>> Now we're recording. >> All right. >> Appreciate that, Hannah. >> Yeah, so I mean, I think in general we continue to do very, very well as a company. I think like everybody, there's economic headwinds today that are unavoidable, but I think we have a couple things going for us. One, we're in the cyberspace, which I think is, for the most part, recession proof as an industry. I think the impact of a recession will impact some vendors and some categories, but in general, I think the industry is pretty resilient. It's like the power industry, no? Recession or not, you still need electricity to your house. Cybersecurity is almost becoming a utility like that as far as the needs of companies go. I think for us, we also have the ability to do the security, the security operations, for a lot of companies, and if you look at the value proposition, the ROI for the cost of less than one to maybe two or three, depending on how big you are as a customer, what you'd have to pay for half to three security operations people, we can give you a full security operations. And so the ROI is is almost kind of brain dead simple, and so that keeps us going pretty well. And I think the other areas, we remove all that complexity for people. So in a world where you got other problems to worry about, handling all the security complexity is something that adds to that ROI. So for us, I think what we're seeing is mostly is some of the larger deals are taking a little bit longer than they have, some of the large enterprise deals, 'cause I think they are being a little more cautious about how they spend it, but in general, business is still kind of cranking along. >> Anything you can share with me that you guys have talked about publicly in terms of any metrics, or what can you tell me other than cranking? >> Yeah, I mean, I would just say we're still very, very high growth, so I think our financial profile would kind of still put us clearly in the cyber unicorn position, but I think other than that, we don't really share business metrics as a private- >> Okay, so how about headcount? >> Still growing. So we're not growing as fast as we've been growing, but I don't think we were anyway. I think we kind of, we're getting to the point of critical mass. We'll start to grow in a more kind of normal course and speed. I don't think we overhired like a lot of companies did in the past, even though we added, almost doubled the size of the company in the last 18 months. So we're still hiring, but very kind of targeted to certain roles going forward 'cause I do think we're kind of at critical mass in some of the other functions. >> You disclose headcount or no? >> We do not. >> You don't, okay. And never have? >> Not that I'm aware of, no. >> Okay, on the macro, I don't know if security's recession proof, but it's less susceptible, let's say. I've had Nikesh Arora on recently, we're at Palo Alto's Ignite, and he was saying, "Look," it's just like you were saying, "Larger deal's a little harder." A lot of times customers, he was saying customers are breaking larger deals into smaller deals, more POCs, more approvals, more people to get through the approval, not whole, blah, blah, blah. Now they're a different animal, I understand, but are you seeing similar trends, and how are you dealing with that? >> Yeah, I think the exact same trends, and I think it's just in a world where spending a dollar matters, I think a lot more oversight comes into play, a lot more reviewers, and can you shave it down here? Can you reduce the scope of the project to save money there? And I think it just caused a lot of those things. I think, in the large enterprise, I think most of those deals for companies like us and Palo and CrowdStrike and kind of the upper tier companies, they'll still go through. I think they'll just going to take a lot longer, and, yeah, maybe they're 80% of what they would've been otherwise, but there's still a lot of business to be had out there. >> So how are you dealing with that? I mean, you're talking about you double the size of the company. Is it kind of more focused on go-to-market, more sort of, maybe not overlay, but sort of SE types that are going to be doing more handholding. How have you dealt with that? Or have you just sort of said, "Hey, it is what it is, and we're not going to, we're not going to tactically respond to. We got long-term direction"? >> Yeah, I think it's more the latter. I think for us, it's we've gone through all these things before. It just takes longer now. So a lot of the steps we're taking are the same steps. We're still involved in a lot of POCs, we're involved in a lot of demos, and I don't think that changed. It's just the time between your POC and when someone sends you the PO, there's five more people now got to review things and go through a budget committee and all sorts of stuff like that. I think where we're probably focused more now is adding more and more capabilities just so we continue to be on the front foot of innovation and being relevant to the market, and trying to create more differentiators for us and the competitors. That's something that's just built into our culture, and we don't want to slow that down. And so even though the business is still doing extremely, extremely well, we want to keep investing in kind of technology. >> So the deal size, is it fair to say the initial deal size for new accounts, while it may be smaller, you're adding more capabilities, and so over time, your average contract values will go up? Are you seeing that trend? Or am I- >> Well, I would say I don't even necessarily see our average deal size has gotten smaller. I think in total, it's probably gotten a little bigger. I think what happens is when something like this happens, the old cream rises to the top thing, I think, comes into play, and you'll see some organizations instead of doing a deal with three or four vendors, they may want to pick one or two and really kind of put a lot of energy behind that. For them, they're maybe spending a little less money, but for those vendors who are amongst those getting chosen, I think they're doing pretty good. So our average deal size is pretty stable. For us, it's just a temporal thing. It's just the larger deals take a little bit longer. I don't think we're seeing much of a deal velocity difference in our mid-market commercial spaces, but in the large enterprise it's a little bit slower. But for us, we have ambitious plans in our strategy or on how we want to execute and what we want to build, and so I think we want to just continue to make sure we go down that path technically. >> So I have some questions on sort of the target markets and the cohorts you're going after, and I have some product questions. I know we're somewhat limited on time, but the historical focus has been on SMB, and I know you guys have gone in into enterprise. I'm curious as to how that's going. Any guidance you can give me on mix? Or when I talk to the big guys, right, you know who they are, the big managed service providers, MSSPs, and they're like, "Poo poo on Arctic Wolf," like, "Oh, they're (groans)." I said, "Yeah, that's what they used to say about the PC. It's just a toy. Or Microsoft SQL Server." But so I kind of love that narrative for you guys, but I'm curious from your words as to, what is that enterprise? How's the historical business doing, and how's the entrance into the enterprise going? What kind of hurdles are you having, blockers are you having to remove? Any color you can give me there would be super helpful. >> Yeah, so I think our commercial S&B business continues to do really good. Our mid-market is a very strong market for us. And I think while a lot of companies like to focus purely on large enterprise, there's a lot more mid-market companies, and a much larger piece of the IT puzzle collectively is in mid-market than it is large enterprise. That being said, we started to get pulled into the large enterprise not because we're a toy but because we're quite a comprehensive service. And so I think what we're trying to do from a roadmap perspective is catch up with some of the kind of capabilities that a large enterprise would want from us that a potential mid-market customer wouldn't. In some case, it's not doing more. It's just doing it different. Like, so we have a very kind of hands-on engagement with some of our smaller customers, something we call our concierge. Some of the large enterprises want more of a hybrid where they do some stuff and you do some stuff. And so kind of building that capability into the platform is something that's really important for us. Just how we engage with them as far as giving 'em access to their data, the certain APIs they want, things of that nature, what we're building out for large enterprise, but the demand by large enterprise on our business is enormous. And so it's really just us kind of catching up with some of the kind of the features that they want that we lack today, but many of 'em are still signing up with us, obviously, and in lieu of that, knowing that it's coming soon. And so I think if you look at the growth of our large enterprise, it's one of our fastest growing segments, and I think it shows anything but we're a toy. I would be shocked, frankly, if there's an MSSP, and, of course, we don't see ourself as an MSSP, but I'd be shocked if any of them operate a platform at the scale that ours operates. >> Okay, so wow. A lot I want to unpack there. So just to follow up on that last question, you don't see yourself as an MSSP because why, you see yourselves as a technology platform? >> Yes, I mean, the vast, vast, vast majority of what we deliver is our own technology. So we integrate with third-party solutions mostly to bring in that telemetry. So we've built our own platform from the ground up. We have our own threat intelligence, our own detection logic. We do have our own agents and network sensors. MSSP is typically cobbling together other tools, third party off-the-shelf tools to run their SOC. Ours is all homegrown technology. So I have a whole group called Arctic Wolf Labs, is building, just cranking out ML-based detections, building out infrastructure to take feeds in from a variety of different sources. We have a full integration kind of effort where we integrate into other third parties. So when we go into a customer, we can leverage whatever they have, but at the same time, we produce some tech that if they're lacking in a certain area, we can provide that tech, particularly around things like endpoint agents and network sensors and the like. >> What about like identity, doing your own identity? >> So we don't do our own identity, but we take feeds in from things like Okta and Active Directory and the like, and we have detection logic built on top of that. So part of our value add is we were XDR before XDR was the cool thing to talk about, meaning we can look across multiple attack surfaces and come to a security conclusion where most EDR vendors started with looking just at the endpoint, right? And then they called themselves XDR because now they took in a network feed, but they still looked at it as a separate network detection. We actually look at the things across multiple attack surfaces and stitch 'em together to look at that from a security perspective. In some cases we have automatic detections that will fire. In other cases, we can surface some to a security professional who can go start pulling on that thread. >> So you don't need to purchase CrowdStrike software and integrate it. You have your own equivalent essentially. >> Well, we'll take a feed from the CrowdStrike endpoint into our platform. We don't have to rely on their detections and their alerts, and things of that nature. Now obviously anything they discover we pull in as well, it's just additional context, but we have all our own tech behind it. So we operate kind of at an MSSP scale. We have a similar value proposition in the sense that we'll use whatever the customer has, but once that data kind of comes into our pipeline, it's all our own homegrown tech from there. >> But I mean, what I like about the MSSP piece of your business is it's very high touch. It's very intimate. What I like about what you're saying is that it's software-like economics, so software, software-like part of it. >> That's what makes us the unicorn, right? Is we do have, our concierges is very hands-on. We continue to drive automation that makes our concierge security professionals more efficient, but we always want that customer to have that concierge person as, is almost an extension to their security team, or in some cases, for companies that don't even have a security team, as their security team. As we go down the path, as I mentioned, one of the things we want to be able to do is start to have a more flexible model where we can have that high touch if you want it. We can have the high touch on certain occasions, and you can do stuff. We can have low touch, like we can span the spectrum, but we never want to lose our kind of unique value proposition around the concierge, but we also want to make sure that we're providing an interface that any customer would want to use. >> So given that sort of software-like economics, I mean, services companies need this too, but especially in software, things like net revenue retention and churn are super important. How are those metrics looking? What can you share with me there? >> Yeah, I mean, again, we don't share those metrics publicly, but all's I can continue to repeat is, if you looked at all of our financial metrics, I think you would clearly put us in the unicorn category. I think very few companies are going to have the level of growth that we have on the amount of ARR that we have with the net revenue retention and the churn and upsell. All those aspects continue to be very, very strong for us. >> I want to go back to the sort of enterprise conversation. So large enterprises would engage with you as a complement to their existing SOC, correct? Is that a fair statement or not necessarily? >> It's in some cases. In some cases, they're looking to not have a SOC. So we run into a lot of cases where they want to replace their SIEM, and they want a solution like Arctic Wolf to do that. And so there's a poll, I can't remember, I think it was Forrester, IDC, one of them did it a couple years ago, and they found out that 70% of large enterprises do not want to build the SOC, and it's not 'cause they don't need one, it's 'cause they can't afford it, they can't staff it, they don't have the expertise. And you think about if you're a tech company or a bank, or something like that, of course you can do it, but if you're an international plumbing distributor, you're not going to (chuckles), someone's not going to graduate from Stanford with a cybersecurity degree and go, "Cool, I want to go work for a plumbing distributor in their SOC," right? So they're going to have trouble kind of bringing in the right talent, and as a result, it's difficult to go make a multimillion-dollar investment into a SOC if you're not going to get the quality people to operate it, so they turn to companies like us. >> Got it, so, okay, so you're talking earlier about capabilities that large enterprises require that there might be some gaps, you might lack some features. A couple questions there. One is, when you do some of those, I inferred some of that is integrations. Are those integrations sort of one-off snowflakes or are you finding that you're able to scale those across the large enterprises? That's my first question. >> Yeah, so most of the integrations are pretty straightforward. I think where we run into things that are kind of enterprise-centric, they definitely want open APIs, they want access to our platform, which we don't do today, which we are going to be doing, but we don't do that yet today. They want to do more of a SIEM replacement. So we're really kind of what we call an open XDR platform, so there's things that we would need to build to kind of do raw log ingestion. I mean, we do this today. We have raw log ingestion, we have log storage, we have log searching, but there's like some of the compliance scenarios that they need out of their SIEM. We don't do those today. And so that's kind of holding them back from getting off their SIEM and going fully onto a solution like ours. Then the other one is kind of the level of customization, so the ability to create a whole bunch of custom rules, and that ties back to, "I want to get off my SIEM. I've built all these custom rules in my SIEM, and it's great that you guys do all this automatic AI stuff in the background, but I need these very specific things to be executed on." And so trying to build an interface for them to be able to do that and then also simulate it, again, because, no matter how big they are running their SIEM and their SOC... Like, we talked to one of the largest financial institutions in the world. As far as we were told, they have the largest individual company SOC in the world, and we operate almost 15 times their size. So we always have to be careful because this is a cloud-based native platform, but someone creates some rule that then just craters the performance of the whole platform, so we have to build kind of those guardrails around it. So those are the things primarily that the large enterprises are asking for. Most of those issues are not holding them back from coming. They want to know they're coming, and we're working on all of those. >> Cool, and see, just aside, I was talking to CISO the other day, said, "If it weren't for my compliance and audit group, I would chuck my SIEM." I mean, everybody wants to get rid of their SIEM. >> I've never met anyone who likes their SIEM. >> Do you feel like you've achieved product market fit in the larger enterprise or is that still something that you're sorting out? >> So I think we know, like, we're on a path to do that. We're on a provable path to do that, so I don't think there's any surprises left. I think everything that we know we need to do for that is someone's writing code for it today. It's just a matter of getting it through the system and getting into production. So I feel pretty good about it. I think that's why we are seeing such a high growth rate in our large enterprise business, 'cause we share that feedback with some of those key customers. We have a Customer Advisory Board that we share a lot of this information with. So yeah, I mean, I feel pretty good about what we need to do. We're certainly operate at large enterprise scales, so taking in the amount of the volume of data they're going to have and the types of integrations they need. We're comfortable with that. It's just more or less the interfaces that a large enterprise would want that some of the smaller companies don't ask for. >> Do you have enough tenure in the market to get a sense as to stickiness or even indicators that will lead toward retention? Have you been at it long enough in the enterprise or you still, again, figuring that out? >> Yeah, no, I think we've been at it long enough, and our retention rates are extremely high. If anything, kind of our net retention rates, well over 100% 'cause we have opportunities to upsell into new modules and expanding the coverage of what they have today. I think the areas that if you cornered enterprise that use us and things they would complain about are things I just told you about, right? There's still some things I want to do in my Splunk, and I need an API to pull my data out and put it in my Splunk and stuff like that, and those are the things we want to enable. >> Yeah, so I can't wait till you guys go public because you got Snowflake up here, and you got Veritas down here, and I'm very curious as to where you guys go. When's the IPO? You want to tell me that? (chuckling) >> Unfortunately, it's not up to us right now. You got to get the markets- >> Yeah, I hear you. Right, if the market were better. Well, if the market were better, you think you'd be out? >> Yeah, I mean, we'd certainly be a viable candidate to go. >> Yeah, there you go. I have a question for you because I don't have a SOC. I run a small business with my co-CEO. We're like 30, 40 people W-2s, we got another 50 or so contractors, and I'm always like have one eye, sleep with one eye open 'cause of security. What is your ideal SMB customer? Think S. >> Yeah. >> Would I fit? >> Yeah, I mean you're you're right in the sweet spot. I think where the company started and where we still have a lot of value proposition, which is companies like, like you said it, you sleep with one eye open, but you don't have necessarily the technical acumen to be able to do that security for yourself, and that's where we fit in. We bring kind of this whole security, we call it Security Operations Cloud, to bear, and we have some of the best professionals in the world who can basically be your SOC for less than it would cost you to hire somebody right out of college to do IT stuff. And so the value proposition's there. You're going to get the best of the best, providing you a kind of a security service that you couldn't possibly build on your own, and that way you can go to bed at night and close both eyes. >> So (chuckling) I'm sure something else would keep me up. But so in thinking about that, our Amazon bill keeps growing and growing and growing. What would it, and I presume I can engage with you on a monthly basis, right? As a consumption model, or how's the pricing work? >> Yeah, so there's two models that we have. So typically the kind of the monthly billing type of models would be through one of our MSP partners, where they have monthly billing capabilities. Usually direct with us is more of a longer term deal, could be one, two, or three, or it's up to the customer. And so we have both of those engagement models. Were doing more and more and more through MSPs today because of that model you just described, and they do kind of target the very S in the SMB as well. >> I mean, rough numbers, even ranges. If I wanted to go with the MSP monthly, I mean, what would a small company like mine be looking at a month? >> Honestly, I do not even know the answer to that. >> We're not talking hundreds of thousands of dollars a month? >> No. God, no. God, no. No, no, no. >> I mean, order of magnitude, we're talking thousands, tens of thousands? >> Thousands, on a monthly basis. Yeah. >> Yeah, yeah. Thousands per month. So if I were to budget between 20 and $50,000 a year, I'm definitely within the envelope. Is that fair? I mean, I'm giving a wide range >> That's fair. just to try to make- >> No, that's fair. >> And if I wanted to go direct with you, I would be signing up for a longer term agreement, correct, like I do with Salesforce? >> Yeah, yeah, a year. A year would, I think, be the minimum for that, and, yeah, I think the budget you set aside is kind of right in the sweet spot there. >> Yeah, I'm interested, I'm going to... Have a sales guy call me (chuckles) somehow. >> All right, will do. >> No, I'm serious. I want to start >> I will. >> investigating these things because we sell to very large organizations. I mean, name a tech company. That's our client base, except for Arctic Wolf. We should talk about that. And increasingly they're paranoid about data protection agreements, how you're protecting your data, our data. We write a lot of software and deliver it as part of our services, so it's something that's increasingly important. It's certainly a board level discussion and beyond, and most large organizations and small companies oftentimes don't think about it or try not to. They just put their head in the sand and, "We don't want to be doing that," so. >> Yeah, I will definitely have someone get in touch with you. >> Cool. Let's see. Anything else you can tell me on the product side? Are there things that you're doing that we talked about, the gaps at the high end that you're, some of the features that you're building in, which was super helpful. Anything in the SMB space that you want to share? >> Yeah, I think the biggest thing that we're doing technically now is really trying to drive more and more automation and efficiency through our operations, and that comes through really kind of a generous use of AI. So building models around more efficient detections based upon signal, but also automating the actions of our operators so we can start to learn through the interface. When they do A and B, they always do C. Well, let's just do C for them, stuff like that. Then also building more automation as far as the response back to third-party solutions as well so we can remediate more directly on third-party products without having to get into the consoles or having our customers do it. So that's really just trying to drive efficiency in the system, and that helps provide better security outcomes but also has a big impact on our margins as well. >> I know you got to go, but I want to show you something real quick. I have data. I do a weekly program called "Breaking Analysis," and I have a partner called ETR, Enterprise Technology Research, and they have a platform. I don't know if you can see this. They have a survey platform, and each quarter, they do a survey of about 1,500 IT decision makers. They also have a survey on, they call ETS, Emerging Technology Survey. So it's private companies. And I don't want to go into it too much, but this is a sentiment graph. This is net sentiment. >> Just so you know, all I see is a white- >> Yeah, just a white bar. >> Oh, that's weird. Oh, whiteboard. Oh, here we go. How about that? >> There you go. >> Yeah, so this is a sentiment graph. So this is net sentiment and this is mindshare. And if I go to Arctic Wolf... So it's typical security, right? The 8,000 companies. And when I go here, what impresses me about this is you got a decent mindshare, that's this axis, but you've also got an N in the survey. It's about 1,500 in the survey, It's 479 Arctic Wolf customers responded to this. 57% don't know you. Oh, sorry, they're aware of you, but no plan to evaluate; 19% plan to evaluate, 7% are evaluating; 11%, no plan to utilize even though they've evaluated you; and 1% say they've evaluated you and plan to utilize. It's a small percentage, but actually it's not bad in the random sample of the world about that. And so obviously you want to get that number up, but this is a really impressive position right here that I wanted to just share with you. I do a lot of analysis weekly, and this is a really, it's completely independent survey, and you're sort of separating from the pack, as you can see. So kind of- >> Well, it's good to see that. And I think that just is a further indicator of what I was telling you. We continue to have a strong financial performance. >> Yeah, in a good market. Okay, well, thanks you guys. And hey, if I can get this recording, Hannah, I may even figure out how to write it up. (chuckles) That would be super helpful. >> Yes. We'll get that up. >> And David or Hannah, if you can send me David's contact info so I can get a salesperson in touch with him. (Hannah chuckling) >> Yeah, great. >> Yeah, we'll work on that as well. Thanks so much for both your time. >> Thanks a lot. It was great talking with you. >> Thanks, you guys. Great to meet you. >> Thank you. >> Bye. >> Bye.

