>> Announcer: Live, from Las Vegas, it's the Cube, covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Hey, welcome back everyone. We are here live in Las Vegas for day two of three days of exclusive coverage from the Cube here at HPE Discover 2017. Our two next guests is Bill Mannel, VP and General Manager of HPC and AI for HPE. Bill, great to see you. And Dr. Nick Nystrom, senior of research at Pittsburgh's Supercomputer Center. Welcome to The Cube, thanks for coming on, appreciate it. >> My pleasure >> Thanks for having us. >> As we wrap up day two, first of all before we get started, love the AI, love the high performance computing. We're seeing great applications for compute. Everyone now sees that a lot of compute actually is good. That's awesome. What is the Pittsburgh Supercomputer Center? Give a quick update and describe what that is. >> Sure. The quick update is we're operating a system called Bridges. Bridges is operating for the National Science Foundation. It democratizes HPC. It brings people who have never used high performance computing before to be able to use HPC seamlessly, almost as a cloud. It unifies HPC big data and artificial intelligence. >> So who are some of the users that are getting access that they didn't have before? Could you just kind of talk about some of the use cases of the organizations or people that you guys are opening this up to? >> Sure. I think one of the newest communities that's very significant is deep learning. So we have collaborations between the University of Pittsburgh life sciences and the medical center with Carnegie Mellon, the machine learning researchers. We're looking to apply AI machine learning to problems in breast and lung cancer. >> Yeah, we're seeing the data. Talk about some of the innovations that HPE's bringing with you guys in the partnership, because we're seeing, people are seeing the results of using big data and deep learning and breakthroughs that weren't possible before. So not only do you have the democratization cool element happening, you have a tsunami of awesome open source code coming in from big places. You see Google donating a bunch of machine learning libraries. Everyone's donating code. It's like open bar and open source, as I say, and the young kids that are new are the innovators as well, so not just us systems guys, but a lot of young developers are coming in. What's the innovation? Why is this happening? What's the ah-ha moment? Is it just cloud, is it a combination of things, talk about it. >> It's a combination of all the big data coming in, and then new techniques that allow us to analyze and get value from it and from that standpoint. So the traditional HPC world, typically we built equations which then generated data. Now we're actually kind of doing the reverse, which is we take the data and then build equations to understand the data. So it's a different paradigm. And so there's more and more energy understanding those two different techniques of kind of getting two of the same answers, but in a different way. >> So Bill, you and I talked in London last year. >> Yes. With Dr. Gho. And we talked a lot about SGI and what that acquisition meant to you guys. So I wonder if you could give us a quick update on the business? I mean it's doing very well, Meg talked about it on the conference call this last quarter. Really high point and growing. What's driving the growth, and give us an update on the business. >> Sure. And I think the thing that's driving the growth is all this data and the fact that customers want to get value from it. So we're seeing a lot of growth in industries like financial services, like in manufacturing, where folks are moving to digitization, which means that in the past they might have done a lot of their work through experimentation. Now they're moving it to a digital format, and they're simulating everything. So that's driven a lot more HPC over time. As far as the SGI, integration is concern. We've integrated about halfway, so we're at about the halfway point. And now we've got the engineering teams together and we're driving a road map and a new set of products that are coming out. Our Gen 10-based products are on target, and they're going to be releasing here over the next few months. >> So Nick, from your standpoint, when you look at, there's been an ebb and flow in the supercomputer landscape for decades. All the way back to the 70s and the 80s. So from a customer perspective, what do you see now? Obviously China's much more prominent in the game. There's sort of an arms race, if you will, in computing power. From a customer's perspective, what are you seeing, what are you looking for in a supplier? >> Well, so I agree with you, there is this arms race for exaflops. Where we are really focused right now is enabling data-intensive applications, looking at big data service, HPC is a service, really making things available to users to be able to draw on the large data sets you mentioned, to be able to put the capability class computing, which will go to exascale, together with AI, and data and Linux under one platform, under one integrated fabric. That's what we did with HPE for Bridges. And looking to build on that in the future, to be able to do the exascale applications that you're referring to, but also to couple on data, and to be able to use AI with classic simulation to make those simulations better. >> So it's always good to have a true practitioner on The Cube. But when you talk about AI and machine learning and deep learning, John and I sometimes joke, is it same wine, new bottle, or is there really some fundamental shift going on that just sort of happened to emerge in the last six to nine months? >> I think there is a fundamental shift. And the shift is due to what Bill mentioned. It's the availability of data. So we have that. We have more and more communities who are building on that. You mentioned the open source frameworks. So yes, they're building on the TensorFlows, on the Cafes, and we have people who have not been programmers. They're using these frameworks though, and using that to drive insights from data they did not have access to. >> These are flipped upside down, I mean this is your point, I mean, Bill pointed it out, it's like the models are upside down. This is the new world. I mean, it's crazy, I don't believe it. >> So if that's the case, and I believe it, it feels like we're entering this new wave of innovation which for decades we talked about how we march to the cadence of Moore's Law. That's been the innovation. You think back, you know, your five megabyte disk drive, then it went to 10, then 20, 30, now it's four terabytes. Okay, wow. Compared to what we're about to see, I mean it pales in comparison. So help us envision what the world is going to look like in 10 or 20 years. And I know it's hard to do that, but can you help us get our minds around the potential that this industry is going to tap? >> So I think, first of all, I think the potential of AI is very hard to predict. We see that. What we demonstrated in Pittsburgh with the victory of Libratus, the poker-playing bot, over the world's best humans, is the ability of an AI to beat humans in a situation where they have incomplete information, where you have an antagonist, an adversary who is bluffing, who is