[Music] [Music] [Music] [Laughter] [Laughter] [Laughter] [Laughter] [Music] [Music] [Music] [Music] you you [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Applause] [Music] wake up feeling blessed peace you warned that Russia ain't afraid to show it I'll expose it if I dressed up riding in that Chester roasted nigga catch you slippin on myself rocks on I messed up like yes sir [Music] [Music] [Music] [Music] our program [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] you are not welcome to Red Hat summit 2018 2018 [Music] [Music] [Music] [Laughter] [Music] Wow that is truly the coolest introduction I've ever had thank you Wow I don't think I feel cool enough to follow an interaction like that Wow well welcome to the Red Hat summit this is our 14th annual event and I have to say looking out over this audience Wow it's great to see so many people here joining us this is by far our largest summit to date not only did we blow through the numbers we've had in the past we blew through our own expectations this year so I know we have a pretty packed house and I know people are still coming in so it's great to see so many people here it's great to see so many familiar faces when I had a chance to walk around earlier it's great to see so many new people here joining us for the first time I think the record attendance is an indication that more and more enterprises around the world are seeing the power of open source to help them with their challenges that they're facing due to the digital transformation that all of enterprises around the world are going through the theme for the summit this year is ideas worth exploring and we intentionally chose that because as much as we are all going through this digital disruption and the challenges associated with it one thing I think is becoming clear no one person and certainly no one company has the answers to these challenges right this isn't a problem where you can go buy a solution this is a set of capabilities that we all need to build it's a set of cultural changes that we all need to go through and that's going to require the best ideas coming from so many different places so we're not here saying we have the answers we're trying to convene the conversation right we want to serve as a catalyst bringing great minds together to share ideas so we all walk out of here at the end of the week a little wiser than when we first came here we do have an amazing agenda for you we have over 7,000 attendees we may be pushing 8,000 by the time we got through this morning we have 36 keynote speakers and we have a hundred and twenty-five breakout sessions and have to throw in one plug scheduling 325 breakout sessions is actually pretty difficult and so we used the Red Hat business optimizer which is an AI constraint solver that's new in the Red Hat decision manager to help us plan the summit because we have individuals who have a clustered set of interests and we want to make sure that when we schedule two breakout sessions we do it in a way that we don't have overlapping sessions that are really important to the same individual so we tried to use this tool and what we understand about people's interest in history of what they wanted to do to try to make sure that we spaced out different times for things of similar interests for similar people as well as for people who stood in the back of breakouts before and I know I've done that too we've also used it to try to optimize room size so hopefully we will do our best to make sure that we've appropriately sized the spaces for those as well so it's really a phenomenal tool and I know it's helped us a lot this year in addition to the 325 breakouts we have a lot of our customers on stage during the main sessions and so you'll see demos you'll hear from partners you'll hear stories from so many of our customers not on our point of view of how to use these technologies but their point of views of how they actually are using these technologies to solve their problems and you'll hear over and over again from those keynotes that it's not just about the technology it's about how people are changing how people are working to innovate to solve those problems and while we're on the subject of people I'd like to take a moment to recognize the Red Hat certified professional of the year this is known award we do every year I love this award because it truly recognizes an individual for outstanding innovation for outstanding ideas for truly standing out in how they're able to help their organization with Red Hat technologies Red Hat certifications help system administrators application developers IT architects to further their careers and help their organizations by being able to advance their skills and knowledge of Red Hat products and this year's winner really truly is a great example about how their curiosity is helped push the limits of what's possible with technology let's hear a little more about this year's winner when I was studying at the University I had computer science as one of my subjects and that's what created the passion from the very beginning they were quite a few institutions around my University who were offering Red Hat Enterprise Linux as a course and a certification paths through to become an administrator Red Hat Learning subscription has offered me a lot more than any other trainings that have done so far that gave me exposure to so many products under red hair technologies that I wasn't even aware of I started to think about the better ways of how these learnings can be put into the real life use cases and we started off with a discussion with my manager saying I have to try this product and I really want to see how it really fits in our environment and that product was Red Hat virtualization we went from deploying rave and then OpenStack and then the open shift environment we wanted to overcome some of the things that we saw as challenges to the speed and rapidity of release and code etc so it made perfect sense and we were able to do it in a really short space of time so you know we truly did use it as an Innovation Lab I think idea is everything ideas can change the way you see things an Innovation Lab was such an idea that popped into my mind one fine day and it has transformed the way we think as a team and it's given that playpen to pretty much everyone to go and test their things investigate evaluate do whatever they like in a non-critical non production environment I recruited Neha almost 10 years ago now I could see there was a spark a potential with it and you know she had a real Drive a real passion and you know here we are nearly ten years later I'm Neha Sandow I am a Red Hat certified engineer all right well everyone please walk into the states to the stage Neha [Music] [Applause] congratulations thank you [Applause] I think that - well welcome to the red has some of this is your first summit yes it is thanks so much well fantastic sure well it's great to have you here I hope you have a chance to engage and share some of your ideas and enjoy the week thank you thank you congratulations [Applause] neha mentioned that she first got interest in open source at university and it made me think red hats recently started our Red Hat Academy program that looks to programmatically infuse Red Hat technologies in universities around the world it's exploded in a way we had no idea it's grown just incredibly rapidly which i think shows the interest that there really is an open source and working in an open way at university so it's really a phenomenal program I'm also excited to announce that we're launching our newest open source story this year at Summit it's called the science of collective discovery and it looks at what happens when communities use open hardware to monitor the environment around them and really how they can make impactful change based on that technologies the rural premier that will be at 5:15 on Wednesday at McMaster Oni West and so please join us for a drink and we'll also have a number of the experts featured in that and you can have a conversation with them as well so with that let's officially start the show please welcome red hat president of products and technology Paul Cormier [Music] Wow morning you know I say it every year I'm gonna say it again I know I repeat myself it's just amazing we are so proud here to be here today too while you all week on how far we've come with opens with open source and with the products that we that we provide at Red Hat so so welcome and I hope the pride shows through so you know I told you Seven Summits ago on this stage that the future would be open and here we are just seven years later this is the 14th summit but just seven years later after that and much has happened and I think you'll see today and this week that that prediction that the world would be open was a pretty safe predict prediction but I want to take you just back a little bit to see how we started here and it's not just how Red Hat started here this is an open source in Linux based computing is now in an industry norm and I think that's what you'll you'll see in here this week you know we talked back then seven years ago when we put on our prediction about the UNIX error and how Hardware innovation with x86 was it was really the first step in a new era of open innovation you know companies like Sun Deck IBM and HP they really changed the world the computing industry with their UNIX models it was that was really the rise of computing but I think what we we really saw then was that single company innovation could only scale so far could really get so far with that these companies were very very innovative but they coupled hardware innovation with software innovation and as one company they could only solve so many problems and even which comp which even complicated things more they could only hire so many people in each of their companies Intel came on the scene back then as the new independent hardware player and you know that was really the beginning of the drive for horizontal computing power and computing this opened up a brand new vehicle for hardware innovation a new hardware ecosystem was built around this around this common hardware base shortly after that Stallman and leanness they had a vision of his of an open model that was created and they created Linux but it was built around Intel this was really the beginning of having a software based platform that could also drive innovation this kind of was the beginning of the changing of the world here that system-level innovation now having a hardware platform that was ubiquitous and a software platform that was open and ubiquitous it really changed this system level innovation and that continues to thrive today it was only possible because it was open this could not have happened in a closed environment it allowed the best ideas from anywhere from all over to come in in win only because it was the best idea that's what drove the rate of innovation at the pace you're seeing today and it which has never been seen before we at Red Hat we saw the need to bring this innovation to solve real-world problems in the enterprise and I think that's going to be the theme of the show today you're going to see us with our customers and partners talking about and showing you some of those real-world problems that we are sought solving with this open innovation we created rel back then for this for the enterprise it started it's it it wasn't successful because it's scaled it was secure and it was enterprise ready it once again changed the industry but this time through open innovation this gave the hardware ecosystem a software platform this open software platform gave the hardware ecosystem a software platform to build around it Unleashed them the hardware side to compete and thrive it enabled innovation from the OEMs new players building cheaper faster servers even new architectures from armed to power sprung up with this change we have seen an incredible amount of hardware innovation over the last 15 years that same innovation happened on the software side we saw powerful implementations of bare metal Linux distributions out in the market in fact at one point there were 300 there are over 300 distributions out in the market on the foundation of Linux powerful open-source equivalents were even developed in every area of Technology databases middleware messaging containers anything you could imagine innovation just exploded around the Linux platform in innovation it's at the core also drove virtualization both Linux and virtualization led to another area of innovation which you're hearing a lot about now public cloud innovation this innovation started to proceed at a rate that we had never seen before we had never experienced this in the past in this unprecedented speed of innovation and software was now possible because you didn't need a chip foundry in order to innovate you just needed great ideas in the open platform that was out there customers seeing this innovation in the public cloud sparked it sparked their desire to build their own linux based cloud platforms and customers are now are now bringing that cloud efficiency on-premise in their own data centers public clouds demonstrated so much efficiency the data centers and architects wanted to take advantage of it off premise on premise I'm sorry within their own we don't within their own controlled environments this really allowed companies to make the most of existing investments from data centers to hardware they also gained many new advantages from data sovereignty to new flexible agile approaches I want to bring Burr and his team up here to take a look at what building out an on-premise cloud can look like today Bure take it away I am super excited to be with all of you here at Red Hat summit I know we have some amazing things to show you throughout the week but before we dive into this demonstration I want you to take just a few seconds just a quick moment to think about that really important event your life that moment you turned on your first computer maybe it was a trs-80 listen Claire and Atari I even had an 83 b2 at one point but in my specific case I was sitting in a classroom in Hawaii and I could see all the way from Diamond Head to Pearl Harbor so just keep that in mind and I turn on an IBM PC with dual floppies I don't remember issuing my first commands writing my first level of code and I was totally hooked it was like a magical moment and I've been hooked on computers for the last 30 years so I want you to hold that image in your mind for just a moment just a second while we show you the computers we have here on stage let me turn this over to Jay fair and Dini here's our worldwide DevOps manager and he was going to show us his hardware what do you got Jay thank you BER good morning everyone and welcome to Red Hat summit we have so many cool things to show you this week I am so happy to be here and you know my favorite thing about red hat summit is our allowed to kind of share all of our stories much like bird just did we also love to you know talk about the hardware and the technology that we brought with us in fact it's become a bit of a competition so this year we said you know let's win this thing and we actually I think we might have won we brought a cloud with us so right now this is a private cloud for throughout the course of the week we're going to turn this into a very very interesting open hybrid cloud right before your eyes so everything you see here will be real and happening right on this thing right behind me here so thanks for our four incredible partners IBM Dell HP and super micro we've built a very vendor heterogeneous cloud here extra special thanks to IBM because they loaned us a power nine machine so now we actually have multiple architectures in this cloud so as you know one of the greatest benefits to running Red Hat technology is that we run on just about everything and you know I can't stress enough how powerful that is how cost-effective that is and it just makes my life easier to be honest so if you're interested the people that built this actual rack right here gonna be hanging out in the customer success zone this whole week it's on the second floor the lobby there and they'd be glad to show you exactly how they built this thing so let me show you what we actually have in this rack so contained in this rack we have 1056 physical chorus right here we have five and a half terabytes of RAM and just in case we threw 50 terabytes of storage in this thing so burr that's about two million times more powerful than that first machine you boot it up thanks to a PC we're actually capable of putting all the power needs and cooling right in this rack so there's your data center right there you know it occurred to me last night that I can actually pull the power cord on this thing and kick it up a notch we could have the world's first mobile portable hybrid cloud so I'm gonna go ahead and unplug no no no no no seriously it's not unplug the thing we got it working now well Berg gets a little nervous but next year we're rolling this thing around okay okay so to recap multiple vendors check multiple architectures check multiple public clouds plug right into this thing check and everything everywhere is running the same software from Red Hat so that is a giant check so burn Angus why don't we get the demos rolling awesome so we have totally we have some amazing hardware amazing computers on this stage but now we need to light it up and we have Angus Thomas who represents our OpenStack engineering team and he's going to show us what we can do with this awesome hardware Angus thank you Beth so this was an impressive rack of hardware to Joe has bought a pocket stage what I want to talk about today is putting it to work with OpenStack platform director we're going to turn it from a lot of potential into a flexible scalable private cloud we've been using director for a while now to take care of managing hardware and orchestrating the deployment of OpenStack what's new is that we're bringing the same capabilities for on-premise manager the deployment of OpenShift director deploying OpenShift in this way is the best of both worlds it's bare-metal performance but with an underlying infrastructure as a service that can take care of deploying in new instances and scaling out and a lot of the things that we expect from a cloud provider director is running on a virtual machine on Red Hat virtualization at the top of the rack and it's going to bring everything else under control what you can see on the screen right now is the director UI and as you see some of the hardware in the rack is already being managed at the top level we have information about the number of cores in the amount of RAM and the disks that each machine have if we dig in a bit there's information about MAC addresses and IPs and the management interface the BIOS kernel version dig a little deeper and there is information about the hard disks all of this is important because we want to be able to make sure that we put in workloads exactly where we want them Jay could you please power on the two new machines at the top of the rack sure all right thank you so when those two machines come up on the network director is going to see them see that they're new and not already under management and is it immediately going to go into the hardware inspection that populates this database and gets them ready for use so we also have profiles as you can see here profiles are the way that we match the hardware in a machine to the kind of workload that it's suited to this is how we make sure that machines that have all the discs run Seth and machines that have all the RAM when our application workouts for example there's two ways these can be set when you're dealing with a rack like this you could go in an individually tag each machine but director scales up to data centers so we have a rules matching engine which will automatically take the hardware profile of a new machine and make sure it gets tagged in exactly the right way so we can automatically discover new machines on the network and we can automatically match them to a profile that's how we streamline and scale up operations now I want to talk about deploying the software we have a set of validations we've learned over time about the Miss configurations in the underlying infrastructure which can cause the deployment of a multi node distributed application like OpenStack or OpenShift to fail if you have the wrong VLAN tags on a switch port or DHCP isn't running where it should be for example you can get into a situation which is really hard to debug a lot of our validations actually run before the deployment they look at what you're intending to deploy