(energizing music) >> Welcome back, everyone to the Cube and Druva special presentation of why ransomware isn't your only problem. I'm John Furrier, host of The Cube. We're here with W. Curtis Preston, Curtis Preston as he is known in the industry, Chief Technical Cult Evangelist at Druva. Curtis, great to see you. We're here at why ransomware isn't your only problem. Great to see you. Thanks for coming on. >> Happy to be here. >> So we always see each other events now. Events are back, so it's great to have you here for this special presentation. The white paper from IDC really talks about this in detail. I can get your thoughts, and I'd like you to reflect on the analysis that we've been covering here and the survey data, how it lines up with the real world that you're seeing out there. >> Yeah, I think it's the survey results really, I'd like to say that they surprised me, but unfortunately they didn't. The data protection world has been this way or a while where there's this difference in belief or difference between the belief and the reality. And what we see is that there are a number of organizations that have been successfully hit by ransomware, paid the ransom and or lost data. And yet the same people that were surveyed, they had the high degrees of confidence in their backup system and you know, I could probably go on for an hour as to the various reasons why that would be the case, but I think that this long running problem that as long as I've been associated with backups, which, you know has been a while, it's that problem of, you know nobody wants to be the backup person. And people often just, they don't want to have anything to do with the backup system. And so it sort of exists in this vacuum. And so then management is like, oh the backup system's great, because the backup person often, you know, might say that it's great because maybe it's their job to say so. But the reality has always been very, very different. >> It's funny, you know, we're good boss, we got this covered. >> Good, it's all good, it's all good. >> Yeah, the fingers crossed, right? So again, this is the reality and as it becomes backup and recovery, which we've talked about many times on The Cube, certainly we have with you before, but now with ransomware also, the other thing is people get ransomware hit multiple times. So it's not only like to get hit once. So you know, this is a constant chasing the tail on some ends, but there are some tools out there that you guys have a solution. And so let's get into that. You know, you have had hands on backup experience. What are the points that surprise you the most about what's going on in this world and the realities of how people should be going forward? What's your take? >> Well, I would say that the one part in the survey that surprised me the most was people that had a huge, you know, that there was a huge percentage of people that said that they had a you know, a ransomware response, you know in readiness program. And you look at that and how could you be, that higher percentage of people be comfortable with their ransomware readiness program and you know which includes a number of things, right? There's the cyber attack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so you believe that your company was ready for that, and then you go, and I think it was 67% of the people in the survey paid the ransom, which as as a person who, you know, has spent my entire career trying to help people successfully recover their data that number I think just hurt me the most is that, because you talked about reinfections. The surest way to guarantee that you get re-attacked and reinfected, is to pay the ransom. This goes back all the way, ransom since the beginning of time, right? Everyone knows if you pay the blackmail all you're telling people is that you pay blackmail. >> And you're in business, you're a good customer. ARR, (indistinct) >> Yeah, exactly. So the fact that, you know 60 what, two thirds, of the people that were attacked by ransomware paid the ransom, that one statistic just hurt my heart. >> Yeah, and I think this is the reality. I mean, we go back and even the psychology of the practitioners was, you know, it's super important to get back in recovery, and that's been around for a long time, but now that's an attack vector, okay? And there's dollars involved, like I said the ARR, I'm joking, but there's recurring revenue for the bad guys if they know you're paying up and if you're stupid enough not to change, you're tooling, right? So again, it works both ways. So I got to ask you, why do you think so many owners are unable to successfully respond after an attack? Is it because, they know it's coming, I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding successfully to this? >> I think it's a litany of things starting with the aspect that I mentioned before that nobody wants to have anything to do with the backup system, right? So nobody wants to be the one to raise their hand because if you're the one that raises their hand you know what, that's a good idea, Curtis why don't you look into that? Right, nobody wants to be-- >> Where's that guy now? He doesn't work here anymore. Yeah, but I hear where you come from. >> Exactly. >> Psychology. >> Yeah, so there's that. But then the second is that because of that no one's looking at the fact that backups are the attack vector, they become the attack vector. And so because they're the attack vector they have to be protected as much if not more than the rest of the environment. The rest of the environment can live off of active directory and you know, things like Okta so that you can have SSO and things like that. The backup environment has to be segregated in a very special way. Backups have to be stored completely separate from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment, why? Because if that production environment is compromised now knowing that the attacks or that the backup systems are a significant portion of the attack vector, then if the production system is compromised then the backup system is compromised. So you've got to segregate all of that. And I just don't think that people are thinking about that. You know and they're using the same backup techniques that they've used for many, many years. >> So what you're saying is that the attack vectors and the attackers are getting smarter. They're saying, hey, we'll just take out the backup first so they can't backup, so we got the ransomware. It makes sense. >> Yeah, exactly. The largest ransomware group out there the Conti Ransomware Group, they are specifically targeting specific backup vendors. They know how to recognize the backup servers. They know how to recognize where the backups are stored and they are exfiltrating the backups first and then deleting them, and then letting you know you have ransom. >> Okay, so you guys have a lot of customers. They all kind of have the same problem. What's the patterns that you're seeing? How are they evolving? What are some of the things that they're implementing? What is the best practice? >> Well again, you've got to fully segregate that data. There are, and everything about how that data is stored and everything about how that data's created and accessed, there are ways to do that with other, you know with other commercial products. You can take a standard product and put a number of layers of defense on top of it or you can switch to the way Druva does things which is a SAS offering that stores your data completely in the cloud in our account, right? So your account could be completely compromised. That has nothing to do with our account. And the, it's a completely different authentication and authorization system. You've got multiple layers of defense between your computing environment and where we store your backups. So basically what you get by default with the way Druva stores your backups is the best you can get after doing many, many layers of defense on the other side and having to do all that work. With us, you just log in and you get all of that. >> I guess, how do you break the laws of physics? I guess that's the question here. >> Well, that's the other thing, is that by storing the data in the cloud, we do and I've said this a few times, that you get to break the laws of physics. And the only way to do that is time travel. And that's what... (chuckles) so yeah, so Druva has time travel. This isn't a criticism, by the way. I don't think this is our official position, but the idea is that the only way to restore data as fast as possible is to restore it before you actually need it. And that's what kind of, what I mean by time travel in that you basically, you configure your DR, your disaster recovery environment in Druva one time, and then we are pre restoring your data as often as you tell us to do to bring your DR environment up to the current environment as quickly as we can. So that in a disaster recovery scenario which is part of your ransomware response, right? Again, there are many different parts but when you get to actually restoring the data you should be able to just push a button and go. The data should already be restored. And that's the way that you break the laws of physics, is you break the laws of time. >> Well, everyone wants to know the next question, and this is the real big question is, are you from the future? >> Yeah. Very much the future. >> What's it like in the future? Back at recovery as a restorer, air gaping everything? >> Yeah. It, well it's a world where people don't have to worry about their backups. I like to use the phrase, get out of the backup business. Just get into the restore business. You know, I'm a grandfather now, and I love having a granddaughter and I often make the joke that if I've known how great grandkids were I would've skipped straight to them, right? Not possible. Just like this. Recoveries are great. Backups are really hard. So in the future, if you use a SAS data protection system and data resiliency system, you can just do recoveries and not have to worry about backups. >> Yeah. And what's great about your background is you've got a lot of historical perspective. I've seen that in the ways of innovation. Now it really is about the recovery and real time. So a lot of good stuff going on and got things automated things got to be rocking and rolling. >> Absolutely. Yeah, I do remember again, having worked so hard with many clients over the years, back then we worked so hard just to get the backup done. There was very little time to work on the recovery. And I really, I kid you not that our customers don't have to do all of those things that all of our competitors have to do to you know, to try to break the laws of physics. I've been fighting the laws of physics my entire career to get the backup done in the first place. Then to secure all the data, right, to air gap it and make sure that a ransomware attack isn't going to attack it. Our customers get to get straight to a fully automated disaster recovery environment that they get to test as often as possible and they get to do a full test by simply pressing a single button. And you know, I wish everybody had that ability. >> Yeah, I mean security's a big part of it. Data's in the middle of it. All this is now mainstream, front lines, great stuff. Curtis, great to have you on, bring that perspective, and thanks for the insight. Really appreciate it. >> Always happy to talk about my favorite subject. (bright music)

>>Keon Cloud Native Con kicks off in Detroit on October 24th, and we're pleased to have Stewart Miniman, who's the director of Market Insights, hi, at, for hybrid platforms at Red Hat back in the studio to help us understand the key trends to look for at the events. Do welcome back, like old, old, old >>Home. Thank you, David. It's great to, great to see you and always love doing these previews, even though Dave, come on. How many years have I told you Cloud native con, It's a hoodie crowd. They're gonna totally call you out for where in a tie and things like that. I, I know you want to be an ESPN sportscaster, but you know, I I, I, I still don't think even after, you know, this show's been around for so many years that there's gonna be too many ties into Troy. I >>Know I left the hoodie in my off, I'm sorry folks, but hey, we'll just have to go for it. Okay. Containers generally, and Kubernetes specifically continue to show very strong spending momentum in the ETR survey data. So let's bring up this slide that shows the ETR sectors, all the sectors in the tax taxonomy with net score or spending velocity in the vertical axis and pervasiveness on the horizontal axis. Now, that red dotted line that you see, that marks the elevated 40% mark, anything above that is considered highly elevated in terms of momentum. Now, for years, the big four areas of momentum that shine above all the rest have been cloud containers, rpa, and ML slash ai for the first time in 10 quarters, ML and AI and RPA have dropped below the 40% line, leaving only cloud and containers in rarefied air. Now, Stu, I'm sure this data doesn't surprise you, but what do you make of this? >>Yeah, well, well, Dave, I, I did an interview with at Deepak who owns all the container and open source activity at Amazon earlier this year, and his comment was, the default deployment mechanism in Amazon is containers. So when I look at your data and I see containers and cloud going in sync, yeah, that, that's, that's how we see things. We're helping lots of customers in their overall adoption. And this cloud native ecosystem is still, you know, we're still in that Cambridge explosion of new projects, new opportunities, AI's a great workload for these type type of technologies. So it's really becoming pervasive in the marketplace. >>And, and I feel like the cloud and containers go hand in hand, so it's not surprising to see those two above >>The 40%. You know, there, there's nothing to say that, Look, can I run my containers in my data center and not do the public cloud? Sure. But in the public cloud, the default is the container. And one of the hot discussions we've been having in this ecosystem for a number of years is edge computing. And of course, you know, I want something that that's small and lightweight and can do things really fast. A lot of times it's an AI workload out there, and containers is a great fit at the edge too. So wherever it goes, containers is a good fit, which has been keeping my group at Red Hat pretty busy. >>So let's talk about some of those high level stats that we put together and preview for the event. So it's really around the adoption of open source software and Kubernetes. Here's, you know, a few fun facts. So according to the state of enterprise open source report, which was published by Red Hat, although it was based on a blind survey, nobody knew that that Red Hat was, you know, initiating it. 80% of IT execs expect to increase their use of enterprise open source software. Now, the CNCF community has currently more than 120,000 developers. That's insane when you think about that developer resource. 73% of organizations in the most recent CNCF annual survey are using Kubernetes. Now, despite the momentum, according to that same Red Hat survey, adoption barriers remain for some organizations. Stu, I'd love you to talk about this specifically around skill sets, and then we've highlighted some of the other trends that we expect to see at the event around Stu. I'd love to, again, your, get your thoughts on the preview. You've done a number of these events, automation, security, governance, governance at scale, edge deployments, which you just mentioned among others. Now Kubernetes is eight years old, and I always hear people talking about there's something coming beyond Kubernetes, but it looks like we're just getting started. Yeah, >>Dave, It, it is still relatively early days. The CMC F survey, I think said, you know, 96% of companies when they, when CMC F surveyed them last year, were either deploying Kubernetes or had plans to deploy it. But when I talked to enterprises, nobody has said like, Hey, we've got every group on board and all of our applications are on. It is a multi-year journey for most companies and plenty of them. If you, you look at the general adoption of technology, we're still working through kind of that early majority. We, you know, passed the, the chasm a couple of years ago. But to a point, you and I we're talking about this ecosystem, there are plenty of people in this ecosystem that could care less about containers and Kubernetes. Lots of conversations at this show won't even talk about Kubernetes. You've got, you know, big security group that's in there. >>You've got, you know, certain workloads like we talked about, you know, AI and ml and that are in there. And automation absolutely is playing a, a good role in what's going on here. So in some ways, Kubernetes kind of takes a, a backseat because it is table stakes at this point. So lots of people involved in it, lots of activities still going on. I mean, we're still at a cadence of three times a year now. We slowed it down from four times a year as an industry, but there's, there's still lots of innovation happening, lots of adoption, and oh my gosh, Dave, I mean, there's just no shortage of new projects and new people getting involved. And what's phenomenal about it is there's, you know, end user practitioners that aren't just contributing. But many of the projects were spawned out of work by the likes of Intuit and Spotify and, and many others that created some of the projects that sit alongside or above the, the, you know, the container orchestration itself. >>So before we talked about some of that, it's, it's kind of interesting. It's like Kubernetes is the big dog, right? And it's, it's kind of maturing after, you know, eight years, but it's still important. I wanna share another data point that underscores the traction that containers generally are getting in Kubernetes specifically have, So this is data from the latest ETR survey and shows the spending breakdown for Kubernetes in the ETR data set for it's cut for respondents with 50 or more citations in, in by the IT practitioners that lime green is new adoptions, the forest green is spending 6% or more relative to last year. The gray is flat spending year on year, and those little pink bars, that's 6% or down spending, and the bright red is retirements. So they're leaving the platform. And the blue dots are net score, which is derived by subtracting the reds from the greens. And the yellow dots are pervasiveness in the survey relative to the sector. So the big takeaway here is that there is virtually no red, essentially zero churn across all sectors, large companies, public companies, private firms, telcos, finance, insurance, et cetera. So again, sometimes I hear this things beyond Kubernetes, you've mentioned several, but it feels like Kubernetes is still a driving force, but a lot of other projects around Kubernetes, which we're gonna hear about at the show. >>Yeah. So, so, so Dave, right? First of all, there was for a number of years, like, oh wait, you know, don't waste your time on, on containers because serverless is gonna rule the world. Well, serverless is now a little bit of a broader term. Can I do a serverless viewpoint for my developers that they don't need to think about the infrastructure but still have containers underneath it? Absolutely. So our friends at Amazon have a solution called Fargate, their proprietary offering to kind of hide that piece of it. And in the open source world, there's a project called Can Native, I think it's the second or third can Native Con's gonna happen at the cncf. And even if you use this, I can still call things over on Lambda and use some of those functions. So we know Dave, it is additive and nothing ever dominates the entire world and nothing ever dies. >>So we have, we have a long runway of activities still to go on in containers and Kubernetes. We're always looking for what that next thing is. And what's great about this ecosystem is most of it tends to be additive and plug into the pieces there, there's certain tools that, you know, span beyond what can happen in the container world and aren't limited to it. And there's others that are specific for it. And to talk about the industries, Dave, you know, I love, we we have, we have a community event that we run that's gonna happen at Cubans called OpenShift Commons. And when you look at like, who's speaking there? Oh, we've got, you know, for Lockheed Martin, University of Michigan and I g Bank all speaking there. So you look and it's like, okay, cool, I've got automotive, I've got, you know, public sector, I've got, you know, university education and I've got finance. So all of you know, there is not an industry that is not touched by this. And the general wave of software adoption is the reason why, you know, not just adoption, but the creation of new software is one of the differentiators for companies. And that is what, that's the reason why I do containers, isn't because it's some cool technology and Kubernetes is great to put on my resume, but that it can actually accelerate my developers and help me create technology that makes me respond to my business and my ultimate end users. Well, >>And you know, as you know, we've been talking about the Supercloud a lot and the Kubernetes is clearly enabler to, to Supercloud, but I wanted to go back, you and John Furrier have done so many of, you know, the, the cube cons, but but go back to Docker con before Kubernetes was even a thing. And so you sort of saw this, you know, grow. I think there's what, how many projects are in CNCF now? I mean, hundreds. Hundreds, okay. And so you're, Will we hear things in Detroit, things like, you know, new projects like, you know, Argo and capabilities around SI store and things like that? Well, you're gonna hear a lot about that. Or is it just too much to cover? >>So I, I mean the, the good news, Dave, is that the CNCF really is, is a good steward for this community and new things got in get in. So there's so much going on with the existing projects that some of the new ones sometimes have a little bit of a harder time making a little bit of buzz. One of the more interesting ones is a project that's been around for a while that I think back to the first couple of Cube Cuban that John and I did service Mesh and Istio, which was created by Google, but lived under basically a, I guess you would say a Google dominated governance for a number of years is now finally under the CNCF Foundation. So I talked to a number of companies over the years and definitely many of the contributors over the years that didn't love that it was a Google Run thing, and now it is finally part. >>So just like Kubernetes is, we have SEO and also can Native that I mentioned before also came outta Google and those are all in the cncf. So will there be new projects? Yes. The CNCF is sometimes they, they do matchmaking. So in some of the observability space, there were a couple of projects that they said, Hey, maybe you can go merge down the road. And they ended up doing that. So there's still you, you look at all these projects and if I was an end user saying, Oh my God, there is so much change and so many projects, you know, I can't spend the time in the effort to learn about all of these. And that's one of the challenges and something obviously at Red Hat, we spend a lot of time figuring out, you know, not to make winners, but which are the things that customers need, Where can we help make them run in production for our, our customers and, and help bring some stability and a little bit of security for the overall ecosystem. >>Well, speaking of security, security and, and skill sets, we've talked about those two things and they sort of go hand in hand when I go to security events. I mean, we're at reinforced last summer, we were just recently at the CrowdStrike event. A lot of the discussion is sort of best practice because it's so complicated. And, and, and will you, I presume you're gonna hear a lot of that here because security securing containers now, you know, the whole shift left thing and shield right is, is a complicated matter, especially when you saw with the earlier data from the Red Hat survey, the the gaps are around skill sets. People don't have the skill. So should we expect to hear a lot about that, A lot of sort of how to, how to take advantage of some of these new capabilities? >>Yeah, Dave, absolutely. So, you know, one of the conversations going on in the community right now is, you know, has DevOps maybe played out as we expect to see it? There's a newer term called platform engineering, and how much do I need to do there? Something that I, I know your, your team's written a lot about Dave, is how much do you need to know versus what can you shift to just a platform or a service that I can consume? I've talked a number of times with you since I've been at Red Hat about the cloud services that we offer. So you want to use our offering in the public cloud. Our first recommendation is, hey, we've got cloud services, how much Kubernetes do you really want to learn versus you want to do what you can build on top of it, modernize the pieces and have less running the plumbing and electric and more, you know, taking advantage of the, the technologies there. So that's a big thing we've seen, you know, we've got a big SRE team that can manage that for use so that you have to spend less time worrying about what really is un differentiated heavy lifting and spend more time on what's important to your business and your >>Customers. So, and that's, and that's through a managed service. >>Yeah, absolutely. >>That whole space is just taken off. All right, Stu I'll give you the final word. You know, what are you excited about for, for, for this upcoming event and Detroit? Interesting choice of venue? Yeah, >>Look, first of off, easy flight. I've, I've never been to Detroit, so I'm, I'm willing to give it a shot and hopefully, you know, that awesome airport. There's some, some, some good things there to learn. The show itself is really a choose your own adventure because there's so much going on. The main show of QAN and cloud Native Con is Wednesday through Friday, but a lot of a really interesting stuff happens on Monday and Tuesday. So we talked about things like OpenShift Commons in the security space. There's cloud Native Security Day, which is actually two days and a SIG store event. There, there's a get up show, there's, you know, k native day. There's so many things that if you want to go deep on a topic, you can go spend like a workshop in some of those you can get hands on to. And then at the show itself, there's so much, and again, you can learn from your peers. >>So it was good to see we had, during the pandemic, it tilted a little bit more vendor heavy because I think most practitioners were pretty busy focused on what they could work on and less, okay, hey, I'm gonna put together a presentation and maybe I'm restricted at going to a show. Yeah, not, we definitely saw that last year when I went to LA I was disappointed how few customer sessions there were. It, it's back when I go look through the schedule now there's way more end users sharing their stories and it, it's phenomenal to see that. And the hallway track, Dave, I didn't go to Valencia, but I hear it was really hopping felt way more like it was pre pandemic. And while there's a few people that probably won't come because Detroit, we think there's, what we've heard and what I've heard from the CNCF team is they are expecting a sizable group up there. I know a lot of the hotels right near the, where it's being held are all sold out. So it should be, should be a lot of fun. Good thing I'm speaking on an edge panel. First time I get to be a speaker at the show, Dave, it's kind of interesting to be a little bit of a different role at the show. >>So yeah, Detroit's super convenient, as I said. Awesome. Airports too. Good luck at the show. So it's a full week. The cube will be there for three days, Tuesday, Wednesday, Thursday. Thanks for coming. >>Wednesday, Thursday, Friday, sorry, >>Wednesday, Thursday, Friday is the cube, right? So thank you for that. >>And, and no ties from the host, >>No ties, only hoodies. All right Stu, thanks. Appreciate you coming in. Awesome. And thank you for watching this preview of CubeCon plus cloud Native Con with at Stu, which again starts the 24th of October, three days of broadcasting. Go to the cube.net and you can see all the action. We'll see you there.

