>>from >>around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Everyone welcome back to the cubes Coverage of AWS reinvent 2020 virtual. This is the Cube virtual. I'm John for your host this year. We're not in person. We're doing remote interviews because of the pandemic. The whole events virtual over three weeks for this week would be having a lot of coverage in and out of what's going on with the news. All that stuff here happening on the Cube Our next guest is a featured segment. Brown Venkatesh, VP of Engineering at Cloudera. Welcome back to the Cube Cube Alumni. Last time you were on was 2018 when we had physical events. Great to see you, >>like good to be here. Thank you. >>S O. You know, Cloudera obviously modernized up with Horton works. That comedy has been for a while, always pioneering this abstraction layer originally with a dupe. Now, with data, all those right calls were made. Data is hot is a big part of reinvent. That's a big part of the theme, you know, machine learning ai ai edge edge edge data lakes on steroids, higher level services in the cloud. This is the focus of reinvents. The big conversations Give us an update on cloud eras. Data platform. What's that? What's new? >>Absolutely. You are really speaking of languages. Read with the whole, uh, data lake architecture that you alluded to. It's uploaded. This mission has always been about, you know, we want to manage how the world's data that what this means for our customers is being ableto aggregate data from lots of different sources into central places that we call data lakes on. Then apply lots of different types of passing to it to direct business value that would cdp with Florida data platform. What we have essentially done is take those same three core tenants around data legs multifunctional takes on data stewardship of management to add on a bunch off cloud native capabilities to it. So this was fundamentally I'm talking about things like disaggregated storage and compute by being able to now not only take advantage of H d efs, but also had a pretty deep, fundamental level club storage. But this is the form factor that's really, really good for our customers. Toe or to operate that from a TCO perspective, if you're going to manage hundreds of terabytes of data like like a lot of a lot of customers do it. The second key piece that we've done with CDP has to do with us embracing containers and communities in a big way on primer heritages around which machines and clusters and things of that nature. But in the cloud context, especially in the context, off managed community services like Amazon CKs, this Lexus spin apart traditional workloads, Sequels, park machine learning and so on. In the context of these Cuban exiles containerized environments which lets customers spin these up in seconds. They're supposed to, you know, tens of minutes on as they're passing, needs grow and shrink. They can actually scale much, much faster up and down to, you know, to make sure that they have the right cost effective footprint for their compute e >>go ahead third piece. >>But the turkey piece of all of this right is to say, along with like cloud native orchestration and cloud NATO storage is that we've embraced this notion of making sure that you actually have a robust data discovery story around it. so increasingly the data sets that you create on top off a platform like CDP. There themselves have value in other use cases that you want to make sure that these data sets are properly replicated. They're probably secure the public government. So you can go and analyze where the data set came from. Capabilities of security and provenance are increasingly more important to our customers. So with CDP, we have a really good story around that data stewardship aspect, which is increasingly important as you as you get into the cloud. And you have these sophisticated sharing scenarios. The >>you know, Clotaire has always had and Horton works. Both companies had strong technical chops. It's well document. Certainly the queues been toe all the events and covered both companies since the inception of 10 years ago. A big data. But now we're in cloud. Big data, fast data, little data, all data. This is what the cloud brings. So I want to get your thoughts on the number one focus of problem solving around cloud. I gotta migrate. Or do I move to the cloud immediately and be born there? Now we know the hyper scale is born in the cloud companies like the Dropbox in the world. They were born in the cloud and all the benefits and goodness came with that. But I'm gonna be pivoting. I'm a company at a co vid with a growth strategy. Lift and shift. Okay, that was It's over. Now that's the low hanging fruit that's use cases kind of done. Been there, done that. Is it migration or born in the cloud? Take us through your thoughts on what does the company do right now? >>E thinks it's a really good question. If you think off, you know where our customers are in their own data journey, right? So increasingly. You know, a few years ago, I would say it was about operating infrastructure. That's where their head was at, right? Increasingly, I think for them it's about deriving value from the data assets that they already have on. This typically means in a combining data from different sources the structure data, some restructure data, transactional data, non transactional, data event oriented data messaging data. They wanna bring all of that and analyze that to make sure that they can actually identify ways toe monetize it in ways that they had not thought about when they actually stored the data originally, right? So I think it's this drive towards increasing monetization of data assets that's driving the new use cases on the platform. Traditionally, it used to be about, you know, sequel analysts who are, if you are like a data scientist using a party's park. So it was sort of this one function that you would focus on with the data. But increasingly, we're seeing these air about, you know, these air collaborative use cases where you wanna have a little bit of sequel, a little bit of machine learning, a little bit off, you know, potentially real time streaming or even things like Apache fling that you're gonna use to actually analyze the data eso when this kind of an environment. But we see that the data that's being generated on Prem is extremely relevant to the use case, but the speed at which they want to deploy the use case. They really want to make sure that they can take advantage of the clouds, agility and infinite capacity to go do that. So it's it's really the answer is it's complicated. It's not so much about you know I'm gonna move my data platform that I used to run the old way from here to there. But it's about I got this use case and I got to stand this up in six weeks, right in the middle of the pandemic on how do I go do that on the data that has to come from my existing line of business systems. I'm not gonna move those over, but I want to make sure that I can analyze the data from their in some cohesive Does that make sense? >>Totally makes sense. And I think just to kind of bring that back for the folks watching. And I remember when CDP was launching the thes data platforms, it really was to replace the data warehouse is the old antiquated way of doing things. But it was interesting. It wasn't just about competing at that old category. It was a new category. So, yeah, you had to have some tooling some sequel, you know, to wrangle data and have some prefabricated, you know, data fenced out somewhere in some warehouse. But the value was the new use cases of data where you never know. You don't know where it's going to come until it comes right, because if you make it addressable, that was the idea of the data platform and data Lakes and then having higher level services. So s so to me. That's, I think, one distinction kind of new category coexisting and disrupting an old category data warehousing. Always bought into that. You know, there's some technical things spark Do all these elements on mechanisms underneath. That's just evolution. But income in incomes cloud on. I want to get your thoughts on this because one of the things that's coming out of all my interviews is speed, speed, speed, deploying high, high, large scale at very large speed. This is the modern application thinking okay to make that work, you gotta have the data fabric underneath. This has always been kind of the dream scenario, So it's kind of playing out. So one Do you believe in that? And to what is the relationship between Cloudera and AWS? Because I think that kind of interestingly points to this one piece. >>Absolutely. So I think that yeah, from my perspective, this is what we call the shared data experience that's central to see PP like the idea is that, you know, data that is generated by the business in one use case is relevant and valid in another use case that is central to how we see companies leveraging data or the second order monetization that they're after, Right? So I think this is where getting out off a traditional data warehouse like data side of context, being able to analyze all of the data that you have, I think is really, really important for many of our customers. For example, many of them increasingly hold what they call this like data hackathons right where they're looking at can be answered. This new question from all the data that we have that is, that is a type of use case that's really hard to enable unless you have a very cohesive, very homogeneous view off all of your data. When it comes to the cloud partners, right, Increasingly, we see that the cloud native services, especially for the core storage, compute and security services are extremely robust that they give us, you know, the scale and that's really truly unparalled in terms of how much data we can address, how quickly we can actually get access to compute on demand when we need it. And we can do all of this with, like, a very, very mature security and governance fabric that you can fit into. So we see that, you know, technologies like s three, for example, have come a long way on along the journey with Amazon on this over the last 78 years. But we both learned how to operate our work clothes. When you're running a terabytes scale, right, you really have to pay attention to matters like scale out and consistency and parallelism and all of these things. These matters significantly right? And it's taken a certain maturity curve that you have to go through to get there. The last part of that is that because the TCO is so optimized with the customer to operate this without any ops on their side, they could just start consuming data, even if it's a terabyte of data. So this means that now we have to have the smarts in the processing engines to think about things like cashing, for example very, very differently because the way you cash data that Zinn hedge defense is very different from how you would do that in the context of his three are similarly, the way you think about consistency and metadata is very, very different at that layer. But we made sure that we can abstract these differences out at the platform layer so that as an as it is an application consumer, you really get the same experience, whether you're running these analytics on clam or whether you're running them in the cloud. And that's really central to how I see this space evolving is that we want to meet the customer where they are, rather than forcing them to change the way they work because off the platform that they're simple. >>So could you take them in to explain some of the integrations with AWS and some customer examples? Because, um, you know, first of all, cost is a big concern on everyone's mind because, you know, it's still lower costs and higher value with the cloud anyway. But it could get away from you. So you know, you're constantly petabytes of scale. There's a lot of data moving around. That's one thing to integration with higher level services. Can you give where does explain how Claudia integration with Amazon? What's the relation of customer wants to know. Hey, you guys, you know, partnering, explain the partnership. And what does it mean for me? >>Absolutely. So the way we look at the partnership hit that one person and ghetto. It's really a four layer cake because the lowest layer is the core infrastructure services. We talked about storage and computing on security, and I am so on and so forth. So that layer is a very robust integration that goes back a few years. The next layer up from that has to do with increasingly, you know, as our customers use analytic experiences from Florida on, they want to combine that with data that's actually in the AWS compute experiences like the red Ship, for example. That's what the analytics layer uploaded the data warehouse offering and how that interrupts would be other services in Amazon that could be relevant. This is common file formats that open source well form it really help us in this context to make sure that they have a very strong level of interest at the analytics there. The third layer up from that has to do with consumption. Like if you're gonna bring an analyst on board. You want to make sure that all of their sequel, like analyst experiences, notebooks, things of that nature that's really strong. And club out of the third layer on the highest layer is really around. Data sharing. That's as aws new and technologies like that become more prevalent. Now. Customers want to make sure that they can have these data states that they have in the different clouds, actually in a robbery. So we provide ways for them, toe browse and search data, regardless of whether that data is on AWS or on traffic. And so that's how the fourth layer in the stack, the vertical slice running through all of these, that we have a really strong business relationship with them both on the on the on the commercial market side as well as in AWS marketplace. Right? So we can actually by having cdp be a part of it of the US marketplace. This means that if you have an enterprise agreement with with Amazon, you can actually pay for CDP toe the credit sexuality purchased. This is a very, very tight relationship that's designed again for these large scale speeds and feeds. Can the customer >>so just to get this right. So if I love the four layer cake icings the success of CDP love that birthday candles can be on top to when you're successful. But you're saying that you're going to mark with Amazon two ways marketplace listing and then also jointly with their enterprise field programs. That right? You say because they have this program you can bundle into the blanket pos or Pio processes That right can explain that again. >>S so if you think this'll states, if you're talking about are significant. So we want to make sure that, you know, we're really aligned with them in terms off our cloud migration strategy in terms of how the customer actually execute to what is a fairly you know, it's a complex deployment to deploy a large multiple functions did and existed takes time, right, So we're gonna make sure that we navigate this together jointly with the U. S. To make sure that from a best practices standpoint, for example, were very well aligned from a cost standpoint, you know what we're telling the customer architecturally is very rather nine. That's that's where I think really the heart of the engineering relationship between the two companies without. >>So if you want Cloudera on Amazon, you just go in. You can click to buy. Or if you got to deal with Amazon in terms of global marketplace deal, which they have been rolling out, I could buy there too, Right? All right, well, run. Thanks for the update and insight. Um, love the four layer cake love gets. See the modernization of the data platform from Cloudera. And congratulations on all the hard work you guys been doing with AWS. >>Thank you so much. Appreciate. >>Okay, good to see you. Okay, I'm John for your hearing. The Cube for Cube virtual for eight of us. Reinvent 2020 virtual. Thanks for watching.

Live from New York It's theCUBE! Covering theCUBE New York City 2018 Brought to you by Silicon Angle Media and it's ecosystem partners >> Hey welcome back and we're live in theCUBE in New York city. It's our 2nd day of two days of coverage CUBE NYC. The hashtag CUBENYC Formerly Big data NYC renamed because it's about big data, it's about the server, it's about Cooper _________'s multi-cloud data. It's all about data, and that's the fundamental change in the industry. Our next guest is Yaron Haviv, who's the CTO of Iguazio, key alumni, always coming out with some good commentary smart analysis. Kind of a guest host as well as an industry participant supplier. Welcome back to theCUBE. Good to see you. >> Thank you John. >> Love having you on theCUBE because you always bring some good insight and we appreciate that. Thank you so much. First, before we get into some of the comments because I really want to delve into comments that David Richards said a few years ago, CEO of RenDisco. He said, "Cloud's going to kill Hadoop". And people were looking at him like, "Oh my God, who is this heretic? He's crazy. What is he talking about?" But you might not need Hadoop, if you can run server less Spark, Tensorflow.... You talk about this off camera. Is Hadoop going to be the open stack of the big data world? >> I don't think cloud necessary killed Hadoop, although it is working on that, you know because you go to Amazon and you know, you can consume a bunch of services and you don't really need to think about Hadoop. I think cloud native serve is starting to kill Hadoop, cause Hadoop is three layers, you know, it's a file system, it's DFS, and then you have server scheduling Yarn, then you have applications starting with map produce and then you evolve into things like Spark. Okay, so, file system I don't really need in the cloud. I use Asfree, I can use a database as a service, as you know, pretty efficient way of storing data. For scheduling, Kubernetes is a much more generic way of scheduling workloads and not confined to Spark and specific workloads. I can run with Dancerflow, I can run with data science tools, etc., just containerize. So essentially, why would I need Hadoop? If I can take the traditional tools people are now evolving in and using like Jupiter Notebooks, Spark, Dancerflow, you know, those packages with Kubernetes on top of a database as a service and some object store, I have a much easier stack to work with. And I could mobilize that whether it's in the cloud, you know on different vendors. >> Scale is important too. How do you scale it? >> Of course, you have independent scaling between data and computation, unlike Hadoop. So I can just go to Google, and use Vquery, or use, you know, DynamoDB on Amazon or Redchick, or whatever and automatically scale it down and then, you know >> That's a unique position, so essentially, Hadoop versus Kubernetes is a top-line story. And wouldn't that be ironic for Google, because Google essentially created Map Produce and Coudera ran with it and went public, but when we're talking about 2008 timeframe, 2009 timeframe, back when ventures with cloud were just emerging in the mainstream. So wouldn't it be ironic Kubernetes, which is being driven by Google, ends up taking over Hadoop? In terms of running things on Kubernetes and cloud eight on Visa Vis on premise with Hadoop. >> The poster is tend to give this comment about Google, but essentially Yahoo started Hadoop. Google started the technology  and couple of years after Hadoop started, with Google they essentially moved to a different architecture, with something called Percolator. So Google's not too associated with Hadoop. They're not really using this approach for a long time. >> Well they wrote the map-produced paper and the internal conversations we report on theCUBE about Google was, they just let that go. And Yahoo grabbed it. (cross-conversation) >> The companies that had the most experience were the first to leave. And I think it may respect what you're saying. As the marketplace realizes the outcomes of the dubious associate with, they will find other ways of achieving those outcomes. It might be more depth. >> There's also a fundamental shift in the consumption where Hadoop was about a ranking pages in a batch form. You know, just collecting logs and ranking pages, okay. The chances that people have today revolve around applying AI to business application. It needs to be a lot more concurring, transactional, real-time ish, you know? It's nothing to do with Hadoop, okay? So that's why you'll see more and more workers, mobilizing different black server functions, into service pre-canned services, etc. And Kubernetes playing a good role here is providing the trend. Transport for migrating workloads across cloud providers, because I can use GKE, the Google Kubenetes, or Amazon Kubernetes, or Azure Kubernetes, and I could write a similar application and deploy it on any cloud, or on Clam on my own private cluster. It makes the infrastructure agnostic really application focused. >> Question about Kubernetes we heard on theCUBE earlier, the VP of Project BlueData said that Kubernetes ecosystem and community needs to