(gentle music playing) >> For centuries, we've been captivated by the concept of machines doing the job of humans. And over the past decade or so, we've really focused on AI and the possibility of intelligent machines that can perform cognitive tasks. Now in the past few years, with the popularity of machine learning models ranging from recent ChatGPT to Bert, we're starting to see how AI is changing the way we interact with the world. How is AI transforming the way we do business? And what does the future hold for us there. At theCube, we've covered Oracle's AI and ML strategy for years, which has really been used to drive automation into Oracle's autonomous database. We've talked a lot about MySQL HeatWave in database machine learning, and AI pushed into Oracle's business apps. Oracle, it tends to lead in AI, but not competing as a direct AI player per se, but rather embedding AI and machine learning into its portfolio to enhance its existing products, and bring new services and offerings to the market. Now, last October at Cloud World in Las Vegas, Oracle partnered with Nvidia, which is the go-to AI silicon provider for vendors. And they announced an investment, a pretty significant investment to deploy tens of thousands more Nvidia GPUs to OCI, the Oracle Cloud Infrastructure and build out Oracle's infrastructure for enterprise scale AI. Now, Oracle CEO, Safra Catz said something to the effect of this alliance is going to help customers across industries from healthcare, manufacturing, telecoms, and financial services to overcome the multitude of challenges they face. Presumably she was talking about just driving more automation and more productivity. Now, to learn more about Oracle's plans for AI, we'd like to welcome in Elad Ziklik, who's the vice president of AI services at Oracle. Elad, great to see you. Welcome to the show. >> Thank you. Thanks for having me. >> You're very welcome. So first let's talk about Oracle's path to AI. I mean, it's the hottest topic going for years you've been incorporating machine learning into your products and services, you know, could you tell us what you've been working on, how you got here? >> So great question. So as you mentioned, I think most of the original four-way into AI was on embedding AI and using AI to make our applications, and databases better. So inside mySQL HeatWave, inside our autonomous database in power, we've been driving AI, all of course are SaaS apps. So Fusion, our large enterprise business suite for HR applications and CRM and ELP, and whatnot has built in AI inside it. Most recently, NetSuite, our small medium business SaaS suite started using AI for things like automated invoice processing and whatnot. And most recently, over the last, I would say two years, we've started exposing and bringing these capabilities into the broader OCI Oracle Cloud infrastructure. So the developers, and ISVs and customers can start using our AI capabilities to make their apps better and their experiences and business workflow better, and not just consume these as embedded inside Oracle. And this recent partnership that you mentioned with Nvidia is another step in bringing the best AI infrastructure capabilities into this platform so you can actually build any type of machine learning workflow or AI model that you want on Oracle Cloud. >> So when I look at the market, I see companies out there like DataRobot or C3 AI, there's maybe a half dozen that sort of pop up on my radar anyway. And my premise has always been that most customers, they don't want to become AI experts, they want to buy applications and have AI embedded or they want AI to manage their infrastructure. So my question to you is, how does Oracle help its OCI customers support their business with AI? >> So it's a great question. So I think what most customers want is business AI. They want AI that works for the business. They want AI that works for the enterprise. I call it the last mile of AI. And they want this thing to work. The majority of them don't want to hire a large and expensive data science teams to go and build everything from scratch. They just want the business problem solved by applying AI to it. My best analogy is Lego. So if you think of Lego, Lego has these millions Lego blocks that you can use to build anything that you want. But the majority of people like me or like my kids, they want the Lego death style kit or the Lego Eiffel Tower thing. They want a thing that just works, and it's very easy to use. And still Lego blocks, you still need to build some things together, which just works for the scenario that you're looking for. So that's our focus. Our focus is making it easy for customers to apply AI where they need to, in the right business context. So whether it's embedding it inside the business applications, like adding forecasting capabilities to your supply chain management or financial planning software, whether it's adding chat bots into the line of business applications, integrating these things into your analytics dashboard, even all the way to, we have a new platform piece we call ML applications that allows you to take a machine learning model, and scale it for the thousands of tenants that you would be. 'Cause this is a big problem for most of the ML use cases. It's very easy to build something for a proof of concept or a pilot or a demo. But then if you need to take this and then deploy it across your thousands of customers or your thousands of regions or facilities, then it becomes messy. So this is where we spend our time making it easy to take these things into production in the context of your business application or your business use case that you're interested in right now. >> So you mentioned chat bots, and I want to talk about ChatGPT, but my question here is different, we'll talk about that in a minute. So when you think about these chat bots, the ones that are conversational, my experience anyway is they're just meh, they're not that great. But the ones that actually work pretty well, they have a conditioned response. Now they're limited, but they say, which of the following is your problem? And then if that's one of the following is your problem, you can maybe solve your problem. But this is clearly a trend and it helps the line of business. How does Oracle think about these use cases for your customers? >> Yeah, so I think the key here is exactly what you said. It's about task completion. The general purpose bots are interesting, but as you said, like are still limited. They're getting much better, I'm sure we'll talk about ChatGPT. But I think what most enterprises want is around task completion. I want to automate my expense report processing. So today inside Oracle we have a chat bot where I submit my expenses the bot ask a couple of question, I answer them, and then I'm done. Like I don't need to go to our fancy application, and manually submit an expense report. I do this via Slack. And the key is around managing the right expectations of what this thing is capable of doing. Like, I have a story from I think five, six years ago when technology was much inferior than it is today. Well, one of the telco providers I was working with wanted to roll a chat bot that does realtime translation. So it was for a support center for of the call centers. And what they wanted do is, Hey, we have English speaking employees, whatever, 24/7, if somebody's calling, and the native tongue is different like Hebrew in my case, or Chinese or whatnot, then we'll give them a chat bot that they will interact with and will translate this on the fly and everything would work. And when they rolled it out, the feedback from customers was horrendous. Customers said, the technology sucks. It's not good. I hate it, I hate your company, I hate your support. And what they've done is they've changed the narrative. Instead of, you go to a support center, and you assume you're going to talk to a human, and instead you get a crappy chat bot, they're like, Hey, if you want to talk to a Hebrew speaking person, there's a four hour wait, please leave your phone and we'll call you back. Or you can try a new amazing Hebrew speaking AI powered bot and it may help your use case. Do you want to try it out? And some people said, yeah, let's try it out. Plus one to try it out. And the feedback, even though it was the exact same technology was amazing. People were like, oh my God, this is so innovative, this is great. Even though it was the exact same experience that they hated a few weeks earlier on. So I think the key lesson that I picked from this experience is it's all about setting the right expectations, and working around the right use case. If you are replacing a human, the level is different than if you are just helping or augmenting something that otherwise would take a lot of time. And I think this is the focus that we are doing, picking up the tasks that people want to accomplish or that enterprise want to accomplish for the customers, for the employees. And using chat bots to make those specific ones better rather than, hey, this is going to replace all humans everywhere, and just be better than that. >> Yeah, I mean, to the point you mentioned expense reports. I'm in a Twitter thread and one guy says, my favorite part of business travel is filling out expense reports. It's an hour of excitement to figure out which receipts won't scan. We can all relate to that. It's just the worst. When you think about companies that are building custom AI driven apps, what can they do on OCI? What are the best options for them? Do they need to hire an army of machine intelligence experts and AI specialists? Help us understand your point of view there. >> So over the last, I would say the two or three years we've developed a full suite of machine learning and AI services for, I would say probably much every use case that you would expect right now from applying natural language processing to understanding customer support tickets or social media, or whatnot to computer vision platforms or computer vision services that can understand and detect objects, and count objects on shelves or detect cracks in the pipe or defecting parts, all the way to speech services. It can actually transcribe human speech. And most recently we've launched a new document AI service. That can actually look at unstructured documents like receipts or invoices or government IDs or even proprietary documents, loan application, student application forms, patient ingestion and whatnot and completely automate them using AI. So if you want to do one of the things that are, I would say common bread and butter for any industry, whether it's financial services or healthcare or manufacturing, we have a suite of services that any developer can go, and use easily customized with their own data. You don't need to be an expert in deep learning or large language models. You could just use our automobile capabilities, and build your own version of the models. Just go ahead and use them. And if you do have proprietary complex scenarios that you need customer from scratch, we actually have the most cost effective platform for that. So we have the OCI data science as well as built-in machine learning platform inside the databases inside the Oracle database, and mySQL HeatWave that allow data scientists, python welding people that actually like to build and tweak and control and improve, have everything that they need to go and build the machine learning models from scratch, deploy them, monitor and manage them at scale in production environment. And most of it is brand new. So we did not have these technologies four or five years ago and we've started building them and they're now at enterprise scale over the last couple of years. >> So what are some of the state-of-the-art tools, that AI specialists and data scientists need if they're going to go out and develop these new models? >> So I think it's on three layers. I think there's an infrastructure layer where the Nvidia's of the world come into play. For some of these things, you want massively efficient, massively scaled infrastructure place. So we are the most cost effective and performant large scale GPU training environment today. We're going to be first to onboard the new Nvidia H100s. These are the new super powerful GPU's for large language model training. So we have that covered for you in case