and they check in the environment is the way that it should be and they'll preempts problems and obviously preemption is a lot better than debugging something new that you probably have not seen before is director managing multiple deployments of different things side by side before we came out on stage we also deployed OpenStack on this rack just to keep me honest let me jump over to OpenStack very quickly a lot of our opens that customers will be familiar with this UI and the bare metal deployment of OpenStack on our rack is actually running a set of virtual machines which is running Gluster you're going to see that put to work later on during the summit Jay's gone to an awful lot effort to get this Hardware up on the stage so we're going to use it as many different ways as we can okay let's deploy OpenShift if I switch over to the deployed a deployment plan view there's a few steps first thing you need to do is make sure we have the hardware I already talked about how director manages hardware it's smart enough to make sure that it's not going to attempt to deploy into machines they're already in use it's only going to deploy on machines that have the right profile but I think with the rack that we have here we've got enough next thing is the deployment configuration this is where you get to customize exactly what's going to be deployed to make sure that it really matches your environment if they're external IPs for additional services you can set them here whatever it takes to make sure that the deployment is going to work for you as you can see on the screen we have a set of options around enable TLS for encryption network traffic if I dig a little deeper there are options around enabling ipv6 and network isolation so that different classes of traffic there are over different physical NICs okay then then we have roles now roles this is essentially about the software that's going to be put on each machine director comes with a set of roles for a lot of the software that RedHat supports and you can just use those or you can modify them a little bit if you need to add a monitoring agent or whatever it might be or you can create your own custom roles director has quite a rich syntax for custom role definition and custom Network topologies whatever it is you need in order to make it work in your environment so the rawls that we have right now are going to give us a working instance of openshift if I go ahead and click through the validations are all looking green so right now I can click the button start to the deploy and you will see things lighting up on the rack directors going to use IPMI to reboot the machines provisioned and with a trail image was the containers on them and start up the application stack okay so one last thing once the deployment is done you're going to want to keep director around director has a lot of capabilities around what we call de to operational management bringing in new Hardware scaling out deployments dealing with updates and critically doing upgrades as well so having said all of that it is time for me to switch over to an instance of openshift deployed by a director running on bare metal on our rack and I need to hand this over to our developer team so they can show what they can do it thank you that is so awesome Angus so what you've seen now is going from bare metal to the ultimate private cloud with OpenStack director make an open shift ready for our developers to build their next generation applications thank you so much guys that was totally awesome I love what you guys showed there now I have the honor now I have the honor of introducing a very special guest one of our earliest OpenShift customers who understands the necessity of the private cloud inside their organization and more importantly they're fundamentally redefining their industry please extend a warm welcome to deep mar Foster from Amadeus well good morning everyone a big thank you for having armadillos here and myself so as it was just set I'm at Mario's well first of all we are a large IT provider in the travel industry so serving essentially Airlines hotel chains this distributors like Expedia and others we indeed we started very early what was OpenShift like a bit more than three years ago and we jumped on it when when Retta teamed with Google to bring in kubernetes into this so let me quickly share a few figures about our Mario's to give you like a sense of what we are doing and the scale of our operations so some of our key KPIs one of our key metrics is what what we call passenger borders so that's the number of customers that physically board a plane over the year so through our systems it's roughly 1.6 billion people checking in taking the aircrafts on under the Amarillo systems close to 600 million travel agency bookings virtually all airlines are on the system and one figure I want to stress out a little bit is this one trillion availability requests per day that's when I read this figure my mind boggles a little bit so this means in continuous throughput more than 10 million hits per second so of course these are not traditional database transactions it's it's it's highly cached in memory and these applications are running over like more than 100,000 course so it's it's it's really big stuff so today I want to give some concrete feedback what we are doing so I have chosen two applications products of our Mario's that are currently running on production in different in different hosting environments as the theme here is of this talk hybrid cloud and so I want to give some some concrete feedback of how we architect the applications and of course it stays relatively high level so here I have taken one of our applications that is used in the hospitality environment so it's we have built this for a very large US hotel chain and it's currently in in full swing brought into production so like 30 percent of the globe or 5,000 plus hotels are on this platform not so here you can see that we use as the path of course on openshift on that's that's the most central piece of our hybrid cloud strategy on the database side we use Oracle and Couchbase Couchbase is used for the heavy duty fast access more key value store but also to replicate data across two data centers in this case it's running over to US based data centers east and west coast topology that are fit so run by Mario's that are fit with VMware on for the virtualization OpenStack on top of it and then open shift to host and welcome the applications on the right hand side you you see the kind of tools if you want to call them tools that we use these are the principal ones of course the real picture is much more complex but in essence we use terraform to map to the api's of the underlying infrastructure so they are obviously there are differences when you run on OpenStack or the Google compute engine or AWS Azure so some some tweaking is needed we use right at ansible a lot we also use puppet so you can see these are really the big the big pieces of of this sense installation and if we look to the to the topology again very high high level so these two locations basically map the data centers of our customers so they are in close proximity because the response time and the SLA is of this application is are very tight so that's an example of an application that is architectures mostly was high ability and high availability in minds not necessarily full global worldwide scaling but of course it could be scaled but here the idea is that we can swing from one data center to the unit to the other in matters of of minutes both take traffic data is fully synchronized across those data centers and while the switch back and forth is very fast the second example I have taken is what we call the shopping box this is when people go to kayak or Expedia and they're getting inspired where they want to travel to this is really the piece that shoots most of transit of the transactions into our Mario's so we architect here more for high scalability of course availability is also a key but here scaling and geographical spread is very important so in short it runs partially on-premise in our Amarillo Stata Center again on OpenStack and we we deploy it mostly in the first step on the Google compute engine and currently as we speak on Amazon on AWS and we work also together with Retta to qualify the whole show on Microsoft Azure here in this application it's it's the same building blocks there is a large swimming aspect to it so we bring Kafka into this working with records and another partner to bring Kafka on their open shift because at the end we want to use open shift to administrate the whole show so over time also databases and the topology here when you look to the physical deployment topology while it's very classical we use the the regions and the availability zone concept so this application is spread over three principal continental regions and so it's again it's a high-level view with different availability zones and in each of those availability zones we take a hit of several 10,000 transactions so that was it really in very short just to give you a glimpse on how we implement hybrid clouds I think that's the way forward it gives us a lot of freedom and it allows us to to discuss in a much more educated way with our customers that sometimes have already deals in place with one cloud provider or another so for us it's a lot of value to set two to leave them the choice basically what up that was a very quick overview of what we are doing we were together with records are based on open shift essentially here and more and more OpenStack coming into the picture hope you found this interesting thanks a lot and have a nice summer [Applause] thank you so much deeper great great solution we've worked with deep Marv and his team for a long for a long time great solution so I want to take us back a little bit I want to circle back I sort of ended talking a little bit about the public cloud so let's circle back there you know even so even though some applications need to run in various footprints on premise there's still great gains to be had that for running certain applications in the public cloud a public cloud will be as impactful to to the industry as as UNIX era was of computing was but by itself it'll have some of the same limitations and challenges that that model had today there's tremendous cloud innovation happening in the public cloud it's being driven by a handful of massive companies and much like the innovation that sundeck HP and others drove in a you in the UNIX era of community of computing many customers want to take advantage of the best innovation no matter where it comes from buddy but as they even eventually saw in the UNIX era they can't afford the best innovation at the cost of a siloed operating environment with the open community we are building a hybrid application platform that can give you access to the best innovation no matter which vendor or which cloud that it comes from letting public cloud providers innovate and services beyond what customers or anyone can one provider can do on their own such as large scale learning machine learning or artificial intelligence built on the data that's unique probably to that to that one cloud but consumed in a common way for the end customer across all applications in any environment on any footprint in in their overall IT infrastructure this is exactly what rel brought brought to our customers in the UNIX era of computing that consistency across any of those footprints obviously enterprises will have applications for all different uses some will live on premise some in the cloud hybrid cloud is the only practical way forward I think you've been hearing that from us for a long time it is the only practical way forward and it'll be as impactful as anything we've ever seen before I want to bring Byrne his team back to see a hybrid cloud deployment in action burr [Music] all right earlier you saw what we did with taking bare metal and lighting it up with OpenStack director and making it openshift ready for developers to build their next generation applications now we want to show you when those next turn and generation applications and what we've done is we take an open shift and spread it out and installed it across Asia and Amazon a true hybrid cloud so with me on stage today as Ted who's gonna walk us through an application and Brent Midwood who's our DevOps engineer who's gonna be making sure he's monitoring on the backside that we do make sure we do a good job so at this point Ted what have you got for us Thank You BER and good morning everybody this morning we are running on the stage in our private cloud an application that's providing its providing fraud detection detect serves for financial transactions and our customer base is rather large and we occasionally take extended bursts of traffic of heavy traffic load so in order to keep our latency down and keep our customers happy we've deployed extra service capacity in the public cloud so we have capacity with Microsoft Azure in Texas and with Amazon Web Services in Ohio so we use open chip container platform on all three locations because openshift makes it easy for us to deploy our containerized services wherever we want to put them but the question still remains how do we establish seamless communication across our entire enterprise and more importantly how do we balance the workload across these three locations in such a way that we efficiently use our resources and that we give our customers the best possible experience so this is where Red Hat amq interconnect comes in as you can see we've deployed a MQ interconnect alongside our fraud detection applications in all three locations and if I switch to the MQ console we'll see the topology of the app of the network that we've created here so the router inside the on stage here has made connections outbound to the public routers and AWS and Azure these connections are secured using mutual TLS authentication and encrypt and once these connections are established amq figures out the best way auda matically to route traffic to where it needs to get to so what we have right now is a distributed reliable broker list message bus that expands our entire enterprise now if you want to learn more about this make sure that you catch the a MQ breakout tomorrow at 11:45 with Jack Britton and David Ingham let's have a look at the message flow and we'll dive in and isolate the fraud detection API that we're interested in and what we see is that all the traffic is being handled in the private cloud that's what we expect because our latencies are low and they're acceptable but now if we take a little bit of a burst of increased traffic we're gonna see that an EQ is going to push a little a bi traffic out onto the out to the public cloud so as you're picking up some of the load now to keep the Layton sees down now when that subsides as your finishes up what it's doing and goes back offline now if we take a much bigger load increase you'll see two things first of all asher is going to take a bigger proportion than it did before and Amazon Web Services is going to get thrown into the fray as well now AWS is actually doing less work than I expected it to do I expected a little bit of bigger a slice there but this is a interesting illustration of what's going on for load balancing mq load balancing is sending requests to the services that have the lowest backlog and in order to keep the Layton sees as steady as possible so AWS is probably running slowly for some reason and that's causing a and Q to push less traffic its way now the other thing you're going to notice if you look carefully this graph fluctuate slightly and those fluctuations are caused by all the variances in the network we have the cloud on stage and we have clouds in in the various places across the country there's a lot of equipment locked layers of virtualization and networking in between and we're reacting in real-time to the reality on the digital street so BER what's the story with a to be less I noticed there's a problem right here right now we seem to have a little bit performance issue so guys I noticed that as well and a little bit ago I actually got an alert from red ahead of insights letting us know that there might be some potential optimizations we could make to our environment so let's take a look at insights so here's the Red Hat insights interface you can see our three OpenShift deployments so we have the set up here on stage in San Francisco we have our Azure deployment in Texas and we also have our AWS deployment in Ohio and insights is highlighting that that deployment in Ohio may have some issues that need some attention so Red Hat insights collects anonymized data from manage systems across our customer environment and that gives us visibility into things like vulnerabilities compliance configuration assessment and of course Red Hat subscription consumption all of this is presented in a SAS offering so it's really really easy to use it requires minimal infrastructure upfront and it provides an immediate return on investment what insights is showing us here is that we have some potential issues on the configuration side that may need some attention from this view I actually get a look at all the systems in our inventory including instances and containers and you can see here on the left that insights is highlighting one of those instances as needing some potential attention it might be a candidate for optimization this might be related to the issues that you were seeing just a minute ago insights uses machine learning and AI techniques to analyze all collected data so we combine collected data from not only the system's configuration but also with other systems from across the Red Hat customer base this allows us to compare ourselves to how we're doing across the entire set of industries including our own vertical in this case the financial services industry and we can compare ourselves to other customers we also get access to tailored recommendations that let us know what we can do to optimize our systems so in this particular case we're actually detecting an issue here where we are an outlier so our configuration has been compared to other configurations across the customer base and in this particular instance in this security group were misconfigured and so insights actually gives us the steps that we need to use to remediate the situation and the really neat thing here is that we actually get access to a custom ansible playbook so if we want to automate that type of a remediation we can use this inside of Red Hat ansible tower Red Hat satellite Red Hat cloud forms it's really really powerful the other thing here is that we can actually apply these recommendations right from within the Red Hat insights interface so with just a few clicks I can select all the recommendations that insights is making and using that built-in ansible automation I can apply those recommendations really really quickly across a variety of systems this type of intelligent automation is really cool it's really fast and powerful so really quickly here we're going to see the impact of those changes and so we can tell that we're doing a little better than we were a few minutes ago when compared across the customer base as well as within the financial industry and if we go back and look at the map we should see that our AWS employment in Ohio is in a much better state than it was just a few minutes ago so I'm wondering Ted if this had any effect and might be helping with some of the issues that you were seeing let's take a look looks like went green now let's see what it looks like over here yeah doesn't look like the configuration is taking effect quite yet maybe there's some delay awesome fantastic the man yeah so now we're load balancing across the three clouds very much fantastic well I have two minute Ted I truly love how we can route requests and dynamically load transactions across these three clouds a truly hybrid cloud native application you guys saw here on on stage for the first time and it's a fully portable application if you build your applications with openshift you can mover from cloud to cloud to cloud on stage private all the way out to the public said it's totally awesome we also have the application being fully managed by Red Hat insights I love having that intelligence watching over us and ensuring that we're doing everything correctly that is fundamentally awesome thank you so much for that well we actually have more to show you but you're going to wait a few minutes longer right now we'd like to welcome Paul back to the stage and we have a very special early Red Hat customer an Innovation Award winner from 2010 who's been going