do a better job with Stapla, they nailed Stapflalis, Stafle application support is something that they need help on. Do you agree with that comment, and then if so, what alternatives do you have for customers who care about Stafe? >> They should use our product (laughing) >> (mumbling) Is Kubernetes struggling there? And if so, talk about your product >> So, I think that our challenge is rounded that there are many solutions in that. I think that they are attacking it from a different approach Many of them are essentially providing some block storage to different containers on really cloud 90. What you want to be able is to have multiple containers access the same data. That means either sharing through file systems, for objects or through databases because one container is generating, for example, ingestion or __________. Another container is manipulating that same data. A third container may look for something in the data, and generate a trigger or an action. So you need shared access to data from those containers. >> The rest of the data synchronizes all three of those things. >> Yes because the data is the form of state. The form of state cannot be associated with the same container, which is what most of where I am very active and sincere in those committees, and you have all the storage guys in the committees, and they think the block story just drag solution. Cause they still think like virtual machines, okay? But the general idea is that if you think about Kubernetes is like the new OS, where you have many processes, they're just scattered around. In OS, the way for us to share state between processes an OS, is whether through files, or through databases, in those form. And that's really what >> Threads and databases as a positive engagement. >> So essentially I gave maybe two years ago, a session at KubeCon in Europe about what we're doing on storing state. It's really high-performance access from those container processes to our database. Impersonate objects, files, streams or time series data, etc And then essentially, all those workloads just mount on top of and we can all share stape. We can even control the access for each >> Do you think you nailed the stape problem? >> Yes, by the way, we have a managed service. Anyone could go today to our cloud, to our website, that's in our cloud. It gets it's own Kubernetes cluster, a provision within less than 10 minutes, five to 10 minutes. With all of those services pre-integrated with Spark, Presto, ______________, real-time, these services functions. All that pre-configured on it's own time. I figured all of these- >> 100% compatible with Kubernetes, it's a good investment >> Well we're just expanding it to Kubernetes stripes, now it's working on them, Amazon Kubernetes, EKS I think, we're working on AKS and GK. We partner with Azure and Google. And we're also building an ad solution that is essentially exactly the same stock. Can run on an edge appliance in a factory. You can essentially mobilize data and functions back and forth. So you can go and develop your work loads, your application in the cloud, test it under simulation, push a single button and teleport the artifacts into the edge factory. >> So is it like a real-time Kubernetes? >> Yes, it's a real-time Kubernetes. >> If you _______like the things we're doing, it's all real-time. >> Talk about real-time in the database world because you mentioned time-series databases. You give objects store versus blog. Talk about time series. You're talking about data that is very relevant in the moment. And also understanding time series data. And then, it's important post-event, if you will, meaning How do you store it? Do you care? I mean, it's important to manage the time series. At the same time, it might not be as valuable as other data, or valuable at certain points and time, which changes it's relationship to how it's stored and how it's used. Talk about the dynamic of time series.. >> Figured it out in the last six or 12 months that since real-time is about time series. Everything you think about real-time censored data, even video is a time-series of frames, okay And what everyone wants to do is just huge amount of time series. They want to cross-correlate it, because for example, you think about stock tickers you know, the stock has an impact from news feeds or Twitter feeds, or of a company or a segment. So essentially, what they need to do is something called multi-volume analysis of multiple time series to be able to extract some meaning, and then decide if you want to sell or buy a stock, as in vacation example. And there is a huge gap in the solution in that market, because most of the time series databases were designed for operational databases, you know, things that monitor apps. Nothing that injects millions of data points per second, and cross-correlates and run real-time AI analytics. Ah, so we've essentially extended because we have a programmable database essentially under the hoop. We've extended it to support time series data with about 50 to 1 compression ratio, compared to some other solutions. You know we've break with the customer, we've done sizing, they told them us they need half a pitabyte. After a small sizing exercise, about 10 to 20 terabytes of storage for the same data they stored in Kassandra for 500 terabytes. No huge ingestion rates, and what's very important, we can do an in-flight with all those cross-correlations, so, that's something that's working very well for us. >> This could help on smart mobility. Kenex 5G comes on, certainly. Intelligent edge. >> So the customers we have, these cases that we applied right now is in financial services, two or three main applications. One is tick data and analytics, everyone wants to be smarter learning on how to buy and sell stocks or manage risk, the second one is infrastructure, monitoring, critical infrastructure, monitoring is SLA monitoring is be able to monitor network devices, latencies, applications, you now, transaction rate, or that, be able to predict potential failures or escalation We have similar applications; we have about three Telco customers using it for real-time time. Series analytics are metric data, cybersecurity attacks, congestion avoidance, SLA management, and also automotive. Fleet management, file linking, they are also essentially feeding huge data sets of time series analytics. They're running cross-correlation and AI logic, so now they can generate triggers. Now apply to Hadoop. What does Hadoop have anything to do with those kinds of applications? They cannot feed huge amounts of datasets, they cannot react in real-time, doesn't store time-series efficiently. >> Hapoop (laughing) >> You said that. >> Yeah. That's good. >> One, I know we don't have a lot of time left. We're running out of time, but I want to make sure we get this out here. How are you engaging with customers? You guys got great technical support. We can vouch for the tech chops that you guys have. We seen the solution. If it's compatible to Kubernetes, certainly this is an alternative to have really great analytical infrastructure. Cloud native, goodness of your building, You do PFC's, they go to your website, and how do you engage, how do you get deals? How do people work with you? >> So because now we have a cloud service, so also we engage through the cloud. Mainly, we're going after customers and leads, or from webinars and activities on the internet, and we sort of follow-up with those customers, we know >> Direct sales? >> Direct sales, but through lead generation mechanism. Marketplace activity, Amazon, Azure, >> Partnerships with Azure and Google now. And Azure joint selling activities. They can actually resale and get compensated. Our solution is an edge for Azure. Working on similar solution for Google. Very focused on retailers. That's the current market focus of since you think about stores that have a single supermarket will have more than a 1,000 cameras. Okay, just because they're monitoring shelves in real-time, think about Amazon go, kind of replication. Real-time inventory management. You cannot push a 1,000 camera feeds into the cloud. In order to analyze it then decide on inventory level. Proactive action, so, those are the kind of applications. >> So bigger deals, you've had some big deals. >> Yes, we're really not a raspberry pie-kind of solution. That's where the bigger customers >> Got it. Yaron, thank you so much. The CTO of Iguazio Check him out. It's actually been great commentary. The Hadoop versus Kubernetes narrative. Love to explore that further with you. Stay with us for more coverage after this short break. We're live in day 2 of CUBE NYC. Par Strata, Hadoop Strata, Hadoop World. CUBE Hadoop World, whatever you want to call it. It's all because of the data. We'll bring it to ya. Stay with us for more after this short break. (upbeat music)

>> PA Announcer: Off the plastic tab, and we'll turn on the colors. Welcome to New Orleans. ♪ This is it ♪ ♪ The part when I say I don't want ya ♪ ♪ I'm stronger than I've been before ♪ ♪ This is the part when I set your free ♪ (New Orleans jazz music) ("When the Saints Go Marching In") (rock music) >> PA Announcer: Ladies and gentleman, would you please welcome state of Louisiana chief design officer Matthew Vince and Choice Hotels director of infrastructure services Stacy Nigh. (rock music) >> Well good morning New Orleans, and welcome to my home state. My name is Matt Vince. I'm the chief design office for state of Louisiana. And it's my pleasure to welcome you all to .Next 2018. State of Louisiana is currently re-architecting our cloud infrastructure and Nutanix is the first domino to fall in our strategy to deliver better services to our citizens. >> And I'd like to second that warm welcome. I'm Stacy Nigh director of infrastructure services for Choice Hotels International. Now you may think you know Choice, but we don't own hotels. We're a technology company. And Nutanix is helping us innovate the way we operate to support our franchisees. This is my first visit to New Orleans and my first .Next. >> Well Stacy, you're in for a treat. New Orleans is known for its fabulous food and its marvelous music, but most importantly the free spirit. >> Well I can't wait, and speaking of free, it's my pleasure to introduce the Nutanix Freedom video, enjoy. ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ Ah, ah, ♪ ♪ Ah, ah, ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I lose everything, so I can sing ♪ ♪ Hallelujah I'm free ♪ ♪ I'm free, I'm free, I'm free, I'm free ♪ ♪ Gritting your teeth, you hold onto me ♪ ♪ It's never enough, I'm never complete ♪ ♪ Tell me to prove, expect me to lose ♪ ♪ I push it away, I'm trying to move ♪ ♪ I'm desperate to run, I'm desperate to leave ♪ ♪ If I lose it all, at least I'll be free ♪ ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> PA Announcer: Ladies and gentlemen, please welcome chief marketing officer Ben Gibson ♪ Ah, ah ♪ ♪ Ah, ah ♪ ♪ Hallelujah, I'm free ♪ >> Welcome, good morning. >> Audience: Good morning. >> And welcome to .Next 2018. There's no better way to open up a .Next conference than by hearing from two of our great customers. And Matthew, thank you for welcoming us to this beautiful, your beautiful state and city. And Stacy, this is your first .Next, and I know she's not alone because guess what It's my first .Next too. And I come properly attired. In the front row, you can see my Nutanix socks, and I think my Nutanix blue suit. And I know I'm not alone. I think over 5,000 people in attendance here today are also first timers at .Next. And if you are here for the first time, it's in the morning, let's get moving. I want you to stand up, so we can officially welcome you into the fold. Everyone stand up, first time. All right, welcome. (audience clapping) So you are all joining not just a conference here. This is truly a community. This is a community of the best and brightest in our industry I will humbly say that are coming together to share best ideas, to learn what's happening next, and in particular it's about forwarding not only your projects and your priorities but your careers. There's so much change happening in this industry. It's an opportunity to learn what's coming down the road and learn how you can best position yourself for this whole new world that's happening around cloud computing and modernizing data center environments. And this is not just a community, this is a movement. And it's a movement that started quite awhile ago, but the first .Next conference was in the quiet little town of Miami, and there was about 800 of you in attendance or so. So who in this hall here were at that first .Next conference in Miami? Let me hear from you. (audience members cheering) Yep, well to all of you grizzled veterans of the .Next experience, welcome back. You have started a movement that has grown and this year across many different .Next conferences all over the world, over 20,000 of your community members have come together. And we like to do it in distributed architecture fashion just like here in Nutanix. And so we've spread this movement all over the world with .Next conferences. And this is surging. We're also seeing just today the current count 61,000 certifications and climbing. Our Next community, close to 70,000 active members of our online community because .Next is about this big moment, and it's about every other day and every other week of the year, how we come together and explore. And my favorite stat of all. Here today in this hall amongst the record 5,500 registrations to .Next 2018 representing 71 countries in whole. So it's a global movement. Everyone, welcome. And you know when I got in Sunday night, I was looking at the tweets and the excitement was starting to build and started to see people like Adile coming from Casablanca. Adile wherever you are, welcome buddy. That's a long trip. Thank you so much for coming and being here with us today. I saw other folks coming from Geneva, from Denmark, from Japan, all over the world coming together for this moment. And we are accomplishing phenomenal things together. Because of your trust in us, and because of some early risk candidly that we have all taken together, we've created a movement in the market around modernizing data center environments, radically simplifying how we operate in the services we deliver to our businesses everyday. And this is a movement that we don't just know about this, but the industry is really taking notice. I love this chart. This is Gartner's inaugural hyperconvergence infrastructure magic quadrant chart. And I think if you see where Nutanix is positioned on there, I think you can agree that's a rout, that's a homerun, that's a mic drop so to speak. What do you guys think? (audience clapping) But here's the thing. It says Nutanix up there. We can honestly say this is a win for this hall here. Because, again, without your trust in us and what we've accomplished together and your partnership with us, we're not there. But we are there, and it is thanks to everyone in this hall. Together we have created, expanded, and truly made this market. Congratulations. And you know what, I think we're just getting started. The same innovation, the same catalyst that we drove into the market to converge storage network compute, the next horizon is around multi-cloud. The next horizon is around whether by accident or on purpose the strong move with different workloads moving into public cloud, some into private cloud moving back and forth, the promise of application mobility, the right workload on the right cloud platform with the right economics. Economics is key here. If any of you have a teenager out there, and they have a hold of your credit card, and they're doing something online or the like. You get some surprises at the end of the month. And that surprise comes in the form of spiraling public cloud costs. And this isn't to say we're not going to see a lot of workloads born and running in public cloud, but the opportunity is for us to take a path that regains control over infrastructure, regain control over workloads and where they're run. And the way I look at it for everyone in this hall, it's a journey we're on. It starts with modernizing those data center environments, continues with embracing the full cloud stack and the compelling opportunity to deliver that consumer experience to rapidly offer up enterprise compute services to your internal clients, lines of businesses and then out into the market. It's then about how you standardize across an enterprise cloud environment, that you're not just the infrastructure but the management, the automation, the control, and running any tier one application. I hear this everyday, and I've heard this a lot already this week about customers who are all in with this approach and running those tier one applications on Nutanix. And then it's the promise of not only hyperconverging infrastructure but hyperconverging multiple clouds. And if we do that, this journey the way we see it what we are doing is building your enterprise cloud. And your enterprise cloud is about the private cloud. It's about expanding and managing and taking back control of how you determine what workload to run where, and to make sure there's strong governance and control. And you're radically simplifying what could be an awfully complicated scenario if you don't reclaim and put your arms around that opportunity. Now how do we do this different than anyone else? And this is going to be a big theme that you're going to see from my good friend Sunil and his good friends on the product team. What are we doing together? We're taking all of that legacy complexity, that friction, that inability to be able to move fast because you're chained to old legacy environments. I'm talking to folks that have applications that are 40 years old, and they are concerned to touch them because they're not sure if they can react if their infrastructure can meet the demands of a new, modernized workload. We're making all that complexity invisible. And if all of that is invisible, it allows you to focus on what's next. And that indeed is the spirit of this conference. So if the what is enterprise cloud, and the how we do it different is by making infrastructure invisible, data centers, clouds, then why are we all here today? What is the binding principle that spiritually, that emotionally brings us all together? And we think it's a very simple, powerful word, and that word is freedom. And when we think about freedom, we think about as we work together the freedom to build the data center that you've always wanted to build. It's about freedom to run the applications where you choose based on the information and the context that wasn't available before. It's about the freedom of choice to choose the right cloud platform for the right application, and again to avoid a lot of these spiraling costs in unanticipated surprises whether it be around security, whether it be around economics or governance that come to the forefront. It's about the freedom to invent. It's why we got into this industry in the first place. We want to create. We want to build things not keep the lights on, not be chained to mundane tasks day by day. And it's about the freedom to play. And I hear this time and time again. My favorite tweet from a Nutanix customer to this day is just updated a lot of nodes at 38,000 feed on United Wifi, on my way to spend vacation with my family. Freedom to play. This to me is emotionally what brings us all together and what you saw with the Freedom video earlier, and what you see here is this new story because we want to go out and spread the word and not only talk about the enterprise cloud, not only talk about how we do it better, but talk about why it's so compelling to be a part of this hall here today. Now just one note of housekeeping for everyone out there in case I don't want anyone to take a wrong turn as they come to this beautiful convention center here today. A lot of freedom going on in this convention center. As luck may have it, there's another conference going on a little bit down that way based on another high growth, disruptive industry. Now MJBizCon Next, and by coincidence it's also called next. And I have to admire the creativity. I have to admire that we do share a, hey, high growth business model here. And in case you're not quite sure what this conference is about. I'm the head of marketing here. I have to show the tagline of this. And I read the tagline from license to launch and beyond, the future of the, now if I can replace that blank with our industry, I don't know, to me it sounds like a new, cool Sunil product launch. Maybe launching a new subscription service or the like. Stay tuned, you never know. I think they're going to have a good time over there. I know we're going to have a wonderful week here both to learn as well as have a lot of fun particularly in our customer appreciation event tonight. I want to spend a very few important moments on .Heart. .Heart is Nutanix's initiative to promote diversity in the technology arena. In particular, we have a focus on advancing the careers of women and young girls that we want to encourage to move