>> From Seattle, Washington, it's 'theCUBE' Covering KubeCon and CloudNativeCon North America 2018, brought to you by 'redhat' The CloudNative computing foundation and it's ecosystem partners. (upbeat music) >> Hello everyone and welcome back to live CUBE coverage here at Seattle for KubeCon, CloudNativeCon2018. I'm John Furrier. Stu Miniman, breaking down all the action here for CloudNative, trend, a lot of ecosystem partners, a lot of new developers, a lot of great open-source action in the cubes here covering it. We've been there from the beginning, our next guest and user, Max Schulze, Advisor and Founder of NBF, welcome to the CUBE, thanks for coming on. >> Thank-you, thank-you for having me. >> So tell me about what you're working on. You are doing something pretty compelling with Kubernetes and CloudNative, take a minute to explain what you do. >> Yeah actually, we are advising a very large energy utility in the Nordics and what we're trying to do with Openshift and Kubernetes is actually to shift loads between different data centers based on power availability. So if you have wind and solar power, you know that you only get energy when the wind is blowing so you really need to be able to match that load of the data center with the actually energy production which is quite challenging to be honest. >> Max you have different take on 'Follow-the-sun' that we used to talk about in IT I'm guessing, yes? >> Yes >> Take us inside a little bit, the sustainability is really interesting and how some of the power, you know, usage and heat and everything and maybe you can explain that a little bit before we get into the data. >> Of course, so generally how we got to a sustainable data center source was that in the Nordics you see a big growth of data centers in general so all the hyperscalers: Google, Microsoft, AWS. They are all coming to build data centers in Nordics. It's cold, power is cheap, you have lots of renewable energy available and we started to think 'Okay, but they have two problems essentially.' They generate a lot of heat, which is just emitted into the atmosphere so it's wasted, and the second problem is that they want 100% reliable power and reliable power you only get from nuclear, you get from gas, coal fire power plants not from renewables. So we looked into this, and we started to think about okay can we maybe get the heat out? Can we extract the heat from a data center and inject it into district heating grids and actually heat homes? With a hyperscale data center from Microsoft, 300 megawatts you can heat about 150,000 homes, that's quite significant. >> Yeah and how are you doing that? I mean I talked to a company once that was like 'Oh well we're going to, you know, we'll just distribute the servers different places and there will be ambient heat off of it.' But you're extracting the heat and sharing it. Explain that a little bit more. >> So most existing data center projects, they extract the heat out of the air but that's really inefficient. You get to about 100 degrees Fahrenheit which is not uh high quality heat. So what we want is 140 degrees Fahrenheit, about 60 degrees celsius, which means that we have to use liquid. So we have to use water in this case and we use a cooling system that is quite ironic from a start up in Germany called Cloud & Heat that uses hot water to cool servers. So the water really flows at a very very high speed through the data center and on it's way picks up a very low amount of temperature and we get out the temperature, we get out the water at 140 degrees Fahrenheit and we put it in at 120 degrees Fahrenheit. So it's quite, not a big difference, but it flows at a very high speed. >> So it makes it work? Makes the numbers work. >> Exactly. And so what's the home count again you mentioned one hyperscale data center, like a Microsoft data center powers heat for how many homes? >> About 150,000 homes from 300 megawatts worth of data center. >> And you guys put this into a grid so that's, does the location of the homes need to be nearby, is there a co-location kind of map or? >> Yeah actually, in order to do this we have to move data centers closer to cities. But luckily, data centers actually want to be closer to cities because your closer to peering points and one of the reasons why they usually can't come closer to cities is because power is not available near a city. So we um try, we can give them both. Right, they can come closer to the city and we can give them power, and we get the heat in return. So, so everybody wins. >> Yeah so I mean, a lot of the discussion we've had is the interaction between software and my data center infrastructure. You've got a story of software, with you know, actual like city underneath the infrastructure. Maybe you got to help explain how that was built out, what tools you're using and walk us through this all. >> So we originally started with Openstack, which was the first test because we need, in order to do this heat extraction we need to also steer really the software, the workloads that run on the data center because you know a chip only gets hot when the server actually does something so we really had to figure this out. We started with Openstack and then