>>And welcome to this special cube conversation. I'm John for a, your host of the cube. We're here in Palo Alto, California, and I'm here with a very special guest coming down from Seattle remotely into the cube studios is the leader at AWS Amazon web services, the vice president of database analytics and machine learning Swami. Great to see you cube alumni recently taking over the database business at AWS as a leader. Congratulations. And thanks for coming on the cube. >>Hey, my pleasure to be here, John, very excited to talk to you. >>Yeah. We've had many conversations on the cube and also in person and also online around all the major mega trends. You've had your hand in all the action, going back to your days when you were in school learning and, and writing papers. And 10 years ago, Amazon web services launched AWS dynamo, DB, fast, flexible, no SQL database that everyone loves today, which has inspired a generation of what I would call database distributing cloud scale, single digit millisecond performance at scale. And again, the key scale. And again, this is 10 years ago, so it seems like yesterday, but you guys are celebrating and your name was on the original paper with CTO Verner. Vogel's your celebrity. Congratulations. >>Thank you. Not sure about the celebrating part, but I'm very excited. At least I played a hand in building such an amazing technology that has enabled so many amazing customers along the way as well. So >>Trivia on the, on the paper as you were an intern at AWS, so you're getting your PhD. And then since, since rising through the ranks and involved in a lot of products over the years, and then leading the machine learning and AI, which is now changing the game at the industry level, but I got to ask you getting back to the story here. A lot of customers have built amazing things on top of dynamo DB, not to mention lots of other AWS and Amazon tech riding on it. Can you share some of the highlights that came out of the original paper? And so with some examples, because I think this is a point in time, 10 years ago, where you start to, so the KickUp of cloud scale, not just, just for developers and building startups, you're really starting to see the scale rise. >>Yeah, I actually, I mean, as you probably know, based on what he read to explain the Genesis of dynamo DB itself had to explain the Genesis of how Amazon got into building the original dynamo, right? And this was during the time when miner, I joined Ron esteem as an intern and, and Amazon was one of the pioneers in pushing the boundary of scale. And a year over year, our Q4 holiday season tends to be really, really bad for all the right reasons. We all want our holiday shopping done during that time. And you want to be able to scale your website, arters fulfillment centers, all of them at that time. And those are the times around 2005. And the answer is when people think our database, they think of a single database server that actually runs on a box and has a certain characteristics and does a scale and availability and whatnot. >>And it's usually relational. And then when we had a major disruption during Q4 that's when yeah, ask ourselves the question, why are we actually using a relational database for some of these things when they really didn't need the data model complexity of relational database. And normally I would say most companies where to actually ask an intern or a few engineers who are early in the career saying like, what the hell are you suggesting? Just go away. But Amazon being enabling Buddhists to build what they want. And they actually let us start reimagining what a database or our scale could look like. And that led to dynamo. And since she unstained mine, then we migrated from an traditional relational database stair this one for some of the amazon.com services. And then I moved on to actually start building some butts off our storage service and then our managed relational database service, I explicitly remember. >>And one of our customer advisory board, we're just the set off some of our leading customers who actually give us feedback on roadmap. Another son, Don, who's the CEO and chief geek of spunk bargain faker. And him actually looking at the Trinity me, I was starting in the corner and saying like you all, both tomorrow and why do I need to keep shotting my, my sequel database and reshooting assigned scaling. And this is the time when the state of the art in most databases were around. Like, you start sharding your relational database and constantly reshaping. And this is when most websites are starting to experience the kind of scale which we consider a normal month. During those times it was mostly, most companies used to have a single relational database backend and start scaling that way. And that conversation led entirely under duress, unaided read, lot of AWS leaders and myself saying like, Hey, what is a cloud database reimagined without the hampering SQL look like? And that led us to start building dynamo DB, but just a key value database at that time. Now we support document might've too, but that single digit millisecond latency at any scale imagine. So >>I think about that time at that time, 10 years ago, when you were having this conversation and I know the smug mug and I, he said, he's in totally geek and he's, he's good to point that out. You also have Netflix as customers too. I'd like to hear how that's evolved, but, but I think back at the time, if you look back then I got to ask you most people we've talked about this before. No one database rules, a world that's now standard people now don't see one database back then it was a one database kind of mindset back then. Yeah. And then you had that big data movement happening with Hadoop. You had the object store developing. So you're in you're you're circling around that area. What was it like then? I mean, take, take us through that because there was obvious visibility that, Hey, let's just store this. Now you see data lakes and that's all happening. But back then object store was kind of new. Yeah. >>Ah, it's a great question. Now, one of the things I realized early on, especially when I was working with binary, when you're saying amazon.com itself as an example, that the access patterns for various applications and Amazon, but let alone AWS customers tend to be very, very, very, some of them really just needed an object store. Some of them needed a relational database. Some of them really wanted a key value store within a fast latency. Some of them really needed a durable cash. And, but it so happens when you have a giant hammer. You use that for everything looks like a map, which is essentially the story at that time. And so everyone kept using the same database, irrespective of what the problem was because nobody else, I mean, thought about like, what else can we build that is better? So this let us do, literally I remember writing a paper with Bernard internally that is widely used in Amazon explaining what are all the menu of booklets that access. >>And then how do we go about actually solving for each of these things so that they can actually grow and innovate faster. And, and this was led to actually the Genesis of not only building IDs and so forth, but also dynamo and various other non-relational data. There's a still let alone not so storage access patterns and what not. So, and this was one of the big revelations he had just that there is not a single database that is going to meet the customer, needs us. The diversity of workloads in the internet is growing. And this was a key pivotal moment because with cloud now applications can scale very more instantly than before now. Building an application for Superbowl is very easier than before. That means that on, I mean, everybody is pushing the boundaries of what scale means, and they are expecting more from their obligations. That's when you need technologies like dynamo, DB, and that's exactly what dynamo already be set out to do. And since then, we are continuing to innovate on behalf of our customers and the purpose of the database story as well. And this concept has resonated well across the board. If you see that the database industry has also embraced this method, >>It's natural that you obviously evolved into the machine learning side of it because that's data is big part of that. And you see back then you, you bringing up kind of like flashes for me where it's like those, the data conversations back then and the data movement was just beginning. So the idea that you can have diversity in access methods of the kind of databases was a use case driven by the application, not so much database saying, this is how you have to work, that the script was flipped. It it's changed from infrastructure dictating to the applications, what to do. Now, the applications are going to the infrastructure and saying, give me what I want. I want to access something here in an office store, something here in no SQL that became the Genesis of infrastructure as code at a, at a global level. And so your paper kind of set the, the, the wave, the influence for this, no SQL did big data movement. It's created tons of value, maybe a third Mongo might've been influenced by this other people have been influenced. Can you share some stories of how people adopted the concept of dynamo DB and how that's changed in the industry and how has that helped the industry evolve? >>I mean, plus file data. Most share our experience of building and dynamo style data store. Very, it is a non-relational API and showing what are some of the experiences that the Venter in building such an paper and these set out early on itself, that it is should not be just a design paper, but it should be something that we shared our experiences. So even now, when I talked to my friends and colleagues and various other companies, one thing they always tell me is they appreciated the openness with which we were sharing. Some of the examples and learnings that we learned to not optimizing for percentile latencies, and what are some of the scalability challenges, how we solved and some of the techniques around things like sloppy Cora or various other stuff. We invented a lot of towns along the way too, but people really appreciated several of some of our findings and as talking about it. >>And since then I met so many other innovations are happening in the industry and the AWS, but also across the entire academia and industry in this space, the databases I've been going through what I call as a period of Renaissance, where one of the things, if you see our own arc, when Roger and I started on the database, front Disney started over the promo saying like, if you were to build a database where cloud is the new normal, this is again in 2008, we asked ourselves that question and what the belt that led us to start building things like dynamo, DB, RDS star. I know that alone, we reimagined data viruses with Redshift and several, and then several other databases like time stream for time series workloads started running Neptune for graph and whatnot. But at the moment we started actually asking that question and working backwards from customers. Then you will start being able to innovate accordingly. And this has worked really well. Then more than a hundred thousand AWS customers have chosen dynamo DB for mobile gaming tech IOT. Many of these are fast growing businesses, such as ledge, Darryl BNB, red fan, as soon as enterprises like Samsung Toyota, capital one and so far. So these are like really some meaningful clouds, let alone amazon.com. I run this. >>We have an internal customer is always good to have that entire inside customer. You know, I really find this a really profound use case because you're just talking, you know, in Amazonian terms, I'll just translate for the audience working backwards from the customer, which is the customer obsession you guys have. So here's, what's going on off the way I see it. You got dynamo, DB, paper, you and Verner, and the team Paul was a great as a great video on your blog posts that goes into the, to the talk he gave at around that time, which is fun to watch if you look back, but you have a radical enabler here, that's disrupting and changing S3 RDS, Aurora. These are game-changing concepts inside the, the landscape of AWS at the same time, you're working backwards from the customer. So the question I have for you as a leader and as a builder, how did you balance the working backwards from the customer while bringing something brand new and radical at that time to the market? >>Yeah, this is one of the S I mean hardest things to be, as leaders need to balance on. If you see many times, then we actually worked backwards from customers. The literal later translated this, literally do what customers are asking for, which is true nine out of 10 times, but there is one or a 10 times, you got to read between the lines on what they are asking. Because many times customers when are articulate that they need to go fast. If in the right way, they might say, Hey, I wish my heart storage goes faster, but they're not going to tell you they need a car, but you need to know and be able to translate and read between the lines we call it under the bucket of innovate on behalf of customers. And that is exactly the kind of a mantra we had when we were thinking about concepts like dynamo DB, because essentially at that time, almost everybody would, if I asked, they would just say, I wish a relational database could actually be able to scale from not just like a hundred gigabyte to one terabyte are, it can take up to like 2 million transactions, a second and so forth and still be cheap and made in reality as relational databases, the way they were engineered at that time, those are not going to meet the scale needs. >>So this is fair. We hunted read between the lines on what are some of the key Mustang needs from customers and then work backwards and then innovate on behalf of these workloads, be enabled by the sun oh four, which are some of the reasons that led to us launching some of the initial sets on dynamo on a single digit millisecond latency and seamless scale. At that time, databases didn't have the elasticity to go from like 10 requests, a second to like a hundred thousand or 1 million requests a second, and then scaled right back in an hour. So that was not possible. And we kind of enabled that. And that was an, a pretty big game changer that showed the elasticity of the cloud to a database. Well, >>Yeah, I think also just to, not to nerd out on this, but it enables a lot of other kind of cool scaled concepts, like queuing storage. It's all kind of together. This database piece of that you guys are solving. And again, props to you guys on the team. Congratulations. I have to ask, you know, more generally, how has your thinking changed since the paper? I'll see, you've got more experience under your belt. You don't yet have the gray hairs yet, but we'll see those soon come in, but you know, you're, you got a lot more experience. You're running teams, you're launching a lot of products. How has your thinking changed in the industry since the paper what's happening now? What's the big evolution. What are those new things now that are in the innovate on behalf of the customer? What's between the lines now, how do you see this happening? >>I mean, now since wanting dynamo via a victim, I had the opportunity to work on various problems in the big data space. There we've worked on some are fire things that you might be aware of in the analytics all the way from Redshift to quick side, too. Then I moved on to start some of our efforts, having built systems that enabled customer to store process and credit, and then analyze them. One of the realizations, I had this, the in around 2015 or 2016, I kinda had that machine learning was hitting a critical point where now it is ready for being scaled at option. Their cloud has basically enabled limitless compute and limitless storage, which are the factors that are holding back machine learning technology. Then I realized that now we have a unique opportunity to bring machine learning BI to everybody, not just folks with PhD in machine learning. >>And that's when I moved on from database and analytics areas, they started machine learning. We're just a descent area because machine learning is powered by data and then started building capabilities like SageMaker, which is our end to end ML platform to build, train and deploy them on models. And this, what does the leading enterprise platform by several gaggled users and then also a bunch of our AI services since then, I view the reason I'm giving all this historical context is one of the biggest realization I had early on itself. And 2016 as first machine learning is one of the most disruptive technologies. She will then country in our generation. This is right after cloud. I think these still are the most amazing combination that is going to revolutionize how we build applications and how we actually reason about that. Now, the second thing is that at the end of the day, when you look at the ANC and journey, it is not just about one database or one data Varroa. >>So one data lake product, or even 1:00 AM out platform. It is about the end to end journey where a customer is storing their order database. And then they are actually building a data lake that test customer history and order history. And they want to be able to personalize. And for their viewer experience are actually forecast what products to staff in their fulfillment center, but then all these things need to work and to handle. And that view is one of the big things that struck me for the past five years. And I've been on this journey in addition to building this Emma building blocks to connect the dots so that customers can go on this modern end to end data strategy as I call it, right. It goes beyond a single database technology or data technology, but putting now all of these end to end together so that customers don't end up spending six months connecting the dots, which has been the state of the down for the last couple of years. And we are bringing it down to matter of the Sundays. Now >>He's incredible Swami. Thank you so much for spending the time with us here in the, >>Yeah, my pleasure. Thanks again, Sean. Thanks for having me.