(bright inspirational music) >> Welcome back everyone to theCUBE and the Druva special presentation of, "Why Ransomware Isn't Your Only Problem." I'm John Furrier, host of theCUBE. We're here with W. Curtis Preston. Curtis Preston, as you know in the industry, Chief Technical Evangelist at Druva. Curtis, great to see you. We're here at, "Why Ransomware Isn't Your Only Problem." Great to see you. Thanks for coming on. >> Happy to be here. >> So we always see each other events, now events are back. So it's great to have you here for this special presentation. The White Paper from IDC really talks about this in detail. Like to get your thoughts, and I'd like you to reflect on the analysis that we've been covering here and the survey data, how it lines up with the real world that you're seeing out there. >> Yeah, I think it's... The survey results really I'd like to say that they surprised me, but unfortunately they didn't. The data protection world has been this way for a while where there's this difference in belief, or difference between the belief and the reality. And what we see is that there are a number of organizations that have been hit- successfully hit by ransomware, paid the ransom and/or lost data. And yet the same people that were surveyed they had high degrees of confidence in their backup system. And, you know, I could probably go on for an hour as to the various reasons why that would be the case, but I think that this long running problem that as long as I've been associated with backups, which, you know, has been a while, it's that problem of, you know, nobody wants to be the backup person. And people often just they don't want to have anything to do with the backup system. And so it sort of exists in this vacuum. And so then management is like, "Oh, the backup system's great," because the backup person often, you know, might say that it's great because maybe it's their job to say so. But the reality has always been very, very different. >> It's funny, you know, "We're good boss, we got this covered." >> Good. All good. It's all good. >> Fingers crossed, right? So again, this is the reality, and as it becomes backup and recovery, which we've talked about many times on theCUBE, certainly we have with you before, but now with ransomware, also, the other thing is people get ransomware hit multiple times. So it's not only like they get hit once. So, you know, this is a constant chasing the tail on some ends, but there are some tools out there. You guys have a solution. And so let's get into that. You know, you have had hands-on backup experience. What are the points that surprise you the most about what's going on in this world and the realities of how people should be going forward? What's your take? >> Well, I would say that the one part in the survey that surprised me the most was people that had a huge, you know, that there was a huge percentage of people that said that they had a, you know, a ransomware response, you know, and readiness program. And you look at that and how could you be, you know, that high a percentage of people be comfortable with their ransomware readiness program and a, you know, which includes a number of things, right? There's the cyber attack aspect of responding to a ransomware attack, and then there's the recovery aspect. And so you believe that your company was ready for that, and then you go, and I think it was 67% of the people in the survey paid the ransom, which as a person who, you know, has spent my entire career trying to help people successfully recover their data, that number I think just hurt me the most is that because you talked about re-infections the surest way to guarantee that you get re-attacked and reinfected is to pay the ransom. This goes back all the way to ransom since the beginning of time, right? Everyone knows if you pay the blackmail all you're telling people is that you pay blackmail. >> You're in business, you're a good customer. ALR for ransomware. >> Yeah. So, the fact that, you know, 60, what, two-thirds of the people that were attacked by ransomware paid the ransom. That one statistic just, just hurt my heart. >> Yeah. And I think this is the reality. I mean, we go back and even the psychology of the practitioners was, you know, super important to get back in recovery. And that's been around for a long time. But now that's an attack vector, okay? And there's dollars involved, like I said, ALR, I'm joking but there's recurring revenue for the for the bad guys if they know you're paying up and if you're stupid enough not to change you're tooling. Right? So again, it works both ways. So, I got to ask you, why do you think so many organizations are unable to successfully respond after an attack? Is it because- they know it's coming. I mean, they're not that dumb. I mean, they have to know it's coming. Why aren't they responding successfully to this? >> I think it's a litany of things starting with that aspect that I mentioned before that nobody wants to have anything to do with the backup system, right? So, nobody wants to be the one to raise their hand because if you're the one that raises their hand "You know what, that's a good idea, Curtis, why don't you look into that?" Right? Nobody wants to be responsible- >> Where's that guy now? He doesn't work here anymore. Yeah, but I hear where you coming from. Psychology (indistinct). >> Yeah. So there's that. But then the second is that because of that no one's looking at the fact that backups are the attack vector. They become the attack vector. And so because they're the attack vector they have to be protected as much, if not more, than the rest of the environment. The rest of the environment can live off of active directory and, you know, and things like Okta so that you can have SSO and things like that. The backup environment has to be segregated in a very special way. Backups have to be stored completely separate from your environment. The login and authentication and authorization system needs to be completely separate from your typical environment. Why? Because if you, if that production environment is compromised now knowing that the attacks or that the backup systems are a significant portion of the attack vector, if the production system is compromised then the backup system is compromised. So you've got to segregate all of that. And I just don't think that people are thinking about that. You know, and they're using the same backup techniques that they've used for many, many years. >> So what you're saying is that the attack vectors and the attackers are getting smarter. They're saying, "Hey, we'll just take out the backup first so they can't back-up. So we got the ransomware." >> Yeah, exactly. The largest ransomware group out there, the Conti ransomware group, they are specifically targeting specific backup vendors. They know how to recognize the backup servers. They know how to recognize where the backups are stored and they are exfiltrating the backups first and then deleting them and then letting you know you have ransom. Right? >> Okay, so you guys have a lot of customers They all kind of have the same- this problem. What's the patterns that you're seeing? How are they evolving? What are some of the things that they're implementing? What is the best practice? >> Well, again, you've got to fully segregate that data, There are, and everything about how that data is stored and everything about how that data is created and accessed. There are ways to do that with other, you know, with other commercial products. You can take a standard product and put a number of layers of defense on top of it or you can switch to the way Druva does things which is a SaaS offering that stores your data completely in the cloud in our account, right? So your account could be completely compromised. That has nothing to do with our account. And the- it's a completely different authentication and authorization system. You've got multiple layers of defense between your computing environment and where we store your backups. So basically what you get by default with the way Druva stores your backups is the best you can get after doing many, many layers of defense on the other side and having to do all that work with us. You just login and you get all of that. >> I guess how do you break the laws of physics? I guess that's the question here. >> Well, when, because that's the other thing is that by storing the data in the cloud, we do it, and I've said this a few times, that you get to break the laws of physics. And the only way to do that is to, is time travel. And that's what, so yeah. So Druva has time travel. What, and this is a courtisism by the way, I don't think this is our official position, but the idea is that the only way to restore data as fast as possible is to restore it before you actually need it. And that's what kind of what I mean by time travel. In that you, basically, you configure your DR, your disaster recovery environment in Druva one time. And then we are pre-restoring your data as often as you tell us to do, to bring your DR environment up to the, you know, the current environment as quickly as we can so that in a disaster recovery scenario which is part of your ransomware response, right? Again, there are many different parts but when you get to actually restoring the data you should be able to just push a button and go. The data should already be restored. And that's the, that's the way that you of physics is you break the laws of time. >> Well, I and everyone wants to know the next question, and this is the real big question is, are you from the future? (light chuckling) >> Yeah. Very much the future. >> What's it like in the future, back-up recovery, how's it restored? Is it air gapping everything? >> Yeah, it, well, it's a world where people don't have to worry about their backups. I like to use the phrase, "get out of the backup business. Just get into the restore business." I, you know, I'm a grandfather now and I love having a granddaughter and I often make the joke that if I'd have known how great grandkids were I would've skipped straight to them. Right? Not possible. Just like this. Recoveries are great. Backups are really hard. So, in the future, if you use a SaaS data protection system and data resiliency system, you can just do recoveries and not have to worry about backups. >> Yeah. And what's great about your background is you've got a lot of historical perspective. I've seen that in the ways of innovation now it's really is about the recovery and real time. So a lot of good stuff going on and got to think automated. Things got to be rocking and rolling. >> Absolutely. Yeah. I do remember, again, having worked so hard with many clients over the years, back then we worked so hard just to get the backup done. There was very little time to work on the recovery. And I really, I kid you not that our customers don't have to do all of those things that all of our competitors have to do to, you know, to try to break the laws of physics. I've been fighting the laws of physics my entire career to get the backup done in the first place. Then to secure all the data, right? To air gap it and make sure that a ransomware attack isn't going to attack it. Our customers get to get straight to a fully automated disaster recovery environment that they get to test as often as possible and they get to do a full test by simply pressing a single button. And you know, I wish that, I wish everybody had that ability. >> Yeah, I mean, security's a big part of it. Data's in the middle of it. All this is now mainstream front lines. Great stuff. Curtis, great to have you on, bring that perspective and thanks for the insight. Really appreciate it. >> Always happy to talk about my favorite subject. >> Alright. We'll be back in a moment. We'll have Stephen Manley, the CTO, and Anjan Srinivas, the GM and VP of Product Management will join me. You're watching theCUBE, the leader in high tech enterprise coverage. (gentle scientific music)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante at our inaugural super cloud 22 event we further refined the concept of a super cloud iterating on the definition the salient attributes and some examples of what is and what is not a super cloud welcome to this week's wikibon cube insights powered by etr you know snowflake has always been what we feel is one of the strongest examples of a super cloud and in this breaking analysis from our studios in palo alto we unpack our interview with benoit de javille co-founder and president of products at snowflake and we test our super cloud definition on the company's data cloud platform and we're really looking forward to your feedback first let's examine how we defl find super cloudant very importantly one of the goals of super cloud 22 was to get the community's input on the definition and iterate on previous work super cloud is an emerging computing architecture that comprises a set of services which are abstracted from the underlying primitives of hyperscale clouds we're talking about services such as compute storage networking security and other native tooling like machine learning and developer tools to create a global system that spans more than one cloud super cloud as shown on this slide has five essential properties x number of deployment models and y number of service models we're looking for community input on x and y and on the first point as well so please weigh in and contribute now we've identified these five essential elements of a super cloud let's talk about these first the super cloud has to run its services on more than one cloud leveraging the cloud native tools offered by each of the cloud providers the builder of the super cloud platform is responsible for optimizing the underlying primitives of each cloud and optimizing for the specific needs be it cost or performance or latency or governance data sharing security etc but those primitives must be abstracted such that a common experience is delivered across the clouds for both users and developers the super cloud has a metadata intelligence layer that can maximize efficiency for the specific purpose of the super cloud i.e the purpose that the super cloud is intended for and it does so in a federated model and it includes what we call a super pass this is a prerequisite that is a purpose-built component and enables ecosystem partners to customize and monetize incremental services while at the same time ensuring that the common experiences exist across clouds now in terms of deployment models we'd really like to get more feedback on this piece but here's where we are so far based on the feedback we got at super cloud 22. we see three deployment models the first is one where a control plane may run on one cloud but supports data plane interactions with more than one other cloud the second model instantiates the super cloud services on each individual cloud and within regions and can support interactions across more than one cloud with a unified interface connecting those instantiations those instances to create a common experience and the third model superimposes its services as a layer or in the case of snowflake they call it a mesh on top of the cloud on top of the cloud providers region or regions with a single global instantiation a single global instantiation of those services which spans multiple cloud providers this is our understanding from a comfort the conversation with benoit dejaville as to how snowflake approaches its solutions and for now we're going to park the service models we need to more time to flesh that out and we'll propose something shortly for you to comment on now we peppered benoit dejaville at super cloud 22 to test how the snowflake data cloud aligns to our concepts and our definition let me also say that snowflake doesn't use the term data cloud they really want to respect and they want to denigrate the importance of their hyperscale partners nor do we but we do think the hyperscalers today anyway are building or not building what we call super clouds but they are but but people who bar are building super clouds are building on top of hyperscale clouds that is a prerequisite so here are the questions that we tested with snowflake first question how does snowflake architect its data cloud and what is its deployment model listen to deja ville talk about how snowflake has architected a single system play the clip there are several ways to do this you know uh super cloud as as you name them the way we we we picked is is to create you know one single system and that's very important right the the the um [Music] there are several ways right you can instantiate you know your solution uh in every region of a cloud and and you know potentially that region could be a ws that region could be gcp so you are indeed a multi-cloud solution but snowflake we did it differently we are really creating cloud regions which are superposed on top of the cloud provider you know region infrastructure region so we are building our regions but but where where it's very different is that each region of snowflake is not one in instantiation of our service our service is global by nature we can move data from one region to the other when you land in snowflake you land into one region but but you can grow from there and you can you know exist in multiple clouds at the same time and that's very important right it's not one single i mean different instantiation of a system is one single instantiation which covers many cloud regions and many cloud providers snowflake chose the most advanced level of our three deployment models dodgeville talked about too presumably so it could maintain maximum control and ensure that common experience like the iphone model next we probed about the technical enablers of the data cloud listen to deja ville talk about snow grid he uses the term mesh and then this can get confusing with the jamaicani's data mesh concept but listen to benoit's explanation well as i said you know first we start by building you know snowflake regions we have today furry region that spawn you know the world so it's a worldwide worldwide system with many regions but all these regions are connected together they are you know meshed together with our technology we name it snow grid and that makes it hard because you know regions you know azure region can talk to a ws region or gcp regions and and as a as a user of our cloud you you don't see really these regional differences that you know regions are in different you know potentially clown when you use snowflake you can exist your your presence as an organization can be in several regions several clouds if you want geographic and and and both geographic and cloud provider so i can share data irrespective of the the cloud and i'm in the snowflake data cloud is that correct i can do that today exactly and and that's very critical right what we wanted is to remove data silos and and when you instantiate a system in one single region and that system is locked in that region you cannot communicate with other parts of the world you are locking the data in one region right and we didn't want to do that we wanted you know data to be distributed the way customer wants it to be distributed across the world and potentially sharing data at world scale now maybe there are many ways to skin the other cat meaning perhaps if a platform does instantiate in multiple places there are ways to share data but this is how snowflake chose to approach the problem next question how do you deal with latency in this big global system this is really important to us because while snowflake has some really smart people working as engineers and and the like we don't think they've solved for the speed of light problem the best people working on it as we often joke listen to benoit deja ville's comments on this topic so yes and no the the way we do it it's very expensive to do that because generally if you want to join you know data which is in which are in different regions and different cloud it's going to be very expensive because you need to move you know data every time you join it so the way we do it is that you replicate the subset of data that you want to access from one region from other regions so you can create this data mesh but data is replicated to make it very cheap and very performant too and is the snow grid does that have the metadata intelligence yes to actually can you describe that a little bit yeah snow grid is both uh a way to to exchange you know metadata about so each region of snowflake knows about all the other regions of snowflake every time we create a new region diary you know the metadata is distributed over our data cloud not only you know region knows all the regions but knows you know every organization that exists in our clouds where this organization is where data can be replicated by this organization and then of course it's it's also used as a way to uh uh exchange data right so you can exchange you know beta by scale of data size and we just had i was just receiving an email from one of our customers who moved more than four petabytes of data cross-region cross you know cloud providers in you know few days and you know it's a lot of data so it takes you know some time to move but they were able to do that online completely online and and switch over you know to the diff to the other region which is failover is very important also so yes and no probably means typically no he says yes and no probably means no so it sounds like snowflake is selectively pulling small amounts of data and replicating it where necessary but you also heard him talk about the metadata layer which is one of the essential aspects of super cloud okay next we dug into security it's one of the most important issues and we think one of the hardest parts related to deploying super cloud so we've talked about how the cloud has become the first line of defense for the cso but now with multi-cloud you have multiple first lines of defense and that means multiple shared responsibility models and multiple tool sets from different cloud providers and an expanded threat surface so listen to benoit's explanation here please play the clip this is a great question uh security has always been the most important aspect of snowflake since day one right this is the question that every customer of ours has you know how you can you guarantee the security of my data and so we secure data really tightly in region we have several layers of security it starts by by encrypting it every data at rest and that's very important a lot of customers are not doing that right you hear these attacks for example on on cloud you know where someone left you know their buckets uh uh open and then you know you can access the data because it's a non-encrypted uh so we are encrypting everything at rest we are encrypting everything in transit so a region is very secure now you know you never from one region you never access data from another region in snowflake that's why also we replicate data now the replication of that data across region or the metadata for that matter is is really highly secure so snow grits ensure that everything is encrypted everything is you know we have multiple you know encryption keys and it's you know stored in hardware you know secure modules so we we we built you know snow grids such that it's secure and it allows very secure movement of data so when we heard this explanation we immediately went to the lowest common denominator question meaning when you think about how aws for instance deals with data in motion or data and rest it might be different from how another cloud provider deals with it so how does aws uh uh uh differences for example in the aws maturity model for various you know cloud capabilities you know let's say they've got a faster nitro or graviton does it do do you have to how does snowflake deal with that do they have to slow everything else down like imagine a caravan cruising you know across the desert so you know every truck can keep up let's listen it's a great question i mean of course our software is abstracting you know all the cloud providers you know infrastructure so that when you run in one region let's say aws or azure it doesn't make any difference as far as the applications are concerned and and this abstraction of course is a lot of work i mean really really a lot of work because it needs to be secure it needs to be performance and you know every cloud and it has you know to expose apis which are uniform and and you know cloud providers even though they have potentially the same concept let's say blob storage apis are completely different the way you know these systems are secure it's completely different the errors that you can get and and the retry you know mechanism is very different from one cloud to the other performance is also different we discovered that when we were starting to port our software and and and you know we had to completely rethink how to leverage blob storage in that cloud versus that cloud because just of performance too so we had you know for example to you know stripe data so all this work is work that's you know you don't need as an application because our vision really is that applications which are running in our data cloud can you know be abstracted of all this difference and and we provide all the services all the workload that this application need whether it's transactional access to data analytical access to data you know managing you know logs managing you know metrics all of these is abstracted too such that they are not you know tied to one you know particular service of one cloud and and distributing this application across you know many regions many cloud is very seamless so from that answer we know that snowflake takes care of everything but we really don't understand the performance implications in you know in that specific case but we feel pretty certain that the promises that snowflake makes around governance and security within their data sharing construct construct will be kept now another criterion that we've proposed for super cloud is a super pass layer to create a common developer experience and an enabler for ecosystem partners to monetize please play the clip let's listen we build it you know a custom build because because as you said you know what exists in one cloud might not exist in another cloud provider right so so we have to build you know on this all these this components that modern application mode and that application need and and and and that you know goes to machine learning as i say transactional uh analytical system and the entire thing so such that they can run in isolation basically and the objective is the developer experience will be identical across those clouds yes right the developers doesn't need to worry about cloud provider and actually our system we have we didn't talk about it but the marketplace that we have which allows actually to deliver we're getting there yeah okay now we're not going to go deep into ecosystem today we've talked about snowflakes strengths in this regard but snowflake they pretty much ticked all the boxes on our super cloud attributes and definition we asked benoit dejaville to confirm that this is all shipping and available today and he also gave us a glimpse of the future play the clip and we are still developing it you know the transactional you know unistore as we call it was announced in last summit so so they are still you know working properly but but but that's the vision right and and and that's important because we talk about the infrastructure right you mentioned a lot about storage and compute but it's not only that right when you think about application they need to use the transactional database they need to use an analytical system they need to use you know machine learning so you need to provide also all these services which are consistent across all the cloud providers so you can hear deja ville talking about expanding beyond taking advantage of the core infrastructure storage and networking et cetera and bringing intelligence to the data through machine learning and ai so of course there's more to come and there better be at this company's valuation despite the recent sharp pullback in a tightening fed environment okay so i know it's cliche but everyone's comparing snowflakes and data bricks databricks has been pretty vocal about its open source posture compared to snowflakes and it just so happens that we had aligotsy on at super cloud 22 as well he wasn't in studio he had to do remote because i guess he's presenting at an investor conference this week so we had to bring him in remotely now i didn't get to do this interview john furrier did but i listened to it and captured this clip about how data bricks sees super cloud and the importance of open source take a listen to goatzee yeah i mean let me start by saying we just we're big fans of open source we think that open source is a force in software that's going to continue for you know decades hundreds of years and it's going to slowly replace all proprietary code in its way we saw that you know it could do that with the most advanced technology windows you know proprietary operating system very complicated got replaced with linux so open source can pretty much do anything and what we're seeing with the data lake house is that slowly the open source community is building a replacement for the proprietary data warehouse you know data lake machine learning real-time stack in open source and we're excited to be part of it for us delta lake is a very important project that really helps you standardize how you lay out your data in the cloud and with it comes a really important protocol called delta sharing that enables you in an open way actually for the first time ever share large data sets between organizations but it uses an open protocol so the great thing about that is you don't need to be a database customer you don't even like databricks you just need to use this open source project and you can now securely share data sets between organizations across clouds and it actually does so really efficiently just one copy of the data so you don't have to copy it if you're within the same cloud so the implication of ellie gotzi's comments is that databricks with delta sharing as john implied is playing a long game now i don't know if enough about the databricks architecture to comment in detail i got to do more research there so i reached out to my two analyst friends tony bear and sanji mohan to see what they thought because they cover these companies pretty closely here's what tony bear said quote i've viewed the divergent lake house strategies of data bricks and snowflake in the context of their roots prior to delta lake databrick's prime focus was the compute not the storage layer and more specifically they were a compute engine not a database snowflake approached from the opposite end of the pool as they originally fit the mold of the classic database company rather than a specific compute engine per se the lake house pushes both companies outside of their original comfort zones data bricks to storage snowflake to compute engine so it makes perfect sense for databricks to embrace the open source narrative at the storage layer and for snowflake to continue its walled garden approach but in the long run their strategies are already overlapping databricks is not a 100 open source company its practitioner experience has always been proprietary and now so is its sql query engine likewise snowflake has had to open up with the support of iceberg for open data lake format the question really becomes how serious snowflake will be in making iceberg a first-class citizen in its environment that is not necessarily officially branding a lake house but effectively is and likewise can databricks deliver the service levels associated with walled gardens through a more brute force approach that relies heavily on the query engine at the end of the day those are the key requirements that will matter to data bricks and snowflake customers end quote that was some deep thought by by tony thank you for that sanjay mohan added the following quote open source is a slippery slope people buy mobile phones based on open source android but it's not fully open similarly databricks delta lake was not originally fully open source and even today its photon execution engine is not we are always going to live in a hybrid world snowflake and databricks will support whatever model works best for them and their customers the big question is do customers care as deeply about which vendor has a higher degree of openness as we technology people do i believe customers evaluation criteria is far more nuanced than just to decipher each vendor's open source claims end quote okay so i had to ask dodgeville about their so-called wall garden approach and what their strategy is with apache iceberg here's what he said iceberg is is very important so just to to give some context iceberg is an open you know table format right which was you know first you know developed by netflix and netflix you know put it open source in the apache community so we embrace that's that open source standard because because it's widely used by by many um many you know companies and also many companies have you know really invested a lot of effort in building you know big data hadoop solution or data like solution and they want to use snowflake and they couldn't really use snowflake because all their data were in open you know formats so we are embracing icebergs to help these companies move through the cloud but why we have been relentless with direct access to data direct access to data is a little bit of a problem for us and and the reason is when you direct access to data now you have direct access to storage now you have to understand for example the specificity of one cloud versus the other so as soon as you start to have direct access to data you lose your you know your cloud diagnostic layer you don't access data with api when you have direct access to data it's very hard to secure data because you need to grant access direct access to tools which are not you know protected and you see a lot of you know hacking of of data you know because of that so so that was not you know direct access to data is not serving well our customers and that's why we have been relented to do that because it's it's cr it's it's not cloud diagnostic it's it's you you have to code that you have to you you you need a lot of intelligence while apis access so we want open apis that's that's i guess the way we embrace you know openness is is by open api versus you know you access directly data here's my take snowflake is hedging its bets because enough people care about open source that they have to have some open data format options and it's good optics and you heard benoit deja ville talk about the risks of directly accessing the data and the complexities it brings now is that maybe a little fud against databricks maybe but same can be said for ollie's comments maybe flooding the proprietaryness of snowflake but as both analysts pointed out open is a spectrum hey i remember unix used to equal open systems okay let's end with some etr spending data and why not compare snowflake and data bricks spending profiles this is an xy graph with net score or spending momentum on the y-axis and pervasiveness or overlap in the data set on the x-axis this is data from the january survey when snowflake was holding above 80 percent net score off the charts databricks was also very strong in the upper 60s now let's fast forward to this next chart and show you the july etr survey data and you can see snowflake has come back down to earth now remember anything above 40 net score is highly elevated so both companies are doing well but snowflake is well off its highs and data bricks has come down somewhat as well databricks is inching to the right snowflake rocketed to the right post its ipo and as we know databricks wasn't able to get to ipo during the covet bubble ali gotzi is at the morgan stanley ceo conference this week they got plenty of cash to withstand a long-term recession i'm told and they've started the message that they're a billion dollars in annualized revenue i'm not sure exactly what that means i've seen some numbers on their gross margins i'm not sure what that means i've seen some numbers on their net retention revenue or net revenue retention again i'll reserve judgment until we see an s1 but it's clear both of these companies have momentum and they're out competing in the market well as always be the ultimate arbiter different philosophies perhaps is it like democrats and republicans well it could be but they're both going after a solving data problem both companies are trying to help customers get more value out of their data and both companies are highly valued so they have to perform for their investors to paraphrase ralph nader the similarities may be greater than the differences okay that's it for today thanks to the team from palo alto for this awesome super cloud studio build alex myerson and ken shiffman are on production in the palo alto studios today kristin martin and sheryl knight get the word out to our community rob hoff is our editor-in-chief over at siliconangle thanks to all please check out etr.ai for all the survey data remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcasts i publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante at siliconangle.com or dm me at devellante or comment on my linkedin posts and please as i say etr has got some of the best survey data in the business we track it every quarter and really excited to be partners with them this is dave vellante for the cube insights powered by etr thanks for watching and we'll see you next time on breaking analysis [Music] you

>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