reacting to you, and who you have to deal with. And I think that's a real breakthrough. We're going to see that move into other aspects of life. It will be buried in apps. It will be transparent to a lot of us, but those sorts of AI's are going to influence a lot. That's going to take a lot of IT on the back end for the infrastructure, because these will continue to be compute-hungry. >> So I always use the example of Kasperov and he got beaten by the machine, and then he started a competition to team up with a supercomputer and beat the machine. Yeah, humans and machines beat machines. Do you expect that's going to continue? Maybe both your opinions. I mean, we're just sort of spitballing here. But will that augmentation continue for an indefinite period of time, or are we going to see the day that it doesn't happen? >> I think over time you'll continue to see progress, and you'll continue to see more and more regular type of symmetric type workloads being done by machines, and that allows us to do the really complicated things that the human brain is able to better process than perhaps a machine brain, if you will. So I think it's exciting from the standpoint of being able to take some of those other roles and so forth, and be able to get those done in perhaps a more efficient manner than we're able to do. >> Bill, talk about, I want to get your reaction to the concept of data. As data evolves, you brought up the model, I like the way you're going with that, because things are being flipped around. In the old days, I want to monetize my data. I have data sets, people are looking at their data. I'm going to make money from my data. So people would talk about how we monetizing the data. >> Dave: Old days, like two years ago. >> Well and people actually try to solve and monetize their data, and this could be use case for one piece of it. Other people are saying no, I'm going to open, make people own their own data, make it shareable, make it more of an enabling opportunity, or creating opportunities to monetize differently. In a different shift. That really comes down to the insights question. What's your, what trends do you guys see emerging where data is much more of a fabric, it's less of a discreet, monetizable asset, but more of an enabling asset. What's your vision on the role of data? As developers start weaving in some of these insights. You mentioned the AI, I think that's right on. What's your reaction to the role of data, the value of the data? >> Well, I think one thing that we're seeing in some of our, especially our big industrial customers is the fact that they really want to be able to share that data together and collect it in one place, and then have that regularly updated. So if you look at a big aircraft manufacturer, for example, they actually are putting sensors all over their aircraft, and in realtime, bringing data down and putting it into a place where now as they're doing new designs, they can access that data, and use that data as a way of making design trade-offs and design decision. So a lot of customers that I talk to in the industrial area are really trying to capitalize on all the data possible to allow them to bring new insights in, to predict things like future failures, to figure out how they need to maintain whatever they have in the field and those sorts of things at all. So it's just kind of keeping it within the enterprise itself. I mean, that's a challenge, a really big challenge, just to get data collected in one place and be able to efficiently use it just within an enterprise. We're not even talking about sort of pan-enterprise, but just within the enterprise. That is a significant change that we're seeing. Actually an effort to do that and see the value in that. >> And the high performance computing really highlights some of these nuggets that are coming out. If you just throw compute at something, if you set it up and wrangle it, you're going to get these insights. I mean, new opportunities. >> Bill: Yeah, absolutely. >> What's your vision, Nick? How do you see the data, how do you talk to your peers and people who are generally curious on how to approach it? How to architect data modeling and how to think about it? >> I think one of the clearest examples on managing that sort of data comes from the life sciences. So we're working with researchers at University of Pittsburgh Medical Center, and the Institute for Precision Medicine at Pitt Cancer Center. And there it's bringing together the large data as Bill alluded to. But there it's very disparate data. It is genomic data. It is individual tumor data from individual patients across their lifetime. It is imaging data. It's the electronic health records. And trying to be able to do this sort of AI on that to be able to deliver true precision medicine, to be able to say that for a given tumor type, we can look into that and give you the right therapy, or even more interestingly, how can we prevent some of these issues proactively? >> Dr. Nystrom, it's expensive doing what you do. Is there a commercial opportunity at the end of the rainbow here for you or is that taboo, I mean, is that a good thing? >> No, thank you, it's both. So as a national supercomputing center, our resources are absolutely free for open research. That's a good use of our taxpayer dollars. They've funded these, we've worked with HP, we've designed the system that's great for everybody. We also can make this available to industry at an extremely low rate because it is a federal resource. We do not make a profit on that. But looking forward, we are working with local industry to let them test things, to try out ideas, especially in AI. A lot of people want to do AI, they don't know what to do. And so we can help them. We can help them architect solutions, put things on hardware, and when they determine what works, then they can scale that up, either locally on prem, or with us. >> This is a great digital resource. You talk about federally funded. I mean, you can look at Yosemite, it's a state park, you know, Yellowstone, these are natural resources, but now when you start thinking about the goodness that's being funded. You want to talk about democratization, medicine is just the tip of the iceberg. This is an interesting model as we move forward. We see what's going on in government, and see how things are instrumented, some things not, delivery of drugs and medical care, all these things are coalescing. How do you see this digital age extending? Because if this continues, we should be doing more of these, right? >> We should be. We need to be. >> It makes sense. So is there, I mean I just not up to speed on what's going on with federally funded-- >> Yeah, I think one thing that Pittsburgh has done with the Bridges machine, is really try to bring in data and compute and all the different types of disciplines in there, and provide a place where a lot of people can learn, they can build applications and things like that. That's really unusual in HPC. A lot of times HPC is around big iron. People want to have the biggest iron basically on the top 500 list. This is where the focus hasn't been on that. This is where the focus has been on really creating value through the data, and getting people to utilize it, and then build more applications. >> You know, I'll