(upbeat music) >> Hi, I'm Peter Burris. Welcome another to theCUBE Conversation from beautiful Palo Alto. Here today, we are with Muddu Sudhakar, who's a CEO investor, and a long-time friend of theCUBE. Muddu, welcome to theCUBE. >> Thank you, Peter. Thanks for having me. >> So, one of the things we're going to talk about, there's a lot of things we could talk about, I mean, you've been around you've invested in a number of companies. You've got a great pedigree, a great track record. ServiceNow, and some other companies, I'll let you talk a bit more about that. But, one of the things we want to talk about is some of the big changes that are happening in the way that IT gets delivered within enterprises. The whole notion of IT operations management is on the forefront of everyone's mind. We've been talking about dev ops for a long time. It hasn't been universally adopted, it clearly needs some help; it's working really well in some places, not so well in other places. We're trying to bring that cloud-operating model into the enterprise. What are some of the things, based on your experience, talk a little bit about yourself, and then use that as a level into, what are some of the things that the IT organization, business overall, has to think about as they think about modernizing IT operations management, or ITOM. >> Great topic, it's very lengthy. We can go on for hours on this, right? As we are talking earlier, Peter, so I think operations IT management has been around for what, 20, 30, years? It started with, I guess, at the time of mainframes, to client server. But, as you rightfully said, we are in the age of cloud. How does cloud, AI machine learning, and the SaaS services going to impact ITOM, our IT operation management? I think that's, it's going to evolve, the question is how it's going to evolve. And, the one area that you are always passionate about talking about is cloud infrastructure itself, and the word that you use is called, Plastic infrastructure. The underlying infrastructure is changing so much. We are moving from virtual machines to server-less architectures, to containers. So this whole server-less architecture presents such a new concept, that the ITOM as itself should evolve to something new. I actually, I mean the industry word for this is, called AI operations. AI is just one piece. But how do you take hybrid cloud, how do you take the actual cloud substrate, and evolve IT operation management is such a big topic, on multiple areas, and how it is going to change industry. >> So, let's break it down a little bit. So, you mentioned the term plastic infrastructure. We've written a bunch about that here at Wikibon, and the basic notion of plastic infrastructure is that we can look at three generations of infrastructure, what we call static infrastructure, which might be brick, you add load to it, it might fall apart, but it was bound into the application. And in the world, or the era of elastic infrastructure is really where the cloud started, and the idea that you no longer had to purchase to your peak. That the elastic infrastructure would allow you to peak up, and peak down, but it would snap back into place, it was almost like a rubber brick. But this notion of plastic infrastructure, how do we add new workloads faster, is how do we but do so in a way that we don't have to manually go in and adust the infrastructure. That the infrastructure just responds to the new workloads in a plastic way. And snaps into a new form. Now to, we are going to need to be able to do that. If we're going to add AI, and we're going to add, you know, ML, machine learning, and all these other new application-oriented technologies to this. Can't imagine how we're going to add all that complexity to the application level, if we don't dramatically automate and simplify the operating load. And that's the basis of plastic infrastructure. What do you think? >> No, I completely, I think you kind of touched all the good points, but the areas that I can add on top of what you mentioned, is if you look at the plastic infrastructure, the one area is, so far IT operations management is built around a human being, around a dev ops, and around a IT admin. In the new world, it will be 90 to 80% to be done automated manner. Your trading is algorithmic, your in a self-driving car age, but at the IT operations management is around an IT admin and a dev ops. That got to change. I think cloud guys, the Amazon, Azure, Google, they're going to disrupt this because they have to do this in an automated manner, right? So that means, the plastic infrastructure will be able to run workloads, it should be malleable. It's like the, it should be changes shape and form. And it should be that's where the server-less really comes in. I don't want to pick a computer, and rent it for so many hours, that's still a silly concept, I think this whole virtualization, and virtual machines, is gone to the point of server-less. So, all these things. How do you manage the workloads? How do you manage your apps? To your point, apps have to be mapped downstream. I call it, as service maps. How do you build these dynamic service maps for your application? How do I know which component is failing at what point in time? Alright, asking what I call the root cause analysis. Do you expect a human being to identify that MongoDB, or a SQL server is down, because of this hardware issue? That has to be detected automatic manner, right? At least, a root cause and triage it to the point where a human being can come and say, I agree, or don't agree, able to take. Then, the final thing is, the infrastructure has to be, should be, take actions. Allow it to be at the point where the under, once you detect a problem, the infrastructure should be able to say algorithmically, progammatically to an API. I should be able to impact the change. The problem in chain infrastructure today is very much it's very much driven through scrapes and through admins. Can I do that in a programmatic manner? It hasn't happened yet. >> Then it should be, I mean when you stop and think about it AI for example, using AI as a general umbrella for a lot of different technologies that are based on you know, pattern-recognition, and anomaly detection. And all the other stuff that is associated with AI. But we have pretty good data sources in the infrastructure. We know how these tools operate, they are programmable, so they get, you know, a range of particular behaviors. But there are discernible patterns associated with those behaviors, so you'd think that infrastructure itself would be a great source, to start to building out some of these AI platforms, some of these new modeled, what we call data-first, type of applications. What do you think? >> Absolutely, you nailed it. I think, if you remember my previous company Caspida, which was acquired by Splunk. We did that for security. We created this whole area called user behavior analytics. Right? For security, understand the behavior of the users, understand the behavior of the attackers, actual inside it. Same thing needs to happen. >> But all represented through a device. >> Through a device. >> That had known characteristics. So we weren't saying, we're making big claims necessarily about people. Which have, you know, unbelievably complex, but when you start with, What is a person doing with a device? That set of behaviors is now constrained, which makes it a great source. >> Absolutely. So I think it, like given the sources in the IT operations area, if you were think about, for example, looking at the patterns and the behavior of the application, the storage, I call it like, think of like the four layers. You have apps, you have compute, your network, and storage. There are different patterns and behavior you can do it. You can do anomalies, and you can understand the various workflow of the patterns. But I call it the three P's problem with AI machine learning. The P's are, you actually said it five P's. The three P's, that I usually talk about is, the proactive, the predictive, and prescriptive nature. If I can take this data sources, whether they come from logs, events, alerts, and able to do this for those, I can do planning. I can be able to implement what changes I can do as a workflow and full actions. 'Cause detecting is no good, if I can't take an action. That's where the prescriptiveness comes in. And I think that whole area of IT operations management, what needs to happen is mundane with a human being, will be automated. And then the question comes in is, Do you do this in batch mode, or real-time? >> You want to do it in real-time. But let me get those straight. So the three P's that you mentioned where, proactive, prescriptive? >> And predictive. >> And predictive. So, that's proactive, predictive, and prescriptive. And just, you know, to level it out, I noted that all this is based on patterns. >> Yes. >> That come out of some of these infrastructure technologies. So, as we think about where ITOM is going, you mentioned earlier AI, systems management, AI services management. When we think about kind of some of the next steps, who do you anticipate are going to be kind of at the leading, or leading the charge, as we move forward here. >> I think there'll be a new sheriff in town. May not, or to your point earlier, that when many sheriffs in town in this area. The great opportunity here is when all there is a fundamental change like this happens, there will be new players will win this market. Definitely the cloud guys have the right substrate. The Amazon's, the Azure's, and the Google's of the world. They have the right infrastructure, they are all moving towards the plastic infrastructure. They just have to do more on workload management. They need to do more on the AI operations. >> They have a, absolutely a sense of urgency, and pressing need. >> They have. >> Their business falls down if they don't do this. >> So I think those guys will definitely there. Then all the start-ups, right? I think there are a whole bunch of start-ups, each of them will be doing, from a small niche player, all over to platform players. It's a great opportunity, greenfield opportunity. It's going to open up a whole wonderful, new players will come in. Who will be the next generations' AIOps operations vendors. >> So, I'm going to ask you two questions, then. One, do you think the big boys, the HPE's, the Oracle's, the Cisco's, the IBM's, are going to be able to change their stripes enough, so that they can do both? We're tryin' to keep our stall base and upgrade, enhance it, and try to introduce this new cloud operating model? And we'll talk about the start-ups in a second. What do you think? Are the big boys going to be able to make this transition? >> I think they have to, their hand is already dealt. I call it, the cloud is a runaway train, the cloud today is 30, 40 billion dollars. If you are those mega-vendors, you don't, if you're not making on this, something is wrong with you. Right? I mean, in this day and age, if you're not making money on the cloud, with this, with what we're talking about. So what they do is, how can they, either they, have to offer a cloud services, public or a PERT. If you are not doing that, might as well get into this game of AIOps, so that you are actually making money on the apps, and on the infrastructure. So, all those big, large vendors that you mentioned, about the Cisco's of the world, the Oracle's of the, they have a genuine interest to make this happen. >> Got it. So in many respects, to kind of summarize that point, it's like, look, the cloud experience is being defined elsewhere. It's being defined by Azure. AWS, Google, GCP, and these vendors are going to have to articulate very, very clearly for their customer base, the role that they're going to play. And that could include bringing the cloud experience on premise, when and if, data is required on premise. >> Absolutely, and I actually call this cloud should be the aircraft carriers, right? As a world when it settles, eventually it won't have hundred aircraft carriers. You'll have this three or four large cloud vendors. On top of them, the people who manage the apps and services will be few. You don't need 20 vendors managing your infrastructure. So there'll be a huge consolidation game. The questions is, when that happens, the winners doesn't have to be the like c-Vendors. >> Right. >> The history always show the legacy always loses out. So that's where the start-ups have an opportunity. >> Alright. So let's talk about the start-ups. Are there any particular class of start-ups out there. Is this going to, or are some of the security guys who manage services going to be able to do a better job, because they can make claims about your data? Or some of the guys, some of the companies coming from middleware? Where do you think the start-up kind of epicenter is going to be as we see new companies introduced in this space? >> That's a good question, I don't have any one particular vendor in mind. But I think that definitely the vendors that will come into play will be people who can do log management better. We already know the IS Splunk's of the world. People who can do events and alerts management. People who can do incident problem change management, right? All those things, if you look at the whole area. And people who can do the whole application management, as earlier you were talking about the workload management. So I think each of these functions, there'll be winners coming in. Eventually all of them will be offered by one single person, as a full-stack solution for the cloud, on the cloud. The key problem that I keep noticing is, most vendors are keep still tied to the old infrastructure, which is mainframe, or physical servers. Nobody is building this thing for the cloud, in the cloud again. So somebody who has the right substrate to build this, as a playbook, will end up winning this game. >> Yeah, it's going to be an interesting period of time. Now, when we stop and think about, I made an assertion earlier, that for us to build more complex applications, which is where everybody talking about, it's essential, in our opinion, that we find ways to simplify and bring more automation to the infrastructure. If we think about servers, storage, network, those type of things, is there a particular part of the infrastructure that you think is going to receive treatment earlier, and therefore is going to kind of lead the way for how, the rest of this stuff. Is storage going to show CPU, and network? Or is network going to step up, because some of the changes that are happening? What do you think? >> That's a very good question. I think, look, the key think the key pain points for most people today, if you look at the way the complex questions are, if there's a problem in the network infrastructure, it's very hard to triage that, so that area has to be automated. I mean, you can't expect a human being to understand why my switch or network is not performing. >> It's just happening too fast >> Why like, why WIFI is not working on sixth floor and seventh floor. It's a very, so network will be one area, it's highly visible. The second will be in the database and storage area. Just because my storage disk is full, I don't want my database to be down. It's such an old pattern behavior, People will catch those things in an automated manner. Right? So storage, network, because. Where you see the higher level items is when an application is not performing well. Is it a performance problem? Or, why this component is tied to what component, right? Is this applicant is built on a load balancer, and a load balancer is talking to, and the database. Building that map of who's-connected-to-who, that's a new graph, algorithms graph to the unit. That doesn't exist today. So I think what'll happen is how do you manage an application, given a problem, and mapping that. That is I think the number one, that will start happening first. Everything else, people will happen over a period of time. But the apps that are visible, where a user and a customer can see the impact, will happen first. >> Yeah, actually we have a prediction here at Wikibon, what we call networks of data. Where the idea that we're going to the next round of network formation is going to be data assets explicitly connecting with each other. And then using that as a way of zoning data assets. And saying, this application requires data from these places, and then all the technology that allows you to either move it in. >> Right. >> Or keep pointers, or whatever else it might be. So this notion, you would agree then. You know, a graph of data is going to drive a lot of the change forward. >> And to actually take you to that, I actually talk about saying it doesn't require a single class of algorithm. I call it an ensemble of machine learning algorithms you need. You need some statistical, some probablistic, some Markovian algortithm, some Bayesian, and mainly graph algorithms. This data has to capture the behaviors and patterns that you want to put in a larger graph, that you should be able to mine on. That doesn't exist today. So everybody is most often, when they talk about like their dynamic thresholding, statistical, that actually is there in idea operation management. The next level of how do you build a graph, like too big to fail, in my opinion fails. What is it relying on, like if I come to Peter's house. How is your house looks like, the area, one-bedroom, you have two kitchens, You know what I'm saying. >> It looks like a network of data right now. >> Exactly, right. (laughing) >> Okay, so, I got one more question for you, Muddu. And that is, you work with us a lot, and some of the crowd chats you do. You're a great research partner for us. As you think about kind of the story that needs to be told to the CxO about some of these changes, how's it different from the story that needs to be told to the DI team leader? I can imagine what some of the differences are, but you're talking to both sides. What would you, what would you're advice and counsel be to companies that are trying to talk to the CEO about this, or the board, what do you think? What would you say to 'em? >> I think you kind of got it yesterday in the crowd chat. I think the key thing that the CIO or CxO or CEO needs to have this is, we used to call it Chief Data Officer, where the data is the key, that delimit was applied for the overall business. That same role needs to happen within the CIO now. How do I use my data to make my IT better? So that, maybe call it a CIO, a CDO for the CIO, is a big role that needs to happen, but the goal of that person and that entity should be is, How can you do, can I run my operation in a light sort manner? I call it IT as a service. People talk about IT and service. But IT as a service to me, is a bigger concept. >> Let me make sure I got this, 'cause this is crucially important point. So in many respects, we should be saying to the CEO, your data is an asset, you have to take steps to appreciate, dramatically and rapidly, appreciate the value of data as an asset, and that requires looking at the CIO with the CDO, data officer, and saying, your job, independent of any technology or any particular set of ITOM processes, your job is to dramatically accelerate how fast we're able to generate data. >> During decisions. >> Value out of our data being able to utilize these technology investments. >> Absolutely. Because that person, once you have the data as addition, what will happen is, you'll still use the existing process, but it gets you the new insight, What can I automate? What can I do more with less people, right? That has to happen, like if I'm a CEO, he should wake up and say, 90% of my things should be able to automate today, right? >> Okay, so let's talk about last question. You've been, you've led a lot of organizations through a lot of change. We're talking about a lot of change within the IT organization, when we talk about these things. What's one bit of advice that you have for that CIO or leader of IT, and help them take their people through the types of changes that we're talking about? >> Make bets. Don't be afraid of making bets, unless you make a bet you're never going to win. So every year, every quarter, make a new bet. Some bets, you are going to fail, some you're going to succeed. Unless you make a bet, you will not innovate. >> Peter: And understand the portfolio, and sustain those bets. And then, when you've lost, don't keep putting money out. >> Exactly, yeah, keep moving on. >> Great. Alright, so, Muddu, thank you very much for being here. >> Peter, always a pleasure. >> Alright, Muddu Sadhakar, investor, CEO, once again, this has been a CUBEConversation, thank you very much for being here. >> Thank you, Peter. >> And we'll talk to you soon. >> Muddu: Thank you always, and John too. (upbeat music)