>> From the Silicon Angle Media Office in Boston Massachusetts, it's "The Cube." (groovy techno music) Now, here's your host, Dave Vellante. >> Hello, everyone. The rise of open source is really powering the digital economy. And in a world where every company is essentially under pressure to become a software firm, open source software really becomes the linchpin of digital services for both incumbents and, of course, digital natives. Here's the challenge, is when developers tap and apply open source, they're often bringing in hundreds, or even thousands of lines of code that reside in open sourced packages and libraries. And these code bases, they have dependencies, and essentially hidden traps. Now typically, security vulnerabilities in code, they're attacked after the software's developed. Or maybe thrown over the fence to the sec-ops team and SNYK is a company that set out to solve this problem within the application development life cycle, not after the fact as a built-on. Now, with us to talk about this mega-trend is Peter McKay, a friend of The Cube and CEO of SNYK. Peter, great to see you again. >> Good to see you, dude. >> So I got to start with the name. SNYK, what does it mean? >> SNYK, So Now You Know. You know, people it's sneakers sneak. And they tend to use the snick. So it's SNYK or snick. But it is SNYK and it stands for So Now You Know. Kind of a security, so now you know a lot more about your applications than you ever did before. So it's kind of a fitting name. >> So you heard my narrative upfront. Maybe you can add a little color to that and provide some additional background. >> Yeah, I mean, it's a, you know, when you think of the larger trends that are going on in the market, you know, every company is going through this digital transformation. You know, and every CEO, it's the number one priority. We've got to change our business from, you know, financial services, healthcare, insurance company, whatever, are all switching to digital, you know, more of a software company. And with that, more software equals more software risk and cybersecurity continues to be, you know, a major. I think 72% of CEOs worry about cybersecurity as a top issue in protecting companies' data. And so for us, we've been in the software in the security space for the four and a half years. I've been in the security space since, you know, Watchfire 20 years ago. And right now, with more and more, as you said, open source and containers, the challenge of being able to address the cybersecurity issues that have never been more challenging. And so especially when you add the gap between the need for security professionals and what they have. I think it's four million open positions for security people. So you know, with all this added risk, more and more open source, more and more digitization, it's created this opportunity in the market where you're traditional approaches to addressing security don't work today, you know? Like you said, throwing it over the fence and having someone in security, you know, check and make sure and finding all these vulnerabilities, and throw it back to developers to fix is very slow and something at this point is not driving to success. >> So talk a little bit more about what attracted you to SNYK early. I mean, you've been with the company, you're at least involved in the company for a couple years now. What were the trends that you saw, and what was it about SNYK that, you know, led you to become an investor and ultimately, CEO? >> Yeah, so four years involved in the business. So you know, I've always loved the security space. I've been in it for a number, almost 20 years. So I enjoy the space. You know, I've watched it. The founder, Guy Podjarny, one of the founders of SNYK, has been a friend of mine for 16 years from back in the Watchfire days. So we've always stayed connected. I've always worked well together with him. And so when you started, and I was on the board, the first board member of the company, so I could see what was going on, and it was this, you know, changing, kind of the right place at the right time in terms of developer first security. Really taking all the things that are going on in the security space that impacts a developer or can be addressed by the developer, and embedding it into the software into that developer community, in a way that developers use, the tools that they use. So it's a developer-first mindset with security expertise built-in. And so when you look at the market, the number of open source container evolution, you know, it's a huge market opportunity. Then you look at the business momentum, just took off over the past, you know, four years. That it was something that I was getting more and more involved in. And then when Guy asked me to join as the CEO, it was like, "Sure, what took you so long?" (Dave laughing) >> We had Guy on at Node JS Summit. I want to say it was a couple years ago now. And what he was describing is when you package, take the example of Node. When you package code in Node, you bring in all these dependencies, kind of what I was talking about there, but the challenge that he sort of described was really making it seamless as part of the development workflow. It seems like that's unique to SNYK. Maybe you could talk about-- >> Yeah, it is. And you know, we've built it from the ground up. You know, it's very difficult. If it was a security tool for security people, and then say, "Oh, let's adapt it for the developer," that is almost impossible. Why I think we've been so successful from the 400,000 developers in the community using Freemium to paid, was we built it from the ground up for developer, embedded into the application-development life cycle. Into their process, the look and feel, easy for them to use, easy for them to try it, and then we focused on just developer adoption. A great experience, developers will continue to use it and expand with it. And most of our opportunities that we've been successful at, the customers, we have over 400 customers. That had been this try, you know, start it with the community. They used the Freemium, they tried it for their new application, then they tried it for all their new, and then they go back and replace the old. So it was kind of this Freemium, land and expand has been a great way for developers to try it, use it. Does it work, yes, buy more. And that's the way we work. >> We're really happy, Peter, that you came on because you've got some news today that you're choosing to share with us in our Cube community. So it's around financing, bring us up to date. What's the news? >> Yeah so you know, I'd say four months ago, five months ago, we raised a $70 million round from great investors. And that was really led by one of our existing investors, who kind of knew us the best and it was you know, Excel Venture, and then Excel Growth came in and led the $70 million round. And part of that was a few new investors that came in and Stripes, which is you know a very large growth equity investor were part of that $70 million round said you know, preempted it and said, "Look it, we know you don't need the money, but we want to," you know, "We want to preempt. We believe your customer momentum," here we did, you know, five or six really large deals. You know, one, 700, seven million, 7.4 million, one's 3.5 million. So we started getting these bigger deals and we doubled since the $70 million round. And so we said, "Okay, we want to make money not the issue." So they led the next round, which is $150 million round, at a valuation of over a billion. That really allows us now to, with the number of other really top tier, (mumbles) and Tiger and Trend and others, who have been part of watching the space and understand the market. And are really helping us grow this business internationally. So it's an exciting time. So you know, again, we weren't looking to raise. This was something that kind of came to us and you know, when people are that excited about it like we are and they know us the best because they've been part of our board of directors since their round, it allows us to do the things that we want to do faster. >> So $150 million raise this round, brings you up to the 250, is that correct? >> Yes, 250. >> And obviously, an up-round. So congratulations, that's great. >> Yeah, you know, I think a big part of that is you know, we're not, I mean, we've always been very fiscally responsible. I mean, yes we have the money and most of it's still in the bank. We're growing at the pace that we think is right for us and right for the market. You know, we continue to invest product, product, product, is making sure we continue our product-led organization. You know, from that bottoms up, which is something we continue to do. This allows us to accelerate that more aggressively, but also the community, which is a big part of what makes that, you know, when you have a bottoms up, you need to have that community. And we've grown that and we're going to continue to invest aggressively and build in that community. And lastly, go to market. Not only invest, invest aggressively in the North America, but also Europe and APJ, which, you know, a lot of the things we've learned from my Veeam experience, you know how to grow fast, go big or go home. You know, are things that we're going to do but we're going to do it in the right way. >> So the Golden Rule is product and sales, right? >> Yes, you're either building it or selling it. >> Right, that's kind of where you're going to put your money. You know, you talk a lot about people, companies will do IPOs to get seen, but companies today, I mean, even software companies, which is a capital-efficient industry, they raise a lot of dough and they put it towards promotion to compete. What are your thoughts on that? >> You know, we've had, the model is very straightforward. It's bottoms up, you know? Developers, you know, there's 28 million developers in the world, you know? What we want is every one of those 28 million to be using our product. Whether it's free or paid, I want SNYK used in every application-development life cycle. If you're one developer, or you're a sales force with standardized on 12,000 developers, we want them using SNYK. So for us, it's get it in the hands. And that, you know, it's not like-- developers aren't going to look at Super Bowl ads, they're not going to be looking. It's you know, it's finding the ways, like the conference. We bought the DevSecCon, you know, the conference for developer security. Another way to promote kind of our, you know, security for developers and grow that developer community. That's not to say that there isn't a security part. Because, you know, what we do is help security organizations with visibility and finding a much more scalable way that gets them out of the, you know, the slows-down, the speed bump to the moving apps more aggressively into production. And so this is very much about helping security people. A lot of times the budgets do come from security or dev-ops. But it's because of our focus on the developer and the success of fixing, finding, fixing, and auto-remediating that developer environment is what makes us special. >> And it's sounds like a key to your success is you're not asking developer to context switch into a new environment, right? It's part of their existing workflow. >> It has to be, right? Don't change how they do their job, right? I mean, their job is to develop incredible applications that are better than the competitors, get them to market faster than they can, than they've ever been able to do before and faster than the competitor, but do it securely. Our goal is to do the third, but not sacrifice on one and two, right? Help you drive it, help you get your applications to market, help you beat your competition, but do it in a secure fashion. So don't slow them down. >> Well, the other thing I like about you guys is the emphasis is on fixing. It's not just alerting people that there's a problem. I mean, for instance, a company like Red Hat, is that they're going to put a lot of fixes in. But you, of course, have to go implement them. What you're doing is saying, "Hey, we're going to do that for you. Push the button and then we'll do it," right? So that, to me, that's important because it enables automation, it enables scale. >> Exactly, and I think this has been one of the challenges for kind of more of the traditional legacy, is they find a whole bunch of vulnerabilities, right? And we feel as though just that alone, we're the best in the world at. Finding vulnerabilities in applications in open source container. And so the other part of it is, okay, you find all them, but prioritizing what it is that I should fix first? And that's become really big issue because the vulnerabilities, as you can imagine, continue to grow. But focusing on hey, fix this top 10%, then the next, and to the extent you can, auto-fix. Auto-remediate those problems, that's ultimately, we're measured by how many vulnerabilities do we fix, right? I mean, finding them, that's one thing. But fixing them is how we judge a successful customer. And now it's possible. Before, it was like, "Oh, okay, you're just going to show me more things." No, when you talk about Google and Salesforce and Intuit, and all of our customers, they're actually getting far better. They're seeing what they have in terms of their exposure, and they're fixing the problems. And that's ultimately what we're focused on. >> So some of those big whales that you just mentioned, it seems to me that the value proposition for those guys, Peter, is the quality of the code that they can develop and obviously, the time that it takes to do that. But if you think about it more of a traditional enterprise, which I'm sure is part of your (mumbles), they'll tell you, the (mumbles) will tell you our biggest problem is we don't have enough people with the skills. Does this help? >> It absolutely-- >> And how so? >> Yeah, I mean, there's a massive gap in security expertise. And the current approach, the tools, are, you know, like you said at the very beginning, it's I'm doing too late in the process. I need to do it upstream. So you've got to leverage the 28 million developers that are developing the applications. It's the only way to solve the problem of, you know, this application security challenge. We call it Cloud Dative Application Security, which all these applications usually are new apps that they're moving into the Cloud. And so to really fix it, to solve the problem, you got to embed it, make it really easy for developers to leverage SNYK in their whole, we call it, you know, it's that concept of shift left, you know? Our view is that it needs to be embedded within the development process. And that's how you fix the problem. >> And talk about the business model again. You said it's Freemium model, you just talked about a big seven figure deals that you're doing and that starts with a Freemium, and then what? I upgrade to a subscription and then it's a land and expand? Describe that. >> Yeah we call it, it's you know, it's the community. Let's get every developer in a community. 