you need this 'cause you want to build these ginormous things. You need a data science platform, a platform where you can open a Python notebook, and just use all these fancy open source frameworks and create the models that you want, and then click on a button and deploy it. And it infinitely scales wherever you need it. And in many cases you just need the, what I call the applied AI services. You need the Lego sets, the Lego death style, Lego Eiffel Tower. So we have a suite of these sets for typical scenarios, whether it's cognitive services of like, again, understanding images, or documents all the way to solving particular business problems. So an anomaly detection service, demand focusing service that will be the equivalent of these Lego sets. So if this is the business problem that you're looking to solve, we have services out there where we can bring your data, call an API, train a model, get the model and use it in your production environment. So wherever you want to play, all the way into embedding this thing, inside this applications, obviously, wherever you want to play, we have the tools for you to go and engage from infrastructure to SaaS at the top, and everything in the middle. >> So when you think about the data pipeline, and the data life cycle, and the specialized roles that came out of kind of the (indistinct) era if you will. I want to focus on two developers and data scientists. So the developers, they hate dealing with infrastructure and they got to deal with infrastructure. Now they're being asked to secure the infrastructure, they just want to write code. And a data scientist, they're spending all their time trying to figure out, okay, what's the data quality? And they're wrangling data and they don't spend enough time doing what they want to do. So there's been a lack of collaboration. Have you seen that change, are these approaches allowing collaboration between data scientists and developers on a single platform? Can you talk about that a little bit? >> Yeah, that is a great question. One of the biggest set of scars that I have on my back from for building these platforms in other companies is exactly that. Every persona had a set of tools, and these tools didn't talk to each other and the handoff was painful. And most of the machine learning things evaporate or die on the floor because of this problem. It's very rarely that they are unsuccessful because the algorithm wasn't good enough. In most cases it's somebody builds something, and then you can't take it to production, you can't integrate it into your business application. You can't take the data out, train, create an endpoint and integrate it back like it's too painful. So the way we are approaching this is focused on this problem exactly. We have a single set of tools that if you publish a model as a data scientist and developers, and even business analysts that are seeing a inside of business application could be able to consume it. We have a single model store, a single feature store, a single management experience across the various personas that need to play in this. And we spend a lot of time building, and borrowing a word that cellular folks used, and I really liked it, building inside highways to make it easier to bring these insights into where you need them inside applications, both inside our applications, inside our SaaS applications, but also inside custom third party and even first party applications. And this is where a lot of our focus goes to just because we have dealt with so much pain doing this inside our own SaaS that we now have built the tools, and we're making them available for others to make this process of building a machine learning outcome driven insight in your app easier. And it's not just the model development, and it's not just the deployment, it's the entire journey of taking the data, building the model, training it, deploying it, looking at the real data that comes from the app, and creating this feedback loop in a more efficient way. And that's our focus area. Exactly this problem. >> Well thank you for that. So, last week we had our super cloud two event, and I had Juan Loza on and he spent a lot of time talking about how open Oracle is in its philosophy, and I got a lot of feedback. They were like, Oracle open, I don't really think, but the truth is if you think about database Oracle database, it never met a hardware platform that it didn't like. So in that sense it's open. So, but my point is, a big part of of machine learning and AI is driven by open source tools, frameworks, what's your open source strategy? What do you support from an open source standpoint? >> So I'm a strong believer that you don't actually know, nobody knows where the next slip fog or the next industry shifting innovation in AI is going to come from. If you look six months ago, nobody foreseen Dali, the magical text to image generation and the exploding brought into just art and design type of experiences. If you look six weeks ago, I don't think anybody's seen ChatGPT, and what it can do for a whole bunch of industries. So to me, assuming that a customer or partner or developer would want to lock themselves into only the tools that a specific vendor can produce is ridiculous. 'Cause nobody knows, if anybody claims that they know where the innovation is going to come from in a year or two, let alone in five or 10, they're just wrong or lying. So our strategy for Oracle is to, I call this the Netflix of AI. So if you think about Netflix, they produced a bunch of high quality shows on their own. A few years ago it was House of Cards. Last month my wife and I binge watched Ginny and Georgie, but they also curated a lot of shows that they found around the world and bought them to their customers. So it started with things like Seinfeld or Friends and most recently it was Squid games and those are famous Israeli TV series called Founder that Netflix bought in, and they bought it as is and they gave it the Netflix value. So you have captioning and you have the ability to speed the movie and you have it inside your app, and you can download it and watch it offline and everything, but nobody Netflix was involved in the production of these first seasons. Now if these things hunt and they're great, then the third season or the fourth season will get the full Netflix production value, high value budget, high value location shooting or whatever. But you as a customer, you don't care whether the producer and director, and screenplay writing is a Netflix employee or is somebody else's employee. It is fulfilled by Netflix. I believe that we will become, or we are looking to become the Netflix of AI. We are building a bunch of AI in a bunch of places where we think it's important and we have some competitive advantage like healthcare with Acellular partnership or whatnot. But I want to bring the best AI software and hardware to OCI and do a fulfillment by Oracle on that. So you'll get the Oracle security and identity and single bill and everything you'd expect from a company like Oracle. But we don't have to be building the data science, and the models for everything. So this means both open source recently announced a partnership with Anaconda, the leading provider of Python distribution in the data science ecosystem where we are are doing a joint strategic partnership of bringing all the goodness into Oracle customers as well as in the process of doing the same with Nvidia, and all those software libraries, not just the Hubble, both for other stuff like Triton, but also for healthcare specific stuff as well as other ISVs, other AI leading ISVs that we are in the process of partnering with to get their stuff into OCI and into Oracle so that you can truly consume the best AI hardware, and the best AI software in the world on Oracle. 'Cause that is what I believe our customers would want the ability to choose from any open source engine, and honestly from any ISV type of solution that is AI powered and they want to use it in their experiences. >> So you mentioned ChatGPT, I want to talk about some of the innovations that are coming. As an AI expert, you see ChatGPT on the one hand, I'm sure you weren't surprised. On the other hand, maybe the reaction in the market, and the hype is somewhat surprising. You know, they say that we tend to under or over-hype things in the early stages and under hype them long term, you kind of use the internet as example. What's your take on that premise? >> So. I think that this type of technology is going to be an inflection point in how software is being developed. I truly believe this. I think this is an internet style moment, and the way software interfaces, software applications are being developed will dramatically change over the next year two or three because of this type of technologies. I think there will be industries that will be shifted. I think education is a good example. I saw this thing opened on my son's laptop. So I think education is going to be transformed. Design industry like images or whatever, it's already been transformed. But I think that for mass adoption, like beyond the hype, beyond the peak of inflected expectations, if I'm using Gartner terminology, I think certain things need to go and happen. One is this thing needs to become more reliable. So right now it is a complete black box that sometimes produce magic, and sometimes produce just nonsense. And it needs to have better explainability and better lineage to, how did you get to this answer? 'Cause I think enterprises are going to really care about the things that they surface with the customers or use internally. So I think that is one thing that's going to come out. And the other thing that's going to come out is I think it's going to come industry specific large language models or industry specific ChatGPTs. Something like how OpenAI did co-pilot for writing code. I think we will start seeing this type of apps solving for specific business problems, understanding contracts, understanding healthcare, writing doctor's notes on behalf of doctors so they don't have to spend time manually recording and analyzing conversations. And I think that would become the sweet spot of this thing. There will be companies, whether it's OpenAI or Microsoft or Google or hopefully Oracle that will use this type of technology to solve for specific very high value business needs. And I think this will change how interfaces happen. So going back to your expense report, the world of, I'm going to go into an app, and I'm going to click on seven buttons in order to get some job done like this world is gone. Like I'm going to say, hey, please do this and that. And I expect an answer to come out. I've seen a recent demo about, marketing in sales. So a customer sends an email that is interested in something and then a ChatGPT powered thing just produces the answer. I think this is how the world is going to evolve. Like yes, there's a ton of hype, yes, it looks like magic and right now it is magic, but it's not yet productive for most enterprise scenarios. But in the next 6, 12, 24 months, this will start getting more dependable, and it's going to change how these industries are being managed. Like I think it's an internet level revolution. That's my take. >> It's very interesting. And it's going to change the way in which we have. Instead of accessing the data center through APIs, we're going to access it through natural language processing and that opens up technology to a huge audience. Last question, is a two part question. And the first part is what you guys are working on from the futures, but the second part of the question is, we got data scientists and developers in our audience. They love the new shiny toy. So give us a little glimpse of what you're working on in the future, and what would you say to them to persuade them to check out Oracle's AI services? >> Yep. So I think there's two main things that we're doing, one is around healthcare. With a new recent acquisition, we are spending a significant effort around revolutionizing healthcare with AI. Of course many scenarios from patient care using computer vision and cameras through automating, and making better insurance claims to research and pharma. We are making the best models from leading organizations, and internal available for hospitals and researchers, and insurance providers