>> 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.

>> From Boston, Massachusetts, it's the Cube covering WTG Transform 2019. Brought to you by Winslow Technology Group. >> Welcome back. I'm Stu Miniman, and we're here at WTG Transform 2019. Happy to welcome to the program first time guest, Marty Sanders who's the Chief Security Services Officer at Arctic Wolf. Marty, thanks so much for joining us. >> Thank you, Stu. >> All right Arctic Wolf's a partner, but before we get there, I have to say welcome back. >> Thank you, thank you. >> Because you're familiar with this event quite well. You have a background at Compellent, which of course we were just talking to Scott Winslow. It's where his company started. Just give our audience a little bit thumbnail of your background. >> Perfect. So yeah, Scott and I go back a long time. We actually started back working together at Zylotech back in the late 90's. After we left Zylotech, we actually went to Compellent. We started building Compellent back in 2002. As a company we wanted to start a new philosophy. Really sit down with customers prior to actually releasing products. So we actually built a customer council. We started that in Minneapolis, and then what we wanted to do is take it to the next level. We wanted to replicate that out to other parts of the country, and the first person we called was Scott. We started to do it with Scott, and started back in 2004. Had the first meeting here at the Commonwealth, actually with a handful of customers, and now it's grown into this. So it's unbelievable what he's done with the company. And when I look at what he does, he provides a tremendous amount of value to the customers and just sells them exactly what they want. But what they need as well. >> Yeah we always know when certain segments of the market that degree of separation, you look on LinkedIn is like, one and a half. >> Absolutely. >> Everybody knows each other. We all run around some of the same circles. So bring us up to speed. Arctic Wolf. I believe you're the first person we've had on from the company. So give us a little bit kind of the who and the what and the why. >> Perfect. ^- [Stu] Of Arctic Wolf. >> And again thank you very much for inviting us out for this as well. Yeah Arctic Wolf has been around since 2012. Started off in the SOC as a service. Obviously, in that small-medium business, they didn't have the capabilities to do a lot of the security work. Actually, Brian NeSmith, our CEO, started the company with his other founder Kim Tremblay. They worked at Blue Coat, they understood the security world. But understood that there was a big hole in that space, in that small-medium enterprise business. So they were actually way ahead of their time. I mean you look at from 2012 to 2015, it was a little bit slow growth. But now you start to look at where we're at, and the adoption of that, having a SOC as a service 7 by 24, hasn't been adopted very well. >> Yeah, I thought it was rather telling, actually in the keynote this morning, some people were asking about security, and they're like, wait, if I do this hybrid cloud stuff, how does that work? And I'm like, yeah I go to too many events. It's like, I have ingrained in my system now security is everyone's problem. There is no such thing as a moat. You assume that they are going to get in, so therefore I need to build at every level of the stack. I need to get in. But I'm an industry watcher. ^- [Marty] Yep. >> The people that are doing, what's their mindset, what's workin' well for them? Is security heightened? How's Arctic Wolf going? >> And you want to take that premise. I mean, one of the things that we do is we actually assign a concierge security team to that customer. So we want to be that extension of their environment. I mean, in fact, as we started to talk to some of the clients that we have here, they're repeating the words, what they feel like. My team is part of their team. And it makes it so much easier. So you're not dealing with somebody fresh every time that you call in. If you have any type of event that validates that there's somebody trying to break in. You want to have that person that understands your environment. Understands exactly where you've been. Making sure that you're up to speed on their network, all their ingress/egress points that they can come into. So it makes it so much easier if you have that consistent face that you're dealing with. >> Okay. Marty, is there a typical customer of Arctic Wolf? Where do you fit in the WTG? Their customer base? >> Yeah, I mean, that's a great question. I mean, when you look at where we really fit is, the first questions that we want to ask is do you have a security team? Do you have it 7 by 24? I mean, that's where we really want to make sure that we're augmenting that. I mean, when you look at a lot of the companies they might have that office admin that became the IT person, that became the security person. What we want to do is make sure that we're providing the true level of high security for those companies 7 by 24. Because obviously the bad guys know that there's going to be a hole after hours or whatever it's going to be. So that's when they want to go in. So we want to make sure that we're covering that. So Scott and his clients are kind of in that medium to small-medium business, moving up into the small enterprise, and it fits really well with them. >> Yeah, so you're saying most of them don't have an entire security SWAT team. >> Exactly. ^- Waiting 7 by 24, to do