[Music] we're on welcome to the special cube conversation we're here with some breaking news we got some startup investment news here in the Q studios palo alto I'm John for your host here at Jerry Chen partnered Greylock and the CEO of rock said Venkat Venkat Rahmani welcome to the cube you guys announcing hot news today series a and seed and Series A funding 21 million dollars for your company congratulations thank you Roxette is a data company jerry great this is one of your nest you kept this secret forever it was John was really hard you know over the past two years every time I sat in this seat I'd say and one more thing you know I knew that part of the advantage was rocks I was a special company and we were waiting to announce it and that's right time so it's been about two and half years in the making I gotta give you credit Jerry I just want to say to everyone I try to get the secrets out of you so hard you are so strong and keeping a secret I said you got this hot startup this was two years ago yeah I think the probe from every different angle you can keep it secrets all the entrepreneurs out there Jerry Chen's your guide alright so congratulations let's talk about the startup so you guys got 21 million dollars how much was the seed round this is the series a the seed was three million dollars both Greylock and Sequoia participating and the series a was eighteen point five all right so other investors Jerry who else was in on this I just the two firms former beginning so we teamed up with their French from Sequoia and the seed round and then we over the course of a year and half like this is great we're super excited about the team bank had Andrew bhai belt we love the opportunity and so Mike for an office coin I said let's do this around together and we leaned in and we did it around alright so let's just get into the other side I'm gonna read your your about section of the press release roxette's visions to Korea to build the data-driven future provide a service search and analytics engine make it easy to go from data to applications essentially building a sequel layer on top of the cloud for massive data ingestion I want to jump into it but this is a hot area not a lot of people are doing this at the level you guys are now and what your vision is did this come from what's your background how did you get here did you wake up one Wednesday I'm gonna build this awesome contraction layer and build an operating system around data make this thing scalable how did it all start I think it all started from like just a realization that you know turning useful data to useful apps just requires lots of like hurdles right you have to first figure out what format the data is in you got to prepare the data you gotta find the right specialized you know data database or data management system to load it in and it often requires like weeks to months before useful data becomes useful apps right and finally you know after I you know my tenure at Facebook when I left the first thing I did was I was just talking you know talking to a lot of people with real-world companies and reload problems and I started walking away from moremore of them thinking that this is way too complex I think the the format in which a lot of the data is coming in is not the format in which traditional sequel based databases are optimized for and they were built for like transaction processing and analytical processing not for like real-time streams of data but there's JSON or you know you know parque or or any of these other formats that are very very popular and more and more data is getting produced by one set of applications and getting consumed by other applications but what we saw it was what is this how can we make it simpler why do we need all this complexity right what is a simple what is the most simple and most powerful system we can build and pulled in the hands of as many people as possible and so we very sort of naturally relate to developers and data scientists people who use code on data that's just like you know kind of like our past lives and when we thought about it well why don't we just index the data you know traditional databases were built when every byte mattered every byte of memory every byte on disk now in the cloud the economics are completely different right so when you rethink those things with fresh perspective what we said was like what if we just get all of this data index it in a format where we can directly run very very fast sequel on it how simple would the world be how much faster can people go from ideas to do experiments and experiments to production applications and how do we make it all faster also in the cloud right so that's really the genesis of it well the real inspiration came from actually talking to a lot of people with real-world problems and then figuring out what is the simplest most powerful thing we can build well I want to get to the whole complexity conversation cuz we were talking before we came on camera here about how complexity can kill and why and more complexity on top of more complexity I think there's a simplicity angle here that's interesting but I want to get back to your background of Facebook and I want to tell a story you've been there eight years but you were there during a very interesting time during that time in history Facebook was I think the first generation we've taught us on the cube all the time about how they had to build their own infrastructure at scale while they're scaling so they were literally blitzscaling as reid hoffman and would say and you guys do it the Greylock coverage unlike other companies at scale eBay Microsoft they had old-school one dotto Technology databases Facebook had to kind of you know break glass you know and build the DevOps out from generation one from scratch correct it was a fantastic experience I think when I started in 2007 Facebook had about 40 million monthly actives and I had the privilege of working with some of the best people and a lot of the problems we were very quickly around 2008 when I went and said hey I want to do some infrastructure stuff the mandate that was given to me and my team was we've been very good at taking open source software and customizing it to our needs what would infrastructure built by Facebook for Facebook look like and we then went into this journey that ended up being building the online data infrastructure at Facebook by the time I left the collectively these systems were surveying 5 plus billion requests per second across 25 plus geographical clusters and half a dozen data centers I think at that time and now there's more and the system continues to chug along so it was just a fantastic experience I think all the traditional ways of problem solving just would not work at that scale and when the user base was doubling early in the early days every four months every five months yeah and what's interesting you know you're young and here at the front lines but you're kind of the frog in boiling water and that's because you are you were at that time building the power DevOps equation automating scale growth everything's happening at once you guys were right there building it now fast forward today everyone who's got an enterprise it's it wants to get there they don't they're not