everywhere. And we truly are looking to become the leader in AI for healthcare. So I think that's a huge focus area. And the second part is, again, going back to the enterprise AI angle. Like we want to, if you have a business problem that you want to apply here to solve, we want to be your platform. Like you could use others if you want to build everything complicated and whatnot. We have a platform for that as well. But like, if you want to apply AI to solve a business problem, we want to be your platform. We want to be the, again, the Netflix of AI kind of a thing where we are the place for the greatest AI innovations accessible to any developer, any business analyst, any user, any data scientist on Oracle Cloud. And we're making a significant effort on these two fronts as well as developing a lot of the missing pieces, and building blocks that we see are needed in this space to make truly like a great experience for developers and data scientists. And what would I recommend? Get started, try it out. We actually have a shameless sales plug here. We have a free deal for all of our AI services. So it typically cost you nothing. I would highly recommend to just go, and try these things out. Go play with it. If you are a python welding developer, and you want to try a little bit of auto mail, go down that path. If you're not even there and you're just like, hey, I have these customer feedback things and I want to try out, if I can understand them and apply AI and visualize, and do some cool stuff, we have services for that. My recommendation is, and I think ChatGPT got us 'cause I see people that have nothing to do with AI, and can't even spell AI going and trying it out. I think this is the time. Go play with these things, go play with these technologies and find what AI can do to you or for you. And I think Oracle is a great place to start playing with these things. >> Elad, thank you. Appreciate you sharing your vision of making Oracle the Netflix of AI. Love that and really appreciate your time. >> Awesome. Thank you. Thank you for having me. >> Okay. Thanks for watching this Cube conversation. This is Dave Vellante. We'll see you next time. (gentle music playing)

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. >> Hello everyone, and welcome to this week's episode of theCUBE insights, powered by ETR. In this breaking analysis, I'm going to provide a little detail on the recent announcement that Insight Partners was acquiring Veeam for five billion dollars. There was a lot of information on the announcement in press releases and in news articles, so what I really want to focus on is what it means for the industry generally, and for the data protection community specifically. So, very briefly this was a five billion dollar exit for Veeam on top of a five hundred million dollar investment lead by the same Insight Partners last year. I think it had earlier investments, kind of a rent, with an option to buy. New management is being promoted from within, which I think is significant, to replace the two founders. Andrei Baronov and Ratmir Timashev are going to step down after the transition and give up their board seats. Veeam is a fascinating company. It started in the 2006, 2007 time frame, after the two founders, who met in college, formed and sold Aleta software to Quest. Then they started a company called AMUST Software, from which they created Veeam. You never hear about AMUST, but I believe it's the engineering and development arm of Veeam. Now the new CEO of Veeam, Bill Largent told theCUBE that AMUST is now a wholly owned subsidiary of Veeam and it won't effect any of the engineering assets that exist in Prague and in Russia. So this I the thing about Veeam, it's a very closely held company controlled by it's two founders, with a domicile in Switzerland. My understanding is Baronov is, well he's the technical guru, and he's a resident of that country in Switzerland, and the HQ there is very lean, the sizable engineering teams, as they say, is in Russia and Prague. Timashev resides in the US, and he's a marketing genius, who helped create this company, and it's always punched above it's weight class with, epic parties, and great products. Now interestingly, Veeam's rise, it coincided with the ascendancy of VMware. Veeam became the standard backup software for small to medium size companies within VMware shops. Their products are renowned for being simple, and working as advertised, and their customer support is outstanding by all accounts. But the US business lagged, despite the fact that most of VMware's business is in the Americas. You'd think you think if they super glued themself to VMware their Americas business would be higher. So a few years ago they decided to really go hard after the enterprise and they brought in Peter Mckay, from VMware, and he began to build up a US presence. But the enterprise business, it requires a lot of things that were kind of antithetical to Veeam. So think about long sales cycles, expensive sales people, belly to belly selling, with the expectations of, road maps, and clarity around enterprise feature sets. Now McKay was named CEO with Baronov, who continued to run engineering. So it was a bit of a culture clash. You got the sales oriented leader wanting the engineering team to turn on a dime and help close large deals, and satiate partners like HPE and Sysco, and you've got this genius co-leader, slash engineer, with an incredible track record of delivering features that the customer loves. So it really didn't work out and then Veeam scaled back on it's ambitions some what. At it's annual user conference in Miami last year, Ratmir came on theCUBE, and he talked about how Veeam's act one was all about dominance in virtualized environment. Let's listen to what he said about act two and then we'll come back and talk about it >> That was act one, we dominated it, we grew from zero to one billion within 10, 12 years. We added three hundred fifty thousand customers over that time frame, and now it's act two. What is act two? Act two is the, again, the new major industry transformation to a hybrid cloud. What are the similarities? Again, Veeam is in a great position because we're at the right time at the right place with a brilliant product. >> Now what we know is that act two is about a few things, one, as Ratmir said, hybrid cloud, multi cloud management, etcetera. But it's also about an awesome exit for it's two founders. Wow five billion dollars, five x revenue multiple, handing over the reigns is really the third thing this is about and creating more traditional governance structure for Veeam. Now they're moving from a governance structure that was closely held and opaque to one that is still going to be closely held, but ideally somewhat less opaque. Which brings me to inside partners. In the money world, you basically have a spectrum of investors. On the one side you've got banks, who are the most conservative. On the other side you've got VCs, now they're the most aggressive, of course. Now somewhere in the middle, you have private equity firms. Now they traditionally invest in companies, and they squeeze them for EBITDA, and they suck money out. But inside is more of a hybrid. They invest in a number of companies as VCs, they take a portion of the ownership. And to me they're more of a rule of forty PE, meaning it's not just about EBITDA, it's about growth plus EBITDA. So a rule of thirty or a rule of forty PE company, they can dial down EBITDA and go for growth, or dial up EBIT and moderate growth. So it's a great model. So I would expect Insight to bring structure and leadership to Veeam, with the goal of taking the company public at some point, because they like to sell to companies for all cash, I don't see a logical buyer at these kind of price points for this company in this market. It's growing market but it's still not a giant market. All right let's shift gears a little bit and get into some of the ETR data. Here's a narrative they put out recently that, to me, sums it up well. ETR said Veeam is one of the few vendors growing share among customers vs previous surveys in the storage sector. And that said, spending intentions are decelerating and continue to look poor in the largest sectors and Veeam trails Rubrik and Cohesity, although on a larger user base. So you can see by this statement that Veeam is of course doing well, but there are some cracks in the enterprise armor that I want to talk about and drill into a little bit. Now this now this Arline customer quote also, to me, sums up one of the reasons for Veeam's success. What this person said is if I want to do a Veeam back up to the cloud, it's basically point and click, very easy to use. Now I've talked to dozens, if not hundreds of Veeam customers, and they all say the same thing, it just works, that's kind of their motto. So this is the big reason why Veeam has steadily gained gained share over time. Now take a look at this chart, which shows the progression over time of Veeam's progress in terms of what ETR calls market share. Now remember, market share is a measure of pervasiveness in the ETR data set. And you can see, in the data, that Veeam has had a steady rise since ETR started tracking them at critical mass back in 2014. And you can see the steady decline in the survey for Veritas and Commvault and what appears to be, rapid momentum building for Rubrik and Cohesity, two companies that I said in my 2020 predictions breaking analysis that would continue to do well this year. Now notice I had to black out the January 2020 survey, which is ending shortly, so stay tuned for those results. But let's drill into Veeam's performance a little bit more. What this chart shows is a candlestick of net score and market share across all the respondents in the ETR survey for Veeam. Remember net score is a measure of spending momentum that subtracts customers that are spending less, the red, from those spending more, the greens. And it's represented over time by this blue line that you see. You can see that this blue line, it bounces around but it holds steady in the past couple of years pretty generally, and really in that thirty to forty percent range which you see on the left hand axis. Now that yellow line, is market share or pervasiveness, it also continues to climb steadily as I showed you in the previous chart. Now again this is amongst all respondents. Let's now take a look at this chart which isolates Veeam's performance in the largest companies, that enterprise push. Notice the pictures is somewhat choppier. Market share is okay, although unlike the previous chart, it's not steady. This is stunning. Peter McKay left in October 2018, and that's when Veeam really pulled back on it's big enterprise push, and you can see, there's a noticeable and steady drop there based on ETR data. So what's happening here is we are entering a new chapter for Veeam, act two so to speak. With new leadership and new governance. Danny Allen is taking over CTO, he previously ran strategy, Bill Largent is going to be CEO, the HQ is moving into the US. So in my opinon, Veeam's issues in the US have been more execution related than anything else. Veeam is a leader. So partnerships with Nutanix, Sysco, HPE, NetApp, should continue to improve and be somewhat productive, actually largely productive. Let's talk a little bit about Veeam's architecture, and a point of discussion that you often hear in the community. Veeam's a Window's based architecture. Now is that a blessing or is that a curse? Well the pros are that the Veeam team came out of a Windows world, and they know the platform very well. They are amazingly good at adding function, without screwing up performance somewhere else. You saw this a couple years back when they were making a big push on the enterprise and they increased the file sizes, and the number of objects that they could support. Another example is when Veeam added cloud back up, it was a really good product, version one. Unlink many products, when they first tried to port to the cloud, that wasn't the case. Recovery from the cloud is very tricky. Things are out of sync, you got a metadata challenge, and generally Veeam was able to achieve consistent levels of performance with it's cloud product. Now flip side of this, is that if you look at most, if not all, modern architectures today, are based on Linux. And once