that. Walk us through maybe if you have a customer example or kind of a genericized version that you can share. What does an engagement look like from when they first plug in to when they're fully engaged? >> Perfect. So typically what we do is we actually once the deal is closed what we want to do is sit down with the customer and understand exactly all their different applications, all their environments. Understand all their ingress/egress points that they have coming in. We want to make sure that we're maximizing coverage. And what we want to do is triangulate anything that comes into that. Understand all the attack vectors that the bad guys may try to come in. So it takes us about 30 days to go through all of that. So once we get them onboarded, we assign that concierge security team. Going to be a senior and a less-senior person dedicated to that team. And basically they're going to go through and review that environment, make sure that they understand all the different applications. Is it Office 365? Any cloud apps that we need to hook up to it? All the different servers to make sure we're getting all that information. We want to provide more quiet service. We don't want to be, anytime someone knocks on the door, we don't want to be calling, Little Red Hen-type stories. We want to make sure that anything that we actually report on is going to be actionable for those customers. So that's that trusted confidante, that's where we build that strong relationship rather than sending out a note and retracting it as a false positive or anything like that. >> Okay. And Marty, I heard you mentioned some SAS applications and their infrastructure environment. Is public cloud included in that also? >> Absolutely. And what we want to do is make sure that we understand, like you said. And like Joe and Rick went through and talked about. There's going to be that private and public cloud. We want to make sure that we're capturing everything internally, but also if you're using those SAS applications on the outside, whatever they may be, we want to make sure that we're capturing all that information so that we can help with that. >> Okay. And billing. Is there multi-year commitments? Or how does the financial piece of this work? >> It can be MRR. I mean, we're going to go through on a monthly basis and we'd like to get at least a year commitment. It can be something that they sign up for a couple of months or they sign up for a year and pay monthly whatever they need to do. But typically what we want to do is provide that level of service and when you think about it, if you were to go out and buy a security team to cover 7 by 24, it's at least a minimum of six, seven people to do that. So when you look at the price point, we want to be less than that. We want to provide that high level of value. When you think about a single team going out and trying to do something, the typical threat is it has been in their environment for at least 100 days before they notice it. What we want to do is get it down to minutes. We want to make sure that any threat that's coming in we're notifying on it immediately. We want to make sure that we're going to capture all those things. >> All right. So Marty, when I talk to the big enterprises, security it's not only top of mind it's often a board-level discussion. When you come down to kind of the mid-size to small companies, where does security fit in their overall pictures? What are some of the biggest things on their mind? >> So it's very interesting. When you start to think about it, one of the things that is challenging, you look at some of the places that were having the greatest adoption rates are those companies that have the biggest threats. You look at where the money is. You look in the healthcare environments. The smaller healthcare. Or you look at the legal side of things. I mean, people know where there's money and where they need to have that data. So when you look at it, it's becoming a higher topic and it's becoming every conversation. And we don't like to say that the conversation gets highlighted after a breach or whatever it's going to be, but it does. I mean, and we'll be in the middle of some discussions and you'll hear about somebody that just got hit in a similar environment. And that's how then it gets brought up. >> Oh, boy. Sounds almost all the discussion is data is the new oil. >> Yes. Well those bad actors out there know where the oil is. >> Absolutely >> And therefore that's a security risk for them. >> Absolutely. And I mean the thing that you look at is, you hear about where some of the Atlanta, and some of the other cities that were hit. I mean they go after the localities and the municipalities of making sure that they're going after. And they know that they're going to pay very quickly because of how incredibly important that data is to do that. And even some of the sitting talking to some of the customers here today. Manufacturing, you know? Just the ability to go in and steal the IP that they have to make their business a little bit unique. That's where the people are concentrating because they want to take that and find that uniqueness in that business. >> All right. Marty, want to give you the final word. WTG Transform 2019. Talk about the partnership, talk about the customers and final takeaways. >> So the partnership, I mean, obviously Scott and I have known each other for a long time. The entire sales team and I know Scott. Rick Gowan actually was a customer of ours at Travelers Insurance. Scott hires great people, great employees. They partner. They take care of their customers better than anybody that I know. I mean, I just love the passion. In fact, some of the customers that we started with back in 2004 are still here. Still using the same products. But they continue to look at what provides the most value for them. >> All right. Marty Sanders the CSSO of Arctic Wolf, thanks so much for joining us. ^- Thank you, Stu. >> And appreciate all the updates. >> Thank you. All right. Full day of coverage here in the shadow of Fenway Park, Boston, Massachusetts. The East Coast team's home game as we like to say. I'm Stu Miniman. Thanks so much for watching the Cube. (gentle techno music)

