(upbeat music) >> Announcer: Live from Copenhagen, Denmark it's the CUBE. Covering Nutanix.Next2019. Brought to you by Nutanix. >> Welcome back everyone to the Cube's live coverage of Nutanix.Next here in Copenhagen, Denmark. I'm your host Rebecca Knight, co-hosting alongside, Stew Miniman. We're joined by Monica Kumar, she is the SVP product marketing at Nutanix. Thank you so much for coming back on the Cube. >> Sure, thank you for having me, I really appreciate it. >> So the last time we met, we were in Anaheim at the last big Nutanix conference and you were fresh into the job, six weeks in, you (laughs) and now you're seven months in, this is after a 22 year career at Oracle. >> Yes >> So you're a tech veteran, but tell us a little bit about how it's going, what you've seen so far, why the opportunity appeal and if it's living up to what your expectations were. It's been an absolute adventure at Nutanix. It's been, actually it's going to be close to eight months now and it was a bit scary for me to take the plunge after 26 years in the tech industry, I've had a fulfilling career. But there was a, actually couple reasons why Nutanix was so appealing to me and it's been a fantastic ride so far. One was, this intense focus on providing technology that's so innovative, that it's geared to simplifying IT's live, and geared to its business outcomes. But there's a bigger goal for Nutanix, which really drew me to the company, which is this obsession with customer delight and providing outstanding customer experience. So here I am, almost eight months later, I'm living it, in the Nutanix world and hoping we're delighting customers as well as we go along. >> Monica, it's a very much a different company. I look at Oracle and Nutanix. Many of the Nutanix executives and team have background in Oracle, you know, Oracle, Software at its heart, and helped deliver one of the stickiest applications in Enterprise as well as a role in IT, I mean the DBA is there. Lot of discussion here at the show here about moving from the discussion of HyperConverge to HyperCloud. Give us your thought as to where you see your customers, today, kind of the state of the industry, and where you see Nutanix fitting in going beyond Hyperconverge into the broader Cloud discussion. >> Yeah I think that's a great question to set up the context. If I think about companies like Oracle, Nutanix, and some of the larger software companies that been around for a while, there's a lot of commonality, I think, between them, right. One is catering to enterprise customers, so even the Nutanix is only 10 years old, I was surprised as to how many big global 2000 companies, big brands actually use Nutanix today. So we've actually almost been born in the enterprise and now we expanding out to the commercial space. So by that what I mean is, when you're born in the enterprise, you know how important data centers are to our customers. They've invested huge amounts, in some cases billions of dollars to create these fully functional data centers that are hosting all the applications and data and all the business critical databases in the data center. And now, they're trying to figure out how do they bring agility and flexibility and speed while preserving all this investment made in the data centers. So I think from that perspective, we very much understand it's about helping our customers who've built big data centers on premises to bring Cloud agility to those customers, whether it's on premises or in public Cloud, and actually the combination of both is where hybrid comes in. >> So what is the status of things, in terms of where are most companies at right now, would you say. >> Yeah, interestingly, we've run a number of surveys and in 2018 when we ran the survey around HybridCloud, 86 percent of the survey respondents said that's the IT model they would prefer because they can exponentially enhance the computing resources, they can actually without investing money in wheeling in servers and storage and space and pulling, they can actually advance and expand the stack where they can deploy applications, right. So it's the most preferred IT model, however, there's lots of issues in making it a reality. And I think we can talk about that. Almost 70 percent said they would love to make it a preferred model, but they are unable to deploy it because of multiple reasons. >> Yeah, it's interesting when I think of what I've heard from customers for years and years, you go talk to IT and they say, "I don't have enough headcount, I don't have enough money," "I can't keep up." Yet, some of the new deployment models, Oh my gosh, you're going to put me out of a job, you know, I won't be able to do anything it's like, wait I thought you didn't have time to do any of the things you want to do and didn't have enough money. If we could make it easier, if some of the pieces could be invisible or just handled, you could go work on all of those other projects that you've been wanting to. How is Nutanix helping customers through kind of that transition to, as you said, they want agility, they want choice, they need to be able to have IT be a participant with, if not a driver for the business. >> Yes, you know, if you think about in the last decade, IT has been very focused on infrastructure modernization or what we call data center modernization. So whatever we have, we want to make it simple, cut costs so it's most efficient, and I think that's a great initiative to embark on, but it's almost very inside, inward-centric. It's about how do I make my life easy, make myself more productive, cut costs in my work. I think if we turn it around to customer delight and IT wanted to delight the customers, and really focus on becoming a service organization, that's when things start changing because now we are talking about consumerization of IT. In our lives, we all are so used to delight, our smartphone response as soon as we click something or swipe something, we get the answers. There're lots of things in life that have changed where it's instant gratification in a way, and I think companies are also asking and demanding that of IT. It's like hey if I want IT resources, I want it right away. So I think IT as an organization is changing and really focusing more on becoming a service organization and delighting their customers and that's where automation comes in. That's where cutting down all the manual tasks, which a machine or a robot or software can do, so the human being can focus on what's more important to them, what's more strategic, and I think that's where having and choosing the right platform comes in, so that IT can provide more resilient services and really provide services at the speed the business is demanding. So to me, I think that's where companies like Nutanix come in, where we can help IT become that service organization. >> So when you're talking about this evolution of IT, I mean, what does that mean for the skills that become the in-demand skills, what does that mean for how IT is placed within an organization and how it interacts with other functions, I mean how does this change really manifest itself. >> Yeah, and I think to your point as well too, I think IT has to become a change agent, no longer can IT just be in a supporting role and just help advance the business because I think now businesses are realizing that if they don't delight customers, they can't really grow. They won't stay competitive, so IT has to become the change agent to use technology to advance and grow the business, and I think from that perspective, if you look at IT admins, Cis admins, storage admins, data administrators, all of them need to start thinking about what is the