make an observation. When we first started doing The Cube, we observed that, we talked about big data, and we said that the practitioners of big data, are where the guys are going to make all the money. And so far that's proven true. You look at the public big data companies, none of them are making any money. And maybe this was sort of true with ERP, but not like it is with big data. It feels like AI is going to be similar, that the consumers of AI, those people that can find insights from that data are really where the big money is going to be made here. I don't know, it just feels like-- >> You mean a long tail of value creation? >> Yeah, in other words, you used to see in the computing industry, it was Microsoft and Intel became, you know, trillion dollar value companies, and maybe there's a couple of others. But it really seems to be the folks that are absorbing those technologies, applying them, solving problems, whether it's health care, or logistics, transportation, etc., looks to where the huge economic opportunities may be. I don't know if you guys have thought about that. >> Well I think that's happened a little bit in big data. So if you look at what the financial services market has done, they've probably benefited far more than the companies that make the solutions, because now they understand what their consumers want, they can better predict their life insurance, how they should-- >> Dave: You could make that argument for Facebook, for sure. >> Absolutely, from that perspective. So I expect it to get to your point around AI as well, so the folks that really use it, use it well, will probably be the ones that benefit it. >> Because the tooling is very important. You've got to make the application. That's the end state in all this That's the rubber meets the road. >> Bill: Exactly. >> Nick: Absolutely. >> All right, so final question. What're you guys showing here at Discover? What's the big HPC? What's the story for you guys? >> So we're actually showing our Gen 10 product. So this is with the latest microprocessors in all of our Apollo lines. So these are specifically optimized platforms for HPC and now also artificial intelligence. We have a platform called the Apollo 6500, which is used by a lot of companies to do AI work, so it's a very dense GPU platform, and does a lot of processing and things in terms of video, audio, these types of things that are used a lot in some of the workflows around AI. >> Nick, anything spectacular for you here that you're interested in? >> So we did show here. We had video in Meg's opening session. And that was showing the poker result, and I think that was really significant, because it was actually a great amount of computing. It was 19 million core hours. So was an HPC AI application, and I think that was a really interesting success. >> The unperfect information really, we picked up this earlier in our last segment with your colleagues. It really amplifies the unstructured data world, right? People trying to solve the streaming problem. With all this velocity, you can't get everything, so you need to use machines, too. Otherwise you have a haystack of needles. Instead of trying to find the needles in the haystack, as they was saying. Okay, final question, just curious on this natural, not natural, federal resource. Natural resource, feels like it. Is there like a line to get in? Like I go to the park, like this camp waiting list, I got to get in there early. How do you guys handle the flow for access to the supercomputer center? Is it, my uncle works there, I know a friend of a friend? Is it a reservation system? I mean, who gets access to this awesomeness? >> So there's a peer reviewed system, it's fair. People apply for large allocations four times a year. This goes to a national committee. They met this past Sunday and Monday for the most recent. They evaluate the proposals based on merit, and they make awards accordingly. We make 90% of the system available through that means. We have 10% discretionary that we can make available to the corporate sector and to others who are doing proprietary research in data-intensive computing. >> Is there a duration, when you go through the application process, minimums and kind of like commitments that they get involved, for the folks who might be interested in hitting you up? >> For academic research, the normal award is one year. These are renewable, people can extend these and they do. What we see now of course is for large data resources. People keep those going. The AI knowledge base is 2.6 petabytes. That's a lot. For industrial engagements, those could be any length. >> John: Any startup action coming in, or more bigger, more-- >> Absolutely. A coworker of mine has been very active in life sciences startups in Pittsburgh, and engaging many of these. We have meetings every week with them now, it seems. And with other sectors, because that is such a great opportunity. >> Well congratulations. It's fantastic work, and we're happy to promote it and get the word out. Good to see HP involved as well. Thanks for sharing and congratulations. >> Absolutely. >> Good to see your work, guys. Okay, great way to end the day here. Democratizing supercomputing, bringing high performance computing. That's what the cloud's all about. That's what great software's out there with AI. I'm John Furrier, Dave Vellante bringing you all the data here from HPE Discover 2017. Stay tuned for more live action after this short break.

>> Announcer: Live from San Francisco, it's theCUBE covering DevNet Create 2017. Brought to you by Cisco. >> Okay, welcome back, everyone. Live in San Francisco. This is theCUBE's exclusive coverage of Cisco's new inaugural DevNet Create event targeting the DevOps open source community as they put their toe in the water, their foray into a community approach to build on top of their success of their classic developer program, DevNet, which is only three years old. Shouldn't call it classics. It's actually emerging still and growing. Arnesc is our pitch, Joshipura GM, Network and Orchestration at the Linux Foundation. I'm also joined with my cohost Peter Burris. Welcome to theCUBE. >> Thank you. >> Good to see you again, welcome back. Cube alumni. Obviously open networking. You guys are involved, you're having a great show, we cover it every year. Open Networking Summit, among other things. Huge demand for the technologies. An appetite for content in your area. Here at Cisco DevNet Create, you're seeing the emergence of Cisco taking their roots in networking and plumbing and operations, which, by the way, you know from the networking world. Sacred cows all over the place. Bringing it to the wild west, agile developer who wants infrastructure at Cisco is bringing that application meets infrastructure saying, we're going to bring programmable networking. That's music to the ears to the developers so we are getting infrastructure as code. That's your wheelhouse. What's going on in the Linux Foundation to continue this momentum? How do you guys look at this trend, give us the update on how the Linux Foundation is participating, supporting, getting involved with this programmable networking infrastructure as code trend. >> Sure. So first of all, let me baseline everybody. Linux Foundation is here to create the largest shared