(upbeat music) >> Hey, everyone. Welcome back to theCUBE's day one coverage of Cloud Native SecurityCon 2023. This has been a great conversation that we've been able to be a part of today. Lisa Martin with John Furrier and Dave Vellante. Dave and John, I want to get your take on the conversations that we had today, starting with the keynote that we were able to see. What are your thoughts? We talked a lot about technology. We also talked a lot about people and culture. John, starting with you, what's the story here with this inaugural event? >> Well, first of all, there's two major threads. One is the breakout of a new event from CloudNativeCon/KubeCon, which is a very successful community and events that they do international and in North America. And that's not stopping. So that's going to be continuing to go great. This event is a breakout with an extreme focus on security and all things security around that ecosystem. And with extensions into the Linux Foundation. We heard Brian Behlendorf was on there from the Linux Foundation. So he was involved in Hyperledger. So not just Cloud Native, all things containers, Kubernetes, all things Linux Foundation as an open source. So, little bit more of a focus. So I like that piece of it. The other big thread on this story is what Dave and Yves were talking about on our panel we had earlier, which was the business model of security is real and that is absolutely happening. It's impacting business today. So you got this, let's build as fast as possible, let's retool, let's replatform, refactor and then the reality of the business imperative. To me, those are the two big high-order bits that are going on and that's the reality of this current situation. >> Dave, what are your top takeaways from today's day one inaugural coverage? >> Yeah, I would add a third leg of the stool to what John said and that's what we were talking about several times today about the security is a do-over. The Pat Gelsinger quote, from what was that, John, 2011, 2012? And that's right around the time that the cloud was hitting this steep part of the S-curve and do-over really has meant in looking back, leveraging cloud native tooling, and cloud native technologies, which are different than traditional security approaches because it has to take into account the unique characteristics of the cloud whether that's dynamic resource allocation, unlimited resources, microservices, containers. And while that has helped solve some problems it also brings new challenges. All these cloud native tools, securing this decentralized infrastructure that people are dealing with and really trying to relearn the security culture. And that's kind of where we are today. >> I think the other thing too that I had Dave is that was we get other guests on with a diverse opinion around foundational models with AI and machine learning. You're going to see a lot more things come in to accelerate the scale and automation piece of it. It is one thing that CloudNativeCon and KubeCon has shown us what the growth of cloud computing is is that containers Kubernetes and these new services are powering scale. And scale you're going to need to have automation and machine learning and AI will be a big part of that. So you start to see the new formation of stacks emerging. So foundational stacks is the machine learning and data apps are coming out. It's going to start to see more apps coming. So I think there's going to be so many new applications and services are going to emerge, and if you don't get your act together on the infrastructure side those apps will not be fully baked. >> And obviously that's a huge risk. Sorry, Dave, go ahead. >> No, that's okay. So there has to be hardware somewhere. You can't get away with no hardware. But increasingly the security architecture like everything else is, is software-defined and makes it a lot more flexible. And to the extent that practitioners and organizations can consolidate this myriad of tools that they have, that means they're going to have less trouble learning new skills, they're going to be able to spend more time focused and become more proficient on the tooling that is being applied. And you're seeing the same thing on the vendor side. You're seeing some of these large vendors, Palo Alto, certainly CrowdStrike and fundamental to their strategy is to pick off more and more and more of these areas in security and begin to consolidate them. And right now, that's a big theme amongst organizations. We know from the survey data that consolidating redundant vendors is the number one cost saving priority today. Along with, at a distant second, optimizing cloud costs, but consolidating redundant vendors there's nowhere where that's more prominent than in security. >> Dave, talk a little bit about that, you mentioned the practitioners and