into STEM and high tech careers. You have the opportunity to engage this week with this important initiative. Please role the video, and let's learn more about how you can do so. >> Video Plays (electronic music) >> So all of you have received these .Heart tokens. You have the freedom to go and choose which of the four deserving charities can receive donations to really advance our cause. So I thank you for your engagement there. And this community is behind .Heart. And it's a very important one. So thank you for that. .Next is not the community, the moment it is without our wonderful partners. These are our amazing sponsors. Yes, it's about sponsorship. It's also about how we integrate together, how we innovate together, and we're about an open community. And so I want to thank all of these names up here for your wonderful sponsorship of this event. I encourage everyone here in this room to spend time, get acquainted, get reacquainted, learn how we can make wonderful music happen together, wonderful music here in New Orleans happen together. .Next isn't .Next with a few cool surprises. Surprise number one, we have a contest. This is a still shot from the Freedom video you saw right before I came on. We have strategically placed a lucky seven Nutanix Easter eggs in this video. And if you go to Nutanix.com/freedom, watch the video. You may have to use the little scrubbing feature to slow down 'cause some of these happen quickly. You're going to find some fun, clever Easter eggs. List all seven, tweet that out, or as many as you can, tweet that out with hashtag nextconf, C, O, N, F, and we'll have a random drawing for an all expenses paid free trip to .Next 2019. And just to make sure everyone understands Easter egg concept. There's an eighth one here that's actually someone that's quite famous in our circles. If you see on this still shot, there's someone in the back there with a red jacket on. That's not just anyone. We're targeting in here. That is our very own Julie O'Brien, our senior vice president of corporate marketing. And you're going to hear from Julie later on here at .Next. But Julie and her team are the engine and the creativity behind not only our new Freedom campaign but more importantly everything that you experience here this week. Julie and her team are amazing, and we can't wait for you to experience what they've pulled together for you. Another surprise, if you go and visit our Freedom booths and share your stories. So they're like video booths, you share your success stories, your partnerships, your journey that I talked about, you will be entered to win a beautiful Nutanix brand compliant, look at those beautiful colors, bicycle. And it's not just any bicycle. It's a beautiful bicycle made by our beautiful customer Trek. I actually have a Trek bike. I love cycling. Unfortunately, I'm not eligible, but all of you are. So please share your stories in the Freedom Nutanix's booths and put yourself in the running, or in the cycling to get this prize. One more thing I wanted to share here. Yesterday we had a great time. We had our inaugural Nutanix hackathon. This hackathon brought together folks that were in devops practices, many of you that are in this room. We sold out. We thought maybe we'd get four or five teams. We had to shutdown at 14 teams that were paired together with a Nutanix mentor, and you coded. You used our REST APIs. You built new apps that integrated in with Prism and Clam. And it was wonderful to see this. Everyone I talked to had a great time on this. We had three winners. In third place, we had team Copper or team bronze, but team Copper. Silver, Not That Special, they're very humble kind of like one of our key mission statements. And the grand prize winner was We Did It All for the Cookies. And you saw them coming in on our Mardi Gras float here. We Did It All for Cookies, they did this very creative job. They leveraged an Apple Watch. They were lighting up VMs at a moments notice utilizing a lot of their coding skills. Congratulations to all three, first, second, and third all receive $2,500. And then each of them, then were able to choose a charity to deliver another $2,500 including Ronald McDonald House for the winner, we did it all for the McDonald Land cookies, I suppose, to move forward. So look for us to do more of these kinds of events because we want to bring together infrastructure and application development, and this is a great, I think, start for us in this community to be able to do so. With that, who's ready to hear form Dheeraj? You ready to hear from Dheeraj? (audience clapping) I'm ready to hear from Dheeraj, and not just 'cause I work for him. It is my distinct pleasure to welcome on the stage our CEO, cofounder and chairman Dheeraj Pandey. ("Free" by Broods) ♪ Hallelujah, I'm free ♪ >> Thank you Ben and good morning everyone. >> Audience: Good morning. >> Thank you so much for being here. It's just such an elation when I'm thinking about the Mardi Gras crowd that came here, the partners, the customers, the NTCs. I mean there's some great NTCs up there I could relate to because they're on Slack as well. How many of you are in Slack Nutanix internal Slack channel? Probably 5%, would love to actually see this community grow from here 'cause this is not the only even we would love to meet you. We would love to actually do this in a real time bite size communication on our own internal Slack channel itself. Now today, we're going to talk about a lot of things, but a lot of hard things, a lot of things that take time to build and have evolved as the industry itself has evolved. And one of the hard things that I want to talk about is multi-cloud. Multi-cloud is a really hard problem 'cause it's full of paradoxes. It's really about doing things that you believe are opposites of each other. It's about frictionless, but it's also about governance. It's about being simple, and it's also about being secure at the same time. It's about delight, it's about reducing waste, it's about owning, and renting, and finally it's also about core and edge. How do you really make this big at a core data center whether it's public or private? Or how do you really shrink it down to one or two nodes at the edge because that's where your machines are, that's where your people are? So this is a really hard problem. And as you hear from Sunil and the gang there, you'll realize how we've actually evolved our solutions to really cater to some of these. One of the approaches that we have used to really solve some of these hard problems is to have machines do more, and I said a lot of things in those four words, have machines do more. Because if you double-click on that sentence, it really means we're letting design be at the core of this. And how do you really design data centers, how do you really design products for the data center that hush all the escalations, the details, the complexities, use machine-learning and AI and you know figure our anomaly detection and correlations and patter matching? There's a ton of things that you need to do to really have machines do more. But along the way, the important lesson is to make machines invisible because when machines become invisible, it actually makes something else visible. It makes you visible. It makes governance visible. It makes applications visible, and it makes services visible. A lot of things, it makes teams visible, careers visible. So while we're really talking about invisibility of machines, we're talking about visibility of people. And that's how we really brought all of you together in this conference as well because it makes all of us shine including our products, and your careers, and your teams as well. And I try to define the word customer success. You know it's one of the favorite words that I'm actually using. We've just hired a great leader in customer success recently who's really going to focus on this relatively hard problem, yet another hard problem of customer success. We think that customer success, true customer success is possible when we have machines tend towards invisibility. But along the way when we do that, make humans tend towards freedom. So that's the real connection, the yin-yang of machines and humans that Nutanix is really all about. And that's why design is at the core of this company. And when I say design, I mean reducing friction. And it's really about reducing friction. And everything we do, the most mundane of things which could be about migrating applications, spinning up VMs, self-service portals, automatic upgrades, and automatic scale out, and all the things we do is about reducing friction which really makes machines become invisible and humans gain freedom. Now one of the other convictions we have is how all of us are really tied at the hip. You know our success is tied to your success. If we make you successful, and when I say you, I really mean Main Street. Main Street being customers, and partners, and employees. If we make all of you successful, then we automatically become successful. And very coincidentally, Main Street and Wall Street are also tied in that very same relation as well. If we do a great job at Main Street, I think the Wall Street customer, i.e. the investor, will take care of itself. You'll have you know taken care of their success if we took care of Main Street success itself. And that's the narrative that our CFO Dustin Williams actually went and painted to our Wall Street investors two months ago at our investor day conference. We talked about a $3 billion number. We said look as a company, as a software company, we can go and achieve $3 billion in billings three years from now. And it was a telling moment for the company. It was really about talking about where we could be three years from now. But it was not based on a hunch. It was based on what we thought was customer success. Now realize that $3 billion in pure software. There's only 10 to 15 companies in the world that actually have that kind of software billings number itself. But at the core of this confidence was customer success, was the fact that we were doing a really good job of not over promising and under delivering but under promising starting with small systems and growing the trust of the customers over time. And this is one of the statistics we actually talk about is repeat business. The first dollar that a Global 2000 customer spends in Nutanix, and if we go and increase their trust 15 times by year six, and we hope to actually get 17 1/2 and 19 times more trust in the years seven and eight. It's very similar numbers for non Global 2000 as well. Again, we go and really hustle for customer success, start small, have you not worry about paying millions of dollars upfront. You know start with systems that pay as they grow, you pay as they grow, and that's the way we gain trust. We have the same non Global 2000 pay $6 1/2 for the first dollar they've actually spent on us. And with this, I think the most telling moment was when Dustin concluded. And this is key to this audience here as well. Is how the current cohorts which is this audience here and many of them were not here will actually carry the weight of $3 billion, more than 50% of it if we did a great job of customer success. If we were humble and honest and we really figured out what it meant to take care of you, and if we really understood what starting small was and having to gain the trust with you over time, we think that more than 50% of that billings will actually come from this audience here without even looking at new logos outside. So that's the trust of customer success for us, and it takes care of pretty much every customer not just the Main Street customer. It takes care of Wall Street customer. It takes care of employees. It takes care of partners as well. Now before I talk about technology and products, I want to take a step back 'cause many of you are new in this audience. And I think that it behooves us to really talk about the history of this company. Like we've done a lot of things that started out as science projects. In fact, I see some tweets out there and people actually laugh at Nutanix cloud. And this is where we were in 2012. So if you take a step back and think about where the company was almost seven, eight years ago, we were up against giants. There was a $30 billion industry around network attached storage, and storage area networks and blade servers, and hypervisors, and systems management software and so on. So what did we start out with? Very simple premise that we will collapse the architecture of the data center because three tier is wasteful and three tier is not delightful. It was a very simple hunch, we said we'll take rack mount servers, we'll put a layer of software on top of it, and that layer of software back then only did storage. It didn't do networks and security, and it ran on top of a well known hypervisor from VMware. And we said there's one non negotiable thing. The fact that the design must change. The control plane for this data center cannot be the old control plane. It has to be rethought through, and that's why Prism came about. Now we went and hustled hard to add more things to it. We said we need to make this diverse because it can't just be for one application. We need to make it CPU heavy, and memory heavy, and storage heavy, and flash heavy and so on. And we built a highly configurable HCI. Now all of them are actually configurable as you know of today. And this was not just innovation in technologies, it was innovation in business and sizing, capacity planning, quote to cash business processes. A lot of stuff that we had to do to make this highly configurable, so you can really scale capacity and performance independent of each other. Then in 2014, we did something that was very counterintuitive, but we've done this on, and on, and on again. People said why are you disrupting yourself? You know you've been doing a good job of shipping appliances, but we also had the conviction that HCI was not about hardware. It was about a form factor, but it was really about an operating system. And we started to compete with ourselves when we said you know what we'll do arm's length distribution, we'll do arm's length delivery of products when we give our software to our Dell partner, to Dell as a partner, a loyal partner. But at the same time, it was actually seen with a lot of skepticism. You know these guys are wondering how to really make themselves vanish because they're competing with themselves. But we also knew that if we didn't compete with ourselves someone else will. Now one of the most controversial decisions was really going and doing yet another hypervisor. In the year 2015, it was really preposterous to build yet another hypervisor. It was a very mature market. This was coming probably 15 years too late to the market, or at least 10 years too late to market. And most people said it shouldn't be done because hypervisor is a commodity. And that's the word we latched on to. That this commodity should not have to be paid for. It shouldn't have a team of people managing it. It should actually be part of your overall stack, but it should be invisible. Just like storage needs to be invisible, virtualization needs to be invisible. But it was a bold step, and I think you know at least when we look at our current numbers, 1/3rd of our customers are actually using AHV. At least every quarter that we look at it, our new deployments, at least 35% of it is actually being used on AHV itself. And again, a very preposterous thing to have said five years ago, four years ago to where we've actually come. Thank you so much for all of you who've believed in the fact that virtualization software must be invisible and therefore we should actually try out something that is called AHV today. Now we went and added Lenovo to our OEM mix, started to become even more of a software company in the year 2016. Went and added HP and Cisco in some of very large deals that we talk about in earnings call, our HP deals and Cisco deals. And some very large customers who have procured ELAs from us, enterprise license agreements from us where they want to mix and match hardware. They want to mix Dell hardware with HP hardware but have common standard Nutanix entitlements. And finally, I think this was another one of those moments where we say why should HCI be only limited to X86. You know this operating systems deserves to run on a non X86 architecture as well. And that gave birth to this idea of HCI and Power Systems from IBM. And we've done a great job of really innovating with them in the last three, four quarters. Some amazing innovation that has come out where you can now run AIX 7.x on Nutanix. And for the first time in the history of data center, you can actually have a single software not just a data plane but a control plane where you can manage an IBM farm, an Power farm, and open Power farm and an X86 farm from the same control plane and have you know the IBM farm feed storage to an Intel compute farm and vice versa. So really good things that we've actually done. Now along the way, something else was going on while we were really busy building the private cloud, we knew there was a new consumption model on computing itself. People were renting computing using credit cards. This is the era of the millennials. They were like really want to bypass people because at the end of the day, you know why can't computing be consumed the way like eCommerce is? And that devops movement made us realize that we need to add to our stack. That stack will now have other computing clouds that is AWS and Azure and GCP now. So similar to the way we did Prism. You know Prism was really about going and making hypervisors invisible. You know we went ahead and said we'll add Calm to our portfolio because Calm is now going to be what Prism was to us back when we were really dealing with multi hypervisor world. Now it's going to be multi-cloud world. You know it's one of those things we had a gut around, and we really come to expect a lot of feedback and real innovation. I mean yesterday when we had the hackathon. The center, the epicenter of the discussion was Calm, was how do you automate on multiple clouds without having to write a single line of code? So we've come a long way since the acquisition of Calm two years ago. I think it's going to be a strong pillar in our overall product portfolio itself. Now the word multi-cloud is going to be used and over used. In fact, it's going to be blurring its lines with the idea of hyperconvergence of clouds, you know what does it mean. We just hope that hyperconvergence, the way it's called today will morph to become hyperconverged clouds not just hyperconverged boxes which is a software defined infrastructure definition itself. But let's focus on the why of multi-cloud. Why do we think it can't all go into a public cloud itself? The one big reason is just laws of the land. There's data sovereignty and computing sovereignty, regulations and compliance because of which you need to be in where the government with the regulations where the compliance rules want you to be. And by the way, that's just one reason why the cloud will have to disperse itself. It can't just be 10, 20 large data centers around the world itself because you have 200 plus countries and half of computing actually gets done outside the US itself. So it's a really important, very relevant point about the why of multi-cloud. The second one is just simple laws of physics. You know if there're machines at the edge, and they're producing so much data, you can't bring all the data to the compute. You have to take the compute which is stateless, it's an app. You take the app to where the data is because the network is the enemy. The network has always been the enemy. And when we thought we've made fatter networks, you've just produced more data as well. So this just goes without saying that you take something that's stateless that's without gravity, that's lightweight which is compute and the application and push it close to where the data itself is. And the third one which is related is just latency reasons you know? And it's not just about machine latency and electrons transferring over the speed light, and you can't defy the speed of light. It's also about human latency. It's also about multiple teams saying we need to federate and delegate, and we need to push things down to where the teams are as opposed to having to expect everybody to come to a very large computing power itself. So all the ways, the way they are, there will be at least three different ways of looking at multi-cloud itself. There's a centralized core cloud. We all go and relate to this because we've seen large data centers and so on. And that's the back office workhorse. It will crunch numbers. It will do processing. It will do a ton of things that will go and produce results for you know how we run our businesses, but there's also the dispersal of the cloud, so ROBO cloud. And this is the front office server that's really serving. It's a cloud that's going to serve people. It's going to be closer to people, and that's what a ROBO cloud is. We have a ton of customers out here who actually use Nutanix and the ROBO