boldly forward with their open hybrid cloud strategy please give a warm welcome to Monty Finkelstein from Citigroup [Music] [Music] hi Marty hey Paul nice to see you thank you very much for coming so thank you for having me Oh our pleasure if you if you wanted to we sort of wanted to pick your brain a little bit about your experiences and sort of leading leading the charge in computing here so we're all talking about hybrid cloud how has the hybrid cloud strategy influenced where you are today in your computing environment so you know when we see the variable the various types of workload that we had an hour on from cloud we see the peaks we see the valleys we see the demand on the environment that we have we really determined that we have to have a much more elastic more scalable capability so we can burst and stretch our environments to multiple cloud providers these capabilities have now been proven at City and of course we consider what the data risk is as well as any regulatory requirement so how do you how do you tackle the complexity of multiple cloud environments so every cloud provider has its own unique set of capabilities they have they're own api's distributions value-added services we wanted to make sure that we could arbitrate between the different cloud providers maintain all source code and orchestration capabilities on Prem to drive those capabilities from within our platforms this requires controlling the entitlements in a cohesive fashion across our on Prem and Wolfram both for security services automation telemetry as one seamless unit can you talk a bit about how you decide when you to use your own on-premise infrastructure versus cloud resources sure so there are multiple dimensions that we take into account right so the first dimension we talk about the risk so low risk - high risk and and really that's about the data classification of the environment we're talking about so whether it's public or internal which would be considered low - ooh confidential PII restricted sensitive and so on and above which is really what would be considered a high-risk the second dimension would be would focus on demand volatility and responsiveness sensitivity so this would range from low response sensitivity and low variability of the type of workload that we have to the high response sensitivity and high variability of the workload the first combination that we focused on is the low risk and high variability and high sensitivity for response type workload of course any of the workloads we ensure that we're regulatory compliant as well as we achieve customer benefits with within this environment so how can we give developers greater control of their their infrastructure environments and still help operations maintain that consistency in compliance so the main driver is really to use the public cloud is scale speed and increased developer efficiencies as well as reducing cost as well as risk this would mean providing develop workspaces and multiple environments for our developers to quickly create products for our customers all this is done of course in a DevOps model while maintaining the source and artifacts registry on-prem this would allow our developers to test and select various middleware products another product but also ensure all the compliance activities in a centrally controlled repository so we really really appreciate you coming by and sharing that with us today Monte thank you so much for coming to the red echo thanks a lot thanks again tamati I mean you know there's these real world insight into how our products and technologies are really running the businesses today that's that's just the most exciting part so thank thanks thanks again mati no even it with as much progress as you've seen demonstrated here and you're going to continue to see all week long we're far from done so I want to just take us a little bit into the path forward and where we we go today we've talked about this a lot innovation today is driven by open source development I don't think there's any question about that certainly not in this room and even across the industry as a whole that's a long way that we've come from when we started our first summit 14 years ago with over a million open source projects out there this unit this innovation aggregates into various community platforms and it finally culminates in commercial open source based open source developed products these products run many of the mission-critical applications in business today you've heard just a couple of those today here on stage but it's everywhere it's running the world today but to make customers successful with that interact innovation to run their real-world business applications these open source products have to be able to leverage increase increasingly complex infrastructure footprints we must also ensure a common base for the developer and ultimately the application no matter which footprint they choose as you heard mati say the developers want choice here no matter which no matter which footprint they are ultimately going to run their those applications on they want that flexibility from the data center to possibly any public cloud out there in regardless of whether that application was built yesterday or has been running the business for the last 10 years and was built on 10-year old technology this is the flexibility that developers require today but what does different infrastructure we may require different pieces of the technical stack in that deployment one example of this that Effects of many things as KVM which provides the foundation for many of those use cases that require virtualization KVM offers a level of consistency from a technical perspective but rel extends that consistency to add a level of commercial and ecosystem consistency for the application across all those footprints this is very important in the enterprise but while rel and KVM formed the foundation other technologies are needed to really satisfy the functions on these different footprints traditional virtualization has requirements that are satisfied by projects like overt and products like Rev traditional traditional private cloud implementations has requirements that are satisfied on projects like OpenStack and products like Red Hat OpenStack platform and as applications begin to become more container based we are seeing many requirements driven driven natively into containers the same Linux in different forms provides this common base across these four footprints this level of compatible compatibility is critical to operators who must best utilize the infinite must better utilize secure and deploy the infrastructure that they have and they're responsible for developers on the other hand they care most about having a platform that can creates that consistency for their applications they care about their services and the services that they need to consume within those applications and they don't want limitations on where they run they want service but they want it anywhere not necessarily just from Amazon they want integration between applications no matter where they run they still want to run their Java EE now named Jakarta EE apps and bring those applications forward into containers and micro services they need able to orchestrate these frameworks and many more across all these different footprints in a consistent secure fashion this creates natural tension between development and operations frankly customers amplify this tension with organizational boundaries that are holdover from the UNIX era of computing it's really the job of our platforms to seamlessly remove these boundaries and it's the it's the goal of RedHat to seamlessly get you from the old world to the new world we're gonna show you a really cool demo demonstration now we're gonna show you how you can automate this transition first we're gonna take a Windows virtual machine from a traditional VMware deployment we're gonna convert it into a KVM based virtual machine running in a container all under the kubernetes umbrella this makes virtual machines more access more accessible to the developer this will accelerate the transformation of those virtual machines into cloud native container based form well we will work this prot we will worked as capability over the product line in the coming releases so we can strike the balance of enabling our developers to move in this direction we want to be able to do this while enabling mission-critical operations to still do their job so let's bring Byrne his team back up to show you this in action for one more thanks all right what Red Hat we recognized that large organizations large enterprises have a substantial investment and legacy virtualization technology and this is holding you back you have thousands of virtual machines that need to be modernized so what you're about to see next okay it's something very special with me here on stage we have James Lebowski he's gonna be walking us through he's represents our operations folks and he's gonna be walking us through a mass migration but also is Itamar Hine who's our lead developer of a very special application and he's gonna be modernizing container izing and optimizing our application all right so let's get started James thanks burr yeah so as you can see I have a typical VMware environment here I'm in the vSphere client I've got a number of virtual machines a handful of them that make up my one of my applications for my development environment in this case and what I want to do is migrate those over to a KVM based right at virtualization environment so what I'm gonna do is I'm gonna go to cloud forms our cloud management platform that's our first step and you know cloud forms actually already has discovered both my rev environment and my vSphere environment and understands the compute network and storage there so you'll notice one of the capabilities we built is this new capability called migrations and underneath here I could begin to there's two steps and the first thing I need to do is start to create my infrastructure mappings what this will allow me to do is map my compute networking storage between vSphere and Rev so cloud forms understands how those relate let's go ahead and create an infrastructure mapping I'll call that summit infrastructure mapping and then I'm gonna begin to map my two environments first the compute so the clusters here next the data stores so those virtual machines happen to live on datastore - in vSphere and I'll target them a datastore data to inside of my revenue Arman and finally my networks those live on network 100 so I'll map those from vSphere to rover so once my infrastructure is map the next step I need to do is actually begin to create a plan to migrate those virtual machines so I'll continue to the plan wizard here I'll select the infrastructure mapping I just created and I'll select migrate my development environment from those virtual machines to Rev and then I need to import a CSV file the CSV file is going to contain a list of all the virtual machines that I want to migrate that were there and that's it once I hit create what's going to happen cloud forms is going to begin in an automated fashion shutting down those virtual machines begin converting them taking care of all the minutia that you'd have to do manually it's gonna do that all automatically for me so I don't have to worry about all those manual interactions and no longer do I have to go manually shut them down but it's going to take care of that all for me you can see the migrations kicked off here this is the I've got the my VMs are migrating here and if I go back to the screen here you can see that we're gonna start seeing those shutdown okay awesome but as people want to know more information about this how would they dive deeper into this technology later this week yeah it's a great question so we have a workload portability session in the hybrid cloud on Wednesday if you want to see a presentation that deep dives into this topic and how some of the methodologies to migrate and then on Thursday we actually have a hands-on lab it's the IT optimization VM migration lab that you can check out and as you can see those are shutting down here yeah we see a powering off right now that's fantastic absolutely so if I go back now that's gonna take a while you got to convert all the disks and move them over but we'll notice is previously I had already run one migration of a single application that was a Windows virtual machine running and if I browse over to Red Hat virtualization I can see on the dashboard here I could browse to virtual machines I have migrated that Windows virtual machine and if I open up a tab I can now browse to my Windows virtual machine which is running our wingtip toy store application our sample application here and now my VM has been moved over from Rev to Vita from VMware to Rev and is available for Itamar all right great available to our developers all right Itamar what are you gonna do for us here well James it's great that you can save cost by moving from VMware to reddit virtualization but I want to containerize our application and with container native virtualization I can run my virtual machine on OpenShift like any other container using Huebert a kubernetes operator to run and manage virtual machines let's look at the open ship service catalog you can see we have a new virtualization section here we can import KVM or VMware virtual machines or if there are already loaded we can create new instances of them for the developer to work with just need to give named CPU memory we can do other virtualization parameters and create our virtual machines now let's see how this looks like in the openshift console the cool thing about KVM is virtual machines are just Linux processes so they can act and behave like other open shipped applications we build in more than a decade of virtualization experience with KVM reddit virtualization and OpenStack and can now benefit from kubernetes and open shift to manage and orchestrate our virtual machines since we know this virtual machine this container is actually a virtual machine we can do virtual machine stuff with it like shutdown reboot or open a remote desktop session to it but we can also see this is just a container like any other container in openshift and even though the web application is running inside a Windows virtual machine the developer can still use open shift mechanisms like services and routes let's browse our web application using the OpenShift service it's the same wingtip toys application but this time the virtual machine is running on open shift but we're not done we want to containerize our application since it's a Windows virtual machine we can open a remote desktop session to it we see we have here Visual Studio and an asp.net application let's start container izing by moving the Microsoft sequel server database from running inside the Windows virtual machine to running on Red Hat Enterprise Linux as an open shipped container we'll go back to the open shipped Service Catalog this time we'll go to the database section and just as easily we'll create a sequel server container just need to accept the EULA provide password and choose the Edition we want and create a database and again we can see the sequel server is just another container running on OpenShift now let's take let's find the connection details for our database to keep this simple we'll take the IP address of our database service go back to the web application to visual studio update the IP address in the connection string publish our application and go back to browse it through OpenShift fortunately for us the user experience team heard we're modernizing our application so they pitched in and pushed new icons to use with our containerized database to also modernize the look and feel it's still the same wingtip toys application it's running in a virtual machine on openshift but it's now using a containerized database to recap we saw that we can run virtual machines natively on openshift like any other container based application modernize and mesh them together we containerize the database but we can use the same approach to containerize any part of our application so some items here to deserve repeating one thing you saw is Red Hat Enterprise Linux burning sequel server in a container on open shift and you also saw Windows VM where the dotnet native application also running inside of open ships so tell us what's special about that that seems pretty crazy what you did there exactly burr if we take a look under the hood we can use the kubernetes commands to see the list of our containers in this case the sequel server and the virtual machine containers but since Q Bert is a kubernetes operator we can actually use kubernetes commands like cube Cpl to list our virtual machines and manage our virtual machines like any other entity in kubernetes I love that so there's your crew meta gem oh we can see the kind says virtual machine that is totally awesome now people here are gonna be very excited about what they just saw we're gonna get more information and when will this be coming well you know what can they do to dive in this will be available as part of reddit Cloud suite in tech preview later this year but we are looking for early adopters now so give us a call also come check our deep dive session introducing container native virtualization Thursday 2:00 p.m. awesome that is so incredible so we went from the old to the new from the close to the open the Red Hat way you're gonna be seeing more from our demonstration team that's coming Thursday at 8 a.m. do not be late if you like what you saw this today you're gonna see a lot more of that going forward so we got some really special things in store for you so at this point thank you so much in tomorrow thank you so much you guys are awesome yeah now we have one more special guest a very early adopter of Red Hat Enterprise Linux we've had over a 12-year partnership and relationship with this organization they've been a steadfast Linux and middleware customer for many many years now please extend a warm welcome to Raj China from the Royal Bank of Canada thank you thank you it's great to be here RBC is a large global full-service is back we have the largest bank in Canada top 10 global operate in 30 countries and run five key business segments personal commercial banking investor in Treasury services capital markets wealth management and insurance but honestly unless you're in the banking segment those five business segments that I just mentioned may not mean a lot to you but what you might appreciate is the fact that we've been around in business for over 150 years we started our digital transformation journey about four years ago and we are focused on new and innovative technologies that will help deliver the capabilities and lifestyle our clients are looking for we have a very simple vision and we often refer to it as the digitally enabled bank of the future but as you can appreciate transforming a hundred fifty year old Bank is not easy it certainly does not happen overnight to that end we had a clear unwavering vision a very strong innovation agenda and most importantly a focus towards a flawless execution today in banking business strategy and IT strategy are one in the same they are not two separate things we believe that in order to be the number one bank we have to have the number one tactic there is no question that most of today's innovations happens in the open source community RBC relies on RedHat as a key partner to help us consume these open source innovations in a manner that it meets our enterprise needs RBC was an early adopter of Linux we operate one of the largest footprints of rel in Canada same with tables we had tremendous success in driving cost out of infrastructure by partnering with rahat while at the same time delivering a world-class hosting service to your business over our 12 year partnership Red Hat has proven that they have mastered the art of working closely with the upstream open source community understanding the needs of an enterprise like us in delivering these open source innovations in a manner that we can consume and build upon we are working with red hat to help increase our agility and better leverage public and private cloud offerings we adopted virtualization ansible and containers and are excited about continuing our partnership with Red Hat in this journey throughout this journey we simply cannot replace everything we've had from the past we have to bring forward these investments of the past and improve upon them with new and emerging technologies it is about utilizing emerging technologies but at the same time focusing on the business outcome the business