(gentle music) >> From the Cube Studios in Palo Alto and Boston, connecting with thought leaders all around the world. This is theCube Conversation. >> Hi everybody, this is Dave Vellante, we're back at Cube on Cloud, and with me is Muddu Sudhakar. He's a long time alum of theCube, a technologist and executive, a serial entrepreneur and an investor. Welcome my friend, good to see you. >> Good to see you, Dave. Pleasure to be with you. Happy elections, I guess. >> Yeah, yeah. So I wanted to start, this work from home, pivot's been amazing, and you've seen the enterprise collaboration explode. I wrote a piece a couple months ago, looking at valuations of various companies, right around the snowflake IPO, I want to ask you about that, but I was looking at the valuations of various companies, at Spotify, and Shopify, and of course Zoom was there. And I was looking at just simple revenue multiples, and I said, geez, Zoom actually looks, might look undervalued, which is crazy, right? And of course the stock went up after that, and you see teams, Microsoft Teams, and Microsoft doing a great job across the board, we've written about that, you're seeing Webex is exploding, I mean, what do you make of this whole enterprise collaboration play? >> No, I think the look there is a trend here, right? So I think this probably trend started before COVID, but COVID is going to probably accelerate this whole digital transformation, right? People are going to work remotely a lot more, not everybody's going to come back to the offices even after COVID, so I think this whole collaboration through Slack, and Zoom, and Microsoft Teams and Webex, it's going to be the new game now, right? Both the video, audio and chat solutions, that's really going to help people like eyeballs. You're not going to spend time on all four of them, right? It's like everyday from a consumer side, you're going to spend time on your Gmail, Facebook, maybe Twitter, maybe Instagram, so like in the consumer side, on your personal life, you have something on the enterprise. The eyeballs are going to be in these platforms. >> Yeah. Well. >> But we're not going to take everything. >> Well, So you are right, there's a permanence to this, and I got a lot of ground to cover with you. And I always like our conversations mood because you tell it like it is, I'm going to stay on that work from home pivot. You know a lot about security, but you've seen three big trends, like mega trends in security, Endpoint, Identity Access Management, and Cloud Security, you're seeing this in the stock prices of companies like CrowdStrike, Zscaler, Okta- >> Right >> Sailpoint- >> Right, I mean, they exploded, as a result of the pandemic, and I think I'm inferring from your comment that you see that as permanent, but that's a real challenge from a security standpoint. What's the impact of Cloud there? >> No, it isn't impact but look, first is all the services required to be Cloud, right? See, the whole ideas for it to collaborate and do these things. So you cannot be running an application, like you can't be running conference and SharePoint oN-Prem, and try to on a Zoom and MS teams. So that's why, if you look at Microsoft is very clever, they went with Office 365, SharePoint 365, now they have MS Teams, so I think that Cloud is going to drive all these workloads that you have been talking about a lot, right? You and John have been saying this for years now. The eruption of Cloud and SAS services are the vehicle to drive this next-generation collaboration. >> You know what's so cool? So Cloud obviously is the topic, I wonder how you look at the last 10 years of Cloud, and maybe we could project forward, I mean the big three Cloud vendors, they're running it like $20 billion a quarter, and they're growing collectively, 35, 40% clips, so we're really approaching a hundred billion dollars for these three. And you hear stats like only 20% of the workloads are in the public Cloud, so it feels like we're just getting started. How do you look at the impact of Cloud on the market, as you say, the last 10 years, and what do you expect going forward? >> No, I think it's very fascinating, right? So I remember when theCube, you guys are talking about 10 years back, now it's been what? More than 10 years, 15 years, since AWS came out with their first S3 service back in 2006. >> Right. >> Right? so I think look, Cloud is going to accelerate even more further. The areas is going to accelerate is for different reasons. I think now you're seeing the initial days, it's all about startups, initial workloads, Dev test and QA test, now you're talking about real production workloads are moving towards Cloud, right? Initially it was backup, we really didn't care for backup they really put there. Now you're going to have Cloud health primary services, your primary storage will be there, it's not going to be an EMC, It's not going to be a NetApp storage, right? So workloads are going to shift from the business applications, and these business applications, will be running on the Cloud, and I'll make another prediction, make customer service and support. Customer service and support, again, we should be running on the Cloud. You're not want to run the thing on a Dell server, or an IBM server, or an HP server, with your own hosted environment. That model is not because there's no economies of scale. So to your point, what will drive Cloud for the next 10 years, will be economies of scale. Where can you take the cost? How can I save money? If you don't move to the Cloud, you won't save money. So all those workloads are going to go to the Cloud are people who really want to save, like global gradual custom, right? If you stay on the ASP model, a hosted, you're not going to save your costs, your costs will constantly go up from a SaaS perspective. >> So that doesn't bode well for all the On-prem guys, and you hear a lot of the vendors that don't own a Cloud that talk about repatriation, but the numbers don't support that. So what do those guys do? I mean, they're talking multi-Cloud, of course they're talking hybrid, that's IBM's big play, how do you see it? >> I think, look, see there, to me, multi-Cloud makes sense, right? You don't want one vendor that you never want to get, so having Amazon, Microsoft, Google, it gives them a multi-Cloud. Even hybrid Cloud does make sense, right? There'll be some workloads. It's like, we are still running On-prem environment, we still have mainframe, so it's never going to be a hundred percent, but I would say the majority, your question is, can we get to 60, 70, 80% workers in the next 10 years? I think you will. I think by 2025, more than 78% of the Cloud Migration by the next five years, 70% of workload for enterprise will be on the Cloud. The remaining 25, maybe Hybrid, maybe On-prem, but I get panics, really doesn't matter. You have saved and part of your business is running on the Cloud. That's your cost saving, that's where you'll see the economies of scale, and that's where all the growth will happen. >> So square the circle for me, because again, you hear the stat on the IDC stat, IBM Ginni Rometty puts it out there a lot that only 20% of the workloads are in the public Cloud, everything else is On-prem, but it's not a zero sum game, right? I mean the Cloud native stuff is growing like crazy, the On-prem stuff is flat to down, so what's going to happen? When you talk about 70% of the workloads will be in the Cloud, do you see those mission critical apps and moving into the car, I mean the insurance companies going to put their claims apps in the Cloud, or the financial services companies going to put their mission critical workloads in the Cloud, or they just going to develop new stuff that's Cloud native that is sort of interacts with the On-prem. How do you see that playing out? >> Yeah, no, I think absolutely, I think a very good question. So two things will happen. I think if you take an enterprise, right? Most businesses what they'll do is the workloads that they should not be running On-prem, they'll move it up. So obviously things like take, as I said, I use the word SharePoint, right? SharePoint and conference, all the knowledge stuff is still running on people's data centers. There's no reason. I understand, I've seen statistics that 70, 80% of the On-prem for SharePoint will move to SharePoint on the Cloud. So Microsoft is going to make tons of money on that, right? Same thing, databases, right? Whether it's CQL server, whether there is Oracle database, things that you are running as a database, as a Cloud, we move to the Cloud. Whether that is posted in Oracle Cloud, or you're running Oracle or Mongo DB, or Dynamo DB on AWS or SQL server Microsoft, that's going to happen. Then what you're talking about is really the App concept, the applications themselves, the App server. Is the App server is going to run On-prem, how much it's going to laureate outside? There may be a hybrid Cloud, like for example, Kafka. I may use a Purse running on a Kafka as a service, or I may be using Elasticsearch for my indexing on AWS or Google Cloud, but I may be running my App locally. So there'll be some hybrid place, but what I would say is for every application, 75% of your Comprende will be on the Cloud. So think of it like the Dev. So even for the On-prem app, you're not going to be a 100 percent On-prem. The competent, the billing materials will move to the Cloud, your Purse, your storage, because if you put it On-prem, you need to add all this, you need to have all the whole things to buy it and hire the people, so that's what is going to happen. So from a competent perspective, 70% of your bill of materials will move to the Cloud, even for an On-prem application. >> So, Of course, the susification of the industry in the last decade and in my three favorite companies last decade, you've worked for two of them, Tableau, ServiceNow, and Splunk. I want to ask you about those, but I'm interested in the potential disruption there. I mean, you've got these SAS companies, Salesforce of course is another one, but they can't get started in 1999. What do you see happening with those? I mean, we're basically building these sort of large SAS, platforms, now. Do you think that the Cloud native world that developers can come at this from an angle where they can disrupt those companies, or are they too entrenched? I mean, look at service now, I mean, I don't know, $80 billion market capital where they are, they bigger than Workday, I mean, just amazing how much they've grown and you feel like, okay, nothing can stop them, but there's always disruption in this industry, what are your thoughts on that. >> Not very good with, I think there'll be disrupted. So to me actually to your point, ServiceNow is now close to a 100 billion now, 95 billion market coverage, crazy. So from evaluation perspective, so I think the reason they'll be disrupted is that the SAS vendors that you talked about, ServiceNow, and all this plan, most of these services, they're truly not a multi-tenant or what do you call the Cloud Native. And that is the Accenture. So because of that, they will not be able to pass the savings back to the enterprises. So the cost economics, the economics that the Cloud provides because of the multi tenancy ability will not. The second reason there'll be disrupted is AI. So far, we talked about Cloud, but AI is the core. So it's not really Cloud Native, Dave, I look at the AI in a two-piece. AI is going to change, see all the SAS vendors were created 20 years back, if you remember, was an operator typing it, I don't respond administered we'll type a Splunk query. I don't need a human to type a query anymore, system will actually find it, that's what the whole security game has changed, right? So what's going to happen is if you believe in that, that AI, your score will disrupt all the SAS vendors, so one angle SAS is going to have is a Cloud. That's where you make the Cloud will take up because a SAS application will be Cloudified. Being SAS is not Cloud, right? Second thing is SAS will be also, I call it, will be AI-fied. So AI and machine learning will be trying to drive at the core so that I don't need that many licenses. I don't need that many humans. I don't need that many administrators to manage, I call them the tuners. Once you get a driverless car, you don't need a thousand tuners to tune your Tesla, or Google Waymo car. So the same philosophy will happen is your Dev Apps, your administrators, your service management, people that you need for service now, and these products, Zendesk with AI, will tremendously will disrupt. >> So you're saying, okay, so yeah, I was going to ask you, won't the SAS vendors, won't they be able to just put, inject AI into their platforms, and I guess I'm inferring saying, yeah, but a lot of the problems that they're solving, are going to go away because of AI, is that right? And automation and RPA and things of that nature, is that right? >> Yes and no. So I'll tell you what, sorry, you have asked a very good question, let's answer, let me rephrase that question. What you're saying is, "Why can't the existing SAS vendors do the AI?" >> Yes, right. >> Right, >> And there's a reason they can't do it is their pricing model is by number of seats. So I'm not going to come to Dave, and say, come on, come pay me less money. It's the same reason why a board and general lover build an electric car. They're selling 10 million gasoline cars. There's no incentive for me, I'm not going to do any AI, I'm going to put, I'm not going to come to you and say, hey, buy me a hundred less license next year from it. So that is one reason why AI, even though these guys do any AI, it's going to be just so I call it, they're going to, what do you call it, a whitewash, kind of like you put some paint brush on it, trying to show you some AI you did from a marketing dynamics. But at the core, if you really implement the AI with you take the driver out, how are you going to change the pricing model? And being a public company, you got to take a hit on the pricing model and the price, and it's going to have a stocking part. So that, to your earlier question, will somebody disrupt them? The person who is going to disrupt them, will disrupt them on the pricing model. >> Right. So I want to ask you about that, because we saw a Snowflake, and it's IPO, we were able to pour through its S-1, and they have a different pricing model. It's a true Cloud consumption model, Whereas of course, most SAS companies, they're going to lock you in for at least one year term, maybe more, and then, you buy the license, you got to pay X. If you, don't use it, you still got to pay for it. Snowflake's different, actually they have a different problem, that people are using it too much and the sea is driving the CFO crazy because the bill is going up and up and up, but to me, that's the right model, It's just like the Amazon model, if you can justify it, so how do you see the pricing, that consumption model is actually, you're seeing some of the On-prem guys at HPE, Dell, they're doing as a service. They're kind of taking a page out of the last decade SAS model, so I think pricing is a real tricky one, isn't it? >> No, you nailed it, you nailed it. So I think the way in which the Snowflake there, how the disruptors are data warehouse, that disrupted the open source vendors too. Snowflake distributed, imagine the playbook, you disrupted something as the $ 0, right? It's an open source with Cloudera, Hortonworks, Mapper, that whole big data that you want me to, or that market is this, that disrupting data warehouses like Netezza, Teradata, and the charging more money, they're making more money and disrupting at $0, because the pricing models by consumption that you talked about. CMT is going to happen in the service now, Zen Desk, well, 'cause their pricing one is by number of seats. People are going to say, "How are my users are going to ask?" right? If you're an employee help desk, you're back to your original health collaborative. I may be on Slack, I could be on zoom, I'll maybe on MS Teams, I'm going to ask by using usage model on Slack, tools by employees to service now is the pricing model that people want to pay for. The more my employees use it, the more value I get. But I don't want to pay by number of seats, so the vendor, who's going to figure that out, and that's where I look, if you know me, I'm right over as I started, that's what I've tried to push that model look, I love that because that's the core of how you want to change the new game. >> I agree. I say, kill me with that problem, I mean, some people are trying to make it a criticism, but you hit on the point. If you pay more, it's only because you're getting more value out of it. So I wanted to flip the switch here a little bit and take a customer angle. Something that you've been on all sides. And I want to talk a little bit about strategies, you've been a strategist, I guess, once a strategist, always a strategist. How should organizations be thinking about their approach to Cloud, it's cost different for different industries, but, back when the cube started, financial services Cloud was a four-letter word. But of course the age of company is going to matter, but what's the framework for figuring out your Cloud strategy to get to your 70% and really take advantage of the economics? Should I be Mono Cloud, Multi-Cloud, Multi-vendor, what would you advise? >> Yeah, no, I mean, I mean, I actually call it the tech stack. Actually you and John taught me that what was the tech stack, like the lamp stack, I think there is a new Cloud stack needs to come, and that I think the bottomline there should be... First of all, anything with storage should be in the Cloud. I mean, if you want to start, whether you are, financial, doesn't matter, there's no way. I come from cybersecurity side, I've seen it. Your attackers will be more with insiders than being on the Cloud, so storage has to be in the Cloud then come compute, Kubernetes. If you really want to use containers and Kubernetes, it has to be in the public Cloud, leverage that have the computer on their databases. That's where it can be like if your data is so strong, maybe run it On-prem, maybe have it on a hosted model for when it comes to database, but there you have a choice between hybrid Cloud and public Cloud choice. Then on top when it comes to App, the app itself, you can run locally or anywhere, the App and database. Now the areas that you really want to go after to migrate is look at anything that's an enterprise workload that you don't need people to manage it. You want your own team to move up in the career. You don't want thousand people looking at... you don't want to have a, for example, IT administrators to call central people to the people to manage your compute storage. That workload should be more, right? You already saw Sierra moved out to Salesforce. We saw collaboration already moved out. Zoom is not running locally. You already saw SharePoint with knowledge management mode up, right? With a box, drawbacks, you name anything. The next global mode is a SAS workloads, right? I think Workday service running there, but work data will go into the Cloud. I bet at some point Zendesk, ServiceNow, then either they put it on the public Cloud, or they have to create a product and public Cloud. To your point, these public Cloud vendors are at $2 trillion market cap. They're they're bigger than the... I call them nation States. >> Yeah, >> So I'm servicing though. I mean, there's a 2 trillion market gap between Amazon and Azure, I'm not going to compete with them. So I want to take this workload to run it there. So all these vendors, if you see that's where Shandra from Adobe is pushing this right, Adobe, Workday, Anaplan, all the SAS vendors we'll move them into the public Cloud within these vendors. So those workloads need to move out, right? So that all those things will start, then you'll start migrating, but I call your procurement. That's where the RPA comes in. The other thing that we didn't talk about, back to your first question, what is the next 10 years of Cloud will be RPA? That third piece to Cloud is RPA because if you have your systems On-prem, I can't automate them. I have to do a VPN into your house there and then try to automate your systems, or your procurement, et cetera. So all these RPA vendors are still running On-prem, most of them, whether it's UI path automation anywhere. So the Cloud should be where the brain should be. That's what I call them like the octopus analogy, the brain is in the Cloud, the tentacles are everywhere, they should manage it. But if my tentacles have to do a VPN with your house to manage it, I'm always will have failures. So if you look at the why RPA did not have the growth, like the Snowflake, like the Cloud, because they are running it On-prem, most of them still. 