environments themselves as one node, two node, three node, five node servers, and it just collapses the entire server closet room in these ROBOs into something really, really small and minuscule. And finally, there's going to be another dispersed edge cloud because that's where the machines are, that's where the data is. And there's going to be an IOT machine fog because we need to miniaturize computing to something even smaller, maybe something that can really land in the palm in a mini server which is a PC like server, but you need to run everything that's enterprise grade. You should be able to go and upgrade them and monitor them and analyze them. You know do enough computing up there, maybe event-based processing that can actually happen. In fact, there's some great innovation that we've done at the edge with IOTs that I'd love for all of you to actually attend some sessions around as well. So with that being said, we have a hole in the stack. And that hole is probably one of the hardest problems that we've been trying to solve for the last two years. And Sunil will talk a lot about that. This idea of hybrid. The hybrid of multi-cloud is one of the hardest problems. Why? Because we're talking about really blurring the lines with owning and renting where you have a single-tenant environment which is your data center, and a multi-tenant environment which is the service providers data center, and the two must look like the same. And the two must look like the same is that hard a problem not just for burst out capacity, not just for security, not just for identity but also for networks. Like how do you blur the lines between networks? How do you blur the lines for storage? How do you really blur the lines for a single pane of glass where you can think of availability zones that look highly symmetric even though they're not because one of 'em is owned by you, and it's single-tenant. The other one is not owned by you, that's multi-tenant itself. So there's some really hard problems in hybrid that you'll hear Sunil talk about and the team. And some great strides that we've actually made in the last 12 months of really working on Xi itself. And that completes the picture now in terms of how we believe the state of computing will be going forward. So what are the must haves of a multi-cloud operating system? We talked about marketplace which is catalogs and automation. There's a ton of orchestration that needs to be done for multi-cloud to come together because now you have a self-service portal which is providing an eCommerce view. It's really about you know getting to do a lot of requests and workflows without having people come in the way, without even having tickets. There's no need for tickets if you can really start to think like a self-service portal as if you're just transacting eCommerce with machines and portals themselves. Obviously the next one is networking security. You need to blur the lines between on-prem and off-prem itself. These two play a huge role. And there's going to be a ton of details that you'll see Sunil talk about. But finally, what I want to focus on the rest of the talk itself here is what governance and compliance. This is a hard problem, and it's a hard problem because things have evolved. So I'm going to take a step back. Last 30 years of computing, how have consumption models changed? So think about it. 30 years ago, we were making decisions for 10 plus years, you know? Mainframe, at least 10 years, probably 20 plus years worth of decisions. These were decisions that were extremely waterfall-ish. Make 10s of millions of dollars worth of investment for a device that we'd buy for at least 10 to 20 years. Now as we moved to client-server, that thing actually shrunk. Now you're talking about five years worth of decisions, and these things were smaller. So there's a little bit more velocity in our decisions. We were not making as waterfall-ish decision as we used to with mainframes. But still five years, talk about virtualized, three tier, maybe three to five year decisions. You know they're still relatively big decisions that we were making with computer and storage and SAN fabrics and virtualization software and systems management software and so on. And here comes Nutanix, and we said no, no. We need to make it smaller. It has to become smaller because you know we need to make more agile decisions. We need to add machines every week, every month as opposed to adding you know machines every three to five years. And we need to be able to upgrade them, you know any point in time. You can do the upgrades every month if you had to, every week if you had to and so on. So really about more agility. And yet, we were not complete because there's another evolution going on, off-prem in the public cloud where people are going and doing reserved instances. But more than that, they were doing on demand stuff which no the decision was days to weeks. Some of these things that unitive compute was being rented for days to weeks, not years. And if you needed something more, you'd shift a little to the left and use reserved instances. And then spot pricing, you could do spot pricing for hours and finally lambda functions. Now you could to function as a service where things could actually be running only for minutes not even hours. So as you can see, there's a wide spectrum where when you move to the right, you get more elasticity, and when you move to the left, you're talking about predictable decision making. And in fact, it goes from minutes on one side to 10s of years on the other itself. And we hope to actually go and blur the lines between where NTNX is today where you see Nutanix right now to where we really want to be with reserved instances and on demand. And that's the real ask of Nutanix. How do you take care of this discontinuity? Because when you're owning things, you actually end up here, and when you're renting things, you end up here. What does it mean to really blur the lines between these two because people do want to make decisions that are better than reserved instance in the public cloud. We'll talk about why reserved instances which looks like a proxy for Nutanix it's still very, very wasteful even though you might think it's delightful, it's very, very wasteful. So what does it mean for on-prem and off-prem? You know you talk about cost governance, there's security compliance. These high velocity decisions we're actually making you know where sometimes you could be right with cost but wrong on security, but sometimes you could be right in security but wrong on cost. We need to really figure out how machines make some of these decisions for us, how software helps us decide do we have the right balance between cost, governance, and security compliance itself? And to get it right, we have introduced our first SAS service called Beam. And to talk more about Beam, I want to introduce Vijay Rayapati who's the general manager of Beam engineering to come up on stage and talk about Beam itself. Thank you Vijay. (rock music) So you've been here a couple of months now? >> Yes. >> At the same time, you spent the last seven, eight years really handling AWS. Tell us more about it. >> Yeah so we spent a lot of time trying to understand the last five years at Minjar you know how customers are really consuming in this new world for their workloads. So essentially what we tried to do is understand the consumption models, workload patterns, and also build algorithms and apply intelligence to say how can we lower this cost and you know improve compliance of their workloads.? And now with Nutanix what we're trying to do is how can we converge this consumption, right? Because what happens here is most customers start with on demand kind of consumption thinking it's really easy, but the total cost of ownership is so high as the workload elasticity increases, people go towards spot or a scaling, but then you need a lot more automation that something like Calm can help them. But predictability of the workload increases, then you need to move towards reserved instances, right to lower costs. >> And those are some of the things that you go and advise with some of the software that you folks have actually written. >> But there's a lot of waste even in the reserved instances because what happens it while customers make these commitments for a year or three years, what we see across, like we track a billion dollars in public cloud consumption you know as a Beam, and customers use 20%, 25% of utilization of their commitments, right? So how can you really apply, take the data of consumption you know apply intelligence to essentially reduce their you know overall cost of ownership. >> You said something that's very telling. You said reserved instances even though they're supposed to save are still only 20%, 25% utilized. >> Yes, because the workloads are very dynamic. And the next thing is you can't do hot add CPU or hot add memory because you're buying them for peak capacity. There is no convergence of scaling that apart from the scaling as another node. >> So you actually sized it for peak, but then using 20%, 30%, you're still paying for the peak. >> That's right. >> Dheeraj: That can actually add up. >> That's what we're trying to say. How can we deliver visibility across clouds? You know how can we deliver optimization across clouds and consumption models and bring the control while retaining that agility and demand elasticity? >> That's great. So you want to show us something? >> Yeah absolutely. So this is Beam as just Dheeraj outlined, our first SAS service. And this is my first .Next. And you know glad to be here. So what you see here is a global consumption you know for a business across different clouds. Whether that's in a public cloud like Amazon, or Azure, or Nutanix. We kind of bring the consumption together for the month, the recent month across your accounts and services and apply intelligence to say you know what is your spent efficiency across these clouds? Essentially there's a lot of intelligence that goes in to detect your workloads and consumption model to say if you're spending $100, how efficiently are you spending? How can you increase that? >> So you have a centralized view where you're looking at multiple clouds, and you know you talk about maybe you can take an example of an account and start looking at it? >> Yes, let's go into a cloud provider like you know for this business, let's go and take a loot at what's happening inside an Amazon cloud. Here we get into the deeper details of what's happening with the consumption of a specific services as well as the utilization of both on demand and RI. You know what can you do to lower your cost and detect your spend efficiency of a dollar to see you know are there resources that are provisioned by teams for applications that are not being used, or are there resources that we should go and rightsize because you know we have all this monitoring data, configuration data that we crunch through to basically detect this? >> You think there's billions of events that you look at everyday. You're already looking at a billon dollars worth of AWS spend. >> Right, right. >> So billions of events, billing, metering events every year to really figure out and optimize for them. >> So what we have here is a very popular international government organization. >> Dheeraj: Wow, so it looks like Russians are everywhere, the cloud is everywhere actually. >> Yes, it's quite popular. So when you bring your master account into Beam, we kind of detect all the linked accounts you know under that. Then you can go and take a look at not just at the organization level within it an account level. >> So these are child objects, you know. >> That's right. >> You can think of them as ephemeral accounts that you create because you don't want to be on the record when you're doing spams on Facebook for example. >> Right, let's go and take a look at what's happening inside a Facebook ad spend account. So we have you know consumption of the services. Let's go deeper into compute consumption, and you kind of see a trendline. You can do a lot of computing. As you see, looks like one campaign has ended. They started another campaign. >> Dheeraj: It looks like they're not stopping yet, man. There's a lot of money being made in Facebook right now. (Vijay laughing) >> So not only just get visibility at you know compute as a service inside a cloud provider, you can go deeper inside compute and say you know what is a service that I'm really consuming inside compute along with the CPUs n'stuff, right? What is my data transfer? You know what is my network? What is my load blancers? So essentially you get a very deeper visibility you know as a service right. Because we have three goals for Beam. How can we deliver visibility across clouds? How can we deliver visibility across services? And how can we deliver, then optimization? >> Well I think one thing that I just want to point out is how this SAS application was an extremely teachable moment for me to learn about the different resources that people could use about the public cloud. So all of you who actually have not gone deep enough into the idea of public cloud. This could be a great app for you to learn about things, the resources, you know things that you could do to save and security and things of that nature. >> Yeah. And we really believe in creating the single pane view you know to mange your optimization of a public cloud. You know as Ben spoke about as a business, you need to have freedom to use any cloud. And that's what Beam delivers. How can you make the right decision for the right workload to use any of the cloud of your choice? >> Dheeraj: How 'about databases? You talked about compute as well but are there other things we could look at? >> Vijay: Yes, let's go and take a look at database consumption. What you see here is they're using inside Facebook ad spending, they're using all databases except Oracle. >> Dheeraj: Wow, looks like Oracle sales folks have been active in Russia as well. (Vijay laughing) >> So what we're seeing here is a global view of you know what is your spend efficiency and which is kind of a scorecard for your business for the dollars that you're spending. And the great thing is Beam kind of brings together you know through its intelligence and algorithms to detect you know how can you rightsize resources and how can you eliminate things that you're not using? And we deliver and one click fix, right? Let's go and take a look at resources that are maybe provisioned for storage and not being used. We deliver the seamless one-click philosophy that Nutanix has to eliminate it. >> So one click, you can actually just pick some of these wasteful things that might be looking delightful because using public cloud, using credit cards, you can go in and just say click fix, and it takes care of things. >> Yeah, and not only remove the resources that are unused, but it can go and rightsize resources across your compute databases, load balancers, even past services, right? And this is where the power of it kind of comes for a business whether you're using on-prem and off-prem. You know how can you really converge that consumption across both? >> Dheeraj: So do you have something for Nutanix too? >> Vijay: Yes, so we have basically been working on Nutanix with something that we're going to deliver you know later this year. As you can see here, we're bringing together the consumption for the Nutanix, you know the services that you're using, the licensing and capacity that is available. And how can you also go and optimize within Nutanix environments >> That's great. >> for the next workload. Now let me quickly show you what we have on the compliance side. This is an extremely powerful thing that we've been working on for many years. What we deliver here just like in cost governance, a global view of your compliance across cloud providers. And the most powerful thing is you can go into a cloud provider, get the next level of visibility across cloud regimes for hundreds of policies. Not just policies but those policies across different regulatory compliances like HIPA, PCI, CAS. And that's very powerful because-- >> So you're saying a lot of what you folks have done is codified these compliance checks in software to make sure that people can sleep better at night knowing that it's PCI, and HIPA, and all that compliance actually comes together? >> And you can build this not just by cloud accounts, you can build them across cloud accounts which is what we call security centers. Essentially you can go and take a deeper look at you know the things. We do a whole full body scan for your cloud infrastructure whether it's AWS Amazon or Azure, and you can go and now, again, click to fix things. You know that had been probably provisioned that are violating the security compliance rules that should be there. Again, we have the same one-click philosophy to say how can you really remove things. >> So again, similar to save, you're saying you can go and fix some of these security issues by just doing one click. >> Absolutely. So the idea is how can we give our people the freedom to get visibility and use the right cloud and take the decisions instantly through one click. That's what Beam delivers you know today. And you know get really excited, and it's available at beam.nutanix.com. >> Our first SAS service, ladies and gentleman. Thank you so much for doing this, Vijay. It looks like there's going to be a talk here at 10:30. You'll talk more about the midterm elections there probably? >> Yes, so you can go and write your own security compliances as well. You know within Beam, and a lot of powerful things you can do. >> Awesome, thank you so much, Vijay. I really appreciate it. (audience clapping) So as you see, there's a lot of work that we're doing to really make multi-cloud which is a hard problem. You know think about working the whole body of it and what about cost governance? What about security compliance? Obviously what about hybrid networks, and security, and storage, you know compute, many of the things that you've actually heard from us, but we're taking it to a level where the business users can now understand the implications. A CFO's office can understand the implications of waste and delight. So what does customer success mean to us? You know again, my favorite word in a long, long time is really go and figure out how do you make you, the customer, become operationally efficient. You know there's a lot of stuff that we deliver through software that's completely uncovered. It's so latent, you don't even know you have it, but you've paid for it. So you've got to figure out what does it mean for you to really become operationally efficient, organizationally proficient. And it's really important for training, education, stuff that you know you're people might think it's so awkward to do in Nutanix, but it could've been way simpler if you just told you a place where you can go and read about it. Of course, I can just use one click here as opposed to doing things the old way. But most importantly to make it financially accountable. So the end in all this is, again, one of the things that I think about all the time in building this company because obviously there's a lot of stuff that we want to do to create orphans, you know things above the line and top line and everything else. There's also a bottom line. Delight and waste are two sides of the same coin. You know when we're talking about developers who seek delight with public cloud at the same time you're looking at IT folks who're trying to figure out governance. They're like look you know the CFOs office, the CIOs office, they're trying to figure out how to curb waste. These two things have to go hand in hand in this era of multi-cloud where we're talking about frictionless consumption but also governance that looks invisible. So I think, at the end of the day, this company will do a lot of stuff around one-click delight but also go and figure out how do you reduce waste because there's so much waste including folks there who actually own Nutanix. There's so much software entitlement. There's so much waste in the public cloud itself that if we don't go and put our arms around, it will not lead to customer success. So to talk more about this, the idea of delight and the idea of waste, I'd like to bring on board a person who I think you know many of you actually have talked about it have delightful hair but probably wasted jokes. But I think has wasted hair and delightful jokes. So ladies and gentlemen, you make the call. You're the jury. Sunil R.M.J. Potti. ("Free" by Broods) >> So that was the first time I came out from the bottom of a screen on a stage. I actually now know what it feels to be like a gopher. Who's that laughing loudly at the back? Okay, do we have the... Let's see. Okay, great. We're about 15 minutes late, so that means we're running right on time. That's normally how we roll at this conference. And we have about three customers and four demos. Like I think there's about three plus six, about nine folks coming onstage. So we'll have our own version of the parade as well on the main stage for the next 70 