outcome for us is serving our clients and delivering the information that they are looking for whenever they need it and in whatever form factor they're looking for but technology improvements alone are simply not sufficient to do a digital transformation creating the right culture of change and adopting new methodologies is key we introduced agile and DevOps which has boosted the number of adult projects at RBC and increase the frequency at which we do new releases to our mobile app as a matter of fact these methodologies have enabled us to deliver apps over 20x faster than before the other point about around culture that I wanted to mention was we wanted to build an engineering culture an engineering culture is one which rewards curiosity trying new things investing in new technologies and being a leader not necessarily a follower Red Hat has been a critical partner in our journey to date as we adopt elements of open source culture in engineering culture what you seen today about red hearts focus on new technology innovations while never losing sight of helping you bring forward the investments you've already made in the past is something that makes Red Hat unique we are excited to see red arts investment in leadership in open source technologies to help bring the potential of these amazing things together thank you that's great the thing you know seeing going from the old world to the new with automation so you know the things you've seen demonstrated today they're they're they're more sophisticated than any one company could ever have done on their own certainly not by using a proprietary development model because of this it's really easy to see why open source has become the center of gravity for enterprise computing today with all the progress open-source has made we're constantly looking for new ways of accelerating that into our products so we can take that into the enterprise with customers like these that you've met what you've met today now we recently made in addition to the Red Hat family we brought in core OS to the Red Hat family and you know adding core OS has really been our latest move to accelerate that innovation into our products this will help the adoption of open shift container platform even deeper into the enterprise and as we did with the Linux core platform in 2002 this is just exactly what we did with with Linux back then today we're announcing some exciting new technology directions first we'll integrate the benefits of automated operations so for example you'll see dramatic improvements in the automated intelligence about the state of your clusters in OpenShift with the core OS additions also as part of open shift will include a new variant of rel called Red Hat core OS maintaining the consistency of rel farhat for the operation side of the house while allowing for a consumption of over-the-air updates from the kernel to kubernetes later today you'll hear how we are extending automated operations beyond customers and even out to partners all of this starting with the next release of open shift in July now all of this of course will continue in an upstream open source innovation model that includes continuing container linux for the community users today while also evolving the commercial products to bring that innovation out to the enterprise this this combination is really defining the platform of the future everything we've done for the last 16 years since we first brought rel to the commercial market because get has been to get us just to this point hybrid cloud computing is now being deployed multiple times in enterprises every single day all powered by the open source model and powered by the open source model we will continue to redefine the software industry forever no in 2002 with all of you we made Linux the choice for enterprise computing this changed the innovation model forever and I started the session today talking about our prediction of seven years ago on the future being open we've all seen so much happen in those in those seven years we at Red Hat have celebrated our 25th anniversary including 16 years of rel and the enterprise it's now 2018 open hybrid cloud is not only a reality but it is the driving model in enterprise computing today and this hybrid cloud world would not even be possible without Linux as a platform in the open source development model a build around it and while we have think we may have accomplished a lot in that time and we may think we have changed the world a lot we have but I'm telling you the best is yet to come now that Linux and open source software is firmly driving that innovation in the enterprise what we've accomplished today and up till now has just set the stage for us together to change the world once again and just as we did with rel more than 15 years ago with our partners we will make hybrid cloud the default in the enterprise and I will take that bet every single day have a great show and have fun watching the future of computing unfold right in front of your eyes see you later [Applause] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] anytime [Music]

>> Announcer: From San Francisco, it's theCUBE. Covering Red Hat Summit 2018. Brought to you by Red Hat. >> Hey, welcome back everyone. This is theCUBE live here in San Francisco at Moscone West Fourth, Red Hat Summit 2018. I'm John Furrier, the co-host of theCUBE with John Troyer, the co-founder of TechReckoning, an advisory firm in the area of open source communities and technology. Our next guest is Cube alumni Dietmar Fauser, head of core platforms and middleware at Amadeus, experienced Red Hatter, event go-er, and practitioner. Great to have you back, great to see you. >> Thank you, good to be here. >> So why are you here, what's going on? Tell us the latest and greatest. What's going on in your world? Obviously, you've been on theCUBE. You go on YouTube, there's a lot of videos on there, you go into great detail on. You been on the Docker journey. You got Red Hat, you got some Oracle. You got a complex environment. You're managing cloud native-like services. Tell us about it. >> We do so, yes, so this time I am here mostly to feed back some experience of concrete implementation out there in the Cloud and on premise so. Paul told me that the theme was mostly hybrid cloud deployments so we have chosen two of our really big applications to explain how concretely this works out with you and when you deploy on the Cloud. >> So you were up on stage this morning in the keynote. I think the scale of your operation maybe raised some eyebrows as well. You're talking about over a trillion transactions. Can you talk a little bit about, talk about your multi-cloud stance and what you showed this morning. >> Okay, so first to frame a bit of the trillion transactions. It's not traditional data based transactions. It's individual data access and highly in-memory cached environment. So I'd say that's a very large number and it's a significant challenge to produce this system. So we're talking about like more than 100,000 core deployments of this applications so. Response time matters extremely in this game because at the end what we are talking here about is the back end that powers large P2C sites, like Kayak, some major search engines, online travel agencies. So it just has to respond in a very fast way. Which pushed us to deploy the solutions very close to where the transactions are really originating to avoid our historical data centers in Germany. We just want to take out the back and forth travel under the Atlantic basically to create a better end user experience at the end. >> Furrier: So you had to drive performance big time? >> We, very much. It's either performance or higher availability or both actually. >> This is a true hybrid cloud, right? You're on prem, you're in AWS, and you're in Google Cloud. So could you talk a little bit about that? All powered by OpenShift. >> OpenShift is the common denominator of the solutions. Some of our core design goals is to build the applications in a platform agnostic way. So an application should not know what's its deployment topology, what's the underlying infrastructure. Which is why I believe that platforms like OpenShift and Kubernetes underneath are so important, because they take over the role of a traditional operating system, but at a larger scale. Either in big Cloud deployments or on premise, but the span of operations that you get with these environments is just like an OS but on a bigger scale. It's not a surprise that people talked about this like a data center operating system for a while. We use it this way so OpenShift is clearly the masterpiece, I would say of the deployment. >> That's the key though, I think, thinking about it as an operating system or an operating environment is the kind of the architectural mindset that you have to be in. Because you've got to look at these resources and connections, link them together. You've got all these team systems constant. So you've got to be a systems person kind of design. How does someone get there that may or may not have traditional systems experience? Like us surly generation systems folks have gone through. Because you have devops automating away things. You have more of an SRE model that Google's talking about. Talking about large scale, it's not a data center anymore, it's an operating environment. How do people get there? What's your recommendation, how do I learn more. What do I do to deploy architecturally? >> That's a key question I think. I think there were two sections to your question, how to get there, so. I think at Amadeus we are pretty good at catching early big trends in the industry. We are very close to large engineering houses like Google and Facebook and others like Red Hat of course and so, it was pretty quickly clear to us, at least to a small amount of these decision-makers that the combination of Red Hat and Google was kind of, a game-changing event, which is why we went there, so. It's, I mean. >> Furrier: The containers have been important for you guys. >> Containers were coming along, so, when this happened Docker became big, our development teams, they wanted to do containers. It was not something that the management has had to push for, it was grassroots type of adoption here. So different pieces fed together that gave us some form of certainty, or a belief that these platforms would be around for a decade to come. >> Developers love Kubernetes, and I mean that, containers, it's like a fish to water, it's just natural. Now talk about Kubernetes now, OpenShift made a bet with Kubernetes, obviously, a few years ago. People were like, what is that about? Now it's obvious why. How are you looking at the Kubernetes trade, obviously it creates a de facto capability, you can wrap services around it, there's a notion of service meshes coming, Istio is the hottest product in the Linux Foundation, CNCF, KubeFlow is right behind it, I mean these are kind of thinking about service and micro-services and workload management. How do you view that, what's your opinion on that direction? >> I'm afraid there is no simple answer to this, because if you start new solutions from scratch, going directly to Kubernetes, OpenShift is the natural way. Now the big thing in large corporations is we all have legacy applications, whatever we call legacy applications, in our case these are pretty large C++ environments that are relatively modern but they are not strictly micro-service based and they are a bit fatter, they have an enterprise service bus on top of this, and so it's not, and we have very awkward, old network protocols, so going straight to the mesh for these applications and micro-services is not a possibility because there is significant re-engineering needed in our own applications before we believe it makes sense to throw them onto a container platform. We could stick all of this in a container but you have to wonder whether you get the benefit you really want to. >> Furrier: Time ROI, return on investment, on the engineering, retrofitting it for service mesh. >> Yes, I mean, the interesting thing is Kubernetes or not, we would have touched these applications anyway to cut them into more manageable pieces. We call this compartmentalization. Other people may call this micro-service-ification, or however we want to call this. So that's, to me this is work that is independent from the cloud strategy in itself. Some of our applications, to move faster, we have decided to put them more or less as they are onto OpenShift, others we take some more time to say, okay let's do the engineering homework first so that we reap the full benefits of this platform, and the benefit really is, what is fundamental for developers, efficiency and agility is that you have relatively small, independent load sets, so that you can quickly load small pieces, you can roll them in. >> Time to production, time from developer to production. >> But also quality, the less isolated, the more you isolate the changes, the less you run the risk that a change is cross-impacting things that are in the same delivery basically. It's a lot about, smaller chunks of software that are managed and for this obviously a micro-service platform is absolutely ideal. So it helps us to push the spirit of the company in this direction, no more monolithical applications, fast daily loads. >> Morale's higher, people happy. >> Well, it's a long journey, so some are happy, some are impatient like me to move faster. Some are still a bit reluctant, it's normal in larger organizations. >> Talk about the scale, I'm really interested in your reaction and experience, let's talk about the scale. I think that's a big story. As cloud enables more horizontally scalable applications, the operating aperture is bigger. It's not like managing systems here, it's a little bit bigger picture. How are you guys looking at the operational framework of that, because now you're essentially a site reliable engineering role, that's what Google talks, in SRE, but now you're operating but you're still developing code, and you're writing applications. So, talk about that dynamic and how you see that playing out going forward. >> So, what we try to do is to separate the platform aspects from the application aspects, so I'm leading the platform engineering unit, including platform operations, so this means that we have the platform SRE role, if you want, so we oversee frontline operations 24 by seven stability of the global system. To me, the game is really about trying to separate and isolate as much as we can from the applications to put it on the platform because we have, like, close to 100 applications running on the platform and if we can fix stuff on the platform for all the applications without being involved in the individual load cycles and waiting for them to integrate some features, we just move much faster. >> You can decouple the application from some core platform features, make them highly cohesive, sounds like an operating system to me. >> It is, and I'll come to the second thought of the SRE a bit later, but currently the big bulk of the work we are doing with OpenShift is now to bring our classical platform stuff under OpenShift. And by classical application, I mean our internal components like security, business rule engines, communication systems, but also the data management side of the house. And I think this is what we're going to witness over the next two or three years, is how can we manage, like, in our case CouchBase, Kafka, all of those things, we want them to be managed as applications under OpenShift with descriptive blueprints, descriptive configurations which means you define the to-be state of a system and you leave OpenShift to ensure that if the to-be state is like, I need 1000 ports for a given application, is violated OpenShift will repair automatically the system. >> That's interesting, you bring up a dynamic that's a trend we're seeing, I want to get your thoughts on this. And it hasn't really been kind of crystallized and yet I haven't heard a good explanation but, the trend seems to be to have many databases. In other words, we're living in a world where there's a database for everything, but not one database. So, like, if I got an application at the edge of the network, it can have its own database, so we shouldn't have to design around a database concept, it should be, concept should still be databases everything, living and growing and managing it. How are, first of all do you believe that, and if so, how do you architect the platform to manage potentially ubiquitous amount of different kinds of databases where the apps are kind of driving their own database role, and working with the core platform. Seems to be an area people are really talking about, because this is where AI shines if you get that right. >> So I agree with you that there are a lot of solutions out there. Sometimes a bit confusing choice, which type of solutions to choose. In our case we have quite a mature, what we call a technical policy, a catalog of technologies that application designers can choose from, so there are several data management stores in there. Traditionally speaking we use Oracle, so Oracle is there and is a good solution for many use cases. We were very early in the Nosql space so we have introduced Couchbase for highly scalable environments, Mongo for more sophisticated objects or operations. We try to educate, or to talk with our application people not to go outside of this. We also use Redis for our platform internal things, so we try to narrow their choices down. >> Stack the databases, what about the glue layer? Any kind of glue layer standards, gluing things together? >> In general we always put an API layer on top of the solutions, so we use our own infrastructure independence layer when we talk to the databases, so we try not to have those native bindings in the application, it's always about disentangling platform aspects from the application. >> So Dietmar, you did talk about this architectural concept, right, of these layers, and you're protecting the application from the platform, what about underneath, right? You're running on multiple clouds. What have been the challenges of, in theory, you know, there's a separation layer there and OpenShift is underneath everything, you've got OpenStack, you've got the public clouds, have there been some challenges operationally in making sure everything runs the same? >> There are multiple challenges, so to start with, the different infrastructures do not behave exactly the same, so just taking something from Google to Amazon, it works in theory but practically speaking the APIs are not exactly the same, so you need to remap the APIs. The underlying behavior is not exactly the same. In general from an application design point of view, and we are pretty used to this anyway because we are distributed systems specialists, but the learning curve comes from the fact that you go to an infrastructure that is, in itself, much less reliable if you look to individual pieces of it. It works fine if you use well the availabilities on concepts and you start with the mindset that you can lose availabilities or even complete regions and take this as a granted, natural event that will happen. If you are in this mindset there aren't so many surprises, OpenShift operates very well with the unreliability of virtual machines. We even contract, in the case of Google, what is called preemptive VM so they get restarted anyway very frequently because they have a different value proposition so if you can run with less reliable stuff you pay less, basically. So if you can take advantage of this, you have another advantage using those. >> Dietmar, it's great to hear your stories, congratulations on your success and all the work you're doing, it's sounds like really cutting-edge and great work. You've been to many Red Hats. What's the revelation this year? What's the big thing that people should know about that's happening in 2018? Is it Kubernetes? What should people pay attention to from your opinion? >> I think we can take Kubernetes now as granted. That's very good news for me and for Amadeus, it was quite a bet at the beginning but we see this now as the de facto standard, and so I think people can now relax and say, okay this is one of the pieces that will be predominant for the decade to come. Usually I'm referring to IT decades, only three years long, not 10 years. >> Okay, and as moving to an operating system environment, I love that analogy. I think it's totally right from the data that we see. We're living in a cloud native world, hybrid cloud on-premise, still true private cloud as Wikibon calls it and really it's an operating system concept architecturally, and IoT is coming fast. It's just going to create more and more data. >> So, what I believe, and what we believe in general at Amadeus is that the next evolution of systems, the big architectural design approach will be to create applications that are much more streaming oriented because it allows to decouple the different computing steps much more. So rather than waiting for a transaction, you subscribe to an event, and any number of processes can subscribe to an event, the producer doesn't have to know who is consuming what, so we go streaming data-centric and massively asynchronous. Which, which, which yields smoother throughput, less hiccups because in transactional systems you always have something that slows down temporarily a little bit, it's very difficult to architect systems with absolute separation of concerns in mind, so sometimes a slowdown of a disk might trigger impacts to other systems. With a streaming and asynchronous approach the systems tend to be much more stable with higher throughput. >> And a lot more scalable. There's the horizontally scalable nature of the cloud, you've got to have the streaming and this architecture in place. This is a fundamental mistake we see with people out there, they don't think like this but then when they hit scale points, it breaks. >> Absolutely, and so, I mean we are a highly transactional shop but many of our use cases already are asynchronous so we go a deep step further on this and we currently work on bringing Kafka massively under OpenShift because we're going to use Kafka to connect data center footprints for all types of data that we have to stream to the application that are out in the public cloud, or on premise basically. >> We should call you professor because this was such a great segment, thanks for sharing an awesome amount of insight on theCube. Thanks for coming on, good to see you again. Dietmar Fauser, head of core platforms and middleware at Amadeus. You know, down and dirty, getting under the hood really at the architecture of scale, high availability, high performance of the systems to be scalable with cloud, obviously open source is powering it, OpenShift and Red Hat. It's theCube bringing you all the power here in San Francisco for Red Hat Summit 2018. I'm John Furrier and John Troyer, we'll be back with more after this short break. (electronic music)