Facebook they don't have this engineering staff they want to get scale they see the cloud clearly the value property has got clear visibility but the economics behind who they hire so they have all this data and they get more increasing amount of data they want to be like Facebook but can't be like Facebook so they have to build their own solutions and I think this is where a lot of the other vendors have to rebuild this cherry I want to ask you because you've been looking at a lot of investments you've seen that old guard kind of like recycled database solutions coming to the market you've seen some stuff in open source but nothing unique what was it about Roxette that when you first talk to them that but you saw that this is going to be vectoring into a trend that was going to be a perfect storm yeah I think you nailed it John historic when we have this new problems like how to use data the first thing trying to do you saw with the old technology Oh existing data warehouses akin databases okay that doesn't work and then the next thing you do is like okay you know through my investments in docker and B and the boards or a cloud aerosol firsthand you need kind of this rise of stateless apps but not stateless databases right and then I through the cloud area and a bunch of companies that I saw has an investor every pitch I saw for two or three years trying to solve this data and state problem the cloud dudes add more boxes right here's here's a box database or s3 let me solve it with like Oh another database elastic or Kafka or Mongo or you know Apache arrow and it just got like a mess because if almond Enterprise IT shop there's no way can I have the skill the developers to manage this like as Beckett like to call it Rube Goldberg machination of data pipelines and you know I first met Venkat three years ago and one of the conversations was you know complexity you can't solve complex with more complexity you can only solve complexity with simplicity and Roxette and the vision they had was the first company said you know what let's remove boxes and their design principle was not adding another boxes all a problem but how to remove boxes to solve this problem and you know he and I got along with that vision and excited from the beginning stood to leave the scene ah sure let's go back with you guys now I got the funding so use a couple stealth years to with three million which is good a small team and that goes a long way it certainly 2021 total 18 fresh money it's gonna help you guys build out the team and crank whatnot get that later but what did you guys do in the in those two years where are you now sequel obviously is lingua franca cool of sequel but all this data is doesn't need to be scheming up and built out so were you guys that now so since raising the seed I think we've done a lot of R&D I think we fundamentally believe traditional data management systems that have been ported over to run on cloud Williams does not make them cloud databases I think the cloud economics is fundamentally different I think we're bringing this just scratching the surface of what is possible the cloud economics is you know it's like a simple realization that whether you rent 100 CPUs for one minute or or one CPU 400 minutes it's cost you exactly the same so then if you really ask why is any of my query is slow right I think because your software sucks right so basically what I'm trying to say is if you can actually paralyze that and if you can really exploit the fluidity of the hardware it's not easy it's very very difficult very very challenging but it's possible I think it's not impossible and if you can actually build software ground-up natively in the cloud that simplifies a lot of this stuff and and understands the economics are different now and it's system software at the end of the day is how do I get the best you know performance and efficiency for the price being paid right and the you know really building you know that is really what I think took a lot of time for us we have built not only a ground-up indexing technique that can take raw data without knowing the shape of the data we can turn that and index it in ways and store them maybe in more than one way since for certain types of data and then also have built a distributed sequel engine that is cloud native built by ground up in the cloud and C++ and like really high performance you know technologies and we can actually run distributor sequel on this raw data very very fast my god and this is why I brought up your background on Facebook I think there's a parallel there from the ground this ground up kind of philosophy if you think of sequel as like a Google search results search you know keyword it's the keyword for machines in most database worlds that is the standard so you can just use that as your interface Christ and then you using the cloud goodness to optimize for more of the results crafty index is that right correct yes you can ask your question if your app if you know how to see you sequel you know how to use Roxette if you can frame your the question that you're asking in order to answer an API request it could be a micro service that you're building it could be a recommendation engine that you're that you're building or you could you could have recommendations you know trying to personalize it on top of real time data any of those kinds of applications where it's a it's a service that you're building an application you're building if you can represent ask a question in sequel we will make sure it's fast all right let's get into the how you guys see the application development market because the developers will other winners here end of the day so when we were covering the Hadoop ecosystem you know from the cloud era days and now the important work at the Claire merger that kind of consolidates that kind of open source pool the big complaint that we used to hear from practitioners was its time consuming Talent but we used to kind of get down and dirty the questions and ask people how they're using Hadoop and we had two answers we stood up Hadoop we were running Hadoop in our company and then that was one answer the other answer was we're using Hadoop for blank there was not a lot of those responses in other words there has to be a reason why you're using it not just standing it up and then the Hadoop had the problem of the world grew really fast who's gonna run it yeah management of it Nukem noose new things came in so became complex overnight it kind of had took on cat hair on it basically as we would say so how do you guys see your solution being used so how do you solve that what we're running Roxette oh okay that's great for what what did developers use Roxette for so there are two big personas that that we currently have as users right there are developers and data scientists people who program on data right - you know on one hand developers want to build applications that are making either an existing application better it could be a micro service that you know I want to personalize the recommendations they generated online I mean offline but it's served online but whether it is somebody you know asking shopping for cars on San Francisco was the shopping you know was the shopping for cars in Colorado we can't show the same