minutes. So let's just jump right into it. I think we've been pretty consistent in terms of our longterm plans since we started the company. And it's become a lot more clearer over the last few years about our plans to essentially make computing invisible as Dheeraj mentioned. We're doing this across multiple acts. We started with HCI. We call it making infrastructure invisible. We extended that to making data centers invisible. And then now we're in this mode of essentially extending it to converging clouds so that you can actually converge your consumption models. And so today's conference and essentially the theme that you're going to be seeing throughout the breakout sessions is about a journey towards invisible clouds, but make sure that you internalize the fact that we're investing heavily in each of the three phases. It's just not about the hybrid cloud with Nutanix, it's about actually finishing the job about making infrastructure invisible, expanding that to kind of go after the full data center, and then of course embark on some real meaningful things around invisible clouds, okay? And to start the session, I think you know the part that I wanted to make sure that we are all on the same page because most of us in the room are still probably in this phase of the journey which is about invisible infrastructure. And there the three key products and especially two of them that most of you guys know are Acropolis and Prism. And they're sort of like the bedrock of our company. You know especially Acropolis which is about the web scale architecture. Prism is about consumer grade design. And with Acropolis now being really mature. It's in the seventh year of innovation. We still have more than half of our company in terms of R and D spend still on Acropolis and Prism. So our core product is still sort of where we think we have a significant differentiation on. We're not going to let our foot off the peddle there. You know every time somebody comes to me and says look there's a new HCI render popping out or an existing HCI render out there, I ask a simple question to our customers saying show me 100 customers with 100 node deployments, and it will be very hard to find any other render out there that does the same thing. And that's the power of Acropolis the code platform. And then it's you know the fact that the velocity associated with Acropolis continues to be on a fast pace. We came out with various new capabilities in 5.5 and 5.6, and one of the most complicated things to get right was the fact to shrink our three node cluster to a one node, two node deployment. Most of you actually had requirements on remote office, branch office, or the edge that actually allowed us to kind of give us you know sort of like the impetus to kind of go design some new capabilities into our core OS to get this out. And associated with Acropolis and expanding into Prism, as you will see, the first couple of years of Prism was all about refactoring the user interface, doing a good job with automation. But more and more of the investments around Prism is going to be based on machine learning. And you've seen some variants of that over the last 12 months, and I can tell you that in the next 12 to 24 months, most of our investments around infrastructure operations are going to be driven by AI techniques starting with most of our R and D spend also going into machine-learning algorithms. So when you talk about all the enhancements that have come on with Prism whether it be formed by you know the management console changing to become much more automated, whether now we give you automatic rightsizing, anomaly detection, or a series of functionality that have gone into it, the real core sort of capabilities that we're putting into Prism and Acropolis are probably best served by looking at the quality of the product. You probably have seen this slide before. We started showing the number of nodes shipped by Nutanix two years ago at this conference. It was about 35,000 plus nodes at that time. And since then, obviously we've you know continued to grow. And we would draw this line which was about enterprise class quality. That for the number of bugs found as a percentage of nodes shipped, there's a certain line that's drawn. World class companies do about probably 2% to 3%, number of CFDs per node shipped. And we were just broken that number two years ago. And to give you guys an idea of how that curve has shown up, it's now currently at .95%. And so along with velocity, you know this focus on being true to our roots of reliability and stability continues to be, you know it's an internal challenge, but it's also some of the things that we keep a real focus on. And so between Acropolis and Prism, that's sort of like our core focus areas to sort of give us the confidence that look we have this really high bar that we're sort of keeping ourselves accountable to which is about being the most advanced enterprise cloud OS on the planet. And we will keep it this way for the next 10 years. And to complement that, over a period of time of course, we've added a series of services. So these are services not just for VMs but also for files, blocks, containers, but all being delivered in that single one-click operations fashion. And to really talk more about it, and actually probably to show you the real deal there it's my great pleasure to call our own version of Moses inside the company, most of you guys know him as Steve Poitras. Come on up, Steve. (audience clapping) (rock music) >> Thanks Sunil. >> You barely fit in that door, man. Okay, so what are we going to talk about today, Steve? >> Absolutely. So when we think about when Nutanix first got started, it was really focused around VDI deployments, smaller workloads. However over time as we've evolved the product, added additional capabilities and features, that's grown from VDI to business critical applications as well as cloud native apps. So let's go ahead and take a look. >> Sunil: And we'll start with like Oracle? >> Yeah, that's one of the key ones. So here we can see our Prism central user interface, and we can see our Thor cluster obviously speaking to the Avengers theme here. We can see this is doing right around 400,000 IOPs at around 360 microseconds latency. Now obviously Prism central allows you to mange all of your Nutanix deployments, but this is just running on one single Nutanix cluster. So if we hop over here to our explore tab, we can see we have a few categories. We have some Kubernetes, some AFS, some Xen desktop as well as Oracle RAC. Now if we hope over to Oracle RAC, we're running a SLOB workload here. So obviously with Oracle enterprise applications performance, consistency, and extremely low latency are very critical. So with this SLOB workload, we're running right around 300 microseconds of latency. >> Sunil: So this is what, how many node Oracle RAC cluster is this? >> Steve: This is a six node Oracle RAC deployment. >> Sunil: Got it. And so what has gone into the product in recent releases to kind of make this happen? >> Yeah so obviously on the hardware front, there's been a lot of evolutions in storage mediums. So with the introduction of NVME, persistent memory technologies like 3D XPoint, that's meant storage media has become a lot faster. Now to allow you to full take advantage of that, that's where we've had to do a lot of optimizations within the storage stack. So with AHV, we have what we call AHV turbo mode which allows you to full take advantage of those faster storage mediums at that much lower latency. And then obviously on the networking front, technologies such as RDMA can be leveraged to optimize that network stack. >> Got it. So that was Oracle RAC running on a you know Nutanix cluster. It used to be a big deal a couple of years ago. Now we've got many customers doing that. On the same environment though, we're going to show you is the advent of actually putting file services in the same scale out environment. And you know many of you in the audience probably know about AFS. We released it about 12 to 14 months ago. It's been one of our most popular new products of all time within Nutanix's history. And we had SMB support was for user file shares, VDI deployments, and it took awhile to bake, to get to scale and reliability. And then in the last release, in the recent release that we just shipped, we now added NFS for support so that we can no go after the full scale file server consolidation. So let's take a look at some of that stuff. >> Yep, let's do it. So hopping back over to Prism, we can see our four cluster here. Overall cluster-wide latency right around 360 microseconds. Now we'll hop down to our file server section. So here we can see we have our Next A File Server hosting right about 16.2 million files. Now if you look at our shares and exports, we can see we have a mix of different shares. So one of the shares that you see there is home directories. This is an SMB share which is actually mapped and being leveraged by our VDI desktops for home folders, user profiles, things of that nature. We can also see this Oracle backup share here which is exposed to our rack host via NFS. So RMAN is actually leveraging this to provide native database backups. >> Got it. So Oracle VMs, backup using files, or for any other file share requirements with AFS. Do we have the cluster also showing, I know, so I saw some Kubernetes as well on it. Let's talk about what we're thinking of doing there. >> Yep, let's do it. So if we think about cloud, cloud's obviously a big buzz word, so is containers in Kubernetes. So with ACS 1.0 what we did is we introduced native support for Docker integration. >> And pause there. And we screwed up. (laughing) So just like the market took a left turn on Kubernetes, obviously we realized that, and now we're working on ACS 2.0 which is what we're going to talk about, right? >> Exactly. So with ACS 2.0, we've introduced native Kubernetes support. Now when I think about Kubernetes, there's really two core areas that come to mind. The first one is around native integration. So with that, we have our Kubernetes volume integration, we're obviously doing a lot of work on the networking front, and we'll continue to push there from an integration point of view. Now the other piece is around the actual deployment of Kubernetes. When we think about a lot of Nutanix administrators or IT admins, they may have never deployed Kubernetes before, so this could be a very daunting task. And true to the Nutanix nature, we not only want to make our platform simple and intuitive, we also want to do this for any ecosystem products. So with ACS 2.0, we've simplified the full Kubernetes deployment and switching over to our ACS two interface, we can see this create cluster button. Now this actually pops up a full wizard. This wizard will actually walk you through the full deployment process, gather the necessary inputs for you, and in a matter of a few clicks and a few minutes, we have a full Kubernetes deployment fully provisioned, the masters, the workers, all the networking fully done for you, very simple and intuitive. Now if we hop back over to Prism, we can see we have this ACS2 Kubernetes category. Clicking on that, we can see we have eight instances of virtual machines. And here are Kubernetes virtual machines which have actually been deployed as part of this ACS2 installer. Now one of the nice things is it makes the IT administrator's job very simple and easy to do. The deployment straightforward monitoring and management very straightforward and simple. Now for the developer, the application architect, or engineers, they interface and interact with Kubernetes just like they would traditionally on any platform. >> Got it. So the goal of ACS is to ensure that the developer ecosystem still uses whatever tools that they are you know preferring while at that same time allowing this consolidation of containers along with VMs all on that same, single runtime, right? So that's ACS. And then if you think about where the OS is going, there's still some open space at the end. And open space has always been look if you just look at a public cloud, you look at blocks, files, containers, the most obvious sort of storage function that's left is objects. And that's the last horizon for us in completing the storage stack. And we're going to show you for the first time a preview of an upcoming product called the Acropolis Object Storage Services Stack. So let's talk a little bit about it and then maybe show the demo. >> Yeah, so just like we provided file services with AFS, block services with ABS, with OSS or Object Storage Services, we provide native object storage, compatibility and capability within the Nutanix platform. Now this provides a very simply common S3 API. So any integrations you've done with S3 especially Kubernetes, you can actually leverage that out of the box when you've deployed this. Now if we hop back over to Prism, I'll go here to my object stores menu. And here we can see we have two existing object storage instances which are running. So you can deploy however many of these as you wanted to. Now just like the Kubernetes deployment, deploying a new object instance is very simple and easy to do. So here I'll actually name this instance Thor's Hammer. >> You do know he loses it, right? He hasn't seen the movies yet. >> Yeah, I don't want any spoilers yet. So once we specified the name, we can choose our capacity. So here we'll just specify a large instance or type. Obviously this could be any amount or storage. So if you have a 200 node Nutanix cluster with petabytes worth of data, you could do that as well. Once we've selected that, we'll select our expected performance. And this is going to be the number of concurrent gets and puts. So essentially how many operations per second we want this instance to be able to facilitate. Once we've done that, the platform will actually automatically determine how many virtual machines it needs to deploy as well as the resources and specs for those. And once we've done that, we'll go ahead and click save. Now here we can see it's actually going through doing the deployment of the virtual machines, applying any necessary configuration, and in the matter of a few clicks and a few seconds, we actually have this Thor's Hammer object storage instance which is up and running. Now if we hop over to one of our existing object storage instances, we can see this has three buckets. So one for Kafka-queue, I'm actually using this for my Kafka cluster where I have right around 62 million objects all storing ProtoBus. The second one there is Spark. So I actually have a Spark cluster running on our Kubernetes deployed instance via ACS 2.0. Now this is doing analytics on top of this data using S3 as a storage backend. Now for these objects, we support native versioning, native object encryption as well as worm compliancy. So if you want to have expiry periods, retention intervals, that sort of thing, we can do all that. >> Got it. So essentially what we've just shown you is with upcoming objects as well that the same OS can now support VMs, files, objects, containers, all on the same one click operational fabric. And so that's in some way the real power of Nutanix is to still keep that consistency, scalability in place as we're covering each and every workload inside the enterprise. So before Steve gets off stage though, I wanted to talk to you guys a little bit about something that you know how many of you been to our Nutanix headquarters in San Jose, California? A few. I know there's like, I don't know, 4,000 or 5,000 people here. If you do come to the office, you know when you land in San Jose Airport on the way to longterm parking, you'll pass our office. It's that close. And if you come to the fourth floor, you know one of the cubes that's where I sit. In the cube beside me is Steve. Steve sits in the cube beside me. And when I first joined the company, three or four years ago, and Steve's if you go to his cube, it no longer looks like this, but it used to have a lot of this stuff. It was like big containers of this. I remember the first time. Since I started joking about it, he started reducing it. And then Steve eventually got married much to our surprise. (audience laughing) Much to his wife's surprise. And then he also had a baby as a bigger surprise. And if you come over to our office, and we welcome you, and you come to the fourth floor, find my cube or you'll find Steve's Cube, it now looks like this. Okay, so thanks a lot, my man. >> Cool, thank you. >> Thanks so much. (audience clapping) >> So single OS, any workload. And like Steve who's been with us for awhile, it's my great pleasure to invite one of our favorite customers, CSC Karen who's also been with us for three to four years. And I'll share some fond memories about how she's been with the company for awhile, how as partners we've really done a lot together. So without any further ado, let me bring up Karen. Come on up, Karen. (rock music) >> Thank you for having me. >> Yeah, thank you. So I remember, so how many of you guys were with Nutanix first .Next in Miami? I know there was a question like that asked last time. Not too many. You missed it. We wished we could go back to that. We wouldn't fit 3/4s of this crowd. But Karen was our first customer in the keynote in 2015. And we had just talked about that story at that time where you're just become a customer. Do you want to give us some recap of that? >> Sure. So when we made the decision to move to hyperconverged infrastructure and chose Nutanix as our partner, we rapidly started to deploy. And what I mean by that is Sunil and some of the Nutanix executives had come out to visit with us and talk about their product on a Tuesday. And on a Wednesday after making the decision, I picked up the phone and said you know what I've got to deploy for my VDI cluster. So four nodes showed up on Thursday. And from the time it was plugged in to moving over 300 VDIs and 50 terabytes of storage and turning it over for the business for use was less than three days. So it was really excellent testament to how simple it is to start, and deploy, and utilize the Nutanix infrastructure. Now part of that was the delight that we experienced from our customers after that deployment. So we got phone calls where people were saying this report it used to take so long that I'd got out and get a cup of coffee and come back, and read an article, and do some email, and then finally it would finish. Those reports are running in milliseconds now. It's one click. It's very, very simple, and we've delighted our customers. Now across that journey, we have gone from the simple workloads like VDIs to the much more complex workloads around Splunk and Hadoop. And what's really interesting about our Splunk deployment is we're handling over a billion events being logged everyday. And the deployment is smaller than what we had with a three tiered infrastructure. So when you hear people talk about waste and getting that out and getting to an invisible environment where you're just able to run it, that's what we were able to achieve both with everything that we're running from our public facing websites to the back office operations that we're using which include Splunk and even most recently our Cloudera and Hadoop infrastructure. What it does is it's got 30 crawlers that go out on the internet and start bringing data back. So it comes back with over two terabytes of data everyday. And then that environment, ingests that data, does work against it, and responds to the business. And that again is something that's smaller than what we had on traditional infrastructure, and it's faster and more stable. >> Got it. And it covers a lot of use cases as well. You want to speak a few words on that? >> So the use cases, we're 90%, 95% deployed on Nutanix, and we're covering all of our use cases. So whether that's a customer facing app or a back office application. And what are business is doing is it's handling large portfolios of data for fortune 500 companies and law firms. And these applications are all running with improved stability, reliability, and performance on the Nutanix infrastructure. >> And the plan going forward? >> So the plan going forward, you actually asked me that in Miami, and it's go global. So when we started in Miami and that first deployment, we had four nodes. We now have 283 nodes around the world, and we started with about 50 terabytes of data. We've now got 3.8 petabytes of data. And we're deployed across four data centers and six remote offices. And people ask me often what is the value that we achieved? So simplification. It's all just easier, and it's all less expensive. Being able to scale with the business. So our Cloudera environment ended up with one day where it spiked to 1,000 times more load, 1,000 times, and it just responded. We had rally cries around improved productivity by six times. So 600% improved productivity, and we were able to actually achieve that. The numbers you just saw on the slide that was very, very fast was we calculated a 40% reduction in total cost of ownership. We've exceeded that. And when we talk about waste, that other number on the board