we started looking into load shifting which immediately brought us to Kubernetes and then Openshift because you can use the internal scheduler to basically force loads across different locations. We connect it to our energy systems, to our forecasting systems and to our heat load management systems and then basically push workloads around. Right now we have two sites where we test this and it's not as easy as it sounds. And we basically want to move workloads, concentrate them where we want, we have heat. So um yeah, Redhat is helping us a lot doing this but still it's not that easy. >> Yeah yeah, it's interesting. You know, I think back you know, virtualization was about you know, how can we drive some utilization and get some out? You really want to you know, concentrate and run things hot. >> Yeah, exactly. >> Quite inter- Alright tell us about your involvement in this ecosystem, you know, what brings you to the show this week, what do you get out of coming to a show like this? >> Yeah, actually I came because Redhat invited us to talk at the Openshift gathering at the beginning of the conference. And generally, we don't really have a commercial interest in making data centers or data infrastructure sustainable, we, we don't gain anything from that, but we believe it's necessary. If you look at the growth curve of data centers you can really see that they will consume more and more power, and then the power they consume is not compatible with renewable energy. So we are hoping that we can influence people and we come here to tell people our story and we actually get great feedback from most of the nerds. >> Well it's a great story. It's one of those things where you're starting to see data centers trying to solve these problems. It's great with the renewable energy, having that kind of success story is really huge. Um, You mentioned that data centers want to be close to cities. I got to ask the question, in Europe, well you've lived around a lot of places. Is there a more cloud city oriented, like is it London, you got Paris, you got... I know Amazon's got data centers in Ireland. Is there certain cities that are more CloudNative culture? How would you break down the affinity towards CloudNative? If you had to map Europe, which major countries and cities would you think are advanced, cloud thinking vs. tire kickers or you know, people just kind of just trying it? >> In Europe there is a region called the FLAP region, that's Frankfurt, London, Amsterdam and Paris. Those are where you have the highest concentration of data centers, but it terms of CloudNative adoption, I would say that probably in the UK you have the most adoption rates and in the Netherlands. Germany is always, I am German so I can say this, we are always a bit behind in terms of cloud technology because we're a bit scared and we don't know- >> You'll watch everyone test it out and then you guys will make it go faster. (john laughs) >> Maybe, maybe, maybe a bit more efficient but uh, generally I think the cloud adoption rate in Germany is the lowest and the UK and the Netherlands is the highest I would say, yeah. >> Awesome, well thanks so much. Congratulations on your success, we'll keep following you and when we're in Europe we're going to come by and say hello. Thanks for coming and sharing the stories. The CUBE, breaking down all the action at KubeCon, CloudNativeCon. I'm John with Stu Miniman. Day 2, we got three days of wall to wall coverage. Thanks for watching. (upbeat techno music)

>> Live from Seattle,Washington, it's theCUBE. Covering KubeCon andCloudNativeCon North America 2018 brought to you by Red Hat, the Cloud Native Computing Foundation, and it's ecosystem partners. >> Hey, welcome back everyone,live Cube coverage here at KubeCon, CloudNativeCon2018 in Seattle. I'm John Furrier with Stu Miniman hosting three days of coverage. Wall to wall, 8,000 people,double from last year, North America, expanding intoChina, Europe, everywhere. The CNCF is expanding, so is Kubernetes. The rise of Kubernetes has spawned the Cloud Native movement going mainstream that's ecosystem driven. We got a great guest here. Steven Bower, data andanalytics infrastructure lead at Bloomberg, featuredthem on siliconangle.com in one of our special reportsand user using Kubernetes and the variety of Cloud Native. Steven welcome to theCUBE. >> Thanks for having me. >> Thanks for coming on,award winning end user, given all the end users,everyone's kind of award winning. >> Yeah, yeah, yeah. >> Congratulations. Bloomberg's known, we've covered you guys, great development team. You guys have a lot ofengineers at Bloomberg as well as being a media company on cable, Bloomberg terminal, everything else. You've got a lot of datascience, you've got a lot of engineers, you're building stuff. What's the focus on Kubernetes? Where are you using it? How are you contributing? What's the dynamic? Why are you winning with Kubernetes? >> Sure, that's a good question. I think, well we're usingit all over the place in lots of different things. We have a huge engineeringteam that does all kinds of different things. So in the area that I manage,which is data and analytics infrastructure, we have been we basically