28 million, we want to get into our community. From there, you know, leverage our Freemium, use it. You know, we encourage you to use it. Everybody to use our Freemium. And it's full functionality. It's not restricted in anyway. You can use it. And there's a subset of those that are ready to say, "Look it, I want to use the paid version," which allows me to get more visibility across more developers. So as you get larger organization, you want to leverage the power of kind of a bigger, managing multiple developers, like a lot of, in different teams. And so that kind of gets that shift to that paid. Then it goes into that Freemium, land, expand, we call it explode. Sales force, kind of explode. And then renew. That's been our model. Get in the door, get them using Freemium, we have a great experience, go to paid. And that's usually for an application, then it goes to 10 applications, and then 300 developers and then the way we price is by developer. So the more developers who use, the better your developer adoption, the bigger the ultimate opportunity is for us. >> There's a subscription service right? >> All subscription. >> Okay and then you guys have experts that are identifying vulnerabilities, right? You put them into a database, presumably, and then you sort of operationalize that into your software and your service. >> Yeah, we have 15 people in our security team that do nothing everyday but looking for the next vulnerability. That's our vulnerability database, in a large case, is a lot of our big companies start with the database. Because you think of like Netflix and you think of Facebook, all of these companies have large security organizations that are looking for issues, looking for vulnerabilities. And they're saying, "Well okay, if I can get that feed from you, why do I have my own?" And so a lot of companies start just with the database feed and say, "Look, I'll get rid of mine, and use yours." And then eventually, we'll use this scanning and we'll evolve down the process. But there's no doubt in the market people who use our solution or other solution will say our known the database of known vulnerabilities, is far better than anybody else in the market. >> And who do you sell to, again? Who are the constituencies? Is it sec-ops, is it, you know, software engineering? Is it developers, dev-ops? >> Users are always developers. In some cases dev-ops, or dev-sec. Apps-sec, you're starting to see kind of the world, the developer security becoming bigger. You know, as you get larger, you're definitely security becomes a bigger part of the journey and some of the budget comes from the security teams. Or the risk or dev-ops. But I think if we were to, you know, with the user and some of the influencers from developers, dev-ops, and security are kind of the key people in the equation. >> Is your, you have a lot of experience in the enterprise. How do you see your go to market in this world different, given that it's really a developer constituency that you're targeting? I mean, normally, you'd go out, hire a bunch of expensive sales guys, go to market, is that the model or is it a little different here because of the target? >> Yeah, you know, to be honest, a lot of the momentum that we've had at this point has been inbound. Like most of the opportunities that come in, come to us from the community, from this ground up. And so we have a very large inside sales team that just kind of follows up on the inbound interest. And that's still, you know, 65, 70% of the opportunities that come to us both here and Europe and APJ, are coming from the community inbound. Okay, I'm using 10 licenses of SNYK, you know, I want to get the enterprise version of it. And so that's been how we've grown. Very much of a very cost-effective inside sales. Now, when you get to the Googles and Salesforces and Nordstroms of the world, and they have already 500 licenses us, either paid or free, then we usually have more of a, you know, senior sales person that will be involved in those deals. >> To sort of mine those accounts. But it's really all about driving the efficiency of that inbound, and then at some point driving more inbound and sort of getting that flywheel effect. >> Developer adoption, developer adoption. That's the number one driver for everybody in our company. We have a customer success team, developer adoption. You know, just make the developer successful and good things happen to all the other parts of the organization. >> Okay, so that's a key performance indicator. What are the, let's wrap kind of the milestones and the things that you want to accomplish in the next, let's call it 12 months, 18 months? What should we be watching? >> Yeah, so I mean it continues to be the community, right? The community, recruiting more developers around the globe. We're expanding, you know, APJ's becoming a bigger part. And a lot of it is through just our efforts and just building out this community. We now have 20 people, their sole job is to build out, is to continue to build our developer community. Which is, you know, content, you know, information, how to learn, you know, webinars, all these things that are very separate and apart from the commercial side of the business and the community side of the business. So community adoption is a critical measurement for us, you know, yeah, you look at Freemium adoption. And then, you know, new customers. How are we adding new customers and retaining our existing customers? And you know, we have a 95% retention rate. So it's very sticky because you're getting the data feed, is a daily data feed. So it's like, you know, it's not one that you're going to hook on and then stop at any time soon. So you know, those are the measurements. You look at your community, you look at your Freemium, you look at your customer growth, your retention rates, those are all the things that we measure our business by. >> And your big pockets of brain power here, obviously in Boston, kind of CEO's prerogative, you got a big presence in London, right? And also in Israel, is that correct? >> Yeah, I would say we have four hubs and then we have a lot of remote employees. So, you know, Tel Aviv, where a lot of our security expertise is, in London, a lot of engineering. So between London and Tel Aviv is kind of the security teams, the developers are all in the community is kind of there. You know, Boston, is kind of more go to market side of things, and then we have Ottawa, which is kind of where Watchfire started, so a lot of good security experience there. And then, you know, we've, like a lot of modern companies, we hired the best people wherever we can find them. You know, we have some in Sydney, we've got some all around the world. Especially security, where finding really good security talent is a challenge. And so we're always looking for the best and brightest wherever they are. >> Well, Peter, congratulations on the raise, the new role, really, thank you for coming in and sharing with The Cube community. Really appreciate it. >> Well, it's great to be here. Always enjoy the conversations, especially the Patriots, Red Sox, kind of banter back and forth. It's always good. >> Well, how do you feel about that? >> Which one? >> Well, the Patriots, you know, sort of strange that they're not deep into the playoffs, I mean, for us. But how about the Red Sox now? Is it a team of shame? All my friends who were sort of jealous of Boston sports are saying you should be embarrassed, what are your thoughts? >> It's all about Houston, you know? Alex Cora, was one of the assistant coaches at Houston where all the issues are, I'm not sure those issues apply to Boston, but we'll see, TBD. TBD, I am optimistic as usual. I'm a Boston fan making sure that there isn't any spillover from the Houston world. >> Well we just got our Sox tickets, so you know, hopefully, they'll recover quickly, you know, from this. >> They will, they got to get a coach first. >> Yeah, they got to get a coach first. >> We need something to distract us from the Patriots. >> So you're not ready to attach an asterisk yet to 2018? >> No, no. No, no, no. >> All right, I like the optimism. Maybe you made the right call on Tom Brady. >> Did I? >> Yeah a couple years ago. >> Still since we talked what, two in one. And they won one. >> So they were in two, won one, and he threw for what, 600 yards in the first one so you can't, it wasn't his fault. >> And they'll sign him again, he'll be back. >> Is that your prediction? I hope so. >> I do, I do. >> All right, Peter. Always a pleasure, man. >> Great to see you. >> Thank you so much, and thank you for watching everybody, we'll see you next time. (groovy techno music)

>>Live from San Diego, California It's the Q covering Koopa and Cloud Native Cot brought to you by Red Cloud, Native Computing Pounding and its ecosystem March. >>Welcome back to the Cube here at Q. Khan Club native Khan, 2019 in San Diego, California Instrumental in my co host is Jon Cryer and first of all, happy to welcome back to the program. Diane Mueller, who is the technical of the tech lead of cloud native technology. I'm sorry. I'm getting the wrong That's director of community development Red Hat, because renew. Goodbye is the technical lead of cognitive technologies at in video game to the end of day one. I've got three days. I gotta make sure >>you get a little more Red Bull in the conversation. >>All right, well, there's definitely a lot of energy. Most people we don't even need Red Bull here because we're a day one. But Diane, we're going to start a day zero. So, you know, you know, you've got a good group of community of geeks when they're like Oh, yeah, let me fly in a day early and do like 1/2 day or full day of deep dives. There So the Red Hat team decided to bring everybody on a boat, I guess. >>Yeah. So, um, open ships Commons gathering for this coup con we hosted at on the inspiration Hornblower. We had about 560 people on a boat. I promised them that it wouldn't leave the dock, but we deal still have a little bit of that weight going on every time one of the big military boats came by. And so people were like a little, you know, by the end of the day, but from 8 a.m. in the morning till 8 p.m. In the evening, we just gathered had some amazing deep dives. There was unbelievable conversations onstage offstage on we had, ah, wonderful conversation with some of the new Dev ops folks that have just come on board. That's a metaphor for navigation and Coop gone. And and for events, you know, Andrew Cliche for John Willis, the inevitable Crispin Ella, who runs Open Innovation Labs, and J Bloom have all just formed the global Transformation Office. I love that title on dhe. They're gonna be helping Thio preach the gospel of Cultural Dev ops and agile transformation from a red hat office From now going on, there was a wonderful conversation. I felt privileged to actually get to moderate it and then just amazing people coming forward and sharing their stories. It was a great session. Steve Dake, who's with IBM doing all the SDO stuff? Did you know I've never seen SDO done so well, Deployment explains so well and all of the contents gonna be recorded and up on Aaron. We streamed it live on Facebook. But I'm still, like reeling from the amount of information overload. And I think that's the nice thing about doing a day zero event is that it's a smaller group of people. So we had 600 people register, but I think was 560 something. People show up and we got that facial recognition so that now when they're traveling through the hallways here with 12,000 other people, that go Oh, you were in the room. I met you there. And that's really the whole purpose for comments. Events? >>Yeah, I tell you, this is definitely one of those shows that it doesn't take long where I say, Hey, my brain is full. Can I go home. Now. You know I love your first impressions of Q Khan. Did you get to go to the day zero event And, uh, what sort of things have you been seeing? So >>I've been mostly I went to the lightning talks, which were amazing. Anything? Definitely. There. A number of shout outs to the GPU one, of course. Uh, friend in video. But I definitely enjoyed, for example, of the amazing D. M s one, the one about operators. And generally all of them were very high quality. >>Is this your first Q? Khan, >>I've been there. I've been a year. This is my third con. I've been accused in Europe in the past. Send you an >>old hat old hand at this. Well, before we get into the operator framework and I wanna love to dig into this, I just wanted to ask one more thought. Thought about open shift, Commons, The Commons in general, the relationship between open shift, the the offering. And then Okay, the comments and okay, D and then maybe the announcement about about Okay. Dee da da i o >>s. Oh, a couple of things happened yesterday. Yesterday we dropped. Okay, D for the Alfa release. So anyone who wants to test that out and try it out it's an all operators based a deployment of open shift, which is what open ship for is. It's all a slightly new architectural deployment methodology based on the operator framework, and we've been working very diligently. Thio populate operator hub dot io, which is where all of the upstream projects that have operators like the one that Reynolds has created for in the videos GP use are being hosted so that anyone could deploy them, whether on open shift or any kubernetes so that that dropped. And yesterday we dropped um, and announced Open Sourcing Quay as project quay dot io. So there's a lot of Io is going on here, but project dia dot io is, um, it's a fulfillment, really, of a commitment by Red Hat that whenever we do an acquisition and the poor folks have been their acquired by Cora West's and Cora Weston acquired by Red Hat in an IBM there. And so in the interim, they've been diligently working away to make the code available as open source. And that hit last week and, um, to some really interesting and users that are coming up and now looking forward to having them to contribute to that project as well. But I think the operator framework really has been a big thing that we've