next level of skillset, which makes me become more of a dev-ops or a data-ops person, or an IT-ops person. As it was to simply just administering something, simply badgering provisioning is not good enough anymore. There needs to be some element of programming, some element of continuous delivery and some element of bridging the gap between a public and private cloud solution, where apps can run on both places, where data can be in both places. So we do want the IT skillsets to evolve in a way that they can become more cloud engineers in my opinion, as opposed to staying administrators. >> Yeah, Monica, I had a great discussion with a customer earlier in the show, and he said that customers what we used to do in IT is follow the rules and what I don't want you doing in the future is following the rules, I want you to try things, I want you to try to break things and they felt that Nutanix was a platform that enabled them to be able to do that. >> Yes, absolutely, I think IT is in such a powerful position today to drive change, and really by uplevelling the skills, the IT administrators would realize they become more strategic to the organization but they even have better job prospects for themselves like individually right. I think they can do so much better in their career as well. >> Yeah, there's the great line that the executives say: what if we train our people up on new stuff and they leave, and the response is what if we don't and they stay. (laughs) >> Yes, I totally agree. >> The danger. So in terms of this evolution of IT as a functional unit in an organization and also as a human being who just works in the industry. We're talking about all these changes. How is it also changing the way organizations work? Do you know what I'm saying, in the sense of how is this evolution of IT driving change in the workplace. >> Absolutely, I think some of the old sidewalls are breaking. Just let's use Nutanix as an example when we first came out with a hybrid on which infrastructure solution, we broke the sidewalls between compute storage and virtualization. You know there was >> Altogether now. >> Yeah, exactly all together now, exactly. So there was either sys-admin, storage admins, already with using hybrid conversions, they started to work together. Now more-so, as dev-ops becomes, like I said you know, it's dev-ops , AI-ops, IT-ops, data-ops, I think we're going to start to seeing the organizations merging almost, right, and maybe there won't be a need for having a separate DBA versus a separate storage admin, versus a separate sys-admin. Maybe we are going to a place where it's going to be dev-ops or some ops, you know, all ops. That organization that's going to help create the platform for apps and data working together because the technology will be so seamless and so simple to actually use that they can focus on the process that they need to create with the organization to deploy the technology and benefit from it. >> Monica, since you've now been at the company almost eight months, I'm wondering if there's anything now being on the inside that you've learned that you'd say, Gee I wish more people on the outside understood this about Nutanix. >> Yes, absolutely I think the one thing which I knew coming in, but you don't really realize it 'till you actually realize it, and you internalize it, it really is the intense focus we have on customer success. I mean we live and breathe by that, every single person from executive level down and I give you a very small example. About two months ago, I got an email, this random email from somebody saying, "Hey I just bought Nutanix" "last week and I'm having some issue" "and I just saw you joined Nutanix, you know," "I want to reach out to you." At first, I thought hm, but I responded and I said, "Well I'm glad you reached out to me." "Is there anybody you're working with at Nutanix?" And turns out he was working with some channel partners and somebody he gave me a name. Within 24 hours, we had done enough trouble-shooting and trying to figure out what the problem was. I reached back out to him saying, you can get the part that you need, and within 48 hours he had a spot and he emailed me saying, "Thank you so much", and by the way this was a really small customer in terms of the size of the opportunity that we had, but it doesn't matter to us. Every customer counts, and every customer's success is paramount to us. >> So all hands on deck kind of base-- >> It is all hands on deck kind of thing, yep, so I can say, to me, even though I knew going into it that that's a Big Four philosophy, but to live it, it's a totally different level. >> Great, well Monica thank you so much and congrats on the new job. >> Thank you. >> I'm Rebecca Knight, first Stew Miniman, stay tuned on more of the Cube's live coverage of .Next. (techno music)

>> Live from San Francisco, it's theCUBE. Covering Google Cloud Next 19. Brought to you by Google Cloud and its eco system partners. >> Hello everyone welcome back here to theCUBE live coverage here in San Francisco, California. We're in the Moscone Center on the ground floor here. Day three of three days of coverage for Google Cloud Next 2019. I'm John Furrier, my co-host, Dave Vellante, Stew Miniman out there getting stories out there He's also been hosting. Dave, great to see you! Evren, Director of Product Management at Google Cloud, doing all the data streaming the data. We're streaming data right now. >> Absolutely, this is it. This is it. >> So let's stream some data. So streaming data has certainly been around for awhile. Dave and I when we first started theCUBE ten years ago, it was part of Silk and Angle Media hadoop was just a small little project. That really kind of was the catalyst moment for around big data that's now evolved to it's own position. Now you have streaming data, you have cloud scale, the Cloud has really changed the game on big data. Changed the nature and dynamics of it and one of the things is streaming data, streaming analytics as a core value proposition for enterprises, and this is fairly new. >> Very true. >> What's your take on it and how does it relate to what's going on with Google Cloud? >> I am glad we're talking about that. This is an exciting time for us. Streaming like you said is growing. Batch is not going away, but streaming is actually overtaking a lot of the applications that we're seeing. Today we're seeing more streaming applications taking place than batch. One of the things that we're seeing is everybody is gathering data from all over the place from your websites, from your mobile phones, from your IoT devices, just like we're doing right now. There's data coming in and people want to make decisions real time whether it's in the banking industry, in your healthcare, retail, it doesn't matter which word cycle you're working with and we're seeing how those messages how those events are coming in and where the decisions are being made real time, milliseconds we're talking about. >> Why is it happening, what's the real catalyst here? Just tsunami of data, nature of the value, all of the above, what's the? >> We believe one of the things is like you mentioned Cloud really changed the game. Where people actually can reach globally data and messages at scale. We're talking about billions of messages coming in and processing capacity is available now we can actually process it and make a decision within milliseconds and get to the results. To me, that was the biggest catalyst. And we're seeing many of us have grown up using batch data, making decisions now everybody is talking about M.L. and A.I. You need that data coming in real time and we can actual process it and make the