>> Announcer: Live from the Moscone Center. It's theCUBE! Covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. (upbeat techno music) >> Hey, welcome back, everyone. We're live here in San Francisco. This is theCUBE's exclusive coverage of AWS Amazon Web Services Summit 2018 with my co-host Stu Miniman. We have two great guests. Hot startup from SingleFx, the CEO, Karthik Rau, and the CTO, Arijit Mukherji. Welcome to theCUBE. Good to see you again. >> Karthik: Yeah, great to see you again. Thanks for having us. >> So, we've been following you guys. You've been out five years. Two years in stealth, three years ago you launched on theCUBE. >> Karthik: Right here on theCUBE. >> We see you at AWS and VMware. Cloud's changed a lot. So, let's get an update. Karthik, take a minute to explain where you guys are at now company-wise, employees, traction momentum, product. Where are you guys at now? >> Karthik: Yeah, absolutely. So, SignalFx, first of all, let me tell you what we do. SignalFx is a realtime streaming operational intelligence solution. Basically, what that means is we collect monitoring data, operational data across the entire cloud environment, from the infrastructure all the way up to the applications. And we apply realtime analytics on that data to help people be a lot more proactive in their monitoring of these distributed environments. We launched the company in 2015. We come ... I'll let Arijit talk about our origins. We came out of Facebook. And we had a lot of experience building this to Facebook. In the past three years, we've been building up our company aggressively. We've now got hundreds of customers including several large Fortune 500 accounts, large web scale accounts like Acquia and HubSpot and Yelp and KAYAK. And we're over 100 employees now, about 120 employees. And yeah, doing great. >> So, Werner Vogels, the CTO, laid out on stage plus a great Matt Wood conversation about machine learning but the real thing that Werner laid out was the old way, the web server, multi-tier architecture stack kind of thing going on there to a more cloud DevOps horizontally scalable where sets of servers that could be spawned in parallel creates a new kind of operating model but also creates challenges around what to instrument. You know, as we would joke, someone left the lights on, implying EC2s been running. And all these kinds of things are going on. And you mentioned some of the Facebook kind of challenges. People were building their own scale. What have you guys learned and how does that apply today's modern infrastructure? What are some of the threshold challenges that companies are facing when they say, one, already there or I want to get there? How do you guys look at the main issues? >> Karthik: Do you want to take that? >> Yeah, so monitoring modern environments and infrastructure is actually quite a challenge. There's obviously a few things going around. One, as you mentioned, is the variety, the sheer variety of things. No longer just the three-tier architecture I have cloud services. I have containers. I have lambdas. I have my own applications. I have the cloud infrastructure itself that all needs to be monitored. And things are also becoming far more numerous. So, there's just many more of everything, right? And so, making sense of that space is becoming a big challenge. And our company was founded on the idea that monitoring is becoming an analytics problem. So, it's no longer about looking at individual servers or applications instances. It's more about making sense holistically over what's going on and being able to combine different types of data from different systems together to provide you with that high level view and that's the kind of functionality that we at SignalFx have been trying to provide. >> What are some of the data flows volumes look like. Cause I've heard multiple people talk about either Facebook or in open compute environments where there's just so much data coming in from the instrumentation that no human could actually get their arms around it. And you need to supplement it with machine learning and intelligence. I mean, is that something that you're seeing? What are some of the -- >> Yes, so actually what we see is different prospects or customers will be in different stages of a spectrum where maybe they were in a stage one where they're sort of using traditional architectures and then moving to these more modern systems. And as they get more modernized themselves, their use cases or the ways they wanted to do monitoring also gets more advanced. And so, we see the whole spectrum of it, as you mentioned. And so, understanding analytically how what we're is doing is great. But then you also want to take the human out of things as much as possible, right? >> Yeah. >> And make things more automated. And you want to look at the data and how things are behaving to learn from existing patterns to find outlines. So, that's really a very interesting challenge. And what I look at what we can do as a company going forward, like all the technological stuff that we can invest in, it's quite interesting. >> Yeah, Karthik, take us inside your customers. How does this modern monitoring, how does it change their business? How does it impact things like feedback loops and DevOps and everything that customers are having to deal in this kind of ever changing environment? >> Yeah, well I'll give you an example. There's a Fortune 500 company. They do product launches. And this is one of our customers and their product launches drive so much traffic that they do 80% of their business in the first two minutes of a product launch. And this is not at all uncommon in today's economy. And they're leveraging a lot of modern technologies, container architectures, serverless function architectures to spin up a bunch of capacity during these launches. And they were effectively flying blind most of the time. Because most of the traditional systems management monitoring solutions are not designed, A, to handle that volume. But, B, to handle the instant discovery requirements of if you're going to do 80% of your business in the first two minutes. So, the challenge is you're always playing defense. You're reacting to issues. And you're mostly flying blind. By leveraging SignalFx, they're getting realtime visibility, realtime discovery of these components as they're coming up. We're the only solution that can do that. So, literally within seconds of spinning up all of these containers, they're getting live streams into their dashboards, and live analytics, and live alerts. And what that's enabled them to do is be a lot more aggressive and effectively doing a lot more of these launches. So, that's driving their business and it's helping them drive their digital strategy forward. >> And microservices is really enabling you guys to be more relevant. Because truly the signal from the noise is where all these services reporting to? >> Karthik: Yeah. >> You talk about container madness. >> Karthik: There are two fundamental problems. So, one there's an architecture shift. And that's driving massive amounts of volume. You have physical machines that will live for three years in a data center. Divide it up into VMs, 10, 20 VMs per server. That'll maybe live for a few months. To now every process running in it's own container that might live for a few minutes. So, you have a massive exponential explosion in the number of components. But that's not the only problem. I was part of an architectural shift at VMware for a number of years. We weren't just affecting an architecture change. What's happening now is there's a cultural change and a process change that's happening as well. Because with containers, your development team can push changes directly out into a production environment. And what you're finding is you're going from sequential product development to parallel product development and a massive exponential increase in the number of code pushes. The only way you can operationalize that is you have to have realtime visibility in everything that's happening. Otherwise, the left arm doesn't know what the right arm is doing. >> John: And you need prescriptive and predictive analytics. >> Exactly. And you need predictive analytics to identify there's something unusual here. It's not a problem yet. But this is highly unusual and maybe it's your canary release. We need to do a code push. So, you want to roll it back. So, having that level of predictiveness becomes absolutely critical. >> Yeah, you mentioned realtime. We used to argue what really is realtime. And it was usually well in time to react to what the customer needs. What does realtime mean to your customers? Architecturally, is there something you do different to kind of understand what that means? >> Arijit: Yeah, so we actually fundamentally took a very different approach when we build a product. Where, typically, monitoring our metrics, monitoring was done with what we call a store and create or a batch-like architecture where you store all the data points that are coming in, then you create from it to any other use cases. While what we build at SignalFx is a fully end-to-end streaming architecture which is realtime. And what we mean by realtime is like two to three seconds between a data point coming through us and it's firing an alert or showing up in your chart. So, that's the kind of realtime. And it requires us to do lots of innovations up and down the stack. And we've built a lot of IP. We've got now patterns. And more are coming because the approach we took was quite novel. Different from-- >> John: You guys got a great management team. And looking at what you guys have done. I've been impressed with you guys. I want to just ask, Karthik, you mentioned about all these parallel processes that are going on. Totally agree. The process change, operationalizing an all new cultural way to create software manage the data. I mean, it really is the perfect storm for innovation. But also, it could literally screw people up. So, I got to ask you, who are you targeting for your customer? Who is the person that you talk to? Assuming it's kind of DevOps, so it's more like a cloud architect. Who do you target? Who do you sell to? Who's the buyer? Who uses your service? >> Karthik: Well, we see ... Every enterprise we see following a very similar journey. So, the first stage is, typically, you're just getting familiar with cloud. And you're probably just lifting and shifting enterprise workloads into the cloud. Probably experimenting with big data on the cloud. You're not yet doing microservices or containers or DevOps. And for them, we're still selling largely to classic IT. There just trying to get better visibility into their digital environment, you know, they're cloud environment. But then, what ends up happening is they very quickly get to what we call basically chaos. It's stage two. And it has a lot of parallels to shadow IT. What happened with SAS, where you have hundreds of different SAS tools is happening all over again with cloud but you've got hundreds or thousands of different operational tools. Different ways of doing monitoring, logging, security. And every team is doing it's own thing. And so, that's a big problem for enterprises who are trying to build best practices across their broader team. In that place, we're typically selling to departments because they don't have a centralize strategy yet. But what we find is the organizations at maturity have figured out that it's important to have certain centralized core services. And that doesn't mean they're forced on the end users. But they provide best practices around monitoring, logging, and such. And just make it easy for them to use those solutions. So, that's almost a new IT organization. It's platform engineering -- >> John: Is that a cloud architect? >> Platform engineering team, infrastructure engineering team, and they are effectively building best practices around the new stack not the traditional stack. >> So, you are or aren't targeting department level? Are you are? >> We sell to departments. But we also sell to the teams that are standardizing across the entire organization. >> So, cloud architects, for instance? >> Depends on the stage of the cloud journey. >> Or company. >> And the company, exactly. >> From an architectural standpoint, you talked that there's virtualization, there's containers, now serverless. How do you even figure out what to monitor in serverless? How fast is that changing? And how is that impacting your road map? >> So, serverless brings a very interesting challenge because they are very, very ephemeral. Like they're ephemeral in some sense. So, we realize there are two things. One is serverless, there's a reason why things are moving faster. It's because you want to be able to move faster. But then you also need to be able to monitor faster. It's no good monitoring serverless at five minutes later, for example. So, one of the things we invested in was how to get metrics, etc. and telemetry from these serverless environments in a very fast fashion. And that's something that we've done. The second thing we are doing that really works for this environment is afterall it's not about how many times a serverless function ran, it's about the value that it's providing the application that's running on it. And by focusing on a platform that let's you send these application metrics in great detail and then be able to monitor and analyze them, I think really amplifies the value in some sense. So, those are the two ... >> John: And talk about the ecosystems. One of the things I want to ask you guys because we've been seeing a collision between a lot of the different clouds. Clients want multicloud. Well, obviously, we're here at Amazon. They believe they should be the only cloud. But I think most customers would look at either legacy systems with some instrumentation and operational data to edge of the network, for instance. I mean, look at the edge of the network. That's just an extension of the data center depending on how you look at it. So, how do you guys view that kind of direction where customer says, "Hey, you know, I got a cloud architect. We're on Amazon. Of course, we have some old Microsoft stuff. So, we've got Azure going up there. We're kicking the tires on Google. And I got this whole IoT Edge project. SignalFx, instrument that for me. (laughs) Is that what you do? Or how do you deal with that? How would you deal with that kind of conversation? >> Well, I think most enterprises, the larger companies we see looking at multiple clouds. And they have different workloads running in different clouds, depending on the needs and what they're looking to do. So, the nice thing about a solution like SignalFx is we span all of these different architectures. And what we find is that most of the larger companies want to separate their business process solutions from their runtime architectures. Because they want to have a solution like SignalFx that it doesn't matter who you're using. If you choose to have your analytics intensive workloads in Google Cloud and your eCommerce workloads in Amazon, but you only want one system that will page someone in the middle of the night if there's a problem, then you have SignalFx to do that. And then you have your choice of runtime environments depending on what your developers need or what the business demands. We provide a lot of that glue across the different environments. >> Do you see that as the preferred architecture with most customers? Cause that makes a lot of sense. I mean, whether you're doing other data services, it kind of makes sense to separate out. Is that consistent? >> To have different applications >> Yeah. >> In different clouds? It depends. I mean, I think we see some people who are more comfortable running on a single cloud vendor and they make the decision based on what a portfolio of platforms and service features that are available. And they really like those, and they say it's easy to just go with one. But more often, we find people wanting to at least have some percentage running in a different cloud vendor. >> John: All right, final question. What's the secret sauce for the company? Tell us about the secret sauce. >> Arijit: I think-- >> We got the patents. I heard patents. You don't have to show all this exactly. But what is the secret DNA of the tech? What's the magic? >> I think it's our very unique architecture. It's entirely different from what you have. It's streaming and it focuses on scale, on timeliness, as well as on analytics capability. I think that unique combination is very special for us. And that, in a way, sort of allows us to address very, very different use cases, including this hybrid environments and what not, in a very effective way. So, it's a very, very powerful platform that can be used for many use cases. >> All right, so that was John's final question. Karthik, I've got one last one for you. What's it like being a CEO of a software company in the cloud era today compared to what it's been earlier in our career? >> Well, it's moving very, very quickly, right? I mean, technology always move very quickly. But I think compared to when I was at VMware in the mid 2000s, it just feels like every 18 months there's a new technology wave. You know, when we started our company five years ago, that was the first year that AWS eclipsed a billion dollars in sales and Dagra hadn't even launched. It launched a month after we started the company. And then serverless came. And now function architecture is all there. So, there's just so much change happening, and it's happening so quickly, it forces vendors like us to really be on the cutting edge and forward looking and making sure that you're keeping an eye out for what's coming cause the markets are moving way faster, I think, then they were 15 years ago. >> John: Well, Karthik, thanks so much. We appreciate you guys coming on, SignalFx. I'll give you the final word on the interview. Take a minute to share something with the audience that they might not know about SignalFx that they should know about. >> Well, I think what people may not realize is how realtime we can actually get. I think most people are used to doing all their monitoring and observation, and they think of realtime in the order of minutes, or if you can get stuff every 30 seconds. We really are the only realtime solution. That's why we say real realtime. We're on the order of seconds. You can build really, really sophisticated analytics and get visibility like you can't anywhere else. So, it's real, realtime. >> And that's soon to be table stakes. TheCUBE is realtime. We're live right here, on theCUBE here, in San Francisco at Amazon Web Services, AWS Summit 2018. We've been covering all the Amazon re:Invents since it started, of course. I'm John Furrier with Stu Miniman. Back with more live coverage after this short break. (upbeat techno music) (gentle instrumental music)