managedatabases and search engines and all kinds of other tech like that. What we've ended uprealizing is that we built something that looks a lot like Kubernetes but doesn't work nearlyas well for all of those different systems, tomanage them at scale. You know, we're talkingthousands of instances of post cross and solar andall kinds of different things and having a singletool, or single platform which we can kind of levelup all of those things really makes a lot of sense in terms of not necessarily like cuttingcosts and things like that 'cause that's actuallynot as interesting to me as actually allowing theteams that manage those things to actually contribute to those projects, contribute to solar or postcross and stuff like that and free them from havingto spend a lot of time managing infrastructure. >> Tim Hopkins said, itwas just on theCUBE here before you came on,from Google, one of the co-leads on Kubernetesat gkegoogles@cloud. He said something interesting. I want to get your reaction to this. One of the benefits of Kubernetesis to give the confidence that deployments are going to be reliable and that confidence gets a flywheel and then people startshipping more as a matter of course of the business,not like oh my God we got to push a new code,oh my God, fingers crossed, press the button. The old model was fingers cross, go, QA, no, no, confidence, theconfidence and the iteration. Is that where you'reseeing the value, too? Does that relate to you? Does that make sense to you?Does that resonate with you? >> Yeah, it definitely does. A lot of the models thatwe're trying to move towards are really like declarative model of both how we develop software andthen how we deploy software and then how we manage it in production. Kubernetes offers that, thatecosystem across the board. That's been really, trying to think of a great way to put this. Being able to have that tooland being able to do that and the repeatability. In the world that I livein, everything we do we don't do one of it,we do, I think we run something like 2000 solar clusters. So all we're doing all daylong is just stamping out the same thing over and overagain and if I can build one system that doesthat very, really cleanly and simply and then I canuse that same system for running post tests orrunning something else that gives us the confidenceand we can test it, we can run it on our laptops. Our developers can developand do all that kind of stuff and it works the same everywherethey go and we can just rinse, lather, repeat kind of. >> So Steve, step back for a second. Your infrastructure, is thisall Bloomberg Data Center's? How does cloud fit into the discussion? >> Yeah, I mean, we dohave some infrastructure running in the cloud but primarily it's all on prem and data center. In my world it's all onmetal because we have all these data systemsthat need direct access to SSDs and MME andall this kind of stuff. >> Can you give us, withoutsharing state secrets, a little bit of the scaleof what you're doing? I love data's at the centerof what you're doing there. We can all understand howimportant data is to your business but talk aboutwhat the requirements are that why you have some special requirements that thetypical enterprise wouldn't. >> Sure, I think, youcan look at Bloomberg as a media company, wehave news, all that stuff. We obviously have the Bloomberg terminal and really what drives that terminal, it's all kinds of software but in the end it's data, right, andit's all kinds of data. What is that definition,big data and all these whatever stuff that everyonewas pitching five years ago. We have all of those problems. We have data that is movingat millions of ticks a second. We have enormous data sets. We have really complex data sets like people scanning courtfilings from tiny little courts all around thecountry and sending that data in and we have tonormalize that and put it in. So all these crazy differenttypes of information. They are both demanding interms of the complexities of parsing data and puttingthem and structuring them into those systems as wellas the scale so we have some pretty enormous andhigh performance systems that require us and kindof drive us to that need for metal and very focused on performance in all different aspects. >> Great, wonder, give us your engagement with this ecosystem here. One of the big questionscoming in is okay, Kubernetes, the thingwe here from the CNTF is well, it's getting kind of boring. I don't know that I agree with the term. I understand they'resaying it's becoming mature and therefore there's less drama around it which is good but this ecosystemis anything but boring. You ask a user like yourself, you've got complex requirements. There's more than 30different projects a year. What do you use out of here? What do you build yourself? What do you contribute to? How do you consideropen-source contributions? It's a big nut and wedon't have a ton of time but if you could scratch thesurface on some of those. >> I think the number onelesson that I've learned from this ecosystem isthat it's moving so rapidly that when we decide tobuild something on our own we have a talk tomorrow aboutour data science platform which we built about