recommendations based on how do we basically personalize it so personalization IOT these kinds of applications developers love that because often what what you need to do is you need to combine real-time streams coming in semi structured format with structured data and you have no no sequel type of systems that are very good at semi structured data but they don't give you joins they don't give you a full sequel and then traditional sequel systems are a little bit cumbersome if you think about it I new elasticsearch but you can do joins and much more complex correct exactly built for the cloud and with full feature sequel and joins that's how that's the best way to think about it and that's how developers you said on the other side because its sequel now all of a sudden did you know data scientist also loved it they had they want to run a lot of experiments they are the sitting on a lot of data they want to play with it run experiments test hypotheses before they say all right I got something here I found a pattern that I don't know I know I had before which is why when you go and try to stand up traditional database infrastructure they don't know how what indexes to build how do i optimize it so that I can ask you know interrogatory and all that complexity away from those people right from basically provisioning a sandbox if you will almost like a perpetual sandbox of data correct except it's server less so like you don't you never think about you know how many SSDs do I need how many RAM do I need how many hosts do I need what configure your programmable data yes exactly so you start so DevOps for data is finally the interview I've been waiting for I've been saying it for years when's is gonna be a data DevOps so this is kind of what you're thinking right exactly so you know you give us literally you you log in to rocks at you give us read permissions to battle your data sitting in any cloud and more and more data sources we're adding support every day and we will automatically cloudburst will automatically interested we will schematize the data and we will give you very very fast sequel over rest so if you know how to use REST API and if you know how to use sequel you'd literally need don't need to think about anything about Hardware anything about standing up any servers shards you know reindex and restarting none of that you just go from here is a bunch of data here are my questions here is the app I want to build you know like you should be bottleneck by your career and imagination not by what can my data employers give me through a use case real quick island anyway the Jarius more the structural and architectural questions around the marketplace take me through a use case I'm a developer what's the low-hanging fruit use case how would I engage with you guys yeah do I just you just ingest I just point data at you how do you see your market developing from the customer standpoint cool I'll take one concrete example from a from a developer right from somebody we're working with right now so they have right now offline recommendations right or every night they generate like if you're looking for this car or or this particular item in e-commerce these are the other things are related well they show the same thing if you're looking at let's say a car this is the five cars that are closely related this car and they show that no matter who's browsing well you might have clicked on blue cars the 17 out of 18 clicks you should be showing blue cars to them right you may be logging in from San Francisco I may be logging in from like Colorado we may be looking for different kinds of cars with different you know four-wheel drives and other options and whatnot there's so much information that's available that you can you're actually by personalizing it you're adding creating more value to your customer we make it very easy you know live stream all the click stream beta to rock set and you can join that with all the assets that you have whether it's product data user data past transaction history and now if you can represent the joins or whatever personalization that you want to find in real time as a sequel statement you can build that personalization engine on top of Roxanne this is one one category you're putting sequel code into the kind of the workflow of the code saying okay when someone gets down to these kinds of interactions this is the sequel query because it's a blue car kind of go down right so like tell me all the recent cars that this person liked what color is this and I want to like okay here's a set of candidate recommendations I have how do I start it what are the four five what are the top five I want to show and then on the data science use case there's a you know somebody building a market intelligence application they get a lot of third-party data sets it's periodic dumps of huge blocks of JSON they want to combine that with you know data that they have internally within the enterprise to see you know which customers are engaging with them who are the persons churning out what are they doing and they in the in the market and trying to bring they bring it all together how do you do that when you how do you join a sequel table with a with a JSON third party dumb and especially for coming and like in the real-time or periodic in a week or week month or one month literally you can you know what took this particular firm that we're working with this is an investment firm trying to do market intelligence it used age to run ad hoc scripts to turn all of this data into a useful Excel report and that used to take them three to four weeks and you know two people working on one person working part time they did the same thing in two days and Rock said I want to get to back to microservices in a minute and hold that thought I won't go to Jerry if you want to get to the business model question that landscape because micro services were all the world's going to Inc so competition business model I'll see you gets are funded so they said love the thing about monetization to my stay on the core value proposition in light of the red hat being bought by by IBM had a tweet out there kind of critical of the transactions just in terms of you know people talk about IBM's betting the company on RedHat Mike my tweet was don't get your reaction will and tie it to the visible here is that it seems like they're going to macro services not micro services and that the world is the stack is changing so when IBM sell out their stack you have old-school stack thinkers and then you have new-school stack thinkers where cloud completely changes the nature of the stack in this case this venture kind of is an indication that if you think differently the stack is not just a full stack this way it's this way in this way yeah as we've been saying on the queue for a couple of years so you get the old guard trying to get a position and open source all these things but the stacks changing these guys have the cloud out there as a tailwind which is a good thing how do you see the business model evolving do you guys talk about that in terms of you can hey just try to find your groove swing get customers don't worry about the monetization how many charging so how's that how do you guys talk about the business model is it specific