decision. To me, that's the catalyst. >> First of all we love streaming data, this topic. One we believe streaming where shooting video but data, real time, has been one of the keys you see self driving cars monging of data, mixing and matching of data to get better signal and better machine learning and I got to ask you, because batch is certainly the role for batch is kind of old school it's some old techniques it's been around for awhile, >> It's not going to go away though. >> It's not going to go away it's established it's place but the knee jerk reaction of existing old school people who haven't migrated to the new modern version they go to the batch kind of mind set. I want to get you're reaction. Data lakes, there's nothing flowing in a lake. Okay, so there is a role for a data lake streaming gives me the impression of like an ocean or a river or something moving fast. Talk about the differences because it's not just the data lake okay that's a batch kind of reaction. >> It is a complementary. Actually it's not going away because all of that data that we had in the back is something we're relying on to really augment and see what's changing. So if you're in a retail house you're buying something, you're going to make a decision and your support is actually behind it. OK here's Evren, he's actually shopping around this and he wants this for his son. That's what the models built around it is looking at what is my behavior and in the moment making a decision for me. So that's not going away. The other thing is batch users are able to take advantage of the technology today. If you look at our data flow, same set of codes, same set of capability can be used by the same folks that are used to batch. You don't have to change anything so that actually we help folks to be up skilled using the same set of tools and become much more experienced and experts in the streaming too. That's not going away we help both of the worlds. >> So, complementary. >> Very complementary. >> So data lakes are good for kind of setting the table if you have to store it somewhere but that's not the end game though. >> No. >> Okay. >> I wonder if we could talk about the evolution from batch to real time streaming. And my favorite example, because I think people can relate to it, is fraud detection. Ten years ago, it was up to the user to go through his or her bill, right? And then you started to get inundated with false positives, and now lately, last couple of years it's getting better and better. Fewer false positives, usually when you usually no news is good news. News is usually bad news now, so take that example and use that to describe how things have evolved. >> I am a student of AI I did my Master's and PhD in that and I went through that change in my career because we had to collect the data, batch it and analyze it, and actually make a decision about it and we had a lot of false positives and in some cases some negative misses too which you don't want that either. And what happened is our modeling capabilities became much better. With this rich data, and you actually tap into that data lake, you can go in there the data is there, and this is spread data we can pull in data from different sources and actually remove the outliers and make our decision real time right there. We didn't have the processing capability we didn't have a place like PostUp where globic can scan and bring in data at hundreds of gigabytes of data. That's messaging you want to deal with at scale no matter where it is and process that, that wasn't available for us. Now it's available it's like a candy shelf for technologists, all the technology is in our hands and we wanted all these things. >> You were talking about I think the simplicity of, I'm able to use my batch processes and apply them. One of the complaints I hear from developers sometimes is that the data pipeline is getting so complicated. You were talking about you're grabbing stuff from websites, from financial databases, and so depending on what data store you're using and what streaming tools you're using or other A.I. tools, the pipeline gets very complicated the A.P.Is start to get complicated but I'm hearing a story of simplicity. Can you elaborate on that and add some color? >> Yeah I'm glad you're asking that question you may have heard, yesterday we announced a whole bunch of new things and ease of use is the top of the line for us. Really are trying to make it easy. If you look at this eco pipeline we're building with data flow, it helps you end to end. Data engineered no matter which angle their coming in should be able to use their known skill sets and be able to build their pipelines end to end so that you can achieve your goals around streaming. We aren't really having to go through a lot of the clusters of the pipelines we are going to continue to push that ease of use over and over, we're not going to let it go because make it easier, everyone will adapt it faster. >> You mentioned you got a PhD in A.I., Master's in A.I., A.I. has been around for awhile. A lot of people have been saying that but machine learning certainly has changed the game. Machine learning plus cloud has been a real accelerant in the academic and now commercial aspects of A.I. So I want to get your thoughts on the notion of scale which you talk about, plus the diversity of data. So if you can bring in data at scale get more signaling points more access to data signaling the diversity of data becomes very key. But cleanliness, data cleaning, used to be an old practice of you get a bunch of data, stack it up, put it in a pile corpus, and you kind of go clean it. With streaming, if it's always flowing there's kind of a behavioral characteristic of data cleanliness, data monitoring, talk about that diversity of data clean data and how that feeds machine learning and makes better A.I. >> Good one, so that's where we actually are able to, if you look at PostUp, you're building joint your table set of datas with streaming set of datas you can actually put it into data filter it and make those analyses. And within both, we provide enough of a window for you to be able to go back, hey are there things that I should be looking at, up to seven days we can provide a snapshot because you will always find something you can go back, you know what I'm going to remove this outlier. All worrying about all the processing we do before we bring in the data so there's a lot of cleanliness that takes place but we have the built in tools we have the built in capabilities for everyone to get going. It's ready to scale for you from the moment you open it up. That's the beauty of it, that's the beauty of when you start from PostUp to data flow to streaming engine it's ready for you to run. >> Talk about what's changed though when people hear diversity of data they get scared, oh my god I work, heavy lifting. Now it's a benefit. What's easier now to deal with all of these diverse data sets, what's the easy revolution? >> So do you remember the big V's of big data right? Volume, velocity, variety. People were scared about the variety. Now I can actually bring in my data from different places. Again, let's go back to the shopping example. Where I shop, what I shop for, that actually defines my behavior around it. Those data sit somewhere else. We bring those in to make a decision about okay everyone wants to go buy a scooter or whatever else, that's the diversity of the data. We're now able to deal to with this at scale. That was not available we could actually bring in and render this, now everything is going to do this much more sequential. We're now able to bring all of them together process it at the same time and make