obviously this event bottoms up focused on the practitioners. It seems like they're really in the driver's seat now. With this being the inaugural Cloud Native SecurityCon, first time it's been pulled out of an elevated out of KubeCon as a focus, do you think this is about time that the practitioners are in the driver's seat? >> Well, they're certainly, I mean, we hear about all the tech layoffs. You're not laying off your top security pros and if you are, they're getting picked up very quickly. So I think from that standpoint, anybody who has deep security expertise is in the driver's seat. The problem is that driver's seat is pretty hairy and you got to have the stomach for it. I mean, these are technical heroes, if you will, on the front lines, literally saving the world from criminals and nation-states. And so yes, I think Lisa they have been in the driver's seat for a while, but it it takes a unique person to drive at those speeds. >> I mean, the thing too is that the cloud native world that we are living in comes from cloud computing. And if you look at this, what is a practitioner? There's multiple stakeholders that are being impacted and are vulnerable in the security front at many levels. You have application developers, you got IT market, you got security, infrastructure, and network and whatever. So all that old to new is happening. So if you look at IT, that market is massive. That's still not transformed yet to cloud. So you have companies out there literally fully exposed to ransomware. IT teams that are having practices that are antiquated and outdated. So security patching, I mean the blocking and tackling of the old securities, it's hard to even support that old environment. So in this transition from IT to cloud is changing everything. And so practitioners are impacted from the devs and the ones that get there faster and adopt the ways to make their business better, whether you call it modern technology and architectures, will be alive and hopefully thriving. So that's the challenge. And I think this security focus hits at the heart of the reality of business because like I said, they're under threats. >> I wanted to pick up too on, I thought Brian Behlendorf, he did a forward looking what could become the next problem that we really haven't addressed. He talked about generative AI, automating spearphishing and he flat out said the (indistinct) is not fixed. And so identity access management, again, a lot of different toolings. There's Microsoft, there's Okta, there's dozens of companies with different identity platforms that practitioners have to deal with. And then what he called free riders. So these are folks that go into the repos. They're open source repos, and they find vulnerabilities that developers aren't hopping on quickly. It's like, you remember Patch Tuesday. We still have Patch Tuesday. That meant Hacker Wednesday. It's kind of the same theme there going into these repos and finding areas where the practitioners, the developers aren't responding quickly enough. They just don't necessarily have the resources. And then regulations, public policy being out of alignment with what's really needed, saying, "Oh, you can't ship that fix outside of Germany." Or I'm just making this up, but outside of this region because of a law. And you could be as a developer personally liable for it. So again, while these practitioners are in the driver's seat, it's a hairy place to be. >> Dave, we didn't get the word supercloud in much on this event, did we? >> Well, I'm glad you brought that up because I think security is the big single, biggest challenge for supercloud, securing the supercloud with all the diversity of tooling across clouds and I think you brought something up in the first supercloud, John. You said, "Look, ultimately the cloud, the hyperscalers have to lean in. They are going to be the enablers of supercloud. They already are from an infrastructure standpoint, but they can solve this problem by working together. And I think there needs to be more industry collaboration. >> And I think the point there is that with security the trend will be, in my opinion, you'll see security being reborn in the cloud, around zero trust as structure, and move from an on-premise paradigm to fully cloud native. And you're seeing that in the network side, Dave, where people are going to each cloud and building stacks inside the clouds, hyperscaler clouds that are completely compatible end-to-end with on-premises. Not trying to force the cloud to be working with on-prem. They're completely refactoring as cloud native first. And again, that's developer first, that's data first, that's security first. So to me that's the tell sign. To me is if when you see that, that's good. >> And Lisa, I think the cultural conversation that you've brought into these discussions is super important because I've said many times, bad user behavior is going to trump good security every time. So that idea that the entire organization is responsible for security. You hear that all the time. Well, what does that mean? It doesn't mean I have to be a security expert, it just means I have to be smart. How many people actually use a VPN? >> So I think one of the things that I'm seeing with the cultural change is face-to-face problem solving is one, having remote teams is another. The skillset is big. And I think the culture of having these teams, Dave mentioned something about intramural sports, having the best people on the teams, from putting captains on the jersey of