's all going in the direction of a supply chain. >> So, when you have so much bubblegum, as Peter said, after it loses its flavor, you get a new piece, right? So, same with software. Final question for you. You guys are doing well, I can imagine that operationally, as coming to operational as opensource, you're a key component there, and that seems like a good opportunity. How early are you on that operational progress? I mean, you just get started, you're making some money, which is good. >> To be frank-- >> You're the customer on the journey, in other words, people realize, "I got a operation on," so they're just doing it, not having a checks and balance. >> Our business is really interesting in the sense that product market fit for any young company can take quite a while, and we're fortunate enough to have a CEO who is remarkably patient and savvy and experienced, his name is Wayne Jackson, for anybody knows, here at the Cisco conference, he was previously the CEO of Sourcefire, so an interesting connection there, but patience is key, and we're being rewarded right now because all of the trends that you guys have already talked about here, and everything we've talked about at Cisco DevNet point to a simple fact, which is that software is key to how companies will compete and win in the future, and as long as that's true, they're going to be looking for ways to improve innovation. Right now, our business is early, we're still creating budget in some situations, but that's increasingly changing, and I would say that you should expect our business to continue to grow-- >> So people are operationalizing opensource, and they're getting serious about some of these things-- >> We're seeing budget now that we didn't see last year, for operationalizing the flow of opensource into a devops-- >> Final, final question, since I want to get your take on the show, Cisco's moves here into this world, obviously, a good move in our opinion, I'm sure you agree, risky for them, a good move, progress, what should they do next? Your thoughts and reaction to DevNet Create, 'cause man, they got DevNet, a growing, robust community of Cisco developers. DevNet Create, a new opportunity, what's your thoughts? >> I've learned a lot, I'm glad to be here, and just saw some things yesterday that make it very, very clear that DevNet Create and what Cisco's doing with it is a great move, I mean, my personal belief is that developers are king, and as you expose core services, network services to developers, an innovation happens, and value gets created, and so they've done so much at the network layer for so many years, and if they're now exposing that network sort of innovation to developers, it'll be exciting to see what kind of innovation happens. >> Matt, thanks for coming on theCUBE, really appreciate it, I'm glad we got you in, great to meet you last night, and congratulations on your startup that you're working with, and growth, and been around the industry a long time, you've seen a lot of waves, and appreciate the insight here on theCUBE, appreciate it. >> Appreciate you having me. >> Alright, we are live in San Francisco for exclusive coverage of Cisco's inaugural event DevNet Create, I'm John Furrier, Peter Burris, stay with us for more day two coverage after this short break. >> Hi, I'm April Mitchell, and I'm the Senior Director of Strategy and Planning for Cisco.