been really hearing, getting a lot of uptake on. It's been the new pattern for deploying applications or service is on getting things beyond just a basic install of a service on open shift or any kubernetes. And that's really where one of the exciting things yesterday on we were talking, you know, and I were talking about this earlier was that Exxon Mobil sent a data scientist to the open ship Commons, Audrey Resnick, who gave this amazing presentation about Jupiter Hub, deeper notebooks, deploying them and how like open shift and the advent of operators for things like GP use is really helping them enable data scientists to do their work. Because a lot of the stuff that data signs it's do is almost disposable. They'll run an experiment. Maybe they don't get the result they want, and then it just goes away, which is perfect for a kubernetes workload. But there are other things you need, like a Jeep use and work that video has been doing to enable that on open shift has been just really very helpful. And it was It was a great talk, but we were talking about it from the first day. Signs don't want to know anything about what's under the hood. They just want to run their experiments. So, >>you know, let's like to understand how you got involved in the creation of the operator. >>So generally, if we take a step back and look a bit at what we're trying to do is with a I am l and generally like EJ infrastructure and five G. We're seeing a lot of people. They're trying to build and run applications. Whether it's in data Center at the and we're trying to do here with this operator is to bring GPS to enterprise communities. And this is what we're working with. Red Hat. And this is where, for example, things like the op Agrestic A helps us a lot. So what we've built is this video Gee, few operator that space on the upper air sdk where it wants us to multiple phases to in the first space, for example, install all the components that a data scientist were generally a GPU cluster of might want to need. Whether it's the NVIDIA driver, the container runtime, the community's device again feast do is as you go on and build an infrastructure. You want to be able to have the automation that is here and, more importantly, the update part. So being able to update your different components, face three is generally being able to have a life cycle. So as you manage multiple machines, these are going to get into different states. Some of them are gonna fail, being able to get from these bad states to good states. How do you recover from them? It's super helpful. And then last one is monitoring, which is being able to actually given sites dr users. So the upper here is decay has helped us a lot here, just laying out these different state slips. And in a way, it's done the same thing as what we're trying to do for our customers. The different data scientists, which is basically get out of our way and allow us to focus on core business value. So the operator, who basically takes care of things that are pretty cool as an engineer I lost due to your election. But it doesn't really help me to focus on like my core business value. How do I do with the updates, >>you know? Can I step back one second, maybe go up a level? The problem here is that each physical machine has only ah limited number of NVIDIA. GPU is there and you've got a bunch of containers that maybe spawning on different machines. And so they have to figure out, Do I have a GPU? Can I grab one? And if I'm using it, I assume I have to reserve it and other people can't use and then I have to give it up. Is that is that the problem we're solving here? So this is >>a problem that we've worked with communities community so that like the whole resource management, it's something that is integrated almost first class, citizen in communities, being able to advertise the number of deep, use their your cluster and used and then being able to actually run or schedule these containers. The interesting components that were also recently added are, for example, the monitoring being able to see that a specific Jupiter notebook is using this much of GP utilization. So these air supercool like features that have been coming in the past two years in communities and which red hat has been super helpful, at least in these discussions pushing these different features forward so that we see better enterprise support. Yeah, >>I think the thing with with operators and the operator lifecycle management part of it is really trying to get to Day two. So lots of different methodologies, whether it's danceable or python or job or or UH, that's helm or anything else that can get you an insult of a service or an application or something. And in Stan, she ate it. But and the operator and we support all of that with SD case to help people. But what we're trying to do is bridge the to this day to stuff So Thea, you know, to get people to auto pilot, you know, and there's a whole capacity maturity model that if you go to operator hab dot io, you can see different operators are a different stages of the game. So it's been it's been interesting to work with people to see Theo ah ha moment when they realize Oh, I could do this and then I can walk away. And then if that pod that cluster dies, it'll just you know, I love the word automatically, but they, you know, it's really the goal is to help alleviate the hands on part of Day two and get more automation into the service's and applications we deploy >>right and when they when they this is created. Of course it works well with open shift, but it also works for any kubernetes >>correct operator. HAB Daddio. Everything in there runs on any kubernetes, and that's really the goal is to be ableto take stuff in a hybrid cloud model. You want to be able to run it anywhere you want, so we want people to be unable to do it anywhere. >>So if this really should be an enabler for everything that it's Vinny has been doing to be fully cloud native, Yes, >>I think completely arable here is this is a new attack. Of course, this is a bit there's a lot of complexity, and this is where we're working towards is reducing the complexity and making true that people there. Dan did that a scientist air machine learning engineers are able to focus on their core business. >>You watch all of the different service is in the different things that the data scientists are using. They don't I really want to know what's under under the hood. They would like to just open up a Jupiter Hub notebook, have everything there. They need, train their models, have them run. And then after they're done, they're done and it goes away. And hopefully they remember to turn off the Jeep, use in the woods or wherever it is, and they don't keep getting billed for it. But that's the real beauty of it is that they don't have to worry so much anymore about that. And we've got a whole nice life cycle with source to image or us to I. And they could just quickly build on deploy its been, you know, it's near and dear to my heart, the machine learning the eyesight of stuff. It is one of the more interesting, you know, it's the catchy thing, but the work was, but people are really doing it today, and it's been we had 23 weeks ago in San Francisco, we had a whole open ship comments gathering just on a I and ML and you know, it was amazing to hear. I think that's the most redeeming thing or most rewarding thing rather for people who are working on Kubernetes is to have the folks who are doing workloads come and say, Wow, you know, this is what we're doing because we don't get to see that all the time. And it was pretty amazing. And it's been, you know, makes it all worthwhile. So >>Diane Renaud, thank you so much for the update. Congratulations on the launch of the operators and look forward to hearing more in the future. >>All right >>to >>be here >>for John Troy runs to minimum. More coverage here from Q. Khan Club native Khan, 2019. Thanks for watching. Thank you.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back to Mosconi North here in San Francisco. I'm student like co host David Dante. You're watching four days of live wall to wall coverage here at IBM. Think twenty nineteen. Happy to welcome back to the program first time in her new role. And she's also moved back to David, my home area of the Boston Massachusetts F area. Stephanie Sherice, who's now the vice president and general manager of Red Hat Enterprise. Lennox Business Unit. That red hat Stephanie. Thanks so much for joining. >> What's my pleasures to It's great to be back with you both. >> All right, Stephanie, be back. You know, I happen to notice quite a few IBM. Er's obviously know you. We've had you on our program and many of the IBM shows in the past. So tell us, what's it like being back at one of the Big Blue shows? >> No, it's great. It's great. As you know, I somewhat grew up at IBM might. I had seventeen years. I know so many people in the thing you miss most is in the network. So it's been it's a great opportunity to be here. Catch up with old friends, Talked to new colleagues. Great. What brought >> you to Red hat? I mean, like, you say, long career at IBM, and it was obviously prior to the acquisition, so you didn't know that was coming? What was the lore? >> So I'd say a couple of things clearly, as you know, I became a student of the Lenox Space while I was in while I was at I B M in the Power Systems unit. So fascinated for what Lennox has taught the industry about. I always say Lennox Lennox taught the world how development is meant to be done through open source in the innovation of a community. So that was a thrilling aspect for me to join. Also, I think I truly believe in the open hybrid, multi cloud strategy that Red Hat has had actually for years. Now. I think open source is all about choice and flexibility. It's what Lennox provides and moving forward their strategy around having a management portfolio, having a Cooper Netease platform all built upon being able to consume Lennox wherever and however you want it, I believe in the strategy. So it's been really exciting, and having the rail aspect is fantastic. >> So, Stephanie, you're right. You own that. Really? The core of red hats business. You know, Red Hat Enterprise Lennox, You know, we've been covering this space heavily for years, and everything that redheads doing comes back to, you know, that Lennox Colonel and there Ah, lot of people don't really understand that. The business model say it's like, Oh, well, you know, red hat cells free and, oh, that's a service model and things like that bring us inside your business and what's exciting and dynamic and happening in that space. >> It's It's such an incredible time. I couldn't ask for a better job, but I love the linen space for a couple of things. As you look at all the things that are changing in the industry today, I always say to customers, you may not know the applications. You'll run next year in three years, in five years, you may not know where you'll want to run them. What you do know it's they'll run on Lennox, right? It's the fastest growing operating system in the industry today. It's number one choice of developers. So, as you look to see, what can you do to prepare for the innovation Its pick your Lennox and Red hat has done an incredible job of making a consumable. If you look at the hundreds of thousands of packages out there, an open source, you take that you pull it into. Really, I feel what well delivers bread had. Enterprise Lennox delivers is an ecosystem. It's a trusted ecosystem. We test the team does an incredible job of testing a breadth of hardware, everything from, you know, X eighty six systems to power systems. Dizzy, too, you know, in video G, D G X. So way test all of that and then all the way up to the applications. We pull that ecosystem with us now, our goal is to be able to provide that anywhere. So you take that capability whether you do it. Bare metal, virtual machine, public cloud, private cloud. Now you move into containers. You know, everything we do in rail translates overto open shift. Whether you consume it as a private cloud and open stack or containerized in open shift, all of that ecosystem follows through. So it really is. When I look at is the bedrock of the of the entire portfolio for red hat, and we really are at Enterprise software company Today we pull in management with things like answerable and satellite. You pull all that together. Automation of the storage portfolio. It's just such an exciting time. It's a real transition from going from a no s company and building >> upon that. >> I mean truly an enterprise software company from multiple clouds. >> So I was talking about more about that because open shift gets all the buzz. Ostensibly, it was a key linchpin of the acquisition that I being made. Well, What's the connection between between rail and the rest of red hats? Portfolio. Maybe you could connect those dogs. >> That would be so, as you look at, and I'm an infrastructure person for a long time, as you know, and coming from the infrastructure up space, most was purchased from an infrastructure of you for many years. Now. It's all about how you consume the applications and the infrastructure comes in and feeds it from an application. Space containers are amazing, right? They bring that incredible flexibility started. Stop it, move it lifted, shifted Everything. Thing is, from an application perspective, it's simple. From a Lennox perspective, it's actually much more complicated, you know, in the days of bare metal or even V EMS. Quite clean cut between your systems, your operating system. You're hyper visor in your application. Once you move into containerized worlds, you've split up your Lennox. You have user space in your container. You have Cooper netease making ten times the number of calls to the colonel space that the hyper visor ever did. Much more complicated. So as you move into that space of Kou Burnett ease and containers and orchestration, you know, you really want someone who knows Lennox because the clinic space is more complicated, bringing simplicity from a container and application >> performance management, security changes >> Absolutely automation. So really is as we look at the portfolio, we have a You know, we believe strongly in the customer experience, we deploy with rail that trusted ecosystem. In order to be able to take that into a container world, we need to be able to get access into the user space into the coup. Burnett ease and into the colonel because they're so intimately twine entwined. So as we transition that open shift is the way we delivered, we build upon the same rail. Colonel, we