technology investment by building sustainable ecosystems. That's the mission in life. Within the Linux Foundation obviously the most successful open source project is Linux. But we're way beyond Linux. We host a whole set of open source projects starting from cloud native, CNCF, cloud foundry to blockchain projects like hyperledger, automotive grade Linux and a whole variety of Let's Encrypt, you name it. That we facilitate this shared technology investment. The area I own, which is networking, has several projects up and down the stack. All the way from data plane acceleration to orchestration, analytics and it's intended for carriers, enterprise, and cloud service providers including one of the most recent, highly successful and much in demand project called ONAP which is a full network automation stack. Open network automation platform. Which again, is an open source way to connect apps to infrastructure. This is the movement that you just mentioned and I'm really excited that the community's finally realizing the implications of the three letter acronym that started this whole thing called SDN. (laughing) >> SDN, SD when, a lot of stuff going on. Software defined, data center, obviously Cisco has a huge dominant preposition in the enterprise, data center in particular, but also they have a huge service provider business MSL. All that, they've been connecting networks on internet scale since the '90s. Really doing a great job. Now they got to really think about the future. What's your view there because I think Linux Foundation, you guys have been great stewards for sustainable ecosystems, but now Cisco has to put their toe into the new ecosystem. What's the meaning of that? What's the view, outlook? What's your take on where they're at? It looks good off the tee, middle of the fairway as we were saying earlier. Messaging's good, 90% of the content's community, agenda's relevant, looks good. >> I think our perspective is there's a major disruption happening. But it's not a technology disruption, it's an end user disruption. What I mean by that is the end users, whether it be carriers, whether it be enterprises whether it be cloud service providers, they are demanding that open source be part of the agenda. The reason for that is very simple. It's providing more agility, providing the access to the source code to allow for much faster feature development. They want to contribute, they want to develop the ecosystem to meet their requirements and everybody is unique as we all know. What is happening is, in this new environment, vendors, service providers, carriers, everybody is re-inventing themselves. They're re-inventing themselves with a new business model and the business model is essentially, how do I take a leadership role in developing this shared technology investment? It's not about a box. It's not about the fastest and the smallest and the largest switch routers, etc. It's about a software plan. >> It used to be about free software. Now, nothing's free because people are putting their company's name on the line. Their business models now are integrated to open source and they have people involved in other parts so technically it's free software but it's really, technically not free. But this is the new business model, this is what people are doing. >> I think you can-- >> It's tier one resource. >> If you look at the world's largest carriers today, whether it's in China, whether it's in US or in Europe, they have deployments that are built on open source. Open source networking specifically is becoming mainstream in terms of deployment. >> What's the hottest mainstream product right now? Is it SDN? What's the hottest in the-- >> SDN is a technology. SDN, NFV, network function virtualization. Those are technologies that enable the deployment of open source projects. We got projects like Open Daylight, ODL, OPNFV, ONAP, these are just names. Again as networking-- >> What's the hottest here, NFV or-- >> Right now ONAP is the hottest. As networking guys we always make these three or four letter acronyms so sorry to bug you. >> That's okay I don't mind. >> But that's how it is. >> So one of the observations at least we made at Wikibon and we made it here a couple times, is that open source has proven to be magnificently successful when the target is well defined. Other words, conventions of an operating system, there's no disagreement about what an operating system does. Hence open source could create a Linux that has just been wildly successful. Open source has not been as good at redefining the new use cases or where the technology might go. Therefore, a lot of times open source developers end up looking at each other and making each other's tools work. Which is, for example, in the big data universe, restricted the adoption of Aduke and the ability of Aduke for example. So getting value you out of it, but it's not as successful as it might be. That raises a question. I'm wondering what role you play in all this. Is there a need for a degree of open source leadership that can set the big picture, the longterm trends without undermining the innovative and inventive freedom of how developers have demonstrated they want to work together? What do you think? >> I think that's an excellent question. What happens is just by throwing software on say, Github, doesn't make you an open source project. I mean yeah, it does make you open source but that doesn't make you a successful open source project. You need a community behind it. You need a community of developers and a sustained ecosystem. One of the things we are championing, and I'm personally driving that agenda, which is thought leadership on how do these pieces fit together. As we are moving from components that were disagregated in networking to production ready software components, to production ready solutions, these all need to fit together and developed in its entirety. When you look at it holistically, from a solutions perspective, the most important thing that matters are use cases. So what we have done-- >> Totally agree. >> What we have done is for every project, strategically, when the requirements are laid down, I think of that as a requirements document. Or when the architecture is laid down. The end user use cases are explicitly defined for the community. The architecture is laid out. In that framework, the Linux Foundation facilitates the developments, the infrastructure the devOps, the agile model to come and co-create this technology in this area. >> So that's how you're doing the ideation. Are you then taking that and stepping up and also doing some of the design work? And it sounds like you are. >> We facilitate the community to do the design work, we give them architectural part leadership, we give them inter-project cross-leadership. For example, we have, in my group, in networking we have about 11 plus projects. There are multiple data plane acceleration projects. When you're putting a solution, you want portion of data plane acceleration to ride on a control plane, to ride on orchestration, to be tested end to end. Projects like OPNFV for example, they test all the pieces. They test things like FDIO, which is an acceleration project, they test open stack. Which again, it's not Linux Foundation but we do bring all the pieces together. Effectively