security folks is going to happen. I think you're going to see a lot more of that going on because there's so many areas to work on. You're going to start to see security embedded in all processes. >> Well, it needs to be and that level of shared responsibility is not trivial. That's across the organization. But they're also begs the question of the people problem. People are one of the biggest challenges with respect to security. Everyone has to be on board with this. It has to be coming from the top down, but also the bottom up at the same time. It's challenging to coordinate. >> Well, the training thing I think is going to solve itself in good time. And I think in the fullness of time, if I had to predict, you're going to see managed services being a big driver on the front end, and then as companies realize where their IP will be you'll see those managed service either be a core competency of their business and then still leverage. So I'm a big believer in managed services. So you're seeing Kubernetes, for instance, a lot of managed services. You'll start to see more, get the ball going, get that rolling, then build. So Dave mentioned bottoms up, middle out, that's how transformation happens. So I think managed services will win from here, but ultimately the business model stuff is so critical. >> I'm glad you brought up managed services and I want to add to that managed security service providers, because I saw a stat last year, 50% of organizations in the US don't even have a security operations team. So managed security service providers MSSPs are going to fill the gap, especially for small and midsize companies and for those larger companies that just need to augment and compliment their existing staff. And so those practitioners that we've been talking about, those really hardcore pros, they're going to go into these companies, some large, the big four, all have them. Smaller companies like Arctic Wolf are going to, I think, really play a key role in this decade. >> I want to get your opinion Dave on what you're hoping to see from this event as we've talked about the first inaugural standalone big focus here on security as a standalone. Obviously, it's a huge challenge. What are you hoping for this event to get groundswell from the community? What are you hoping to hear and see as we wrap up day one and go into day two? >> I always say events like this they're about educating, aspiring to action. And so the practitioners that are at this event I think, I used to say they're the technical heroes. So we know there's going to be another Log4j or a another SolarWinds. It's coming. And my hope is that when that happens, it's not an if, it's a when, that the industry, these practitioners are able to respond in a way that's safe and fast and agile and they're able to keep us protected, number one and number two, that they can actually figure out what happened in the long tail of still trying to clean it up is compressed. That's my hope or maybe it's a dream. >> I think day two tomorrow you're going to hear more supply chain, security. You're going to start to see them focus on sessions that target areas if within the CNCF KubeCon + CloudNativeCon area that need support around containers, clusters, around Kubernetes cluster. You're going to start to see them laser focus on cleaning up the house, if you will, if you can call it cleaning up or fixing what needs to get fixed or solved what needs to get solved on the cloud native front. That's going to be urgent. And again, supply chain software as Dave mentioned, free riders too, just using open source. So I think you'll see open source continue to grow, but there'll be an emphasis on verification and certification. And Docker has done a great job with that. You've seen what they've done with their business model over hundreds of millions of dollars in revenue from a pivot. Catch a few years earlier because they verify. So I think we're going to be in this verification blue check mark of code era, of code and software. Super important bill of materials. They call SBOMs, software bill of materials. People want to know what's in their software and that's going to be, again, another opportunity for machine learning and other things. So I'm optimistic that this is going to be a good focus. >> Good. I like that. I think that's one of the things thematically that we've heard today is optimism about what this community can generate in terms of today's point. The next Log4j is coming. We know it's not if, it's when, and all organizations need to be ready to Dave's point to act quickly with agility to dial down and not become the next headline. Nobody wants to be that. Guys, it's been fun working with you on this day one event. Looking forward to day two. Lisa Martin for Dave Vellante and John Furrier. You're watching theCUBE's day one coverage of Cloud Native SecurityCon '23. We'll see you tomorrow. (upbeat music)

>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