(upbeat music) >> Hello everyone. We're here at theCUBE startup showcase made possible by AWS. Thanks so much for joining us today. You know, when Zhamak Dehghani was formulating her ideas around data mesh, she wasn't the only one thinking about decentralized data architectures. HelloFresh was going into hyper-growth mode and realized that in order to support its scale, it needed to rethink how it thought about data. Like many companies that started in the early part of the last decade, HelloFresh relied on a monolithic data architecture and the internal team it had concerns about its ability to support continued innovation at high velocity. The company's data team began to think about the future and work backwards from a target architecture, which possessed many principles of so-called data mesh, even though they didn't use that term specifically. The company is a strong example of an early but practical pioneer of data mesh. Now, there are many practitioners and stakeholders involved in evolving the company's data architecture many of whom are listed here on this slide. Two are highlighted in red and joining us today. We're really excited to welcome you to theCUBE, Clemence Chee, who is the global senior director for data at HelloFresh, and Christoph Sawade, who's the global senior director of data also of course at HelloFresh. Folks, welcome. Thanks so much for making some time today and sharing your story. >> Thank you very much. >> Thanks, Dave. >> All right, let's start with HelloFresh. You guys are number one in the world in your field. You deliver hundreds of millions of meals each year to many, many millions of people around the globe. You're scaling. Christoph, tell us a little bit more about your company and its vision. >> Yeah. Should I start or Clemence? Maybe take over the first piece because Clemence has actually been longer a director at HelloFresh. >> Yeah go ahead Clemence. >> I mean, yes, about approximately six years ago I joined and HelloFresh, and I didn't think about the startup I was joining would eventually IPO. And just two years later, HelloFresh went public. And approximately three years and 10 months after HelloFresh was listed on the German stock exchange which was just last week, HelloFresh was included in the DAX Germany's leading stock market index and that, to mind a great, great milestone, and I'm really looking forward and I'm very excited for the future for HelloFresh and also our data. The vision that we have is to become the world's leading food solution group. And there are a lot of attractive opportunities. So recently we did launch and expand in Norway. This was in July. And earlier this year, we launched the US brand, Green Chef, in the UK as well. We're committed to launch continuously different geographies in the next coming years and have a strong path ahead of us. With the acquisition of ready to eat companies like factor in the US and the plant acquisition of Youfoodz in Australia, we are diversifying our offer, now reaching even more and more untapped customer segments and increase our total address for the market. So by offering customers and growing range of different alternatives to shop food and to consume meals, we are charging towards this vision and this goal to become the world's leading integrated food solutions group. >> Love it. You guys are on a rocket ship. You're really transforming the industry. And as you expand your TAM, it brings us to sort of the data as a core part of that strategy. So maybe you guys could talk a little bit about your journey as a company, specifically as it relates to your data journey. I mean, you began as a startup, you had a basic architecture and like everyone, you've made extensive use of spreadsheets, you built a Hadoop based system that started to grow. And when the company IPO'd, you really started to explode. So maybe describe that journey from a data perspective. >> Yes, Dave. So HelloFresh by 2015, approximately had evolved what amount, a classical centralized data management set up. So we grew very organically over the years, and there were a lot of very smart people around the globe, really building the company and building our infrastructure. This also means that there were a small number of internal and external sources, data sources, and a centralized BI team with a number of people producing different reports, different dashboards and, and products for our executives, for example, or for different operations teams to see a company's performance and knowledge was transferred just by our talking to each other face-to-face conversations. And the people in the data warehouse team were considered as the data wizard or as the ETL wizard. Very classical challenges. And it was ETL, who reserved, indicated the kind of like a style of knowledge of data management, right? So our central data warehouse team then was responsible for different type of verticals in different domains, different geographies. And all this setup gave us in the beginning, the flexibility to grow fast as a company in 2015. >> Christoph, anything to add to that? >> Yes, not explicitly to that one, but as, as Clemence said, right, this was kind of the setup that actually worked for us quite a while. And then in 2017, when HelloFresh went public, the company also grew rapidly. And just to give you an idea how that looked like as well, the tech departments have actually increased from about 40 people to almost 300 engineers. And in the same way as the business units, as there Clemence has described, also grew sustainably. So we continue to launch HelloFresh in new countries, launched new brands like Every Plate, and also acquired other brands like we have Factor. And that grows also from a data perspective, the number of data requests that the central (mumbles), we're getting become more and more and more, and also more and more complex. So that for the team meant that they had a fairly high mental load. So they had to achieve a very, or basically get a very deep understanding about the business and also suffered a lot from this context, switching back and forth. Essentially, they had to prioritize across our product requests from our physical product, digital product, from a physical, from, sorry, from the marketing perspective, and also from the central reporting teams. And in a nutshell, this was very hard for these people, and that altered situations that let's say the solution that we have built. We can not really optimal. So in a, in a, in a, in a nutshell, the central function became a bottleneck and slow down of all the innovation of the company. >> It's a classic case. Isn't it? I mean, Clemence, you see, you see the central team becomes a bottleneck, and so the lines of business, the marketing team, sales teams say "Okay, we're going to take things into our own hands." And then of course IT and the technical team is called in later to clean up the mess. Maybe, maybe I'm overstating it, but, but that's a common situation. Isn't it? >> Yeah this is what exactly happened. Right. So we had a bottleneck, we had those central teams, there was always a bit of tension. Analytics teams then started in those business domains like marketing, supply chain, finance, HR, and so on started really to build their own data solutions. At some point you have to get the ball rolling, right? And then continue the trajectory, which means then that the data pipelines didn't meet the engineering standards. And there was an increased need for maintenance and support from central teams. Hence over time, the knowledge about those pipelines and how to maintain a particular infrastructure, for example, left the company, such that most of those data assets and data sets that turned into a huge debt with decreasing data quality, also decreasing lack of trust, decreasing transparency. And this was an increasing challenge where a majority of time was spent in meeting rooms to align on, on data quality for example. >> Yeah. And the point you were making Christoph about context switching, and this is, this is a point that Zhamak makes quite often as we've, we've, we've contextualized our operational systems like our sales systems, our marketing systems, but not our, our data systems. So you're asking the data team, okay, be an expert in sales, be an expert in marketing, be an expert in logistics, be an expert in supply chain and it's start, stop, start, stop. It's a paper cut environment, and it's just not as productive. But, but, and the flip side of that is when you think about a centralized organization, you think, hey, this is going to be a very efficient way across functional team to support the organization, but it's not necessarily the highest velocity, most effective organizational structure. >> Yeah. So, so I agree with that piece, that's up to a certain scale. A centralized function has a lot of advantages, right? So it's a tool for everyone, which would go to a destined kind of expert team. However, if you see that you actually would like to accelerate that in specific as the type of growth. But you want to actually have autonomy on certain teams and move the teams, or let's say the data to the experts in these teams. And this, as you have mentioned, right, that increases mental load. And you can either internally start splitting your team into different kinds of sub teams focusing on different areas, however, that is then again, just adding another piece where actually collaboration needs to happen because the external seized, so why not bridging that gap immediately and actually move these teams end to end into the, into the function themselves. So maybe just to continue what Clemence was saying, and this is actually where our, so, Clemence and my journey started to become one joint journey. So Clemence was coming actually from one of these teams who builds their own solutions. I was basically heading the platform team called data warehouse team these days. And in 2019, where (mumbles) become more and more serious, I would say, so more and more people have recognized that this model does not really scale, in 2019, basically the leadership of the company came together and identified data as a key strategic asset. And what we mean by that, that if he leveraged it in a, in a, an appropriate way, it gives us a unique, competitive advantage, which could help us to, to support and actually fully automate our decision making process across the entire value chain. So once we, what we're trying to do now, or what we would be aiming for is that HelloFresh is able to build data products that have a purpose. We're moving away from the idea that it's just a bi-product. We have a purpose why we would like to collect this data. There's a clear business need behind that. And because it's so important to, for the company as a business, we also want to provide them as a trustworthy asset to the rest of the organization. We'd say, this is the best customer experience, but at least in a way that users can easily discover, understand and securely access, high quality data. >> Yeah. So, and, and, and Clemence, when you see Zhamak's writing, you see, you know, she has the four pillars and the principles. As practitioners, you look at that say, okay, hey, that's pretty good thinking. And then now we have to apply it. And that's where the devil meets the details. So it's the for, the decentralized data ownership, data as a product, which we'll talk about a little bit, self-serve, which you guys have spent a lot of time on, and Clemence your wheelhouse, which is, which is governance and a federated governance model. And it's almost like if you, if you achieve the first two, then you have to solve for the second two, it almost creates a new challenges, but maybe you could talk about that a little bit as to how it relates to HelloFresh. >> Yes. So Chris has mentioned that we identified kind of a challenge beforehand and said, how can we actually decentralized and actually empower the different colleagues of ours? And this was more a, we realized that it was more an organizational or a cultural change. And this is something that someone also mentioned. I think ThoughtWorks mentioned one of the white papers, it's more of an organizational or a cultural impact. And we kicked off a phased reorganization, or different phases we're currently on, in the middle of still, but we kicked off different phases of organizational restructuring or reorganization trying to lock this data at scale. And the idea was really moving away from ever growing complex matrix organizations or matrix setups and split between two different things. One is the value creation. So basically when people ask the question, what can we actually do? What should we do? This is value creation and the how, which is capability building, and both are equal in authority. This actually then creates a high urge in collaboration and this collaboration breaks up the different silos that were built. And of course, this also includes different needs of staffing for teams staffing with more, let's say data scientists or data engineers, data professionals into those business domains, enhance, or some more capability building. >> Okay, go ahead. Sorry. >> So back to Zhamak Dehghani. So we, the idea also then crossed over when she published her papers in May, 2019. And we thought, well, the four pillars that she described were around decentralized data ownership, product, data as a product mindset, we have a self-service infrastructure. And as you mentioned, federated computational governance. And this suited very much with our thinking at that point of time to reorganize the different teams and this then that to not only organizational restructure, but also in completely new approach of how we need to manage data, through data. >> Got it. Okay. So your businesses is exploding. The data team was having to become domain experts to many areas, constantly context switching as we said, people started to take things into their own hands. So again, we said classic story, but, but you didn't let it get out of control and that's important. And so we, we actually have a picture of kind of where you're going today and it's evolved into this, Pat, if you could bring up the picture with the, the elephant, here we go. So I will talk a little bit about the architecture. It doesn't show it here, the spreadsheet era, but Christoph, maybe you could talk about that. It does show the Hadoop monolith, which exists today. I think that's in a managed hosting service, but, but you, you preserve that piece of it. But if I understand it correctly, everything is evolving to the cloud. I think you're running a lot of this or all of it in AWS. You've got, everybody's got their own data sources. You've got a data hub, which I think is enabled by a master catalog for discovery and all this underlying technical infrastructure that is, is really not the focus of this conversation today. But the key here, if I understand correctly is these domains are autonomous and that not only this required technical thinking, but really supportive organizational mindset, which we're going to talk about today. But, but Christoph, maybe you could address, you know, at a high level, some of the architectural evolution that you guys went through. >> Yeah, sure. Yeah. Maybe it's also a good summary about the entire history. So as you have mentioned, right, we started in the very beginning, it's a monolith on the operational plan, right? Actually it wasn't just one model it was two, one for the backend and one for the front end. And our analytical plan was essentially a couple of spreadsheets. And I think there's nothing wrong with spreadsheets, but it allows you to store information, it allows you to transform data, it allows you to share this information, it allows you to visualize this data, but all kind of, it's not actually separating concern, right? Every single one tool. And this means that it's obviously not scalable, right? You reach the point where this kind of management's set up in, or data management is in one tool, reached elements. So what we have started is we created our data lake, as we have seen here on our dupe. And just in the very beginning actually reflected very much our operation upon this. On top of that, we used Impala as a data warehouse, but there was not really a distinction between what is our data warehouse and what is our data lakes as the Impala was used as kind of both as a kind of engine to create a warehouse and data lake constructed itself. And this organic growth actually led to a situation. As I think it's clear now that we had the centralized model as, for all the domains that were really lose Kimball, the modeling standards and there's new uniformity we used to actually build, in-house, a base of building materialized use, of use that we have used for the presentation there. There was a lot of duplication of effort. And in the end, essentially the amendments and feedback tool, which helped us to, to improve of what we, have built during the end in a natural, as you said, the lack of trust. And this basically was a starting point for us to understand, okay, how can we move away? And there are a lot of different things that we can discuss of apart from this organizational structure that we have set up here, we have three or four pillars from Zhamak. However, there's also the next, extra question around, how do we implement product, right? What are the implications on that level and I think that is, that's something that we are, that we are currently still in progress. >> Got it. Okay. So I wonder if we could talk about, switch gears a little bit, and talk about the organizational and cultural challenges that you faced. What were those conversations like? And let's, let's dig into that a little bit. I want to get into governance as well. >> The conversations on the cultural change. I mean, yes, we went through a hyper growth through the last year, and obviously there were a lot of new joiners, a lot of different, very, very smart people joining the company, which then results that collaborations got a bit more difficult. Of course, the time zone changes. You have different, different artifacts that you had recreated in documentation that were flying around. So we were, we had to build the company from scratch, right? Of course, this then resulted always this tension, which I described before. But the most important part here is that data has always been a very important factor at HelloFresh, and we collected more of this data and continued to improve, use data to improve the different key areas of our business. Even when organizational struggles like the central (mumbles) struggles, data somehow always helped us to grow through this kind of change, right? In the end, those decentralized teams in our local geographies started with solutions that serve the business, which was very, very important. Otherwise, we wouldn't be at the place where we are today, but they did violate best practices and standards. And I always use the sports analogy, Dave. So like any sport, there are different rules and regulations that need to be followed. These routes are defined by, I'll call it, the sports association. And this is what you can think about other data governance and then our compliance team. Now we add the players to it who need to follow those rules and abide by them. This is what we then call data management. Now we have the different players, the professionals they also need to be trained and understand the strategy and the rules before they can play. And this is what I then called data literacy. So we realized that we need to focus on helping our teams to develop those capabilities and teach the standards for how work is being done to truly drive functional excellence in the different domains. And one of our ambition of our data literacy program for example, is to really empower every employee at HelloFresh, everyone, to make the right data-informed decisions by providing data education that scales (mumbles), and that can be different things. Different things like including data capabilities with, in the learning path for example, right? So help them to create and deploy data products, connecting data, producers, and data consumers, and create a common sense and more understanding of each other's dependencies, which is important. For example, SIS, SLO, state of contracts, et cetera, people get more of a sense of ownership and responsibility. Of course, we have to define what it means. What does ownership means? What does responsibility mean? But we are teaching this to our colleagues via individual learning patterns and help them upscale to use also their shared infrastructure, and those self-service data applications. And of all to summarize, we are still in this progress of learning. We're still learning as well. So learning never stops at Hello Fresh, but we are really trying this to make it as much fun as possible. And in the end, we all know user behavior is changed through positive experience. So instead of having massive training programs over endless courses of workshops, leaving our new joiners and colleagues confused and overwhelmed, we're applying gamification, right? So split different levels of certification where our colleagues, can access, have had access points. They can earn badges along the way, which then simplifies the process of learning and engagement of the users. And this is what we see in surveys, for example, where our employees value this gamification approach a lot and are even competing to collect those learning pet badges, to become the number one on the leaderboard. >> I love the gamification. I mean, we've seen it work so well in so many different industries, not the least of which is crypto. So you've identified some of the process gaps that you, you saw, you just gloss over them. Sometimes I say, pave the cow path. You didn't try to force. In other words, a new architecture into the legacy processes, you really had to rethink your approach to data management. So what did that entail? >> To rethink the way of data management, 100%. So if I take the example of revolution, industrial revolution or classical supply chain revolution, but just imagine that you have been riding a horse, for example, your whole life, and suddenly you can operate a car or you suddenly receive just a complete new way of transporting assets from A to B. So we needed to establish a new set of cross-functional business processes to run faster, drive faster, more robustly, and deliver data products which can be trusted and used by downstream processes and systems. Hence we had a subset of new standards and new procedures that would fall into the internal data governance and compliance sector. With internal, I'm always referring to the data operations around new things like data catalog, how to identify ownership, how to change ownership, how to certify data assets, everything around classical is software development, which we now apply to data. This, this is some old and new thinking, right? Deployment, versioning, QA, all the different things, ingestion policies, the deletion procedures, all the things that software development has been doing, we do it now with data as well. And it's simple terms, it's a whole redesign of the supply chain of our data with new procedures and new processes in asset creation, asset management and asset consumption. >> So data's become kind of the new development kit, if you will. I want to shift gears and talk about the notion of data product, and we have a slide that, that we pulled from your deck. And I'd like to unpack it a little bit. I'll just, if you can bring that up, I'll, I'll read it. A data product is a product whose primary objective is to leverage on data to solve customer problems, where customers are both internal and external. so pretty straightforward. I know you've, you've gone much deeper in your thinking and into your organization, but how do you think about that and how do you determine for instance, who owns what, how did you get everybody to agree? >> I can take that one. Maybe let me start as a data product. So I think that's an ongoing debate, right? And I think the debate itself is the important piece here, right? You mentioned the debate, you've clarified what we actually mean by that, a product, and what is actually the mindset. So I think just from a definition perspective, right? I think we find the common denominator that we say, okay, that our product is something which is important for the company that comes with value. What do you mean by that? Okay. It's a solution to a customer problem that delivers ideally maximum value to the business. And yes, leverage is the power of data. And we have a couple of examples, and I'll hit refresh here, the historical and classical ones around dashboards, for example, to monitor our error rates, but also more sophisticated based for example, to incorporate machine learning algorithms in our recipe recommendation. However, I think the important aspects of a data product is A: there is an owner, right? There's someone accountable for making sure that the product that you're providing is actually served and has maintained. And there are, there's someone who's making sure that this actually keeps the value of what we are promising. Combined with the idea of the proper documentation, like a product description, right? The people understand how to use it. What is this about? And related to that piece is the idea of, there's a purpose, right? We need to understand or ask ourselves, okay, why does a thing exist? Does it provide the value that we think it does? Then it leads in to a good understanding of what the life cycle of the data product and product life cycle. What do we mean? Okay. From the beginning, from the creation, you need to have a good understanding. You need to collect feedback. We need to learn about that, you need to rework, and actually finally, also to think about, okay, when is it time to decommission that piece So overall I think the core of this data product is product thinking 101, right? That we start, the point is, the starting point needs to be the problem and not the solution. And this is essentially what we have seen, what was missing, what brought us to this kind of data spaghetti that we have built there in Rush, essentially, we built it. Certain data assets develop in isolation and continuously patch the solution just to fulfill these ad hoc requests that we got and actually really understanding what the stakeholder needs. And the interesting piece as a results in duplication of (mumbled) And this is not just frustrating and probably not the most efficient way, how the company should work. But also if I build the same data assets, but slightly different assumption across the company and multiple teams that leads to data inconsistency. And imagine the following scenario. You, as a management, for management perspective, you're asking basically a specific question and you get essentially from a couple of different teams, different kinds of graphs, different kinds of data and numbers. And in the end, you do not know which ones to trust. So there's actually much (mumbles) but good. You do not know what actually is it noise for times of observing or is it just actually, is there actually a signal that I'm looking for? And the same as if I'm running an AB test, right? I have a new feature, I would like to understand what is the business impact of this feature? I run that with a specific source and an unfortunate scenario. Your production system is actually running on a different source. You see different numbers. What you have seen in the AB test is actually not what you see then in production, typical thing. Then as you asking some analytics team to actually do a deep dive, to understand where the discrepancies are coming from, worst case scenario again, there's a different kind of source. So in the end, it's a pretty frustrating scenario. And it's actually a waste of time of people that have to identify the root cause of this type of divergence. So in a nutshell, the highest degree of consistency is actually achieved if people are just reusing data assets. And also in the end, the meetup talk they've given, right? We start trying to establish this approach by AB testing. So we have a team, but just providing, or is kind of owning their target metric associated business teams, and they're providing that as a product also to other services, including the AB testing team. The AB testing team can use this information to find an interface say, okay, I'm drawing information for the metadata of an experiment. And in the end, after the assignment, after this data collection phase, they can easily add a graph to a dashboard just grouped by the AB testing barrier. And we have seen that also in other companies. So it's not just a nice dream that we have, right? I have actually looked at other companies maybe looked on search and we established a complete KPI pipeline that was computing all these information and this information both hosted by the team and those that (mumbles) AB testing, deep dives and, and regular reporting again. So just one last second, the, the important piece, Now, why I'm coming back to that is that it requires that we are treating this data as a product, right? If we want to have multiple people using the thing that I am owning and building, we have to provide this as a trust (mumbles) asset and in a way that it's easy for people to discover and to actually work with. >> Yeah. And coming back to that. So this is, to me this is why I get so excited about data mesh, because I really do think it's the right direction for organizations. When people hear data product, they think, "Well, what does that mean?" But then when you start to sort of define it as you did, it's using data to add value that could be cutting costs, that could be generating revenue, it could be actually directly creating a product that you monetize. So it's sort of in the eyes of the beholder, but I think the other point that we've made, is you made it earlier on too, and again, context. So when you have a centralized data team and you have all these P&L managers, a lot of times they'll question the data 'cause they don't own it. They're like, "Well, wait a minute." If it doesn't agree with their agenda, they'll attack the data. But if they own the data, then they're responsible for defending that. And that is a mindset change that's really important. And I'm curious is how you got to that ownership. Was it a top-down or was somebody providing leadership? Was it more organic bottom up? Was it a sort of a combination? How do you decide who owned what? In other words, you know, did you get, how did you get the business to take ownership of the data and what does owning the data actually mean? >> That's a very good question, Dave. I think that one of the pieces where I think we have a lot of learning and basically if you ask me how we could stop the filling, I think that would be the first piece that we need to start. Really think about how that should be approached. If it's staff has ownership, right? That means somehow that the team has the responsibility to host themselves the data assets to minimum acceptable standards. That's minimum dependencies up and down stream. The interesting piece has to be looking backwards. What was happening is that under that definition, this extra process that we have to go through is not actually transferring ownership from a central team to the other teams, but actually in most cases to establish ownership. I make this difference because saying we have to transfer ownership actually would erroneously suggest that the dataset was owned before, but this platform team, yes, they had the capability to make the change, but actually the analytics team, but always once we had the business understand the use cases and what no one actually bought, it's actually expensive, expected. So we had to go through this very lengthy process and establishing ownership, how we have done that as in the beginning, very naively started, here's a document, here are all the data assets, what is probably the nearest neighbor who can actually take care of that. And then we, we moved it over. But the problem here is that all these things is kind of technical debt, right? It's not really properly documented, pretty unstable. It was built in a very inconsistent way over years. And these people that built this thing have already left the company. So this is actually not a nice thing that you want to see and people build up a certain resistance, even if they have actually bought into this idea of domain ownership. So if you ask me these learnings, what needs to happen is first, the company needs to really understand what our core business concept that we have the need to have this mapping from this other core business concept that we have. These are the domain teams who are owning this concept, and then actually linked that to the, the assets and integrate that better, but suppose understanding how we can evolve, actually the data assets and new data builds things new and the, in this piece and the domain, but also how can we address reduction of technical depth and stabilizing what we have already. >> Thank you for that Christoph. So I want to turn a direction here and talk Clemence about governance. And I know that's an area that's passionate, you're passionate about. I pulled this slide from your deck, which I kind of messed up a little bit, sorry for that. But, but, but by the way, we're going to publish a link to the full video that you guys did. So we'll share that with folks, but it's one of the most challenging aspects of data mesh. If you're going to decentralize, you, you quickly realize this could be the wild west, as we talked about all over again. So how are you approaching governance? There's a lot of items on this slide that are, you know, underscore the complexity, whether it's privacy compliance, et cetera. So, so how did you approach this? >> It's yeah, it's about connecting those dots, right? So the aim of the data governance program is to promote the autonomy of every team while still ensuring that everybody has the right interoperability. So when we want to move from the wild west, riding horses to a civilized way of transport, I can take the example of modern street traffic. Like when all participants can maneuver independently, and as long as they follow the same rules and standards, everybody can remain compatible with each other and understand and learn from each other so we can avoid car crashes. So when I go from country to country, I do understand what the street infrastructure means. How do I drive my car? I can also read the traffic lights and the different signals. So likewise, as a business in HelloFresh we do operate autonomously and consequently need to follow those external and internal rules and standards set forth by the tradition in which we operate. So in order to prevent a, a car crash, we need to at least ensure compliance with regulations, to account for societies and our customers' increasing concern with data protection and privacy. So teaching and advocating this imaging, evangelizing this to everyone in the company was a key community or communication strategy. And of course, I mean, I mentioned data privacy, external factors, the same goes for internal regulations and processes to help our colleagues to adapt for this very new environment. So when I mentioned before, the new way of thinking, the new way of dealing and managing data, this of course implies that we need new processes and regulations for our colleagues as well. In a nutshell, then this means that data governance provides a framework for managing our people, the processes and technology and culture around our data traffic. And that governance must come together in order to have this effective program providing at least a common denominator is especially critical for shared data sets, which we have across our different geographies managed, and shared applications on shared infrastructure and applications. And as then consumed by centralized processes, for example, master data, everything, and all the metrics and KPIs, which are also used for a central steering. It's a big change, right? And our ultimate goal is to have this non-invasive federated, automated and computational governance. And for that, we can't just talk about it. We actually have to go deep and use case by use case and QC by PUC and generate learnings and learnings with the different teams. And this would be a classical approach of identifying the target structure, the target status, match it with the current status, by identifying together with the business teams, with the different domains and have a risk assessment, for example, to increase transparency because a lot of teams, they might not even know what kind of situation they might be. And this is where this training and this piece of data literacy comes into place, where we go in and trade based on the findings, based on the most valuable use case. And based on that, help our teams to do this change, to increase their capability. I just told a little bit more, I wouldn't say hand-holding, but a lot of guidance. >> Can I kind of kind of chime in quickly and (mumbled) below me, I mean, there's a lot of governance piece, but I think that is important. And if you're talking about documentation, for example, yes, we can go from team to team and tell these people, hey, you have to document your data assets and data catalog, or you have to establish a data contract and so on and forth. But if we would like to build data products at scale, following actual governance, we need to think about automation, right? We need to think about a lot of things that we can learn from engineering before, and just starts as simple things. Like if we would like to build up trust in our data products, right? And actually want to apply the same rigor and the best practices that we know from engineering. There are things that we can do. And we should probably think about what we can copy. And one example might be so the level of service level agreements, so that level objectives. So the level of indicators, right, that represent on a, on an engineering level, right? Are we providing services? They're representing the promises we make to our customer and to our consumers. These are the internal objectives that help us to keep those promises. And actually these audits of, of how we are tracking ourselves, how we are doing. And this is just one example of where I think the federated governance, governance comes into play, right? In an ideal world, you should not just talk about data as a product, but also data product that's code. That'd be say, okay, as most, as much as possible, right? Give the engineers the tool that they are familiar with, and actually not ask the product