the decision. >> What's the key products that will make all of those happen, take us through the portfolio if I want that would you just said which is a great value. It sounds like not a heavy lift all I have to do is point the data sources into this engine, what are the products that make up that capability? >> So if I look at the overall portfolio on Google Cloud from our data analysts point of view, so you actually can bring in your data through PostUp, lots of messaging capability globally and you can actually do it regionally because we have a lot of regional requirements coming from various countries and data flow is where we actually transfer the data. That's where you do the processing. And you use all of these advance analytics capabilities through your streaming engine that we released and you have your B query, you have your OMLs, you have all kinds of things that you can bring in you're big tables and what have you. That's all easily integrated end to end for any analyst to be able to use. >> What is beam? >> Beam ah that's great I'm so glad you asked that question I almost forgot! Beam is one of our open sources we donated the same set, just like we did with Koppernes few years ago, we donated to the open source it's growing. This year actually it won The Technology Awards. So the source is open the community really took it upon, they use that toolkit to build their pipelines you can use any kind of a code that you want Java, Gold, whatever you want to do it and they contribute. We use it internally and externally. It's one of those things that's going to grow. We have a lot of community events coming up this year. We might, and I've seen the increase, I'm really really proud of that community. >> Evren, I love the A.I. can't get my mind off your background and academic because I studied A.I. as well in the 80s and 90s all that good stuff. Young kids are flocking to computer science now because A.I. is very sexy, it's very intoxicating and it's so easy to deal with now. You guys had a hack-a-thon here with NCAA using data really kind of real time and kind of cool things are happening. So it's a moment now for A.I. this is the moment. What's your advice, you've been through the wars you've done your chore duty all those years now it's actually happening. What's your advice for young people who want to come in, get their hands dirty, build things, use A.I., what's your advice, how they should tackle that? >> I am living it, both of my sons one is finishing junior high, the other one is a senior in high school, their both in it. So when I hear my young kids come and say, "hey bubba we just built this using transfer flow." Like it is making me really proud. At the middle school level they were doing it. So the good news is we have all of this publicly available data for them. I encourage every one of them. If you look at what we provide from Google Cloud, you come in there, we have the data for them, we have the tools for them, it's all ready for them to play so schools get free access to it too. >> It's a major culture but how do they get someone who's interested but never coded before, how do they jump right in and get ingratiated and immersed into the code, what do they do? >> We have some community reaches that we're actually doing as Google. We go out to them and we're actually establishing centers to really build community events for them to really learn some new skills. And we're making this easy for them. And I'm happy to hear more and do it, but I'm an advocate I go to middle schools, I go to high schools, I go to colleges. Colleges are a different story. We provide school classes and we provide our technologies at the universities because enterprises need that talent, need that skill, when they graduate, their going to hire them just like I'm going to hire them into my organization. >> So my number one complaint my kids have about school, they're talking about kids that, oh school's going to be a waste it's so linear I can learn everything on YouTube and Google.com. All the stuff I learned in school I'm never going to use in the real world. So the question is, what skill should kids learn that could be applied to machine learning, thinking, the kind of constructs, data structures, or methodologies, what are some of the skills and classes that can tease out and be natural lead into computer science and machine learning A.I.? >> You know, actually their going to build up the skills. The languages will evolve and so forth. As long as they have that inner curiosity asking new questions, how can I find the answer a little faster, that will push them towards different sets of tools, different sets of areas. If you go to Berkeley in here, you will see a whole bunch of high school kids working side by side with graduate students asking those questions, developing those skill sets, but it's all coming down to their curiosity. >> And I think that applies for business too. I mean there's a big gap between the A.I. haves and have-nots I always say. And the good news here that my take away is, you're going to buy A.I, you're going to buy it from people like Google and you're going to build it and apply it, you're going to spend time applying it, and that's how these incumbents can close the gap and that's the good news here. >> Very true if you look at it, look at all the A.P.Is that we have. From text recognition to image recognition to whatever it is, those are all built models and I've seen some customers build some fantastic applications starting from there and they use their own data, bring it in, they update their model for their own businesses cases. >> It's composition it's composing. It's not coding it's composing. >> Exactly, it's composing. We are taking it to the next level. That abstraction is going to actually help others come into the field because they know their field of expertise, they can ask direct questions. You and I may not know it but, they will ask direct questions. And they will go with the tools available for them for the curiosity that they reach. >> Okay what's the coolest thing you're working on right now? >> Coolest thing, I just y'know streaming is my baby. We are working on, I want to solve all the streaming challenges, whatever the industry is. I really want to welcome everyone, bring you to us. I think, if I look at it, one of the things we discussed today was Antos was fantastic right? I mean we're really going to change the game for all enterprises to be able to provide those capabilities at the infrastructure. But imagine what we can do with all the data analytics capabilities we have on top of it. I think this is the next five years is going to be fantastic for us. >> What's the coolest use case thing you see emerging out of streaming? >> Ah you know, yesterday I actually had one of my clients with me onstage, AB Tasty. They had a fantastic capability that they built. They tried everything. And we were not their first choice, I'll be very open. They said the same thing to everybody, you guys were not our first choice. They went around, they looked at all the tool kits, everything. They came they used PostUp, they used data flow, they used engine, streaming engine. And they AB testing for marketing. And they do that at scale, billions of messages every minute, and they do it within seconds, milliseconds, 32 milliseconds at most. Because they have to make the decision. That was awesome, go check. I don't know if you're familiar with that. One of our customers, they provide these real time delivery. In India, imagine where things are. In global leaders, you can actually ask for a food to be delivered and they have to optimize, depending on what the