there is when I saved the company one hour of maintenance activity or unplanned downtime in a month which we're now able to do the majority of our maintenance activities without disrupting any of our business solutions, I'm saving $750,000 each time I save that one hour. >> Wow. All right, Karen from CSE. Thank you so much. That was great. Thank you. I mean you know some of these data points frankly as I started talking to Karen as well as some other customers are pretty amazing in terms of the genuine value beyond financial value. Kind of like the emotional sort of benefits that good products deliver to some of our customers. And I think that's one of the core things that we take back into engineering is to keep ourselves honest on either velocity or quality even hiring people and so forth. Is to actually the more we touch customers lives, the more we touch our partner's lives, the more it allows us to ensure that we can put ourselves in their shoes to kind of make sure that we're doing the right thing in terms of the product. So that was the first part, invisible infrastructure. And our goal, as we've always talked about, our true North is to make sure that this single OS can be an exact replica, a truly modern, thoughtful but original design that brings the power of public cloud this AWS or GCP like architectures into your mainstream enterprises. And so when we take that to the next level which is about expanding the scope to go beyond invisible infrastructure to invisible data centers, it starts with a few things. Obviously, it starts with virtualization and a level of intelligent management, extends to automation, and then as we'll talk about, we have to embark on encompassing the network. And that's what we'll talk about with Flow. But to start this, let me again go back to one of our core products which is the bedrock of our you know opinionated design inside this company which is Prism and Acropolis. And Prism provides, I mentioned, comes with a ton of machine-learning based intelligence built into the product in 5.6 we've done a ton of work. In fact, a lot of features are coming out now because now that PC, Prism Central that you know has been decoupled from our mainstream release strain and will continue to release on its own cadence. And the same thing when you actually flip it to AHV on its own train. Now AHV, two years ago it was all about can I use AHV for VDI? Can I use AHV for ROBO? Now I'm pretty clear about where you cannot use AHV. If you need memory overcome it, stay with VMware or something. If you need, you know Metro, stay with another technology, else it's game on, right? And if you really look at the adoption of AHV in the mainstream enterprise, the customers now speak for themselves. These are all examples of large global enterprises with multimillion dollar ELAs in play that have now been switched over. Like I'll give you a simple example here, and there's lots of these that I'm sure many of you who are in the audience that are in this camp, but when you look at the breakout sessions in the pods, you'll get a sense of this. But I'll give you one simple example. If you look at the online payment company. I'm pretty sure everybody's used this at one time or the other. They had the world's largest private cloud on open stack, 21,000 nodes. And they were actually public about it three or four years ago. And in the last year and a half, they put us through a rigorous VOC testing scale, hardening, and it's a full blown AHV only stack. And they've started cutting over. Obviously they're not there yet completely, but they're now literally in hundreds of nodes of deployment of Nutanix with AHV as their primary operating system. So it is primetime from a deployment perspective. And with that as the base, no cloud is complete without actually having self-service provisioning that truly drives one-click automation, and can you do that in this consumer grade design? And Calm was acquired, as you guys know, in 2016. We had a choice of taking Calm. It was reasonably feature complete. It supported multiple clouds. It supported ESX, it supported Brownfield, It supported AHV. I mean they'd already done the integration with Nutanix even before the acquisition. And we had a choice. The choice was go down the path of dynamic ops or some other products where you took it for revenue or for acceleration, you plopped it into the ecosystem and sold it at this power sucking alien on top of our stack, right? Or we took a step back, re-engineered the product, kept some of the core essence like the workflow engine which was good, the automation, the object model and all, but refactored it to make it look like a natural extension of our operating system. And that's what we did with Calm. And we just launched it in December, and it's been one of our most popular new products now that's flying off the shelves. If you saw the number of registrants, I got a notification of this for the breakout sessions, the number one session that has been preregistered with over 500 people, the first two sessions are around Calm. And justifiably so because it just as it lives up to its promise, and it'll take its time to kind of get to all the bells and whistles, all the capabilities that have come through with AHV or Acropolis in the past. But the feature functionality, the product market fit associated with Calm is dead on from what the feedback that we can receive. And so Calm itself is on its own rapid cadence. We had AWS and AHV in the first release. Three or four months later, we now added ESX support. We added GCP support and a whole bunch of other capabilities, and I think the essence of Calm is if you can combine Calm and along with private cloud automation but also extend it to multi-cloud automation, it really sets Nutanix on its first genuine path towards multi-cloud. But then, as I said, if you really fixate on a software defined data center message, we're not complete as a full blown AWS or GCP like IA stack until we do the last horizon of networking. And you probably heard me say this before. You heard Dheeraj and others talk about it before is our problem in networking isn't the same in storage. Because the data plane in networking works. Good L2 switches from Cisco, Arista, and so forth, but the real problem networking is in the control plane. When something goes wrong at a VM level in Nutanix, you're able to identify whether it's a storage problem or a compute problem, but we don't know whether it's a VLAN that's mis-configured, or there've been some packets dropped at the top of the rack. Well that all ends now with Flow. And with Flow, essentially what we've now done is take the work that we've been working on to create built-in visibility, put some network automation so that you can actually provision VLANs when you provision VMs. And then augment it with micro segmentation policies all built in this easy to use, consume fashion. But we didn't stop there because we've been talking about Flow, at least the capabilities, over the last year. We spent significant resources building it. But we realized that we needed an additional thing to augment its value because the world of applications especially discovering application topologies is a heady problem. And if we didn't address that, we wouldn't be fulfilling on this ambition of providing one-click network segmentation. And so that's where Netsil comes in. Netsil might seem on the surface yet another next generation application performance management tool. But the innovations that came from Netsil started off at the research project at the University of Pennsylvania. And in fact, most of the team right now that's at Nutanix is from the U Penn research group. And they took a really original, fresh look at how do you sit in a network in a scale out fashion but still reverse engineer the packets, the flow through you, and then recreate this application topology. And recreate this not just on Nutanix, but do it seamlessly across multiple clouds. And to talk about the power of Flow augmented with Netsil, let's bring Rajiv back on stage, Rajiv. >> How you doing? >> Okay so we're going to start with some Netsil stuff, right? >> Yeah, let's talk about Netsil and some of the amazing capabilities this acquisition's bringing to Nutanix. First of all as you mentioned, Netsil's completely non invasive. So it installs on the network, it does all its magic from there. There're no host agents, non of the complexity and compatibility issues that entails. It's also monitoring the network at layer seven. So it's actually doing a deep packet inspection on all your application data, and can give you insights into services and APIs which is very important for modern applications and the way they behave. To do all this of course performance is key. So Netsil's built around a completely distributed architecture scaled to really large workloads. Very exciting technology. We're going to use it in many different ways at Nutanix. And to give you a flavor of that, let me show you how we're thinking of integrating Flow and Nestil together, so micro segmentation and Netsil. So to do that, we install Netsil in one of our Google accounts. And that's what's up here now. It went out there. It discovered all the VMs we're running on that account. It created a map essentially of all their interactions, and you can see it's like a Google Maps view. I can zoom into it. I can look at various things running. I can see lots of HTTP servers over here, some databases. >> Sunil: And it also has stats, right? You can go, it actually-- >> It does. We can take a look at that for a second. There are some stats you can look at right away here. Things like transactions per second and latencies and so on. But if I wanted to micro segment this application, it's not really clear how to do so. There's no real pattern over here. Taking the Google Maps analogy a little further, this kind of looks like the backstreets of Cairo or something. So let's do this step by step. Let me first filter down to one application. Right now I'm looking at about three or four different applications. And Netsil integrates with the metadata. So this is that the clouds provide. So I can search all the tags that I have. So by doing that, I can zoom in on just the financial application. And when I do this, the view gets a little bit simpler, but there's still no real pattern. It's not clear how to micro segment this, right? And this is where the power of Netsil comes in. This is a fairly naive view. This is what tool operating at layer four just looking at ports and TCP traffic would give you. But by doing deep packet inspection, Netsil can get into the services layer. So instead of grouping these interactions by hostname, let's group them by service. So you go service tier. And now you can see this is a much simpler picture. Now I have some patterns. I have a couple of load balancers, an HA proxy and an Nginx. I have a web application front end. I have some application servers running authentication services, search services, et cetera, a database, and a database replica. I could go ahead and micro segment at this point. It's quite possible to do it at this point. But this is almost too granular a view. We actually don't usually want to micro segment at individual service level. You think more in terms of application tiers, the tiers that different services belong to. So let me go ahead and group this differently. Let me group this by app tier. And when I do that, a really simple picture emerges. I have a load balancing tier talking to a web application front end tier, an API tier, and a database tier. Four tiers in my application. And this is something I can work with. This is something that I can micro segment fairly easily. So let's switch over to-- >> Before we dot that though, do you guys see how he gave himself the pseudonym called Dom Toretto? >> Focus Sunil, focus. >> Yeah, for those guys, you know that's not the Avengers theme, man, that's the Fast and Furious theme. >> Rajiv: I think a year ahead. This is next years theme. >> Got it, okay. So before we cut over from Netsil to Flow, do we want to talk a few words about the power of Flow, and what's available in 5.6? >> Sure so Flow's been around since the 5.6 release. Actually some of the functionality came in before that. So it's got invisibility into the network. It helps you debug problems with WLANs and so on. We had a lot of orchestration with other third party vendors with load balancers, with switches to make publishing much simpler. And then of course with our most recent release, we GA'ed our micro segmentation capabilities. And that of course is the most important feature we have in Flow right now. And if you look at how Flow policy is set up, it looks very similar to what we just saw with Netsil. So we have load blancer talking to a web app, API, database. It's almost identical to what we saw just a moment ago. So while this policy was created manually, it is something that we can automate. And it is something that we will do in future releases. Right now, it's of course not been integrated at that level yet. So this was created manually. So one thing you'll notice over here is that the database tier doesn't get any direct traffic from the internet. All internet traffic goes to the load balancer, only specific services then talk to the database. So this policy right now is in monitoring mode. It's not actually being enforced. So let's see what happens if I try to attack the database, I start a hack against the database. And I have my trusty brute force password script over here. It's trying the most common passwords against the database. And if I happen to choose a dictionary word or left the default passwords on, eventually it will log into the database. And when I go back over here in Flow what happens is it actually detects there's now an ongoing a flow, a flow that's outside of policy that's shown up. And it shows this in yellow. So right alongside the policy, I can visualize all the noncompliant flows. This makes it really easy for me now to make decisions, does this flow should it be part of the policy, should it not? In this particular case, obviously it should not be part of the policy. So let me just switch from monitoring mode to enforcement mode. I'll apply the policy, give it a second to propagate. The flow goes away. And if I go back to my script, you can see now the socket's timing out. I can no longer connect to the database. >> Sunil: Got it. So that's like one click segmentation and play right now? >> Absolutely. It's really, really simple. You can compare it to other products in the space. You can't get simpler than this. >> Got it. Why don't we got back and talk a little bit more about, so that's Flow. It's shipping now in 5.6 obviously. It'll come integrated with Netsil functionality as well as a variety of other enhancements in that next few releases. But Netsil does more than just simple topology discovery, right? >> Absolutely. So Netsil's actually gathering a lot of metrics from your network, from your host, all this goes through a data pipeline. It gets processed over there and then gets captured in a time series database. And then we can slice and dice that in various different ways. It can be used for all kinds of insights. So let's see how our application's behaving. So let me say I want to go into the API layer over here. And I instantly get a variety of metrics on how the application's behaving. I get the most requested endpoints. I get the average latency. It looks reasonably good. I get the average latency of the slowest endpoints. If I was having a performance problem, I would know exactly where to go focus on. Right now, things look very good, so we won't focus on that. But scrolling back up, I notice that we have a fairly high error rate happening. We have like 11.35% of our HTTP requests are generating errors, and that deserves some attention. And if I scroll down again, and I see the top five status codes I'm getting, almost 10% of my requests are generating 500 errors, HTTP 500 errors which are internal server errors. So there's something going on that's wrong with this application. So let's dig a little bit deeper into that. Let me go into my analytics workbench over here. And what I've plotted over here is how my HTTP requests are behaving over time. Let me filter down to just the 500 ones. That will make it easier. And I want the 500s. And I'll also group this by the service tier so that I can see which services are causing the problem. And the better view for this would be a bar graph. Yes, so once I do this, you can see that all the errors, all the 500 errors that we're seeing have been caused by the authentication service. So something's obviously wrong with that part of my application. I can go look at whether Active Directory is misbehaving and so on. So very quickly from a broad problem that I was getting a high HTTP error rate. In fact, usually you will discover there's this customer complaining about a lot of errors happening in your application. You can quickly narrow down to exactly what the cause was. >> Got it. This is what we mean by hyperconvergence of the network which is if you can truly isolate network related problems and associate them with the rest of the hyperconvergence infrastructure, then we've essentially started making real progress towards the next level of hyperconvergence. Anyway, thanks a lot, man. Great job. >> Thanks, man. (audience clapping) >> So to talk about this evolution from invisible infrastructure to invisible data centers is another customer of ours that has embarked on this journey. And you know it's not just using Nutanix but a variety of other tools to actually fulfill sort of like the ambition of a full blown cloud stack within a financial organization. And to talk more about that, let me call Vijay onstage. Come on up, Vijay. (rock music) >> Hey. >> Thank you, sir. So Vijay looks way better in real life than in a picture by the way. >> Except a little bit of gray. >> Unlike me. So tell me a little bit about this cloud initiative. >> Yeah. So we've won the best cloud initiative twice now hosted by Incisive media a large magazine. It's basically they host a bunch of you know various buy side, sell side, and you can submit projects in various categories. So we've won the best cloud twice now, 2015 and 2017. The 2017 award is when you know as part of our private cloud journey we were laying the foundation for our private cloud which is 100% based on hyperconverged infrastructure. So that was that award. And then 2017, we've kind of built on that foundation and built more developer-centric next gen app services like PAS, CAS, SDN, SDS, CICD, et cetera. So we've built a lot of those services on, and the second award was really related to that. >> Got it. And a lot of this was obviously based on an infrastructure strategy with some guiding principles that you guys had about three or four years ago if I remember. >> Yeah, this is a great slide. I use it very often. At the core of our infrastructure strategy is how do we run IT as a business? I talk about this with my teams, they were very familiar with this. That's the mindset that I instill within the teams. The mission, the challenge is the same which is how do we scale infrastructure while reducing total cost of ownership, improving time to market, improving client experience and while we're doing that not lose sight of reliability, stability, and security? That's the mission. Those are some of our guiding principles. Whenever we take on some large technology investments, we take 'em through those lenses. Obviously Nutanix went through those lenses when we invested in you guys many, many years ago. And you guys checked all the boxes. And you know initiatives change year on year, the mission remains the same. And more recently, the last few years, we've been focused on converged platforms, converged teams. We've actually reorganized our teams and aligned them closer to the platforms moving closer to an SRE like concept. >> And then you've built out a full stack now across computer storage, networking, all the way with various use cases in play? >> Yeah, and we're aggressively moving towards PAS, CAS as our method of either developing brand new cloud native applications or even containerizing existing applications. So the stack you know obviously built on Nutanix, SDS for software fine storage, compute and networking we've got SDN turned on. We've got, again, PAS and CAS built on this platform. And then finally, we've hooked our CICD tooling onto this. And again, the big picture was always frictionless infrastructure which we're very close to now. You know 100% of our code deployments into this environment are automated. >> Got it. And so what's the net, net in terms of obviously the business takeaway here? >> Yeah so at Northern we don't do tech for tech. It has to be some business benefits, client benefits. There has to be some outcomes that we measure ourselves against, and these are some great metrics or great ways to look at if we're getting the outcomes from the investments we're making. So for example, infrastructure scale while reducing total cost of ownership. We're very focused on total cost of