managers, for example, to document the data assets in the data catalog, but make it part of the configuration has as, as a, as a CDCI continuous delivery pipeline, as we typically see in other engineering, tasks through it and services maybe say, okay, there is configuration, we can think about PII, we can think about data quality monitoring, we can think about the ingestion data catalog and so on and forth. But I think ideally in a data product goals become a sort of templates that can be deployed and are actually rejected or verified at build time before we actually make them and deploy them to production. >> Yeah so it's like DevOps for data product. So, so I'm envisioning almost a three-phase approach to governance. And you're kind of, it sounds like you're in the early phase of it, call it phase zero, where there's learning, there's literacy, there's training education, there's kind of self-governance. And then there's some kind of oversight, some, a lot of manual stuff going on, and then you, you're trying to process builders at this phase and then you codify it and then you can automate it. Is that fair? >> Yeah. I would rather think, think about automation as early as possible in a way, and yes, it needs to be separate rules, but then actually start actually use case by use case. Is there anything that small piece that we can already automate? If just possible roll that out at the next extended step-by-step. >> Is there a role though, that adjudicates that? Is there a central, you know, chief state officer who's responsible for making sure people are complying or is it, how do you handle it? >> I mean, from a, from a, from a platform perspective, yes. This applies in to, to implement certain pieces, that we are saying are important and actually would like to implement, however, that is actually working very closely with the governance department, So it's Clemence's piece to understand that defy the policies that needs to be implemented. >> So good. So Clemence essentially, it's, it's, it's your responsibility to make sure that the policy is being followed. And then as you were saying, Christoph, you want to compress the time to automation as fast as possible. Is that, is that-- >> Yeah, so it's a really, it's a, what needs to be really clear is that it's always a split effort, right? So you can't just do one or the other thing, but there is some that really goes hand in hand because for the right information, for the right engineering tooling, we need to have the transparency first. I mean, code needs to be coded. So we kind of need to operate on the same level with the right understanding. So there's actually two things that are important, which is one it's policies and guidelines, but not only that, because more importantly or equally important is to align with the end-user and tech teams and engineering and really bridge between business value business teams and the engineering teams. >> Got it. So just a couple more questions, because we got to wrap up, I want to talk a little bit about the business outcome. I know it's hard to quantify and I'll talk about that in a moment, but, but major learnings, we've got some of the challenges that, that you cited. I'll just put them up here. We don't have to go detailed into this, but I just wanted to share with some folks, but my question, I mean, this is the advice for your peers question. If you had to do it differently, if you had a do over or a Mulligan, as we like to say for you, golfers, what, what would you do differently? >> I mean, I, can we start with, from, from the transformational challenge that understanding that it's also high load of cultural exchange. I think this is, this is important that a particular communication strategy needs to be put into place and people really need to be supported, right? So it's not that we go in and say, well, we have to change into, towards data mash, but naturally it's the human nature, nature, nature, we are kind of resistant to change, right? And (mumbles) uncomfortable. So we need to take that away by training and by communicating. Chris, you might want to add something to that. >> Definitely. I think the point that I've also made before, right? We need to acknowledge that data mesh it's an architectural scale, right? If you're looking for something which is necessary by huge companies who are vulnerable, that are product at scale. I mean, Dave, you mentioned that right, there are a lot of advantages to have a centralized team, but at some point it may make sense to actually decentralize here. And at this point, right, if you think about data mesh, you have to recognize that you're not building something on a green field. And I think there's a big learning, which is also reflected on the slide is, don't underestimate your baggage. It's typically is you come to a point where the old model doesn't work anymore. And as had a fresh write, we lost the trust in our data. And actually we have seen certain risks of slowing down our innovation. So we triggered that, this was triggering the need to actually change something. So at this transition applies that you took, we have a lot of technical depth accumulated over years. And I think what we have learned is that potentially we have, de-centralized some assets too early. This is not actually taking into account the maturity of the team. We are actually investigating too. And now we'll be actually in the face of correcting pieces of that one, right? But I think if you, if you, if you start from scratch, you have to understand, okay, is all my teams actually ready for taking on this new, this new capability? And you have to make sure that this is decentralization. You build up these capabilities and the teams, and as Clemence has mentioned, right? Make sure that you take the, the people on your journey. I think these are the pieces that also here it comes with this knowledge gap, right? That we need to think about hiring literacy, the technical depth I just talked about. And I think the, the last piece that I would add now, which is not here on the slide deck is also from our perspective, we started on the analytical layer because it was kind of where things are exploding, right? This is the bit where people feel the pain. But I think a lot of the efforts that we have started to actually modernize the current stage and data products, towards data mesh, we've understood that it always comes down basically to a proper shape of our operational plan. And I think what needs to happen is I think we got through a lot of pains, but the learning here is this needs to really be an, a commitment from the company. It needs to have an end to end. >> I think that point, that last point you made is so critical because I, I, I hear a lot from the vendor community about how they're going to make analytics better. And that's not, that's not unimportant, but, but true data product thinking and decentralized data organizations really have to operationalize in order to scale it. So these decisions around data architecture and organization, they're fundamental and lasting, it's not necessarily about an individual project ROI. They're going to be projects, sub projects, you know, within this architecture. But the architectural decision itself is organizational it's cultural and, and what's the best approach to support your business at scale. It really speaks to, to, to what you are, who you are as a company, how you operate and getting that right, as we've seen in the success of data-driven companies is, yields tremendous results. So I'll, I'll, I'll ask each of you to give, give us your final thoughts and then we'll wrap. Maybe. >> Just can I quickly, maybe just jumping on this piece, what you have mentioned, right, the target architecture. If you talk about these pieces, right, people often have this picture of (mumbled). Okay. There are different kinds of stages. We have (incomprehensible speech), we have actually a gesture layer, we have a storage layer, transformation layer, presentation data, and then we are basically putting a lot of technology on top of that. That's kind of our target architecture. However, I think what we really need to make sure is that we have these different kinds of views, right? We need to understand what are actually the capabilities that we need to know, what new goals, how does it look and feel from the different kinds of personas and experience view. And then finally that should actually go to the, to the target architecture from a technical perspective. Maybe just to give an outlook what we are planning to do, how we want to move that forward. Yes. Actually based on our strategy in the, in the sense of we would like to increase the maturity as a whole across the entire company. And this is kind of a framework around the business strategy and it's breaking down into four pillars as well. People meaning the data culture, data literacy, data organizational structure and so on. If you're talking about governance, as Clemence had actually mentioned that right, compliance, governance, data management, and so on, you're talking about technology. And I think we could talk for hours for that one it's around data platform, data science platform. And then finally also about enablements through data. Meaning we need to understand data quality, data accessibility and applied science and data monetization. >> Great. Thank you, Christoph. Clemence why don't you bring us home. Give us your final thoughts. >> Okay. I can just agree with Christoph that important is to understand what kind of maturity people have, but I understand we're at the maturity level, where a company, where people, our organization is, and really understand what does kind of, it's just kind of a change applies to that, those four pillars, for example, what needs to be tackled first. And this is not very clear from the very first beginning (mumbles). It's kind of like green field, you come up with must wins to come up with things that you really want to do out of theory and out of different white papers. Only if you really start conducting the first initiatives, you do understand that you are going to have to put those thoughts together. And where do I miss out on one of those four different pillars, people process technology and governance, but, and then that can often the integration like doing step by step, small steps, by small steps, not pulling the ocean where you're capable, really to identify the gaps and see where either you can fill the gaps or where you have to increase maturity first and train people or increase your tech stack. >> You know, HelloFresh is an excellent example of a company that is innovating. It was not born in Silicon Valley, which I love. It's a global company. And, and I got to ask you guys, it seems like it's just an amazing place to work. Are you guys hiring? >> Yes, definitely. We do. As, as mentioned right as well as one of these aspects distributing and actually hiring as an entire company, specifically for data. I think there are a lot of open roles, so yes, please visit or our page from data engineering, data, product management, and Clemence has a lot of roles that you can speak to about. But yes. >> Guys, thanks so much for sharing with theCUBE audience, you're, you're pioneers, and we look forward to collaborations in the future to track progress, and really want to thank you for your time. >> Thank you very much. >> Thank you very much Dave. >> And thank you for watching theCUBE's startup showcase made possible by AWS. This is Dave Volante. We'll see you next time. (cheerful music)

>>Mhm Hello, I'm jennifer with the cube. We're here at Rogers vice president of EC two Product Manager, NWS raj. Thanks for coming off its quick cube conversation. Um Congratulations on your 15th birthday of E C two. You get the keys to the kingdom of one of the hottest products. The most important product you look at. I look at our billets. Ec two is the highest, it's always the best everyone focuses on. It's the compute a lot of other goodness with amazon cloud. Thanks for coming on. >>Thank you. Thanks for having me. >>So, can you break down the graviton two processor overview? Why is custom Silicon important and why should architects and developers understand the opportunity with graviton to these are the other opportunities within 80 bucks. What's the, what's the magic do it we should that they think about as the architect their cloud. >>Yeah. So, I mean, I think why it's important is what you said like so much uh the workloads that they're running at the end of the day is running on EC two, whether it's running on Ec two directly or running on one of the other AWS services that's built on a C two and when you have, when you're able to, when we're able to innovate and deliver a very significant price performance advantage, not just lowers their costs. So like there, It's hardly a day of industry where you're able to go and do a pretty simple migration and get a 40% price performance improvement and that's huge and I think that's why this is, you know, raising a lot of interest. Is that um, customers, I found it relatively easy to go and do this migration and get that benefit. >>That's awesome mirage. I gotta ask you ec two offers more than 400 instant types with different combinations of compute memory, networking and storage, which is obviously the backbone of the cloud. A lot of people that are coming in learning about clouds, what does it mean that there's all these instances that because it's just more combinations, different workloads, why 400 instance types? What does that mean for someone learning about clouds? Does it mean anything to you actually? Would you explain the difference of instance types of 400 of them? >>Yeah. So, I mean when you think about an instance type, it's essentially configuration of a virtual machine, there's a certain amount of memory, there's a certain amount of processing power. Uh there could be a certain amount of disk and workloads, uh, the different ratios of these uh, dimensions, these characteristics. So by offering selection across a wide variety of instances were really able to optimize the compute that particular workload needs. The customers could essentially uh, increase their performance and have a more optimized price for what they want to get done. So ultimately, that's what that's what it's about having the right form factor for a given workload and the more configurations that we have, the more we're able to tune for those workloads. >>It's like having a driver riding a car you want the driver type to match the road, match the engine. So the instance has to match the profile of the app, the workload and kind of, and is that kind of where you're getting at getting met? You can do that. >>Yeah. And you know, and one of the things that we're also investing in at the same time as tools to enable customers to realize and learn what the right instance is. So, you know, we launched about a year ago uh capability called compute optimizer that lets customers look at their workloads, you know, in flight essentially and make recommendations saying, hey, instead of this instance, you know, you could Move to um this other instance type and save 50% or you know, as an example. So, um, you know, part of it, creating the selection and the other part of it is creating the tools. So customers, do you know what the right fit is for them so that they can really optimize their thin >>Well Roger, I really preach this is going to ask me anything guru question, but here's the simple one. What is gravitas to, at the end of the day when someone asks you what is graviton too? >>Yeah. So I mean grandma can do is a processor, it's a chip, it's a CPU um and so what that means essentially is and it's an arm. Basic. So um, you know, with, with are just like you have intel and AMG processors, these are the, the circuitry and the computer that does the work. Right. And um with, with Gravitas on we support arm which is a different architecture set but one that has been around long enough and it's pretty ubiquitous across mobile devices and servers now. So the operating systems that you know, you know all the Linux operating system, the tools that you know, they all work and are able to run on Graviton too. So this means that when you have applications, you can very easily take it from the same AMG or intel X 86 platform and move it over and just get the efficiencies that gravity to offers with lower power envelope and higher performance >>there it is many master class here at raj. Pie Vice President Ec two product management laying down the graviton to knowledge and for folks learning about cloud and architects really want to know the difference. It's a 40% performance improvement, lower power envelope, 20% less than cost. I believe something those range about right about in the same territory there. So basically high performance, lower costs, better power. So for workloads that demanded you got the option raj. Thank you for sharing. Thank you. All right. I'm john for, with the cube Thanks for watching. Mhm mm

(upbeat music) >> Overnight COVID completely exposed those companies that were really not ready for the digital age. There was a mad rush to the cloud in an effort to reshape the very notion of business resiliency and enable employees to remain productive so that they continue serve customers. Data protection was at the heart of this shift and cloud data protection has become a fundamental staple of organizations operating models. Hello, everyone. This is Dave Vellante and welcome to this CUBE conversation. I'm joined by two longtime friends of theCUBE, Rob Emsley is the director of product marketing at Dell Technologies. And Stephen Manley is the Chief Technology Officer at Druva. Guys, great to have you on the program. Thanks for being here. >> Yeah, great to be here, Dave. >> This is the high point of my day, Dave. >> I'm glad to hear it, Stephen. It's been a while since we... Missing you guys to tell you face to face maybe it'll happen before 22, >> We haven't aged a bit, Dave. >> (laughing) Ditto. Listen, we've been talking for years about this shift to the cloud. In the past 12 months, boy, we've seen the pace of workloads that have moved to the cloud really accelerate. So Rob, maybe you could start it off. How do you see the market and perhaps what are some of the blind spots maybe that people need to think about when they're moving workloads so fast in the cloud? >> Yeah. Good question Dave. I mean, you know, we've spoken a number of times around how our focus has significantly shifted over the last couple of years. I mean, only a couple of years ago, our focus was very much on on-premise data protection, but over the last couple of years, more workloads have shifted to the cloud. Customers have started adopting SaaS applications and all of these environments are creating data that is so critical to these customers to protect, we've definitely found that more and more of our conversations have been centered around what can you do for me when it comes to protecting workloads in the client environment? >> Yeah. Now of course, Stephen, this is kind of your wheelhouse. How are you thinking about the these market shifts? >> Yeah. You know, it's interesting in the data protection market. heck the data market in general, you see these sort of cycles happen. And for a long time, we had a cycle where applications and environments were consolidating a lot. It was all VMs and Oracle and SQL and we seem to be exploding out the other way to this massive sprawl of different types of applications in different places. Like Rob said, we've got Microsoft 365 and you've got Salesforce and you've got workloads running in the cloud. The world looks different. And you add on top of that the new security threats as people moving to the cloud. A number of years ago we talked how ransomware was an emerging threat. We're way past emerging into... there's a ransomware attack every six seconds and everybody wakes up terrified about it. And so we really see the market has shifted I think in terms of what the apps are and also in terms of what the threats and the focus and this that's come into play. >> Right. Well, thanks for that. There's some hard news which we're going to get to, but before we do, Rob, Stephen was mentioning the SaaS apps and we've been sort of watching that space for a while but a lot of people will ask why do I need a separate data protection layer? Doesn't my SaaS provider protect my data? Don't they replicate it? They're cloud vendors, why do I need to buy yet another backup product? >> Yeah, that's a fairly common misconception, Dave, that both SaaS application vendors and cloud vendors, inherently are providing all of the data protection that you need. The reality is that they're not, you know I think when you think about a lot of the data within those environments, certainly they're focused on providing availability. And availability is absolutely one thing that you can, for the most part, rely on the cloud vendors to deliver to you. But when it comes to actually protecting yourself from accidental deletion. Protecting yourself from cyber threats and cyber crime that may infect your data through malicious acts, that's really where you need to supplement the environment that the cloud providers provide you, with best in class data protection solutions. And this is really where, waywardly looking to introduce new innovations into the market to really, really help customers with that cloud based data protection. >> Yeah. Now you got some news here. Let's kind of dig in, if we could, to the innovations behind that. Maybe Rob, you could kick it off and then, Stephen, we'll bring you in. >> Yeah. So first piece of news that we're really happy to announce is the introduction of a new Dell EMC PowerProtect backup service which is a new cloud data protection solution powered by Druva, hence the reason that Stephen and I are here today. It's designed to deliver additional protection without increasing IT complexity. >> So powered by Druva. what does that mean? Can you add some color to that? >> Absolutely. So, when we really started looking at the expansion of our PowerProtect portfolio, we already have the ability to deliver both on-premises protection and to deliver that same software within the public cloud from a PowerProtect software delivery model. But what we really didn't have within the portfolio is a cloud data protection platform. And we really looked at what was available in the market. We looked at our ability to develop that ourselves. And we decided that the best path for our customers to bring capability to them as soon as we possibly could was to partner with Druva. And we really looked at the capabilities that Druva has been delivering for many years, the capabilities that they have across many dimensions of cloud-based workloads. And we already engaged with them probably about six months ago, first introduced Druva as an option to be resold by ourselves, Salesforce and partners. And then we're pleased to introduce a Dell EMC branded service PowerProtect backup service. >> Okay, so just one more point of clarification, then, Stephen, I want to bring you in. So we're talking about... this includes SaaS apps as well, I'm talking 365, the Google apps which we use extensively, CRM, Salesforce, for example. >> Absolutely. >> What platforms are you actually connecting to and providing protection for? >> Yeah, so the real priority for us was to expand our PowerProtect portfolio to support a variety of SaaS applications. You mentioned, real major ones with respect to Microsoft 365, Google workplace, as well as Salesforce. But the other thing that we also get with PowerProtect backup service is the ability to provide a cloud-based data protection service that supports endpoints such as laptops and desktops but also the ability to support hybrid workloads. So for some customers the ability to use PowerProtect backup service to give them support for virtual machine backups, both VMware and Hyper-V, but also application environments like Oracle and SQL. And lastly, but not least, one of the things that backup service also provides when it comes to virtual machines is not only virtual machines on premises, but also virtual machines within the public cloud, specifically VMware cloud on AWS. >> So, Stephen, I remember I was talking to Jaspreet several years ago, and I've always liked sort of the Druva model but it felt at the time you were like a little ahead of your time, but boy, the market has really come to you. Maybe you could just tell us a little bit more about the just generally cloud-based data protection and the sort of low down on your platform. >> Yeah, and I think you're right, the market has absolutely swept in this direction. Like we were talking about with applications in so many places and end points in so many places and data centers and remote offices with data sprawled everywhere. We find customers are looking for a solution that can connect to everything. I don't want seven different backup solutions, one for each of those things, I want one centralized solution. And so kind of a data protection as a service becomes really appealing because instead of setting all of these things up on your own, well, it's just built in for you. And then the fact that it's as a service helps with things like the ransomware protection because it's off site in another location under another account. And so we really see customers saying this is appealing because it helps keep my costs down. It helps keep my complexity down. There's fewer moving parts. And one of the nicest things is as I move to the cloud I get that one fixed cost, right? I'm not dealing with the, oh, wow, this bill is not what I was expecting. It just comes in with what I was carrying. And so it really comes down to, as you go to the cloud, you want a platform that's got everything built in, something that, and let's face it, Dell EMC, this has always been the case, that storage of last resort that backup that you can trust, right? You want something with a history, like you said, you've been talking to Jaspreet for awhile, Druva is a company that's got a proven track record that your data is going to be safe and it's going to be recoverable and you're going to want someone that can innovate quickly, right? So that as more new cloud applications arise, we're there to help you protect them as they emerge. >> So talk a little bit more about the timing. I mean, we talked earlier about, okay, COVID really forced this shift to the cloud and you guys clearly have skated to the pocket and you also... You referenced sort of new workloads and I'm just wondering how you see that from a timing standpoint. And at this moment in time why this is such a, you know, the right fit. >> We've seen a lot of customers over the last again 12 months or so, one really accelerate their shift to things like SaaS applications, Microsoft 365, and we're not just talking exchange online and One Drive, but SharePoint online, Microsoft teams, really going all in because they're finding that, as I'm distributed, as I have a remote workforce, my end points became more important again, but also the ability to have collaboration became important. And the more I depend on those tools to collaborate, the more I'm depending on them to replace what used to be in-person meetings where we could have a whiteboard and discuss things. And it's done through collaboration online tools. Well, I need to protect that. Not just because the data's important, but because that's now how my business is running. And so that entire environment is important. And so it's really accelerated people coming and looking for solutions because they've realized how important these environments and this data is. >> So, Stephen, you mentioned that you guys, I mean, obviously you have a track record but you got some vision too. And I want to sort of poke at that a little bit. I mean, essentially is what you're building is an abstraction layer that is essentially my data protection cloud. Is that how we should think about this? And you've referenced pricing, I've seen your pricing, it's clean. It looks to me anyway like a true cloud pricing. Going to dial it up, dial it down, pay as you go, consume it as you wish. Maybe talk about that a little bit. >> Yeah. I mean, I think if you think about the future of consumption is that so many customers are looking for different choices than what many vendors have provided them in the past. I think the days of of going through a long procurement cycle and working through purchasing in order to get a big capital expense approved it's just not the way that many of our customers are looking to operate now. So I think that one of the things that we're looking at across the portfolio, whether or not it be on premises solutions or cloud-based services, is to provide all of that capability as a service. I think that that will be a real future point of arrival for us as we really rotate to offer that across all of our capabilities, Dave, whether or not it be in the domain of storage, or in the domain of data protection, the concept of everything as a service is really something which is going to become more of the norm versus the exception. >> So what does a customer have to do to be up and running? What's that experience like, is he just going to log on and everything's sort of there to them, what do they see? What's the experience like? >> Yeah, that's one of the great things about PowerProtect backup services, that once the customer has worked through that, their Dell technologies sells a team or the Dell technologies partner, they effectively get an activation code to sign up and set up the credentials with PowerProtect backup service. And once they actually do that, one of the things that they don't have to worry about is the deployment of the infrastructure. The infrastructure is always on ready to go. So all they do is they simply point PowerProtect backup service at the data sources that they wish to protect. That's one of the great advantages around a SaaS based data protection platform and it's one of the things that makes it very easy to get customers up and running with PowerProtect backup service. >> So I'm guessing you have a roadmap, you may be, you may be not, you may be holding out on us in some of the other things that you're doing in this space, but what can you tell us about other things you might be doing or what might be coming? What can we expect? >> Well, I mean, Dave, that one of the things that we always talk about is the power of the portfolio. So, with the addition of PowerProtect backup service, it's not the only news that we're making with respect to client data protection. You know, I mentioned earlier that we have the ability to deploy our on premises solutions in the public cloud with PowerProtect data manager and our PowerProtect virtual appliances, and with this announcement that brings backup service into the portfolio. We're also pleased to expand our support of the public cloud with full support of Google cloud platform, making PowerProtect data manager available in the Google marketplace. And then lastly, but not least, you know our other cloud snapshot manager offering is now also fully integrated with our PowerProtect virtual appliances to allow customers to store AWS snapshots in a debilitative fashion within AWS S3. So that's an excellent capability that we've introduced to reduce the cost of storing AWS infrastructure backups for longer periods of time. So really, we've really continued to double down in bringing new client data protection capabilities to our customers, wherever they may be. >> And nice to have, Stephen, you guys must be stoked to have a partner like Dell, a massive distribution channel. I wonder if you could give us any final thoughts, thoughts on the relationship, how you see the future unfolding. >> Yeah, I mean, and obviously I've got history with Dell and EMC and Rob. And one of the things I think Dell has always been fabulous at is giving customers the flexibility to protect their data when they want, how they want, where they want, with the investment protection that if it shifts over time, they'll be there for them, right. Going all the way back to the data protection suite and all those fantastic things we've done historically. And so it's really, it's great to align with somebody that's got the same kind of value as we do, which is with Druva, it's that same model, right? Wherever you want to protect your data, wherever it is, we're going to be there for you. And so it was great that I think Dell and Druva both saw this demand from our customers. And we said, this is the right match, right? This is how we're going to help people keep their data safe as they start and continue and extend their journeys to the cloud. And so, Dell proposes the PowerProtect backup service powered by Druva. And everybody wins. The Dell's customers are safer. Dell completes this offering, and let's face it, it does help to really accelerate our momentum. So this is and it's a lot of fun just hanging out with the people I used to work with especially it's good seeing them again. >> Well, you guys both have kind of alluded to the portfolio and the optionality that Dell brings to its customers, but Rob, you know, I'll give you the final word. A lot of times optionality brings complexity, but this seems to be a really strong step in the direction of simplifying the world for your customers. But, Rob, we'll give you the last word. >> Yeah, for sure. I mean, we've always said that it's not a one size fits all world. You know, I think that one of the things that this evolution of a PowerProtect portfolio brings is an excellent added option for our customers. Many of the customers, if not, almost all of the customers that we currently sell to, have a requirement for SaaS application protection. Many of them now, especially after the last year, have an added sensitivity to endpoint protection. So those two things alone I think are two things that all Dell technology customers can really take advantage of with the introduction of perhaps that backup service. This is just a continued evolution of our capabilities to bring innovative data protection for multi-cloud workloads. >> That last point is a great point about the end points because you've got remote workers, so exposed, guys, thanks so much for sharing the announcement details, and the relationship, and really good luck with the offering. We'll be watching. >> Thanks, Dave. >> Thanks Dave. >> And thank you for watching this CUBE conversation. This is Dave Vellante for theCUBE. We'll see you next time. (soft music)

>>everybody, this is Dave Vellante. May 27th were hosting a crowd chat going on crowdchat dot net slash data ops. Data ops is all about automating the data pipeline infusing AI and operationalize ing ai and the Data Pipeline and your organizations, which has been a real challenge for companies over the last several years in most of the decade. With me is aljaz cannoli. What's changed? That companies can now succeed at automating and operationalize in the data pipeline. >>You're so right, David. As's faras. I remember myself in this industry data challenges that the bottlenecks are the bottlenecks. So why now? I think we can answer that one from three angles. People process technology. What changing people? What changes process will change with technology. Let me start with the technology part on the technology front. Right now. The compute power is they were rare and the cloud multi cloud artificial intelligence, Social mobile all connected and giving the power to the organizations to deal with these problems, especially, I want to highlight the artificial intelligence part, and I will highlight it with how IBM is leveraging artificial intelligence to solve some of the dormant data problems. One of the major major doorman problem is on boarding data. If you're unable to onboard your data fast, however beautiful factory the all the factor lines shining, waiting for data if you cannot. Onboard data fast, all dress is waiting. But what IBM did automated made metadata generation capabilities which is on boarding data leveraging artificial intelligence models so that it is not only on boarding the data but on boarding the data in a way that everyone can understand it. When data scientist looks at the data, look at the data. They don't stare at the data but they understand what that data means because it >>is >>interpreted into business taxonomy into business language in the fast fashion that is one the technology, the second part people and process parts so important in the process part the methodology. Now we have the methodologies, the first methodology that I would just say as a change. Sometimes we we call that as a legal I don't know whether you heard about it in an agile So these legal methodologies now asking us to how alterations fail >>fast, Try fast, fail fast, Try fast >>and these agile methodologies are now being applied to data pipelines in weeks, off iterations, we can look at the most important business challenge with the KP eyes that you're trying to achieve and then map those KP eyes to data sources needed to answer those KP eyes and then streamline everything in between passed. So that renders a change like this the market that we are in. Then all those data flows are streamlined and optimize. And during the Cube interview during the Cube program that we put together, you will see some of the organizations will mention that is agile practice they put in place in every geography is now even getting them closer and closer, because now we all depend on and >>live on digital. So I'm very excited because ah, interviewing Standard Bank Associated Bank. Harley Davidson, IBM chief data officer into public. Sorry to talk about how IBM is sort of drunk, its own champagne eating. It's own dog food. Whatever you prefer. This is not the the mumbo jumbo marketing. This is practitioners who are gonna talk about how they succeeded, how they funded these initiatives, how they did the business case, some of the challenges that they face, how they dealt with classification and metadata and some of the outcomes that they have. So join us on the crowd. Chat crowdchat dot net slash data ops on May 27th. Go there at your calendar. We'll see you in the crowdchat.