you start getting into mulit cloud, and cross cloud management, you're going to bump into and be interfacing with lots of Linux based systems. So Veeam is going to have migrate code, and maintaining consistent performance is going to be tougher. But as David Fourier, my colleague points out, there are many many ways to skin a cat, and Veeam's engineering team has really, based on it's track record, has proven that it can solve tough problems, and really deliver a great product consistently. I think the bigger issue and challenge for Veeam again, is execution in the US, and of course the enterprise. Customers in EBC's executive briefing centers, they want to see road maps, and enterprise features, and specials. And so we'll see, if that's something that Veeam has an appetite for. If they do, and I'm one of the incumbents, I'd be worried that Veeam could do a land and expand. Where Veeam isn't as strong in large enterprises, big companies they buy from Veeam. Maybe it's a smaller division, or remote location, but it's not like they don't do business in large accounts, they do. So in a way, they've already landed and they have an opportunity to expand, so that's something to pay attention to. If I'm an enterprise customer, I would be pressing Veeam on it's roadmap, and having them clarify their vision around hybrid and multi cloud management. Will Veeam be more transparent and willing to do specials for the enterprise, and their big partners, who expect them, when they say jump, they expect Veeam to say how high. How will Veeam's culture change, is the other thing I want to focus on. As the two founders step down, are they going to be able to main their engineering ethos, and customer loyalty, and can they figure out the enterprise. I'm a big fan of founder lead companies, when founders leave cultures often change. When founders stay, they're intensely committed, even beyond great CEOs who aren't founders. Look at Michael Dell. He went to the mat to keep his company against the great icon, now look at Dell technologies, after the EMC acquisition, it was completely transformed. Look at Oracle, look at the lengths that Larry Ellison goes to win. Compare that to a great CEO Joe Tucci, when he was at EMC, but you know when he was done, he was done, it was over. It wasn't his baby. So my point is how will this effect Veeam's culture and prospects in the long term. For me the bottom line is the big opportunity's in the US. And that's about execution. And I expect with the move to US HQ, new management, I expect they're going to see consistent market share gains, that's going to continue. The enterprise however, that's going to take longer, it's going to require more patience and more money. And with Veeam transitioning from essentially the two founder's lifestyle business into a company that's really built for an exit, they're going to have more money to invest, greater transparency, I hope, and a path to really build on their past successes. So this Dave Vellante signing out from the latest episode of theCUBE insights, powered by ETR. Thanks for watching everybody and we'll see you next time. (upbeat music)

(intense orchestral music) >> Hello everyone, welcome to this special CUBEConversation, I'm John Furrier, co-host of theCUBE, co-founder of SiliconANGLE Media. I'm here with Erica Brescia, who's the co-founder and Chief Operating Officer at Bitnami, it's the app store for the cloud, they do automated packaging, an application provider. Great to see you, CUBE alumni, great to have you in the studio, thanks for coming in. >> Great to be here, thanks for having me. >> So, so much going on, you've been to theCUBE multiple times, we see each other at conferences and, you made some time, thanks for comin' down, appreciate it. >> Yeah. >> So Bitnami's doing some great things, so give us the update, what's goin' on with the company? >> Sure. So we just launched our new offering called Stacksmith, which is our first enterprise offering that basically takes all the tooling that we've built to deliver the application catalog that we have onto all the major cloud vendors, and allows enterprise IT departments to package up their own applications, both for cloud and cloud-native platforms, as well as for whatever they're running in the enterprise today. So, it kind of meets them where they are, helps them automate the application packaging and maintenance in place today, and then sets them up to successfully move to the cloud and Kubernetes and containers over time. >> So it's kind of reverse of this journey to the cloud, you go to where the user, the customers are, help them put it together. >> And make the journey, really. So what we find is a lot of the more traditional orchestration and packaging tools just aren't well suited to cloud and containers in particular. And so enterprises are looking for new tools to help them solve current problems, which is: we need to support all these different platforms, we might have some things running internally in VMware, we're running some things on Amazon, maybe using cloud formation, and now they're trying to get to Kubernetes, and they're trying to figure out how they can do that without having a separate pipeline for everything, and that's the problem that Bitnami solves. >> Yeah, and that's been a bit, we've identified a product at Amazon, then, I want Azure, I want Google Cloud, I got to hire a different development team, different stacks. So there's kind of this problem with multi-cloud. How are you guys talkin' to customers about it? 'Cause this seems to be the hybrid cloud main problem today. It's like, okay I see the cloud, I understand I'm going to be doing a lot of stuff in the cloud, or cloud's going to be on-prem, and it's going to be in the cloud. How do I get ready for the cloud? That seems to be a number one question. >> Yeah, and I think what people are struggling with is, you know, there're a lot of companies out there, particularly in the cloud-native space, that just say: if you just rebuild everything, then your life will be so much better, right? But that's not really realistic for most companies. They need to be able to take what they have, and be able to package it in such a way that they get a lot of the benefits of the cloud and containers without completely re-architecting everything. Because, it might be practical for, say a new start up, or a company like Netflix or Spotify to do that, but lets face it, most companies are not that, most companies have too many demands on their IT and Ops teams already, hiring talent is hard even for the startups working at the forefront of Kubernetes, so, you really need tools that are approachable and solve current problems, but again, I think the key is, set you up for success in the future, and I think we help people kind of bridge the gap between what they're doing today and what they're doing in the future without trying to push them in one direction, which might not make sense for them. >> Yeah, in Netflix, and the Googles of the world, are potential future scenarios of what they might look like, but they got to take care of the current move from IT to cloud, get ready for it. >> Yeah, maybe, and you know, for a lot of these internal applications it doesn't make sense to completely re-architect and rewrite them, like the ROI isn't there, and there are companies out there that have thousands of Java or .NET applications that they just need to be able to move perhaps out of their data center, in many cases it's being shut down, and, onto cloud platforms and so we try to find that nice balance between helping you get the advantage of the automation of cloud without having to invest in re-architecting apps that just aren't worth re-architecting. >> Got to ask you Erica, we've had a couple conversations, I forget what you were founded, at Bitnami, you've had a great journey, a lot of things have changed. When did you guys found 2010, or 2011? >> So we started Bitnami in 2013. The company before Bitnami was Bitrock, and we went through YCombinator in 2013, and that's when we really started growing out the company. First around the app catalog that we deliver both via Bitnami.com as well as all the major cloud platforms, and that's allowed us to bootstrap the business up to this point. And then obviously we took all of the learnings and the technology from delivering 140 applications across 14 different platforms, native and cloud, and productize that in Stacksmith, so our enterprise users, you know, we have over a million deployments a month, but people have only been consuming the things that we build now they can use our tooling, that we've been building out over the years, to automate the packaging of their own applications. >> And it's, just to kind of put some color commentary around that time, it wasn't the most calm waters of the cloud world, massive growth, a lot of things have happened, so containers come to the scene with Docker and that becomes standardized, now you've got Kubernetes, you got service meshes right around the corner, kind of now it sets a perfect opportunity for you guys to bring customers to this app store concept, for you guys. >> Yeah, and we see this great, we call it kind of the great unbundling, right? Where apps used to be distributed with the operating system and they kind of were this one cohesive piece, and now, with Kubernetes and cloud APIs, the applications are very separate, and so there's kind of this new operating system coming together, which is the operating system of containers and Kubernetes and cloud, and it allows you to combine these different pieces in ways that you never could before. Before, you know, you would just go to your OS repo to pull in the app that you wanted. >> And you see the trends, I mean, Google has the SRE concept sight, reliability, engineer, the operators on the VMware side, dealing with VMs kind of all converging together. So I got to ask you, how does that impact your customers with your new Stacksmith offering, what's the impact to the customers? Is it ease of use, is it ease of deployment, what's the main value at? >> So, I think the most important thing is, as you said, there're all these new technologies coming out and there's also cloud formation on AWS, and there's ARM on Azure, and each cloud vendor is coming out with their own tooling and then, like you said, there's operators for Kubernetes. The advantage that you get with Bitnami is you don't have to understand the intricacies of how to package for all of those different platforms because we do that for you. We abstract away having to understand how to build a cloud formation template versus a helm chart helps that Kubernetes, you know, package manager essentially and we've been very involved in helping define and further that project. We're actually the top provider of the official helm charts. So we see a lot of promise there but, what's interesting about Bitnami is at the end of the day we're platform agnostic. And once you start using Bitnami and Stacksmith, you can very easily add support for other platforms. So we have a customer who started out on AWS, for example, they wanted to give a try to running some things on Azure, and they essentially just had to flip a switch, and then they get an ARM template, instead of-- >> What was your alternative to that? If they didn't do that, what would they have to do? >> They would have had to do it either manually, or find system specific tools for each platform, to do it. So, there's no other like singular tool chain that lets you build natively for all the different platforms and that's the key, we don't try to abstract away ARM or any of these other orchestration technologies by giving you some kind of layer on top of them. We just make it really easy to build for those technologies and also, to maintain those applications and templates over time, so this isn't point-in-time thing, we track all of the updates in everything that goes into that image or a set of images, and allow you to automatically rebuild and redeploy across any of those platforms you need to support. >> You guys have been very successful in the cloud, but also have scar tissue like everybody else that's been through the cloud wars. And now, as it starts to hit kind of an inflection point, how has cloud changed now, what are we seeing now in cloud versus, say 2014, 2015 timeframe? >> Oh