the end user has it relatively easy to adopt and start installing. >> Congratulations, I saw that the Linux Foundation recently hired Sheryl Chamberlain as the Chief of Staff. Cube alumni been on many times, shout out for Cheryl. So you guys are growing. How are you guys handling the growth? I want to get your thoughts and you don't have to speak for the whole foundation but in general, for the folks not necessarily familiar with the inner workings of the Linux Foundation, like open source, you guys are always evolving and growing. How are you serving your stakeholders, your members and taking care and maintaining the sustainable ecosystems? >> The difference between a typical, throw the code up on GitHub versus actively managed, sustainable ecosystem is where Linux Foundation comes in. What we provide to projects in different capacity, is everything from IT as a service, marketing as a service, program management, thought leadership, executive directors, PR, media, and most importantly, events, global events to get the word out. All of that service, if you may, is what facilitates the community. Once the community is all coming together, things happen. I'll just give you an example, we just completed a developer summit on one of the projects called ONAP. Ran out of capacity, clearly. 200 people from world-wide, top-notch architects got in a room and they discussed how to merge almost 15 million lines of code. And they figured it out in four days. >> Over coffee. >> Not over coffee, it's like four days. >> I'm kidding (laughing). >> But they figured it out. I think that level of facilitation that we can provide, because you can't have it on a blank piece of paper. You need some framework, some governance, some model and some processes on how to do it. That's what Linux Foundation excels at. >> I want to move into the third area I want to discuss with you, us. You mentioned the three major customer and end users. Carriers, enterprises, cloud service providers. How do you guys relate and serve those customers when there's other stuff going on in the industry? We see Open Compute, Facebook's doing a lot of stuff, Google's throwing in a ton of open source. We have yet to see Amazon make their move with donating really good networking stuff. Certainly we've seen some machine learning out there, but, we're expecting to see an arm's race of presents coming in. It's like open bar at the hotel. More goodness is coming in from the big guys sponsoring great code. >> My mission is this year, at least, one of the things I've laid out at ONS this year was to harmonize the ecosystem. And harmonization doesn't mean merge it all so now we're one solution. Harmonization means understand where each other solutions interwork, inter-operate. If they overlap, we end up merging the projects, like what we did for ECOMP and OpenAL. That's one of the missions. Now in that process, we're looking, not just within the Linux Foundation and in my role, but also outside. That includes not just the software stacks, but also the hardware infrastructure layers. That would be OCP, that could be TIP, etc. And several others that are coming up. As well as harmonization with standards bodies. We believe that standards and open source coexist and there is a complimentary relationship there. We've been actively working with several of the standards. MEF, Team Forum, etc., etc. Trying to get a view. We just published a white paper on the Linux Foundation website on harmonizing standards on open source. There is a whole movement of ecosystem because at the end of the day, a carrier wants to solve a problem. They don't care how we solve it. I mean they do but not in a fragmented sense. And that problem is different from what an enterprise wants to solve and it's different from what a cloud. Now to your earlier question, the great news is cloud carriers and enterprises, they're looking and smelling the same as cloud native apps, cloud container networking and open source networking, they're all start combining, coming together. >> So I want to share with you a comment we had the other day. There's a story of the four wolves that were put into Yellowstone Park and changed the ecosystem cause Yellowstone had a river problem. So they injected four wolves into the ecosystem. Turns out, the deer went away, things started growing, and the whole ecosystem became so much more sustainable. Not that I'm trying to get at who's the wolves, but balancing and coexistence is the point here. You can live with wolves and not get eaten, unless you're their target. But there's a balancing act on ecosystems. And to have a good, sustainable ecosystem you need to have freshness, certainly standards and new blood, new ideas. What is your vision on coexistence because this is one of those things that we're seeing right now emerging, less about my project's better than your project. You're seeing a lot more collaboration going across communities. >> Correct. >> More than ever. >> A hundred percent agree. I think the fundamental problem has always been only the technical geeks understand the differences between the projects. And then the layer of abstraction in people, whether it's management or media, they start looking and feeling as if they are competing. I'll give you an example. In the data plane acceleration kit, we have projects like FDIO, DPDK, Iovisor, OVS, there's lots of projects there. And people like, oh my god, there's so many. Well, guess what? One of them is a kernel driven thing, other one is a set of libraries, third one builds on the libraries. So that level of understanding is missing. >> John: Interplay between all the projects. >> It's interplay. >> Peter Burris: And dependency. >> And dependencies. So that's one of the things that we want to highlight here, very significantly this year in terms of just sheer education. Because part of the coexistence is understanding each other. If we understand each other on what role each of the projects play, it's easy. Whether it's Linux Foundation or outside. So that's the first step. The second step is if they're complimentary, I want to take the next step and test them out for inter-operability. Because now you have put two pieces together. Remember, networking was a fully black box five years ago. >> Literally. >> We took it, blew it up, fragmented it, dis-segregated it, and now we got to pull... And we got tremendous innovation out of each of these layers. We were very successful on the whole disaggregation and SDN disruption. Not it's time to put it into a production ready solution. As we put those things in, we'll see that harmonization is going to play a big role. >> Arpit great to have you on here, sharing the insight. Always great to get the inner workings plus a great perspective on the industry trends and congratulations on your success and we'll continue to follow you and all your work in the networking area, all the projects Stu Miniman and team. We're going to continue to see you at the Open Networking Summit, among all the great shows. >> Thank you very much. >> Alright. >> Thank you. >> Thanks for coming on, live coverage here in San Francisco, as part of our exclusive two day coverage of the inaugural Cisco DevNet Create event. I'm John here with Peter Burris, we'll be back with more after this short break, stay with us. >> Hi I'm April Mitchell and I'm the Senior Director