(upbeat music) >> Hey, welcome back everybody. Jeff Frick here with the CUBE's 2018, a new year. I think this is actually my first interview of the year. I'm pretty excited. I have a CUBE conversation here in the Palo Alto studios to talk about a pretty interesting topic. It's been growing over time but it's getting more and more sophisticated and a much bigger reach. And that's dynamic pricing. It's not just stick the sticker on the item like it used to be back in the day. And that's the price and it's much more complicated. Much more sophisticated. And we're excited to have Alex Shartsis. He's the CEO of Perfect Price. Alex, good to see ya. >> Thanks for having me. >> So, dynamic pricing, right. We've saw it. I guess probably the airlines are maybe the first ones to do it. Or you know, Priceline.com was kind of the first one to talk about. You know, hotels have rooms they can't get rid of. But it's moved a lot further down the path than that. I mean now the Giants I think have have flex pricing. Whether it's the Dodgers on a Friday night or it's Toronto on a Tuesday. >> Yeah, I think it's kind of just a really interesting subject, cause everybody's experienced it, right? I mean, you may not know you've experienced it. But everybody. Whether you've taken an Uber, taken a flight, stayed in a hotel. Even at this point going to an A's game or a Giants game. You've been dynamically priced. And I think what people don't realize is a lot of times they benefit from it. You're able to get that flight for a little bit less. You're able to get the Uber for a little bit less, especially than a taxi. And yeah sometimes there's surge pricing. There's last minute fares. There's things that are more expensive but it's something that every consumer has dealt with. And I think a lot of us think about pricing from a consumer standpoint cause we're all consumers. But from a business standpoint there's nothing more impactful than dynamic pricing. >> Yea, and pricing in and of itself is such a complicated issue. You go through some of the stuff on your website. You know are you coming at it from a cost point of view? Is it a cost plus kind of a model? Or is it a value model? So there's a lot of factors, right? There is no kind of perfect price. You don't want a price at the top of the market. You know, then you're giving up some volume. So what are some of the factors when you talk to people as the pricing evolution is happening from kind of what they used to do to what they're trying to do now with dynamic pricing and how you can help them? >> Yeah, so I think if you think about sort of pricing evolving from. Cost plus was kind of the beginning. Like I bought the potato from the farmer for five bucks a pound. And I'm going to sell it for 10 bucks a pound. That covers my cost of shipping it. Having a stall at the Bazaar, whatever. I think, you know today, a lot of companies still do that. Which still shocks me. But there's you know, there became this sort of in the middle of the last century. Which is kind of weird to say. Value based pricing became a thing. So it wasn't that I would sell them for 10 bucks a pound cause it was just double what I paid for them. It's people are willing to pay 10 bucks a pound and then if I try and sell them for 12 nobody buys them. Or a lot fewer people buy them and if I sell them for seven I run out. And I could have made a lot more money. So what value based pricing was is really like what is my customer willing to pay? And the Bazaar was a great place. You have a conversation. You know, Alex, how much do you really need this potato? How much do you really want this thing? Oh, you're like wearing a nice suit. I think I'm going to charge you more for this. And that obviously went away when the department store was invented. And people would walk around and see a tag on the item. And so what we do and I think what our customers are really benefiting from is this notion of really accurately figuring out what that. Not only the value the customer's getting but also factoring in all the other business related costs and fixed costs and things like that. That should or should not be part of that equation. So that the company can sometimes sell maybe at a loss on that one unit. But you know, in the case of a travel business like an airline or hotel. Loss is a very subjective thing. And you're able to make money by lowering the price for a certain segment. Or for a certain time or for a certain origin, destination. Whatever that combination is. And increase your overall profitability by doing so. Plus bring in some customers that wouldn't have been able to buy from you before. >> So, that's an interesting point of view right. Cause always what are you optimizing for? Are you optimizing for the single transaction? Or are you optimizing for the bucket of transactions? And then that can get you to very different places. So as you seen it kind of evolve what are some of the key factors that tell one of your customers you've got a great opportunity to increase profitability. Increase revenue, increase client satisfaction. Again, what are you measuring? What are you optimizing for by incorporating a dynamic pricing and how did it get started? >> Right, those are great questions. So we went into this thinking there are a lot of businesses that are stuck in cost plus pricing. And they would benefit the most from dynamic pricing. Or from using AI to price things because they're doing such a bad job of it today. And it turns out they liked doing a bad job of it for whatever reason. And we have now been successful at convincing them that maybe there's a better way to do it. But the companies that already have a lot of people and a lot invested in pricing in some fashion. Some companies call it revenue management. Those companies are the ones that really benefit and the reason is they've already seen an impact. So one of the key things for us as you. One of the first questions we ask people is why are we talking about pricing? Did you do something? Did something change in your business? Did you notice it had an impact? And everyone of our customers has been able to say yes to that. Somebody made a mistake and they changed the price and they saw a huge swing in their business. And they realize maybe we should think about it this time. >> It's usually some kind of mistake that undercuts. >> Not usually but more than once it has happened. And sometimes it's like we should do software here or not. And not let people fat finger things in. But for the more sophisticated companies. They've already seen. Some of the companies we've worked with have had pricing teams since the 70's. And so they are constantly improving and they see using AI to do dynamic pricing is the next evolution. And they don't want to get left behind. They know know it's a core of their business. And just as Enterprise Software is moving to the Cloud. Machine learning people are starting to use or have been using the graphics core for a while. You can't ignore that trend if it's a core to their business. >> So that's interesting so and we didn't really kind of talk about the impact of AI. And just really AI. Or intelligence to do a better job of optimization because as you said if you've already invested in pricing it's a complicated thing. There's so many factors and another thing about. Kind of Amazon and the Amazon pricing strategy. Or the vendors within Amazon even. And then how do you factor in convenience? How do you factor in prime? I mean there's these other things that have absolutely nothing to do with the physical price that can enable you. You know as you said, get more revenue. Get more profitability in these factors. So now we have AI. We have these crazy big machines. We have Cloud computing and big data. Huge disrupter to this marketplace and then really new opportunities to bring a lot more power to bare I would imagine. >> So I think Amazon is a great example. Cause people have really experienced dynamic pricing with Amazon. Just cause you put something in your cart the next day it changes by five cents. And Amazon's January pricing is really interesting because Bezos is being very vocal about being consumer centric. And so they're looking at what the market is doing and what things are priced elsewhere. And they're always trying to be competitive and give you value because they recognize. You said earlier. What are you trying to optimize for? Is it revenue, is is profit? There are other things you can optimize for that actually improve both of those numbers. Like how frequently you come back to that as a customer. Do I go to Amazon or do I look at Target or Walmart first. That is a huge impact in Amazon's profitability. And you may do that because of price that one time or over your experience with Amazon as a retailer. So I think what's interesting about AI is that it enables us to go. Just like the ad industry did. Went from having a lot of humans. Trying to solve a problem that really wasn't solvable by humans. So taking a lot of shortcuts. Doing what they could. It actually solves a problem. So if you think about the ad industry. If you're spending 10 million dollars on ads which I'm sure some of your listeners would be. And you're running a campaign. You probably have an agency. They probably have 10 people managing your campaign. They're looking at the 30 or 40 creatives. They have a 1,000 publishers it's running on. But pretty soon the numbers get big. I'm not going to do it right now on camera. But you multiply it out. You're talking about billions. >> And they're all multi varied right. So there's all the different. >> Right, well is the purple creative doing well on the female focus websites for 20 to 30. But not for 40 to 50 and at some point you can't keep track of all the permutation. And one of the weird twists I learned working in that industry is that. When you get down to people who actually click and convert. That's a very small number. So you might have millions or tens of millions of impressions. But you might only have a thousand or two thousand customers that ended up out of it. So you're trying to back out. Okay, that was a customer. Where did they start? And that becomes a very, very thin line to draw. And 10 years ago that was all people. You know, you had your agency. You had literally thousands of people that we traffic those campaigns. And today 78% of those ads are served by AI. Those decisions aren't made by humans anymore. And I think if you think about dynamic pricing for businesses that are very large and have really complex businesses. Like rental car companies, hotels, airlines. Transportation trucking where you're dealing with thousands of different factors. Why would you trust that to people if you don't have to? >> Yeah, as long as you have the data right. And the sophistication gets pretty interesting. You guys have a better appeal to people that already understand the value of dynamic pricing. Which you're really offering them is a new way to do it. An AI based way to do it. A Cloud based way to do it. >> The one place where we found a lot of interest that haven't had sophisticated solutions in the past. The companies that don't have a lot of direct competition. Cause a lot of, at least in travel, a huge part of the revenue manager function is what are the Jones' doing? Right, find the Hilton. What's the Marriot around the corner selling their rooms for? And for better or for worse I think there's a place for it. But it don't think it's quite the same place it's just easy for a human to go to your boss and say well boss. The Marriot around the corner is at 250 a night so we're at 260 cause I think our rooms are nicer. And yet in your data is actually the optimal price. If you look at your data. You can actually get to that price. Maybe you set some rules or you put some limits on the AI. So if the Marriot is at 300 you're not at a 1,000. Maybe you should be, right. You should maybe think about that a little bit if that's what the AI is thinking. But if you don't have that crutch. If you don't have a direct competitor around the corner from you. Then it becomes really hard. And that's why Uber started doing this in the first place. Because they knew taxi pricing was wrong. But to Travis and Ryan and the people who started Uber. The key part of it. The value proposition was always being able to get a car. And so the only way you could do that is basically by pressing people out of the market when you don't have enough cars. And then that one person who really needs to go to the hospital. Or is in DC and needs to go to a New Year's party. Whatever it is. They can pay the $200 to get to that thing they really need to cause there still is a car as opposed to not having a car. >> So you bring up a whole other kind of layer of complexity and that's the third party provider. And it just fascinates me that everyday it seems like there's a new Trivago or Kayak. Or God knows how many other kind of secondary marketplaces there are. So how does that factor in when you not only are worrying about your own pricing? Vis-a-vis your competition around the street or kind of your classic set of competitors. But now you've got this whole other layer of distribution that's kind of outside of your direct control with a whole different type of a pricing structure I would imagine. In terms of supporting. Are you seeing that expand to other places or is travel such a unique thing because of the perishability of the assets? >> So I think it will expand to other places. We think transportation in general, also trucking. I mean everything that has these sort of high operating leverage models. Where you have a lot of vehicles or distribution centers or things. The more accurately you fit your pricing to your demand the more money you'll make. The better run your business will be. The more time you save. It has a lot of implications. One of the things that's really interesting about the different channels is traditionally they have played a roll. You know you think about Nordstrom Rack or TJ Max or Priceline. Hotwire, right. You as the Hilton don't want to ruin your brand by renting your rooms for 50 bucks a night even though you know they're going to be empty. So you give them to Hotwire or you give them to Priceline. That always going to play a roll. A lot of these other places are drawing from the same inventory. So it's just yet another front door for you as a hotel or airline or a rental car company to get business from. What's interesting is because of software. Because of legal agreements and also because of software. There isn't a lot of variation in price. Even though every travel site says cheapest prices or best price guaranteed or whatever. They're all getting their pricing data from the same place. It is the same price. And so it's sort of. Unless it is run in inventory. Unless it is Hotwire where it's opaque. Where you don't know what you're getting. If you're getting a room at a Hilton. You could pretty positive that where ever you book that room Hilton's going to be the same price. >> So it's just pure marketing when they're trying to compete. Because ultimately the system kicks out what that third party available price is or is that even dynamically? >> Well, if you think about. I worked in the travel industry for a while so I don't want to share things that I shouldn't share but if you just think about. If you were the company that powered all these different sites. And had your own big consumer facing website. Would you be okay if Hilton rented its rooms for 50 or a 100 bucks less on its website? Then it lets you rent them for it. >> Probably not. >> Alex: Probably not. (laughing) >> So before we run out of time. So what are the key kind of attributes to the business that really lend itself to having an opportunity to increase profitability and revenue with dynamic pricing? >> So the biggest one is that you've seen. You've had some experience. It could be how ever trivial. And you've seen an impact. Pricing did impact your business. The second one is having a significant number of things that you sell. So if your ring and you sell doorbells and you have one product. Dynamically pricing the product is going to cause a lot more problems than it solves. But if you're a rental car company with thousands of cars. An hotel company with thousands of rooms. Anything where's there's either a lot of variation over a small number of products or a large number of products with a lot of variation. And finally to us it seems like there's this. That you're already a data focused company. Other people have written about this but you know that there's value in their data. You haven't figured out how to get it out of there yet. Or maybe you're doing some things with it. But you are committed to running your business more efficiently. I guess the marketers would call it a psycho graphic profile but that kind of attitude. You know not being content with. Hey, we've done this for four years this way and its worked great. But really wanted to leverage your data and knowing that there is enough data there. Those are the three things that really give us. >> And we don't really worry about price protection I guess. Nobody goes back once they buy their item their like. This is what I wanted. This is perfect. So and I just wondered too. What industries are people not thinking about maybe that you're starting to see get more involved in dynamic pricing. I mean obviously we know travel and those types. You've mentioned cars a number of times. Talked about kind of some of the crazy stuff that goes on Amazon. But is there other kind of ones that people might never think about? >> I mean I think the two big ones are the transportation trucking industry. There a ton of permutation there and they kind of got left out and went web 1.0. And so I think there's a lot to be done there. The other one is event ticketing. You mentioned the A's and the Giants but they're kind of the exceptions. I think there's a lot of ink that's been spilled over price gouging and scalpers and things like that. And I think that if that is you take a hard look at pricing their products more effectively. Everybody would be better off. Consumers and the promoters and the venues themselves. >> Yes, in the Boss' Letter he likes to talk a lot about the concert industry. Alright well Alex Shartsis. CEO of Perfect Price. Thanks for taking a few minutes our of your day and sharing the story. >> Thank you. >> Alrighty, he's Alex. I'm Jeff you're watching the CUBE from our Palo Alto studios. Happy New Year everybody. See you next time. (upbeat music) Welcome back everybody Jeff Frick here with the CUBE. It's 2018, a new year. I think this is actually my first interview of the year. I'm pretty excited to have a CUBE conversation here in the Palo Alto studios to talk about a pretty interesting topic. It's been growing over time but it's getting more and more Sophisticated in a much bigger region. That's dynamic pricing. It's not just stick the sticker on the item like it used to be back in the day. And that's the price and it's much more complicated. Much more sophisticated and we're excited to have Alex Shartsis. He is the CEO of Perfect Price. Alex, good to see you. >> Thanks for having me. So dynamic pricing, right. We've saw it I guess probably the airlines maybe the first ones to do it. Or Priceline.com was kind of the first one to talk about. Hotels have rooms they can't get rid of. But it's moved a lot further down the path in that. I mean now even the Giants I think have flex pricing whether its the Dodgers on a Friday night. Or it's Toronto on a Tuesday. >> Yeah, I think it's king of a really interesting subject cause everybody has experienced it, right. I mean you may not know you've experienced it but everybody whether you've taken an Uber or taken a flight. Stayed in a hotel. Even at this point gone to an A's game or Giant's game. You've been dynamically priced. And what I think that people don't realize is a lot of times they benefit from it. They're able to get that flight for a little bit less. You're able to get the Uber for a little bit less especially than a taxi. And yeah, sometimes there's surge pricing.