ownership. We, for example, there was a build team that was very focus on building servers, deploying applications. That team's gone down from I think 40, 45 people to about 15 people as one example, one metric. Another metric for reducing TCO is we've been able to absorb additional capacity without increasing operating expenses. So you're actually building capacity in scale within your operating model. So that's another example. Another example, right here you see on the screen. Faster time to market. We've got various types of applications at any given point that we're deploying. There's a next gen cloud native which go directly on PAS. But then a majority of the applications still need the traditional IS components. The time to market to deploy a complex multi environment, multi data center application, we've taken that down by 60%. So we can deliver server same day, but we can deliver entire environments, you know add it to backup, add it to DNS, and fully compliant within a couple of weeks which is you know something we measure very closely. >> Great job, man. I mean that's a compelling I think results. And in the journey obviously you got promoted a few times. >> Yep. >> All right, congratulations again. >> Thank you. >> Thanks Vijay. >> Hey Vijay, come back here. Actually we forgot our joke. So razzled by his data points there. So you're supposed to wear some shoes, right? >> I know my inner glitch. I was going to wear those sneakers, but I forgot them at the office maybe for the right reasons. But the story behind those florescent sneakers, I see they're focused on my shoes. But I picked those up two years ago at a Next event, and not my style. I took 'em to my office. They've been sitting in my office for the last couple years. >> Who's received shoes like these by the way? I'm sure you guys have received shoes like these. There's some real fans there. >> So again, I'm sure many of you liked them. I had 'em in my office. I've offered it to so many of my engineers. Are you size 11? Do you want these? And they're unclaimed? >> So that's the only feature of Nutanix that you-- >> That's the only thing that hasn't worked, other than that things are going extremely well. >> Good job, man. Thanks a lot. >> Thanks. >> Thanks Vijay. So as we get to the final phase which is obviously as we embark on this multi-cloud journey and the complexity that comes with it which Dheeraj hinted towards in his session. You know we have to take a cautious, thoughtful approach here because we don't want to over set expectations because this will take us five, 10 years to really do a good job like we've done in the first act. And the good news is that the market is also really, really early here. It's just a fact. And so we've taken a tiered approach to it as we'll start the discussion with multi-cloud operations, and we've talked about the stack in the prior session which is about look across new clouds. So it's no longer Nutanix, Dell, Lenova, HP, Cisco as the new quote, unquote platforms. It's Nutanix, Xi, GCP, AWS, Azure as the new platforms. That's how we're designing the fabric going forward. On top of that, you obviously have the hybrid OS both on the data plane side and control plane side. Then what you're seeing with the advent of Calm doing a marketplace and automation as well as Beam doing governance and compliance is the fact that you'll see more and more such capabilities of multi-cloud operations burnt into the platform. And example of that is Calm with the new 5.7 release that they had. Launch supports multiple clouds both inside and outside, but the fundamental premise of Calm in the multi-cloud use case is to enable you to choose the right cloud for the right workload. That's the automation part. On the governance part, and this we kind of went through in the last half an hour with Dheeraj and Vijay on stage is something that's even more, if I can call it, you know first order because you get the provisioning and operations second. The first order is to say look whatever my developers have consumed off public cloud, I just need to first get our arm around to make sure that you know what am I spending, am I secure, and then when I get comfortable, then I am able to actually expand on it. And that's the power of Beam. And both Beam and Calm will be the yin and yang for us in our multi-cloud portfolio. And we'll have new products to complement that down the road, right? But along the way, that's the whole private cloud, public cloud. They're the two ends of the barbell, and over time, and we've been working on Xi for awhile, is this conviction that we've built talking to many customers that there needs to be another type of cloud. And this type of a cloud has to feel like a public cloud. It has to be architected like a public cloud, be consumed like a public cloud, but it needs to be an extension of my data center. It should not require any changes to my tooling. It should not require and changes to my operational infrastructure, and it should not require lift and shift, and that's a super hard problem. And this problem is something that a chunk of our R and D team has been burning the midnight wick on for the last year and a half. Because look this is not about taking our current OS which does a good job of scaling and plopping it into a Equinix or a third party data center and calling it a hybrid cloud. This is about rebuilding things in the OS so that we can deliver a true hybrid cloud, but at the same time, give those functionality back on premises so that even if you don't have a hybrid cloud, if you just have your own data centers, you'll still need new services like DR. And if you think about it, what are we doing? We're building a full blown multi-tenant virtual network designed in a modern way. Think about this SDN 2.0 because we have 10 years worth of looking backwards on how GCP has done it, or how Amazon has done it, and now sort of embodying some of that so that we can actually give it as part of this cloud, but do it in a way that's a seamless extension of the data center, and then at the same time, provide new services that have never been delivered before. Everyone obviously does failover and failback in DR it just takes months to do it. Our goal is to do it in hours or minutes. But even things such as test. Imagine doing a DR test on demand for you business needs in the middle of the day. And that's the real bar that we've set for Xi that we are working towards in early access later this summer with GA later in the year. And to talk more about this, let me invite some of our core architects working on it, Melina and Rajiv. (rock music) Good to see you guys. >> You're messing up the names again. >> Oh Rajiv, Vinny, same thing, man. >> You need to back up your memory from Xi. >> Yeah, we should. Okay, so what are we going to talk about, Vinny? >> Yeah, exactly. So today we're going to talk about how Xi is pushing the envelope and beyond the state of the art as you were saying in the industry. As part of that, there's a whole bunch of things that we have done starting with taking a private cloud, seamlessly extending it to the public cloud, and then creating a hybrid cloud experience with one-click delight. We're going to show that. We've done a whole bunch of engineering work on making sure the operations and the tooling is identical on both sides. When you graduate from a private cloud to a hybrid cloud environment, you don't want the environments to be different. So we've copied the environment for you with zero manual intervention. And finally, building on top of that, we are delivering DR as a service with unprecedented simplicity with one-click failover, one-click failback. We're going to show you one click test today. So Melina, why don't we start with showing how you go from a private cloud, seamlessly extend it to consume Xi. >> Sounds good, thanks Vinny. Right now, you're looking at my Prism interface for my on premises cluster. In one-click, I'm going to be able to extend that to my Xi cloud services account. I'm doing this using my my Nutanix credential and a password manager. >> Vinny: So here as you notice all the Nutanix customers we have today, we have created an account for them in Xi by default. So you don't have to log in somewhere and create an account. It's there by default. >> Melina: And just like that we've gone ahead and extended my data center. But let's go take a look at the Xi side and log in again with my my Nutanix credentials. We'll see what we have over here. We're going to be able to see two availability zones, one for on premises and one for Xi right here. >> Vinny: Yeah as you see, using a log in account that you already knew mynutanix.com and 30 seconds in, you can see that you have a hybrid cloud view already. You have a private cloud availability zone that's your own Prism central data center view, and then a Xi availability zone. >> Sunil: Got it. >> Melina: Exactly. But of course we want to extend my network connection from on premises to my Xi networks as well. So let's take a look at our options there. We have two ways of doing this. Both are one-click experience. With direct connect, you can create a dedicated network connection between both environments, or VPN you can use a public internet and a VPN service. Let's go ahead and enable VPN in this environment. Here we have two options for how we want to enable our VPN. We can bring our own VPN and connect it, or we will deploy a VPN for you on premises. We'll do the option where we deploy the VPN in one-click. >> And this is another small sign or feature that we're building net new as part of Xi, but will be burned into our core Acropolis OS so that we can also be delivering this as a stand alone product for on premises deployment as well, right? So that's one of the other things to note as you guys look at the Xi functionality. The goal is to keep the OS capabilities the same on both sides. So even if I'm building a quote, unquote multi data center cloud, but it's just a private cloud, you'll still get all the benefits of Xi but in house. >> Exactly. And on this second step of the wizard, there's a few inputs around how you want the gateway configured, your VLAN information and routing and protocol configuration details. Let's go ahead and save it. >> Vinny: So right now, you know what's happening is we're taking the private network that our customers have on premises and extending it to a multi-tenant public cloud such that our customers can use their IP addresses, the subnets, and bring their own IP. And that is another step towards making sure the operation and tooling is kept consistent on both sides. >> Melina: Exactly. And just while you guys were talking, the VPN was successfully created on premises. And we can see the details right here. You can track details like the status of the connection, the gateway, as well as bandwidth information right in the same UI. >> Vinny: And networking is just tip of the iceberg of what we've had to work on to make sure that you get a consistent experience on both sides. So Melina, why don't we show some of the other things we've done? >> Melina: Sure, to talk about how we preserve entities from my on-premises to Xi, it's better to use my production environment. And first thing you might notice is the log in screen's a little bit different. But that's because I'm logging in using my ADFS credentials. The first thing we preserved was our users. In production, I'm running AD obviously on-prem. And now we can log in here with the same set of credentials. Let me just refresh this. >> And this is the Active Directory credential that our customers would have. They use it on-premises. And we allow the setting to be set on the Xi cloud services as well, so it's the same set of users that can access both sides. >> Got it. There's always going to be some networking problem onstage. It's meant to happen. >> There you go. >> Just launching it again here. I think it maybe timed out. This is a good sign that we're running on time with this presentation. >> Yeah, yeah, we're running ahead of time. >> Move the demos quicker, then we'll time out. So essentially when you log into Xi, you'll be able to see what are the environment capabilities that we have copied to the Xi environment. So for example, you just saw that the same user is being used to log in. But after the use logs in, you'll be able to see their images, for example, copied to the Xi side. You'll be able to see their policies and categories. You know when you define these policies on premises, you spend a lot of effort and create them. And now when you're extending to the public cloud, you don't want to do it again, right? So we've done a whole lot of syncing mechanisms making sure that the two sides are consistent. >> Got it. And on top of these policies, the next step is to also show capabilities to actually do failover and failback, but also do integrated testing as part of this compatibility. >> So one is you know just the basic job of making the environments consistent on two sides, but then it's also now talking about the data part, and that's what DR is about. So if you have a workload running on premises, we can take the data and replicate it using your policies that we've already synced. Once the data is available on the Xi side, at that point, you have to define a run book. And the run book essentially it's a recovery plan. And that says okay I already have the backups of my VMs in case of disaster. I can take my recovery plan and hit you know either failover or maybe a test. And then my application comes up. First of all, you'll talk about the boot order for your VMs to come up. You'll talk about networking mapping. Like when I'm running on-prem, you're using a particular subnet. You have an option of using the same subnet on the Xi side. >> Melina: There you go. >> What happened? >> Sunil: It's finally working.? >> Melina: Yeah. >> Vinny, you can stop talking. (audience clapping) By the way, this is logging into a live Xi data center. We have two regions West Coat, two data centers East Coast, two data centers. So everything that you're seeing is essentially coming off the mainstream Xi profile. >> Vinny: Melina, why don't we show the recovery plan. That's the most interesting piece here. >> Sure. The recovery plan is set up to help you specify how you want to recover your applications in the event of a failover or a test failover. And it specifies all sorts of details like the boot sequence for the VMs as well as network mappings. Some of the network mappings are things like the production network I have running on premises and how it maps to my production network on Xi or the test network to the test network. What's really cool here though is we're actually automatically creating your subnets on Xi from your on premises subnets. All that's part of the recovery plan. While we're on the screen, take a note of the .100 IP address. That's a floating IP address that I have set up to ensure that I'm going to be able to access my three tier web app that I have protected with this plan after a failover. So I'll be able to access it from the public internet really easily from my phone or check that it's all running. >> Right, so given how we make the environment consistent on both sides, now we're able to create a very simple DR experience including failover in one-click, failback. But we're going to show you test now. So Melina, let's talk about test because that's one of the most common operations you would do. Like some of our customers do it every month. But usually it's very hard. So let's see how the experience looks like in what we built. >> Sure. Test and failover are both one-click experiences as you know and come to expect from Nutanix. You can see it's failing over from my primary location to my recovery location. Now what we're doing right now is we're running a series of validation checks because we want to make sure that you have your network configured properly, and there's other configuration details in place for the test to be successful. Looks like the failover was initiated successfully. Now while that failover's happening though, let's make sure that I'm going to be able to access my three tier web app once it fails over. We'll do that by looking at my network policies that I've configured on my test network. Because I want to access the application from the public internet but only port 80. And if we look here under our policies, you can see I have port 80 open to permit. So that's good. And if I needed to create a new one, I could in one click. But it looks like we're good to go. Let's go back and check the status of my recovery plan. We click in, and what's really cool here is you can actually see the individual tasks as they're being completed from that initial validation test to individual VMs being powered on as part of the recovery plan. >> And to give you guys an idea behind the scenes, the entire recovery plan is actually a set of workflows that are built on Calm's automation engine. So this is an example of where we're taking some of power of workflow and automation that Clam has come to be really strong at and burning that into how we actually operationalize many of these workflows for Xi. >> And so great, while you were explaining that, my three tier web app has restarted here on Xi right in front of you. And you can see here there's a floating IP that I mentioned early that .100 IP address. But let's go ahead and launch the console and make sure the application started up correctly. >> Vinny: Yeah, so that .100 IP address is a floating IP that's a publicly visible IP. So it's listed here, 206.80.146.100. And that's essentially anybody in the audience here can go use your laptop or your cell phone and hit that and start to work. >> Yeah so by the way, just to give you guys an idea while you guys maybe use the IP to kind of hit it, is a real set of VMs that we've just failed over from Nutanix's corporate data center into our West region. >> And this is running live on the Xi cloud. >> Yeah, you guys should all go and vote. I'm a little biased towards Xi, so vote for Xi. But all of them are really good features. >> Scroll up a little bit. Let's see where Xi is. >> Oh Xi's here. I'll scroll down a little bit, but keep the... >> Vinny: Yes. >> Sunil: You guys written a block or something? >> Melina: Oh good, it looks like Xi's winning. >> Sunil: Okay, great job, Melina. Thank you so much. >> Thank you, Melina. >> Melina: Thanks. >> Thank you, great job. Cool and calm under pressure. That's good. So that was Xi. What's something that you know we've been doing around you know in addition to taking say our own extended enterprise public cloud with Xi. You know we do recognize that there are a ton of workloads that are going to be residing on AWS, GCP, Azure. And to sort of really assist in the try and call it transformation of enterprises to choose the right cloud for the right workload. If you guys remember, we actually invested in a tool over last year which became actually quite like one of those products that took off based on you know groundswell movement. Most of you guys started using it. It's essentially extract for VMs. And it was this product that's obviously free. It's a tool. But it enables customers to really save tons of time to actually migrate from legacy environments to Nutanix. So we took that same framework, obviously re-platformed it for the multi-cloud world to kind of solve the problem of migrating from AWS or GCP to Nutanix or vice versa. >> Right, so you know, Sunil as you said, moving from a private cloud to the public cloud is a lift and shift, and it's a hard you know operation. But moving back is not only expensive, it's a very hard problem. None of the cloud vendors provide change block tracking capability. And what that means is when you have to move back from the cloud, you have an extended period of downtime because there's now way of figuring out what's changing while you're moving. So you have to keep it down. So what we've done with our app mobility product is we have made sure that, one, it's extremely simple to move back. Two, that the downtime that you'll have is as small as possible. So let me show you what we've done. >> Got it. >> So here is our app mobility capability. As you can see, on the left hand side we have a source environment and target environment. So I'm calling my AWS environment Asgard. And I can add more environments. It's very simple. I can select AWS and then put in my credentials for AWS. It essentially goes and discovers all the VMs that are running and all the regions that they're running. Target environment, this is my Nutanix environment. I call it Earth. And I can add target environment similarly, IP address and credentials, and we do the rest. Right, okay. Now migration plans. I have Bifrost one as my migration plan, and this is how migration works. First you create a plan and then say start seeding. And what it does is takes a snapshot of what's running in the cloud and starts migrating it to on-prem. Once it is an on-prem and the difference between the two sides is minimal, it says I'm ready to cutover. At that time, you move it. But let me show you how you'd create a new migration