>> Hi everybody, this is Dave Velante with the CUBE. And when we talk to practitioners about data and AI they have troubles infusing AI into their data pipeline and automating that data pipeline. So we're bringing together the community, brought to you by IBM to really understand how successful organizations are operationalizing the data pipeline and with me to talk about that is Aliye Ozcan. Aliye, hello, introduce yourself. Tell us about who you are. >> Hi Dave, how are you doing? Yes, my name is Aliye Ozcan I'm the Data Operations Data ops Global Marketing Leader at IBM. >> So I'm very excited about this project. Go to crowdchat.net/dataops, add it to your calendar and check it out. So we have practitioners, Aliye from Harley Davidson, Standard Bank, Associated Bank. What are we going to learn from them? >> What we are going to learn from them is the data experiences. What are the data challenges that they are going through? What are the data bottlenecks that they had? And especially in these challenging times right now. The industry is going through this challenging time. We are all going through this. How the foundation that they invested. Is now helping them to pivot quickly to market demands, the new market demands fast. That is fascinating to see, and I'm very excited having individual conversations with those experts and bringing those stories to the audience here. >> Awesome, and we also have Inderpal Bhandari from the CDO office at IBM, so go to crowdchat.net/dataops, add it to your calendar, we'll see you in the crowd chat.

(upbeat music) >> From Santa Clara, in the heart of Silicon Valley, it's the Cube, covering the Churchills, 2019. Brought to you by Silicon Angle Media. >> Welcome back here Jeff Frick here with the Cube. We're at the Chuchill's, it's the 9th annual award celebration put on by the Churchill club and the theme is all about leadership this year. We're really excited to have a very special guest John W. Thompson, chairman of Microsoft, a partner at Lightspeed Ventures, he's been around a long time. He's known and talks to a lot of leaders. So john, great to have you on. >> Nice to be here, thank you very much for having me. >> So leadership is such an interesting topic right? You go everything from, um, West point and trying to train young men to be leaders in a military situation to a start up that starts as some small company that had some interesting idea that grows to a huge corporate thing that's changing the world. Ya know, what are some of your thoughts as Silicon Valley is going through some hiccups right now and when you look, >> [John W. Thompson] We are? >> Just a couple little ones. >> I did recognize any of those. >> Well maybe not looking at the stock market. I don't know when that thing is coming back down. But you know when you think about leaders, what are somethings people maybe don't think about and really more interestingly how should people grow or what do you look for in a board member when you're talking to some CEO of a hot rising company? >> Well I think leadership is is as much about your personality and the business that use chose to go run is anything else. And the skills and experiences that someone might need to run a, pick a business, a business the size of Microsoft are fundamentally different than what you might need to run Rubrik, which is a company whose board I serve on. But that being said, leadership has some core principles that are critical independent of the size of the company or organization you're on. First of which is, integrity, second of which is focus, third of which is follow through and execution. There is lots of things that fundamental do and do well. And those who don't do well, don't become or stay leaders very long, that's for sure. >> It's interesting to look at Microsoft cause, ya know, three big personalities. Obviously Bill got it started as a young kid, I mean he was literally a kid in college. Um, then you had Steve Ballmer come in, completely different personalities and ya know, interesting for Bill to be willing to give up their reigns and then ya know, some tough times at Microsoft little bit stagnant and then Satya came in and just has supercharged and really driven a huge transformation in a giant big company. What are some of the attributes when you look at those three as leaders and you've worked with them, that make them so successful? >> Well, I think each of them brought something fundamentally different to the table when they were in the leadership role. In the case of Bill, he clearly was a visionary. He defined a point of view about the technology industry. That had he not done that, we wouldn't be where we are in the world today. And so, Bills role was unique. In the case of Steve, the company had hit a significant bump in the road all around the anti-trust activity. And candidly, it's my impression that Bill really didn't want to be involved in that, so he turned to Steve and says tag you're it. And Steve had a very fundamental view about execution. He was very much focus on execute, execute, execute. And if you look at the way the company preformed, its revenue grew from roughly ten, fifteen billion to almost eighty billion dollars during his term as CEO. However, the stock did not perform very well. So people weren't very happy with that. Ironically enough Satya come in, Satya had run the search business, had run the cloud business, had even run the enterprise software business. So he had a very fundamental view about of what he thought the company needed to do. And there were two issues, issues number one was strategy around cloud. And on the day of his announcement, he announced mobile first, cloud first are the strategies of Microsoft. And then he quickly, quickly made it clear that the number two issue, for the company, was about its culture. And while I am unbelievably fascinated by how much progress we've made on the product front, I'm even more encouraged by what has happened on the, candidly, on the cultural front. >> Right. So on the cultural front that is, are you a harder thing to impact especially on a large global company with hundreds of thousands of employees distributed all over the world, so what are the secrets that change culture like that? >> Its fundamental, it's about openness and honesty and candor. Um, one of the things that happens here in the valley, often for some companies is when they do their quarterly or monthly employee all hands meetings, guess what? They screen and filter all of the questions. Well, we don't do that at Microsoft office. Satya does not do that. He wants to be open and honest and candid with his employees with what's going on. My gosh! That's what real leaders do. And so I think what he has done is nothing that is unique, it's just consistent. He has been very very consistent and predictable in his execution of what openness, listening rather than talking, all of the things that good leaders are able to do. >> Right, its funny the one word you haven't said since we have been sitting here, you keep saying execution of focus, which I love focus execute and delight the customer. You haven't said strategy one single time. you said vision, but not strategy. Its interesting because I think a lot of people don't put enough emphasis on, its just work, you just got to execute. >> Its one thing to have a strategy, but if you can't execute the strategy, of what value is it? So I have always had a view in my roles as leader that it's about focus and executing. Yes, you have to come up with a vision and yes you have to create ideas that employees, and partners, and customers can become excited about. But ultimately it's about execution day in and day out. 368 days of the years, not 365. >> Alright, final question I know you've got a busy night. As you look as some leaders that you look up to, maybe not of this generation that you've been working with, but maybe of a past generation, who are some of the folks that you look to for your inspiration on the leadership side? >> Well, I would have to say the first one was the former vice chairman of IBM, who I was the chief of staff to many many many years ago. His name was Paul Rizzo. Paul was probably one of the most influential people in the company during that period of time, but you'd never know it. He had a level of humility about himself. He had a level of openness and candor in his interaction with employees at all levels up and down the line. And a company of IBM's size back in those days, it was two, three hundred thousand people big. And so he would be the first leader that comes to my mind as someone who was impactful on me. Another one would have been, a guy who created Akamai. He's on the board of Oracle and he's an awesome awesome friend of mine. He was the guy that ran the America's and gave me my first really really big job. And the fact that he was willing to give a guy like me a job like that, was a pretty important move. George Conrades is his name by the way. And so those two people were very very influential as leaders. As I would look at them and try to determine whether or not can I, can I pattern myself after that? Or are there things that they do and say and execute that I should consider as I think about my evolving leadership. >> Right so important to have people that you can look up to, learn from, and to take care of ya and help you along the way. >> [John W. Thompson] I agree >> John, thanks for spending some time it's always great to sit down with you >> Nice to see you as well. >> And continue success. We'll hopefully see you next time not to long from now. >> Lets hope not. >> Alright, he's John W. Thompson and I'm Jeff Frick. You're watching the Cube, were at the Churchill's in Santa Clara California. Thanks for watching we'll see you next time. (upbeat music)

(upbeat music) >> Hey welcome back everybody. Jeff Frick here with theCube. We're at Xerox PARC in Palo Alto, one of the most historic pieces of ground really in the history of computer science. We're excited to be here for a special event. It's the Innovators Master Class put on by the Conference Board. Relatively small event, great content. We've been here all morning and we're excited to have our next guest, she's Maureen Rinkunas. She's the Innovations System Designer, Specialty Products Division for DowDuPont. Maureen, great to see you. >> It's great to be here. >> So you're, you're giving a panel in a little bit about really how do big companies work with little companies to basically be more innnovative, so what are some of the things that you're looking forward to, what are some of the lessons that you've learned, 'cause you've had a very varied experience, you've been in academia, you've been in industry, you've been kind of big company and little company. >> Yes, and I think, you know, you learn a lot from being able to look outside of your sphere. And so that's what I'm really excited about on this panel, we're going to be talking with startups and VCs and it's not surprising, people are really keeping an eye on what's happening in Silicon Valley but I think for large corporations, we have to go beyond that. We have to say, let's not just be observers, let's be active participants in the ecosystem. And so I think that by engaging with some of the startups and businesses on this panel, we're really going to get some pragmatic advice on how to do that in the best way possible. >> Yeah, you had some great statements, I've been doing some research on you, about some tricks to innovation and one of the great ones was, new hires as change agents. I wonder if you could dig into that a little bit because I think, you know, unfortunately new hires, especially at a big company, they don't have status, they don't have title, you know, they don't necessary have formal authority but there's a real opportunity for companies to take advantage of this fresh new outlook to help look at things in a slightly different way. >> Yeah, it's actually been great to be here at the conference for an event because I've talked with a lot of organizations that are bringing in this fresh view and especially in innovation centers where the proportion of people coming from outside the organization is sometimes as high as 80 percent of the team at that facility and so it's really great to have people who aren't carrying the baggage of how we always have done things. >> Right right. >> And they can push the limits a little bit which is sometimes what we need to, to really break out of our routines and I think as well, you know, bringing people in who have experience in startups, people who, perhaps, are coming from the venture world also offers that opportunity for people who have experienced working in that really fast-paced environment, they are very impatient, which is a good thing and I think really push teams to move faster. So it's great to be able to bring that, an element, into your team. >> Right. There was a great presentation earlier today about DevOps and, you know, agile software development and it's easy in software, you know, you can have a two week spread and get something out new. In the chemical world, right, there's lots of different axes of innovation but you guys, kind of by rule, have to move slower. These are much bigger investments in factory and plant, you know, there's ecological implications to all these things. So when you look at the innovation challenges and opportunities at a big company like DowDuPont, what are some of the easier paths to go down that you can, you can help to drive some of that innovative thought process and products? >> Well I think, you know, certainly we don't want to take any shortcuts with safety, and so you're absolutely right, that in some ways we can't move as quick as launching a new app to market, but we really do need to challenge ourselves to think about how we move as quickly as possible. One way to do that is to look at outside innnovations and so, I've just recently was working with a team and they had mapped out their development pipeline, they thought, oh this is 3 to 5 years in the making, and then we were able to connect them with a startup who cut about 4 years out of that and so, they are actually really excited, they're going to be partnering with that startup and moving forward with a customer in a very short timeframe. So, I think there are ways to make that window a much shorter timeline. >> Right. And then what about just the culture clash? I mean, just this example specifically, you've got people that had probably a very comfortable, maybe they thought it was aggressive, timeline that went out for 4 or 5 years, then you bring up this crazy aggressive startup who are doing things much quicker. Was it simply process? Was it a new technology innovation? Was it just a different kind of spin of the lens that they were able to reframe their problem differently? And then how do you get those two groups of people to work together effectively? >> Well you know, I think in the corporate space, there's a lot of this, well we don't care because it wasn't invented here, syndrome. We're very fortunate that at a leadership level at DuPont, there has been very much this perspective that we need to get beyond that, we need to collaborate with our customers, we need to move externally, and so, you know, that helps, having someone who champions looking outside for alternatives, but I think, too, it's helpful to have those change agents within, people who are really brave, people who aren't afraid to push back, often these are the people who are coming outside with the legacy, they're not worried about getting fired and they're pushing for what they know is right and that's moving fast and hopefully making some positive change. >> Right, and not breaking too many things, right? >> (laughs) >> We've kind of got away from the move fast and break things. So final question, you know, we're here at this Innovation Master Class, what are you looking to get out of this type of event? Have you been here before and you know, what types of things do you take away of kind of this small, intimate little affair? >> Yeah so this is my second time here and you know, after seeing what we've learned this morning and reflecting on what I learned last year, I think you always take things away that are really actionable, you know, the folks that come to these events are in the field, they are getting things done, and so you really have an opportunity to learn from people who have tested things, they've learned from those experiments, sometimes they've failed and we can learn from those failures too and so that's what I really appreciate about having this opportunity to be here. >> Well Maureen, thanks for taking a few minutes. Good luck on your panel this afternoon. I can't wait to, can't wait to watch. >> Great, thanks. >> Alright, she's Maureen, I'm Jeff, you're watching theCube. We are at the Innovation Master Class put on by the Conference Board at Xerox PARC. Thanks for watching. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering AWS Reinvent 2017, presented by AWS, intel, and our ecosystem of partners. >> Well, welcome back. We're live here in Las Vegas at Reinvent. AWS putting on it's annual show, and you might notice the volume's gone up a little bit around here. Well, it's 5 o'clock reception time here, so the show floor has a little different vibe to it, you might say, right now. Justin Warren, John Walls, you kind of feel it, don't you, right now? >> Oh yeah, there is an energy just sort of vibrating around. I can feel the energy lifting as the booze starts to flow some more. >> Energy's a good way to put it. >> Yeah. >> Right. We're with W. Curtis Preston, who is the chief technical architect at Druva, and Curtis, thanks for being with us. >> Glad to be here. >> Do you feel a vibe, too? >> I feel the vibe. I feel the vibe standing out in the big line to get in here. >> Yeah, in here. >> And now we're in here, it's yeah, it's a lot of people. >> By the way, for those of you at home not familiar, you were named, this year, on the Deloitte Technology Fast 500 list, 175. >> Hey. >> Quite an honor. >> I assume you're talking about Druva, not me personally. >> Well, yeah, Druva, not you. Although maybe you did, I don't know. >> Yeah, I don't think. >> But that's quite an accomplishment, though. And quite an honor for the company. I mean, tell a little bit about that, about that process, and what do you think that means? What's that stamp of approval for what you guys are doing? >> Well, I think it's just, you know, like a lot of those lists, it's a recognition of the position that we're holding, right? I mean, Druva historically is really well known for their protection of endpoints and SaaS applications. They're expanding into data center and Cloud protection, but I think they're absolutely recognized as the leader in the protection of endpoints. >> Okay, so characterize the Cloud work you guys are doing. Like you said, this is a new move for you, I mean relatively new move, but the market's driving that way, right? >> Yeah. >> People starting to nod their head, and they're thinking, yep, this is where we need to be. >> Yeah, yep. >> So, what has been your strategy then, as far as facilitating what's no longer a trend, it's a way of life. >> Yeah, so I'd say first off, we are definitely unlike a lot of other players. We are a Cloud first company, in that, it's not a strategy, it's a way of life, so our entire application is built in and for the cloud, and by that I mean that it takes advantage of everything that the Cloud offers, right? And when you look at specifically AWS, a lot of backup software products use, well, they all use some kind of database, some kind of catalog to keep track of all the backups. And all of those catalogs, all of those databases, whether it's SQL Server or Db2 or Oracle, they all have scalability limits. We chose to use DynamoDB, which is an incredibly scalable no-SQL database. It's built and available in Amazon as a service, and then all of our products all run in Amazon, right? And so, we can scale both up and down to meet the requirements of a customer. So if we get a new customer. We had a customer that I can't mention by name, but they're a large company that started out with what we consider a small installation of about 10,000 laptops. And that was nice. And then it went well. And then there was a ransomware scare, and so they said, you know what, we're gonna go ahead and do everything. And so suddenly we needed to do 10 times as many laptops. Well, because of the way AWS is, we could scale both the database, the compute, and the storage all instantly to meet the demands of that client. And then once that's done, scale it back down to get back to a state of normal, right? So, for us the Cloud is sort of the core of who we are, and then the only expansion for us is actually protecting the Cloud. So, we've always used the Cloud as our destination, but now our newest offering, Apollo, actually is designed to protect starting with AWS and then expanding into the rest of the Amazon, well, I should say starting with EC2, and then eventually expanding into the rest of the AWS world. >> All right, so, with the tradition of endpoint protection and... >> You're gonna have to speak up, it's really loud in here. >> It's really loud, I'll make sure I'm yelling. So with the heritage that you've got of backing up endpoints and being able to protect endpoints, and now you're moving to protect Cloud workloads, as you say, you've got this Cloud heritage, but you're now looking at protecting workloads that live in the Cloud, what are some of the things that Druva's bringing from that endpoint knowledge that applies to those Cloud type workloads? >> Well I think the idea is that, you know, one of the things about the Cloud, people sort of view, I think there's steps of people using AWS, right? They sort of experiment, and they try out this and that, but once somebody really understands like we did, the things you can do when you can scale your VMs instantly and limitlessly, and your storage and your compute and your databases, once they go down that route, I think the fact that we, it's not necessarily the history of the endpoint itself, but the infrastructure that we built in order to protect those endpoints is already totally scalable and ready to meet the needs of however big of a workload that you'll put in AWS. >> Yeah, I often like to say that Cloud is a state of mind, so if you've already got that state of mind that I want to run my workloads in a Cloud-like way, well I want to be able to protect them in a Cloud-like way, and it sounds like that's really what you're trying to nail there. >> Yeah, and it's a big, because any like, I can look out and see multiple backup products available, and there's a lot of good backup products here. And any of them can run in the cloud, right? You can create a Linux VM or a Windows VM and install your backup software, but it's not going to magically become more scalable because you're running it in Amazon, right? So, designing the product for Amazon and that scalable way of doing things, that's why we talk about being Cloud native. >> Yeah, so how are you attracting customers who would have traditionally thought of you as an endpoint company. It's like, now you're actually saying, look we have these different offerings. So how are you starting to talk to those different kind of customers. How are you finding them and what is it that you're finding resonates with them as compared to some of the other options that they might have? >> Yeah, so as you probably know, I've been in the backup space now for, quarter of a century... (clearing throat) >> Literally wrote the book. >> Literally wrote the book, right? It's on O'Reilly. (laughing) Oreilly.com. >> We'll give you a plug later. >> Don't worry. >> Yeah, yeah, yeah. >> Literally wrote the book. >> Yeah, one thing I can say, there's a couple of things I can say about backups in general, in the average data center. One is, everybody hates their backup software. Right? Like, nobody likes it because it's so hard, right? It's so hard to configure, and using disc as a mechanism instead of tape as a primary mechanism, it's made things better, but it hasn't really solved it, right? It's still this really difficult to manage. There's this massive amount of infrastructure that has to be put in place to do all of that. And because that's so hard and it's so error prone and you're invisible or you're in trouble. No one cares about the millions of backups you get right, only the one restore you got wrong. And so what that translates into is the other truth, which is nobody wants to be the backup guy, right? >> I mean the way I got my first job in backups 24 years ago was a guy named Ron Rodriguez did not want to be the backup guy. >> Curtis, you're it. >> Yeah, you're it. And I within two months, had my first major failure as the backup guy for a 35 billion dollar company, and I thought I was done, I thought I was fired, like so many other backup people, and somehow just accidentally I ended up staying, and so what happens is, it's so hard. So, to go to your question, well what if it was simple, right? The situation is, the current system's not scalable. You're always buying another media server, you're always buying another tape driver, you're always buying another dedupe box. You know, you're always out of something, right? I remember having to go to my boss and being out of tapes. This is, you know, back when tapes were a thing. And I remember saying, "hey, I'm out of tapes." and she was like, we don't have budget." She's like, "what are our choices?" and I go, well, I can stop the backups. She's like, "that's not funny." I'm like, "that's our choice." Right? >> I have so much capacity here. >> These are our choices, right? And so she gave me the tapes that I needed, right? And so it's not scalable, the current system. You're always in need of some piece. It's also super expensive, right? And it's super hard. So we try to be the opposite of that. We try to be scalable, simple, and you know save people money. Right? I know we have a 4S thing. >> It's right there on the tip of your tongue. >> It's right there on the tip of my tongue. But basically we try to be the opposite of everything that backups are. So the big thing is, it's way easier. Just put a piece of software and magic happens, right? And if you're large enough data center that you need to do what we call seeding, where you have to use sneakernet to get the data to us, we have a system for that. If you have a large enough system where the RTO is not going to be able to be met by a copy that's on the other side of the internet, then we have a caching appliance that goes onsite to provide fast recovery. So it's like it's super simple, way less expensive. And I do mean way less expensive. I've seen some TCOs where we compete against other companies, we're even less expensive than renewing what you have, let alone going and buying. >> John: Replacing. >> And replacing it with something, because that happens all the times. Because people are always swapping their backup software, because the problem has got to be the backup software. Right? And I think in the end, it is, right? But, it's because that core architecture, that core way we've done backups, has essentially stayed the same since before I started. All we did was we changed tape to disc, right? And we introduced dedupe, which was great, but there's this technology that we call dedupe, that is really hard when you do it on the backend. You know, there's a company here who makes a lot of money on selling those appliances, right? Except it's really hard to do that, and so it's really expensive to do that. And then you gotta pay for one here and you gotta pay for one over there. With us, you don't buy that. You just go straight to us, and then because we're in AWS, it's already in three locations, right? And it's already offsite. >> Well Curtis, they said 24 years ago it wasn't gonna last, but it did. You made it, congratulations. >> Thanks. >> We appreciate the time here. >> Thanks. >> Thanks for being here with us on theCUBE and onto 175th. Next year who knows where you're going, right? >> Who knows where we're going. >> Excellent, Curtis Preston, joining us here from Druva. Back with more live from Las Vegas. We are at Reinvent at AWS. Back with more in a bit.