traffic is and go with their scooters, and provide you this delivery. They aren't doing it as well. Okato, they believe, provide food in UK 70% of the population use our technologies for real time delivery. Those are some great examples. >> Evren, great insight, great to have you on. Just a final word here, next couple years, how do you see the trajectory of machine learning A.I. Analytics feeding into the value of making life easier society better, and businesses more productive? >> We are seeing really good pull from enterprises from every archival that you can think of. Regulated, retail, what have you. And we're going to solve some really hard problems whether it's in health care industry, financial industry, retail industry, we're going to make lives of people much easier. And their going to benefit from it at scale. And I believe we're just scratching the tip of it and you're seeing this energy in here. Year over year this has gotten better and better. I can't wait to see what's going to happen next year. >> Evren Eryurek great energy, expert at A.Is, streaming analytics, again this is early days of a brand new shift that's happening. You get on the right side of history it's A.I. machine learning, streaming analysts. Thanks for coming, I appreciate it. >> Thank you so much, take care guys. >> More live coverage here in theCUBE in San Francisco at Google next Cloud 2019. We'll be back after this short break.

(upbeat music) >> Narrator: Live from Vancouver, Canada, it's theCUBE covering OpenStack Summit North America, 2018, Brought to you by Red Hat, the OpenStack foundation, and its ecosystem partners. >> Welcome back, I'm Stew Miniman here with theCUBE's coverage of OpenStack Summit 2018 in Vancouver. My co-host is John Troyer. Happy to welcome to the program, we have Berna Devrim, who is the Senior Director of Product Marketing of Platform at Red Hat. And we are thrilled to have a customer on, Nico Wellner, who's a Unix Systems Engineer with Finanz Informatik out of Germany. Thank you both so much for joining. Alright, Berna let's start with you. Just give, your first time on the program I believe, so a little bit about your background. You've been with Red Hat less than a year so tell us your role there. >> Yeah, yeah I've been at Red Hat for nine, 10 months now. I've very very excited to be here in the Open Source community development model. It's a very unique opportunity, as I've been leading the platform's marketing, which includes Red Hat Enterprise Linux, as well as Red Hat Virtualization, and Red Hat OpenStack platform, of course, which is why we are here at OpenStack summit. >> Great. We've got Rhel, and RHV, and RHOSP, and lots of other "LMNOP's." So Nico, give us a little bit about your background. Tell us about your organization and then lets get into the mini case study we'll do with you. >> It's an honor for me to be here. Thank you very much for this. I working for Finanz Informatiks, as you said, and it's a centralized IT service provider in the S Finance Group in Germany, for savings banks and state banks. We always have about 400 institutes. Savings banks, individual savings banks. On our systems we are supporting more than 120 million accounts, bank accounts, nearly half of them online accounts. We also develop the software for the savings banks for our customers, not savings banks only. Also, assurances and state banks. We operate the applications we developed previously. It's a huge and amazing company with a lot of different groups and systems. >> Well, we're really glad you could make it here. With GDPR banging down the door in just a couple of days we expect everybody in Europe to be pretty busy getting ready for that. Tell us your role inside the organization. What's your team do? Your title has Unix in it, so what's that entail? Give us the scope of what you cover. >> I'm assistant engineer, as you said and I'm working in the department. We are integrating and operating the Unix systems, which are AIX, we have a huge AIX, and why-mite and a huge Lenox, and why-mite in our data centers. On these Lenox systems, we started with OpenStack in 2014, with testing, and went into production in 2015, half a year later. We integrated OpenStack. We operated and served for our customers internally on the OpenStack platform. We host one of our core applications, it's the internet banking for our customers, as I said for about 50 millions account. We have multiple OpenStack Clouds. My department is responsible for the clouds and for operating them well. >> Nico I wonder if we step back for a second and what led to you going down this path. Was the company figuring out its cloud strategy? Obviously financial institutions, we understand there's governance, compliance, security is a huge concern. What does Cloud mean to your team? What led you to OpenStack? Let's start with kind of that problem statement that you had. >> Yeah, it was the main reason we introduced OpenStack was the time to market was our applications, it was our environment. And it's a plummet process. Took a long time normally and the environment. With OpenStack we could dramatically increase the time to deploy the systems from days or weeks to minutes. So we solved one huge problem with OpenStack. What was another reason was vendor lock-in. We wanted to avoid vendor lock-in. So we decided for OpenStack because it's a huge open source software, great community, and very stable, in our case. So it's OpenStack for us. >> So Berna, I've actually had the opportunity to interview quite a few Red Hat customers. I remember three years ago we were actually in the other hallway here talking to FICO about their role out of Red Hat OpenStack. I hear some similar themes, but you've got access to way more customers than I do. What are you hearing from customers in general? Is this kind of the typical? Is speed and agility at the top of the list when it comes to their Cloud environment? >> Exactly Stew, just like Nico said, actually. Our customers tell us all the time that it is about speed and agility. But it's also about different types of use cases and the workloads that they're actually looking at in their environments. Very popular ones, the use cases are. For example, scale-out IS, as well as they have test environments for the clouds needs applications, for example. Also we do see that big data analytics, NFV also. So there are many different types of use cases we see from our customers. We also have been hearing that they are actually using Open Shift on top of the Red Hat OpenStack platform. Majority of them are either deploying it or planning to deploy containers. So we do see a lot of different, but similar, aspects as well. >> Yeah. Nico have you started to go down that path with containers, Kubernetes, all that stuff yet? >> Not so far. We plan to do so. In general will use containers, we are planning to. But we already started the process, but it would take a little bit. I'm saying that we're not sure if start with OpenStack, containers on OpenStack or plain, but I think that with OpenStack could be a great way to do so. Because one of the reasons is our OpenStack environment is very reliable. This is important for us, very important for us and our customers. Over the years, as I said, since 2015 we had no outage due to OpenStack and the whole environment is great for us. >> That's great. So where are you now in your Red Hat OpenStack deployment? You have an OpenStack in production and now you're already a Red Hat customer in other products and you're now going out with Red Hat OpenStack platform, is that correct? >> Yes that's correct, yeah. >> I'm kind of curious. One of the conversations around OpenStack is the