80% of the RP revenue is On-prem, running On-prem, that needs to be called clarified. So AI, RPA and the SAS, are the three reasons Cloud will take off. >> Awesome. Thank you for that. Now I want to flip the switch again. You're an investor or a multi-tool player here, but so if you're, let's say you're an ecosystem player, and you're kind of looking at the landscape as you're in an investor, of course you've invested in the Cloud, because the Cloud is where it's at, but you got to be careful as an ecosystem player to pick a spot that both provides growth, but allows you to have a moat as, I mean, that's why I'm really curious to see how Snowflake's going to compete because they're competing with AWS, Microsoft, and Google, unlike, Frank, when he was at service now, he was competing with BMC and with on-prem and he crushed it, but the competitors are much more capable here, but it seems like they've got, maybe they've got a moat with MultiCloud, and that whole data sharing thing, we'll see. But, what about that? Where are the opportunities? Where's that white space? And I know there's a lot of white space, but what's the framework to look at, from an investor standpoint, or even a CEO standpoint, where you want to put place your bets. >> No, very good question, so look, I did something. We talk as an investor in the board with many companies, right? So one thing that says as an investor, if you come back and say, I want to create a next generation Docker or a computer, there's no way nobody's going to invest. So that we can motor off, even if you want to do object storage or a block storage, I mean, I've been an investor board member of so many storage companies, there's no way as an industry, I'll write a check for a compute or storage, right? If you want to create a next generation network, like either NetSuite, or restart Juniper, Cisco, there is no way. But if you come back and say, I want to create a next generation Viper for remote working environments, where AI is at the core, I'm interested in that, right? So if you look at how the packets are dropped, there's no intelligence in either not switching today. The packets come, I do it. The intelligence is not built into the network with AI level. So if somebody comes with an AI, what good is all this NVD, our GPS, et cetera, if you cannot do wire speed, packet inspection, looking at the content and then route the traffic. If I see if it's a video package, but in UN Boston, there's high interview day of they should be loading our package faster, because you are a premium ISP. That intelligence has not gone there. So you will see, and that will be a bad people will happen in the network, switching, et cetera, right? So that is still an angle. But if you work and it comes to platform services, remember when I was at Pivotal and VMware, all models was my boss, that would, yes, as a platform, service is a game already won by the Cloud guys. >> Right. (indistinct) >> Silicon Valley Investors, I don't think you want to invest in past services, right? I mean, you might come with some lecture edition database to do some updates, there could be some game, let's say we want to do a time series database, or some metrics database, there's always some small angle, but the opportunity to go create a national database there it's very few. So I'm kind of eliminating all the black spaces, right? >> Yeah. >> We have the white spaces that comes in is the SAS level. Now to your point, if I'm Amazon, I'm going to compete with Snowflake, I have Redshift. So this is where at some point, these Cloud platforms, I call them aircraft carriers. They're not going to stay on the aircraft carriers, they're going to own the land as well. So they're going to move up to the SAS space. The question is you want to create a SAS service like CRM. They are not going to create a CRM like service, they may not create a sales force and service now, but if you're going to add a data warehouse, I can very well see Azure, Google, and AWS, going to create something to compute a Snowflake. Why would I not? It's so close to my database and data warehouse, I already have Redshift. So that's going to be nightlights, same reason, If you look at Netflix, you have a Netflix and you have Amazon prime. Netflix runs on Amazon, but you have Amazon prime. So you have the same model, you have Snowflake, and you'll have Redshift. The both will help each other, there'll be a... What do you call it? Coexistence will happen. But if you really want to invest, you want to invest in SAS companies. You do not want to be investing in a compliment players. You don't want to a feature. >> Yeah, that's great, I appreciate that perspective. And I wonder, so obviously Microsoft play in SAS, Google's got G suite. And I wonder if people often ask the Andy Jassy, you're going to move up the stack, you got to be an application, a SAS vendor, and you never say never with Atavist, But I wonder, and we were talking to Jerry Chen about this, years ago on theCube, and his angle was that Amazon will play, but they'll play through developers. They'll enable developers, and they'll participate, they'll take their, lick off the cone. So it's going to be interesting to see how directly Amazon plays, but at some point you got Tam expansion, you got to play in that space. >> Yeah, I'll give you an example of knowing, I got acquired by a couple of times by EMC. So I learned a lot from Joe Tucci and Paul Merage over the years. see Paul and Joe, what they did is to look at how 20 years, and they are very close to Boston in your area, Joe, what games did is they used to sell storage, but you know what he did, he went and bought the Apps to drive them. He bought like Legato, he bought Documentum, he bought Captiva, if you remember how he acquired all these companies as a services, he bought VMware to drive that. So I think the good angle that Microsoft has is, I'm a SAS player, I have dynamics, I have CRM, I have SharePoint, I have Collaboration, I have Office 365, MS Teams for users, and then I have the platform as Azure. So I think if I'm Amazon, (indistinct). I got to own the apps so that I can drive this workforce on my platform. >> Interesting. >> Just going to developers, like I know Jerry Chan, he was my peer a BMF. I don't think just literally to developers and that model works in open source, but the open source game is pretty much gone, and not too many companies made money. >> Well, >> Most companies pretty much gone. >> Yeah, he's right. Red hats not bad idea. But it's very interesting what you're saying there. And so, hey, its why Oracle wants to have Tiktok, running on their platform, right? I mean, it's going to. (laughing) It's going to drive that further integration. I wanted to ask you something, you were talking about, you wouldn't invest in storage or compute, but I wonder, and you mentioned some commentary about GPU's. Of course the videos has been going crazy, but they're now saying, okay, how do we expand our Team, they make the acquisition of arm, et cetera. What about this DPU thing, if you follow that, that data processing unit where they're like hyper dis-aggregation and then they reaggregate, and as an offload and really to drive data centric workloads. Have you looked at that at all? >> I did, I think, and that's a good angle. So I think, look, it's like, it goes through it. I don't know if you remember in your career, we have seen it. I used to get Silicon graphics. I saw the first graphic GPU, right? That time GPU was more graphic processor unit, >> Right, yeah, work stations. >> So then become NPUs at work processing units, right? There was a TCP/IP office offloading, if you remember right, there was like vector processing unit. So I think every once in a while the industry, recreated this separate unit, as a co-processor to the main CPU, because main CPU's inefficient, and it makes sense. And then Google created TPU's and then we have the new world of the media GPU's, now we have DPS all these are good, but what's happening is, all these are driving for machine learning, AI for the training period there. Training period Sometimes it's so long with the workloads, if you can cut down, it makes sense. >> Yeah. >> Because, but the question is, these aren't so specialized in nature. I can't use it for everything. >> Yup. >> I want Ideally, algorithms to be paralyzed, I want the training to be paralyzed, I want so having deep use and GPS are important, I think where I want to see them as more, the algorithm, there should be more investment from the NVIDIA's and these guys, taking the algorithm to be highly paralyzed them. (indistinct) And I think that still has not happened in industry yet. >> All right, so we're pretty much out of time, but what are you doing these days? Where are you spending your time, are you still in Stealth, give us a little glimpse. >> Yeah, no, I'm out of the Stealth, I'm actually the CEO of Aisera now, Aisera, obviously I invested with them, but I'm the CEO of Aisero. It's funded by Menlo ventures, Norwest, True, along with Khosla ventures and Ram Shriram is a big investor. Robin's on the board of Google, so these guys, look, we are going out to the collaboration game. How do you automate customer service and support for employees and then users, right? In this whole game, we talked about the Zoom, Slack and MS Teams, that's what I'm spending time, I want to create next generation service now. >> Fantastic. Muddu, I always love having you on you, pull punches, you tell it like it is, that you're a great visionary technologist. Thanks so much for coming on theCube, and participating in our program. >> Dave, it's always a pleasure speaking to you sir. Thank you. >> Okay. Keep it right there, there's more coming from Cuba and Cloud right after this break. (slow music)

(gentle music) >> From the Cube Studios in Palo Alto and Boston, connecting with thought leaders all around the world. This is theCube Conversation. >> Hi everybody, this is Dave Vellante, we're back at Cube on Cloud, and with me is Muddu Sudhakar. He's a long time alum of theCube, a technologist and executive, a serial entrepreneur and an investor. Welcome my friend, good to see you. >> Good to see you, Dave. Pleasure to be with you. Happy elections, I guess. >> Yeah, yeah. So I wanted to start, this work from home, pivot's been amazing, and you've seen the enterprise collaboration explode. I wrote a piece a couple months ago, looking at valuations of various companies, right around the snowflake IPO, I want to ask you about that, but I was looking at the valuations of various companies, at Spotify, and Shopify, and of course Zoom was there. And I was looking at just simple revenue multiples, and I said, geez, Zoom actually looks, might look undervalued, which is crazy, right? And of course the stock went up after that, and you see teams, Microsoft Teams, and Microsoft doing a great job across the board, we've written about that, you're seeing Webex is exploding, I mean, what do you make of this whole enterprise collaboration play? >> No, I think the look there is a trend here, right? So I think this probably trend started before COVID, but COVID is going to probably accelerate this whole digital transformation, right? People are going to work remotely a lot more, not everybody's going to come back to the offices even after COVID, so I think this whole collaboration through Slack, and Zoom, and Microsoft Teams and Webex, it's going to be the new game now, right? Both the video, audio and chat solutions, that's really going to help people like eyeballs. You're not going to spend time on all four of them, right? It's like everyday from a consumer side, you're going to spend time on your Gmail, Facebook, maybe Twitter, maybe Instagram, so like in the consumer side, on your personal life, you have something on the enterprise. The eyeballs are going to be in these platforms. >> Yeah. Well. >> But we're not going to take everything. >> Well, So you are right, there's a permanence to this, and I got a lot of ground to cover with you. And I always like our conversations mood because you tell it like it is, I'm going to stay on that work from home pivot. You know a lot about security, but you've seen three big trends, like mega trends in security, Endpoint, Identity Access Management, and Cloud Security, you're seeing this in the stock prices of companies like CrowdStrike, Zscaler, Okta- >> Right >> Sailpoint- >> Right, I mean, they exploded, as a result of the pandemic, and I think I'm inferring from your comment that you see that as permanent, but that's a real challenge from a security standpoint. What's the impact of Cloud there? >> No, it isn't impact but look, first is all the services required to be Cloud, right? See, the whole ideas for it to collaborate and do these things. So you cannot be running an application, like you can't be running conference and SharePoint oN-Prem, and try to on a Zoom and MS teams. So that's why, if you look at Microsoft is very clever, they went with Office 365, SharePoint 365, now they have MS Teams, so I think that Cloud is going to drive all these workloads that you have been talking about a lot, right? You and John have been saying this for years now. The eruption of Cloud and SAS services are the vehicle to drive this next-generation collaboration. >> You know what's so cool? So Cloud obviously is the topic, I wonder how you look at the last 10 years of Cloud, and maybe we could project forward, I mean the big three Cloud vendors, they're running it like $20 billion a quarter, and they're growing collectively, 35, 40% clips, so we're really approaching a hundred billion dollars for these three. And you hear stats like only 20% of the workloads are in the public Cloud, so it feels like we're just getting started. How do you look at the impact of Cloud on the market, as you say, the last 10 years, and what do you expect going forward? >> No, I think it's very fascinating, right? So I remember when theCube, you guys are talking about 10 years back, now it's been what? More than 10 years, 15 years, since AWS came out with their first S3 service back in 2006. >> Right. >> Right? so I think look, Cloud is going to accelerate even more further. The areas is going to accelerate is for different reasons. I think now you're seeing the initial days, it's all about startups, initial workloads, Dev test and QA test, now you're talking about real production workloads are moving towards Cloud, right? Initially it was backup, we really didn't care for backup they really put there. Now you're going to have Cloud health primary services, your primary storage will be there, it's not going to be an EMC, It's not going to be a ETAP storage, right? So workloads are going to shift from the business applications, and this business App again, will be running on the Cloud, and I'll make another prediction, make customer service and support. Customer service and support, again, we should be running on the Cloud. You're not want to run the thing on a Dell server, or an IBM server, or an HP server, with your own hosted environment. That model is not because there's no economies of scale. So to your point, what will drive Cloud for the next 10 years, will be economies of scale. Where can you take the cost? How can I save money? If you don't move to the Cloud, you won't save money. So all those workloads are going to go to the Cloud are people who really want to save, like global gradual custom, right? If you stay on the ASP model, a hosted, you're not going to save your costs, your costs will constantly go up from a SAS perspective. >> So that doesn't bode well for all the On-prem guys, and you hear a lot of the vendors that don't own a Cloud that talk about repatriation, but the numbers don't support that. So what do those guys do? I mean, they're talking multi-Cloud, of course they're talking hybrid, that's IBM's big play, how do you see it? >> I think, look, see there, to me, multi-Cloud makes sense, right? You don't want one vendor that you never want to get, so having Amazon, Microsoft, Google, it gives them a multi-Cloud. Even hybrid Cloud does make sense, right? There'll be some workloads. It's like, we are still running On-prem environment, we still have mainframe, so it's never going to be a hundred percent, but I would say the majority, your question is, can we get to 60, 70, 80% workers in the next 10 years? I think you will. I think by 2025, more than 78% of the Cloud Migration by the next five years, 70% of workload for enterprise will be on the Cloud. The remaining 25, maybe Hybrid, maybe On-prem, but I get panics, really doesn't matter. You have saved and part of your business is running on the Cloud. That's your cost saving, that's where you'll see the economies of scale, and that's where all the growth will happen. >> So square the circle for me, because again, you hear the stat on the IDC stat, IBM Ginni Rometty puts it out there a lot that only 20% of the workloads are in the public Cloud, everything else is On-prem, but it's not a zero sum game, right? I mean the Cloud native stuff is growing like crazy, the On-prem stuff is flat to down, so what's going to happen? When you talk about 70% of the workloads will be in the Cloud, do you see those mission critical apps and moving into the car, I mean the insurance companies going to put their claims apps in the Cloud, or the financial services companies going to put their mission critical workloads in the Cloud, or they just going to develop new stuff that's Cloud native that is sort of interacts with the On-prem. How do you see that playing out? >> Yeah, no, I think absolutely, I think a very good question. So two things will happen. I think if you take an enterprise, right? Most businesses what they'll do is the workloads that they should not be running On-prem, they'll move it up. So obviously things like take, as I said, I use the word SharePoint, right? SharePoint and conference, all the knowledge stuff is still running on people's data centers. There's no reason. I understand, I've seen statistics that 70, 80% of the On-prem for SharePoint will move to SharePoint on the Cloud. So Microsoft is going to make tons of money on that, right? Same thing, databases, right? Whether it's CQL server, whether there is Oracle database, things that you are running as a database, as a Cloud, we move to the Cloud. Whether that is posted in Oracle Cloud, or you're running Oracle or Mongo DB, or Dynamo DB on AWS or SQL server Microsoft, that's going to happen. Then what you're talking about is really the App concept, the applications themselves, the App server. Is the App server is going to run On-prem, how much it's going to laureate outside? There may be a hybrid Cloud, like for example, Kafka. I may use a Purse running on a Kafka as a service, or I may be using Elasticsearch for my indexing on AWS or Google Cloud, but I may be running my App locally. So there'll be some hybrid place, but what I would say is for every application, 75% of your Comprende will be on the Cloud. So think of it like the Dev. So even for the On-prem app, you're not going to be a 100 percent On-prem. The competent, the billing materials will move to the Cloud, your Purse, your storage, because if you put it On-prem, you need to add all this, you need to have all the whole things to buy it and hire the people, so that's what is going to happen. So from a competent perspective, 70% of your bill of materials will move to the Cloud, even for an On-prem application. >> So, Of course, the susification of the industry in the last decade and in my three favorite companies last decade, you've worked for two of them, Tableau, ServiceNow, and Splunk. I want to ask you about those, but I'm interested in the potential disruption there. I mean, you've got these SAS companies, Salesforce of course is another one, but they can't get started in 1999. What do you see happening with those? I mean, we're basically building these sort of large SAS, platforms, now. Do you think that the Cloud native world that developers can come at this from an angle where they can disrupt those companies, or are they too entrenched? I mean, look at service now, I mean, I don't know, $80 billion market capital where they are, they bigger than Workday, I mean, just amazing how much they've grown and you feel like, okay, nothing can stop them, but there's always disruption in this industry, what are your thoughts on that. >> Not very good with, I think there'll be disrupted. So to me actually to your point, ServiceNow is now close to a 100 billion now, 95 billion market coverage, crazy. So from evaluation perspective, so I think the reason they'll be disrupted is that the SAS vendors that you talked about, ServiceNow, and all this plan, most of these services, they're truly not a multi-tenant or what do you call the Cloud Native. And that is the Accenture. So because of that, they will not be able to pass the savings back to the enterprises. So the cost