>> Announcer: Live from San Francisco, it's theCUBE, covering DevNet Create 2017, brought to you by Cisco. >> Okay, welcome back, everyone. We're here live in San Francisco for theCUBE's exclusive coverage of Cisco's new inaugural event called DevNet Create, an extension, an augmentation, a community-focused event of their DevNet community, which is a Cisco developer community, now out in the wild. Our next guest is Steven Pousty, lead developer and evangelist at Red Hat, I'm John Furrier, and my co-host Peter Burris. Steven, welcome to theCUBE. >> Thank you, thank you very much. It's exciting to be here. >> Great to have you on. We were just talking before on camera, getting all animated like, "Hey, turn the cameras on. "We got to get this conversation." We're talking about open source and really looking at some of the trends, but more importantly, the impact. >> Steven: Right. >> Also, we've had you guys on many times on theCUBE. We covered Red Hat Summit, Jim Whitehurst. So, abstractions layers in software, open source ecosystems, you have a background in nature. >> Steven: Yeah. I- >> And ecosystems, literally. >> Steven: Yeah. Yeah, yeah. Yeah, actually I have my PhD in ecology. I'm actually a conservation biologist by training, but IT and computer programming pays the bills a lot better than-- >> Hey, anthropologists and ecologists do very well in the tech world, believe it or not. >> Steven: Yeah, I love big data. >> Peter: And philosophers. >> Yeah, and philosophers. Yeah, with all that logic and the ontologies and all that. >> Ontologies and symbiotics. >> Steven: Yep, yep. >> John: Okay, so I got to ask you, obviously Red Hat has been really the poster child for open source companies going public. We've heard since over the past generation, "The Red Hat of blank, The Red Hat of," and that got played. Certainly we downplayed that. People were trying to call Cloudera the Red Hat of Hadoop (mumbles) realizing that that's never going to happen. You were a once in a generational company, but Red Hat was a tier two company back in those days. Now, open source is certainly tier one software across the board, and I think this event at Cisco kind of amplifies that. Look at it, open source has gone a whole nother generation. A lot of young kids coming in. It's tier one software. The business model is open source. Four new companies just went public recently. So, done deal. >> Right, I mean, I think if you look in the technology ecosystem as a whole, if you don't start with open source you either have some incredibly magic sauce that no one else has or you're done. You couldn't even look at the movies... The arch enemy when I was growing up in software was Microsoft of open source, right? If you look at them now with Satya, they've made great strides to be part of the open source ecosystem at a real level, not like just lip service like they used to do sometimes. Like when I interact with some of our Microsoft partners, you can tell that there's a different change and they really believe in that open source-- >> Microsoft used to be known as lip service and vaporware and they used to kind of freeze the market with their monopoly power as some would say, but more recently they've... Back in the old days, Linux was a cancer. Steve Ballmer said, "Linux is the cancer to the industry." >> Steven: And so-- >> John: Now they're doing Linux with .NET. >> And so at the Red Hat Summit just recently I did the Microsoft keynote, I was the Red Hat person on the Microsoft keynote, and we demonstrated .NET Core running in OpenShift on Linux machines, we demonstrated SQL Server running in containers on OpenShift, and then for the end we showed some of the community work, because both of us are involved in Kubernetes. We actually showed a Windows container spinning up IIS being orchestrated from a Linux OpenShift. So, it was actually the Linux server, the Linux OpenShift server, was talking to Windows containers and spinning up Windows containers on the fly. So, I never thought that would've happened. So, it's definitely a sea change. >> And boy was that partly the sea change, we can encapsulate it, is that we used to think in terms of winners and losers in the tech industry, and now it's big winners and less big winners, but the question is how is, I think the realization Microsoft had, is that open source does not demarcate winners from losers. It demarcates, or rather suggests, a new way of thinking about how software gets developed, how software gets integrated and packaged, and ultimately how software gets diffused. So, talk a little bit about this notion of the new world of winners and winners and how this thing moves together, almost in an ecosystem type of way, so that the capabilities overall improve over time, because that's really where we're going is digital business being able to do more for customers. >> Right, and I think that's one of the things that you're seeing coming out from the open source world now is it's becoming less and less about I have this technology versus this is the technology, this open source technology, that we use to help solve your business problems. I gave a talk about this a couple times. There's a concept in ecology called, now I'm blocking on the word, but you probably came across it in school, probably even elementary school. It's the idea that you have bare earth, and then a few plants show up and they start breaking it up, and those plants create a condition where new trees come in, and then it just keeps going and going and going, and then you finally have a rainforest at the end, right? >> Peter: Diversity? >> No, it's-- >> Anyway, we don't want to put you out. >> Yeah, I'm stuck on the word and I can't remember-- >> Here's an ecology question. I saw a Facebook thing where in Yellowstone National Park they introduced four wolves to the ecosystem, and all of a sudden the rivers are no longer wide, they're tighter, there's pools. So four wolves create dynamics. So there's a coexistence, but there's still wolves. >> Right, and so the-- >> John: Who's the wolves in the industry? >> See, that's the thing, it's not that. Just because there are wolves in the industry doesn't mean that they control the entire ecosystem. So I think what I say at the end of this talk is there is no right or wrong about where you are in the ecosystem or in your evolution as an ecosystem, right? There is what is right for your business problem. So, we have this in our, especially in the United States, we have this idea of you're either the winner in this space, you're the cloud solution and you're the winner, or you're not, you're nothing. It's like the Talladega Nights, "If you're not first, you're last!" >> He runs around in his underwear. That's your outcome if you have that strategy. >> Great strategy. >> It was such a good movie. But so the point that I was trying to make in this talk is there's lots of different... So like with bird species, when they need to share a tree, there can be six different species all in the same tree, and what they do is what's called niche differentiation. That means, "Oh, I'm going to specialize "in the tops of the trees "and I'm going to only eat this type of caterpillar." And the one on the bottom says, "I