>> live from Las Vegas, Nevada. It's the Cube covering E M C. World 2015. Brought to you by E. M. C Brocade and D. C. >> You're watching E m C World Live here on the Q. Looking Angles Flagship program. We go out to the event they start the season noise. I'm John Kerry of my coast Dude. Minutemen. Our next guest is a cube. Alumni have been on a cute many times before and back again. 2011 John Thompson is the CEO of Virtual Instruments and also the chairman of a company called Microsoft. Um, welcome back to the cubes. Nice to be about Great to see you in the A M World week didn't interview on Virtual Instruments with CEO, and we were really riffing on this whole idea of data instrumentation. And we it was really free Internet of things. So give us the update. What's going on with virtue Instruments here? I see Microsoft has a conference going on ignite. Even though you're chairman. The board. You're also the CEO of Virgin Instruments and you're gonna do some business here. What's going on? What business are you doing? Well, this is an important conference for virtual instruments. DMC is one of our strongest go to market partners, and candidly, many of their customers are virtual instruments customers. And so it's an opportunity for me to be here to spend time with our partners and our customers in one venue. Our business is doing quite well. We just had a very, very strong March quarter, which is always a little bit of a down quarter for most tech companies. But we were up 27 28% year over year for the calendar. Q. One so we feel pretty good about that. This is the most important quarter of the year, though, which is always the case in Texas. So we're hoping that we can knock the ball out of the park again this quarter. We launched our virtual wisdom for platform in the spring of last year, and it is gaining tremendous traction, certainly in the U. S. And around the globe. It is all about health utilization in performance of the infrastructure, and we've defined a model where you can look at an application inside that infrastructure, monitor its performance and its availability, and that idea is so critical in a world where everything will someday live in the cloud and will you will want to assure a level of performance and, quite frankly, a level of responsiveness to customers as they come on says it's a reset to share the folks out. This is not a new concept for you guys. We talked about this years ago. It's not like you woke up one boys. Hey, things is trendy. This data center in fermentation takes us quickly back. Where did it come from? Was an itch to scratch. What original product as you have and how does that morph into today's crazy, data driven world, where dash boring riel time is actually competitive advantage and now table stakes? Well, if you were to go back to the genesis of virtual instruments, we started as a small technology investment inside a larger company called Venice are that was trying to solve the inevitable performance problem in the fibre channel world. And as the market crashed in 7 4008 the team at Venice or had to decide, how are we gonna clean up our portfolio? And the result waas. They sold off the assets? Were we, in fact, created virtual instruments. So a small group of investors, led by Jim Davidson from Silver Lake and Michael Marks from Riverwood, helped to fund the original investment and virtual instruments. We've been at it now for about seven years. We have clearly evolved the product quite a bit since then, and we've captured a number of very, very strong venture capital investment so long away as we made the choice. That said, we need the shift from being a fiber channel company to be in an infrastructure performance management company because the inevitable movement to the cloud will drive an opportunity for us. Yeah, and you're a senior executive private equity. I mean, this is pretty much a big bet. There's a lot of money involved with private equity. So it wasn't like you're, like, throw in the Silicon Valley startup together. It was really like, Okay, there's big money behind it. Well, you guys, did you see it turning out this way? What? What was learning that have been magnified from that trajectory? Well, I think in the early days we thought the path was a little different than what we've actually followed. We thought the path waas that the fibre channel World was so big and it needed better visibility. This would in fact give the world better visibility in the fibre channel space. What we have observed, however, is that the entire infrastructure has become Maur and more opaque, and therefore you need to not just drive visibility in the storage layer, but across the entire converge staff. And so the platform that we have evolved is all about supporting this converged platform not just fibre Channel, but filed a storage not just VM where, but all virtualized server environments. And we believe that's, ah, multibillion dollar market. And that's why we were able to attract both private equity initially and venture capital later as we built out of product. It's interesting. You see some of these ideas come a come around full circle. I'm curious. Just in industry trend. Your your opinion on Veritas, you know, being spun out. It's it's It's both sad for me personally, but I think it speaks to how difficult the cultural integration might have been between the two companies. While I really had a vision back in the old four or five days of security and backup coming together, I think It was a really, really difficult thing to make happen in the context of what has evolved at Samantha, so the fact that they've chosen to spend it out, it's perhaps a little disappointing for me personally, but not a surprise. So what is your vision of security today? My understanding, You advise, even sit on the board of ah Lumia company. We've way we've talked to the company really, what's happening in security. So if you think about how security has evolved once upon a time, it was about protecting the device candidly and a cloud based world. It's going to be more about protecting the workloads as they move around. And that's one of the elements of what a lumia does, in fact, provide. Furthermore, I have believed for a very, very long time that as time goes on, security will have to get closer and closer to that which is deemed to be most critical. In other words, you can't protect all of the data. You can't protect all of the instances that air on the Web, but you can identify those that are most critical and therefore need a level of protection beyond what the standard would be. And so my belief is that companies like a Loom EO and others that will evolve will get closer to the workload, and we'll get closer to the data that's most critical. And so data classification and things of that nature will become much, much more important than they have. You're an investor in aluminum. You on the board are okay, so you're on the board of director and investor. We covered their launch. Great company. The cracking is low slides, as as Alan Cohen would say, they phenomenal funding round gone from stealth two years and now the big $100,000,000 really funding round massive guerrilla marketing. Still going on at the air say, was kind of clever. The perimeter lists cloud is a factor. And what tech enabled? Do you see the key thing? Alan Cohen described it as 1000 foot shoulds soldiers protecting assets because there's no more perimeter that no front door any more. What is the technology driver for that? Well, the whole idea behind the loom Eo, is to have a what I would call a portable policy enforcement engine that can move as the workload moves around the cloud. So policy management, security policy management has been a very, very difficult task for most large enterprises. So if I can define security policies for every server of where workloads can go to and from on that server and make sure that nothing violates that policy, hence I enforce it routinely. Oh, I can change. The dynamic of House security gets delivered in a cloud based world because no workload is gonna run in any single place on a cloud world. That workload is gonna move to where there is capacity to handle. I gotta ask you because we have a lot of people out there that follow tech business test tech athletes that you are. But also, you're a senior executive who has a lot of experience, and we could be presenting to Harvard Business School, Stanford Business School. I want to get your kind of business mind out to the audience. And that is, is that as an executive who's seen the big, big companies, the big battleships, the big aircraft carriers, from the IBM days to the M in a world of the nineties and the transformation of the Internet now in a complete shift, an inflection point with things like a Loom, Eo and Cloud and and Virtual instruments and the new Microsoft and the Silicon Angles and the crowd shots out there, What do you advise managers out there to operate from a management perspective. I mean, there's a classic business school numbers quarter on the challenges of going public, managing enormous dynamic technology change. So every theater is kind of exploding the technology theater, the business theater, the social theater as an executive. How would you advise someone as a CEO are rising growing startup how they should stitch themselves together? If you can draw in from previous experiences? Or is there a pattern recognition you can share? Well, it's It's never simply about the numbers, while the numbers air always important and the numbers will always be the underpinning of evaluation or whatever. In reality, it's about having a team that is able to rally around a leader with vision that says, Here's how we're gonna change the world. Here's how we're going to make an impact as this industry goes through, the natural inflection points that it always does. And if you look at what has occurred in this industry about every 8 to 10 years, something significant changes. And so a company that may have missed an opportunity six or eight years ago has another shot at it six or eight years later because of the inflection points that we go through. So it's important for the leader of a company toe. Believe that I can change the world based upon the industry that I'm a part of and have a compelling point of view about what changing the world means for that company and that team. And if you could get the team together around that idea, what about cloud and big data and mobile thes dynamics that you would? If someone just wants a roadmap for navigation or what decked me to go after, What would you say? What do you say? You know, get it all in the cloud or go poke at a duel are indeed new, agile management. Things were happening like, Well, I think it starts with what are the court confidence is that you have as a team or company, so you can't say g I'm gonna go and do cloud and oh, by the way, I have no confidence in the management infrastructure for large enterprises or I'm gonna go do mobile and I really have no experience in the mobile space whatsoever. So core competencies matter and leveraging the core strengths of the company matters now. Oftentimes, what companies will do its supplement their core strengths through M, and we'll go out and acquire something and bolted on the hard part of M and A, which is what we were referencing early around. Veritas is Can you integrate it? Can you really make it work after you bought it? Buying it is the easy part. Generating it and making it work is the really, really tough part. And arguably we didn't do is good a job as I would have liked with Samantha. And so basically you're saying is if you as an executive, you want to look at the winds of change for hand, get the sails up, if you will, to confuse the metaphor and get into that slipstream so you can actually drive and you can't. Being an amateur, you gotta actually have some competency. You have a leverage point. Look, one of the great things about this industry is it doesn't take some brilliant business leader to create a new idea. I mean, no one ever would have viewed Zucker Bird as a business leader or some of the young, really, really powerful CEO built phenomenal, phenomenal companies in this industry. But they had an idea, and they were able to create a team around that idea and go change the world. And that's what's so powerful about this industry that I've had the pleasure to be a part of for 40 some years. Yes. Speaking about CEOs that changed the industry, John Chambers announced that he's stepping aside from the CEO role this morning. So you know when you look back, you know John was one of the four horsemen of the Internet era and 20 years there. Chuck Robbins is coming in. He's been there since C. I think 97. What do you think of that move? And you know what's happening with Cisco in leadership for the big companies? Well, John's a really, really good friend, and I admire him for all of what he's done and Cisco and I wish him well as he makes this transition. Interestingly enough, the transition is to executive chairman, with the new CEO stepping in so What that says is that John plans that have a little more involvement, perhaps in what goes on in the company. Then I do it. Microsoft. My title is not executive chairman of Microsoft. Thank goodness I wouldn't want it to. But it also speaks to the fact that John spend the CEO. It just goes since 1995 like that. So he has an enormous amount of knowledge and insight about the company industry, its customers, partners, culture, all of those culture. And so all of those things will be valuable and important to the new CEO. And I think him stepping into that role is trying to leverage that. Cenedella came in and made his voice heard really instantly. And Microsoft has been a great company to watch, you know, since Auntie's came on board, you know, just Cisco need to make some bold moves or are they pretty stable where they are is kind of the dominant? That's a better question for John and CEO. I think what is clear is that all all companies, at some point after find a way to redefine and Sasha's role at Microsoft. He has redefined Microsoft as a cloud first mobile first, and that's all about recognizing. Were acts are gonna run on what devices and what kind of service is. And that redefinition, I think, is important for any industry leader, regardless of how long you just brought us to the tagline of this show, M C World is redefined. So any comments, How's the emcee doing it? Redefining themselves, I think the emcees a terrific company. Joe's a longtime friend of mine. I mean, I know Joe forever on. It's been amazing to see how it's gone from being a storage company to this federation of companies that have capabilities that are so broad and so diverse. I hope they don't get pushed to do something that isn't in the best interest of customers, but maybe enamored by some investors. The angel of the activist pressure. Yeah, that's always and that that's unfortunate, but I think they have a nice balance now. They have a huge installed base and this competitive pressure so they gotta push that. But I have to. I have to ask, is that? You know, I was getting some tweets earlier about Microsoft, and I know you, you know, you're only chairman of the board executive chairman. But you were involved in a very historic where you were on the executive search committee for the CEO replacement for Steve Balmer, of which they chose sake. Nutella Cube alumni We interviewed at the XL Partners Innovation Summit in Stanford that that's about culture. That's about transitions, about inflection points. And Sister used to mention Cisco. Not similar situation. But Microsoft is the legend company. I think the computer industry like an apple. Microsoft was their big part of the computer revolution. Big seismic changing. You were right there. Just share some color on what that whole experience like for you personally. And if you can share any insights to the audience, I know it's a sense might be sensitive topic. But what's that like? And, you know, the outcomes. Looking good. As he says, he's doing great. What? What can you share? Well, I think it would be fair to say that it was a more consuming process than I ever thought it would be. I went from being a new board member of Microsoft in the spring of 2012 to be in the lead independent director in the fall of 2012 to leading the search starting in the summer of 2013. I mean, I never could have imagine my involvement there changing that dramatically, Nor would I have imagined that searching for a CEO of a company would consume 80% of my time when I was also running a company. So for a period of about six months, it's like athlete right there. I had two full time jobs where I was on the phone all day, every day, trying to get something done for the eye and on the phone all day, every day, trying to get something done for Microsoft as well. It was, I would also have to say and incredibly incredibly exhilarating experience. I talked to some phenomenal leaders from around the world way had hard, long look anywhere we wanted at any CEO or candidate that we wanted, and we settled on someone who was a Tech athlete. We believe that the company was at a really, really important inflection point where over the course of the next 12 to 24 months, we're gonna have to make some really, really important technology decisions that would set the course from Microsoft for many, many years to come. And so, while there was much speculation in the press about this person or that person, and what a great business leader, that person waas What we, as a board concluded, was that what our company needed at that moment in time was a true technology visionary who could drive the strategy of the company because it had assets. I mean, they had a whole search thing that they quote missed on paper. But they had, like you said, they could come back at it again with being the subtle art of assets. Here, Cloud was built out. Everything was kind of like in place for that tech athlete on. And I think soccer has done an amazing job. I'm quite proud of them. I'm happy toe say I have some small part in that, but I'm or happy for the way he has executed in the job. I mean, he steps into the job with a level of humility but confidence that is so important for the CEO of a company of that size, and to maintain that cultural DNA because you have one of most competitive companies on the planet. A question to the point where they had to be almost broken up by the DOJ from the Bill Gates kind of DNA and bomber to continued, be competitive, live in this new era. Really tough challenge. Well, he's he's a bright guy. He, as I said, has great humility and has the respect of the team. And it's been interesting to see the internal shift behavior and attitude with a guy who I jokingly say he has two ears and one mouth and he uses them proportionately. And that's a very important lesson for someone trying to transform a company. You must listen more than you talk, and I think he does a great job. We try to do that. The Cuban we talk all day long way do interviews, but I gotta ask you back to virtual instruments. Okay, gets a good business going on with the emcee Goto partner about the anywhere in the federation of a partner with you as well, say, Is it all Federation? It's mostly through E M. C. And while the em wears of small V I customer, we don't do much with them on the go to market side on the go to market side. We rely more heavily, if you will. On AMC, that partnership has evolved. I mean, from the early days it was viewed as G. We're not sure who you are and what you do and whether or not you're competitive with us today, we have very, very common go to market processes around the globe. I'd love to see them stronger. I just left to cheese office in San GI Joe. We could doom. Or but when it's when it's all said and gone, this is one of the strongest go to market partners we have that's also shared the folks out there what they might not know about insurance, that you could share their hearing this now for the first time and working on the radar future of your business, your division product, extensive bility. Future of Internet of everything. Future Internet of things, whatever you want to put on a big data and the data center now, and the migration of cloud is all here. So at our core, we believe that every large enterprise will inevitably have some, if not all, of their work in the class. So the question is, how do you help them manage that inevitable migration to the cloud by de risking the migration and ensuring appropriate infrastructure performance management. Once you arrive there, we focus on the largest enterprises in the world. So unlike many tech startups, that will start with a midsize or small company and work their way up well, the largest banks in the universe, the largest insurance companies in the universe, the largest of every sector in the universe is a customer of the eye or will be someday. And that notion of solving very, very complex problems is something that our team has great pride in our ability to do that I want to get philosophical with you. You can for second kind of sit back and, you know, have a glass of wine and kind of talk to the younger generation out there with all your history on experience. How great of an opportunity for the young entrepreneurs and CEOs out there right now. Given the the confluence of the shift and inflection points, can you compare this to an error? We on the Cubes say It's like the PC revolution bundled in with the clients, terrorists and the Internet. All kind of at once do you agree? And would you say it? Guys, you have an amazing opportunity. Well, I think example of just how crazy it is. I I was driving to the airport this morning, and what I thought would be our long drive took two hours. Because there's so many people on the road in the Valley going to work. There's just so much going on in Silicon Valley right now. It is amazing. And for anyone who has a really, really great idea, the thing that's equally amazing is there's lots of capital out there to support those ideas. And so I would encourage any young entrepreneur who has a thought socialize your thought, Get it out so people can learn about it and then go get money to support and back that though. There's lots of money out there for good ideas. Lots of money. \ewelry officially taking the time coming out. Your busy schedule. CEO Virtual Instruments, chairman of Microsoft Here inside the Cube tech athletes is a big deal. You are one of the great great. Always have a conversation with you, sharing your thanks so much. Just the Cuban. Be right back with more insights and the signal from the noise at this short break

>>The cube at IBM. Impact 2014 is brought to you by headline sponsor. IBM. Here are your hosts, John furrier and Paul Gillin. >>Hey, welcome back everyone. This is Silicon angle's the cube. It's our flagship program. We go out to the events district as soon from the noise. We're ending out day two of two days of wall to wall coverage with myself and Paul Galen. Uh, 10 to six 30 every day. I'm just, we'll take as much as we can just to get the data. Share that with you. Restrict the signal from the noise. I'm John furrier the bonus look at angle Miko is Paul Gilliam and our special guests, Holger Mueller, Mueller from constellation research analyst covering the space. Ray Wang was here earlier. You've been here for the duration. Um, we're going to break down the event. We'll do a wrap up here. Uh, we have huge impact event for 9,000 people. Uh, Paul, I want to go to you first and get your take on just the past two days. And we've got a lot of Kool-Aid injection attempts for Kool-Aid injection, but IBM people were very, very candid. I mean, I didn't find it, uh, very forceful at all from IBM. They're pragmatic. What's your thoughts on it? >>I think pragmatism is, is what I take away, John, if it gets a good, that's a good word for it. Uh, what I saw was a, uh, not a blockbuster. Uh, there was not a lot of, of, uh, of hype and overstatement about what the company was doing. I was impressed with Steve mills, but our interview with him yesterday, we asked about blockbuster acquisitions and he said basically, why, why, I mean, why should we take on a big acquisition that is going to create a headache, uh, for us in integrating into your organization? Let's focus on the spots where we have gaps and let's fill those. And that's really what they've, you know, they really have put their money where their mouth is and doing these 150 or more acquisitions over the last, uh, three or four years. Um, I think that the, the one question that I would have, I don't think there's any doubt about IBM's commitment to cloud as the future about their investment in big data analytics. They certainly have put their money where their mouth is. They're over $25 billion invested in big data analytics. One question I have coming out of this conference is about power and about the decision to exit the x86 market and really create confusion in a part of their business partners, their customers about about how they're going to fill that gap and where are they going to go for their actually needs and the power. Clearly power eight clearly is the future. It's the will fill that role in the IBM portfolio, but they've got to act fast. >>Do you think there's a ripple effect then so that that move I'll see cause a ripple effect in their ecosystem? >>Well, I was talking to a, I've talked to two IBM partners today, fairly large IBM partners and both of them have expressed that their customers are suffering some whiplash right now because all of a sudden the x86 option from IBM has gone away. And so it's frozen there. Their purchasing process and some of them are going to HP, some of them are looking at other providers. Um, I don't think IBM really has has told a coherent story to the markets yet about how >>and power's new. So they've got to prop that up. So you, so you're saying is okay, HP is going to get some new sales out of this, so frozen the for IBM and yet the power story's probably not clear. Is that what you're hearing? >>I don't think the power story is clear. I mean certainly it was news to me that IBM is taking on Intel at the, at this event and I was surprised that, that, >>that that was a surprise. Hold on, I've got to go to you because we've been sitting here the Cuban, we've been having all the execs come here and we've been getting briefed here in the cube. Shared that with the audience. You've been out on the ground, we've bumped into you guys, all, all the other analysts and all the briefings you've been in, the private sessions you've been in the rooms you've been, you've been, you've been out, out in the trenches there. What have you, what are you finding, what have you been hearing and what are the, some of the soundbites that you could share with the audience? It's not the classic God, Yemen, what are the differences? >>The Austin executives in cloud pedal, can you give me your body language? He had impact one year ago because they didn't have self layer at a time, didn't want to immediately actionable to do something involving what? A difference things. What in itself is fine, but I agree with what you said before is the messaging is they don't tell the customers, here's where we are right now. Take you by the hand. It's going to be from your door. And there's something called VMs. >>So it's very interesting. I mean I would consider IBM finalized the acquisition only last July. It's only been nine months since was acquired. Everything is software now. It leads me to think of who acquired who IBM acquired a software or did soflar actually acquire IBM because it seems to, SoftLayer is so strategic. IBM's cloud strategy going forward. >>Very strategic. I think it's probably why most transformative seemed like the Nexans agenda. And you've heard me say assault on a single thing. who makes it seven or eight weeks ago? It's moving very far. >>What do you think about the social business? Is that hanging together, that story? Hang on. It's obviously relevant direction. It's kind of a smarter planet positioning. Certainly businesses will be social. Are you seeing any meat on the bone there? On the collaboration side, >>one of the weakest parts, they have to be built again. Those again, they also have an additional for HR, which was this position, this stuff. It's definitely something which gives different change. >>I have to say, John, I was struck by the lack of discussion of social business in the opening keynote in particular a mobile mobile, big data. I mean that that came across very clear, but I've been accustomed to hearing that the social business rugby, they didn't, it didn't come out of this conference. >>Yeah. I mean my take on that was, is that >>I think it's pretty late. I don't think there's a lot of meat in the bone with the social, and I'll tell you why. I think it's like it's like the destination everyone wants to go to, but there's no really engine yet. Right. I think there's a lot of bicycle riding when they need a car. Right? So the infrastructure is just not is too embryonic, if you will. A lot of manual stuff going on. Even the analytics and you know you're seeing in the leaderboard here in the social media side and big data analytics. Certainly there are some core engine parts around IBM, but that social engine, I just don't see it happening. You risk requires a new kind of automation. It's got some real times, but I think that this is some, some nice bright spots. I love the streams. I love this zone's concept that we heard from Watson foundations. >>I think that is something that they need to pull out the war chest there and bring that front and center. I think the thinking about data as zones is really compelling and then I'll see mobile, they've got all the messaging on that and to give IBM to the benefit of the doubt. I mean they have a story now that they have a revenue generating story with cloud and with big data and social was never a revenue generating story. That's a software story. It's not big. It's not big dollars. And they've got something now that really they're really can drive. >>I'll tell you Chris Kristin from mobile first. She was very impressive and, and I'll tell you that social is being worked on. So I put the people are getting it. I mean IBM 100% gets social. I think the, the, it's not a gimmick to them. It's not like, Oh, we got some social media stuff. I think in the DNA of their soul, they, they come from that background of social. So I give them high marks on that. I just don't see the engine yet. I'm looking for analytics. I'm looking for a couple of eight cylinders. I just don't see it yet. You know, the engine, the engines, lupus and she wants to build the next generation of education. Big data, tons of mobile as the shoulder equivalent to social. I'm skeptical. I'm skeptical on Bloomix. I'll tell you why. I'm not skeptical. I shouldn't say that. >>It's going to get some plane mail for that. Okay. I'll say I'll see what's out there. I'll say it. I'm skeptical of Blumix because it could be a Wright brothers situation. Okay, look, I'm wrong guys building the wrong airplane. So the question is they might be on the wrong side of history if they don't watch the open source foundations because here's the problem. I have a blue mix, gets rushed to the market. Certainly IBM has got muscle solutions together. No doubt debting on cloud Foundry is really a risk and although people are pumping it up and it's got some momentum, they don't have a big community, they have a lot of marketing behind it and I know Jane's Wars over there is doing a great job and I'm Josh McKinsey over there with piston cloud. It'll behind it. It has all the elements of open collaboration and architecture or collaboration. However, if it's not a done deal yet in my mind, so that's a, that is a risk factor in my my mind. >>We've met a number of amazing, maybe you can help to do, to put these in order, a number of new concepts out there. We've got Bloomex the soft player, and we've got the marketplace, and these are all three concepts that approval, which is a subset of which, what's the hierarchy of these different platforms? >>That's hopefully, that's definitely at the bottom. The gives >>us visibility. You talk about the CIO and CSI all the time. Something you securities on every stupid LCO one on OCS and the marketplace. Basically naming the applications. Who would folded? IBM. IBM would have to meet opensource platform as a service. >>Well, it's not, even though it's not even open source and doing a deal with about foundries, so, so they've got, I think they're going in the middle. Where's their angle on that? But again, I like, again, the developer story's good, the people are solid. So I think it's not a fail of my, in my mind that all the messaging is great. But you know, we went to red hat summit, you know, they have a very active community, multiple generations in the data center, in the Indiana prize with Linux and, and open, you know, they're open, open shift is interesting. It's got traction and it's got legit traction. So that's one area. The other area I liked with Steve mills was he's very candid about this turf. They're staking out. Clearly the cloud game is up, is there is hardcore for them and in the IBM flavor enterprise cloud, they want to win the enterprise cloud. They clearly see Amazon, they see Amazon and its rhetoric and Grant's narrative and rhetoric against Amazon was interesting saying that there's more links on SoftLayer and Amazon. Now if you count links, then I think that number is skewed. So it's, you know, there's still a little bit of gamification going to have to dig into that. I didn't want to call him out on that, but know there's also a hosting business versus, you know, cloud parse the numbers. But what's your take on Amazon soft layer kind of comparison. >>It's, it's fundamentally different, right? Mustn't all shows everything. Why did see retailers moves is what to entirely use this software, gives them that visibility machine, this accommodation more conservatively knowing that I buy them, I can see that I can even go and physically touch that machine and I can only did the slowly into any cloud virtualization shed everything. >>Oh, Paul, I gotta say my favorite interview and I want to get your take on this. It was a Grady food. She was sat down with us and talk with us earlier today. IBM fell up, walks on water with an IBM Aussie legend in the computer industry. Just riveting conversation. I mean, it was really just getting started. I mean, it felt like we were like, you know, going into cruising altitude and then he just walked away. So they w what's your take on that conversation? >>Well, I mean, certainly he, uh, the gritty boujee interview, he gave us the best story of, of the two days, which is, uh, they're being in the hospital for open heart surgery, looking up, seeing the equipment, and it's going to be used to go into his chest and open his heart and knowing that he knows the people who program that, that equipment and they programmed it using a methodology that he invented. Uh, that, that, that's a remarkable story. But I think, uh, uh, the fact that that a great igloo can have a job at a company like IBM is a tribute to IBM. The fact that they can employ people like that who don't have a hard revenue responsibility. He's not a P. and. L, he's just, he's just a genius and he's a legend and he's an IBM to its crude, finds a place for people like that all throughout his organization. >>And that's why they never lost their soul in my opinion. You look at what HP and IBM, you know, IBM had a lot of reorganizations, a lot of pivots, so to speak, a lot of battleship that's turned this in way. But you know, for the most part they kept their R and D culture. >>But there's an interesting analogy too. Do you remember the case methodology was mutual support of them within the finance language that you mailed something because it was all about images, right? You would use this, this methodology, different vendors that were prior to the transport itself. Then I've yet to that credit, bring it together. bring and did a great service to all for software engineering. And maybe it's the same thing at the end, can play around diversity. >>You've got to give IBM process a great point. Earlier we, Steve mills made a similar reference around, it wasn't animosity, it was more of Hey, we've helped make Intel a big business, but the PC revolution, you know, where, what's in it for us? Right? You know, where's our, you know, help us out, throw us a bone. Or you know, you say you yell to Microsoft to go of course with the licensing fee with Gates, but this is the point, the unification story and with grays here, you know IBM has some real good cultural, you know industry Goodwill, you agree >>true North for IBM is the Antal quest customer. They'll do what's right where the money and the budget of the enterprise customers and press most want compatibility. They don't want to have staff, of course they want to have investment protection >>guys. I'd be able to do a good job of defining that as their cloud strategy that clearly are not going head to head with Amazon. It's a hybrid cloud strategy. They want to, they see the enterprise customers that legacy as as an asset and it's something they want to build on. Of course the risk of that is that Amazon right now is the pure play. It has all the momentum. It has all the buzz and and being tied to a legacy is not always the greatest thing in this industry, but from a practical revenue generating standpoint, it's pretty good. >>Hey guys, let's go down and wrap up here and get your final thoughts on the event. Um, and let's just go by the numbers, kind of the key things that IBM was promoting and then our kind of scorecard on kind of where they, where they kind of played out and new things that popped out of the woodwork that got your attention. You see the PO, the power systems thing was big on their messaging. Um, the big data story continues to be part of it. Blue mix central to the operations and the openness. You had a lot of open, open openness in their messaging and for the most part that's pretty much it. Um, well Watson, yeah, continue. Agents got up to Watson. >>Wow. A lot of news still to come out of Watson I think in many ways that is their, is their ACE in the hole and then that is their diamond. Any other thoughts? >>Well, what I missed is, which I think sets IBM apart from this vision, which is the idea of the API. Everybody else at that pure name stops the platform or says, I'm going to build like the org, I'm going to build you. That's a clear differentiator on the IBM side, which you still have to build part. They still have to figure out granularity surface that sets them apart that they have to give one. >>Yeah, and I think I give him an a plus on messaging. I think they're on all the right fault lines on the tectonic shifts that we're seeing. Everyone, I asked every every guest interview, what's the game changing moment? Why is it so important? And almost consistently the answers were, you know, we're living in a time of fast change data, you know, efficiency spare or you're going to be left behind. This is the confluence of all these trends, these fall lines. So I think IBM is sitting on these fall lines. Now the question is how fast can they cobbled together the tooling from the machineries that they have built over the years. Going back to the mainframe anniversary, it's out there. A lot of acquisitions, but, but so far the story and the story >>take the customer by the hand. That's the main challenge. I see. This wasn't often we do in Mexico, they want zero due to two times or they're chilling their conferences. It's the customer event and you know, and it's 9,000 people somehow have to do something to just show, right? So why is my wave from like distinguished so forth and so and so into? Well Lou mentioned, sure for the cloud, but how do we get there, right? What can we use, what am I SS and leverage? How do I call >>guys, really appreciate the commentary. Uh, this is going to be a wrap for us when just do a shout out to Matt, Greg and Patrick here doing a great job with the production here in the cube team and we have another cube team actually doing a simultaneous cube up in San Francisco service. Now you guys have done a great job here. And also shout out to Bert Latta Moore who's been doing a great job of live tweeting and help moderate the proud show, which was really a huge success and a great crowd chat this time. Hopefully we'll get some more influencers thought leaders in there for the next event and of course want to thank Paul Gillen for being an amazing cohost on this trip. Uh, I thought the questions and the and the cadence was fantastic. The guests were happy and hold there. Thank you for coming in on our wrap up. >>Really appreciate it. Constellation research. Uh, this is the cube. We are wrapping it up here at the IBM impact event here live in Las Vegas. It's the cube John furrier with Paul Gillen saying goodbye and see it. Our next event and stay tuned if it's look at angel dot DV cause we have continuous coverage of service now and tomorrow we will be broadcasting and commentating on the Facebook developer conference in San Francisco. We're running here, Mark Zuckerberg and all Facebook's developers and all their developer programs rolling out. So watch SiliconANGLE TV for that as well. Again, the cube is growing with thanks to you watching and thanks to all of our friends in the industry. Thanks for watching..