used the user space. >> So, Stephanie, like you, I'm an infrastructure person. And, you know, my background is in, you know, the OS. And, you know, down that environment, there's been a wave of, you know, just enough operating system. How do we slice these up? I look of Cora West, which read, Had acquired was originally a We're going to slim down, you know, the colonel and make things easily. Where's the innovation still happening? Lenox And, well, you know why is still Lin It's going to be relevant going forward. You talked about, you know, containers, things like server list all threatened to say, Oh, well, you know, my application development person shouldn't have to think about it. But why is it still important? >> Yeah. So you know whether things I love about my role is with the position that red hat has in the industry with rail. And, you know, we have Ah, we have a approximately fifty thousand set of that fifty thousand customers who use rail and trust us. So as we look at how we drive innovation, I love the ability to kind of help redefine what an operating system is. And you know, certainly we bring added value did in real seven and now we have the relic beta out. So we're continuously adding things. We added in a few things about consumption base. We added app streams which separates out the ability to update your user space at a different rate in pace than your core. A court sort of based level which allows you to do faster updates in your user space. Continue on your core. Run multiple versions of your user space. It's a fantastic way to pull an innovation faster. We've also done a number of things with our capabilities around taking that first step into container ization, including tools like Build a pod man scope EOE so that within the operating system itself you conduced those based kind of capabilities for container ization. That first step. And then when you need orchestration, you can move over to open ship. So there's a ton of innovation left in the operating system. Security is core to everything we do. S o the innovation around security remains a constant were in the typical open source fashion. We've released the Beta here in November. We're gathering great feedback. We have about one hundred and forty high touch beta customers who were working hand in hand with to get feedback. And we're looking forward to bringing rally to market >> What? One of the big pieces of feedback you're getting a lot of people excited about in terms of Really. >> Certainly everyone looks to us for their security. So that's been that's been a great place for us. We had work to do on making it easier to consume as we continue to drive things with developers. And we have a new portal that's allowing sort of a single user space view those kinds of consumption. Things are very important today because, as you said, you want skills to be easily transferrable. Easily updated s o A lot of the consumption based things we've been >> working on, >> um, as well as thie tooling? >> Yeah. You talk about that skill set that's one of the biggest challenges in a multi cloud world is if I'm going to live in all these iron mint, what's the same and what's different communities is only a small piece. But Lennox is, you know something that's transferrable. What are you seeing? What are you hearing from customers in that regard? >> Yeah, I think, and that's one thing. We're working hard to try and make sure that you know, I think like when you when you buy a house, right, you can buy a house. You could buy an apartment building in Pine Office building. What doesn't change is the land underneath. You need that land to be stable, and you know you can build whatever you want on it. And that's how we view our lennox consuming anywhere you want. It's always secure. It's always stable in multiple public clouds. I think really it's the flexibility when I look at that pull open hybrid cloud space, customers aren't looking to buy a product. They're looking to establish a relationship with someone who's going to provide them what they need to do today on their mission critical applications but have the flexibility going forward to take them where they want to go. They may pick Ascent one public cloud today. They want to move it in two years and three years to a different public cloud. It's establishing that relationship to be able to consume that Lennox, preserve those skills but have the flexibility. And tomorrow >> Red has made a number of storage acquisitions recently. Obviously, the tight relationship between the operating system and the I O how do you look at that space? The opportunity, You know, the TAM talk a little bit about the storage moments >> we have so clearly we have our storage division. We've been working very closely with them to build up capabilities. Largely, you'll see it with open shift. The container ization and storage management within containers is tricky business. So as we pulled together the collaboration between our storage unit as well as our container unit, that's providing real capabilities for that ease of consumption. How do you bring the storage with the container deploys. My team has worked very closely with the management team as you pull in the management aspect with things like automation and management satellite capabilities, answerable is an amazing tool. Amazing tool. In fact, we've pulled in things like system rolls directly into the operating system so that you can set up things like networking. You. Khun, set up storage with answerable playbooks in a much simpler way. That's allowing us to get that ease of consumption. It is about, you know, David's fully about being able for us Tow leverage the portfolio. How do we allow clients to take the journey using Lennox from everything from bare metal and VM out to container ization, Pull in multiple clouds, get the storage features and functions and get the automation and management. >> So, Stephanie, you would looked at and partnered with Red had quite a bit before you had joined the company. What surprised you coming inside the company? Is there anything but being on the inside now that you look back here like, Wow, I didn't expect that or was different than what I had seen from the outside. >> You know, I think what I think, what I love and surprise me a bit was the passion of open source. You know, you look at any company from the outside and and certainly as a student from the outside, you look at the business and how the business is doing and how it's growing in his study. All of that, Well, you don't get to see from the outside is the open source passion of the developers who I get to work with every day. I mean, they just they understand the market. They do it as a hobby on the weekends. It's it's It's just unbelievable, right? I love being I'm up in Westford is, you know, with all the developers, it's great. >> So I'm gonna ask you a lot of talk about the culture, you know, between Red Hat and IBM. You you've been in both camps. Now what do you thoughts in the culture >> s O? You know, I think when I look at the culture, I love the culture at Red Hat. As you know, I've been in many places at IBM and multiple divisions and multiple units. There's a lot of autonomy between the business units at IBM from my own experience. And there's so many people I miss working with colleagues at IBM that, you know I worked in and head with, and WeII brought amazing things to mark it. So I look forward to working with them again. You know, I always look for those groups that are passionate, and there's a lot of passionate IBM is I miss working with. So I look forward to bringing that back >> seventy one to give you the final word. We know. You know Jim Whitehurst has got a president and he's doing later today. I believe Red Hat has a has a good presence there, tells Red Hat here it think. What should be people be looking >> for? Yeah, I think so. Clearly, there's a lot of buzz and excitement about what both Red Hat and IBM Khun do together for the open hybrid cloud. I come at it now from a full Lennox perspective, and I couldn't be more excited about what Lennox is going to deliver for innovation and for customers to consume an innovation as we pull in and look, look to all these discussion that will happen with Jim and Jeannie on stage today, it's it's great. We'll be able to take what Red Hat has done and scale it now with the help of IBM, so very excited about the future. All right, >> Well, Stephanie, we really appreciate your sharing. Congratulations. You're going >> to see about thanks for the time. >> So we still have, you know, about three more days left here at IBM Thinking, of course, the Cube will be at Red Hat Summit twenty nineteen, which is back in Boston, Massachusetts, for Dave A lotta arms to minimum. Thanks for watching the cue

>> No. Yeah. Wait. >> Hi, everyone, and welcome to the big data. Deep Dive with the Cube on AMC TV. I'm Richard Schlessinger, and I'm here with tech industry entrepreneur and wicked bond analyst Dave Volonte and Silicon Angle CEO and editor in chief John Furrier. For this last segment in our show, we're talking about the future of big data and there aren't two better guys to talk about that you and glad that you guys were here. Let me sort of tee up the this conversation a little bit with a video that we did. Because the results of big data leveraging are only as good as the data itself. There has to be trust that the data is true and accurate and as unbiased as possible. So AMC TV addressed that issue, and we're just trying to sort of keep the dialogue going with this spot. >> We live in a world that is in a constant state of transformation, political natural transformation that has many faces, many consequences. A world overflowing with information with the potential to improve the lives of millions with prospects of nations with generations in the balance way are awakening to the power of big data way trust and together transform our future. >> So, Gentlemen Trust, without that, where are we and how big of an issue is that in the world of big data? Well, you know, the old saying garbage in garbage out in the old days, the single version of the truth was what you were after with data warehousing. And people say that we're further away from a single version of the truth. Now with all this data. But the reality is with big data and these new algorithms you, khun algorithmic Lee, weed out the false positives, get rid of the bad data and mathematically get to the good data a lot faster than you could before. Without a lot of processes around it. The machines can do it for you. So, John, while we were watching that video, you murmured something about how this is the biggest issue. This is cutting edge stuff. This is what I mean. >> Trust, trust issues and trust the trust equation. Right now it is still unknown. It's evolving fast. You see it with social networks, Stevens go viral on the internet and and we live in a system now with mobility and cloud things. Air scaling infinitely, you know, these days and so good day two scales, big and bad data scales being so whether it's a rumor on you here and this is viral or the data data, trust is the most important issue, and sometimes big data can be creepy. So a. This really, really important area. People are watching it on DH. Trust is the most important thing. >> But, you know, you have to earn trust, and we're still sort of at the beginning of this thing. So what has to happen to make sure that you know you don't get the garbage in, so you get the garbage. >> It's iterative and and we're seeing a lot of pilot projects. And then those pilot projects get reworked, and then they spawn into new projects. And so it's an evolution. And as I've said many, many times, it's very early we've talked about, were just barely scratching the surface here. >> It's evolving, too, and the nature of the data is needs to be questioned as well. So what kind of data? For instance, if you don't authorize your data to be viewed, there's all kinds of technical issues around. >> That's one side of it, But the other side of it, I mean, they're bad people out there who would try to influence, Uh, you know what? Whatever conclusions were being drawn by big data programs, >> especially when you think about big data sources. So companies start with their internal data, and they know that pretty well. They know where the warts are. They know how to manipulate. It's when they start bringing in outside data that this gets a lot fuzzier. >> Yeah, it's a problem. And security talk to a guy not long ago who thought that big data could be used to protect big data, that you could use big data techniques to detect anomalies in data that's coming into the system, which is poetic if nothing else, that guys think data has told me that that that's totally happened. It's a good solution. I want to move on because way really want to talk about how this stuff is going to be used. Assuming that these trust issues can be solved on and you know, the best minds in the world are working on this issue to try to figure out how to best, you know, leverage the data, we all produce, which has been measured at five exabytes every two days. You know, somebody made an analogy with, like something. If a bite was a paper clip and you stretched five exabytes worth of paper clips, they would go to the moon or whatever. Anyway, it's a lot of bike. It's a lot of actually, I think that's a lot of fun and back way too many times one hundred thousand times I lost track of my paper. But anyway, the best minds are trying to figure out, you know, howto, you know, maximize that the value that data. And they're doing that not far from here where we sit. Uh, Emmett in a place called C Sale, which was just recently set up, See Sail stands for the computer signs, an artificial intelligence lab. So we went there not long ago. It's just, you know, down the Mass. Pike was an easy trip, and this is what we found. It's fascinating >> Everybody's obviously talking about big data all the time, and you hear it gets used to mean all different types of things. So he thinks we're trying to do in the big data. Is he? Still program is to understand what are the different types of big data that exists in the world? And how do we help people to understand what different problems or fall under the the overall umbrella of big data? She sells the largest interdepartmental laboratory and mitt, so there's about one hundred principal investigators. So that's faculty and sort of senior research scientists. About nine hundred students who are involved, >> basically with big data, almost anything to do with it has