boy. So, I think the most interesting thing is how quickly Azure in particular has evolved. If I had to pick one thing that has been incredibly impressive and important in the changing cloud landscape, it's, you know, you go back to 2014, it was pretty much all AWS all the time, right? And, Amazon isn't quite the Goliath it used to be anymore, I mean there's-- >> Well it's still pretty damn big. >> They're still huge. Yeah, absolutely, but I'll tell you what, the others are gaining a lot of ground, and they have really interesting and different advantages, right? Google will send all of their amazingly smart engineers in to help you architect applications, or move them over, I've heard a lot of workloads moving off of AWS onto Google because Google is giving them so much love and support and trying to attract those workloads over. But Azure's advantage is their ecosystem, right? They really understand partnering in a way that Amazons retail DNA just, it doesn't lend itself to that, and so, I think Microsoft's approach to building out a really great ecosystem around Azure, coupled with their huge field sales team, which Amazon has just been building, they've never had an enterprise sales team, is making things really interesting and creating, for us, a great dynamic in the market because we like to see a number of cloud vendors flourish. >> You're an arms dealer. >> Yeah exactly! (Erica laughs) >> Whatever you want, any cloud. >> I don't know if our CMO would want me to put it that way, but. (laughing) >> Dave Alante's favorite term, by the way. >> Sure. >> It's good to be an arms dealer, or be Switzerland, as they, to be more politically correct. >> Yeah, we go with Switzerland. >> Azure's interesting, I was just having conversation with Dave about this, because, you know, you've got, consumerization of IT, and digital transformation, have been the biggest buzz words in IT for the past decade. First it was consumerization of IT, now it's digital transformation. If you think about it Amazon and Google are really the consumer companies, Azure is an enterprise company with an ecosystem, so it's going to be very interesting to see if consumerization is the winning formula or is it digital transformation on the enterprise side? So you got to be, watching that pretty closely. Your thoughts? >> So, I would say on the consumerization of IT side, I mean that is absolutely happening, and, there, we could talk for hours probably on why that trend is here and why it's not going away, just, expectations in general have changed with the advent of iPhone and app stores and convenience across every aspect of our lives, so, I think even Microsoft gets that, and I don't think that the consumer DNA of those companies actually gives them a real edge in this case. What is interesting is, every company is starting to really focus on their app stores and their marketplace strategies, and trying to provide a frictionless buying experience. And there're a bunch of announcements coming, both on the AWS side, and the Azure side in particular, around things that they're doing to ease the enterprise buying process. >> Well we identified the three things, SAS business is table stakes, IOT is coming, connected devices, and then you've got the mobile. Those three things are on 20 year runs. Talking about Bitnami's update, you mentioned Stacksmith, you have some new stuff there, you guys are hiring, what's the ramp up, marketing, cash flow, top line revenues? Go ahead, share it. >> I'm not giving you all that. (both laughing) But, yeah it's a really exciting time for us, obviously bringing this enterprise product to market. We're gearing up to scale quite significantly, so, Bitnami's is kind of unusual in the Valley in that we're bootstrapped, and we're very heavily engineering driven. >> So no outside funding? >> A million dollars in total, which pretty much doesn't even count in Silicon Valley, and that was really just they had a number of individual folks involved in the company, when we went through YC. >> So no venturing? >> No, no institutional funding So, we are just getting ready to build out the whole go to market team around the Stacksmith product, which is very new in the market, just launched in the last couple months. >> So is it generally available? >> Oh yes! Generally available, customers, lots of great things to talk about, but, we don't have the full sales team in place. >> And what's the benefits of Stacksmith? What's the bottom line value proposition? >> It's really helping you to automate the packaging and maintenance of your applications, whether internal or external, you know, third-party commercial apps that you're using internally, and deploying them on any of the platforms that you need to support. >> App store for the cloud, I love that. So let's talk about what you're workin' on, one of the things I'm really impressed, first of all I'm really impressed with what you've done with Bitnami, I love it, love the bootstrap stories, we were bootstrapped as well in the run of SiliconANGLE. So it's great, in Silicon Valley, I think that's like the top tier player, if you can bootstrap it to economic visibility around scale, that's a success so congratulations. But you also have something exciting going on with venture investing. X factor, >> X factor, yep. >> This is super impressive. You raised a small little fund, X factor, investing in women entrepreneurs. Take a minute to explain what X factor is, do you have some news coming, another fund coming? >> Sure, yeah it's been very exciting, so, in the free free time that I really don't have, but this is such a good cause it's worth it. We put together a three million dollar fund, to invest a hundred thousand dollars in 30 different companies, with at least one female founder. And this actually was spun out of fly bridge, we have our token guys, we call 'em Chip Hazard, who's a career venture investor, who's doing a lot of interesting things. But, he basically led the charge with a woman named Anna Palmer, to put together a group of female founders, that's what really differentiates us, I think, from the rest of the market, who are operating their own companies, to invest in these very early stage female founded companies And, I think that gives us a really unique advantage in the market of venture, in that first we have an incredible pipeline and deal flow because, you know, we know these folks who are starting the companies. And we also have a unique perspective on the challenges of getting a new venture off the ground, and I think we can really be an ally to the entrepreneurs that we're funding, and helping them get that first bit of funding in the door, we typically help them with their series A rounds and beyond and they really see us as a peer and someone they can relate to and come to for advice, and so, I think it's a pretty unique value prop that we have as a VC fund. >> Operating experience brings a lot to the table, so, you want to get those first three steps goin', get that venture off the ground, trust. >> Yeah, and we have a very diverse range of experiences that we can bring to bare too, I mean some of us have deep infrastructure experience, some folks are on the consumer side, we've got a few East Coast people, a few West Coast people, a few people scattered in other areas. And we all have different areas of expertise, right? I'm pretty strong on the business development side, and I'm business model, SAS, enterprise software. Some of the other women are much more familiar with like distribution deals, or hardware deals, or other consumer businesses as well, so I think we have a really unique range of experiences and expertise that we can bring to bare in supporting our founders. >> And mentoring too, it's being there for, you know, don't give up! >> Yeah! And we've had founders go through things, and they'll call us at, one of our founders I was just on the phone with, and she was looking at changing her role within the company to take on more responsibility, and we had a great conversation around that, and that resulted in her becoming the COO, which was fantastic. Another founder was going through a difficult time where she and her co-founder were splitting up, and I was able to talk her through that. And we have a lot of those stories where, I think, you know, we have really been seen as an ally who can help founders get through those times, because we've been there, and we can empathize. And, it's an interesting dynamic because everybody knows that we're not going to invest in the next round, so there's never any posturing to make sure that they're still selling us on investing in the company. It's all about, once we're in, we're in, and we'll do anything we can do to help you scale successfully over time. >> And the key is get to that next round, or get a clear line of sight on visibility in the union economics or, scale. >> Exactly. >> Alright, so how much is going into the next funding? Can you talk about the amount, or? >> Yeah, so we're not raising yet, we're just about to start raising, we're going to be expanding the number of investment partners on the team, which is fantastic, and I'm really excited to bring some amazing new women on board, so, you know, for the women out there who are maybe interested in starting to learn a little more about venture and have raised funding and build their own companies, please send us an email: hello@xfactorventures the fund should be about 10 million dollars, is the current target. >> How is it structured? Are they structured as limited partners, general partners? How is it, so if someone comes on board, as you expand the partnership what does it look like? >> Sure, so, we all do invest our own money, but the fund has LPs just like any other fund, so there's a number of great folks who have backed up X factor. We do bring in some of our own folks along the way, you know, I had people that I know, who have invested in the fund and I'm sure that will be the case in the next one, but it's not like the fund is only funded by the investment partners, we have LPs like any other fund. >> But you guys are taking profits out of it, through the caring, right? So typical venture capital? >> It's typical venture capital, you know, it's a fairly small fund to start as we work through things, but we expect it to grow quite significantly over time. I'll tell you, without giving away too much, that we have quite grand ambitions for the long term. >> Alright, well let's keep in touch on the deal flow, congratulations on Bitnami, and, we'll see you at the cloud shows, Amazon, Microsoft Ignite, Google Next. >> Everywhere, yep, I'll be there. >> Erica, thanks for coming on and spending some time here on theCUBE. CUBEConversations here in Palo Alto, I'm John Furrier, you're watching CUBEConversations, thanks for watching. (intense orchestral music)