and you guys have clear visibility on that what's the story on that I mean I think yeah I always tell Bank had this kind of three hurdles you know you have something worthwhile one well someone listen to your pitch right people are busy you like hey John you get pitched a hundred times a day by startups right will you take 30 seconds listen to it that's hurdle one her will to is we spend time hands on keyboards playing around with the code and step threes will they write you a check and I as a as a enter price offered investor in a former operator we don't overly folks in the revenue model now I think writing a check the biz model just means you're creating value and I think people write you checking screening value but you know the feedback I always give Venkat and the founders work but don't overthink pricing if the first 10 customers just create value like solve their problems make them love the product get them using it and then the monetization the actual specifics the business model you know we'll figure out down the line I mean it's a cloud service it's you know service tactically to many servers in that sentence but it's um it's to your point spore on the cloud the one that economists are good so if it works it's gonna be profitable yeah it's born the cloud multi-cloud right across whatever cloud I wanna be in it's it's the way application architects going right you don't you don't care about VMs you don't care about containers you just care about hey here's my data I just want to query it and in the past you us developer he had to make compromises if I wanted joins in sequel queries I had to use like postgrads if I won like document database and he's like Mongo if I wanted index how to use like elastic and so either one I had to pick one or two I had to use all three you know and and neither world was great and then all three of those products have different business models and with rocks head you actually don't need to make choices right yes this is classic Greylock investment you got sequoia same way go out get a position in the market don't overthink the revenue model you'll funded for grow the company let's scale a little bit and figure out that blitzscale moment I believe there's probably the ethos that you guys have here one thing I would add in the business model discussion is that we're not optimized to sell latte machines who are selling coffee by the cup right so like that's really what I mean we want to put it in the hands of as many people as possible and make sure we are useful to them right and I think that is what we're obsessed about where's the search is a good proxy I mean that's they did well that way and rocks it's free to get started right so right now they go to rocks calm get started for free and just start and play around with it yeah yeah I mean I think you guys hit the nail on the head on this whole kind of data addressability I've been talking about it for years making it part of the development process programming data whatever buzzword comes out of it I think the trend is it looks a lot like that depo DevOps ethos of automation scale you get to value quickly not over thinking it the value proposition and let it organically become part of the operation yeah I think we we the internal KPIs we track are like how many users and applications are using us on a daily and weekly basis this is what we obsess about I think we say like this is what excellence looks like and we pursue that the logos in the revenue would would you know would be a second-order effect yeah and it's could you build that core kernels this classic classic build up so I asked about the multi cloud you mention that earlier I want to get your thoughts on kubernetes obviously there's a lot of great projects going on and CN CF around is do and this new state problem that you're solving in rest you know stateless has been an easy solution VP is but API 2.0 is about state right so that's kind of happening now what's your view on kubernetes why is it going to be impactful if someone asked you you know at a party hey thank you why is what's all this kubernetes what party going yeah I mean all we do is talk about kubernetes and no operating systems yeah hand out candy last night know we're huge fans of communities and docker in fact in the entire rock set you know back-end is built on top of that so we run an AWS but with the inside that like we run or you know their entire infrastructure in one kubernetes cluster and you know that is something that I think is here to stay I think this is the the the programmability of it I think the DevOps automation that comes with kubernetes I think all of that is just like this is what people are going to start taking why is it why is it important in your mind the orchestration because of the statement what's the let's see why is it so important it's a lot of people are jazzed about it I've been you know what's what's the key thing I think I think it makes your entire infrastructure program all right I think it turns you know every aspect of you know for example yeah I'll take it I'll take a concrete example we wanted to build this infrastructure so that when somebody points that like it's a 10 terabytes of data we want to very quickly Auto scale that out and be able to grow this this cluster as quickly as possible and it's like this fluidity of the hardware that I'm talking about and it needs to happen or two levels it's one you know micro service that is ingesting all the data that needs to sort of burst out and also at the second level we need to be able to grow more more nodes that we we add to this cluster and so the programmability nature of this like just imagine without an abstraction like kubernetes and docker and containers and pods imagine doing this right you are building a you know a lots and lots of metrics and monitoring and you're trying to build the state machine of like what is my desired state in terms of server utilization and what is the observed state and everything is so ad hoc and very complicated and kubernetes makes this whole thing programmable so I think it's now a lot of the automation that we do in terms of called bursting and whatnot when I say clock you know it's something we do take advantage of that with respect to stateful services I think it's still early days so our our position on my partner it's a lot harder so our position on that is continue to use communities and continue to make things as stateless as possible and send your real-time streams to a service like Roxette not necessarily that pick something like that very separate state and keep it in a backhand that is very much suited to your micro service and the business logic that needs to live there continue should continue to live there but if you can take a very hard to scale stateful service split it into two and have some kind of an indexing system Roxette is one that you know we are proud of building and have your stateless communal application logic and continue to have that you know maybe use kubernetes scale it in lambdas you know for all we care but you can take something that is very hard to you know manage and scale today break it into the stateful part in the stateless part and the serval is back in like like Roxette will will sort of hopefully give you