>> Announcer: Live from Washington, D.C., it's theCube covering .NEXT conference brought to you by Nutanix. >> Welcome back to the District everybody. This is theCube, the leader in live tech coverage. And this is our special presentation of Nutanix NEXT Conf, hashtag NEXTConf. My name is Dave Vellante, I'm here with Stu Miniman, my cohost for the two days of coverage at this event. Adam Japhet is here. He's the head of infrastructure at Scholastic Corp. Adam, thanks for coming on the Cube. >> Thanks for having me. >> So, is this your first .NEXT? >> This is my first .NEXT. >> Dave: What do ya think? >> There's a lot of energy here. It's a tremendous amount of energy. Just even in the size of the place. But the number of partners that you've got here and the number of customers, I'm really excited to be here. >> Well, the best is yet to come. Nutanix always does a really good job with the keynotes. >> Adam: Yeah, you haven't even opened the keynote yet, and it's already this much energy. >> Yeah, always very crisp messaging. They have great outside speakers. Robert Gates last year, Condi Rice and then, who was the illusionist? They had a-- >> Oh yeah, the guy in the box, David Blaine. Yeah, David Blaine held his breath for like nine minutes. >> He was holding his breath under water while the SE configured-- >> For the entire session? >> Yeah while the SE configured because the argument was it only takes eight minutes to configure a Nutanix solution. >> Wow. And then he came out, after eight minutes. You know he was able to configure the solution. Big hugs afterwards. Wet hugs. But anyway, it's a fun show here and it really hasn't even started yet. It started with Cube interviews. >> We've been interviewing. >> Now I'm even more excited. >> Dave: Yeah, so we've been interviewing practitioners all day. So tell us about Scholastic Corp. What do you guys do? >> Sure, so Scholastic, if you went to school in the US, you probably heard of Scholastic, but I'll reiterate it. It's the, actually, the world's largest, not just in the US, the world's largest children's book publisher and distributor. It's also a major education technology firm, so we do a lot of work within the education space with administrators, librarians, and other educators in your school system. But we're probably most recognized for our trade businesses. Which, Book Clubs, which is now called Reading Clubs, fairs and trade, and just the access to so many of the titles that so many kids in the US have grown up on. >> So, you're making sure the next generation will at least have the opportunity to read. (laughing) >> It's interesting, because I don't know if you're aware of this, but it was actually just two days ago, was the 20th anniversary of the release of the first Harry Potter book. What was called Harry Potter and the Philosopher's Stone in England and now it was called Harry Potter and the Sorcerer's Stone in the US. And actually they did some analysis. Some of the articles I was reading about it about literacy and they actually think that the Harry Potter series has contributed to, I guess we're calling them Gen Z or the post millennials or whatever, they grew up with Harry Potter, really improving literacy in the US. That's how important some of these books that we publish over the years have been. >> So you actually said, used to call it Book Club, now you call it Reading Club. So, that's sort of an indication that your business model's evolving, going digital. So when we talk about some of the drivers there. >> Absolutely, I mean that was really one of the key drivers, I think. I've been at Scholastic a long time now. 17 plus years. So I've seen lots of different evolutions have been evolved and a lot of different technology projects have been evolved, different launches. And I think in particular in 2011, when the iPad came out, and we saw such a rapid transition with newspapers, and periodicals, and magazines. Myself included, I felt myself going through it. Switching to using electronic devices for consumption. The next immediate question is, is this going to make all physical books go away? And so, you know, we really pivoted hard into the digital arena at that time, because we wanted to be where our constituencies are. And interestingly, we found that actually digitization in the children's book space, maybe a little bit in the young adult space, but especially in the elementary school space, it actually has been fairly resistant of digitization. It's there. We've got a number of excellent products there. With Storia and a number of other products for delivering digital content to our consumers, but primarily children. But ultimately kids still read physical books. My kids are 11 and nine, and our house is full of physical books and we really kind of segregate the two together so that they have both the digital reading experience, which is somewhat different from the physical reading experience. Nevertheless, it is continuing to transform our industry. >> We were talking to to Virginia Gambale before. She's an advisor, a strategic advisor, to a number of companies, board member, investor. And she was talking about capital allocation and one of the questions I have is when you guys sort of look at this digital disruption, the change, at what point do you decide, okay hey, we've got to change or we'll be changed. Or we need to get ahead of this. How does that all take, how did it take place in your organization? Was it more reactive, proactive, and sort of where are you headed? >> I mean, I think the proactive elements around it is that we want to make sure that when our consumers are ready to go digital, we've got a viable product that responsive to as many devices as we think our consumers are going to use. And parallel information there, we've been watching really in the last three years how much Google has sweeped into the educational space and they have kind done that at the expense of Microsoft and Apple. And so, we see trends like that and we see how quickly digital can move into the educational spaces which is where the primary customers are and how we sell our products to children. And we knew that we needed to have a viable product there, so I think a lot of things for us are looking at different channels. Making sure that we've got a singular view of our customer and recognizing that our primary customers are really educators. That we're connecting with them and we're understanding how they're using our different models, our different lines of businesses. How they're communicating our products to the parents and children that consume them. And really getting that right balance of physical and digital products in front of every kid. I mean, our core mission is to get kids to learn to love to read. It's to generate literacy so that kids become young adults and full adults and they love to read, and that's really what the core mission is behind Scholastic. And however we can deliver the products to satisfy that mission, we're prepared to do that. >> Adam, reaching the ultimate user in that whole digital transformation, that tends to put a lot of stresses on infrastructure which is the hat you wear. So, maybe explain a little bit some of those challenges you were having and what you've done to transform on the infrastructure side to meet the requirements of the business. >> Absolutely. So in my role, in my various roles that I've had at Scholastic over the years, one of the things I've been able to experience is how different parts of the company move at different speeds. And some of it is just the nature of the function of the company. You know, your back office corporate spaces obviously are going to move somewhat slower than your digital engagement and your e-commerce space. In a role I had several years ago, where I was delivering e-commerce and digital services, I quickly realized that the traditional infrastructure models simply wasn't going to cut it at this point. We were delivering infrastructure trying to scale it out for very seasonal demand. Three, six month lead times trying to stack text stacks all stuff that end up being undifferentiated heavy lifting. So ultimately, for us, we took a couple of big leaps. One of the big leaps that we took was really moving into the public cloud several years ago and that worked out tremendously for us and we've really been able to find the right infrastructure model for delivering our customer engagement experiences has been the public cloud. But when we started to pivot towards the fact that we move physical products, you know a lot of companies don't necessarily deal with physical products anymore. I could be wrong but I don't know that Facebook has a physical, Well I guess they have their VR. They acquired, I forget the name of the VR company now but generally, companies don't deal with physical products. An all in public cloud model can work pretty well for them. But when you're dealing with physical products, latency matters. Geodata locality matters. And some of the applications that you're dealing with can be very centric to the delivery of your manufacturing and your warehouse operations. So, that's actually part of why we've been investing in Nutanix. Because we want to have that same kind of agility with our infrastructure and get out of mixing and matching various vendors text stacks deliver essentially what's a foundational platform for us to deliver business value out of. I'd rather go with one vendor, right? And have a finite set of vendors where we're delivering network and compute and storage and the service delivery of our applications on top of that, and Nutanix has worked out very well for us. >> Appreciate that Adam, and it's really interesting. We talk to customers, the two terms that get thrown out are hybrid or multi-cloud and you laid out where you're using public cloud. Do you consider your Nutanix solution, is that private cloud, hybrid cloud? (speaking over each other) Does that interact with multi-data center or any other services? >> I've kind of avoided the term hybrid cloud because what was originally marketed to us as hybrid cloud was the idea that your workload is seamlessly portable between all these different cloud providers. And we kind of realized that was never really our intent. I think multi-cloud is probably a better model for us, because we're finding that our various cloud provider services, and if you even scale beyond just the basic IS, you get to the pads and the especially SaaS layer, they're all cloud services but they're fairly fit for purpose. And a lot of what our role is as a technology organization has moved towards assembling all of these fit for purpose cloud solutions together into a service delivery that we from a technology group can deliver to our internal and external customers. And so I prefer the term multi-cloud. >> So if we could follow up on this, if I may, skepticism on hybrid cloud, but this idea of a control plane that spans multiple physical clouds, including on-prem. Is something that, am I understanding that you don't feel that that's needed in your organization or that's not feasible technically? >> I think it really depends on the applications that will be delivered to that. So for example, we're finally making our first real foray into containers. And so, we've looked at a couple of different technologies. There's a number out there like OpenShift and Kubernetes and that's really we feel the best opportunity for us to find a way to deploy a true hybrid cloud model where you can actually provision your workload. Maybe not to get so far as to the Priceline type Kayak type view of I want to deploy this workload right now and GCP is the most optimal at this point in time for that. That could be a potential future state, but again, even that feels like it's still a fair amount of undifferentiated heavy lifting for our service delivery. So we find the right mix of products so that we can deliver a kind of a cost optimal workload. And in many cases, I think that technology vendors still haven't quite figured out how to handle state. It works great with the stateless part of your applications but you need to persist your state somewhere. We're probably in the earlier stages, I would say, around utilized service delivery. >> What I heard I think is, you chose by application whether this is going to be something we do in-house because whether there is the locality, the analytics or data processing, something I need it for a reason, as opposed to other things. It's undifferentiated. Public cloud can take care of it and there's not a need to own it in town. >> Yes, you said it better than I said it. >> So the question, I think Dave's asking is how do you manage across? Do you manage them separately or do you want to manage it together? >> Probably at our maturity level, at this point we're probably really only at the governance stage. So we understand what we've got. We've got a good understanding of our cost structures in the public cloud. We don't nearly have as good as an understanding of our cost structures when we're doing hybrid deployments or on-prem deployments. And so that's probably as far as we've matured at this point, I would say. I think we do want to get to a future state where if we take other considerations in particular latency, the particular nature of that application or any other sovereignty or legal concerns outside, that we want to maintain maximum flexibility. Part of my role in the infrastructure group is to provide that kind of foundation. So, hoarding that workload is seamless across these different cloud providers and those application teams can really position the application where it is the best fit for purpose aligned with the price performance I have in mind. >> So bring it back to Nutanix for a little bit. Where do they fit? Talk about your journey a little bit. Maybe paint of picture of the infrastructure of the before, the after, what business impact it had. >> So there were really a couple of drivers for us through Nutanix. One of them is that as we moved a vast majority of our assets out of our data centers to these various cloud providers, we were left with a number of physical data centers and in many cases now, the only data centers that we're actually left with are our on-prem data centers that were no longer sized in accordance with the workload we want to maintain. Additionally for us, a lot of the investment of moving to the public cloud, we deferred a lot of the regular capital investments that we made in traditional infrastructure and we accepted the aging of that infrastructure but we recognize now that there is a fair amount of infrastructure there we need to maintain for these more local applications. And so, I wanted my team, I challenged my team last year to really take a modern approach, right? I don't want to necessarily assemble everything that we've done in the past, but in a much smaller scale to manage the local applications. I know that conversion, in particular hybrid converge, had matured pretty far by 2016. You know, what are the options out there? And so when we do our due diligence and we settled on Nutanix, we really felt that, it's both pioneering, at times even a little bit scary, because it was moving into a new foray with us. But I think it's worked out tremendously. We've started in our back office so that was actually really for that location if some mission critical workload in terms of how we actually do the fulfillment of our physical books, and we're in the process of bringing on a number of those applications off of traditional infrastructure with your segregation between your blade servers, and your chassis, and your racks, and your fiber storage, and your inline networking switches, and your storage array, and just having one condensed box that's going to run that system. >> So, for your in-house deployments, is that all Nutanix today or what's your mix? >> I'd say Nutanix is probably more, I'm getting up to the 20% range, and so 80% is still on traditional. But my goal is about a year from now that we'll, I don't know if they will be necessarily flipped but it will be more than 50 percent Nutanix. >> Is there anything that you're waiting for from Nutanix to be able to move those or is it just kind of budgets. >> It's our own people and process. >> Yeah, people and process. At this point, we're not, with any of these cloud providers, we're not as much hindered by the technology. The technology at this point is in many cases lapped our ability to actually consume it. We're drinking from several simultaneous fire hoses now, and it's which one we turn our mouths to, so. >> And you're taking advantage of Acropolis hypervisor or? >> Absolutely. That was also one of the key drivers. That was the hyper part of it really. I challenged the team. I said I want a solution where we can present a general purpose operating system and our application stack and to me bringing on a third party hypervisor at this point, it just felt like undifferentiated heavy lifting. >> And the container discussion, is Nutanix part of that too? >> Probably in our early stages. When we look at our workload right now, we don't have any on-prem workload that's been designated with containers. But I know having made the choice of Nutanix, if and when we come to that time, we'll be able to provision that on Nutanix and Acropolis. >> Not sure if you heard actually. This morning there was an announcement of partnership between Google and Nutanix so that should accelerate us on containers. >> I saw. That's very exciting. >> What's exciting about that to you? >> Well Google Cloud is one of the cloud providers we actively use today and I think they've really been a great thought leader in this space. We use a number of their services and I know they've really advanced the community around containers with Kubernetes and some of the technologies that they're working on. They have a very mature cloud offering today. And so I think the opportunity for us, that Google and Nutanix to work more closely together, I think a company like Scholastic is really only going to see the fruits, the benefits, of that relationship, and ease our growth into both platforms. >> Right. Adam, we have to leave it there. Thanks very much for coming on theCube and sharing your insights and your story. >> Adam: Appreciate it, appreciate it. Thanks having me on. >> You're very welcome. >> Adam: Okay. >> Alright keep it right there everybody. Stu and I'll be back with our next guest right after this short break. This is theCube. We're live from D.C. at Nutanix.Next. We'll be right back. (techno music)