economics, the economics that the Cloud provides because of the multi tenancy ability will not. The second reason there'll be disrupted is AI. So far, we talked about Cloud, but AI is the core. So it's not really Cloud Native, Dave, I look at the AI in a two-piece. AI is going to change, see all the SAS vendors were created 20 years back, if you remember, was an operator typing it, I don't respond administered we'll type a Splunk query. I don't need a human to type a query anymore, system will actually find it, that's what the whole security game has changed, right? So what's going to happen is if you believe in that, that AI, your score will disrupt all the SAS vendors, so one angle SAS is going to have is a Cloud. That's where you make the Cloud will take up because a SAS application will be Cloudified. Being SAS is not Cloud, right? Second thing is SAS will be also, I call it, will be AI-fied. So AI and machine learning will be trying to drive at the core so that I don't need that many licenses. I don't need that many humans. I don't need that many administrators to manage, I call them the tuners. Once you get a driverless car, you don't need a thousand tuners to tune your Tesla, or Google Waymo car. So the same philosophy will happen is your Dev Apps, your administrators, your service management, people that you need for service now, and these products, Zendesk with AI, will tremendously will disrupt. >> So you're saying, okay, so yeah, I was going to ask you, won't the SAS vendors, won't they be able to just put, inject AI into their platforms, and I guess I'm inferring saying, yeah, but a lot of the problems that they're solving, are going to go away because of AI, is that right? And automation and RPA and things of that nature, is that right? >> Yes and no. So I'll tell you what, sorry, you have asked a very good question, let's answer, let me rephrase that question. What you're saying is, "Why can't the existing SAS vendors do the AI?" >> Yes, right. >> Right, >> And there's a reason they can't do it is their pricing model is by number of seats. So I'm not going to come to Dave, and say, come on, come pay me less money. It's the same reason why a board and general lover build an electric car. They're selling 10 million gasoline cars. There's no incentive for me, I'm not going to do any AI, I'm going to put, I'm not going to come to you and say, hey, buy me a hundred less license next year from it. So that is one reason why AI, even though these guys do any AI, it's going to be just so I call it, they're going to, what do you call it, a whitewash, kind of like you put some paint brush on it, trying to show you some AI you did from a marketing dynamics. But at the core, if you really implement the AI with you take the driver out, how are you going to change the pricing model? And being a public company, you got to take a hit on the pricing model and the price, and it's going to have a stocking part. So that, to your earlier question, will somebody disrupt them? The person who is going to disrupt them, will disrupt them on the pricing model. >> Right. So I want to ask you about that, because we saw a Snowflake, and it's IPO, we were able to pour through its S-1, and they have a different pricing model. It's a true Cloud consumption model, Whereas of course, most SAS companies, they're going to lock you in for at least one year term, maybe more, and then, you buy the license, you got to pay X. If you, don't use it, you still got to pay for it. Snowflake's different, actually they have a different problem, that people are using it too much and the sea is driving the CFO crazy because the bill is going up and up and up, but to me, that's the right model, It's just like the Amazon model, if you can justify it, so how do you see the pricing, that consumption model is actually, you're seeing some of the On-prem guys at HPE, Dell, they're doing as a service. They're kind of taking a page out of the last decade SAS model, so I think pricing is a real tricky one, isn't it? >> No, you nailed it, you nailed it. So I think the way in which the Snowflake there, how the disruptors are data warehouse, that disrupted the open source vendors too. Snowflake distributed, imagine the playbook, you disrupted something as the $ 0, right? It's an open source with Cloudera, Hortonworks, Mapper, that whole big data that you want me to, or that market is this, that disrupting data warehouses like Netezza, Teradata, and the charging more money, they're making more money and disrupting at $0, because the pricing models by consumption that you talked about. CMT is going to happen in the service now, Zen Desk, well, 'cause their pricing one is by number of seats. People are going to say, "How are my users are going to ask?" right? If you're an employee help desk, you're back to your original health collaborative. I may be on Slack, I could be on zoom, I'll maybe on MS Teams, I'm going to ask by using usage model on Slack, tools by employees to service now is the pricing model that people want to pay for. The more my employees use it, the more value I get. But I don't want to pay by number of seats, so the vendor, who's going to figure that out, and that's where I look, if you know me, I'm right over as I started, that's what I've tried to push that model look, I love that because that's the core of how you want to change the new game. >> I agree. I say, kill me with that problem, I mean, some people are trying to make it a criticism, but you hit on the point. If you pay more, it's only because you're getting more value out of it. So I wanted to flip the switch here a little bit and take a customer angle. Something that you've been on all sides. And I want to talk a little bit about strategies, you've been a strategist, I guess, once a strategist, always a strategist. How should organizations be thinking about their approach to Cloud, it's cost different for different industries, but, back when the cube started, financial services Cloud was a four-letter word. But of course the age of company is going to matter, but what's the framework for figuring out your Cloud strategy to get to your 70% and really take advantage of the economics? Should I be Mono Cloud, Multi-Cloud, Multi-vendor, what would you advise? >> Yeah, no, I mean, I mean, I actually call it the tech stack. Actually you and John taught me that what was the tech stack, like the lamp stack, I think there is a new Cloud stack needs to come, and that I think the bottomline there should be... First of all, anything with storage should be in the Cloud. I mean, if you want to start, whether you are, financial, doesn't matter, there's no way. I come from cybersecurity side, I've seen it. Your attackers will be more with insiders than being on the Cloud, so storage has to be in the Cloud and encompass compute whoever it is. If you really want to use containers and Kubernetes, it has to be in the public Cloud, leverage that have the computer on their databases. That's where it can be like if your data is so strong, maybe run it On-prem, maybe have it on a hosted model for when it comes to database, but there you have a choice between hybrid Cloud and public Cloud choice. Then on top when it comes to App, the app itself, you can run locally or anywhere, the App and database. Now the areas that you really want to go after to migrate is look at anything that's an enterprise workload that you don't need people to manage it. You want your own team to move up in the career. You don't want thousand people looking at... you don't want to have a, for example, IT administrators to call central people to the people to manage your compute storage. That workload should be more, right? You already saw Sierra moved out to Salesforce. We saw collaboration already moved out. Zoom is not running locally. You already saw SharePoint with knowledge management mode up, right? With a box, drawbacks, you name anything. The next global mode is a SAS workloads, right? I think Workday service running there, but work data will go into the Cloud. I bet at some point Zendesk, ServiceNow, then either they put it on the public Cloud, or they have to create a product and public Cloud. To your point, these public Cloud vendors are at $2 trillion market cap. They're they're bigger than the... I call them nation States. >> Yeah, >> So I'm servicing though. I mean, there's a 2 trillion market gap between Amazon and Azure, I'm not going to compete with them. So I want to take this workload to run it there. So all these vendors, if you see that's where Shandra from Adobe is pushing this right, Adobe, Workday, Anaplan, all the SAS vendors we'll move them into the public Cloud within these vendors. So those workloads need to move out, right? So that all those things will start, then you'll start migrating, but I call your procurement. That's where the RPA comes in. The other thing that we didn't talk about, back to your first question, what is the next 10 years of Cloud will be RPA? That third piece to Cloud is RPA because if you have your systems On-prem, I can't automate them. I have to do a VPN into your house there and then try to automate your systems, or your procurement, et cetera. So all these RPA vendors are still running On-prem, most of them, whether it's UI path automation anywhere. So the Cloud should be where the brain should be. That's what I call them like the octopus analogy, the brain is in the Cloud, the tentacles are everywhere, they should manage it. But if my tentacles have to do a VPN with your house to manage it, I'm always will have failures. So if you look at the why RPA did not have the growth, like the Snowflake, like the Cloud, because they are running it On-prem, most of them still. 80% of the RP revenue is On-prem, running On-prem, that needs to be called clarified. So AI, RPA and the SAS, are the three reasons Cloud will take off. >> Awesome. Thank you for that. Now I want to flip the switch again. You're an investor or a multi-tool player here, but so if you're, let's say you're an ecosystem player, and you're kind of looking at the landscape as you're in an investor, of course you've invested in the Cloud, because the Cloud is where it's at, but you got to be careful as an ecosystem player to pick a spot that both provides growth, but allows you to have a moat as, I mean, that's why I'm really curious to see how Snowflake's going to compete because they're competing with AWS, Microsoft, and Google, unlike, Frank, when he was at service now, he was competing with BMC and with on-prem and he crushed it, but the competitors are much more capable here, but it seems like they've got, maybe they've got a moat with MultiCloud, and that whole data sharing thing, we'll see. But, what about that? Where are the opportunities? Where's that white space? And I know there's a lot of white space, but what's the framework to look at, from an investor standpoint, or even a CEO standpoint, where you want to put place your bets. >> No, very good question, so look, I did something. We talk as an investor in the board with many companies, right? So one thing that says as an investor, if you come back and say, I want to create a next generation Docker or a computer, there's no way nobody's going to invest. So that we can motor off, even if you want to do object storage or a block storage, I mean, I've been an investor board member of so many storage companies, there's no way as an industry, I'll write a check for a compute or storage, right? If you want to create a next generation network, like either NetSuite, or restart Juniper, Cisco, there is no way. But if you come back and say, I want to create a next generation Viper for remote working environments, where AI is at the core, I'm interested in that, right? So if you look at how the packets are dropped, there's no intelligence in either not switching today. The packets come, I do it. The intelligence is not built into the network with AI level. So if somebody comes with an AI, what good is all this NVD, our GPS, et cetera, if you cannot do wire speed, packet inspection, looking at the content and then route the traffic. If I see if it's a video package, but in UN Boston, there's high interview day of they should be loading our package faster, because you are a premium ISP. That intelligence has not gone there. So you will see, and that will be a bad people will happen in the network, switching, et cetera, right? So that is still an angle. But if you work and it comes to platform services, remember when I was at Pivotal and VMware, all models was my boss, that would, yes, as a platform, service is a game already won by the Cloud guys. >> Right. (indistinct) >> Silicon Valley Investors, I don't think you want to invest in past services, right? I mean, you might come with some lecture edition database to do some updates, there could be some game, let's say we want to do a time series database, or some metrics database, there's always some small angle, but the opportunity to go create a national database there it's very few. So I'm kind of eliminating all the black spaces, right? >> Yeah. >> We have the white spaces that comes in is the SAS level. Now to your point, if I'm Amazon, I'm going to compete with Snowflake, I have Redshift. So this is where at some point, these Cloud platforms, I call them aircraft carriers. They're not going to stay on the aircraft carriers, they're going to own the land as well. So they're going to move up to the SAS space. The question is you want to create a SAS service like CRM. They are not going to create a CRM like service, they may not create a sales force and service now, but if you're going to add a data warehouse, I can very well see Azure, Google, and AWS, going to create something to compute a Snowflake. Why would I not? It's so close to my database and data warehouse, I already have Redshift. So that's going to be nightlights, same reason, If you look at Netflix, you have a Netflix and you have Amazon prime. Netflix runs on Amazon, but you have Amazon prime. So you have the same model, you have Snowflake, and you'll have Redshift. The both will help each other, there'll be a... What do you call it? Coexistence will happen. But if you really want to invest, you want to invest in SAS companies. You do not want to be investing in a compliment players. You don't want to a feature. >> Yeah, that's great, I appreciate that perspective. And I wonder, so obviously Microsoft play in SAS, Google's got G suite. And I wonder if people often ask the Andy Jassy, you're going to move up the stack, you got to be an application, a SAS vendor, and you never say never with Atavist, But I wonder, and we were talking to Jerry Chen about this, years ago on theCube, and his angle was that Amazon will play, but they'll play through developers. They'll enable developers, and they'll participate, they'll take their, lick off the cone. So it's going to be interesting to see how directly Amazon plays, but at some point you got Tam expansion, you got to play in that space. >> Yeah, I'll give you an example of knowing, I got acquired by a couple of times by EMC. So I learned a lot from Joe Tucci and Paul Merage over the years. see Paul and Joe, what they did is to look at how 20 years, and they are very close to Boston in your area, Joe, what games did is they used to sell storage, but you know what he did, he went and bought the Apps to drive them. He bought like Legato, he bought Documentum, he bought Captiva, if you remember how he acquired all these companies as a services, he bought VMware to drive that. So I think the good angle that Microsoft has is, I'm a SAS player, I have dynamics, I have CRM, I have SharePoint, I have Collaboration, I have Office 365, MS Teams for users, and then I have the platform as Azure. So I think if I'm Amazon, (indistinct). I got to own the apps so that I can drive this workforce on my platform. >> Interesting. >> Just going to developers, like I know Jerry Chan, he was my peer a BMF. I don't think just literally to developers and that model works in open source, but the open source game is pretty much gone, and not too many companies made money. >> Well, >> Most companies pretty much gone. >> Yeah, he's right. Red hats not bad idea. But it's very interesting what you're saying there. And so, hey, its why Oracle wants to have Tiktok, running on their platform, right? I mean, it's going to. (laughing) It's going to drive that further integration. I wanted to ask you something, you were talking about, you wouldn't invest in storage or compute, but I wonder, and you mentioned some commentary about GPU's. Of course the videos has been going crazy, but they're now saying, okay, how do we expand our Team, they make the acquisition of arm, et cetera. What about this DPU thing, if you follow that, that data processing unit where they're like hyper dis-aggregation and then they reaggregate, and as an offload and really to drive data centric workloads. Have you looked at that at all? >> I did, I think, and that's a good angle. So I think, look, it's like, it goes through it. I don't know if you remember in your career, we have seen it. I used to get Silicon graphics. I saw the first graphic GPU, right? That time GPU was more graphic processor unit, >> Right, yeah, work stations. >> So then become NPUs at work processing units, right? There was a TCP/IP office offloading, if you remember right, there was like vector processing unit. So I think every once in a while the industry, recreated this separate unit, as a co-processor to the main CPU, because main CPU's inefficient, and it makes sense. And then Google created TPU's and then we have the new world of the media GPU's, now we have DPS all these are good, but what's happening is, all these are driving for machine learning, AI for the training period there. Training period Sometimes it's so long with the workloads, if you can cut down, it makes sense. >> Yeah. >> Because, but the question is, these aren't so specialized in nature. I can't use it for everything. >> Yup. >> I want Ideally, algorithms to be paralyzed, I want the training to be paralyzed, I want so having deep use and GPS are important, I think where I want to see them as more, the algorithm, there should be more investment from the NVIDIA's and these guys, taking the algorithm to be highly paralyzed them. (indistinct) And I think that still has not happened in industry yet. >> All right, so we're pretty much out of time, but what are you doing these days? Where are you spending your time, are you still in Stealth, give us a little glimpse. >> Yeah, no, I'm out of the Stealth, I'm actually the CEO of Aisera now, Aisera, obviously I invested with them, but I'm the CEO of Aisero. It's funded by Menlo ventures, Norwest, True, along with Khosla ventures and Ram Shriram is a big investor. Robin's on the board of Google, so these guys, look, we are going out to the collaboration game. How do you automate customer service and support for employees and then users, right? In this whole game, we talked about the Zoom, Slack and MS Teams, that's what I'm spending time, I want to create next generation service now. >> Fantastic. Muddu, I always love having you on you, pull punches, you tell it like it is, that you're a great visionary technologist. Thanks so much for coming on theCube, and participating in our program. >> Dave, it's always a pleasure speaking to you sir. Thank you. >> Okay. Keep it right there, there's more coming from Cuba and Cloud right after this break. (slow music)