a huge boost in being able to go from you know an experiment to okay I'm gonna roll it out to a smaller you know set of audience to like I want to do a worldwide you know you can do all of that without having to worry about and think about the alternative if you did it the old way yeah yeah and that's like talent you'd need it would be a wired that's spaghetti everywhere so Jerry this is a kubernetes is really kind of a benefit off your your investment in docker you must be proud and that the industry has gone to a whole nother level because containers really enable all this correct yeah so that this is where this is an example where I think clouds gonna go to a whole nother level that no one's seen before these kinds of opportunities that you're investing in so I got to ask you directly as you're looking at them as a as a knowledgeable cloud guy as well as an investor cloud changes things how does that change how is cloud native and these kinds of new opportunities that have built from the ground up change a company's network network security application era formants because certainly this is a game changer so those are the three areas I see a lot of impact compute check storage check networking early days you know it's it's it's funny it gosh seems so long ago yet so briefly when you know I first talked five years ago when I first met mayor of Essen or docker and it was from beginning people like okay yes stateless applications but stateful container stateless apps and then for the next three or four years we saw a bunch of companies like how do I handle state in a docker based application and lots of stars have tried and is the wrong approach the right approach is what these guys have cracked just suffered the state from the application those are app stateless containers store your state on an indexing layer like rock set that's hopefully one of the better ways saw the problem but as you kind of under one problem and solve it with something like rock set to your point awesome like networking issue because all of a sudden like I think service mesh and like it's do and costs or kind of the technologies people talk about because as these micro services come up and down they're pretty dynamic and partially as a developer I don't want to care about that yeah right that's the value like a Roxanna service but still as they operate of the cloud or the IT person other side of the proverbial curtain I probably care security I matters because also India's flowing from multiple locations multiple destinations using all these API and then you have kind of compliance like you know GDP are making security and privacy super important right now so that's an area that we think a lot about as investors so can I program that into Roxette what about to build that in my nap app natively leveraging the Roxette abstraction checking what's the key learning feature it's just a I'd say I'm a prime agent Ariane gdpr hey you know what I got a website and social network out in London and Europe and I got this gdpr nightmare I don't we don't have a great answer for GDP are we are we're not a controller of the data right we're just a processor so I think for GDP are I think there is still the controller still has to do a lot of work to be compliant with GDP are I think the way we look at it is like we never forget that this ultimately is going to be adding value to enterprises so from day one we you can't store data and Roxette without encrypting it like it's just the on you know on by default the only way and all transit is all or HTTPS and SSL and so we never freaked out that we're building for enterprises and so we've baked in for enterprise customers if they can bring in their own custom encryption key and so everything will be encrypted the key never leaves their AWS account if it's a you know kms key support private VP ceilings like we have a plethora of you know security features so that the the control of the data is still with the data controller with this which is our customer but we will be the the processor and a lot of the time we can process it using their encryption keys if I'm gonna build a GDP our sleeves no security solution I would probably build on Roxette and some of the early developers take around rocks at our security companies that are trying to track we're all ideas coming and going so there the processor and then one of the companies we hope to enable with Roxette is another generation security and privacy companies that in the past had a hard time tracking all this data so I can build on top of rocks crack okay so you can built you can build security a gbbr solution on top rock set because rock set gives you the power to process all the data index all the data and then so one of the early developers you know stolen stealth is they looking at the data flows coming and go he's using them and they'll apply the context right they'll say oh this is your credit card the Social Security is your birthday excetera your favorite colors and they'll apply that but I think to your point it's game-changing like not just Roxette but all the stuff in cloud and as an investor we see a whole generation of new companies either a to make things better or B to solve this new category problems like pricing the cloud and I think the future is pretty bright for both great founders and investors because there's just a bunch of great new companies and it's building up from the ground up this is the thing I brought my mother's red hat IBM thing is that's not the answer at the root level I feel like right now I'd be on I I think's fastenings but it's almost like you're almost doubling down to your your comment on the old stack right it's almost a double down the old stack versus an aggressive bet on kind of what a cloud native stack will look like you know I wish both companies are great people I was doing the best and stuff do well with I think I'd like to do great with OpenStack but again their product company as the people that happen to contribute to open source I think was a great move for both companies but it doesn't mean that that's not we can't do well without a new stack doing well and I think you're gonna see this world where we have to your point oh these old stacks but then a category of new stack companies that are being born in the cloud they're just fun to watch it all it's all big all big investments that would be blitzscaling criteria all start out organically on a wave in a market that has problems yeah and that's growing so I think cloud native ground-up kind of clean sheet of paper that's the new you know I say you're just got a pic pick up you got to pick the right way if I'm oh it's gotta pick a big wave big wave is not a bad wave to be on right now and it's at the data way that's part of the cloud cracked and it's it's been growing bigger it's it's arguably bigger than IBM is bigger than Red Hat is bigger than most of the companies out there and I think that's the right way to bet on it so you're gonna pick the next way that's kind of cloud native-born the cloud infrastructure that is still early days and companies are writing that way we're gonna do well and so I'm pretty excited there's a lot of opportunities certainly this whole idea that you know this change is coming societal change you know