plan. So let me name it, Bifrost 2. Okay so what I have to do is select a region, so US West 1, and target Earth as my cluster. This is my storage container there. And very quickly you can see these are the VMs that are running in US West 1 in AWS. I can select SQL server one and two, go to next. Right now it's looking at the target Nutanix environment and seeing it had enough space or not. Once that's good, it gives me an option. And this is the step where it enables the Nutanix service of change block tracking overlaid on top of the cloud. There are two options one is automatic where you'll give us the credentials for your VMs, and we'll inject our capability there. Or manually you could do. You could copy the command either in a windows VM or Linux VM and run it once on the VM. And change block tracking since then in enabled. Everything is seamless after that. Hit next. >> And while Vinny's setting it up, he said a few things there. I don't know if you guys caught it. One of the hardest problems in enabling seamless migration from public cloud to on-prem which makes it harder than the other way around is the fact that public cloud doesn't have things like change block tracking. You can't get delta copies. So one of the core innovations being built in this app mobility product is to provide that overlay capability across multiple clouds. >> Yeah, and the last step here was to select the target network where the VMs will come up on the Nutanix environment, and this is a summary of the migration plan. You can start it or just save it. I'm saving it because it takes time to do the seeding. I have the other plan which I'll actually show the cutover with. Okay so now this is Bifrost 1. It's ready to cutover. We started it four hours ago. And here you can see there's a SQL server 003. Okay, now I would like to show the AWS environment. As you can see, SQL server 003. This VM is actually running in AWS right now. And if you go to the Prism environment, and if my login works, right? So we can go into the virtual machine view, tables, and you see the VM is not there. Okay, so we go back to this, and we can hit cutover. So this is essentially telling our system, okay now it the time. Quiesce the VM running in AWS, take the last bit of changes that you have to the database, ship it to on-prem, and in on-prem now start you know configure the target VM and start bringing it up. So let's go and look at AWS and refresh that screen. And you should see, okay so the SQL server is now stopping. So that means it has quiesced and stopping the VM there. If you go back and look at the migration plan that we had, it says it's completed. So it has actually migrated all the data to the on-prem side. Go here on-prem, you see the production SQL server is running already. I can click launch console, and let's see. The Windows VM is already booting up. >> So essentially what Vinny just showed was a live cutover of an AWS VM to Nutanix on-premises. >> Yeah, and what we have done. (audience clapping) So essentially, this is about making two things possible, making it simple to migrate from cloud to on-prem, and making it painless so that the downtime you have is very minimal. >> Got it, great job, Vinny. I won't forget your name again. So last step. So to really talk about this, one of our favorite partners and customers has been in the cloud environment for a long time. And you know Jason who's the CTO of Cyxtera. And he'll introduce who Cyxtera is. Most of you guys are probably either using their assets or not without knowing their you know the new name. But is someone that was in the cloud before it was called cloud as one of the original founders and technologists behind Terremark, and then later as one of the chief architects of VMware's cloud. And then they started this new company about a year or so ago which I'll let Jason talk about. This journey that he's going to talk about is how a partner, slash customer is working with us to deliver net new transformations around the traditional industry of colo. Okay, to talk more about it, Jason, why don't you come up on stage, man? (rock music) Thank you, sir. All right so Cyxtera obviously a lot of people don't know the name. Maybe just give a 10 second summary of why you're so big already. >> Sure, so Cyxtera was formed, as you said, about a year ago through the acquisition of the CenturyLink data centers. >> Sunil: Which includes Savvis and a whole bunch of other assets. >> Yeah, there's a long history of those data centers, but we have all of them now as well as the software companies owned by Medina capital. So we're like the world's biggest startup now. So we have over 50 data centers around the world, about 3,500 customers, and a portfolio of security and analytics software. >> Sunil: Got it, and so you have this strategy of what we're calling revolutionizing colo deliver a cloud based-- >> Yeah so, colo hasn't really changed a lot in the last 20 years. And to be fair, a lot of what happens in data centers has to have a person physically go and do it. But there are some things that we can simplify and automate. So we want to make things more software driven, so that's what we're doing with the Cyxtera extensible data center or CXD. And to do that, we're deploying software defined networks in our facilities and developing automations so customers can go and provision data center services and the network connectivity through a portal or through REST APIs. >> Got it, and what's different now? I know there's a whole bunch of benefits with the integrated platform that one would not get in the traditional kind of on demand data center environment. >> Sure. So one of the first services we're launching on CXD is compute on demand, and it's powered by Nutanix. And we had to pick an HCI partner to launch with. And we looked at players in the space. And as you mentioned, there's actually a lot of them, more than I thought. And we had a lot of conversations, did a lot of testing in the lab, and Nutanix really stood out as the best choice. You know Nutanix has a lot of focus on things like ease of deployment. So it's very simple for us to automate deploying compute for customers. So we can use foundation APIs to go configure the servers, and then we turn those over to the customer which they can then manage through Prism. And something important to keep in mind here is that you know this isn't a manged service. This isn't infrastructure as a service. The customer has complete control over the Nutanix platform. So we're turning that over to them. It's connected to their network. They're using their IP addresses, you know their tools and processes to operate this. So it was really important for the platform we picked to have a really good self-service story for things like you know lifecycle management. So with one-click upgrade, customers have total control over patches and upgrades. They don't have to call us to do it. You know they can drive that themselves. >> Got it. Any other final words around like what do you see of the partnership going forward? >> Well you know I think this would be a great platform for Xi, so I think we should probably talk about that. >> Yeah, yeah, we should talk about that separately. Thanks a lot, Jason. >> Thanks. >> All right, man. (audience clapping) So as we look at the full journey now between obviously from invisible infrastructure to invisible clouds, you know there is one thing though to take away beyond many updates that we've had so far. And the fact is that everything that I've talked about so far is about completing a full blown true IA stack from all the way from compute to storage, to vitualization, containers to network services, and so forth. But every public cloud, a true cloud in that sense, has a full blown layer of services that's set on top either for traditional workloads or for new workloads, whether it be machine-learning, whether it be big data, you know name it, right? And in the enterprise, if you think about it, many of these services are being provisioned or provided through a bunch of our partners. Like we have partnerships with Cloudera for big data and so forth. But then based on some customer feedback and a lot of attention from what we've seen in the industry go out, just like AWS, and GCP, and Azure, it's time for Nutanix to have an opinionated view of the past stack. It's time for us to kind of move up the stack with our own offering that obviously adds value but provides some of our core competencies in data and takes it to the next level. And it's in that sense that we're actually launching Nutanix Era to simplify one of the hardest problems in enterprise IT and short of saving you from true Oracle licensing, it solves various other Oracle problems which is about truly simplifying databases much like what RDS did on AWS, imagine enterprise RDS on demand where you can provision, lifecycle manage your database with one-click. And to talk about this powerful new functionality, let me invite Bala and John on stage to give you one final demo. (rock music) Good to see you guys. >> Yep, thank you. >> All right, so we've got lots of folks here. They're all anxious to get to the next level. So this demo, really rock it. So what are we going to talk about? We're going to start with say maybe some database provisioning? Do you want to set it up? >> We have one dream, Sunil, one single dream to pass you off, that is what Nutanix is today for IT apps, we want to recreate that magic for devops and get back those weekends and freedom to DBAs. >> Got it. Let's start with, what, provisioning? >> Bala: Yep, John. >> Yeah, we're going to get in provisioning. So provisioning databases inside the enterprise is a significant undertaking that usually involves a myriad of resources and could take days. It doesn't get any easier after that for the longterm maintence with things like upgrades and environment refreshes and so on. Bala and team have been working on this challenge for quite awhile now. So we've architected Nutanix Era to cater to these enterprise use cases and make it one-click like you said. And Bala and I are so excited to finally show this to the world. We think it's actually Nutanix's best kept secrets. >> Got it, all right man, let's take a look at it. >> So we're going to be provisioning a sales database today. It's a four-step workflow. The first part is choosing our database engine. And since it's our sales database, we want it to be highly available. So we'll do a two node rack configuration. From there, it asks us where we want to land this service. We can either land it on an existing service that's already been provisioned, or if we're starting net new or for whatever reason, we can create a new service for it. The key thing here is we're not asking anybody how to do the work, we're asking what work you want done. And the other key thing here is we've architected this concept called profiles. So you tell us how much resources you need as well as what network type you want and what software revision you want. This is actually controlled by the DBAs. So DBAs, and compute administrators, and network administrators, so they can set their standards without having a DBA. >> Sunil: Got it, okay, let's take a look. >> John: So if we go to the next piece here, it's going to personalize their database. The key thing here, again, is that we're not asking you how many data files you want or anything in that regard. So we're going to be provisioning this to Nutanix's best practices. And the key thing there is just like these past services you don't have to read dozens of pages of best practice guides, it just does what's best for the platform. >> Sunil: Got it. And so these are a multitude of provisioning steps that normally one would take I guess hours if not days to provision and Oracle RAC data. >> John: Yeah, across multiple teams too. So if you think about the lifecycle especially if you have onshore and offshore resources, I mean this might even be longer than days. >> Sunil: Got it. And then there are a few steps here, and we'll lead into potentially the Time Machine construct too? >> John: Yeah, so since this is a critical database, we want data protection. So we're going to be delivering that through a feature called Time Machines. We'll leave this at the defaults for now, but the key thing to not here is we've got SLAs that deliver both continuous data protection as well as telescoping checkpoints for historical recovery. >> Sunil: Got it. So that's provisioning. We've kicked off Oracle, what, two node database and so forth? >> John: Yep, two node database. So we've got a handful of tasks that this is going to automate. We'll check back in in a few minutes. >> Got it. Why don't we talk about the other aspects then, Bala, maybe around, one of the things that, you know and I know many of you guys have seen this, is the fact that if you look at database especially Oracle but in general even SQL and so forth is the fact that look if you really simplified it to a developer, it should be as simple as I copy my production database, and I paste it to create my own dev instance. And whenever I need it, I need to obviously do it the opposite way, right? So that was the goal that we set ahead for us to actually deliver this new past service around Era for our customers. So you want to talk a little bit more about it? >> Sure Sunil. If you look at most of the data management functionality, they're pretty much like flavors of copy paste operations on database entities. But the trouble is the seemingly simple, innocuous operations of our daily lives becomes the most dreaded, complex, long running, error prone operations in data center. So we actually planned to tame this complexity and bring consumer grade simplicity to these operations, also make these clones extremely efficient without compromising the quality of service. And the best part is, the customers can enjoy these services not only for databases running on Nutanix, but also for databases running on third party systems. >> Got it. So let's take a look at this functionality of I guess snapshoting, clone and recovery that you've now built into the product. >> Right. So now if you see the core feature of this whole product is something we call Time Machine. Time Machine lets the database administrators actually capture the database tape to the granularity of seconds and also lets them create clones, refresh them to any point in time, and also recover the databases if the databases are running on the same Nutanix platform. Let's take a look at the demo with the Time Machine. So here is our customer relationship database management database which is about 2.3 terabytes. If you see, the Time Machine has been active about four months, and SLA has been set for continuously code revision of 30 days and then slowly tapers off 30 days of daily backup and weekly backups and so on, so forth. On the right hand side, you will see different colors. The green color is pretty much your continuously code revision, what we call them. That lets you to go back to any point in time to the granularity of seconds within those 30 days. And then the discreet code revision lets you go back to any snapshot of the backup that is maintained there kind of stuff. In a way, you see this Time Machine is pretty much like your modern day car with self driving ability. All you need to do is set the goals, and the Time Machine will do whatever is needed to reach up to the goal kind of stuff. >> Sunil: So why don't we quickly do a snapshot? >> Bala: Yeah, some of these times you need to create a snapshot for backup purposes, Time Machine has manual controls. All you need to do is give it a snapshot name. And then you have the ability to actually persist this snapshot data into a third party or object store so that your durability and that global data access requirements are met kind of stuff. So we kick off a snapshot operation. Let's look at what it is doing. If you see what is the snapshot operation that this is going through, there is a step called quiescing the databases. Basically, we're using application-centric APIs, and here it's actually RMAN of Oracle. We are using the RMan of Oracle to quiesce the database and performing application consistent storage snapshots with Nutanix technology. Basically we are fusing application-centric and then Nutanix platform and quiescing it. Just for a data point, if you have to use traditional technology and create a backup for this kind of size, it takes over four to six hours, whereas on Nutanix it's going to be a matter of seconds. So it almost looks like snapshot is done. This is full sensitive backup. You can pretty much use it for database restore kind of stuff. Maybe we'll do a clone demo and see how it goes. >> John: Yeah, let's go check it out. >> Bala: So for clone, again through the simplicity of command Z command, all you need to do is pick the time of your choice maybe around three o'clock in the morning today. >> John: Yeah, let's go with 3:02. >> Bala: 3:02, okay. >> John: Yeah, why not? >> Bala: You select the time, all you need to do is click on the clone. And most of the inputs that are needed for the clone process will be defaulted intelligently by us, right? And you have to make two choices that is where do you want this clone to be created with a brand new VM database server, or do you want to place that in your existing server? So we'll go with a brand new server, and then all you need to do is just give the password for you new clone database, and then clone it kind of stuff. >> Sunil: And this is an example of personalizing the database so a developer can do that. >> Bala: Right. So here is the clone kicking in. And what this is trying to do is actually it's creating a database VM and then registering the database, restoring the snapshot, and then recoding the logs up to three o'clock in the morning like what we just saw that, and then actually giving back the database to the requester kind of stuff. >> Maybe one finally thing, John. Do you want to show us the provision database that we kicked off? >> Yeah, it looks like it just finished a few seconds ago. So you can see all the tasks that we were talking about here before from creating the virtual infrastructure, and provisioning the database infrastructure, and configuring data protection. So I can go access this database now. >> Again, just to highlight this, guys. What we just showed you is an Oracle two node instance provisioned live in a few minutes on Nutanix. And this is something that even in a public cloud when you go to RDS on AWS or anything like that, you still can't provision Oracle RAC by the way, right? But that's what you've seen now, and that's what the power of Nutanix Era is. Okay, all right? >> Thank you. >> Thanks. (audience clapping) >> And one final thing around, obviously when we're building this, it's built as a past service. It's not meant just for operational benefits. And so one of the core design principles has been around being API first. You want to show that a little bit? >> Absolutely, Sunil, this whole product is built on API fist architecture. Pretty much what we have seen today and all the functionality that we've been able to show today, everything is built on Rest APIs, and you can pretty much integrate with service now architecture and give you your devops experience for your customers. We do have a plan for full fledged self-service portal eventually, and then make it as a proper service. >> Got it, great job, Bala. >> Thank you. >> Thanks, John. Good stuff, man. >> Thanks. >> All right. (audience clapping) So with Nutanix Era being this one-click provisioning, lifecycle management powered by APIs, I think what we're going to see is the fact that a lot of the products that we've talked about so far while you know I've talked about things like Calm, Flow, AHV functionality that have all been released in 5.5, 5.6, a bunch of the other stuff are also coming shortly. So I would strongly encourage you guys to kind of space 'em, you know most of these products that we've talked about, in fact, all of the products that we've talked about are going to be in the breakout sessions. We're going to go deep into them in the demos as well as in the pods. So spend some quality time not just on the stuff that's been shipping but also stuff that's coming out. And so one thing to keep in mind to sort of takeaway is that we're doing this all obviously with freedom as the goal. But from the products side, it has to be driven by choice whether the choice is based on platforms, it's based on hypervisors, whether it's based on consumption models and eventually even though we're starting with the management plane, eventually we'll go with the data plane of how do I actually provide a multi-cloud choice as well. And so when we wrap things up, and we look at the five freedoms that Ben talked about. Don't forget the sixth freedom especially after six to seven p.m. where the whole goal as a Nutanix family and extended family make sure we mix it up. Okay, thank you so much, and we'll see you around. (audience clapping) >> PA Announcer: Ladies and gentlemen, this concludes our morning keynote session. Breakouts will begin in 15 minutes. ♪ To do what I want ♪