ayear-and-a-half, two-years ago. By the time we were ready to talk about it and everything like that,you have all the other different technologiesthat have moved forward. So it made us realize thatif we're going to start something internally,a new project, either A we should go look and seewhat's out there and contribute to that or we should juststart it in open source to begin with rather thanthat oh, let's build it and then we'll open source it. >> Chasing your tail kind of thing. >> Yeah, it's like we have tobecome part of the ecosystem in our entirety. >> That brings up a good question. I want to ask you this incontext of thinking about your peers that mightnot be as progressive as Bloomberg on the tech side. You guys certainly do a greatjob and it's well documented. Classic IT shop, racking andstacking servers and boxes and now we got the wholedigital transformation thing going on, same old, same old but now, 2019, real impact. The investments they'remaking on how to change their IT, their data isnow in front of them. They have to deal with them. This is right front andcenter 'cause companies are realizing they'regoing to go out of business if they don't actually make the adoption 'cause the data's super valuable. So how do you see the Kubernetesand the CNC of ecosystem changing the investment practices of a classic enterprise IT? You know, if your peerscalled you and said hey Steven, hey help me out,what's the secret playbook? Where do I go? I don't want to get, Igot to make some changes. What do they change? What's the impact of theinvestment with Kubernetes? What's the end game? What's the real impact? >> I think, it's a toughthing, right, 'cause Bloomberg is really notlike your typical IT shop. We are a software company at heart and so that makes us alittle bit different. When I talk to other people,I say that in the sense that not a lot of companiescan afford to decide to make a project open-- >> 'cause they outsource everything. >> Right, outsource it. Well, I mean-- >> They outsource everything. >> That's actually a huge change though. We're not sitting heretalking about hundreds of commercial products that are owned by a small handful of vendorsthat are multi-million dollar investments foreverything we're doing. We're talking about lotsof little tiny companies that have products thatare really, really valuable that are in the open sourceworld that we can get our hands on and startworking with before we even make a decision about talkingabout support or whatever. There's all kinds of technologies that, I walk into this room andthese are like friends all around 'cause we'veworked with all their software and we're like hey, theseguys have a company now. This was just a GitHubrepo a couple years ago and I think that that's abig change and embracing that, that's probablyreally hard for your typical kind of IT shop where theywant to have this clear line of I can call techsupport and get someone on the phone and that's like the main-- >> The classic old software model but it's changed. >> So Steve, one of thethings we're trying to get some insight on here isit's not just running Kubernetes in production,it's what am I doing with it. How does that change my business? I understand ML is a big pieceof what you're doing there. Give us some insight as to how does this transform your business? Does it transform your business? >> Specifically on the MLside and we'll talk about this actually that's kind of thefocus of our talk tomorrow so I don't want to stealtheir thunder too much but a lot of it was really about looking at okay, how did ML, deep ML people work? How did they want to work? If you ask an ML personwhat they really want they want an infinitely scalable cluster that it's just theirs and they want to an assay to manage all theinfrastructure for them and a data engineer to managecleaning up all the data and all these things and they wanted that all to themselves and not haveto share it with anyone else. So a lot of what we try tofigure out is how we can actually deliver that to themand it really has transformed. Once people realize that onour platform they had access to an enormous pool of GPUs,it went from oh, I want to work on my box and can you giveme GPUs on my one little box to wow, I can dohyper-parameter tuning across hundreds of GPUs overnight or during the day or whatever their needs are. It really unlocked people's capabilities and they're actuallylike, they went from being skeptical of a systemthat they had to share and things like that 'causeit actually just works and that's really the-- >> That's really thedopamine effect for them. They can see value withouthaving to go through the slogging of the configurationsand the normal stuff >> Yeah, exactly.