to be in a much larger scale than we're used to, and the way it changes that equation is you have to You have to have the hardware and software to do the things you're used to doing. You have to meet them of comedy's a larger size a much larger size >> of times. When people talk about big data, they, I mean, not so much the volume of the data, but that the data, for example, is too complex for their existing data. Processing system to be able to deal with it. So it's I've got information from Social network from Twitter. I've got your information from a person's mobile phone. Maybe I've got information about retail records. Transactions hole Very diverse set of things that need to be combined together. What this clear? It says this is If you added this, credit it to your query, you would remove the dots that you selected. That's part of what we're trying to do here. And big data is he sail on. Our big data effort in general at MIT is toe build a set of software tools that allow people to take all these different data sets, combine them together, asked questions and run algorithms on top of them that allowed him to extracting sight. >> I'm working with it was dragged by NASA, but the purpose of my work right now is Tio Tio. Take data sets within Davis's, and instead of carrying them for table results, you query them, get visualizations. So instead of looking at large sets of numbers and text him or not, you get a picture and gave the motivation Behind that is that humans are really good into pretty pictures. They're not so that interpreting huge tables with big data, that's a really big issue. So this will have scientists tio visualize their data sets more quickly so they can start exploring And, uh, just looking at it faster, because with big data, it's a challenge to be able to visualize an exploiter data. >> I'm here just to proclaim what you already know, which is that the hour of big data has arrived in Massachusetts, and >> it's a very, very exciting time. So Governor Patrick was here just a few weeks ago to announce the Mass Big Data Initiative. And really, I think what he recognizes and is partly what we recognize here is that there's a expertise in the state of Massachusetts in areas that are related to big data, partly because of companies like AMC, as well as a number of other companies in this sort of database analytic space, CMC is a partner in our big data detail, initiatives and big data and See Sale is industry focused initiative that brings companies together to work with Emmet T. Think about it. Big data problems help to understand what big data means for the companies and also to allow the companies to give feedback. Tow us about one of the most important problems for them to be working on and potentially expose our students and give access to these companies to our students. >> I think the future will tell us, and that's hard to say right now, because way haven't done a lot of thinking, and I was interpreting and Big Data Way haven't reached our potential yet, and I just there's just so many things that we can't see right now. >> So one of the things that people tell us that are involved in big data is they have trouble finding the skill sets the data. Science can pick capability and capacity. And so seeing videos like this one of them, it is a new breed of students coming out there. They're growing up in this big data world, and that's critical to keep the big data pipeline flowing. And Jon, you and I have spent a lot of time in the East Coast looking at some of the big data cos it's almost a renaissance for Massachusetts in Cambridge and very exciting to see. Obviously, there's a lot going on the West Coast as well. Yeah, I mean, I'll say, I'm impressed with Emmett and around M I. T. In Cambridge is exploding with young, young new guns coming out of there. The new rock stars, if you will. But in California we're headquartered in Palo Alto. You know we in a chance that we go up close to Google Facebook and Jeff Hammer backer, who will show a video in a second that I interview with him and had dupe some. But he was the first guy a date at Facebook to build the data platform, which now has completely changed Facebook and made it what it is. He's also the co founder of Cloudera The Leader and Had Duke, which we've talked about, and he's the poster child, in my opinion of a data scientist. He's a math geek, but he understands the world problems. It's not just a tech thing. It's a bigger picture. I think that's key. I mean, he knows. He knows that you have to apply this stuff so and the passion that he has. This video from Jeff Hammer Bacher, cofounder of Cloud Ear, Watches Video. But and then the thing walk away is that big data is for everyone, and it's about having the passion. >> Wait. Wait. >> Palmer Bacher Data scientists from Cloudera Cofounder Hacking data Twitter handle Welcome to the Cube. >> Thank you. >> So you're known in the industry? I'LL see. Everyone knows you on Twitter. Young Cora heavily follow you there at Facebook. You built the data platform for Facebook. One of the guys mean guys. They're hacking the data over Facebook. Look what happened, right? I mean, the tsunami that Facebook has this amazing co founder Cloudera. You saw the vision on Rommedahl always quotes on the Cube. We've seen the future. No one knows it yet. That was a year and a half ago. Now everyone knows it. So do you feel about that? Is the co founder Cloudera forty million thousand? Funding validation again? More validation. How do you feel? >> Yeah, sure, it's exciting. I think of you as data volumes have grown and as the complexity of data that is collected, collected and analyzed as increase your novel software architectures have emerged on. I think what I'm most excited about is the fact that that software is open source and we're playing a key role in driving where that software is going. And, you know, I think what I'm most excited about. On top of that is the commodification of that software. You know, I'm tired of talking about the container in which you put your data. I think a lot of the creativity is happening in the data collection integration on preparation stage. Esso, I think. You know, there was ah tremendous focus over the past several decades on the modeling aspect of data way really increase the sophistication of our understanding, you know, classification and regression and optimization. And all off the hard court model and it gets done. And now we're seeing Okay, we've got these great tools to use at the end of the pipe. Eso Now, how do we get more data pushed through those those modeling algorithm? So there's a lot of innovative work. So we're thinking at the time how you make money at this or did you just say, Well, let's just go solve the problem and good things will happen. It was it was a lot more the ladder. You know, I didn't leave Facebook to start a company. I just left Facebook because I was ready to do something new. And I knew this was a huge movement and I felt that, you know, it was very gnashing and unfinished a software infrastructure. So when the opportunity Cloudera came along, I really jumped on it. And I've been absolutely blown away by the commercial success we've had s o. I didn't I certainly didn't set out with a master plan about how to extract value from this. My master plan has always been to really drive her duped into the background of enterprise infrastructure. I really wanted to be as obvious of a choice as Lennox and you See you, you're We've talked a lot at this conference and others about, you know, do moving from with fringe to the mainstream commercial enterprises. And all those guys are looking at night J. P. Morgan Chase. Today we're building competitive advantage. We're saving money, those guys, to have a master plan to make money. Does that change the dynamic of what you do on a day to day basis, or is that really exciting to you? Is an entrepreneur? Oh, yeah, for sure. It's exciting. And what we're trying to do is facilitate their master plan, right? Like we wanted way. Want to identify the commonalities and everyone's master plan and then commoditize it so they can avoid the undifferentiated heavy lifting that Jeff Bezos points out. You know where you know? No one should be required, Teo to invest tremendous amounts of money in their container anymore, right? They should really be identifying novel data sources, new algorithms to manipulate that data, the smartest people for using that data. And that's where they should be building their competitive advantage on. We really feel that, you know, we know where the market's going on. We're very confident, our product strategy. And I think over the next few years, you know, you guys are gonna be pretty excited about the stuff we're building, because I know that I'm personally very excited. And yet we're very excited about the competition because number one more people building open source software has never made me angry. >> Yeah, so So, you know, that's kind of market place. So, you know, we're talking about data science building and data science teams. So first tell us Gerald feeling today to science about that. What you're doing that, Todd here, around data science on your team and your goals. And what is a data scientist? I mean, this is not, You know, it's a D B A for her. Do you know what you know, sheriff? Sure. So what's going on? >> Yeah, So, you know, to kind of reflect on the genesis of the term. You know, when we were building out the data team at Facebook, we kind of two classes of analysts. We had data analysts who are more traditional business intelligence. You know, building can reports, performing data, retrieval, queries, doing, you know, lightweight analytics. And then we had research scientists who are often phds and things like sociology or economics or psychology. And they were doing much more of the deep dive, longitudinal, complex modeling exercises. And I really wanted to combine those two things I didn't want to have. Those two folks be separate in the same way that we combined engineering and operations on our date infrastructure group. So I literally just took data analyst and research scientists and put them together and called it data scientist s O. So that's kind of the the origin of the title on then how that's translating what we do at Clyde era. So I've recently hired to folks into a a burgeoning data science group Cloudera. So the way we see the market evolving is that you know the infrastructure is going to be commoditized. Yes, mindset >> to really be a data scientists, and you know what is way should be thinking about it. And there's no real manual. Most people aboard that math skills, economic kinds of disciplines you mentioned. What should someone prepared themselves? How did they? How does someone wanna hire data scientist had, I think form? Yeah, kinds of things. >> Well, I tend to, you know, I played a lot of sports growing up, and there's this phrase of being a gym rat, which is someone who's always in the gym just practicing. Whatever support is that they love. And I find that most data scientists or sort of data rats, they're always there, always going out for having any data. So you're there's a genuine curiosity about seeing what's happening and data that you really can't teach. But in terms of the skills that are required, I didn't really find anyone background to be perfect. Eso actually put together a course at University California, Berkeley, and taught it this spring called Introduction to Data Science, and I'm teaching and teaching it again this coming spring, and they're actually gonna put it into the core curriculum. Uh, in the fall of next year for computer science. >> Right, Jack Harmer. Bakar. Thanks so much for that insight. Great epic talk here on the Cube. Another another epic conversations share with the world Live. Congratulations on the funding. Another forty months. It's great validation. Been congratulations for essentially being part of data science and finding that whole movement Facebook. And and now, with Amaar Awadallah and the team that cloud there, you contend a great job. So congratulations present on all the competition keeping you keeping a fast capitalism, right? Right. Thank >> you. But it's >> okay. It's great, isn't it? That with all these great minds working in this industry, they still can't. We're so early in this that they still can't really define what a data scientist is. Well, what does talk about an industry and its infancy? That's what's so exciting. Everyone has a different definition of what it is, and that that what that means is is that it's everyone I think. Data science represents the new everybody. It could be a housewife. It could be a homemaker to on eighth grader. It doesn't matter if you see an insight and you see something that could be solved. Date is out there, and I think that's the future. And Jeff Hamel could talked about spending all this time and technology with undifferentiated heavy lifting. And I'm excited that we are moving beyond that into essentially the human part of Big Data. And it's going to have a huge impact, as we talked about before on the productivity of organizations and potentially productivity of lives. I mean, look at what we've talked about this this afternoon. We've talked about predicting volcanoes. We've talked about, you know, the medical issues. We've talked about pretty much every aspect of life, and I guess that's really the message of this industry now is that the folks who were managing big data are looking too change pretty much every aspect of life. This is the biggest inflexion point in history of technology that I've ever seen in the sense that it truly affects everything and the data that's generated in the data that machine's generate the data that humans generate, data that forest generate things like everything is generating data. So this's a time where we can actually instrument it. So this is why this massive disruption, this area and disruption We should say the uninitiated is a good thing in this business. Well, creation, entrepreneurship, copies of being found it It's got a great opportunity. Well, I appreciate your time, I unfortunately I think that's going to wrap it up for our big date. A deep dive. John and Dave the Cube guys have been great. I really appreciate you showing up here and, you know, just lending your insights and expertise and all that on DH. I want to thank you the audience for joining us. So you should stay tuned for the ongoing conversation on the Cube and to emcee TV to be informed, inspired and hopefully engaged. I'm Richard Schlessinger. Thank you very much for joining us.