component nature of it and that many OpenStack deployments are different. So as you're now deploying Red Hat and you were already on OpenStack, are the skills transferable? Do you find the the processes transferable? Do you feel that this was a good investment, no up time for three years now and now you're moving to this new platform. Do you and your team feel like you're able to properly instrument and maintain and operate it? >> I think it's the best platform for us for infrastructure and management, Lenix and why-mite. We want to in-wolf it furthermore. >> Stew: And the skills will still transfer? The skills you've known for years will still transfer to the new OpenStack? >> Yes we have only a few people working actively on the design and the architecture, and operating for OpenStack. It's turned out that we could do fine with them. Now we have huge experience with OpenStack, feel comfortable with it. We are planning to increase the OpenStack environment, slightly I think. But scale out works great for us. The OpenStack itself, in our case, we could very flexible do a systems releases, which is one important thing for us. I think the OpenStack itself is the best platform for us and our application tools. >> That's great. Berna I was at Red Hat Summit and the interesting thing there for me was the portfolio, the breadth of portfolio, right? One of the messages was clear. You've always depended on Red Hat Enterprise Lenix, and that's still there and containers are Lenix. There was lot of multi-cloud talk and stuff like that, and OpenStack was part of the mix. Can you talk a little bit about OpenStack as part of the Red Hat portfolio and what you all are bringing to the table, and how you're thinking of open shift on OpenStack and that sort of thing? >> Yeah, exactly. As you pointed out Red Hat is all about open hybrid cloud. Within that Red Hat OpenStack platform plays a big role, of course as you can imagine. What we are trying to do at OpenStack platform is to help our customers like Nico get towards the digital transformation. With that comes, again, the need for speed and agility. What we are enabling with OpenStack platform is we would like to call it powering the digital transformation through enabling our customers to accelerate their businesses by simplifying their applications and delivery as well as the services delivery, which then, of course, moves towards innovation, fast innovation at the speed of the business. At the same time, we are trying to enable IT teams to be empowered so that they can actually do the innovations at their own pace without worry, with all of the Red Hat portfolio, as you pointed out. Yeah. >> Nico, we'd love to hear your take on digital transformation. I think back, five years ago we were talking about financial institutions, oh well we need to go mobile. Well it's much more than that for most companies that I talk to. Do you consider a digital transformation in your company? How does that relate to what IT does to what the business does, to what your users need? >> It's one of our core tasks in our company to help our customers for digital transformation. Finanz Informatik itself sees itself to be the best partner for our customers to do this transformation. With leading technologies like OpenStack and a special case was Red Hat OpenStack, of course, which is a product which enables us to be flexible, secure, and fast with our environment, and to drive this process of digital transformation in the S Finance Group, Savings Finance Group. >> Alright, so you've been at this for three or four years now with OpenStack, I'd love to get what learnings you've had for peers of yours that might be earlier in their journey. What have you learned? What advice might you give them? Let's start there. >> Overall I would say the OpenStack environment is very reliable. More reliable as I thought at the beginning. But it's turned out it's really good. From the automation perspective it's a really nice, let's say tool, for our environment. I found OpenStack is a great project with a lot of software components you can combine. We have a flexible platform. We can add some components we do not have today, but are part of OpenStack community of OpenStack product at all, to enable additional functionalities to the environment, let's say for containers, for object solid, and something like that, and new services for our customers to decrease the time to market. >> Okay. One of the things that this show we're seeing is looking beyond where we've been. I think the keynote this word, people are asking to do more and in more places. Everything from containers, and edge, and server lists, and the like. What's interesting you these days as you look down the road? Different technologies that are in your roadmap in the future, inside or outside OpenStack? >> For our company, we are in the process to integrate new needs for our customers and we are planning to do a lot of big data. Maybe OpenStack could be part of the white platform forward for the future we are planning. I think it will be much more diverse in future because right now we do have one application running on it, one co-application. It's a co-application where we partnered for us. But we will maybe will spread it or enable it for other applications, because of the great experience we've made with it. >> Nico and Berna, thank you so much for giving us the updates on where you stand with OpenStack and all of your deployment. We'll be back here with lots more coverage here at OpenStack Summit 2018 in Vancouver for John Troyer. I'm Stew Miniman. Thanks for watching theCUBE. (techno music)

>> Narrator: Live, from Austin Texas it's the Cube. Covering DockerCon 2017. Brought to you by Docker and support from it's ecosystem partners. >> Hi, and welcome back to the Cube SiliconAngle Media's production of DockerCon 2017. I'm Stew Miniman, and joining me for the rap today I have Jim Kobilus who's been my host for the whole day, part of the Wikibon team. Jim, it's been a long day. Your first full day on the Cube, you've been on many times. >> It's been invigorating, I've learned so much. This is an awesomely substantial show. It's been wonderful. We've had so many great guests, oh my gosh. Ben Golub and everybody who came before. Amazing material. >> Stu: And my other guest for the wrap up is John Troyer who's been on the program many times. He sometimes guest host of the program so Chief Reckoner at TechReckoning. John, thanks for joining us. >> Hey, thanks so much for having me, Stu. >> Alright, so you know, we think right, guests we had some really good guests. It's easy for me at the end of the day when you're like oh it's energy flag oh let's have Ben Golub, the CEO of the company that where Docker's gone, and Jerry Chen who always brings energy, part of the V mafia like yourself, John so really interesting stuff. I want to step back, let's talk about the keynote. So I guess John, I'll start with you. Something we've been talking the last year or so is this Docker, Docker, Docker hype. I felt like a little bit of a hype was let out over the last year with the Docker data center, Docker swarm type activity, some of the ecosystem was a little frustrated with the direction that Docker the company was going, compared to where they wanted the open source part to do. Lot of open source, lot of developer talk today. What's your take on the announcements, the ecosystem, opensource? There's so many things, but let's get us started. >> Sure. Well I didn't quite know what to expect, Stu. We hear about Docker going more enterprise, they just made a big enterprise announcement, so I thought we might come in here and hear 45 minutes on digital