>> From Times Square in the heart of New York City, it's theCUBE, covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Manhattan, actually midtown Manhattan, at Automation Anywhere Imagine 2018, 1100 people talkin' about bots, talkin' about Robotics Process Automation, or RPA. And we're excited to have the guy that counts the money at the end of the day; it's important part of any business. He's a co-founder, Ankur Kothari, Chief Revenue Officer and Co-Founder, Automation Anywhere. Ankur, great to see you. >> Great to be here, Jeff, thanks for having me. >> So, first off, as a co-founder, I think you're the third or fourth co-founder we've had on today. A little bit of reflection since you guys started this like 14 years ago. >> Yeah. Here we are, there's 1100 people, the room is packed. They had the overflow, they're actually all over us out here with the overflow for the keynote. Take a minute and kinda tell us how you feel about how this thing has evolved over time. >> It feels like a great party to be part of. Always, you're always happy. >> Right. >> One of the traits that you'll find a lot of co-founders is that they are always happy, never satisfied. They're always looking for the next big one. >> Right. >> But it's amazing to be part of Imagine because we learn so much from our customers and our partner as well. It's not just that we bring them together and we're talking. We're learning every time. It's becoming a big ecosystem. >> Right. >> And, an idea as big as a bot or a future of work is too big an idea for one company to continue. You want as many people to come. >> Right. >> So, our idea of Imagine was a little bit like Field of Dreams, you build and they'll come and they'll collaborate and it'll become bigger and bigger. >> And look all around us. I mean, we're surrounded by people and really, the ecosystem. >> And the bots as well, there are bots on the walls and everything else. >> Bots on the walls, partners everywhere. So let's dive into it a little bit. I mean, one of the ways that you guys participate in the ecosystem, and the ecosystem participates, is the Bot Store. >> Yes. >> So it's just like any other kind of an app store. >> Exactly. >> You've got people contributing. I assume you guys have contributed stuff. But we saw earlier in the keynote by Accenture, and EY, and Deloitte. And all types of companies are contributing bots into this ecosystem for lots of different functions or applications. So really, an interesting thing. How's that workin' out? Where'd you come up with the idea? And why's that so important? >> At Automation Anywhere we like to ask ourselves hard questions, as the leaders in this space. And we asked ourselves this question, "What can we now do to further accelerate our journey of all our customers to become a digital enterprise?" The answer came that we are to share in the new bot economy. Now once that answer was clear, every economy requires a marketplace. >> Right. >> And that's where the Bot Store came. It's a marketplace where producers meet the consumers, and you connect them. All we do is, we curate and make sure that the right things go up. But other than that, it's just like any other marketplace. And we thought that if we'll build the right marketplace where the producers meet consumers, we have thousands of customers and large companies looking at it. It will allow perfect place where all the right ideas get converted into product. >> Right. >> We have tons of partners who have domain expertise, functional expertise, vertical expertise; they can prioritize their expertise, they can convert it into IP. >> Right. >> They can do it for free, they can monetize it. So there's lots to gain for producers of all these bots. And if I am a consumer, now suddenly my time clock to make further shrinks, because instead of creating these bots all from scratch, I can download them from this Bot Store and snap them together like a Lego block. >> Right. >> So that's how the whole idea came. We launched it just two months ago and we have hundreds-- >> You just launched it two months ago? >> Yeah! And we have hundreds of bots in it. More than 80-100 partners have participated. We are getting at least 20-30 more submissions coming every day, and we have few hundred submissions coming every week. So, just like any free marketplace, it has an exponential nature. And that's the thing we are counting on. >> That's amazing, that you've got that much traction in such a short period of time. >> Thousands of downloads on a daily basis. Thousands of users just in two month's time. >> You know, we go to a ton of shows. We do over a hundred shows a year. And once shows get to a certain size, it starts to change a little bit. But when they're small like this, it's a very intimate affair on a couple floors here at the Sheraton, everyone is still really involved. They're really sharing. >> Yes. >> There's so much sharing of information. Not so much, you know ... Because they're not really competitors. Within their own companies, they're all part of this same team that are trying to implement this new thing. >> Exactly. >> And you really feel it. >> Exactly. >> So, the store's cool, but the bot economy. When you talk about the bot economy, we talk about API economy a lot. >> Yes. >> How do you see the bot economy? What are the factors that drive the bot economy, and how's it gonna evolve over time? >> We look at it as a few elements. The current version, we think that bot economy, like any economy, has a marketplace, which is our Bot Store. We have a program which we call Bot Games, because any good economy, any new economy, one of the trait is that the good idea can come from anyone. >> Right. >> It can come from anyplace. Like, any customers, any partner, anyone can bring. A good economy, what it does is it brings that idea from anyone, and it gives these vehicles for good ideas to take flight. If the idea is good, it becomes viral, and it has vehicles where those ideas can go to market. What we did was, we created a program called Bot Games. Yesterday on May 29th, we had the 1st Inaugural Bot Games. We invited developers, people who are part of these programs and their companies. And we gamified and created different games. And we thought that if we bring all these champions and pioneers and like-minded people in the same room, give them certain same problem, and then gamify it, put a clock on it, a lot of great ideas will come out of it. >> Right. >> And that came. And some of those ideas will make it to the marketplace, like a Bot Store, like an Imagine. >> Right. >> So that's where all the ideas connect to the customers. And the people who bring those ideas, they also come up. So that's the other aspect. So the Bot Games is where the ideas, you can crowdsource from places. Bot Store is where they go to the market. In between there is a gap. And we are trying to remove that gap by creating a stimulus package for this new bot economy. Like any economy time and again requires a stimulus pack, and we have created one. What we have done is that if you want to learn Automation Anywhere, right? If you want to understand, because that gap is you're to understand Automation Anywhere. We have created Automation Anywhere University a year ago. And now anyone can take courses for free to learn how to create bots. Whether they are customers or partners. And then, if you purchase these bots through one of our certified partners, the first three bots in year one are free. So we are removing the friction in between. If you have not started on this journey, your learning is free, you get ideas from different places, we can get these prebuilt bots, and the first three bots, if you purchase it through our partners, they are free. So we are removing that friction. And then, we are supporting that whole economy with the industry's largest customer success program. >> Right. So I'm curious if you know, maybe you don't know, of the bots in the bots store, how many are free and how many are paid, as a percentage? >> Interestingly, I don't have that stat because we don't actually worry about that. We let all our partners and people who are contributing to this Bot Store decide that. >> Right. >> Some bots they may decide to monetize, some they may not. It's listed on the Bot Store. Offhand, I would say-- >> Take a guess. Is it 50/50? A third? Two-thirds? >> The nature of it looks like 50/50. >> That's a good guess. Full caveat, it's a guess. We didn't do the analysis. >> Exactly. But here is the unique aspect. Yesterday we had a Bot Game, and the winner had an amazing idea that none of us had ever think of. He created this bot that automates the COE of all these programs. Now, we are talking. He is thinking of putting that on Bot Store. That's the power of bringing multiple people together. >> Right. >> That's the power of free economy, where the exponential nature of it is what we are counting on. And we are getting on a daily basis these new bot ideas, these new bots that are making it to the Bot Store. Just like your App Store. I go to App Store to get ideas what I can do on my phone. >> Right, right. >> Just like that, now we are finding our customers are going to Bot Store to figure out what else can they automate. >> Right, right. >> And that's been another amazing part of it. >> You know, it's so consistent. All these shows we go to, right? How do you unlock innovation? There's some really simple ways. One is, give more people the power, give more people the tools, and give more people the data. >> Exactly. >> And you'll get stuff out of it that the small subset of people that used to have access to those three things, they never found. They just didn't think of it that way, right? >> Exactly. And then we firmly believe that any technology, anything, once you democratize it, you give it in hands of everyone-- >> Right, right. >> You can't have a thriving economy unless everyone forms their own point of view. Unless everyone creates their own perspective. And that's our vision of this bot economy. We are bringing everyone and giving them these vehicles to try it out. Look, the technology has reached a stage where it's cheaper to try it out than talk about it. >> Yes. >> And we are doing that so that everyone forms their own unique point of view, and then they express that point of view and we connect those points of view to these thousands of customers worldwide. >> Right. >> Good ideas take flight, and all we have to do is create vehicles for those good ideas to take flight. >> Alright. So, Ankur, I gave you the last word before we wrap up here. If we come back next year, a year from now, inspired 2019, what are we gonna be talking about? What's on your roadmap? What're some of the priorities that you guys are workin' on over the next 12 months? >> We are talking about ... The next 12 months, we are looking at how to further accelerate this journey. Because what people are in this, the real problem people are trying to achieve is how to become a digital enterprise. Not just to automate, but how do you create a digital enterprise? You cannot become a digital enterprise unless your operations are digital. You cannot make your operations digital unless your processes are digital. And you cannot do that unless your workforce is digital. So we are trying to create technologies, vehicles, platforms, so that everyone can scale their program. Where pretty much everyone should have a digital colleague. Everyone should be able to create a bot. Everyone should be able to work with a bot. Every process, every department, every system should have a digital workforce working in it and that can allow you to create a digital enterprise that can scale up and scale down with the demand and supply. >> Alright-- >> That's what we are trying to start. >> Well, we look forward to gettin' the update next year. >> Exactly. >> Alright, Ankur, thanks for taking a few minutes out of your busy day with us. >> Thanks for having me here, and I appreciate and enjoy the conversation. >> Alright, he's Ankur, I'm Jeff. We're at Automation Anywhere Imagine 2018. Thanks for watching theCUBE. See you next time.