>>Ed, welcome to the Cube. All right, Thanks guys. Good >>To see you. Thanks. Good to see you as well, >>John. Okay. Ed runs Biz dev for Cloudera, Industry veteran, worked at VMware. Ed, gotten to know you the past year. You guys have been doing great. What a difference one year makes, right? I mean, absolutely. Tell us, just let's start it off with what's happened in a year. I mean, you know, here at Hadoop World Cloudera, the ecosystem. Just give us your view of your perspective of what a difference one year makes. >>I think more than double is probably the, the fastest answer I could give you, which is, I mean, even looking around at the conference, it's, it itself is literally double from what it was last year. But in terms of the number of partners that have entered the market and really decided to work with, with Cloudera, but also in general, just the, the, the, the scope and size of the ecosystem itself, investors from every angle. You've got companies really well-branded marquee companies like Oracle coming into the mix and saying, Hey, Hadoop is the, is the real deal and we need to invest here. Marquee companies like IBM and EMC also doing the same. And of course, you know, as a result, you know, lots and lots of customer interest in the technology. And Cloudera's been fortunate to have been in the market early and really made the right investments with the right team. And so we're able to serve a lot of those customer needs. So it's been really, it's been a fantastic year for the company. >>So we had a great day yesterday with Cloudera. We had Kirk on, we had AER on twice, who by the way went viral with his modern warfare review, but we had Jeff Harmar Baer on, so we had pretty much the brain trust, Mike and Michaelson. Yep. The brain trust, the Cloudera. So we talked about the risk factors for Cloudera. Obviously you guys are number one, you've been kind of had untouchable lead and then all of a sudden boom competition. So Mike talked about that. So the strategy and the product side, they addressed, you're on the, the biz dev side, so you know, when you were number one, everyone wants to stand next to you and your phone rings off the hook from tier one partners all the way down to anyone's just getting in the business. Who wants a big data strategy on the execution. Now, what are you guys doing right now to, to continue your lead on the, on the sales marketing biz dev? I mean, I know you get the partner program, but what's your strategy for Phil, how to continue >>In that lead? The, the beautiful thing is honestly, our strategy hasn't changed at all. And I know that might sound counterintuitive, but we started off with a, a really crisp vision. And we want, what we wanna do is create a very attractive platform for partners. And, and, you know, one of the core, you know, sort of corporate strategy, Edix for Quadera is a recognition that the end of the day, the platform itself, Hado is an input into a solution. And Quadra is not likely to deliver the complete solution to market. Instead, it's going to be companies like Dell, for example, or it's going to be companies on the, on the ISV side like Informatica, which you're gonna deliver not only a base platform, but also the, the, the, the BI or analytics or data integration technologies on top. And as a result, what we've done is we've really focused in on creating a very attractive platform to vendors to build on. >>And one of the, I think one of the biggest misconceptions that I'm excited about that, you know, we are now having an opportunity to correct and that's a result, frankly, of the additional competitive dynamic. And I think the, the Wiki bond team pointed that out rather pointedly in their most recent articles. But is, is the sort of the lack of understanding around what CDH is and also the, some of the other investments that we're making to create a truly attractive platform for vendors to build on. And you know, I mean, I think you, you may have familiarity with exactly what CDH is, but for the sake of the audience here, what I'd like to do is say, say, first off, you know, first and foremost this is a hundred percent free in Apache license open source. But more importantly, it is everything that we build on the platform, meaning it's completely full featured. >>We put all of that out in the open. There's no turbo version of Hadoop that we've got hiding in the closet for our, our four pay customers. We're absolutely making investment. But I think, you know, when you think about it from the vendor perspective, and that's my bias. So I always think about, I treat all of the potential partners as really my customer. And when you think about it from that perspective, the things that matter most to vendors, number one, transparency. They need to understand exactly what our business model is, where we plan to make money and where we plan, don't make money. They need to know what we're really good at developing and what we're not so good at developing. And sort of where we draw the, the boundaries around that investment. I think, you know, a testament to that, for example, is tomorrow we're hosting a partner summit. >>So after this event, there are gonna be over 60 individuals, but they max two per per vendor. So we're gonna have over 35 vendors attending this event. And what they're gonna hear from is our entire management team is as deeply as we can and as open as we can. And you know, it, it's, it's, it's funny, you know, I think I saw this article in Forbes the other day about Cloudera. It was this, the title of the article was something like Spies Like Us. And it it, and it, what it highlighted was that some, some competitor of Cloudera had actually hired a, a, a competitive intelligence agency to go on and, and try to engage with, you know, and, and try to learn more about Cloudera. And so they went on to Cora, which we have a lot of active engineers on Cora. And they, you know, they went out and they asked a bunch of product related questions to our to, to someone on Cora. And our engineers immediately responded and they started being very transparent, completely open to what, what they're building and why they're building it. And the article basically summarized to say, Hey, you know what, you know, clearly some people aren't all that sophisticated in figuring out, you know, who they're talking to. And it's really important to do that. And they got the absolute wrong conclusion. Our engineers are actually encouraged and in fact rewarded for being extremely transparent in the market because we believe that it's transparency will ultimately allow us to be that platform vendor. >>And that's what attracts me. Jeff Hummer Bucker, who's active on core as well, he's recruiting there too. So you guys are out engaging the community. Yeah. So just let me just review, cuz this is cool that you're addressing this because Hortonworks and others, and I'll say the name Hortonworks has been pumping up the PR and creating a lot of noise around open and kind of Depositioning Cloudera. So you guys are completely open, a hundred percent Hadoop, open source, everything you build in, in every way, in every way. You have engineers building core, you've got tools and all the other stuff is being built in Cloudera then contributing into the community. >>Actually it's the other way around. We build it and the community@apache.org. So all of our technology is built@apache.org. It's, it's developed there. It's, it's, it's initially shared there. And then we have another team inside our company that pulls down bits from apache.org and then assembles them and integrates them. So it's really, it's a really key thing. And there's no, we do, we have no bits that we don't develop@apache.org that are part of cdh. So there, I mean there can be no mistake that everything that that is in CDH is everything we got. >>So CDH is free. >>It is free >>And every it's open source. It's open you >>Charge enterprise edition. That's the only thing that's different you guys charge >>Yeah. Which is your management console, right. >>Management >>Suite and all kinds of >>The tools. And that's not free and that's not open source. That's correct. Just to be clear. Yep. But so AER took us yesterday through, I don't know, half a dozen probably open source projects and then the one is the, the management console. And that's what you charge for, that's where you're gonna make money? >>Yeah. We, we manufacture, essentially we manufacture two products, but we sell one. So we manufacture the Quadera distribution, including Apache Duke, that's free. It's free. And then we all in open source and built it Apache and, and really heavily tested and well documented and, and, and well integrated. And then we also manufacture quadera Enterprise, which includes support and indemnities and warranties for that full featured CDH product and also includes the Quadra management suite. And >>That's a subscription. >>And that's a subscription. And so customers can, can run cdh, they can then buy and license Cloudera Enterprise and then someday if they decide they don't need Cloud Air Enterprise for whatever reason, if they're, if their team are scripting wizards and they've decided that they, you know, they don't need the extra opportunity for being able to track all of the things that Cloudier Enterprise allows 'em to, they can step off of cloud enterprise and continue to use full feature to do as they see >>Fit. So take an example of one of your partners that you announced this week. NetApp NetApp's gonna package your cdh CDH and the subscription Correct. To their, their customers. And then they're gonna let their channel either, you know, they'll pre bule it or do a reference architecture, you'll get paid for that subscription that's bundled. That's correct. Will make money off of its filers. Yes. And the customer gets a package solution. >>Exactly. Right. And in fact, that's another important thing that you know, is probably worth discussing, which is our go to market model. I don't know if you guys had a chance to talk with anyone yesterday on that, but I'm responsible for our channel strategy and one of the key things that we've agreed to as a, as a company is that we really are gonna go to market through channel partners. Yeah. >>We covered sgi, that was a great announcement. >>Yep, a >>Hundred percent >>As, as close as we can get. Okay. I mean that is our, he's >>Still doing the direct deals. You still have that belly to belly sales force because it's still early, right? So there's a mix of direct and indirects, not a pure >>Indirect, but as, and that's only, that's only as we're able to, until we're able to ramp up our partners fully, in which case we really want our, the current team that is working belly to belly to really support our partners. >>So all so VMware like, but I I wanted to ask >>You VMware, like NetApp, like very similar. >>Yes. Very, very NetApp. Like NetApp probably 75%, you know. Exactly. What are the similarities and differences with VMware in, in the ecosystem? You know it well, >>I do know it well. Yeah. I spent several years working at VMware and you know, I think, I mean the first and most obvious difference is that when you think, when I think about platform software in general, you know, there are a few different flavors of platform. One of the things that makes Hadoop very unique, very unique relative to other platforms is that it, not only is it Apache license, but it really is, it's dependent upon other external innovators to, to create the entire full value of the ecosystem. So, or, or you know, of the solution, right? So unlike for example, so like, let's take a platform like everyone's familiar with like Apple iTunes, right? What happens is Apple creates the platform and they put it kind of in the middle on top of and behind the scenes is the innovator, the app builder, he builds it, he publishes it on Apple, and then Apple controls all access to the >>Customer. Yep. >>That's not adu, right? Right. Let's take VMware or Red Hat for example. So in that case, they publish a platform they own and control the, the absolute structure and boundaries of what that platform is. And then on top of that application vendors build and then they deliver to the, the customer. But you know, at the end of the day, the, you know, the relationship really is, you know, from that external innovator straight down, and there's no, there's, you know, there's no way for them to really modify the platform. And you take kadu, which is a hundred percent Apache licensed to open source, and you really, you really open up the opportunity for vendors to take ADU as an input into their system and then deliver it straight to their customers or for customers themselves to say, I want straight up vanilla Hadoop, I'm gonna go this way and I'm gonna add on my own be app of applications. So you're, we're seeing all sorts of variants right now in the market. We're seeing software as a service being delivered that's based on Hadoop. There was a great announcement a few weeks ago from a company named Tidemark, previously known as Per Ferry, and they're taking all of cdh. They're, but they're, the customer doesn't know that they're, and what they're doing is they're delivering software as a, as a service based on adu. >>Yeah. So I mean, you know, we are psyched that you're clearing this up because obviously we're seeing, we saw all that stuff, but I really think that indirect strategy as a home run, I'm said it when we talked about the SGI thing, and it's accelerates you guys, you enable, but you know, channels is an interesting business. I mean the, you have to have pure transparency as you mentioned, but they need comp, people need confidence and, and they don't, they worry about competition. So channel conflict is always the big issue, right? Right. Is Cloudera gonna compete with us? So talk that, talk us through that, that strategy. So obviously the market's growing, new solutions are coming around the corner, These guys wanna make money. I mean channel, it's all about, you know, what have you done for me today? >>Right. That, that is exactly right. And you know what, that's, that's why we decided on the channel strategy specifically around our product is because we recognize that each and every single potential channel partner of ours can actually innovate themselves on top of and create differentiation. And we're not an obstacle to that process. So we provide our platform as an input and we're capable of managing that platform, but ultimately creating differentiation is all in the hands of our partners and we're there to help, but it gives them wide latitudes. So take for example, the differences between Dell and NetApp solution, they are very different reference architectures leveraging the exact same platform. >>Yeah. And they have to make money. I mean, the money making side of it is, you know, people have kind of, don't really talk about that, but, you know, channel partners loyalty is all about who can help them make cash. Right. Right. Exactly. What are you hearing there in terms of the ecosystem? Has the channels Bess and the partnerships or the more as size, what's the profile of your, of your partners? I mean, can you give us the breakdown of Sure. We have what you look like from Dell. We know Dell and NetApp, but they're gear guys. But, >>So a big part of our strategy is to work with IHVs and then Ihv resellers. So you're talking about companies like Dell, like sgi, like NetApp, for example, independent hardware manufacturers. Another part of our strategy though, and a key, a key requirement from our customers is to work with a whole variety of ISVs, particularly in the data management space. So you've got really marquee companies in the database space like IBM's Netezza or Terradata. You've got in companies like Informatica and Talent, you've got companies on the BI side, like Micro Strategy and Tableau. These kinds of technologies are currently in play at our customers that have made substantial investments. And ultimately they want to be able to continue to leverage them with the data platform, whichever data platform that they end up choosing. So we invest considerably there. A big part of that has been our Qera Connect partner program. >>It's an opportunity for us to help the customer to understand which technologies work and work well with, with our platform. It's also an opportunity for us to engage directly and assist the vendor. So one of the things that we created as part of that program is first off, immediate and absolute discounted access to any part of our training. Second, lots of free information, access to our world class knowledge base, access to our support team, direct access to our support team. The, the vendors also get access to a developer portal that would created specifically for them. So