>>from around the globe, it's the cube with digital coverage of >>IBM. think 2021 >>brought to you by IBM. >>Welcome to the cubes coverage of IBM Think 2021. I'm lisa martin joined next by Peter morrow, the VP of sales and marketing at IBM partner TRM. Peter welcome to the program. >>I thank you. Happy to be here. >>Tell me a little bit about yourself and TRM before we dig in. >>Um Well Trn is a longtime business partner for IBM, we for about 30 years have specialized in helping IBM customers implement maximo and um have a lot of deep technology expertise and in maximo and and related um software and the enterprise asset management industry um On the VP of sales and marketing. I've been at TRM for about 10 years and I'm I'm proud to lead our talented sales teams and our sole mission is to help our customers get value out of their am solutions and and we're really excited about recent developments in Ai and and bringing value um to a lot of our customers and their organization and finally get our ally out of their longtime investments in the am. >>Let's dig in a bit more to the IBM relationship, I know TRM as a gold partner, but talk to me about that and how TRM has leveraged that partnership with IBM to help your customers be successful. >>Um sure, now, you know, we're a little bit of a unique partner with IBM for a long time, we've been pure resell and implementation services and and recently we've transitioned into an O E M relationship with IBM where we actually embed IBM products into broader TRM offerings. And I, you know, this, this relationship that we have with with IBM is really important as IBM is the, is the dominant player in the A, m and A I and and hybrid cloud. It's really a natural fit for us to leverage those really mature solutions and build on top of them. Uh, TRS deep expertise and the technology and the reliability side to offer more of an end to end solution to our customers. >>Got it. So the last year or so we've seen a lot of market dynamics. Talk to me about the E a M, market, what's going on there? What are some of the changes? >>Um well, there's a couple of key changes that that we see. Um one of the biggest changes I think that impacts our business and IBM is that customers really don't have an appetite for long expensive implementations of custom solutions. They're really looking for more turnkey solutions that have proven value already and and very mature. You know, they've already spent tens of millions of dollars implementing, you know, maximo or related E AM solution. They really don't want to embark on, you know, this really expensive long journey um to get to that next level. And so to me this requirement, we've been focused for the past couple years on developing much more turnkey solutions, one of which is is one that we call TRM maximo A. M solution and that's built on maximum, but it's also layered with IBM's new AI solution for maximo customers. And you know, we marry that with our deep reliability expertise and you know, we're really excited about being able to roll it out and in literally weeks instead of months or years for a lot of new customers and you know, that's a really short time to value. And our ally, it's something that's pretty much unheard of until now in this industry. >>Talk to me about some of the advantages that your customers are getting like on a general level from ai from hybrid cloud from data. >>Um I mean this is really groundbreaking. What we're finding is that there's, you know, until very recently, a I was really not embraced as a practical solution to a lot of maintenance problems. You know, you're looking at a community of of pretty old school mindsets and maintenance and reliability where you know, it's a very, you know, R. C. M is a very structured methodology for breaking down um equipment and failure types and and and solutions, you know, ways to predict those failures and you know, for a long time RCM specialists didn't really feel like a I was a solution that that was the answer. And what we're finding is that, you know, with the maturity level of IBMS products, it is now at a point where a I is a great fit and you take an experienced reliability specialist and you arm them with A. I tools like like IBM is asset monitor and maximum health and predict and you give them those tools and they can, they can roll out predictive solutions that scale like like really they've never had the chance to before >>and talk to me about some of the the adaptations that TRM has made in the last year or so as the market has been so much in flux and so many dynamics going on. How have you adapted to that to really help those customers take advantage of the latest technologies and for example use aI >>you know, well the big thing for us is recognizing that that customers really aren't interested in a long expensive, drawn out solution. You know, they recognize they have problems but until you can come to the table with something that they can digest in in small bites and that, is that a price point that isn't over the top there really happy staying with the status quo at least until the solutions, you know, can be delivered in like that, you know, very um bite sized um implementation program. So we've, we've spent a lot of time trying to make our solutions more turnkey, packaging up offerings in a way that you can start small, but all that effort you put in on a small scale, you can ramp up and scale enterprise wide without making a huge investment and it doesn't take years to roll it out. You can really do something and make an impact within a couple of weeks or months rather than many months and years down the road. >>That time to value is key, especially I think we've learned in the last year that that real time is so essential for so many things. I'm just curious of any industries in particular that TRM and IBM are really helping transform energy, for example, give me some examples of industries that are really moving forward with your technologies. >>It's really the classic asset intensive industries, utilities are really big maximum users and they're they're the ones that, you know, they um there embraced, they've embraced maximum for many, many years, they're hungry for innovative technology, but still, you know, cautious about moving forward on a large scale, but we're able to get them excited with the programs that we're offering and the same goes with oil and gas, that's another big user of maximum, you know, asset intensive organization and you know, manufacturing, you know, definitely big maximo users, all three have been, you know, very interested in moving forward with, you know, the ai for maintenance solutions that, you know, TRM and and IBM are together bringing to the market, >>You summed up, you know, across the oil and gas energy utilities, as you mentioned, what are some of the biggest things that you hear in terms of demands from customers when you're in sales meetings, what are they looking for problems they need you to help solve? >>You know, it's honestly, it's it's the classic problems that we've been working with them for 20 years and really have, they haven't been able to solve effectively, you know, where they're talking about, you know, critical assets that break down unexpectedly, you know, maintenance teams running around doing a lot of maintenance on assets that's in perfect health, um making big promises on transforming maintenance, you know, massively reducing maintenance budgets and it really hasn't happened. And there's really been until now no real solution that solves those problems directly. And we believe the combination of Ai and reliability engineering and in the key e A. M fundamental principles is what's going to help our customer base really get value and really solve the problems that they really suffered from all these years. >>It's interesting that you say that it really they haven't been able to solve those problems and but from a technological perspective, the technology is there now to help them do that. What's the time window when you're talking with customers, especially given the market dynamics that were still living in, are they coming to you saying help us? You know, within a week two weeks we've got to turn this around. >>I mean the ones that are approaching this with an open mind, you know, we can we can communicate to them that a huge undertaking is not required. They can they can get started on a small project, select one critical asset and then begin to plug in some data, um, you know, around that asset that they know is related to equipment failures. We can get that data connected with the maximum asset monitor and you know, within weeks they begin monitoring that asset health, They do some anomaly detection and it does not require a big long term investment. And so for somebody who is willing to keep an open mind about AI and and really wants to give it a try, you know, that sale cycle is very short. They're willing to get going relatively quickly. You know, we do find that many organizations want to step back, take it slow, assess other options. And for them, that's that aligns more with the classic, you know, big bang type of implementation project where that takes months of planning, you know, budget planning approvals and and that goes into that 12, 18 months sales cycle or project planning phase that, you know, that's fine. And at the end of that, you know, it's a big project but we really do recommend starting small, it is definitely possible to see some early quick winds and then roll out on a larger scale and you know, frankly you could have something deployed at scale within that entire period of planning that they would otherwise naturally do on their own. >>Take us out here peter with some predictions, some thoughts maybe a crystal ball on where you see the ea m market going the rest of this year and what TRM is planning to do to help customers really leverage opportunities and growth. >>You know, I really do believe we're at a tipping point where there's been a lot of anticipation leading up to um the release of maximo and the max maximum eight and the maximum application suite. There's the Ai apps that are in the sweet like asset monitor and health and predict that they really are mature products. There's not, you know, I think until now there's the customer base has, has viewed ai as more of like a fantasy or science fiction as it relates to two maintenance. But you know, these products are real and I think with a lot of spending having been on hold over the past year, there's a lot of interest in learning more, trying to test the waters. I really think that we're going to see a lot of interest in predictive solutions, a lot of interest in IOT projects and you know, we're in a position where we're ready to begin rolling these out and it's really exciting. >>Yeah, the maturation is there, the technology is the customer interest is there? Certainly the opportunities in there. Peter take us out with customers, go to learn more information about your solutions. >>I mean, the best places to check us out on our website, W W W dot TRM net dot com were also on linked in. We do a lot of blogs, we do a lot of webinars, you know, we're out in front and trying to make um, you know, the market aware of our thought leadership and deep expertise in, you know, maximo and e a M and and in predictive solutions. Um We've got a Youtube channel where we post demos and, you know, all of our webinars, so we're, you know, we're trying to push information out there, um you know, happy to, you know, we look forward to interacting with prospects and customers about how our solutions can impact them. >>Excellent. Peter thanks for stopping by and sharing with us more about the TRM IBM relationship, the opportunities in the A. M. Market and the appetite for AI that >>your customers and >>very big industries are having. We appreciate your time. >>Hey, thank you very much. I enjoyed it. >>Two for Peter Morrow. I'm Lisa Martin. You're watching the cubes coverage of IBM think 2021 Yeah.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Welcome back, everyone. Live Cube Live coverage here in San Francisco, California in the Mosconi North lobby for V Emerald 2019 tapes our 10th year covering with some great guest, three days of wall to wall coverage that an amazing signorina Rob Salmon is the president CEO of Cohee City. Dave Solo, presidency of the Special Olympics Northern California. Thanks for coming on. Thanks to spend the time. Thanks for doing. Set the table. Why we hear what we're talking about. What's the purpose here? I know I wouldn't want to set it up more >> absolutely. I've been involved with Special Olympics for several years now. When former company Netapp Matt Thompson over Adobe called me and said, We got this high tech challenge. Dr. We've never sold it out. We want it. We want to get more companies involved when you help out, and the answer was absolutely and that led to David asking me to be on the board. So I've been involved with David, the team for an awful long time. KOHI City When I joined the company, some of the folks there knew of my involvement is that we'd like to start participating as well, which has led to what we're doing here. Of'em World >> David Talk about Special Olympics Quick mission for sure about the folks that might not given update for sure. >> John Yes, so Special Olympics enriches the lives of children, adults with intellectual disabilities. And so, in our footprint in Northern California, with serve over 23,000 athletes ages eight above and it's it's it's interesting. There's a lot of misconceptions people will say to me That's a great event that you do every four years And they referring the World Games, especially its world games, where athletes from all over the world get a common compete. But locally, through the state programs, hundreds of competitions happen a each and every year. And in Northern California we have, or 400 competitions per year in 14 different sports provides a wonderful ray of opportunities for athletes to demonstrate what what they can do when given the opportunity >> to do so. Talk about the community of aspect of it because I think What's interesting is what's on TV and what's in the mainstream press. It's more reach people that can be known for that. But it's deeper than as you point out. But >> talk about the >> community aspect. Got volunteers, people, individuals involved. Yeah, but the makeup of the network? No, it's an incredible network. >> I think we've really brought in an expanded our reach over the last 10 years. It used to be well known primarily for sports programming. So now we have inclusive education and health programs. We're able to bring together people with and without intellectual disabilities through those mediums. So if I'd resource is to schools an education and they run special Olympics programming during the school day. So educators wanna have us because we're improving school clamp campuses, reducing bowling, enhancing social emotional learning. And so the work that we're doing is so so critical with that community, then the area health. We have inclusive health. So now we got health and medical crypt, uh, professionals that are now providing health screenings for athletes. So some of the younger volunteers that we get that they're wanting to make a career in the medical field they're exposed to our population, right? And so they learn more about their specific health needs. So it's really about changing people's attitudes. And so this community of supporters volunteers, health professionals, education, Really. Our goal is to change people's attitudes fundamentally worldwide about people with intellectual disabilities and really kind of produce inclusive mindsets. We call it really promote understanding. >> If I may. I I really think what David and his team does and folks of sports Special Olympics around the world, they're dying. Changing attitudes are changing lives, lives of the athletes, lives of the people that work with the athletes, lives of the families. If you go to these events and there's something special, there are a lot of fun. And when you get involved and you see it, it definitely touches your heart and you realize we could be doing so much more. We could be doing so much more. >> I'm struck by you. Clearly, there's a passion thread here, and your background is really interesting to me because you're an accomplished student athlete, played football on and then you started a career in nonprofit right away, and now Rob, he was somebody would have hired right. It was like the perfect student athlete. You know, magna cum laude. I want this guy on my team. My hard driving says that How did you get into this? And described the background of that >> know for sure, sewn with nonprofit work. I kind of kind of started out. I was working for Boys and Girls Clubs of America, raising money to go to grad school, to be a history professor of all things. And so I got involved with the Boys and Girls Club with special Olympics. When the opportunity came, what was what was unique about it? It's really about how sports changes people's lives. Growing up, my father left me when I was 10 years old, and so was my coaches. They were the ones that really wasn't for them. I don't know that I would be here today, so they really took an active role in my life. So I've been very passion. I believe sports is a catalyst for social change, changed my life and provide an opportunity for me to be successful. And so that's what I want to help get back to our after. And it's also so. It's interesting is it's also proves that takes a village, you know, in these experiences changes lives. I think this is the big story, and it points to that. The sports is one element of other things. Health care. So you start getting connected in this is where the magic happens. This is the key. Yeah, some of the stories that wherever just phenomenal. I think society focuses on what our athletes can't do and dwells on the disability. We don't do that. So what? We're passionate about showcasing what they can do and having our volunteer, you know, certified train coaches work with our athletes to really help them get to the next level so they could be successful not only on the field, but off the field. So I mean, I got to get involved. Talk about the virtual. You're in Northern California. That's your territory, your area. But people, how they get involved, they wanna be share some no points of touch. Yeah, for sure. So a couple key points to touch would be number one. We have over 20,000 volunteers in our footprints, so we have a tremendous need for volunteers both globally and here locally, with Special Olympics, Northern California number two is from a donor standpoint. So everything that we do for athletes is completely free. And we're able to do that because the support of our community partners, our corporate partners like, Oh, he city, you know, individual supporters foundations were able to do that because of themselves. You know, either someone could go to the global website Special Olympics dot order come to W w dot s, O N C dot or for Northern California. We're always looking for volunteers, donor's community supporters, and we're also looking for board members, particularly from the tech sector. Senior executives in the tech sector. Justin, you stay channel lies for the people involved that also includes the people who volunteered. I'm sure people that want to make a difference whether you're thinking of senior approach, rather urine or your employees who want to give back so tell about the lives changing impact there because this is a corporate angle here that's not doesn't it's not for profit thing. It's a four good thing. >> Oh, this is for a good thing, and the thing I did to that is, and we touched briefly on Boys and Girls Clubs of America. These are all great organizations. I know Patton is key note. This morning, touched on giving back. This is an opportunity. Well, we're all blessed. We should give back. But the whole notion of getting more involved in touching lives I'll start with my two boys. They went to summer games and U C Davis three or four years ago. Now both of her good runners and they had some other kids on the high school team go with them. They were incredibly impressed. They had a lot of fun. A little banter with the athletes. Newsome, Bath, please. Out there there, Let's talk your heart. The gun goes off for the start, and they're already you get the arms up, curing away, and there's others incredibly talented athletes as well. It's so it just opened your eyes of what is possible. You're the one thing I touch on Is self esteem matters for every one of us, whether you have a disability or not, whether you're young or my age, it matters for someone to tell you that you are good. You are really worthy. Your hard work is paying off. You see these athletes when they finish the race or accomplished something that couldn't be more proud going to these events it will want. You will want to get involved. That's what typically happens. >> It sounds like you do coverages gonna be making its way to these events. Actually, wait, are fully got this part in the NHL MLB, NFL Masters golf tournaments. We have to get a pro circuit going on here way. Wonderful. Yeah. Hey, this is a really great cause. Any final thoughts again, back for people who want to get involved in the North California group. What? What can you offer people? No, I think we offer people a tangible way, especially when we think of the tech sector. And we think of the, you know, the employees and the millennials and hands on way for people to come out to our regional competitions and actually engage with our athletes and volunteer and be hands on and actually see where your money goes. You know, see, see that it's something tangible and you're helping provide that venue for athletes to be successful. One of things I didn't mention that we're really proud of. So we have a way of athletes are college students. We have athletes that are full time employees. Married couples, >> Um, >> and then we have a published poet. But last couple months we have an athlete that passed the bar exam who is now going to be a practicing attorney on. So that's really shows that you know, one of the things that you guys are hitting on here, Rob, I know you guys do a lot with your company. You guys even donating one of your tech sessions for a survey that John Troyer's team did around. Check burnout. People get it and even my kids to go to the high school In a lot of high schools like this now, where people get stressed out of the weirdest things, >> This is the kind >> of thing that getting involved in these community events like this really could help everybody. She allowed a little bit, Really. Take a load off, work with people, see the connection, see the impact. It's a burnout tactic option. It's also a way to relieve some stress. Feel >> good about it. >> The employees of Cohee City, when they came to me and said they want to get more evolved, they didn't do it because of me, they did it because they're excited about working with Special Olympics and they're beaming. Means some of the athletes 11 9 with a bunch of athletes going the baseball game tonight, Hamilton tomorrow night, their families as well. We couldn't be more excited, But I agree with you. You look at all the stresses in our lives, and I think this notion of what you do, who you do with how you give back is really, really important. I think that gives back piece, I think more of us allowing employees to do that, helping our children and school understand truly important the value. Um, is this absolutely >> You guys are making a great point because we've both been involved in youth sports all our lives, and it's kind of become twisted where you've got kids needs and parents needs and the parents trying to meet him in the middle, and that's not the way it should be. Your initiatives, I mean, it underscores what it's really all about. Self esteem, having fun, supporting your teammates and the broader community. >> But they stay well and compete and win two that they're in there. See some of those players. I mean, they're >> hard. I've seen some hard core competition, no doubt. But how well do they start? So >> eight years always started eight. And we have an athlete that's 81 that participates in watching. >> So okay, so appropriate. But the reason I miss it because, you know, having studied this allowed it. It's like 12 years old is the crossover point where people start to get crazy. And if you start before then, in other words Oh, this kid is nine. But he's not that good. Who could tell what a nine year old Michael Jordan got cut from his freshman basketball team? So it just goes to show you. So I think that that again, the values that you guys air promoting our worthy thanks >> me feel better about what we're doing. A cohesive it really does. Thank you for doing this. Being able to put two things I'm really passionate about together. Ah, this is pretty special for me. And I think my it around our founder and the rest of the company. And in David and team, they just do a fantastic job. I just wanna make sure we keep building on it. >> Congratulations. Great to get the word out. Congratulations. All your hard work. Awesome Cube coverage live in San Francisco. We back with more after this short break.