>> Live from Midtown Manhattan, it's the CUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Fifth year of coverage of our own event Big Data NYC where we cover all the action in New York City. For this week in big data, in conjunction with Strata Data which was originally Hadoop World in 2010. We've been covering it for eight years. It became Strata Conference, Strata Hadoop, now called Strata Data. Will probably called Strata AI tomorrow. Who knows, but certainly the trends are going in that direction. I'm John Furrier, your co-host. Our next guest here in New York City is Sergei Rabotai, who is the Head of Business Development at InData Labs from Belarus. In town, doing some biz dev in the big data ecosystem. Welcome to theCUBE. >> Yeah. Good morning. >> Great to have you. So, obviously Belarus is becoming known as the Silicon Valley of Eastern Europe. A lot of great talent. We're seeing that really explode. A lot of great stuff going on globally, even though there's a lot of stuff, you know GDPR and all these other things happening. It's clearly a global economy with tech. Silicon Valley still is magical. I live there in Palo Alto but you're starting to see peering points within these ecosystems of entrepreneurship and now big companies are taking advantage of it as well. What do you guys do? I mean you're in the middle of that. What is InData Labs do in context of all this? >> Well, InData Labs is a full stack data science company. Which means that we provide professional services for data strategy, big data engineering and the data science. So, yeah, like you just said, we are based - my team is based in Minsk, Belarus. We are about 40 people strong at the moment. And in our recent years we have been very successful starting this business and we have been getting customers from all over the world, including United States, Great Britain, and European Union. The company was launched about four years ago and very important thing, that it was launched by two tech leaders who come from very data-driven industries. Our CEO, Ilya Kirillov, has been running several EdTech companies for many years. Our second founder, Marat Karpeko, has been holding C-Level positions in one of the most successful gaming companies in the world. >> John: So they know data. They're data guys. >> Yeah they're data guys. They know data from different aspects and that brings synergy to our business. >> You guys bring that expertise now into professional services for us. Give me an example of some of the things someone might want to call you up on, because the thing we're hearing here in New York City this week is look, we need more data sciences and they got to be more productive. They're spending way too much time wrangling and doing stuff that they shouldn't be doing. In the old days, sysadmins were built to let people be productive and they ran the infrastructure. That's not what data scientists should be doing. They're the users. There's a level of setting things up and then there's a level of provisioning, it's actually data assets, but then the data scientists just want to do their job. How do you help companies do that? >> Well I would probably, if I take all of our activities, I would split them into two big parts. First of all, we are helping big companies, who already have a lot of data. We help them in managing this data more effectively. We help them with predictive analytics. We help them with, helping them build the churn prediction and user segmentation solutions. We have been recently involved into several natural language processing projects. In one of our successful key studies we helped one of the largest gaming companies to automate their customer feedback processing. So, like, a couple years ago they were working manually with their customer feedback and we built them a tool that allows them to instantly get the sentiment of what the user says. It's kind of like a voice of a customer, which means they can be more effective in developing new things for their games. So, we-- >> So what would someone engage? I'm just trying to peg a order of magnitude of the levels of engagements you do. Startups come in? Is it big companies? What kind of size scoped work do you do? >> So I would say at the moment we work with startups, but it's a bit of a different approach than we have with big or well-established companies. When startups typically approach us with asking to help them implement some brand new technologies like neural networks or deep learning. So they want to be effective from the start. They want to use the cutting edge technology to be more attractive, to provide a better value on the market and just to be effective and to be a successful business from the start. The other part, the well-established companies, who already have the data but they understand that so far their data might not be used that effectively as it should have been used. Therefore, they approach us with a request to help them to get more insights out of the data. Let's say, implement some machine learning that can help them. >> How about larger companies? What kind of projects do you work for them? >> It could be a typical project like churn prediction, that is very actual for the companies who have got a lot of customer data. Then it could be companies from such industries like betting industry, where churn is a very big issue. And, the same probably applies to companies who do trading. >> So is scale one of the things you differentiate around? It sounds like your founders have an EdTech background obviously must be a larger, large data set. Is your profile of engagements large scale? Is it ... I'm just trying to get a handle of if someone's watching who, what is the kind of engagements people should be calling you for? Give us an example of that. >> Like, let's say there is a company who has got a lot of customer data, has got some products and they have a problem of churn, or they have a problem of segmenting their customers so they can later address the specific segments of the customers with the right offers at the right time and through the right marketing channel. Then it could be customers or requests where natural text processing is required where we have to automate some understanding of the written or spoken text. Then I should say that we have been getting recently some requests where computer vision skills are required. I think the first stage of AI being really intelligent was the speech recognition and I think nowadays we manage to reach to the level of what we earlier saw in fantastic movies or sci-fi movies. Computer vision is going to be the next leap in all that AI buzz we're having at the moment. >> So you solve, the problem that you solve for customers is data problems. If they're swimming in a lot of data, you can help them. >> Sergei: Yep. >> If they actually want to make that data do things that are cutting edge, you guys can help them. >> Sergei: Yeah. That's-- >> Alright, so here's a question for you. I mean, Belarus has obviously got good things going on. I've heard the press that you guys have been getting, the whole area, and you guys in particular. So I'm a buyer, one of the questions I might ask is "Hey Sergei, how do I know that you'll keep that talent because the churn is always a big problem. I've dealt with outsourcing before and in the US it's hard to keep talent but I've heard there's a churn." How do you guys keep the talent in the country? How do you keep talent on the projects? Is there certain economic rules over there? What's happening in Belarus? Give us the economical. >> Yeah, so, basically what you're saying. The churn problem has always been known for companies who have their development teams in Asian regions. That's a known problem because I have a lot of meetings with clients in the UK and the US, potential prospects, I would say. So they say it is a problem for them. With Belarus, I don't think we have that because from what I know, we have an average churn of under 10 percent. That's the figures across the industry. In smaller companies, the churn is even less and there are specific reasons for that. First of all, that due to Belarusian mentality, we always try to keep to a job that we're having. Yeah? So we do not-- >> John: That's a cultural thing. >> That's just the cultural thing. We do not ... >> You honor, you honor a code, if you will. >> Yeah. >> Okay. >> So, that's one of the things. Another thing is that Belarusian IT industry is very small. We have, I would say, no more than 40 thousand people being involved in different IT companies. The community is very small, so if somebody is hopping jobs from one job to another, it is going to be known and this person is not likely to have like, a good career. >> So job hoppers is kind of like a code of community, honor. Silicon Valley works that way too, by the way. >> Yeah. >> You get identified, that's who you are. >> Yeah. And so nowadays-- >> Economic tax breaks going on over there? What's the government to get involved? >> One of the key things is, the special tax and legal regulations that Belarus has got at the moment. I can definitely say that there is no country in the world that has got the same tax preferences, and the same support from the government. If a Belarusian company, IT company, becomes a part of Belarusian High Tech Park it means the company becomes automatically exempt from BET tax, corporate income tax. The employees of that company having the reliefs on their income, personal income tax rate, and there are a lot more reliefs that make the talent stay in the country. Having this relief for the IT business allows the companies to provide better working conditions for the employees and stop the people from migrating to other parts of the world. That's what we have. >> Sort of created an environment where there's not a lot of migration out of the area. The tech community kind of does it's own policing of behavior for innovation. >> Yeah but I think before those initiatives were adopted there was a certain percentage of people migrating but I think that nowadays even if it happens, yes, you're right, it's not that substantial. >> Great. Tell us ... Great overview of the company and congratulations, it's a good opportunity for folks watching to explore new areas of talent, especially ones that have the work ethic and knowledge you guys have over there. New York here, there's codes here too. Get the job done. Be on time. What's your experience like in New York here? What's your goal this week? What's some of the meetings you're having? Share with the folks kind of your game plan for Big Data NYC. >> Well, yeah, I've really enjoyed my stay here. It, so far, has been a very enjoyable experience. From the business perspective, I had over 10 meetings with the prospective customers. And we are likely to have follow-ups coming in the next couple of weeks. I can definitely say there is a great demand for professional services. You can see that if you go to whichever center you can see there's a lot of jobs being posted on the job boards. It means that there is lack of knowledge here in the US, yeah? One more important thing that I wanted to share with you from my personal observations that USA, UK and maybe Nordic countries, they have very, very strong background for creating the business ideas but Eastern Europe or Eastern European countries and Belarus in particular, they are very strong in actually implementing those ideas. >> Building them. >> Yes, building them. I think we have lots of synergies and we can ... we can ... >> John: Great. >> We can work together. I also got some meetings with our existing customers here in the US and so far we had good experiences. I can see that New York is moving fast. I travel a lot. I've been to over 40 countries in the previous five years and I just ... New York is different. >> It's fun. >> Different. Even different from many other cities in the US. >> Lot of banks are here. Lot of business in New York. New York is a great town. Love New York City. It's one of my favorites. Love coming here as I grew up right across the river in New Jersey. >> Yeah. But, great town, obviously California, Palo Alto, >> Yeah. >> Is a little more softer in terms of weather, but they have a culture there too. Sounds a lot like what's going on in Belarus, so congratulations. If we get some business for you, should we give them theCUBE discount, tell them John sent you and you get 10 percent off? Alright? >> Alright, yes. Sounds great. We can make it a good deal. (laughter) >> Tell them John sent you, you get 10% off. No I'm only kidding because it's services. Congratulations. Final question. What's the number one thing that people are buying for service from you guys? Number one thing. What's the most requested service you provide? >> The most requested services ... First of all, many customers they understand that they have got a lot of data. They want to do something with their data. But before you actually do some implementation you have to do a lot of discovery or preparatory work. I would say, no matter how we end up with a customer, this stage is basically ... The idea of that stage is to identify the ways data science can be implemented and can provide benefits to the business. That's the most important. I think that, like, 95 percent of the customers they approach us with this thing in the first place. And based on the results of that preparatory stage we can then advise the customers. What can they do? Or how they can actually benefit from the existing data? Or what other things they should collect in order to make their business more effective. >> Sergei, thanks for coming on. Belarus has got a lot of builders there. Check 'em out. >> Thanks a lot. >> Builders are critical in this new world. Lots of them with clout, a lot of great opportunities. A lot of builders in Belarus. This is theCUBE, bringing you all the action from New York City. More after this short break. We'll be right back. (theme music) (no audio) >> Hi, I'm John Furrier, the co-founder of SiliconANGLE Media and co-host of theCUBE. I've been in the tech ...