what's going on mission based companies from whether it's the NGO to full scale or all the applications that the clouds can enable from data privacy your wearables or cars or health thing we're seeing it every single day I'm pretty sad if you took amazon's revenue and then edit edit and it's not revenue the whole ready you look at there a dybbuk loud revenue so there's like 20 billion run which you know Microsoft had bundles in a lot of their office stuff as well if you took amazon's customers to dinner in the marketplace and took their revenue there clearly would be never for sure if item binds by a long shot so they don't count that revenue and that's a big factor if you look at whoever can build these enabling markets right now there's gonna be a few few big ones I think coming on they're gonna do well so I think this is a good opportunity of gradual ations thank you thank you at 21 million dollars final question before we go what are you gonna spend it on we're gonna spend it on our go-to-market strategy and hiding amazing people as many as we can get good good answer didn't say launch party that I'm saying right yeah okay we're here Rex at SIA and Joe's Jerry Chen cube cube royalty number two all-time on our Keeble um nine list partner and Greylock guy states were coming in I'm Jeffrey thanks for watching this special cube conversation [Music]

(upbeat electronic music) >> Announcer: Live from Las Vegas, it's the CUBE. Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to the Aria in Las Vegas everybody. This is the CUBE, the leader is live tech coverage. And we're here covering Veritas Vision, #VtasVision. I'm Dave Vellante with Stu Miniman. Bill Coleman is here. He's the CEO of Veritas. Bill, thanks for coming on the CUBE, good to see you. >> My pleasure, thank you for hosting us. >> Well, you're very welcome. And so, hot off the keynote, how do you feel, how's the show going for you so far? >> Well, I'll tell you what. I feel verit-awesome! >> (laughs) Verit-awesome is the watchword here. Get the crowd talk of Verit-awesome. I love that you started out with a little retrospective from last year. You used the term digital twin. We love that term, and you said it's sort of grown up now. I like to think the digital twins are sort of in their adolescent or even teenage years. The data is sort of out of control. We're not hearing today a message of legacy backup. We're hearing a vision of the future. Talk about that and what that vision looks like. >> Our customers obviously need data protection. They need resiliency. They need everything they've needed in the past. But that's not what they're interested in. That's assumed, that has to work. What they're interested in is the power of information. We like to say that our mission is to harness the power of information. And it's what's called digital transformation. Being able to use all that data out on the internet with all of their data, to change how they do business. To change what their products are. To change their supply chain. It's all about machine learning, predictive analytics, and the power of information. >> So I started in this business the same year that Veritas was born. And so I saw the ascendancy of Veritas and the many different forms that the company had taken. But I used to use Veritas as an example. You want to be like Veritas, with no hardware agenda. You want to be the glue that brings things together. And I saw in the conversation today a little bit of BEA-like thinking. The binder, if you will. Binding clouds together. My term, you guys didn't use that term, but to us, that's a critical value-add, and it's all around the data. You guys talked about digital business. To us, digital business means data, and it seems like we sort of share that common belief. >> Absolutely. You know, we've called this the information age for 50 years? But it's not been about information, it's been about technology. We finally have the ability to address that information, and do it over the internet, everywhere and everything. That's really what our vision is. You know, at BEA, we saw the internet emerging. And the world had to distribute, and take advantage of all that power across the whole world. And we invented that. But the key was, when I came up with the first concept of BEA in '93, I said, "You know, by the year 2000, "the network is going to be the computer." The network needs an operating system to make it all work. Well the concept here, and the reason that I actually took this job, is looking ahead ten years. Everything's going to be about information. No organization's going to be able to exist without leveraging the power of that information. Because that's the only way they'll bring their customer the value they need. That's the only way they compete, and without it, their business is just going to go down. >> Yeah, Bill, how are customers going to leverage data? You mentioned it's about the information, it's not about the technology. But you know, I look at customers. They've had storage people, they have network people. You know, "Oh, I'm excited about containers." We spent the last 15 years focused on virtualization. Is it Chief Data Officer? Or is it some other structure that customers, how are some of the leading customers that are going to be able to adopt this, how are they changing to be able to leverage that data and information? >> Well first, you have to understand, the technology has been complex, hard to use, hard to manage. As we saw earlier in the keynotes, it's like building a Rube Goldberg device. They had 27 different software products, and 14 different hardware products to sort of work together. Well, that's all disappearing. With cloud and the internet, it's becoming like a utility. You just subscribe to it. So that goes away. Now what you have to do, what we have to do, is we have to give them the tools that they can easily, visually look at that data, determine what's in that data, be maneuvering it, move it around, like in the movie, uh-- >> Stu: Minority Report? >> Minority Report. And literally, the things we talked about today, the demos we showed can lead to that. With machine learning predictive analytics, our biggest customers are already investing billions of dollars to do that. 