>> Announcer: Live from San Francisco, it's theCUBE covering RSA Conference 2020 San Francisco, brought to you by SiliconANGLE Media. >> Okay, welcome back, everyone, to CUBE's coverage here in San Francisco at RSA Conference 2020. I'm John Furrier, your host. You know, cybersecurity industry's changing. Enterprises are now awake to the fact that it's now a bigger picture around securing the enterprise, 'cause it's not only the data center. It's cloud, it's the edge, a lot of great stuff. We've got a great guest here from Dell EMC. Peter Gerr's a consultant, cyber resilience solutions and services marketing at Dell EMC. Great to see you. >> You too, John. >> Thanks for coming on. >> Good to see you again, thank you. >> So, you know, I was joking with Dave Volante just this morning around the three waves of cloud, public cloud, hybrid cloud, multicloud. And we see obviously the progression. Hybrid cloud is where everyone spends most of their time. That's from ground to cloud, on-premises to cloud. So pretty much everyone knows-- >> Peter: On-ramp, kind of. >> That on-prem is not going away. Validated by all the big cloud players. but you got to nail the equation down for on-premises to the cloud, whether it's, I'm Amazon-Amazon, Azure-Azure, whatever, all those clouds. But the multicloud will be a next generation wave. That as an industry backdrop is very, very key. Plus AI and data are huge inputs into solving a lot of what is going to be new gaps, blind spots, whatever insecurity. So I got to, you know, Dell has a history with huge client base, traditional enterprises transforming. You're in the middle of all this, so you got the airplane at 30,000 feet and the companies have to swap out their engines and reboot their teams, and it's a huge task. What's going on with cyber and the enterprises? What are some of the key things? >> Well, so I like to keep it pretty simple. I've been in this industry over 20 years and I've really consistently talked about data as the global currency, right? So it's beautifully simple. Whatever industry you're in, whatever size company you're in, enterprise or even now small to medium businesses, their businesses are driven by data. Connectivity to that data, availability of the data, integrity of the data, and confidentiality of the data. And so sort of the area of the world that I focus upon is protecting customers' most valuable data assets, now, whether those are on-prem, in the cloud, or in a variety of modalities, and ensuring that those assets are protected and isolated from the attack surface, and then ability to recover those critical assets quickly so they can resume business operations. That's really the area that I work in. Now, that data, as you pointed out, it could start on-prem. It could live in multicloud. It can live in a hybrid environment. The key is really to understand that not all data is created equally. If you were to have a widespread cyber attack, really the key is to bring up those critical applications systems and data sets first to return to business operations. >> Yeah, it's funny-- >> Peter: It's really challenging >> You know, it's not funny, it's actually just ironic, but it's really kind of indicative of the society now is that EMC was bought by Dell Storage and the idea of disruption has always been a storage concept. We don't want a lot of disruption when we're doing things, right? >> Peter: None, we can't, yeah. >> So whether it's backup and recovery or cyber ransomware, whatever it is, the idea of non-disruptive operations-- >> Absolutely. >> Has been a core tenant. Now, that's obviously the same for cyber, as you can tell. So I got to ask you, what is your definition and view of cyber resilience? Because, well, that's what we're talking about here, cyber resilience. What's your view on that? >> So when we started developing our cyber recovery solution about five years ago, we used the NIST cybersecurity framework, which is a very well-known standard that defines really five pillars of how organizations can think about building a cyber resilience strategy. A cyber resilience strategy really encompasses everything from perimeter threat detection and response all the way through incident response after an attack and everything that happens in between, protecting the data and recovering the data, right? And critical systems. So I think of cyber resilience as that holistic strategy of protecting an organization and its data from a cyber attack. >> That's great insight. I want to get your thoughts on how that translates into the ecosystem, because this is an ecosystem around cyber resilience. >> Peter: Absolutely. >> And let's just say, and you may or may not be able to comment on this, but RSA is now being sold. >> Peter: Yeah, no, that's fair. >> So that's going out of the Dell family. But you guys have obviously VMware and Secureworks. But it's not just you guys. It's an ecosystem. >> It really is. >> How does Dell now without, with and without RSA, fit into the ecosystem? >> So as I mentioned, cyber resilience is really thought of as a holistic strategy. RSA and other Dell assets like Carbon Black fit in somewhere in that continuum, right? So RSA is really more on threat detection and response, perimeter protection. The area of the business that I work on, data protection and cyber recovery, really doesn't address the prevention of attacks. We really start with the premise that preventing a cyber attack is not 100% possible. If you believe that, then you need to look at protecting and recovering your assets, right? And so whether it's RSA, whether it's Carbon Black, whether it's Secureworks, which is about cyber incident and response, we really work across those groups. It's about technology, processes, and people. It's not any one thing. We also work outside of the Dell technologies umbrella. So we integrate, our cyber recovery solution is integrated with Unisys Stealth. So there's an example of how we're expanding and extending the cyber recovery solution to bring in other industry standards. >> You know, it's interesting. I talk to a lot of people, like, I'm on theCube here at RSA. Everyone wants better technology, but there's also a shift back to best-of-breed, 'cause you want to have the best new technology, but at the same time, you got to have proven solutions. >> Peter: That's the key. >> So what are you guys selling, what is the best-of-breed from Dell that you guys are delivering to customers? What are some of the areas? >> So I'm old EMC guy myself, right? And back from the days of disaster recovery and business continuity, right? More traditional data protection and backup. The reality is that the modern threats of cyber hackers, breaches, insider attacks, whatever you like, those traditional data protection strategies weren't built to address those types of threats. So along with transformation and modernization, we need to modernize our data protection. That's what cyber recovery is. It's a modern solution to the modern threat. And what it does is it augments your data, excuse me, your disaster recovery and your backup environment with a purpose-built isolated air gap digital vault which is built around our proven Data Domain and PowerProtect DD platforms that have been around for over a decade. But what we've done is added intelligence, analytics, we've hardened that system, and we isolate it so customers can protect really their most valuable assets in that kind of a vault. >> So one of things I've been doing some research on and digging into is cyber resilience, which you just talked about, cyber security, which is the industry trend, and you're getting at cyber recovery, okay? >> Peter: Correct. >> Can you talk about some examples of how this all threads together? What are some real recent wins or examples? >> Sure, sure. So think of cyber recovery as a purpose-built digital vault to secure your most valuable assets. Let me give you an example. One of our customers is a global paint manufacturer, okay? And when we worked with them to try to decide what of their apps and data sets should go into this cyber recovery vault, we said, "What is the most critical intellectual property "that you have?" So in their case, and, you know, some customers might say my Oracle financials or my Office 365 environment. For this customer it was their proprietary paint matching system. So they generate $80 to $100 million every day based upon this proprietary paint matching system which they've developed and which they use every day to run their business. If that application, if those algorithms were destroyed, contaminated, or posted on the public internet somewhere, that would fundamentally change that company. So that's really what we're talking about. We're working with customers to help them identify their most critical assets, data, systems, applications, and isolate those from the threat vector. >> Obviously all verticals are impacted by cyber security. >> Every vertical is data-driven, that's right. >> And so obviously the low-hanging fruit, are they the normal suspects, financial services? Is there a particular one that's hotter than, obviously financial services has got fraud and all that stuff on it, but is that still number one, or-- >> So I think there's two sides to the coin. One, if you look at the traditional enterprise environments, absolutely financial services and healthcare 'cause they're both heavily regulated, therefore that data has very high value and is a very attractive target to the would-be hackers. If you look on the other end of the spectrum, though, the small to medium businesses that all rely on the internet for their business to run, they're the ones that are most susceptible because they don't have the budgets, the infrastructure, or the expertise to protect themselves from a sophisticated hacker. So we work across all verticals. Obviously the government is also very susceptible to cyber threats. But it's every industry, any business that's data-driven. I mean, everyone's been breached so many times, no one even knows how many times. I got to ask you about some cool trends we're reporting on here. Homomorphic encryption is getting a lot of traction here because financial services and healthcare are two-- >> Peter: Homomorphic? >> Homomorphic, yeah. Did I say that right? >> It's the first time I've ever heard that term, John. >> It's encryption at in use. So you have data at rest, data in flight, and data in use. So it's encryption when you're doing all your, protecting all your transactional data. So it's full implementation with Discovery. Intel's promoting it. We discovered a startup that's doing that, as well. >> Peter: Yeah, that's new for me, yeah. >> But it allows for more use cases. But data in use, not just motion, or in-flight, whatever they call it. >> Peter: I get it, yeah, static. >> So that's opening up these other thing. But it brings up the why, why that's important, and the reason is that financial services and healthcare, because they're regulated, have systems that were built many moons ago or generations ago. >> Absolutely. >> So there was none of these problems that you were mentioning earlier, like, they weren't built for that. >> Correct. >> But now you need more data. AI needs sharing of data. Sharing is a huge deal. >> Real-time sharing, too, right? >> Real-time sharing. >> And I think that's where the homomorphic encryption comes in. >> That's exactly right. So you mentioned that. So these industries, how can they maintain their existing operations and then get more data sharing? Do you have any insight into how you see that? Because that's one of those areas that's becoming like, okay, HIPAA, we know why that was built, but it's also restrictive. How do you maintain the purity of a process-- >> If your infrastructure is old? That is a challenge, healthcare especially, because, I mean, if I'm running a health system, every dollar that I have should really go into improving patient care, not necessarily into my IT infrastructure. But the more that every industry moves towards a real-time data-driven model for how we give care, right, the more that companies need to realize that data drives their business. They need to do everything they can to protect it and also ensure that they can recover it when and if a cyber attack happens. >> Well, I really appreciate the insight, and it's going to be great to see Dell Technologies World coming up. We'll dig into a lot of that stuff. While we're here and talking us about some of these financial services, banking, I want to get your thoughts. I've been hearing this term Sheltered Harbor being kicked around. What is that about? What does that mean? >> Sheltered Harbor, you're right, I think you'll hear a lot more about it. So Sheltered Harbor is a financial industries group and it's also a set of best practices and specifications. And really, the purpose of Sheltered Harbor is to protect consumer and financial institutions' data and public confidence in the US financial system. So the use case is this. You can imagine that a bank having a cyber attack and being unable to produce transactions could cause problems for customers of that bank. But just like we were talking about, the interconnectedness of the banking system means that one financial institution failing because of a cyber attack, it could trigger a cascade and a panic and a run on the US financial banks and therefore the global financial system. Sheltered Harbor was developed to really protect public confidence in the financial system by ensuring that banks, brokerages, credit unions are protecting their customer data, their account records, their most valuable assets from cyber attack, and that they can recover them and resume banking operations quickly. >> So this is an industry group? >> It's an industry group. >> Or is it a Dell group or-- >> No, Sheltered Harbor is a US financial industry group. It's a non-profit. You can learn more about it at shelteredharbor.org. The interesting thing for Dell Technologies is we're actually the first member of the Sheltered Harbor solution provider program, and we'll be announcing that shortly, in fact, this week, and we'll have a cyber recovery for Sheltered Harbor solution in the market very shortly. >> Cyber resilience, great topic, and you know, it just goes to show storage is never going away. The basic concepts of IT, recovery, continuous operations, non-disruptive operations. Cloud scale changes the game. >> Peter: It's all about the data. >> It's all about the data. >> Still, yes, sir. >> Thanks for coming on and sharing your insights. >> Thank you, John. >> RSA coverage here, CUBE, day two of three days of coverage. I'm John Furrier here on the ground floor in Moscone in San Francisco. Thanks for watching (electronic music)

>> Narrator: Live from San Diego, California. It's theCube! Covering KubeCon and CloudNativeCon, brought to you by Red Hat. A cloud native computing foundation. >> Welcome back. 12 thousand here in attendance for KubeCon CloudNativeCon 2019 in San Diego. I am Stu Miniman, my cohost for this afternoon is John troyer. And happy to welcome to the program, recently out of Stealth, two gentlemen from Chronosphere, Austin. To my right is Martin Mao who is the co-founder and CEO and his co-founder Rob Skillington, who's also the CTO, we've stated on theCUBE actually, you understand where this conference is, where co-founder and CTO is like you know, the most prominent title that we've seen to get on here, because that's the type of geeks we love on the program and in this community. So first of all, congratulations on the launch >> Thank you so much >> And thank you so much for joining us. >> No worries. >> All right, when I've got the founders on, I'm going to start with the whys. How was kind of the problem statement, where you were coming from, and what led to the creation of Chronosphere. >> For sure for sure. So with Chronosphere we found a actual gap in the monitoring market, and a very crowded monitoring market, we found a gap, and the gap exists when companies with very large complex technology stacks, or large enterprises, move on to Cloud Native Technology and Kubernetes. So with this migration, what we've found was there's actually a lot more monitoring data being produced, because there's a lot more pieces now, we're moving from monoliths microservices, we're moving from like physical machines to VMs, to containers and pods. And that generates a lot more things that you need to monitor and track. And not only a lot more things, but you generally monitoring the relationship between these things. So as the number of things increases, the number of relationships exponentially increases. So yeah, that's the sort of problem we're solving, it's like monitoring all of these things at large scale, and when we couldn't find anything, and I could even store all of theses things, so that's it sort of. >> All right, so what is the background of the team that made you into position to work on this problem? >> Yeah great question. I mean me and Martin go back quite a few years. I officiated his wedding, only very very recently actually. And I, yeah we basically work together at several different companies. You know, I think both of us are entrepreneurial at heart. I'll let Martin talk a little bit more about the last few years. >> Yeah, so like you know, a few years ago we started working at Uber. And at Uber, we went through this migrations to our native communities and through that migration that's when we sort of had to solve the problem ourselves. And we solved the problem at Uber, with an open-source project called M3. That's really where this whole thing started. And Chronosphere sort of you know, building on top of M3, and now providing a product on top of the open-source platform that we created. >> Can we talk a little bit about the business? I noticed that you know, there are many ways of approaching open-source, in 2019, you know open core and but also as a service. So can you talk a little bit about how you've approached your business model. >> Yeah for sure. So we're very much in the position or in the camp of as a service, right, because you know a lot of companies do do open core, and they're sort of going into the enterprise support model, we sort of didn't want to go down that route. And also with our open-source product, it's not really an end to end solution in itself, like you use an open-source M3, but you still need to plug it together with other things yourself. So what we really wanted to do was to give customers, and end to end solution, and that was built on top of the great technology, we built with M3, but really it solves the problem sort of end to end, and we do that best as a service. >> Rob maybe you can help explain M3 a little bit for us as to how that fits in the landscape, but what it works with and the like. >> Yeah of course. Yeah it's basically at it's heart a metrics platform, that is built on, at first the lower layer in 3DB, which is a distributive time series database. And then on top of that, we have basically an aggregation platform, that is actually aggregating a lot of the samples, and metrics that we're, collecting. So we can really do some transformations on the data, as it comes in, before it's stored in the database itself. And this let's us do a lot of like smart processing, of what signals actually matter, what signals don't matter, kind of like storing them in a way that can be accessed, much faster than like, other typical systems that don't really do any aggregation before it gets stored. And then, you know we have of course like a query engine that works with this distributed set of data, and so, you know, it's really a database that was designed from day one, to be a metric store. You know, it's not built on Cassandra, it doesn't use Rocks DB, at the lower layers, it literarily every part of it, was built for this purpose. >> Can you talk a little bit about dimensionality and cardinality? Because as I look at this observability monitoring space, I see a lot of current discussion about that and frankly a little bit of fighting, and I'm not always, I can kind of see it, why it's important, but what are some of the reasons and what do people do where you know by having it, and what is it actually, let's start with that. >> Yeah for sure. So you know, with this hot topic of like high cardinality and high dimensionality is, what I was talking about earlier, where as you move into cloud native world, you're now monitoring things at like a pod level. So it's like instead of tracking things on like a per host level, you're now tracking things on like a per pod level now, and that is at >> (interjects) You're tracking more things per pod. >> More things per pod and like every pod unit, these are ephemeral pods now, so they don't live for very long. So you end up having more pieces of data and they're kept around for shorter period of time. And now you need a system that can store all of these pieces of data, because you want to see them uniquely. So you want to monitor each individual pod to see exactly what is running at the finest levels. Right, so you actually need technology that can store a lot more data than you could before. >> And I you know, adding to that, there's a lot more people running with like mobile applications, they use you know that are running in markets all round the world, using different cell providers, and different backend services. You may deploy your backend services multiple times, a week or even a day, and if you want to tag you know, the meta data on and slice and dice by that metadata, with your business and with your applications and your system, that requires you know, adding yet another dimension on your data, which adds to that cardinality. Every time you add a dimension, you know that just multiplies the cardinality of your existing data set of monitoring data. >> And it quickly adds up a lot right, so. >> All right Martin, maybe, since you're just out of Stealth, give us some of the speeds and feeds you know, the product GA, is it globally available? Series A funding, who's behind that? >> Yeah so we just kind of still two weeks ago, we closed up Series A a few months ago actually. It was led by Great Luck, we raised 11 million dollars, and our partner at Great Luck is Gary, and we like him very much. And