>> Narrator: Live, from Santa Clara in the heart of Silicon Valley, it's theCUBE. Covering Cloud Foundry Summit 2017. Brought to you by the Cloud Foundry Foundation and Pivotal. >> Hi this is Stu Miniman, joined with my cohost, John Troyer. Happy to welcome to the program a first-time guest, Chip Childers, who's the CTO of the Cloud Foundry Foundation. Chip, fresh off the keynote stage, >> Yep. >> how's everything going? >> It's going great. We're really happy with the turnout of the conference. We are really happy with the number of large enterprises that are here to share their story. The really active vendor ecosystem around the project. It's great. It's a wonderful event so far. >> Yeah, I was looking back, I think the last time I came to the Cloud Foundry Show, it was before the Foundation existed, We were in the Hilton in San Francisco, it was obviously a way smaller group. Tell us kind of the goals of the Foundation, doing the event, bringing the community in. >> Yeah, you can think about our goals as being of course, we're the stewards of the intellectual property, the actual software that the vendors distribute. We see our role in the ecosystem as being really two key things. One: we're focused on supporting the users, the customers, and the direct uses of the Open Source software. That's first and foremost. Second though, we want to make sure there is a really robust market ecosystem that is wrapped around this project, right. Both in terms of the distribution, the regional providers that offer Cloud Foundry based services, but also large system integrators that are helping those customers go through digital transformation. Re-platform applications, you know really figure out their way through this process. So, it's all about supporting the users and then supporting the market around it. >> Yeah, as we go to a lot of these events, you know, there are certain themes that emerge. There were two big ones that both of them showed up in what you did in the Keynote. Number one is Multicloud, number two is you got all of these various open sourced pieces, >> Chip: Yep. you know, what fits together, what interlocks together, you know which ones sit side by side. Why don't we start with kind of the open source piece first? Because you're heavily involved in a lot of those. Cloud Foundry, you know, what are the new pieces that are bolting on, or sitting on top, or digging into it, and what's going on there? >> You know, I think first I want to start with a basic philosophy of our upstream community. There are billions of dollars that rely on this platform today. And that continues to grow. Right, because we're showing up in Fortune 500, Global 2000, as well as lots of small start-ups, that are using Cloud Foundry to get code shipped faster. So our community that builds the UpStream software, spends a lot of time being very thoughtful about their technical decisions. So what we release and that what gets productized by the down streams is a complete system. From operating system all the way up to including the various programming languages and frameworks and everything in between. And because we release a complete platform, at a really high velocity, so many people rely on it's quality, we're very thoughtful about when is the right time to build our own, when should we adopt and embrace and continue to support another OpenSource project, so we spend a lot of time really thinking about that. And the areas today that I highlight around specific collaborations include the Open Service Broker API which we actually spun out of being just a Club Foundry implementation. And we embrace other communities, and found a way to share the governance of that. So we move forward as a big industry together. >> Stu: Yeah and speaking on that a little bit more. Very interesting to see. I saw Red Hat for instance speaking with Open Shift, Kubernetes is there. So, how should customers think about this? Are the path wars over? Now you can choose all the pieces that you want? Or, it's probably oversimplifying it. >> I think it's over simplifying it, it depends. You can go try to build your own platform if you want, through a number of serious components, or you can just use something like Cloud Foundry, that has solve for that. But the important thing is that we have specifically designed Cloud Foundry to allow for the backing services to come from anywhere. And so, it's both a differentiator for the various distributions of Cloud Foundry, but also an opportunity for Cloud providers, and even more importantly, it's an opportunity for the enterprise users that live in complex worlds, right? They're going to have multiple platforms, they're going be multiple levels of abstraction from Bms to containers, you know, to the path abstraction even event driven frameworks. We want that all to work really well together. Regardless of the choices you make, because that's what's most valuable to the customers. >> Okay, the other piece, networking you talked about. Why don't you share. >> Yeah, yeah so, besides the Service Broker API, we've added support for what's called Container to Container Networking. I don't necessarily need to dig into the details there, but let's just say that when you're building microservices that the application that the user is experiencing is actually a combination of a lot of different applications. That all talk to each other and rely on each other. So we want to make sure there's a policy-based framework for describing how the webs here is going to talk to the authentication service or is going to talk to the booking service, or the inventory service. They all need to have rules about how they communicate with each other. And we want to do that in the most efficient way possible. So we've adopted the Containing Networking interface as the standard plugin that is now at CNCF, the Cloud Native Computing Foundation. We think it's the right abstraction, we think it's great. It gives us access to all the fascinating work that is going on around software networking, overlay networking, industry standard API plugin to our policy-driven framework. >> Along the same theme, Kubo, a big new news project also kind of integration of some Cloud Foundry concepts with a broader ecosystem, in this case another CNCF project, Kubernetes. Could you speak a little bit to that? >> The Kubernetes community is doing a great job creating great container driven experience. You know that abstraction is all about the container. It's not about, you know, the code. So it's different than Cloud Foundry. There are workloads that make sense to run in one or the other. And we want to make sure that they run really well. Right, so the problem that we're solving with the Kuber project is what deploys Kubernetes? What supports Kubernetes if there is an infrastructure adage and a node goes offline? Right, because it does a great job of restarting containers, but if you have ten nodes in a cluster, and then now you're down to nine, that's a problem. So what Bosh does, is it takes care of solving the node outage level problem. You can also do rolling upgrades that are seamless, no downtime for the Kubernetes cluster. It brings a level of operational maturity to the Kubernetes users that they may not have had otherwise. >> Chip, can you bring us inside a little bit the creation of Kubo, is that something that the market and customers drove towards you? I talked to a couple other Cloud Foundry ecosystem members that were doing some other ways of integrating in Kubernetes. So what lead to this way of deploying it with Bosh? >> Yeah, absolutely so, it came out of a direct collaboration between Pivotal and Google. And it was driven based on Pivotal customer demand. It also, if you speak with people from Google that are involved in the project, they also see it as a need, for the Kubernetes ecosystem. So it's driven based on real-world large financial services companies that wanted to have the multiple abstractions available, they wanted to do it with a common operational platform that is proven mature that they've already adopted. And then as that collaboration board, the fruit of the project, and it was announced by Pivotal and Google several months back, they realized that they needed to move it to the vendor neutral locations so that we can continue to expand the community that can work on it, that can build up the story. >> The other topic I raised at the beginning of the interview, was the Multicloud. So in a panel, Microsoft, Google, MTC for Amazon was there. All of the Cloud guys are going to tell you we have the best platform and can do the best things for you. >> Of course they do. >> How do you balance the "We want to live in a multicultural Cloud world" and be able to go there versus "Oh I'm going to take standard plus and get in a little bit deeper to make sure that we're stickier with the customers there." What role does Cloud Foundry play? What have you seen in the marketplace for that? >> Well the public lab providers are, if you look at the services that they offer, you can roughly categorize them with two things. One, are the infrastructure building blocks. Two, are the higher level services, like their database capabilities, their analytics capabilities, log aggregation, you know, and they all have a portfolio that varies, some have specific things that are very similar. So when we talk about MultiCloud we talk about Cloud Foundry as a way to make use of those common capabilities, now they're going to differentiate based on speeds and feeds, availability, whatever they choose to, but you can then as a user have choice. And then secondarily, that Open Service Broker initiative is what's really about saying "great, there's also all these really valuable additional capabilities, that, as a user, I may choose to integrate with a Google machine learning-service, or I may choose to integrate with a wonderful Microsoft capability, or an Amazon capability." And we just want to make that easy for a developer to make that choice. >> Chip, Cloud Founder was very early in terms of a concept of a platform of services, let's not call it platform as a service right now. But you know, this platform that going to make developers lives easier, multi-target, MultiCloud we call it now, on from your laptop to anywhere. And it's been a really interesting discussion over the last couple years as this parallel container thread can come up with Kubernetes and Mesosphere and all the orchestration tools, and the focus has been on orchestration tools. And I've always thought Cloud Foundry was kind of way ahead of the game in saying "wait a minute, there's a set of services that you're going to have for full life-cycles, day two operation, at scale that you all are going to have to pull together from components." As we're doing this interview here, and this year at Cloud Foundry Summit are there anything that you think people don't kind of realize that over and over again people who are using Cloud Foundry go, "Wow I'm really glad "I had logging or identity management," or what are some of the frameworks that people sometimes don't realize is in there that actually is a huge time-savor. >> Yeah, there are a lot of operational capabilities in the Cloud Foundry platform. When you include both our Bosh layer, as well as the elastic runtime which is in the developer centers experience-- >> John: Anything that people don't often realize is in there? >> Well, I think that the right way to think of it is, it's all the things you need in one application, right? So we've been doing this for years as developers. In the applications operators team, we've been doing it. We've just been doing it via bunch of tickets, we've been doing it via bunch of scripts. What Cloud Foundry does is it takes all of those capabilities you need to really trust a platform to operate something on your behalf, and give you the right view into it, right? The appropriate telemetry, log aggregation, and know that there's going to be help monitoring there. It makes it really easy. Right, so we were talking earlier about the haiku, that Onsi Fakhouri from Pivotal had authored, it's appropriate. It's a promise that a platform makes. And platforms designed to let a user trust that the declarative nature of asking a platform to do X, Y, or Z, will be delivered. >> Chip, we've been hearing Pivotal talks a lot about Spring, when Cloud Foundry's involved. Is it so much so that the Foundation needs to be behind that, or support that? How does that interact and work? >> Well, we're super supportive of all the languages in the framework communities that are out there. You know, even if you pick a particular vendor, Pivotal in this case has a very strong investment in the Spring, Spring Cloud, Spring Boot, they're doing really amazing things. But that's also, it's our software, you know, they steward that community, so all the other vendors actually get the advantage of that. Let's take Dot Net and Microsoft. Microsoft open sourced Dot Net. So now you can run Dot Net applications on Linux. They're embrace of the container details and the APIs and their operating system is making it so that now it can also run on Windows. So the whole Microsoft technology stack, languages and frameworks, they matter quite a bit to the enterprise as well. So we see ourselves as supportive of all of these communities, right? Even ones like the Ruby community. When there's an enterprise developer that chooses to use something like Ruby, with the Ruby on Rails framework, if they use Cloud Foundry, they're getting the latest and greatest version of that language, framework, they know that it's secure, they know that it's going to be patched for them. So it's actually a great experience for that developer, that's working with the language. So, we like to support all of them, we're big fans of any that work really well with the platform and maybe integrate deeper. But it's a polyglot platform. >> We want to give you the final word. People take away from Cloud Foundry Summit 2017, what would you want them to take away? >> Yeah the simple takeaway that I can give you is that this is an absolutely enterprise grade open source ecosystem. And you don't hear that often, right? Because normally we talk about products, being enterprise great. >> Did somebody say in the keynote enterprise great mean that there's a huge salesforce that's going to try sell you stuff? (Chip laughs) Well that's coming from the buying side of the market for years. And you know, it was a bit of a joke. What is "enterprise great?" Well, it means that there's a piece of paper that says, this product will cost x dollars and the salesperson is offering it to you. So of course it's going to be enterprise great. But really, we see it as four key things, right? It's about security, it's about being well-integrated, it's about being able to scale to the needs of even the largest enterprises, and it's also about that great developer experience. So, Cloud Foundry is an ecosystem and all of our downstream distributions get the advantage of this really robust and mature technical community that is producing this software. >> Chip, really appreciate you sharing all the updates with us, and appreciate the foundation's support to bring theCUBE here. We'll be back with lots more coverage here from The Cloud Foundry Summit 2017, you're watching theCUBE. (techno music)