'Cause they know if they don't jump ahead, their competition's going to do it. It's the power of information. >> So one of the things I might take away today was not only is Veritas hardware agnostic, but in many respects, you're workload agnostic. In other words, what I mean by that is, a lot of the events that Stu and I and the CUBE goes to, the enterprise companies are talking about on prem and that's where their business is, and much of your business, of course, is on prem. But we heard a message today of, "We really don't care where it lives. "We want to be the innovator "to help you get value out of your data "no matter where it lives." Now a lot of people will say that, but you really don't care where it lives. Is that true? >> And we can't. Look at, data's not just in an enterprise's data centers anymore. They're using clouds. We've surveyed our customers. Our average enterprise customer is using three public clouds already. And they have dozens of SASS applications like Salesforce, Workday, ServiceNow. Their data's in there too. That's really complex. What we've done is we've take and build the products that run in the cloud, across the cloud, to and from the cloud all by one policy orchestration. So you don't have to think about any of that. You can discover the data, categorize the data, manage the data and analyze the data all from one interface, end to end. >> So the obvious hard question follow-up is that what give you confidence that the cloud guys, once they get that workload, aren't going to just sort of usurp that agenda? What do you have to do to maintain that customer delight? >> Well, the first thing is the cloud, the public cloud providers, are our very close partners. You know, the first month we started this, Bill Voss, who heads storage for AWS, and I worked with him and Sun, came down to us and said, "Look, our customers need backup." You know, snapshots are great, but if somebody deletes a snapshot, it's gone. Your data's gone. How are you going to protect that? How are you going to analyze that data? When we want to partner with you? So we partnered with them. But the other thing he said was, "And if we do it exclusively, "the enterprises aren't going to use us." I had the CIO of one of the top five banks in the world tell me right after I started this, "We've got to be using three clouds simultaneously. "We never want to be stuck in the cloud." So the cloud service providers know that the enterprise customers want and demand that portability. And we become their, we're the premier partner for Amazon, for Microsoft, for Google, and for IBM. >> So, it's relationships. >> Right. >> But it's also innovation. >> Absolutely. >> So talk about where you are with R & D. You're purchased by a private equity company. You might have heard the narrative beforehand. A lot of the old private equity model is to suck all the cash out. Kind of the new private equity model is to invest, grow the valuation of the company. I think that's where I see you guys going. But talk about how you're able to innovate. Talk about the R & D mojo that you guys have. >> You had several questions there. >> Yeah (laughs). >> But let me start with that, with the last one. When we carved this company out 19 months ago, it became apparent that we weren't a real player in the cloud. We weren't in some of the more modern workloads. And we had to change rapidly. So, we created a strategy that led to this whole 360 data management integrated platform, software-defined storage. Integrating it with a restful API interface. And then in one year, we built seven new products from scratch that operate in the cloud, on prem, or across cloud. Automated that entire thing. We literally took the startup mentality. Now I've been a startup guy most of my life. I spent the last five and a half years before this funding early-stage startups, and the thing is being agile, and moving fast. We can move faster than anyone around now. We're a big company. Let's take Cloudpoint. We just introduced our Cloud Snapshot. That was a thought in somebody's eye in February. We defined what we needed to do, working with our customers. We put together the team. We built a micro-service end to end archistructure, and we shipped it, supporting the major, all the major cloud snapshot capability in five months, end to end. Totally new product. Now that is a startup mentality. >> Yeah, Bill, can you explain to us a little bit some of the internal plumbing of how you've managed that. On the one hand, Veritas, trusted company, strong engineering culture, product like NetBackup, you know. 15 years, leader in it's space, versus brand new stuff, whole new spaces. What staying the same, what's changing? How do you manage some of those transitions? Because you know, typical company, it's like, "We've got 7500 employees." It's like, "Well, I've got revenue streams "and product lines that I know how to do "and can keep chugging, but I've got the new stuff too." So how do you manage that internally? >> I've have a very simple philosophy of what it takes to lead a major company. You got to have a direction to go in, you have to draw higher-grade people, and you have to organize around the first two. But the key is where are you going? Where's the puck going to be in five to 10 years? And I call that the three V's. WHat's the vision of where the market's going to be? And number two, what's the value that brings to customer? The value that will justify their switching costs. And the third is, what are the values that you build your company on, that customers and partners will be able to trust and count on. So, when you start with that, we created the vision. It has to be a compelling and urgent vision. Ten years from now, all of our products are going to be obsolete. They're going to mostly be obsolete in five years. All of our traditional products. It's all going to be a microservice. Change on the fly, customers never have to upgrade kind of environment, right? There's an urgency there. And customers want to transform. There's an urgency there. The key is, based on your values, you have to develop a culture that embodies the norms to execute your strategy. And then you keep those things and balances. The cultural change has been the most profound and the most important thing we've done in this company. And this company now has a startup, win-in-the-marketplace, customer-first culture. >> So you laid out the vision. In terms of the value to customers you said, when you talk to your CIO customers and other customers, three things came out. Cut costs, deal with governance and compliance, and then help us with the digital transformation. Help us become a digital business, essentially. >> Yeah. >> So those two are pretty clear. Talk about the values that you espouse. What are they? >> So, when you start with values have to be built around what you're providing to a customer. And there's sort of three aspects of that. I'm going to give them the best possible products. I'm going to give them the lowers possible price, or I'm going to give them the best possible service that they can count on. I'm asking our customers to bet their future. So it has to be the third. So it starts with, we produce customer value, right? Then the next aspect of it is, they have to believe that what you're doing is going to be there for them, that it's going to really work. So our next one is, we're going to do that by inventing the future, to bring them the customer value. We're not going to look back and try to add features and functions where we are. We need to help them jump ahead to where they need to be. The third part of that, the pyramid there is customers are going to rely on you. So trust, accountability, ethics, integrity. Those three things come together. Then, we're all about employees, right? So, how do you empower employees to succeed, grow, and be accountable. And you put these values together, and the values will never change. The culture will evolve as strategy moves, and keeping in balance means you're going to have to reorganize on a continual basis around where you are in your strategy. I told this company, we're going to be reorganizing continuously, at least once a year. We're about to do a pretty fundamental reorganization in parts of our company. And this is second