transformation. And the standard enterprise keynote that you get at every other keynote. And we did not get that this morning. >> I've seen Michael Dell give that keynote in this building. (laughs) So, totally. >> At least we didn't get that here we've all heard that elsewhere. >> Well, at every conference for the last five years, I think. Ten years. So we talked about the ecosystem, that was the first message this morning. It was about growth of the ecosystem, about growth of the partnership, growth of the projects and so that was definitely playing to their strengths, and then they went straight to the code. This was a developer centered keynote, they did live demos with real code. And so they were really playing to the audience here which I think is still predominately developers. So they were signaling that hey, they weren't going all enterprise. Now, the announcements were also interesting. But I think the signal from the keynote was that we are still here, we're all about developer experience, we're about making things simple. >> Yeah, I don't think there's too many shows where you'd start off and they're like oh, here's how you can build really large containers, easier with this multi-part build and filling all this Docker stuff. It's not the suits, it's not the big customers. Having said, does that mean you won't go to tomorrow's keynote because Ben said it's going to be all the enterprise stuff tomorrow. >> I live for the enterprise stuff. I'm really excited about tomorrow. So hopefully, not too much digital transformation. But I think what Docker has announced the last month, not even talking about what happened today, but the Docker packaging, the Docker data, Docker enterprise edition versus consumer edition, and then not consumer, community addition, sorry. And then the tiers of the Docker, Docker enterprise edition, I think is really kind of brilliant. Docker is at a real turning point in its evolution right now. And there was a lot of confusion around what is Docker the project, what is Docker the engine, what is Docker the company, and I think with this kind of packaging, and then with the announcements today, I really think that they've just cleared up a whole lot of confusion in the ecosystem. >> Yeah, I mean coming in I think I heard a lot of people who were really excited that container D got open sourced. We went to, all three of us went to kubernetes event last night that was over at the Google Fiber Space a couple of blocks from here. And it was oh, cool I get all the opensource like Docker one, that stuff I need, but not all that upper level stuff and advanced things that Docker is building in to it so there's opensource pieces. That goes into the Moby project. Docker's committing, doubling down on a lot of this. We're going to take all these pieces. We're going to work on them, community's going to build it, they can take that compostable view of putting their solutions. And Docker will package and have monetization and things that they'll do there but the partner ecosystem can do different things with that. So what do you guys take on, let's just start with the Moby project first, some of these open source, the whole ecosystem. Positive, you think it's good? >> Yes, very much so. So the maturation of the container ecosystem is in the form of, what you see though the announcements, one of which is customization. So customize containers to the finest degree. They've got that capability now with Moby, exactly. It's all about containers everywhere. Containerization of applications is now the dominant theme in the developer community across all segments. So I think Docker has done the right thing which is doubling down on developers, doubling down on the message and the tooling now for both customization of containers but also for portability with the Linux kit announcement and so forth. Containerization, micro services and so forth across all segments. One of the areas I focus on is artificial intelligence, deep learning. Containerization is coming to that in a big way as well. A lot of it is to drive things like autonomous vehicles and drones and whatnot. But we're going to see containerization come to every other segment of data science, deep learning, machine learning and so forth. It's not just the people at this show, it's other developer communities that are coming to containerization in a big way. And Docker is becoming a premier development tool then for them. Or will be. >> So Jim, Stu, I think even more tactically, there was this confusion about Docker the engine, Docker the container run time, Docker the container specification. Now as pulling that out with container D and now with Linux kit, you always had the thing where Red Hat would say well we have open shift, it's like Docker or it has a piece of Docker or it can work with Docker, you have Cloud Foundry it's like Docker, or has a Docker, or can work with Docker now. And so everybody had to do this dance by saying well, we use some of the technology there. Now, very clean split, very different branding, we use Linux kit, we use container D, we use the Moby framework. And that actually will help again, look, the death of commercial success is confusion. If a buyer does not understand how to get what you want or what you're selling, he's never going to buy anything. >> Yeah, I think we've seen the end of Docker's well, batteries included but removable, cause some confusion in the marketplace. People are like well, but it's not easy, that's kind of what's there, I want to be able to choose the pieces up front. We talked about with Brian Gracely earlier today, what is the pinioned platform because there's certain solutions. Microsoft wants to build what they want. And they've lots of options, but when they want to build an upper level service, they have the pieces underneath that they care about. It's not like oh, okay wait. I have to do this, then I have to uninstall this, that was like in Linux all the time. It's like up, I'm recompiling, I'm recompiling, I have to add things in and remove them it's like no, no, no. I want it in box. In the kernel. And then I can choose and activate what I need. >> My guess is that next year, my prediction is that next year at DockerCon Docker will double down on experience, developer experience. There's not a enough of it yet, here. I think that will be a core theme for them going forward to continue to deepen their mind share in that community. >> I actually, I'll take that and double it. So, one of the reasons that, I think one of the factors, that caused VMWare to come to prominence was its operator experience and its simplicity. VMWare HA high availability was a one check box. VMWare distributed resource schedule which moved virtual machines around, one check box, right? And so with Docker's focus on developer usability and developer experience with today's announcements of Linux kit, that could actually be a huge, huge deal. If in the future, the application development pipeline greatly depends on building a just enough operating system as we used to say back in the day of VMWare with Jerry Chen. >> Stu: Yeah, good 'ol juice. >> Yeah, if that becomes the defining characteristic of building cloud native apps, and it is right? The Docker file is the defining document of our time. If that's the case, and now they've taken it into the Linux distribution world, which could have repercussions for the whole ecosystem, that could be Docker's, you know, again, their magic check box, the developer experience of rolling out a custom stack has just been the level has just been raised. And Linux kit is not new to the world. They just open sourced it today. But it's what they're