you know the state of the companies that we are currently in private beta right now. So with our hosted platform, we are onboarding to customers into a private offering right now. And early next year, we'll sort of open that up for more public beta. Yeah. >> And the way folks would use this. You'll be using Prometheus or Graphite or something, and you'd be, so you'd have tracing, you'd have logs, you'd have other things and you would be plugging all of them into, into your services. >> Yeah it's a great question. So you mentioned two of the technologies. So if you're Prometheus or Graphite like to try find metrics, both of those can be pushed into the M3 system for sure. We actually just announced a trace integration, this week a KubeCon actually, Rob David spoke about that integration earlier this week at KubeCon. We haven't moved into the logs yet because the way we look at the problem is not from like a sort of like providing a one-stop shop for all observability solutions, we actually look at it from a use case perspective. So the use case we're looking at is like, realtime monitoring and remediation. So tracing is a part of that stroy, it's a critical part of that story, and now to add additional context, when you get to load it based on your metrics, but, we haven't quite moved into logging yet. >> Yeah, and we don't really want to solve any of these problems without knowing it'll work at scale, you know like a fundamental reason we even built the open-source project in the first place, was we were dealing with cardinality in the tens of billions of unique time series, and so, we don't want to just kind of like roll into any, every single feature under the sun, we really want to solve it once correctly and be able to systematically roll that out to enterprises at scale. >> Without, I mean without talking too much about Uber and any Uber secrets, I mean it seems like the game has changed with that kind of a scale of, you could not have done, you can't run Uber if you're tracking all those cars like literarily without some sort of a tracing like high cardinality sort of a system right? Because you're literarily tracking cars all over the world people all over the world, routes all over the world. >> Exactly, well uniquely positioned, we had the requirements to solve it at such a scale, and that's why we had to build this technology to solve it for that unique situation, because you know technologies ahead of time, did not really have this use case to solve. So that's why we had to sort of, we couldn't find anything out in the market because to solve it at that scale, that's why we sort of had to build our own, to uniquely solve it for this use case. >> And yeah, I would add to that, that typically engineers you know, at larger organizations, tend to want to organize everything very nicely, and split it up, and really control how they're monitoring that data, but we've noticed actually, definitely over the last few years, more and more people are open to letting people just start collecting you know, random data, that is relevant to the systems that they're building as they're rolling it out, even as they're experimenting with it, and you know systems today that are built from scratch, to deal with, to be as efficient as possible, with very unstructured data is becoming wildly popular because that's how developers want to develop software. You know, they don't want to have to have to like slice and dice it neatly and package it up and pass it on to others to run. They want to basically slice and dice however they want to, and dynamically , and as they scale up. >> I've always enjoyed every sequel skimmer I've had two, or change oh, yeah. (laughter) >> All right, how have you found the show? How's the reception been? Give us a little bit of the vibe of the show and how it's been going for you. >> Yeah it's been fantastic for us actually. So we just came in at silk so like the name is still quite new, but yeah, we've had a bunch of folks set up with the whole day, we've been giving a demo on the product, so a lot of companies are getting excited about it. I think a we're solving at a scale and that really resonates with, you know, a lot of the people here at the show, we're still solving at a scope, we're solving at a scale that's also in a cost efficient way as well. So that's really been our, we sleep quite well so far. >> Yeah Rob, you gave some sessions. What kind of feedback are you getting from people? Is the problem statement that we talked about at the beginning you know resonating with people that you talk to. >> I mean, I was really, yeah pleased to hear that after my session today, that a lot of people came up to me and said you know, I've never really seen metrics been linked to tracers, the way that we're doing it, in fact that's the first time they'd ever seen a demo, that can do, what we're kind of trying to upstream, we're actually you know, up-streaming a lot of those changes in the open-source well, as well at the same time. And so, you know we've found especially in a lot of the companies today that are pushing everything forward with development wise and how they are running operations is that they using a lot of pages in open source, and then those pages are battle tested in open-source, generally it becomes abstracted, to the point where we're actually a very large amount of people, but then when they need to scale it up, that's when it becomes difficult. So, no I think that you know, a lot of people have been very positive with basically us being able to also push forward the feature on >> Back upstream into the M3 project. >> And also into Prometheus. So I, you know I'm an open metrics, contributor and that's essentially, an exposition format that's built on the Prometheus, exposition format. So it's kind of become a standard way of exchanging metrics, from one system to another. And that's kind of like, basically commoditized and democratize the exchange of metrics to make a lot more systems, interoperable with each another. Which we fundamentally believe in as well, of course we're developing in open-source, and we believe that this systems need to play nicely together. So we can build you know, have building blocks that large companies and organizations can all share and build better things on top of. >> All right, so looking to go to public beta early 2020s, what we said, when we come back in 2020, what kind of the, some of the key KPIs and metrics that you'll be looking at to be successfull in your first year out of Stealth. >> Yeah it's a great question. So you know, since some of the KPIs you guys were looking at doing is coming at the public beta, making it available to a large range of companies, because right now we're sort of onboarding companies sort of one or two at a time, so yeah it's seeing how many companies adopt the product and also, we're again adding more features over time, for that particular use case of like you know, monitoring your technology just like in your business in real time. So it'll be a lot more features coming down the pipeline, and a lot more customer adoption along with that. >> And I would also say you know, our hosted platform is really about offering like deep isolation, between our tenants as well, so basically when we you know, in the next few months to come, we want to make sure that it works basically like clockwork, and everyone can, we can roll out and scale that highly isolated platform for you know tens and hundreds of organizations, and thousands eventually. And so, and doing that at scale is hard. So I think yeah, we'll see how we're doing with that. >> Yeah for sure. >> All right. Rob, Martin congratulations on coming out of Stealth, look forward to hearing more and thank you so much for joining us. >> Glad, thank you so much. >> All right, for John Troyer I'm Stu Miniman, we'll be back getting towards the end of three days, want to walk over here KubeCon, CloudNativeCon thanks for watching. (upbeat music)

(energetic music playing) >> Hi, I'm Stu Miniman here at the Silicon Ango Media Office in Palo Alto, happy to welcome back to the program Kiran Bhageshpur, who is the CEO of Igneous Systems. Kiron, great to see you. >> Great to see you again, Stu. >> Alright, so we've been really busy at theCUBE looking at so many big trends, and of course, really looking at kind of massively scalable distributed type of architectures are something we've been looking at, and something I know Igneous has been doing since the earliest days. But, the exact focus of what you've been working on, I think's changed a little bit since you first came out of Stealth and we've been looking at what your doing. So, why don't you bring our audience up to speed. >> Love to do that. It's not changed so much as expanded if you will. We launched, I believe I was here last, in October of last year, just as we were getting ready to launch. And, at that time, we launched the company and the platform, which the beginning services was object of the service, televert as a service and the enterprise data center. And, that was just the beginning. We've gone on since then, expanded the number of native services available, but really what we have done is built applications on top of that. So, the first application that we have developed and deployed at customers is backup and archive for massive file systems. So, we are talking about people who have terabytes of data, billions of files, spread across hundreds of systems. So, that's kind of been a pretty exciting thing, and it's a very unique set of challenges both for customers and for us to go forward. >> So, it's interesting, just step back for a second, object storage is something. If you talk to anybody that's a storage technologist they're like absolutely the way we need to architect things. But, usually we tend to get away from talking about object storage itself, and truly what do I do with it, what are those applications, what are those use cases. So, there's still object underneath it if I understand it right, it's just you're getting closer, moving up the stack a little bit, and getting closer to what your customers were asking for. >> Absolutely. The underlying infrastructure is still a collection of cloud services, not just object and S3, but a bunch of other services, which are very API compatible with the cloud, but, really, that doesn't matter because those are just tools. What matters is what are you doing with that, and what we are doing to begin with is really backup, archive, and discovery of massive files inside the enterprise. >> Alright, so there're some backup we've been doing for a long time, but backup has been broken. We were at the VM world show, there was a lot of buzz around some of the new companies, sometimes they called them secondary storage; you know, Rubric, Cohesity, Veem who everybody knows from the virtualization world, why don't you tell us are you part of kind of a similar wave? How do you kind of compare and contrast that to some of those other players? >> Great question. It's similar, but quite different. So, if you look at Rubric or Veem, for example, Veem really came about by doing tight integration with Veemware and doing a Veemware specific backup, which was the right technology, the right time for VMS and virtualization. Similarly, Rubric, and for that matter Cohesity, are really re-imagining data protection primarily for structured workflows, databases, physical servers, VMS, tightly integrating it and re-imagining how that feels from an experience point of view. We are really looking explicitly at unstructured data. This is data which lives on network devices from a net-app or a deliMC or a whole bunch of others and the content is really digital assets. It's data that could be media data, it could be microscopy imaging, it could be design data for a variety of work flows and this stuff continues to grow. It is monotonically increasing in every place, whether it is on premises or on the cloud or the edge, and protecting and managing this data is really a challenge and getting worse for customers. >> Yeah, the word that keeps coming up a lot is data. And, one of the things I know we've been excited about storage use to be about storing it. Now when we're talking about data, how do I leverage it? How do I get get value out of it? How do I discover different pieces of it? How have you been seeing these changes, your background you worked on some of the scale-out NASA solutions in the past, so how do we see kind of, unlocking the value of data? >> Yeah, you are absolutely right. If you go back 10 years ago, the real problem with how do I store all of this data, today there are plenty of solutions for ways you store data, especially on the primary teir, right? The challenge is really getting data from where it lives to where it's needed, whether it is backing it up or archiving it into the cloud. Being able to automatically discover things about it. Simple things like how is it growing, who is using it, how big is it, how much of it is what size of data? What about things you can infer about it by looking at the type of data it is. This is what now becomes valuable because if you look at the data sets and sizes, even modest size businesses today will have para bytes of data, billions of files, and that's challenging for any system system to go, sort of understand, unless you build it as a part of the platform. >> Okay, how about organizationally? Yah know, one of the other shifts we've seen is, you know, it used to be the storage administrator. How do I, how do I grow, how do I manage it, how do I have all of my protections and things set? A lot of the types of applications you are using are closer to the business, this is what runs the business. The business user needs to be involved. How are you setting your solution up to, you know, do what the business user needs? >> Great, yeah that's a good question. Today if you look at this data sets, this is not stuff that is an IT application. It's an end-user business focused application where they research in a life sciences world, or its designed in an electronic design world, right? And in all of these cases, essentially the end-user cares, because this data is critical to their daily working, working experience. Now, IT is clearly involved; it's a clear sort of partner of the business unit and actually operationalizing this data and making it easier to go consume. But now, it's really a joint thing, the final decision maker is always the end-user. In fact, we find ourselves in multiple places where we talk to IT, and talk to the IT teams. They get excited, but very quickly they bring in the end-users to make certain, whether the end-users are researchers or software developers, or even (mumbles) to make it so that they're comfortable with what we're talking about and they get really excited and that's sort of the starting point for our deployments. >> Yeah, we saw a similar dynamic between the business and the IT when we talked about cloud. And when I talked cloud I specifically mean public cloud and your customers, I have to imagine, they're all using public cloud in one way or another. Maybe, explain that dynamic how public cloud fits in with what your doing and how some of those IT and business people. >> Right. Look, cloud is simply the most disruptive trend in the last 10 years. In fact, you have to go back to Veemware, and Veemware's virtualization to see another trend of that magnitude. And all of our customers are embracing the cloud. They are wanting to go adopt cloud patterns, if you will. But the 180 over there massively challenged is around large data sets. Think about it, if you have terabytes of data that continues to grow, it's billion of files, it's spread across multiple geographies and dozens to hundreds of systems, it's a challenge to go leverage this in the cloud. So they're looking to ask, to be able to go chart the journey from all on premise, to a true hybrid world where they can use those cloud patterns much more effectively. >> Yah know I'm curious, and maybe it doesn't fit exactly for what Igneous is doing today. But, we've been talking about the data center versus the public cloud and a lot of those environments. I talked to some companies, that, you know, when I'm building those data legs, I'm doing that in the public cloud too. Then the discussion that's come up a lot in the past year, is Edge; so, IOT applications, we know we're going to have orders of magnitude more devices, and there's going to be a lot of data but the requirement for the data center versus the public cloud versus the Edge are very different. How does Igneous look at that? How are you having those discussions? Customers, how do they get their arms around all the various places of data?-- >> Right. You're absolutely right. The requirements are different, as in the public cloud is this massive hyper-scale, always available. The enterprise is a smaller version of that. And the Edge has a very different physical characteristics. But, what we believe is important is the same patterns, the same API's are available everywhere. And if you look at what the big public cloud providers are doing, Amazon with, you know, Snowball, and Green Grass, they're trying to go move their API's out and we completely embrace that trend. And, that's one of the reasons we built our platform to be API compatible with the cloud, with a variety of the cloud services. Because that means the services we run can run in the enterprise data center or in the public cloud or on the Edge all on a platform which is appropriate for the three. >> Yeah, and, to drill down to specifically, you say API compatible, that's S3, that's fully compatible. And do we have an API creep every cloud seems to have not only one API but many API's especially our friends at Amazon, what are you seeing out there, and what is the breath of offering they have today? >> Yeah, so, its SS3 is a constant storage leg is the obvious one, but the ones we did not talk about the last time were things like index store. So this is the equal of Amazon's dynamoDB, or Azure's table store the ability to go store a massive amount of index. But it's not just that. It's also the ability to go around compute, close to the data, which boils down to Cubanaties and containers. So all these three are part of our on the line platform. We don't talk about that to customers except after they become customers; we really focus on the application which is back up, archive, and discovery of all of their file data. >> Yeah, Kiran, take me inside the customers you are talking to; a lot of times we're like, I hear this term secondary storage out there and I worked on converge and hyper-converge stuff, you know, those terms are something that customers hear about after awhile, but they don't solve the problem. What, can you help translate for us, what's going on in your customers and why is secondary storage important to them? What's different than traditional back up, and how do you fit in? >> Right, so if you look at all of these guys, the data, the fundamental truth is data sets are growing and they are growing monotonically. Every year it is more. We've talked to folks where in the two years that we've spent as we were growing up as a company, they've sort of essentially had a 40 percent growth in their on search data sets, right? So then, the question is a couple of things. One, they clearly realize that not all of that stuff needs to live, or should live, on high performance, relatively expensive primary tiers. Right? That's the first set of piece. But the question is, how do you find out, what is active what is not active and how do you move it to the appropriate place; so this is sort of trend line and this is the patterns that they are living with. What we do is go in, very simply start off by saying, lets go find all of your filers, you know some of them, some of them you may not even know about, and let's go automatically back-up all of the data, and give you intelligence about all that. What is sort of simple intelligence. The intelligence could be how infrequently are these data sets changing, how frequently are parts of this data being accessed or modified by your applications. So that's sort of first part of this. And when this drives to is, not only does this reduce the cost of backup, which is really an insurance policy, it makes possible a bunch of intelligence about the data itself which is the beginnings of, sort of appropriately staging data on the right infrastructure. >> Alright. Kiran, you've had a number of customers since the early days talk to us a little bit about the journey you've been going on with them. How many of them have been pulling you towards the direction you are now going? What's their response been? To I guess what you call it, kind of storage as a service? >> Yeah, you know people love the whole concept of our offering as a service; initially when we