(upbeat music) >> From theCube Studios in Palo Alto in Boston, bringing you data driven insights from theCube and ETR. This is Breaking Analysis with Dave Vellante. >> While by no means a safe haven, the cybersecurity sector has outpaced the broader tech market by a meaningful margin, that is up until very recently. Cybersecurity remains the number one technology priority for the C-suite, but as we've previously reported the CISO's budget has constraints just like other technology investments. Recent trends show that economic headwinds have elongated sales cycles, pushed deals into future quarters, and just like other tech initiatives, are pacing cybersecurity investments and breaking them into smaller chunks. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis we explain how cybersecurity trends are reverting to the mean and tracking more closely with other technology investments. We'll make a couple of valuation comparisons to show the magnitude of the challenge and which cyber firms are feeling the heat, which aren't. There are some exceptions. We'll then show the latest survey data from ETR to quantify the contraction in spending momentum and close with a glimpse of the landscape of emerging cybersecurity companies, the private companies that could be ripe for acquisition, consolidation, or disruptive to the broader market. First, let's take a look at the recent patterns for cyber stocks relative to the broader tech market as a benchmark, as an indicator. Here's a year to date comparison of the bug ETF, which comprises a basket of cyber security names, and we compare that with the tech heavy NASDAQ composite. Notice that on April 13th of this year the cyber ETF was actually in positive territory while the NAS was down nearly 14%. Now by August 16th, the green turned red for cyber stocks but they still meaningfully outpaced the broader tech market by more than 950 basis points as of December 2nd that Delta had contracted. As you can see, the cyber ETF is now down nearly 25%, year to date, while the NASDAQ is down 27% and change. Now take a look at just how far a few of the high profile cybersecurity names have fallen. Here are six security firms that we've been tracking closely since before the pandemic. We've been, you know, tracking dozens but let's just take a look at this data and the subset. We show for comparison the S&P 500 and the NASDAQ, again, just for reference, they're both up since right before the pandemic. They're up relative to right before the pandemic, and then during the pandemic the S&P shot up more than 40%, relative to its pre pandemic level, around February is what we're using for the pre pandemic level, and the NASDAQ peaked at around 65% higher than that February level. They're now down 85% and 71% of their previous. So they're at 85% and 71% respectively from their pandemic highs. You compare that to these six companies, Splunk, which was and still is working through a transition is well below its pre pandemic market value and 44, it's 44% of its pre pandemic high as of last Friday. Palo Alto Networks is the most interesting here, in that it had been facing challenges prior to the pandemic related to a pivot to the Cloud which we reported on at the time. But as we said at that time we believe the company would sort out its Cloud transition, and its go to market challenges, and sales compensation issues, which it did as you can see. And its valuation jumped from 24 billion prior to Covid to 56 billion, and it's holding 93% of its peak value. Its revenue run rate is now over 6 billion with a healthy growth rate of 24% expected for the next quarter. Similarly, Fortinet has done relatively well holding 71% of its peak Covid value, with a healthy 34% revenue guide for the coming quarter. Now, Okta has been the biggest disappointment, a darling of the pandemic Okta's communication snafu, with what was actually a pretty benign hack combined with difficulty absorbing its 7 billion off zero acquisition, knocked the company off track. Its valuation has dropped by 35 billion since its peak during the pandemic, and that's after a nice beat and bounce back quarter just announced by Okta. Now, in our view Okta remains a viable long-term leader in identity. However, its recent fiscal 24 revenue guide was exceedingly conservative at around 16% growth. So either the company is sandbagging, or has such poor visibility that it wants to be like super cautious or maybe it's actually seeing a dramatic slowdown in its business momentum. After all, this is a company that not long ago was putting up 50% plus revenue growth rates. So it's one that bears close watching. CrowdStrike is another big name that we've been talking about on Breaking Analysis for quite some time. It like Okta has led the industry in a key ETR performance indicator that measures customer spending momentum. Just last week, CrowdStrike announced revenue increased more than 50% but new ARR was soft and the company guided conservatively. Not surprisingly, the stock got absolutely crushed as CrowdStrike blamed tepid demand from smaller and midsize firms. Many analysts believe that competition from Microsoft was one factor along with cautious spending amongst those midsize and smaller customers. Notably, large customers remain active. So we'll see if this is a longer term trend or an anomaly. Zscaler is another company in the space that we've reported having great customer spending momentum from the ETR data. But even though the company beat expectations for its recent quarter, like other companies its Outlook was conservative. So other than Palo Alto, and to a lesser extent Fortinet, these companies and others that we're not showing here are feeling the economic pinch and it shows in the compression of value. CrowdStrike, for example, had a 70 billion valuation at one point during the pandemic Zscaler top 50 billion, Okta 45 billion. Now, having said that Palo Alto Networks, Fortinet, CrowdStrike, and Zscaler are all still trading well above their pre pandemic levels that we tracked back in February of 2020. All right, let's