using to get out their Docker for AWS and Docker for Google cloud. And Docker on public clouds already uses it so it's already in production today. I'm super impressed. >> And I think there was potential that it could have caused more confusion or upset in the ecosystem. But we interviewed Red Hat, and Canonical today and I'm not saying that jumped up and down and embraced and said oh goody, but it wasn't it was like okay, that's fine. It's not there, because there's always got to be that cooptive. I mean Jim, you came most recently from IBM. The company that I most associated with that word co-opetition. So, there's always, there's the swim lanes, there's where you partner together and there's where you sometimes bump heads as to strategy. >> Yeah. And I don't think people should be too alarmed, I mean from a technical level, right there's stuff that runs in containers, there's stuff that runs underneath containers. There's still a role for Ubuntu and there's still a role for Red Hat and there's still a role for CoreOS and Rancher. I don't know enough, I don't have enough of a crystal ball to say what we'll be talking about next year. It could actually have a fairly large dripple effect going out in our ecosystem. >> John, you've also, you've dug into with a couple of vendors here, what about the storage space? It's one we've been digging out of bed. There's still the general consensus is, we still have a little ways to go on the maturity and it's the furthest behind. Big surprise just like VMWare. We spent over a decade doing that. What's your take on storage? Any other comments on just the broad ecosystem, just what needs to work, be worked on and improved over time. >> I think storage is the next area that needs to be worked on. I think that's the next piece that we see as still a little bit fragmented. I've heard from many vendors here at the show that even from Docker itself, that the surprising thing is that containers are not just for cloud native apps. A lot of the enterprise journey, and I imagine we're going to hear about that in tomorrow's keynote, starts with containerizing your big legacy apps. >> Yeah, it's funny. I made a comment at the Google cloud event in San Francisco a month ago. I'm like, hey when did lift and shift all of a sudden become sexy? (laughs) It's of course nuanced on that, and we've had a few interviews Jim, where we've talked about look, there's initiatives that we want to do the cool app modernization and everything there but in the meantime, it is not a bimodal world. We're not going to leave our old stuff there and let it slowly have Larry the engineer keep an eye on it and sleep all the time. The whole world kind of needs to move forward, containers are part of the way to give us the bridge to the future if you will. >> Yeah, how do you containerize the legacy app the mainframe app for example, it's got a petabyte of data in its storage, I mean you just got to work through the data, I mean the deep data issues there, you know. >> Yeah, you can run Docker on a mainframe. I mean, I've done interviews on that. You work with those people, Jim. And it's one of those oh wait, okay, right. So there's pieces that'll be updated and people that are changed. John, you and I have talked. I remember early days of VMWare. It was let me take that horrible 10 year old application that's running on Windows NT which is going into life, and my hardware's going to die, let me shove it into VM and leave it there for another five, ten years. And it was like, please don't do that. >> Sometimes the real world intrudes. I think we are, part of this problem does get smoothed over or confused but we're talking about both on prem apps and public cloud apps. And that can get a little confusing because the storage issues, going back to storage, are a little different. Right? Especially in the public cloud, you've got issues of data locality, you've got issues of latency, even performance and so you see a number of vendors who are approaching it. It's very easy to connect the container to some sort of persistent volume. It is very hard to give something that its performance and is backed up and is, you know is going to be there. People have spent, the storage industry has spent decades on those problems. I don't think we're there yet in terms of the generic container that is floating either in public cloud or on prem. >> And they can handle the hybrid cloud, hybrid data clouds of which there are a myriad in terms of high public private zones within a distributed data architecture with varying degrees of velocity and variety. Managing all that data in a containerized environments with rich orchestration among them, to replication and streaming and so forth. >> You can do it, but it's not, it's cutting edge right now. >> Yeah, it's cutting edge. >> So, John last question I have to ask you is something near and dear to your heart. When you talk about careers and people that are doing, there's a lot of people here, people I used to see in the VMWare community that learning all the cool new stuff. Anything you see is Docker doing evangelism? Program the influencer program type thing? Are you seeing anything in the educational spaces from career space, what can you share? >> Sure, Docker is very rich in community it's kind of been the engine of their growth. They've long had a huge user group program, they have a campus program, they have a mentorship program, and they also have the Docker captains. The Docker captains started, oh I don't know, a year, a year and a half ago and is an advocacy program, I think there's 70 of them now, they work very closely with them. The come from all across the ecosystem which is kind of interesting. Everybody from Dehli MC and many companies. So that's pretty cool that these people, it feels a lot like early days of VMWare, these people have day jobs but yet they spend their nights and weekends hacking on Docker. And Docker takes advantage of that, I mean in the best sort of way. They give them opportunities, they give them platforms to speak, they give them platforms to help others. And I see that's in full force here. They have a track here at the show, so Dockers are leaning heavily on its community. I even saw one person here, Stu from from a mainline storage company said you know what, my company's not here but I am because I have to learn how to do this. I think people who are here have a good next phase of their career. >> That's a smart. A community advocacy program of that sort is actually is even more important than an event like this in terms of deepening the loyalty of the developers to leverage providers and their growing stacks. >> John: Docker the company is very small. There's a very large community and a very small company. >> Stu: Three hundred and some odd people. >> They have to leverage those resources. >> John: Exactly. >> Well, Jim thanks for all your help co-hosting today, John, really appreciate you coming in, especially some of that community ecosystem expertise that you bring. By the way, John's going to be co-hosting open stack summit with me. Another one that will have lost (mumbles) where that ecosystem community is and where it's going in a couple of weeks in my home state of Massachusetts in Boston. So be sure to tune in tomorrow, we've got a full day of coverage. First guest is going to be Solomon Hykes coming off the day two keynote. We're going to talk a little bit more about enterprise. We got a full lineup of guests. So be sure to check out siliconangle.tv for everything there. So for Jim Kobielus, John Troyer and myself Stu Miniman, thank you for watching day one of the Cube's coverage of DockerCon 2017. (upbeat music)