talked of customers they kind of a little skeptical of our ability to go do this but they very quickly fall in love with that. It's pretty amazing. What's not to like about infrastructure that is inside your data center but that you do not have to manage at all? And when I say do not manage, people don't even look at things like drives or CPUs or network. That's not the world they live in. They live in the world of what's logically important to them, which if my backup's running, is my data being archived, how quickly is my data growing, who is accessing this data? And so on, and it goes to the next level, which is they don't have to go to manage things like software updates, just like you don't know what version of Gmail you're running or you do not know what version of S3 is being used in the cloud. Our customers don't know what version it is. Is it API level compatible or is it guarantee the services are not interrupted; and they absolutely love that aspect once they get used to it. We tell our customers, "You don't call us, we call you if there is an issue." And we're living up to that and they are pretty jazzed about that. >> Yeah, I love that. Kind of the version control thing is something we said is something, is cloud experience is actually what we want. (Mumbles) when we wrote true private cloud is exactly that; you don't know or care what version of Azure you're running, you assume that they're going to test that out and do that. Can you give us any kind of concrete examples, customers, love if you can share any names, but a lot of your customers are quite big, but what are the concrete results? What are they seeing, any good stories you can share? >> Yeah! So I give you an example of one of our largest customers, can't mention the name, but it is a large tech company in California. There's a lot of large tech companies in California-- (giggles) >> There's a bunch, yeah. >> Well, lets go through the South in California. And, these folks had an enormous amount of data. We started off by telling them, "Hey give us your most "complex systems, the ones that you are not able "to go back up today." And we started with their file systems, which were literally had this thing called file density, which is an enormous number of files in a relatively small amount of storage. So you're talking about a billion plus files and terabytes of data, and this is things that they had never been able to back up and we go off and we were able to go back it up and completely system protect. So, that's an example of a used case where we can go to a customer and allow them to accomplish what they cannot do today just from a basic back-up point of view. And, take it to the next level. In fact they did this great demo for their internal teams where they showed how easy it is to search through this data and essentially accomplish in seconds what typically, in their current world, takes hours to do. >> Okay, yeah, that's great. Yeah, sounds like you have some really good interesting, large companies there. Is that, what's the typical profile you see? Is it really companies that have specific challenges because they've got the massive scale? How far down does this scale? >> So. Uh, that's a common question that comes along. And the way I like to answer that is we are applicable to people with lots of data. It turns out it could be much smaller companies with lots of data, so we've got customers who are in the hundreds of people only world-wide, maybe two or three locations, but they are really looking at a multi-terabyte sized data problem. Similar data density problem. In fact, another one that we are working with has got 300 million files and a terabyte of data. How do you back it up? How do you go discover information about that? That's what we solve, and for these smaller companies which still have the problem, they are actually starting to find out about us and come to us. Which is really gratifying. >> Okay, well you seem pretty excited about it, about the space, what's exciting you the most about where we are today with the technology. >> The really sure is, people talk about data and they immediately go to databases, they talk about virtualization and physical servers. But that's not where the data lives. The data hasn't lived there for over a decade. And more and more of the data lives outside in files and object and there is this sort of ability to go understand that better, manage that better, protect that better and last but not least, provide intelligence to users because this data is something they care about. People are not keeping this because somebody else told them to; it is their life blood. It is their sort of livlihood, if you will, from a company point of view, and helping customers be able to go take that to the next level will bring this sort of cloud patterns to these used cases. That's pretty exciting. >> Yeah, absolutely! Want to sort of give you the final word. I hear this and I think about, you know, the whole wave of big data, what we're starting to talk about, you know, continuously with AI and ML really it is about unlocking data, so huge opportunities going forward. Any of the other trends outside what we've discussed already that you want to give us for a final word? >> You know, the last thing that I say is it is about data. It is about complete automation all across the, across the sky, weather it is storing, managing, or deriving intelligence and the reason you want to go automate all that stuff using intelligence in the software systems itself is simply because it's too large. There's no other way to go do it. And last, but not the least, all of the stuff has to be offered as a service because the cloud has gotten people really hooked on this sort of, comparatively, easy world of not having to go managing infrastructure. And I think those are the three things we should, we hold by. >> Alright, Kiran Bhageshpur, I really appreciate the update on Igneus systems. Absolutely customers dealing with massive amounts of data, how do I unlock the value of that without having to be down in the guts which has really been the history of storage. I'm Stu Miniman, thanks so much for watching theCUBE. (energetic music playing)

>> Announcer: Live from Gillette Stadium in Foxboro, Massachusetts, it's theCUBE, covering #VTUG's New England Winner Warmer 2017. Now, your host, Stu Miniman. >> And we're back, with SiliconANGLE Media's presentation of theCUBE, we're the worldwide leader in enterprise tech coverage, happy to welcome back to the program, Steve Pao, who's the CMO of Igneous Systems, Steve flew out from Seattle here to, welcome to the home of the New England Patriots. >> Oh my gosh. Number 12, number 12! >> The 12 man representing here, you've got, I have to say, I almost canceled my season tickets when Pete Carroll was our coach, so, luckily he's worked out better for you than he did for us. My wife's a Brown fan, she says the same thing about Bill Belichick. So, it's the coaching fraternity is kind of like the tech world, it's a small group, you all kind of get to know each other and move around, so, thanks for joining us. >> Yes, well thanks for having me! >> Alright, so Steve, we've been talking to you guys since you were coming out of Stealth, why don't you give our audience, what's the update on Igneous? >> Okay, well for those of you who don't know us, what Igneous really does is we offer an onsite private cloud storage service, and that's our first offering, it's part of our greater mission of providing true cloud for local data, and what we basically offer today is an unstructured data store that's completely delivered as a service, we take our own equipment, we install it, we monitor it, we manage it, we even refresh it when necessary, and all the customer has to do is really subscribe, and that's it. It's all pay-as-you-go, and it's all zero touch for the customer. We launched back in October, as you recall, and one of the things that I think that it's been really great since launching is that we've really started to see how customers that didn't know us are actually really evaluating, really, I think, the convergence of two trends, one is there's this data growth, data trend that goes on, and pretty much everybody we talk to, citing data growth rates on the order of doubling every three years, where IT budgets are growing less than 5% a year, so there's this mismatch where, basically everybody's hitting this juncture that what they used to do can't work because the data's growing faster than the budget. And at the same time, there's this data growth that's actually happening, and the data growth is not from relational databases and structured data, but rather, a lot of new applications that are logging sensor data that are supporting machine learning, AI, really, it's machine-generated data being analyzed by machines, with humans really just training the AI and the machine learning. >> Yes, Steve, I want to unpack that a little bit, let's talk it, because many of us that watch storage, it's been like, well the storage industry, it needs to change, it's not about selling boxes, it's not about capacity, and even on unstructured data, it was kind of like, okay well, what's creating data and what's actually valuable? How much is it just, do I stick it on a cheap tier, what do I actually do with it, what's interesting you guys do, some of those use cases, throughout machine learning, machine data, things like sensors, every time I hear that word, that IoT buzzword kind of pops into our head, but maybe you could talk to some of those, what's bringing customers, what's that driving challenge that they have, that you're helping to solve, that's different from the way storage has been done for many years? >> Yeah, I think, that's a great question, and I think that there's just been a real transition, and I think the transition has been largely created by the kinds of data that we want to manage and that we want to curate, and as we're seeing these sort of large unstructured data sets, it starts with the data, so as an example, you take equipment that used to exist in the past, like let's say in scientific computing. You used to have flow cytometers, which were just time-series data, and then what's now happened is is associate with ever flow cytometers, now a real-time video feed. When you look at the old world of microscopy, what you used to do is you used to flash freeze a sample, and basically take a picture of it, and now what you can do with lattice light-sheet microscopy is you can actually look at cells in vivo, while they're alive, and you can, I've personally gotten to watch a T cell move through a collagen matrix, and that's all microscopy, but generating orders of magnitude more data. That is, we're looking at these very, very different data sets, we're looking at very, very different kinds of computing, and what that requires is very, very different kind of infrastructure. And so, the infrastructure has just had to get a lot more intelligent, and the architecture has had to get a lot different, and what we've noticed is is that, that a lot of the patterns that are actually being built in the public cloud as they've taken kind of a fresh look at the computing models, have really become appropriate for this new kind of computing, and we don't see that on the premises, and that's really what we set out to go do. >> Yeah, it's interesting, it's probably the wrong term, but it sounds like we're describing kind of object storage 2.0. 1.0, I remember this healthcare use cases, everybody, when I was doing radiology, when you're doing certain healthcare and sciences, I need metadata, I need to understand that, but now there's just orders of magnitude more data, and technologies are making, it's denser, prices have come down, so the idea has been around for a little bit while, but it sounds like the technology's matured to allow kind of an explosion-- >> Well, and it's just a computing model, it's like one of these things where we're really, because of the emergence of microservices, one of the things that we've seen is applications want a restful interaction with the storage layer, and so, so it turns out that that tends to be very, very perfect for a cloud-like implementation where you can actually implement high volume, unstructured data really, really well via a restful API, where in the old world of POSIX semantics and that kind of transactional model, you just lost scalability. Either you had a lot of proprietary hardware, with that VRAM, you had proprietary interconnects data with things like InfiniBand, and nowadays, being able to loosely couple distributed systems is really the name of the game, and that's ultimately what we aim to build at Igneous, and that's all the technology, in terms of our commercial offering, the customer doesn't care what's behind it, but fundamentally, what you're looking for is the scalability and resilience that the cloud offers by doing that on premises. >> Yeah, so Steve, we had a really interesting crowd chat about a month or so ago talking about hybrid cloud, and the thing I've been saying for the last, probably year, is, as customers try to figure out what goes where in the cloud environment, you know, I've got SaaS, I've got public out of, I've got my private cloud, it's follow the data and follow the applications. In the cloud, things like mobile and even some video streaming, I think we understand how to do that, but why does on-premises make sense for your customers, your workloads, and your solution? >> Yeah, absolutely, and so, first, a little bit on hybrid cloud, there are kind of two different definitions of hybrid cloud, one is kind of the AWS VMWare scheme where what you're really looking to do is run your old stuff that you were running on-prem, in the public cloud, and you call that hybrid. But there's another way to look at it, which is to say, hey, let's take a look at the computing patterns that are being run in the public cloud, how do I bring that down to the premises? And the reason that you might want to do that is, it's really twofold, one is the gravity of the data, so it might just be that the datasets are too big to move back and forth over very thin internet pipes, and so you want to actually keep the data close to its source. The other is something that we've seen, which is really more of a preference, which is that while I think that cloud technologies actually have a lot of capability for security, there are a lot more hoops for folks to run through to ensure that they're compliant with their own internal policies, and where they've already set out a set of policies for how they run the stuff behind the firewall, sometimes it's just simpler for them to actually keep all of the data on the premises, and not actually have to worry about some of the issues in tracking, and compliance issues associated with how you move the data around. >> Yeah. One of the things we've heard from users is when they use public cloud, one of the things they really like is, sometimes the CFO's not fully onboard, but buying things as a service, so, they want to understand predictability, but they want to buy it as a service, understand, how does your solution fit into that kind of paradigm? >> That's great, I think our solution fits into both trends really, really well, because what we're really offering, we talked a little bit about technology, but really fundamentally, we're offering a service, and so when Igneous goes to a customer, our interaction is as a service. Customers interact with our service via APIs, and they get a bill for a subscription, and so it's an as-a-service model, you don't buy hardware, you don't install software, you don't have systems to manage. At the same time, there is a predictability that's a little bit of the downside of the public cloud, because there's a fee, generally, to access your data at a storage, and often, when people don't actually understand their data access and their data movement patterns, the costs of running applications in public cloud become quite unpredictable, and you actually don't run into that unpredictability with a solution like Igneous, because our data is on your local area network, and we don't charge you to access the data that's on your own network. >> So, I've come to an event like this, if I'm thinking about my storage today, the conversation in the marketplace has been, well, the new choices out there is, there's, the HCI, the hyper-convergence infrastructure, and there's flash, the AFA devices out there. And of course, even the lines between those are blurring, because I can have an all-flash configuration of hyper-converged, and some of the all-flasher a things are getting converged and put into more things, how do you help customers as the, what's the bullet point as to, well, this is for this kind of application, this is for this solution, and hey, there's this whole new category that you need to be thinking about. >> Yeah, I think that's perfect, and I think the real trick here is is that there's a difference between your hot tier and your flash tier, and your capacity tier, and fundamentally, the flash tier is really good when Time To First Byte is very important, so that might be for your relational database applications and things of that sort, where there tends to be a lot of searching through an index, and so you've got a lot of low-latency requirements. And then on the other hand, what you have is a capacity tier, they may be your video surveillance, they may be your large, unstructured documents, they may be your censor data, and in those contexts, you don't necessarily need the Time To First Byte, what you really need is capacity throughput, and so the overhead of setting up, for example, a restful connection is not significant when compared to the amount of data that actually needs to go through the system, and that's actually where restful semantics actually gets superior to positive semantics, when you have very, very large, unstructured data sets. Hyper-converge is actually a little bit of a different world, and I think that while hyper-converge has worked out pretty well, I think, for virtualization workloads, we've really found that when it comes to these very, very large unstructured data sets, hyper-converge isn't necessarily always the way to go, you tend to find a utilization issue between your compute and your storage layers, where you have to actually think about how you're balancing all this stuff, and so, really, the world that we've really seen emerge as new applications come forward, is there's really a trend to write microservices that are stateless, and to have them talk to a stateful layer, that's why in the public cloud, there's a pattern of having things like elastic container services talking to an S3, and we definitely see on premises that same type of things that's going to emerge. There's going to be some time to get there, admittedly, as I was mentioning kind of at the beginning, we've seen this really interesting set of interest patterns, one is from the folks who are developing these new applications that are utilizing unstructured data, there's a lot of interest we're getting right now from IT folks that are just getting started with object storage to do secondary workloads, to do backups, to do archives, and it's been interesting that we've been getting a lot of interest in our service as a new way to approach some of these data protection workflows. >> Alright, so Steve, last question I've got for you, came out of Stealth Q4 last year, what do we look for in 2017 from Igneous? >> Yeah, so I think that you'll see it on both of those fronts, I think that one thing that's going to be seen in 2017 is a lot more development on our side around building up a tool chain for folks to use for a data protection tier, and so, we've got a new offering coming online, we're calling it Igneous Insights, which provides information about what's currently on your primary storage tiers, we've got a whole set of replication services, they're coming up to do backup, archive, things like replication to the cloud, but what we're also really moving forward with is a lot of what's needed in the tool chain to really support hybrid and multi-clouds, so how you facilitate the data movement in and out of the cloud, as well how you do the auditing and management of the data, no matter where it lives. >> Alright, Steve Pao, really appreciate you catching up, and if you want to find out more about this category, check out cube365.net/trueprivatecloud, that's C-U-B-E, number 365.net/trueprivatecloud, which has resources from the whole industry, including from Igneous, including from Wikibon and theCUBE, as to what's happening kind of this true private cloud, hybrid cloud environment. We'll be back with lots more coverage here, thanks for watching theCUBE. (electronic music) >> Announcer: Since the dawn of the cloud, theCUBE has been there.