if, if you think about it this way, Hadoop gets built@apache.org, but solutions don't get built@apache.org. Right? So what we're really trying to help our vendors do is be able to develop their solutions by having real clear visibility to the API level points of Hadoop. They're not necessarily interested in, in trying to figure out how, how MR two works or, or contributing code to that. >>But they absolutely are interested in figuring out how to run and execute their software on top of a do. So when I think about the things that matter to create an attractive platform, and at the end of the day, that's what we're really trying to do, first and foremost is transparency, right? Second really ultimately is really clear visibility to the APIs and the documentation of that platform so that there's no ambiguity that the, the vendor, this is the user in this case, it's building a solution, can absolutely absorb all of that content really cleanly. And then ultimately, you know, I think it's customers, right? Users of the technology. And I think our download numbers are, they're, they're, there's something we're proud of. >>We, we are, we're hearing good feedback. I mean, the feedback we hear from folks is, yeah, I love how they take away the complexity of handling versions and whatnot. So, you know, I think totally is a great way, The CDH is a great bundle. You know, the questions that we have for you is what are you hearing about the other products, the ones you're actually selling? Does that create the lock in? So that's something that we asked Elmer directly, you know, is that the, is that the lock in and what happens when the deployments get so big? You know, >>I mean, the way, I >>Don't really see an issue there, but that's what people are afraid of. I mean, that's kind of the, it's more of fear. I mean, some people can use that fear and, and >>Play against. I think, I think what we've seen in other markets is that management tools are ultimately interchangeable. And the only way that we're gonna retain a customer is by out innovating the competition on the management side, the lock in, the lock in component, as you will, is not really part of our business model. It's very difficult to achieve with an Apache licensed platform and a management suite that sits on outside of that, that licensed artifact. So ultimately, if we don't owe innovate, we're gonna lose. So we're working on the innovation and that's, >>How's the hiring go? Oh, go ahead. >>I, I had a, I wanted to come back to that. You mentioned download numbers. Can you share the numbers >>With the others? I can't, I can't share them publicly, but what I can say is that they've been on an incredible trajectory. Okay. That, and what we've seen is month to month growth rates, every single month we continue to see really significant growth rates. >>And then I, I had a follow up question on, you talked about the, the partner program. How do you manage all those partners? How do you prioritize them? I mean, the, the hardware vendors, it's pretty easy. There's a few big whales, but the, the ISVs, they're, I mean, your phone, like John said, must be ringing off the hook. How do you juggle that and, and can you do it better than VMware, for example? >>Well, we do it, we handle the, the influx of partner interest in two ways. One, we've been relatively structured with the Quadra Connect partner program, and we make real investments there. So we have dedicated folks that are there to help. We have our engineering team that is actually feeding inputs, and we're, we're leveraging some of the same resources that we provide to our customers and feeding those directly to our partners as well. So that's one way that we handle it. But the other way, frankly, is, I mean, customers help here having access to and, and a real customer population, they help you set priorities pretty quickly. And so we're able to understand what we track in inside of our systems, which, which technologies our customers use. So we know, for example, what percentage of our customer base has has SaaS installed, and we'd like to use that with a, do we know which percentage of our customer base is currently running on Red Hat and which is not. So having core visibility, that helps us to prioritize. >>How about incentives? I mean, obviously channel businesses as, like I said, very fickle people, you know, you know the channel business, I spent, you know, almost a decade in, in HP's channel organization and you know, you have to provide soft dollars. There's a lot of kind of blocking and tackling. You guys are clearly building out that tier one with the SGIs of the world and other vendors, and then get the partner connect program for kinda everyone else who's gonna grow up into a tier one. Yeah. Training, soft dollars incentives. You guys have that going yet, or is the >>Roadmap? We do. And in fact, you know, in addition to the sort of more wide publicized relationships you see with companies like Dell and Cloudera, we're actually building a very successful network of independent ours. And the VAs in general. What we do is we prioritize and select ours based on the top level relationships that we have, because that really helps them to hone in. They've got validation from, for, for example, someone that sells resells. SGI is an organization that now is heard really loud and clear from sgi the, the specific platform configurations that they're gonna represent to their customers, and they ultimately wanna represent them directly. And how we make investments is we're, I mean, the investments we're making ultimately in our sales org, I'm gonna lose the word direct from that conversation because our sales org is being built to help our partners succeed. And I think that's where you're, >>The end game is to go completely indirect and have all your support go into managing that channel. What, what's the mix of revenue generation from your partners? Obviously as a, you know, with sgi they have pre-built channels that you're funneling in, you got NetApp and they're wrapping their products and services around it. How much is services and how much is a solution specifically? Do you have any visibility or a feel for that at this >>Point? I mean, services relative to, You mean for Cloudera particularly, or for our >>Partner? No, for the, for the part. I mean, if I'm a partner, I'm like, Hey, okay, I'm gonna use cdh. I'm on bundles. I don't mind paying you a wholesale if I'm gonna be able to throw off more cash on, you know, deployment and cloud and services, et cetera. And or if I'm a product manufacturer, a product, a solution I fund you in. I need to have that step >>Up a absolutely great question. So depending upon the partner we're dealing with, they like to either monetize or generate their revenue in different ways. So for example, NetApp, NetApp is a company that has very limited services, and their, their focus is a business is really on delivering hardware and software configured together. And they, they rely heavily on a services channel to fulfill, you take in, in contrast to a company like, for example, Dell, which has a very successful services business and really is excited about having service offerings around Hadoop. So it depends upon the company. But when we talk about our VAR channel in particular, one of the things that's a, in an internal acronym, but I'll share it publicly here. We, we call our, our supervisors and what makes them super and why, why we've selected the, the, the organizations that we are selecting right now to be our bar is that they not only can fulfill orders for hardware and software, particularly data management or infrastructure software, but they also have a services team on hand because we recognize that there is a services opportunity with every Hadoop deployment. And we want our partners to have that. So as an organization, we're structuring our, our services staff to facilitate and enable our partners not to be sold >>Directly. Okay. So that's the follow up that I had tomorrow when the partners ask, Okay, what do you want to be when you're really growing up? Is it services, is it software? >>Is it Carter is a software company, Crewing through, >>Oh, er we kind of got ett, well, he didn't say it, but we said it's a operating system. Yeah. >>So given that, so given that, I mean, you can make money on services, right? People need services. Okay, great. >>And partners will make that money for >>Us. And, and you know, early on you, you had to do some of that and you're, you've been very clear about where it's going. It's hard to make money in software when you're given all the software away for free. Well, >>We're not giving all >>The software. I know you've got that piece now, but, but here's my question. As ADU goes into the enterprise, which is clearly doing, is that that whole bundling, like what you're doing with NetApp is that really ultimately how you're gonna start to, to monetize and, and successfully monetize your software, >>Is by pushing it through >>Yeah. Packaging and that bundling that solution, in other words, our enterprise customer is gonna be more receptive to that solution package than say the, the fridge that has been using Hadoop for the last >>Two or three years. I think there's no question about it. If you, if you look at what Quadra Enterprise does, I don't know if, if you've had a chance to attend any of the sessions, maybe where Quadra Enterprise is, is currently being demonstrated. >>We just had Alex Williams as about on the air. Did a review, >>Okays >>Been going good and impressed with it? >>Yeah, there's no question about it. And I, I don't, and Alex probably hasn't seen the new version that, you know, our team is working on and it's, you know, quietly working on in the background. Incredible, incredible developments in, And that's really a function of when you have direct access to so many customers and you're getting so much input and feedback and they're the kinds of access to the kinds of customers we ultimately wanna serve. So real enterprises, what you get is really fast innovation from a really talented team that knows to do well. I mean, we are years ahead on the management side. Absolutely. Years ahead. And you know, I, so I was a guy who worked at VMware for several years, and I can tell you that while the hypervisor itself was, was a core component to VMware success, the monetization strategy was very squarely around vCenter. Yeah. Yes. Out. And we're not ignorant to that. Yeah. >>You can learn a lot from your VMware experience cause absolutely. The, the market changed significantly. And, you know, >>There were free hypervisors available all of a sudden. VMware itself had a free hypervisor. We had, we had VMware server and we had also our VMware player products, right? And those were all free. And they were very good technology. They were the best available in the market for free. And they were better, in my opinion, they were better than anything else. Open or not. No, our time >>Too, since still >>Are, they were, they, they were, they were superior products in every way. But yet how VMware was successful was recognizing that in the interest of running a production environment with an sola, you need management software. And they've also built the best management software. And there's no question that we understand that strategy and >>A phenomenal ecosystem. I mean, there's the >>Similarities, right? They did. And you, and the, and the ecosystem was in, in large part predicated on transparency act, very clear access to the APIs and a willingness to help partners be successful with those APIs. And ultimately drawing a very tight box about what the company wanted to do and didn't want to do. >>I mean, look, you're not, you're not gonna lose friends when you make people money. That's my philosophy, right? I agree. So when you're in that business where you can come in and enable a channel and have options on your growth strategy, which you do, I mean, you can say, Okay, bundling, I can go, you know, I can have this sold direct, or at least as long as you've got the options, you can grow with that market. So, you know, again, the, it's a money making opportunity for the partnerships, but there's >>More than that, right? Because you mentioned Apple, iTunes, Oracle's another example. And the way you make money with Apple and the way you make money with Oracle is different than the way you make money with VMware and presumably Cloudera. >>Yeah, I mean, our strategy is, if you make this base platform easier to install, more reliable, and you make it ultimately, you know, really rock solid from an integration standpoint, more people are gonna use it. So what happens when more people use it? First thing that happens is more solu, it's out there. So it's more solutions get built. When more solutions get built, then you see more clusters get developed. When more clusters are out there, they start to move into production. And then they, they need an sla when they need an sla, Cloudera and Enterprise gets purchased. But along that path, when those solutions got built, guess what else happened? More cloud units got sold, more servers got sold, more networking. Gear got sold, more services got created. You get, you get ultimately more operating systems got sold, more databases, got data into them, more BI clients got created. The ecosystem is deep and rich, and a lot of people stand to make money hop >>In people. The water's great. >>What about, what about support? Okay, so, you know, the other guys are saying, We're just gonna make money on support. I mean support, You guys still are doing support, right? I mean, you're selling >>Support. There's no question. Quad Enterprise contains two things, right? The management suite and support this is, this is not uncomplicated technology and having a world class support team is of value and customers do want to pay for that value. But we, we believe that support in and of itself is not enough. And that ultimately, when you wanna deliver an sla, being able to call when you have a problem is the wrong approach. You want to be proactive and understand the problem well in advance of it actually occurring. That's really important. When, for example, if you're a customer, a lot of our customers have a data pipeline that >>They, they're building out basically. I mean they're, it's, it's new and emerging. So they're building out, It's not just support. They need other tools. >>Yeah. And it building out I think is an understatement for some, where some of our customers are. I mean, when you have a thousand node cluster that you're operating Yeah, Yeah. To, that's mission critical to your business. I don't think that's building out anymore. I think that's an investment in a technology that's mission critical. And what you wanna see when you have a mission critical technology is you wanna know early and often when a problem may emerge. Not, Oh, oh my gosh, we have a problem now I need to go, you know, phone a friend, phone a friend is, is kind of a last resort. We offer that. But what we really do is, and that's the, that's the beau, That's why we don't decouple our support from our management suite. It's not about phone a friend. It's about understanding the operation of your cluster the entire way through 24. >>And the other op the other thing that people don't talk about in the support is that with open source, a lot of support gets handled in the community as well. So like That's right. So in a way, you're already pre cannibalized with the community >>By us and by others. Absolutely. But you, you'll never see to that Forbes article I referenced earlier. You will never, you will not see our, our engineers are not trained to withhold information and under any circumstances to anyone free or paying. Yeah. This is about getting, You >>Don't wanna hold back your business. I mean, you have nothing to hide. It's open rights. >>Open source. It's open. And we're here to help. We're here to help. Whether you're paying us or not, >>This is value to that anticipatory >>Remediation. Yeah. That's what you're packaging and clearing up the air. Great. Great cube guest, you're awesome on the cube. Gonna have you more on because great to get the info out there. Really impressed with the channel strategy. Love the love the growth strategy, the cloud air. You guys are really impressive. I'm really, really impressed to see that you guys got everything pumping on all cylinders, Kirk, and you are cranking out on the business execution. We're in the team playing this chest mask open. Perfect. So great. Congratulations. Great. Thanks. You guys just in the financing. >>Oh, thank you as >>Well. Hey, Ed from Cloudera, clearing it up here inside the cube. We're gonna take a quick break and we'll be right back with more video. >>Thanks guys. All right.