specialize on beetles and I do this." And I think what you're seeing with the open source stuff is all these things can coexist. Like GNOME versus KDE. Everybody was claiming GNOME or KDE was the winner for forever. They're still around for forever. So, what I think with this cloud software as well where everybody is like, "Oh, this is the one winning," or this is the, there's a whole host of places for them all to live, and with open source I think things just live forever. >> John: What's your ecosystem analogy that coexistence is actually a better philosophy looking at the big picture than some dominant wolf or whatever. >> That's right, it's the diversity, it's the mutualism, it's the coevolution, it's the right diversity. Like a desert is actually a beautiful place if you go to it. Like we like to pick on the desert, but if you actually spend time in the desert it's gorgeous. There's nothing wrong with the desert. So, if you're some company who doesn't need Kubernetes and all the other pieces in this huge cloud environment, don't feel like that's something you have to take on. >> Peter: But they are the desert. >> That's right, but they are the desert. But, all my PhD research was in the desert, and I used to hate it, because I started this little rolly polly in the desert, and by the time I left I was like, "Oh, I miss the desert when I don't have it." >> John: The sunrises are beautiful. >> Sunrises are beautiful. You can see forever. If you actually pay attention to the small things... All I'm trying to point out is people live in Kansas, people live in New York, people live all over, and they usually find where they live, unless it's some disgusting dump, they say this is a beautiful-- >> Peter: They find beauty in it. >> Yeah, and I think it shouldn't necessarily be everybody has to get to the same place and use all the same technology. There's technology reasons for everything. >> So, I want to pick up on that concept. So the industry used to be pretty much structured around asset specificity. This asset does this for you. As we move more to a software orientation that notion of asset specificity starts to blend away. I think that's one of the seminal features of digital business and digital business transformation is the reduction of asset specificity, but it does mean that increasingly we need to focus on what I'll call value specificity, that we're moving away from the asset being the dominant determinant of structure and how you do things to the value that's being generated and the value that's being presented in any number of different fashions, and that becomes what dictates or describes who you are, what you do, both as an individual, also as a company, as well as a piece of software data. So talk a bit about kind of this notion of niche specialization being more tied to the value that you create as opposed to the asset that you bring. >> That's right, and we're seeing this a lot with our customers, who... You know, OpenShift is based off of Kubernetes and Docker and all that stuff, and containers, and so what we're seeing is a lot of companies come to us and say, "Well, I want to use OpenShift for this. "I want to use OpenShift for that." It's no more that we go to customers and say, "Here's OpenShift and you will use it "for purposes X, Y, and Z." What it is is well, that IT group might say well I've got three different business groups that I have to produce stuff for them that they can use. And they'll say, "Can I use Kubernetes for this? "Can I use, oh, I can't? "Well, then I'll get something else for this, or can we adapt-- >> Or complement it. >> Yeah, it's about creating value for the business unit, and it's becoming more and more that now. I think it's an evolution that we've seen, again, this evolution of stuff with the shadow IT and all that stuff. It became less about you're some sort of specialized high priest with this special asset that only you know how to control, I know how to do GIS software, I know how to do big data, no, what value do you produce for me? I don't care that you can buy these kinds of servers and provision them. If I can't use them, what does that do for me, right? So I think we see that at Red Hat a lot where we were the enterprise Linux company, and I think our leaders have done a really good job of saying, "Yeah, that's a good place "where the puck is right now, "but that's not where the puck is staying. "It's moving towards value, "it's moving towards integrated solutions." Go ahead. >> Let me extend this a little bit. So one of the things that we've observed within (mumbles) SiliconAngle, and we've talked to some other people today specifically about this, was the idea that open source has done a really good job of looking at a thing, a convention, that's well defined and well established and then building an open source variant of it. Open source has not been as successful, for example, in the big data world, where the use case or the definition of where we're going is amorphous. Instead, a lot of open source development ends up looking at each other saying, "Well, I'll fix your problem and you'll fix my problem, kind of. Nothing wrong with that, but the vision of where the industry is going to go. How are different companies, what will be open source leadership at redefining where this industry goes so that the open source developers can both be free to do what they need to do, create value as they need to, but at the same time, share a common understanding of where this ends up? >> So I think this goes back to what you were talking about with value, right? So I think what ends up... I'll use the example of big data. So I did a lot of statistical analysis for my PhD, and back then you used SAS or S-PLUS, both proprietary solutions. I think what has caused some of the explosion in big data is that you had these data scientists, the statisticians, intermingling, fertilizing with the computer science people who were handling these other really big problems. So what comes out of that, this is that margin thing again, right? You have statistics and-- >> Peter: Diversity and interesting things happen in the margin. >> At the margin. So what you have is these two groups come together, and suddenly you have the computer science people saying, "Oh, well I know a lot about algorithms "and I'm going to help you figure out "how to get value of what... "You're trying to solve this statistical algorithm, "I'm going to help you build distributed software that does that and that's where we get that happening. >> So the collaboration at the edge, the fringe, the lunatic fringe, or whatever you want to call it, the margin, is where the innovation is. >> I think that's where the innovation is because that helps avoid the navel gazing, right? Like, "Oh, I'm looking at what you exactly built, "and I'm going to build a slight variation on it." Well no, I actually need some, when you bring other disciplines in they say, "Well, this is the problem I'm going to solve," and the computer science person or the other side will say, "Well, that sounds "kind of like this thing, but let's try," and then suddenly new ideas come up and new ways to handle things. So I think, again, switching to value rather than what technology am I going to build is what's going to actually drive like, we need