>>Come back here. This is Silicon Valley coverage of ADU Summit. I'm John Fur, the founder. We're, we're pleased to have a friend inside the cube. It's rare to have such luminaries, Ama Aala, good friend and also co-founder of Cloudera. Really the pioneer in the space that helped build this industry that we're living here at at Hadoop Summit. I'm with Dave Ante from wiba.org. Amour, welcome back to the Cube Cub alumni. Thank you for having me here. Wow, what a journey. Are you co-founded Cloudera? I remember when you in Stealth Mo, I really can't talk about it. And, and then of course the history of Silicon Angle being, you know, founded and kind of built in in your office when you only had like 20 something employees. Yep. We owe a great deal of gratitude to you and, and congratulations to you Michael Olson, the team for building an industry. So I just wanted Thank you. Thank you. And welcome to the Cube. >>Thank you. It was great to be here. >>So what do you think, what's your take on the current Hadoop ecosystem right now? I mean, obviously a lot's happened. I mean it's big now. It's growing up fast. Yeah. The word enterprise grade is out there. You're seeing it move from, you know, trying to change the world. Our first interview, you said, I've seen the future, I want to bring it to the mainstream. It's here. Yeah. It's hitting mainstream right now. Yeah. What's your take of the current situation of the ecosystem and it's, and its value? >>Yeah, so I, I have a quick question first. Should I look to you or look to the camera? Look to >>The camera or both? Whatever you, whatever you'd like. >>So I think it's, the ecosystem is definitely growing, which is very, very healthy. However, there is a side question there, which is what do you think of all the competition coming into the space? So five years ago when Cloudera was started was just Cloudera. There was no other commercial vendor trying to support or enable Hadoop in the, in the industry for enterprises. And today there is at least 10 of them trying to compete with us, right? And that includes big companies, established companies that decided, hey, we gonna start addressing the space, but includes many, many newcomers who like Hortonworks, who were founded over the last couple of years. That's a healthy thing. I mean, that's absolutely a sign of a growing market. If the market wasn't growing, if there wasn't money in the market, if there wasn't, if it was just hype, there wouldn't have been all of these new companies and new ventures showing up. That said, I never look at competition as something that worries me, that I'm afraid now or what's gonna happen to me, or that's normal. That's exactly what happens to successful companies. If you look at Red Hat, when Red Hat was launching with the Linux, they had 25 competitors or even more 30 competitors. That's when Red Hat was forming out. And today, even of these 25, 30 competitors, they still have six or seven still left. So I think it's a very, very healthy sign of the graph of this market and the maturity that's reaching. >>What do you think about some of the, the white spaces that are evolving? You guys have obviously been involved in a lot of deployments at Cloudera. Again, you're doing a lot of, lot of work with the top, top names and the clients that you have aren't usually disclosed cuz you really can't disclose them. What, what are you seeing right now as the white spaces for things to do in the Hado platform? >>It's a very, very good question. So first I can't talk about future, future roadmap. Right now we're becoming a big company at that level where we can't comment on future roadmaps. >>Ah, that's sinus sign of the >>Time. You're well media train, good to see they're doing a good job keeping you >>A, You want more information on that? I can connect you with a pt, >>Please. No, no, no, we're good. We're good. We'll get it outta you. But, >>But our vision, our vision for Cloudera from day one, like you were saying earlier, we saw the future, right? So our vision from from day one was really to build this data system where we can have detail of any type, whether that data is structured or unstructured or images, it doesn't matter. And then on top of that data run any type of workloads. That workload could be the initial genesis of Hado, which is map use, which is batch processing. But now as as we made many announcements through the last few years, we also now have Impala for interactive analytics as a workload. We have a very, very strong partner partnership with SaaS for doing machine learning and statistics as a workload. And a few weeks ago we announced search as another workload. So you have multiple types of workloads that can handle different types of problems that you have within your organization and bring all of these workloads to all of your data regardless of type. And that's the vision that we'll continue to deliver on. That's exactly what we're building going into the >>Future. So how's that fit in with yarn, right? We're hearing a lot at this conference about yarn, the ability to, you know, do more with less in a lot of the things that you typically hear with the enter within the enterprise. And, and so talk about that a little bit. >>Yarn is a very core part to our platform. In fact, yarn has been part of CDH four for more than a year now out in the, in the markets. So we did bring, we were one of the, I think we were the first vendor who brought yarn into a distribution of Hado out there. It's very, very fundamental to us because that is how we're gonna coordinate. We are gonna be using yarn to coordinate launching all of these different type of workloads. You're gonna have the map produce workload, which is very batch oriented. The Impala workload, which is very latency sensitive. The, the search workload, which is also very latency sensitive. The machine learning workload, which is more batch oriented, et cetera, et cetera. And yarn is a very, very central piece to helping us coordinate all of these different types of workloads onto the >>Platform. Cloudera has been a great citizen in the community also. You, you mentioned and, and we witnessed that your team create the industry. You guys were there, you took the chance, you were the first ones commercially funded by the venture capitalists, you know, then others will follow and I'll see huge ecosystem here. Yes. A lot of noise. A lot of people trying to get attention. So I got to ask you, because I want you to address this because I know it's been talked about in some of the other blogs is there's a lot of fud going on around who's doing what? Who's doing what, and in some cases maybe flat out, you know, misinformation and that happens in a growing market, you know, the elbows get sharp. Yes. So I want you share with the audience anything that you want say about the fud around what people say about Cloudera or about others or what you're doing. Just to clarify, cuz there has been, I mean I've gotten back channel information around, you know, not sure the committers this, and it's been, it's been well documented. There's a lot of fu out there. What, what would you say to the folks out there to clarify >>That? Yes, I, I would say that our focus should be to continue to work as a community, to push the platform forwards. I would say that at Cloudera we do a lot of contributions. Horton works definitely is one of the top contributors out there as well. I'll acknowledge that. So as many, many, many other companies and we wanna continue to see the platform evolve. I will stress though that at Cloudera we do have a number of the original project founders working at the company. So it's not just the, the contribution that we bring, but the fact that we have the founders of these projects working at Cloudera. And some of these projects actually were created at Cloudera from day one as opposed to created in some other company. And then you hire the employee and they work for you. So I gave you what examples from Cloudera dot cutting. >>He is the creator of Hudu dot Cutting is also the creator of Luine, which became solar, which is part of the search project that we launched recently. Dot Cutting wasn't with Cloudera from day one, right? So, so when he created these technologies, he actually was at Tia for example, when he created had he was at ta, wasn't at Cloudera. However, he now works for Cloudera. So we get that because now that cutting works for Cloudera. So that's one example. On the flip side, there is projects like Flume and Scoop that are now part of every single distribution out there. And flu and Scoop were both created at Calera. They were actually created inside of Cloudera. Yeah. So the key point is, and and that's what I would like all of the vendors out there that are trying to leverage had and get benefit about out Hadoop is please don't be just takers. >>There are some vendors out there who are just takers. Just wanna take from the open source, take from the open source and don't give back. Right? I'm not gonna name them, but there is a few of them out there. Please, please, please. I mean that that, that is very, very a selfish behavior. It's not gonna help the ecosystem in the long term. We would like to see you both take and give at the same time. So that would be my core message. And that's for example, like I thank Hortonworks because that's exactly what Hortonworks is doing. They're both giving and taking at the same >>Time. You guys have always been clear on that. Nobody, I mean here contribution to open source has been well documented and there's, there's no question about that. John and I have talked about it a lot that you guys help get it all started. And even Haak when we had 'em on a couple years ago, when Horton Works came to the market said, Hey, the more people work on an open source, the better. >>Yeah, >>Exactly. So yeah, it's always been, been your posture. You're not playing games there. Anyways, having said that, you you, you have a strategy to layer on top of that open source some of your own proprietary code. And so you have choices to make Yes. In terms of how you allocate those resources. So as an engineering manager, how do you allocate those resources in terms of, okay, what do we do for the community and what do we do for our own, you know, future because of the business model that we chose? How do you make those trade offs? >>Yes, that's a very, very good question. So first it's important to stress that our core platform, CDH, is open source. Everything we put in the core platform is open source. So for example, in Palo, which we launched very recently as a ga, now we launched beta last year, but now's ga is a hundred percent Apache license, a hundred percent open source search, which we announced very recently is also open source. So the platform itself, we're committing to everything in there to be open source. Now we believe fundamentally just from having lots of history in studying the open source markets from our ceo Mike Olson himself being one of the very first open source people in the world with, with sleepy cats, the company that he sold to Oracle before founding Cloudera from our investors, helping many other open source companies. To have a successful open co open source company, you need to have a very good engine between the business model that generates revenue and between the product that you are creating. If you don't have a good feedback loop there between these two, you won't be able to sustain the innovation to continue to push the, the boundaries of how good the product is. So we strongly believe in that if you are, if your product is literally a hundred percent open source, meaning both the management and every, there is nothing proprietary whatsoever inside of your products. I can't tell what that is. It's >>Taking a picture. >>Oh, sorry, I thought somebody was waiting >>For me. >>Sorry about that. >>It's a cheap signal. >>It >>Was like a's really good. >>I thought it's like a card of paper with some writing. You, >>You, you have a fan fans out there. They're storming the, the concert here. >>Okay, that's, that's good to hear. That's good to hear. Sorry about that interruption. So if, if, if you have everything a hundred percent open source, that creates two problems. First you have no differentiation whatsoever, meaning another big corporation without naming who the big corporations could be, we just can take everything you do, literally every single bit of source code you have and say, Hey, we can do it too. Come to us, don't work with those guys. Right? We have the latest, greatest things that they have. Why do you wanna continue to work with them? So no, no differentiation is number one, which is very dangerous. And number two, when it becomes, if, if it's a hundred percent open source and there is lots of other vendors able to take the art, the open source artifact and work with it, then it becomes now purely about maintenance and insurance on the products, which is a commodity product, which obviously the prices for that will go down to the ground and you won't be able to have this sustain this positive feedback effect between your business model and between your product code map and won't be able to build a long-lasting company. >>So that's why we do have a combination of open source artifacts and proprietary artifacts. Now our pro proprietary AR artifacts is always around the management of the system, right? So how do we manage the security of the system? How do we manage the, the data flow within the system? How do we manage the services inside the, of the system across all layers, right? Not just the Hado player but the edge based layer, the zookeeper layer, et cetera, et cetera. So that's where we focus our efforts going forward and that's how we differentiate ourself from our, from other vendors out there. Cloudera manager, Cloudera navigator are very unique to us. Nobody else has anything close to those capabilities out there. >>So it sounds like the contributions you make to open source are cultural of, of, in nature, I mean DNA of sorts of Right. And so you're, that's something that you guys do cuz you've always done it. Absolutely. And then the, the artifacts that are proprietary are essentially around rationalizing the revenue opportunity with the expense that you're gonna apply there and making a business case decided >>How to balance. That's that's one. And then two, the differentiation from other competitors. So these two things, Yes. >>Okay. >>I believe that's fundamental to business to open source business models. >>Yeah, I mean there are many open source business models, right? You can go pure service, you can go, like you said, you can totally bogart the code. >>There is no, there is no pure service open source model company that was able to build the longlasting surviving public company, never happened in history. They always get acquired because it becomes a commodity. I >>Mean, right. I mean, I mean and even ibm, right? >>Tom or I want to ask you about the storage thing. We were talking before camera, the, the hor and worst announcement storage you, what's your take on that? >>Which one? The Gluster, the one with Red Hats? Yes. Yes. So Red Hats and yeah, there has been recent news about Red Hat with, with Hor Works having a version of the Haddo platform that uses map use for the computation but uses Red Hat for the storage, right? So Red Hat has a new storage offering that was built based off of a company they acquired was called Guster. And that, that news was very, very surprising to me. And it, the reason why it was surprising, it's correlated also with a shift in messaging from, from Horton works. If you look at Horton Works last year at had Summit last year, one of the key messages that they deliver to us is that within the next five years or by 2015, the tagline back then by 2015, and you're doing research right now to see if I'm saying the right thing. By 2015, half the world data data will be on, will be stored in had would be stored in had. Yes. If you look today at the slides, it >>Doesn't say that it says within five years, >>Right? No, no, no. It says, well >>That was the second iteration was within five years. And now they say something >>Different. Now say they say within 2015 by, sorry, by 2015, half the world's data will be processed by Hado and instead of stored by Hado. And that's a very, very fundamental So >>It's a nuance. >>It's a, it's a very important >>Nuance. Well it's a big deal because yes, when I first saw that I said, Hmm, what does this all mean? And then it sounds 2015 sounds a little early. Yes. And now you're saying processed by, Okay that's different. >>Yes, exactly. And and the reason why now is we believe s GFS is very, very core to the had platform. S GFS is very core to had platform, the storage system of had we want. It's really the layer that Mid had with is more than anything else is how scalable, how reliable and how economical the sdfs storage layer is. So we, we really, I mean ask qu works and ask all the companies working in the, in the had community not to fragment at the storage layer. We need the storage for had to stay inside of had and not to fragment that out. That's very, very critical. >>Okay. So but so >>You're saying that they're in indicating through the gesture that, that they're not come out saying we're going to fragment Hgfs, but the way that this is position might signal >>No, no, no. The announcement, the announcement with Red Hat is >>That is the direct signal. It's >>Literally, we, you'll be able to run map produce directly on top of Red Hat storage instead of sdfs. >>Okay. So >>I >>Interpreted it, I interpret it as they were just hortonwork was hedging on its prediction, which I said Okay, I'll give 'em a break on that. You're saying it's something different, >>It's a shift in strategy potentially. Yeah. Which can be dangerous. It's shift in strategy. >>Is that a compliance issue? Cuz you know, the, the Dishon Hads poss Yeah. Red Hat does have a lot of enterprise customers. Yeah. So is that just maybe if >>Then invest in making had poss compliance, which actually by the way, we are as a community investing in that. Yeah. Yes. You must have. Yeah. So we are investing in adding compulsive poss compliance to had, we're investing in adding snapshots into had, which will be coming very, very soon overnight. >>Well, do you think that that pick a year, I don't care if it's 2015 2000, 22,000 whenever that the majority of the world's data will be running into do >>The majority of worse data that has to do with analytics. Yes. Okay. So so there is, >>So that is that >>Is it's very important, the caveat. Yes, exactly. Because there is lots of types of data that are not very suitable for, had at all. For example, that data storage for Oracle systems, for Oracle database systems. No, you wanna store that in an NetApp emc you don't wanna store that in Hao the, the, the, the, the data storage for streaming video files, right? For just streaming lots and lots of video files. No, you don't wanna store that indu. It's >>A huge >>Proportion of the data. Yeah. Which is a huge, huge >>Proportion of data files, in fact that could overwhelm the data. >>Yeah. So the new nuance, like I would say like I agree that the half thing but the half thing within the world of data for the purpose of analysis. >>Yeah. Okay. So that's, that's >>Narrow down the >>Yeah, okay. But it's a more reasonable, But I've, I >>Never, It's still a huge market by the way. It is. Yeah, >>It is. Yes. Okay. So, so what's next for you? A are you, you, you've gone on this, this journey, you start this company. You've, you've been traveling around like crazy working with customers. What's the next phase of aara do's, you know, career? >>What >>Do you want to have happen next? I mean, what, what do you, what excites you? What do you, what are you working on? >>Yeah, it's just to continue to grow cloud there to be the biggest company it can be. I mean, we want to be literally, we want be one of the very few companies that we're able to take an open source model and turn that into a large publicly traded corporation. >>So you've talked about that you guys brought a new CEO on Right. Look at the background of the ceo and it's, you know, clearly it's got some IPO chops. Yes. So that's, that's an aspiration that you guys have put forth. Okay. >>And you're outward facing now. So you're doing a lot of travel. Yes. So what, what, where have, what have your travels taken now? You've been in China, you obviously you've got a European office Yeah. Open. So what's going on internationally? Give us some sound bites of, of what's happening in the field. Yeah, >>So in, in internationally, I mean, Europe definitely is our next big focus right now. And we now have a big operation in Europe and we have an office presence in, in Europe and a big team down there. And it's growing very quickly. I would say Europe is about two years behind the US kind of like that's how the, how the growth usually matters. What's happening here. And yeah, so we, our, our next big market is Europe. We are looking at China. We don't have a big process in China right now. Japan, we have a big presence in Japan. Japan is growing very quickly. So yeah, I mean we're obviously Canada with the US growing very quickly as well. >>Great to have you on the cube again, for me personally and, and for, for Dave. And I wanna say thanks to Cloudera for some great support over the years. You guys have been fantastic. You know, I say it's built a great company. It's so hard to build a company. You guys have done a great job. I gotta ask you the final question because you did bring that first sound bite, which was, I saw the future, this is back when you guys were just in your B round in, in Palo Alto office, just ramping up, just starting to ramp what's next? What do you see as around the corner? Obviously we're on a trajectory right now. A lot of things gonna get done. Positive compliance, a lot of stuff's gonna fill in. The platform's gonna get stronger. Yeah. We think that open source will win. Yeah. Through all the democratization of open source. What's next? What's the, what's around the corner that you're watching personally that you're, that's interesting to you? A or around where this will take us? >>Yeah. So what, what's next is having this, having this vision become true. Having this future vision that, that you refer to become true. Meaning having a single platform that can store all of your data and that can, regardless of the type of that data, and allow you to extract value for different types of workloads, whether that be batch, interactive machine learning or search or more, right? There will be more things that will come to the platform, but how to bring your applications, all of your data applications, how to bring them to your data and all of your data as opposed to have the data go to them. >>And what are the landmines out there that you need to avoid Yes. In the industry and community needs to avoid to make that a reality. >>The, the key landmine, it's, it's a bit technical. The landmine is a bit technical, which is making sure that they, they are vision continues to evolve and that we have the capability to properly have a multi workload resource management system that allows me to run all of these type of workloads without having them step on each other's steps. That's the key key step going forward. And >>Of course, playing well together in the sandbox. And as always, competitive competition is good. And again, Hadup is doing great. Amma Aala, co-founder of Cloudera inside the Cube. This is Silicon Angle and Wiki Bond's exclusive coverage of ADU Summit here in Silicon Valley. Right back with our next guest after the short break.