>> that they had to do. >> Authentication. >> So we've been hearingthreads of the CICD pipeline is a big benefit,which you're kind of seeing as well but whatwe're also seeing people building below Kubernetes seeing storage and networking getting better. How do you see that holistically? Are you seeing is thenetwork more performant, that notion of programmabilitybecomes now part of it, automation, it's software. Everyone has to build software. In fact, I talked to theVP of Technology Innovation at Proctor and Gamble andhe's saying hey, we outsourced everything, I got to start hiring software so maybe not as big asBloomberg but the trend is let's get more software people on board but they still got networks,they still got storage, they still got the gear. What's the impact, the under-the-hood? >> Yeah, I think it'scomplex because you typically have these structures thatare built inside companies where you have a networkingteam and you have an infrastructure, ahardware team and whatever. One of the SREs on my team the other day, he was like, do you thinkwe can talk to the network team about puttingsoftware on their switches? That's a really interestingquestion to start asking and he actually had areally good use case. That makes a lot of sense, maybewe should think about that. And then dealing with, there'sobviously the technology aspect of that but there's also skillsets. Someone that's been workingwith a bunch of switches for a bunch of years isn'tnecessarily a programmer, used to a typical CICDprocess and things like that. >> On the flip side, I thinkthat's cool to recognize the networking guy butwe heard Tim Hopkins say there's a lot of policyknobs in Kubernetes that the networking guyscould potentially take advantage of so it mightwork the other way. Are the network guys looking at Kubernetes saying hey, or are theynot yet that sophisticated but they would love, they'd love policy. Network guys write policy. Wouldn't you want-- >> Yeah, yeah, oh absolutely. It's actually one of thebiggest draws of using Kubernetes in our ecosystem. We've made heavy use ofapplying network policy down to the workload level which means that from a securityperspective, if I know that I'm transmittingdata between two different places and I've only openedup assets for that one application, for thatone particular use case, rather than saying well,I know that I'm running the same workload on thesame box and I got to open it up for everyoneon that box but maybe someone might use thatthing but maybe they won't and like worrying about stuff like that, it's like no, I can runa workload and I know that these are the only two end points that it can talk to. >> Oh, that's a relief. That's like, hey, we're done. >> So for them this is their panacea. I know exactly whatworkloads are doing exactly what on the network andwhat they're capable of so that's been-- >> That's real progress. That's progress. >> Oh, it's huge progress, yeah. And we've been able todo things that we used to not be able to do for years. >> Talk about the-- >> I just had a quicklittle question there. You mentioned you've gotten SREs. When did you pick that up asa term that you called there and how do you see if you talk a little bit to the skill set and the jobs of peoplethat you have inside. >> Bloomberg's a big companyso the terminology of it and what actuallyindividual teams are doing is probably a little bitvaried across the organization. It's been something that'scome in over probably the last two to three years at Bloomberg. In my organization, it wasactually really interesting 'cause when I started off with, you know, you read the Google book and whatever. What I did is I wentto the guys on my team that were going to becomethe SREs for the organization and I had them write thismanifesto about how we should build and deploy and managesoftware and I didn't tell them necessarily up front thatthis is what was going to happen but when they finishedwriting that and agreed that this is how thingsshould work and they argued for a while, I said, okay,now go build all the tooling to make this easy forpeople to do, all right. And that's what we, and thenthey've just been building off their tooling. Turns out when you're workingwith a lot of the tools and the CNTF and then with Kubernetes, that's actually not that hard. There's lots of thingsthere that are just easy when you get to that place and so that's the kind of journey we'vebeen on to really try to build that infrastructure andthey've done a good job. The engineers downstream of them the speed that they're able to develop and the assurance that there was a CVE forKubernetes two weeks ago and we patched it theafternoon the CVE came out. Being able to do that in anysort of company of scale is I've worked a lot ofbanking and stuff like that in my past and it's unheard of to be able to deploy things in that speed. >> And that's really, Imean this is the goodness of clouds, the goodnessof having that kind of consistency operationally. It's funny you use SRE,that's a Google term. It's a great term andyou've got developers, you got operations kindof working together now. That's the magic. Well Steven, thank you so much for sharing this great insight on theCUBE. Certainly great valuefor the folks watching. Lot of traction, a lot ofpeople, end users contributing and consuming Kubernetes,building around it. Great trend, it's really fun to watch. A lot of composable servicesup and down the stack so congratulations. Steve Bower, Data andAnalytics Infrastructure Lead at Bloomberg. This is theCUBE bringingyou all the action, sharing the data here at KubeCon. This is theCUBE. We'll be right back withmore after this short break. (electronic music)