something to handle our big data. That's what's going to drive the vision. So you see in the big data world you see Spark, you see Zeppelin, you see all these different things competing, but what they're all doing is trying to drive how do I analyze big data efficiently? So you get some competing solutions. Then over time I think that's the vision that they're driving. >> I got to ask you, so like naval gazers is one dimension, but also there's the rearranging the deck chairs, like someone says, "Let's move things around "and magic will happen." Well you're pushing a whole nother concept, which I think is legit, which is as you put people together it might be uncomfortable, but then innovation can come out of it. Okay, so here's the ways. Computer and science and cloud computing, all that great stuff is happening, compute, storage, algorithm, etc., data, now society. So now society has issues, because what's the societal impact? These are first generation problems that we're facing, which side of the street does the cards drive on? Who gets hit first? They have to make these decisions. You see all these new issues, from even younger kids, cyber bullying, online behavior, across the board, societal impact. We are those margins. >> So I think for me tools... I thought about this a lot, right, because in the college I was kind of a tools person, and I think tools are value neutral. Any tool can be used for good or for bad. So, what we're doing right now in the open source world is develop, and in IT in general, is developing new tools, and what usually ends up happening is society develops norms after the tools have been created. In some ways, I think... I some ways, I kind of... It's a hard one. This is a much longer discussion and probably would involve some sort of alcoholic liquid or something to draw it out. >> It's a double edged sword, or tool, depending on how you look at it. We got to see it first before you can problem solve it. >> But the problem is-- >> You can't problem solve vapor. >> That's right, but on the other hand, sometimes you can see if you stopped and aren't so enamored with the latest and greatest tool without thinking about like, "Oh, well what are actually the implications of it?" I was going to say, I think the Europeans do a little bit of a better job of putting a little bit of foresight into tools when they come out saying, "Hold on, let's take a look at this." >> John: At the impact? >> Yeah, at the impact. >> So let me add one more thing to the conversation, because I think you're spot on, that the tools may be value neutral, but the impact, the transaction cost, of doing certain types of work in a different ways, and some work, and work is not necessarily value neutral. We may look at some tools and say, "That work is not good. "This tool reduces the transaction cost "of performing that work faster "or more completely than that work, "so that tool is going to have a less positive impact--" >> Impact on society as a whole >> "Than some other tool." And I think we can start introducing that kind of an analysis into it. >> I think so. I think that was... I live in this area, like I'm in Santa Cruz, so when I want to I say I'm not in the Valley, but when I want to I say I am in the Valley, I think the Valley is particularly enamored with the toys, or the tools, that it produces, and how technology will solve all our problems, and technology is great, and it is inherently good, and I like to say, "No, it's a tool, "and so a tool could be used for good or for bad." Like one example is ride sharing. Everybody was like, "Oh, this is the best! "This is awesome!" One of the things I thought of, my father is an immigrant, so I'm first generation on my father's side, and he wasn't a taxi driver, but I know how hard it is for first generation immigrants if you don't speak the language really well. So what used to happen with those ride shares is you had to have the capital to acquire a car before you could actually do ride sharing. So what you were basically doing was disenfranchising people who didn't have the capital from actually having this as a source of income when they came to the country. So, I was very conflicted about it to start with. Now, I'm less conflicted. I actually don't think ride share, given the economics I've seen actually play out I actually think ride sharing is not as big of a market and as game changing as everybody was making it. It was just some funny economics. >> Well Steven, certainly the conversation is very awesome. We should have you at the studio in Palo Alto next time you're in the Valley. >> Sounds great. >> You have plenty of tools and shiny new toys. >> Go by the Baylands and then go birding together at the Baylands, or maybe some fishing. >> Let's bring theCube over to Santa Cruz for a couple days. >> We should go down. >> That's great. >> Chill in Santa Cruz. Surf those waves, cloud, data, society. >> There you go. >> theCube on the boardwalk. >> Final question for you. Cisco is trying to push the margin with this event. It's a new event. It's an extension. It's outside their comfort zone. They had some projects that were kind of dismissed, interclouding, other things, this is a statement. Your thoughts on this show, because they have DevNet, why DevNet Create? Your thoughts. >> I think DevNet Create is a great opportunity for Cisco. I've been to the Cisco, is it Cisco Live, the huge gazillion people event? And there's a lot of energy around that, but that's mostly like network engineers and people who were bread and butter Cisco people. I really like that Cisco, that blurring between software and hardware means that Cisco really should be pushing people more in the, "We're going to help you create really interesting solutions." The more they make that easy for the developers... I think some developers are hardware hackers and love it. I am not one of those, and there's a lot of us who are not, and the more you make it easy for me to use software to create really interesting hardware things, the better it is for us. >> It's a classic case, the data scientists meets the algorithm guy. >> Steven: Exactly. >> So they're trying to bring these margins together where it might be awkward at first, but magic can happen. >> If I got to sit with some hardware people and like, "You need to make it so that I can write in Python "and do a whole bunch of neat networking and stuff "so at my house I can keep track "of how many birds are coming to my bird feeder "because I want to do this really cool experiment, "make that easy for me." >> By the way, you got camera, so you got bird recognition software. >> Steven: Exactly, exactly. >> A new feature on AWS. >> Yeah, I've seen demos of that. It's incredible what they can actually pull out now. >> Steven Pousty, Lead Developer at Red Hat, thanks for coming on theCube. Great conversation. >> Thank you very much. >> We'll have to continue it in Palo Alto. More live coverage here at Cisco Systems' DevNet Create. It's their inaugural event for developers. It's where IoT and app developers meet infrastructure, application infrastructure (mumbles). I'm John Furrier, Peter Burris with theCube. We'll be right back. Stay with us. (techno music) >> Hi, I'm April Mitchell, and I'm the Senior Director of Strategy & Planning for Cisco DevNet.