(upbeat electronic music) >> Announcer: Live from Santa Clara, California, it's theCUBE covering Open Networking Summit 2017. Brought to you by The Linux Foundation. >> Hey, welcome back, everybody, Jeff Frick here with theCUBE. We are in Santa Clara, California at the Open Networking Summit 2017. Really happy to be joined by my co-host for the next couple of days, Scott Raynovich. And we've been talking to a lot of providers and technical people, but now we want to talk to customers. We love talking to customers, and we're really excited to have Rashesh Jethi. He's the SVP, Head of R&D for the Americas for Amadeus, which is a big travel company. Welcome. >> Thank you so much, Jeff. Thank you, Scott. >> So like I said, we'd love to talk to a practitioner. So you're out on the frontlines, you're seeing all this talk of software-defined and software-defined networking. From your point of view, how real is it, where are we on this journey? What do you see from your point of view? >> Super real. Have you searched for a flight lately? >> I have searched for a flight. >> Excellent. I'm proud to tell you that your flight search very likely was powered by Amadeus, and it's running on a software-defined data center completely. So this stuff is real. We are, I believe, one of the first companies who have actually taken this from what was a very strong academic kind of research project onto this start-up ecosystem, but we're actually out there deploying it, running real world business, using a very purposeful and deliberate software-defined strategy. >> And it's interesting because you said before we got on camera that you guys are actually very active participants in the open source movement and development of this stuff. You're not just kind of a participant waiting in the wings for this stuff to get developed. >> I mean absolutely, and to me, that's one of the reasons which if you're serious about open source, you have to use it. You can't just talk about it. You can't just say it looks like a nice idea. You have to get out there and get your hands dirty and do it. But the other thing also is you have to contribute back. I think that's a big tenet of the open source community. And we all and certainly the company, we grew up and we've seen tech evolve through the ages. And a big part, especially in the last 10 years or so, has been the open source movement, and it's contributing back. It's one of the reasons I'm here. It's one of the reasons the conference organizers invited me, is to actually talk about how we use open source and software-defined strategy for our technology. >> That's cool. So where do you run this software? You run it in private cloud, public cloud? Do you guys build your own data centers? How do you run it? >> Quick history lesson and our quick history-- >> Let's back up. First off, where is Amadeus today for people that aren't familiar with the company? >> We are actually a 30-year-old company. We are celebrating our 30th birthday this year. The company was started in the late '80s as a consortium between four leading European airlines, Lufthansa, Air France, Iberia, and Scandinavian. So we started off, which was very typical at that time, as a mainframe shop, and that's where a lot of our core systems were built. We're a big provider of technology in general to the travel industry even though we were founded by airlines. So to put it in perspective, we carry about 95% of the world's scheduled commercial seats, airline seats, on our platform. >> 95%. >> 95%, so we work with the world's-- >> Are available to purchase. Obviously, 95% of the purchases don't go through your system. >> Right. They are available. They are used by over 90,000 travel agents, retail travel agents, corporate travel, online travel. And we work with over, like I said, 700 airlines, work for their inventory. So chances are if you travel on an airplane, very good chances that our software was used to make the reservation. We also have airline ID systems and hotel ID systems, and we work with the airports. And this is where we do departure control, flight management, baggage reconciliation, a lot of the back end processes. And we started the company, essentially runs as we write our own software. We are offered as a service from day one, so we are one of the oldest software service providers in the industry. And obviously, when we got started to do that, you had to own your own infrastructure. So we are pretty good at it. We have very strong kind of technical chops. We have a large data center outside Munich Airport and a bunch of smaller data centers all over the world. And what we're doing now is really very deliberately making the journey towards a cloud, both our private cloud, so taking our own infrastructure, virtualizing it, and making it available as a service for our own applications, and then where it makes sense, to leverage public cloud infrastructures where they are available. >> So different apps in different clouds, is that-- >> Different apps in different clouds based on customer preferences. The core reservation booking engines, they are in our own private cloud because we do have a lot of regulatory security, privacy considerations. So that stuff, we keep kind of close where we can keep a very watchful eye on it, but there are a lot of transactions we are also talking about. The volume of searches has grown up, right? Obviously, Google has seen a lot of search volume. If you look at our business, it used to be when you wanted to book a flight, you'd go to a travel agent and be able to look at a bunch of flight options and you'd pick one. About 20 years ago, you call it the look to book ratios. You'd look at 10 to 20 options and you'd book one. You want to guess what it is today? >> The look to book ratio was 20 to one. That's got to be way higher. That's got to be 80 to one. >> It's more like 1,000 to one. >> 1,000 to one. >> 1,000 to one. It's partly people like you and I who have a spare moment and have a vacation in mind, and we are looking at options. But keep in mind, anything that you search, it has to come into our systems. We have to configure the journey. We have to price it. We have to make sure it's available before we offer it up to you, right? So it's very transaction and computing intensive even before it touches any of the back ends where we do core kind of booking and passenger processing. And so to handle that scale, those are the kind of very logical applications that make sense for the public cloud. And those are the ones that we've looked to move. Certainly, for customers, we are a global company. We have customers all over the world. Some customers want to have some of these systems closer to their geographic location. So we look at all use cases kind of. >> That's amazing to think of. These things have so changed behavior and the way that we interact. I assume that 20 to one was a function because you would sit down. Now you sit down at your desk, time to book that flight, and maybe you don't get it done that day. You come back two or three times. But as you said, now it's grabbing little bits of time throughout the day whenever we can. But do you get paid on a regular subscription, or do you get paid on the transaction? Has that just increased your overhead, whatever the ratio 20 to 1,000 is? >> Absolutely, no, our business model has been very consistent from day one. We get paid on the number of bookings we make and the number of people that board aircraft, I mean roughly speaking. There are smaller lines of businesses, but those are our two main revenue drivers. So we see a lot of transaction volume upfront, but it doesn't translate to a booking which logically, it won't. Yes, that's noise or revenue for us, but we still have to service that volume because that's eventually, the funnels just gotten wider. And so it makes sense to do that in the most cost efficient manner but without compromising quality, without compromising speed. I mean if you're like me, if you have to wait for more than two or three seconds, you're like, "Ah, I'm moving on." >> Oh, two seconds. It's milliseconds, isn't it? >> Absolutely. >> And by the way, I still don't always find the flight I want. So where are those extra flights? Can you provide those for your service? >> Jeff: That extra 5% those are under. >> That's very different. It's got nothing to do with open source and kind of what we're talking about here, but a lot of what you're doing in there from an engineering perspective is just looking at, for example, machine learning algorithms. And what you said is actually a very common complaint, is how do I find kind of the right sort of flights. And more importantly, if you have certain preferences with airports or airlines or loyalty programs or time of day, how do I provide you context-sensitive results? We are doing a lot of kind of core R&D work for that, but our customers are doing amazing work as well. KAYAK is one of our customers, very close to our offices in the Boston area, and they do pretty amazing work in terms of getting their context right and then applying machine learning technologies and artificial intelligence. It's very, very early days but very exciting, very promising. >> One of the cool features I like are these fare alerts. I don't know if you use them. It tells you, it predicts this is going to go up. You better book now, wait. Do you guys do that sort of thing too? >> Our customers do that. We have a very simple model. Our customers are travel agencies, online, American Express, Expedia, metasearches like KAYAK, Skyscanner, et cetera, the airlines themselves whose products we host in our system and we sell. So a lot of our engineering work is learning to offering kind of core innovation so that they can offer products for people like you and me, their customers, the best products out there. So we focus on enabling them. And then at an operational level, we try to do it in the most efficient manner and the most future proof that we can think of. >> What about security? I mean it sounds like a lot of sensitive data changing hands here, right, where are people going to sit on an airplane, where are they going. You must have incredible security demands on your data now. >> Yes. (Jeff and Scott laugh) I mean you understand, obviously, it's paramount to us. And the good news is, look, we've been in this business for 30 years. We have really deep domain expertise in that. And also, you'll understand why I wouldn't want to talk too much about what we do and how we do it, but absolutely, that's one of the-- >> Scott: You just lock it down. >> Prime drivers of everything we think all the way from application design to things like the infrastructure planning and design to the physical level. I mean everything you can think of and probably a couple of things you may not think of. >> Hopefully a few things we didn't think of. So where do you go next? It sounds like you're enabling a lot of the innovation on your partner's side. You just mentioned KAYAK and people writing some of the machine learning and AI algorithms to help the end traveler find what they're looking for. Where are you guys concentrating? You said you've been at it for 30 years. What are some of the next big hurdles that you're looking to take down? >> It's wonderful, I think, being close to our customers. And one of the reasons I'm in Boston, we are a European company. We are actually headquartered in Madrid. Our core engineering team, our central engineering team is in France. The reason I'm in Boston and my team is in Boston is we've started doing a lot of business here in North America, and we try to stay very close to our customers. And when you listen carefully, and that's why we have two ears and one mouth is to hopefully try to listen a lot, you do see their pain points, you do see where they are going with kind of their business. And it gives us a chance to have a front row seat in designing new products that they can use. So to me, it's kind of two pronged. One is we want to offer the best technology we can to our customers at the best price point we can. And obviously, by now, you've figured out it's mission critical stuff has to always be on. Keeping those kind of boundary conditions in mind, you want to be the best technology provider, and then we want to innovate. So one of the things I'm seeing at this conference, there's a lot of friends from the service providers who are talking about 5G technology. And so with connected cars, with virtual reality, I mean these are all trends that are going to impact us as travelers in a positive way. And so we have a dedicated innovation team across all our business lines. We do a lot of work with academic institutions, with ETH in Zurich, with MIT here, close to my office in Boston. And there's just a chockfull of possibilities in terms of what can be done. >> All right, I'll give you the last word, impressions on the show. What do you get out of a show like this? Why is it important for you to come? >> It's amazing. I mean this morning, Martin Casado was there. He's called kind of the grand daddy of software-defined networking (mumbles). >> He's not that old yet, but he's going to like seeing that clip. (laughs) >> It's true. I read that at The Guardian. It was on one of the newspapers. But the fact is we used NSX for virtualization in our entire data center, and we have close to 20,000 infrastructure devices. All our computers are virtualized, 100% of it, and it's all using NSX from VMware, right? Now this was a sort of brilliant idea by an extremely intelligent and persuasive graduate student at Stanford 15 years ago that is, as he announced this morning, is a billion-dollar business today, right? And we are actually using the technology, and it's very real, to process all of this. So it's great to be able to see what people like him, I mean from Google, he's a great partner of ours. We use Kubernetes for kind of the container deployment strategy for our cloud network. We hear him speak about what they're thinking about in terms of investments and how the network is going to essentially drive the movement of data analytics. It's just phenomenal to get the top leadership. I'm obviously very honored and privileged to be presenting to this audience and to share our thoughts and what we're doing and just to see a lot of the buzz around here and what wonderful ideas are happening in the Valley. There's so much action, as always, going on. >> Great, great, great summary. Well, glad you could take a few minutes to stop by theCUBE. >> Completely my pleasure. Thank you very much. Great meeting you, and have a great rest of the show. >> All right. He's Rashesh, he's Scott, I'm Jeff. You're watching theCUBE from Open Networking Summit 2017 in Santa Clara. We'll be back after this short break. Thanks for watching. (upbeat electronic music) >> Announcer: Robert Herjavec. >> People obviously know you from Shark Tank, but The Herjavec Group has been really laser focused on cybersecurity. >> I actually helped to bring upon Checkpoint to (mumbles) firewalls, URL filtering, that kind of stuff. >> But you're also...