time in six months. But you have, you know, you have to be an agile organization. >> Bill, the venture community thinks that this is a hot space. There's a whole number of startups, highly focused. Obviously they're smaller than you, don't have the breadth of products. How do you look at the marketplace? What do you say about that aspect? >> Well, as I said, I spent five and a half years in early-stage venture. >> Yeah. >> We had the highest return fund for our first fund of multiple of any venture capital company. I really love that world. Venture capital is the the center of invention, the center of innovation in this country, in the world. You know, back in the 40s, 50s and 60s, you used to have these big corporate labs. You know, Bell Labs, Sarnoff Labs, et cetera. They don't exist anymore. It's all done by these. So they're inventing the future. Now the difference between the pre-dot-com era and after is, the vast majority of startups are, well, the the vast majority have failed. >> Will fail. (laughs) The vast majority of what's left are acquired, and a few go public, right? So to me, number one, they are the laboratory. They are in the areas that we that are merging, and that we don't necessarily have a core competence, we want to look on how to do that. In BEA, in six years, I did 24 acquisitions to build the company. I never acquired anything that came to us. It was all, here's part of our strategy, we need this competency, we need this time to market. How do we make it work, right? Matter of fact, there was a joke. BEA stood for Built Entirely on Acquisitions. (hosts laugh) >> Well, people used to, Larry Elison himself used to denegrate people for writing checks, not code. And then, of course, he changed the software business with (laughs) some big checks. Well, I wonder if you could talk a little bit more about the team. So when you took over here at Veritas, you mentioned off camera, you started with the team. How did you go about that? Maybe describe, add some color to the team. >> You know, like I said, one of the three pillars of my management is hire great people. And if you're going to transform a company, if you're going to do a turnaround, it has to start with the leadership team. Period, you can't start anywhere else. But you have to have a leadership team that shares the vision, shares the drive, knows how to work hard together. And when they walk in that room, there's not one thought about my organization or my career, or my compensation. Because they all know, if we make this work, all the rest can take care of itself. Now, when you're doing these sort of things, there are certain times in certain organizations, that people's skills are optimal. You know, the group that was managing this as part of Semantec, they weren't necessarily the best people to manage it as a change in culture, change in strategy. So I had to go out, and I brought in a couple of folks that I've worked with before. We brought in some real amazing people. Mike Palmer is just unbelievable at all dimensions of product development. Scott Genereux, he knows sales back, forward. He knows every customer out there by name, and he knows how to really motivate a sales force. Well, every member of my leadership team except Todd Hauschildt, the CIO, has come in with the same vision, the same, and of course that works down the organization as you're building. And that's how you change the culture. With that, here's the vision of where we're going. Here's the values, what we are going to do. This is how we're going to lead it. >> So major objectives. Obviously you want to keep moving fast. >> I presume you're going to, >> Yeah. >> You're reorganizing frequently to support that. But what are the main objectives that we should be looking for as outside observers over the next six, nine, 12, 18 months? We are changing the agenda of the information management industry. The first place is, for digital transformation, corporations have to switch. They have to get off what they're doing today ultimately and go to something new. And in an enterprise, that can only be one platform. You can't have two platforms deleting, moving data asynchronously. So, its going to be a major transformation. Now that has to be a platform. We've put the stake in the ground. We have that platform. Now, this is our battle to lose, because the incumbents in a transformation get to win if they're good enough. You know, in the disruption, only a startup can win. That's how I won at BEA, how we won at Sun. But this isn't disruption. Nobody's going to throw away all their data centers and jump into somebody before who said, "Oh, I've managed 100 terabytes. "Give me your 50 pedabytes." (Dave laughs) You know? And no customer is going to trust them. So this is our battle to win. We're changing the entire agenda with 360 data management. What we, our number one challenge is, we have to change the positioning in our own customers' minds, because they know us as the 30 years of that legacy, backup, recovery and archiving company. And it's really working. But that's number one. That's my number one objective. 'Cause the rest will take care of itself. >> And as a private company, do you feel like you're in a more advantageous position to do that, and why? >> Well, I don't think I could do this as other than a private company. Because it changes the economics dramatically. Also, at the same time, we're switching from mostly licensed revenue, to mostly rateable avenues, we move to subscription. In a public company, that's a, "Oh, our revenue's going to go down for awhile, "and so is our profits, but trust me." >> Hang with us. (laughs) >> Yeah, hang with us. There are companies like adobe that did that flawlessly, but it's not an easy thing to do. >> Yeah, it's not easy. >> And I'll tell you, I have the best partner in the world. When I, when we started this whole carveout, and I figured out, "Whoa, we don't have the right products. "We got to build this whole thing." I went to Carlisle with the strategy and the vision of what we needed to do. And I said, "Look, because pricing pressure is so high, "We're not going to be able to grow based on your plan." How you invested. "But if you want me to do that, "I can do it, and you need to invest this much more. "But I recommend that we invest as fast as we can "to get to digital transformation." They chose the third. They chose to, we're spending 99 million more dollars in R & D and go-to-market this year than was in the original plan. I wouldn't be able to do that in the public markets. >> Yeah. >> You know? But they are the perfect partner. They build for growth. They stay in two to four years after an IPO. Their return is based on multiples of growth, and that's what, so our goals are totally aligned, and aligned with what the customers are going to need. >> Bill, great story, I know you're super busy. A lot of customers to meet. So thanks very much for taking time out and joining us on the CUBE. >> Bill: This has been a pleasure. Thank you, >> You're welcome. >> Bill: you got me all stimulated. >> All right, good deal. All right, keep it right there everybody. Stu and I will be back with our next guest. This is the CUBE. We're live from Veritas Vision 2017. We'll be right back. (electronic rhythmic music)