go now back to ETR'S January survey and take a look at how much things have changed since the beginning of the year. Remember, this is obviously pre Ukraine, and pre all the concerns about the economic headwinds but here's an X Y graph that shows a net score, or spending momentum on the y-axis, and market presence on the x-axis. The red dotted line at 40% on the vertical indicates a highly elevated net score. Anything above that we think is, you know, super elevated. Now, we filtered the data here to show only those companies with more than 50 responses in the ETR survey. Still really crowded. Note that there were around 20 companies above that red 40% mark, which is a very, you know, high number. It's a, it's a crowded market, but lots of companies with, you know, positive momentum. Now let's jump ahead to the most recent October survey and take a look at what, what's happening. Same graphic plotting, spending momentum, and market presence, and look at the number of companies above that red line and how it's been squashed. It's really compressing, it's still a crowded market, it's still, you know, plenty of green, but the number of companies above 40% that, that key mark has gone from around 20 firms down to about five or six. And it speaks to that compression and IT spending, and of course the elongated sales cycles pushing deals out, taking them in smaller chunks. I can't tell you how many conversations with customers I had, at last week at Reinvent underscoring this exact same trend. The buyers are getting pressure from their CFOs to slow things down, do more with less and, and, and prioritize projects to those that absolutely are critical to driving revenue or cutting costs. And that's rippling through all sectors, including cyber. Now, let's do a bit more playing around with the ETR data and take a look at those companies with more than a hundred citations in the survey this quarter. So N, greater than or equal to a hundred. Now remember the followers of Breaking Analysis know that each quarter we take a look at those, what we call four star security firms. That is, those are the, that are in, that hit the top 10 for both spending momentum, net score, and the N, the mentions in the survey, the presence, the pervasiveness in the survey, and that's what we show here. The left most chart is sorted by spending momentum or net score, and the right hand chart by shared N, or the number of mentions in the survey, that pervasiveness metric. that solid red line denotes the cutoff point at the top 10. And you'll note we've actually cut it off at 11 to account for Auth 0, which is now part of Okta, and is going through a go to market transition, you know, with the company, they're kind of restructuring sales so they can take advantage of that. So starting on the left with spending momentum, again, net score, Microsoft leads all vendors, typical Microsoft, very prominent, although it hadn't always done so, it, for a while, CrowdStrike and Okta were, were taking the top spot, now it's Microsoft. CrowdStrike, still always near the top, but note that CyberArk and Cloudflare have cracked the top five in Okta, which as I just said was consistently at the top, has dropped well off its previous highs. You'll notice that Palo Alto Network Palo Alto Networks with a 38% net score, just below that magic 40% number, is healthy, especially as you look over to the right hand chart. Take a look at Palo Alto with an N of 395. It is the largest of the independent pure play security firms, and has a very healthy net score, although one caution is that net score has dropped considerably since the beginning of the year, which is the case for most of the top 10 names. The only exception is Fortinet, they're the only ones that saw an increase since January in spending momentum as ETR measures it. Now this brings us to the four star security firms, that is those that hit the top 10 in both net score on the left hand side and market presence on the right hand side. So it's Microsoft, Palo Alto, CrowdStrike, Okta, still there even not accounting for a Auth 0, just Okta on its own. If you put in Auth 0, it's, it's even stronger. Adding then in Fortinet and Zscaler. So Microsoft, Palo Alto, CrowdStrike, Okta, Fortinet, and Zscaler. And as we've mentioned since January, only Fortinet has shown an increase in net score since, since that time, again, since the January survey. Now again, this talks to the compression in spending. Now one of the big themes we hear constantly in cybersecurity is the market is overcrowded. Everybody talks about that, me included. The implication there, is there's a lot of room for consolidation and that consolidation can come in the form of M&A, or it can come in the form of people consolidating onto a single platform, and retiring some other vendors, and getting rid of duplicate vendors. We're hearing that as a big theme as well. Now, as we saw in the previous, previous chart, this is a very crowded market and we've seen lots of consolidation in 2022, in the form of M&A. Literally hundreds of M&A deals, with some of the largest companies going private. SailPoint, KnowBe4, Barracuda, Mandiant, Fedora, these are multi billion dollar acquisitions, or at least billion dollars and up, and many of them multi-billion, for these companies, and hundreds more acquisitions in the cyberspace, now less you think the pond is overfished, here's a chart from ETR of emerging tech companies in the cyber security industry. This data comes from ETR's Emerging Technologies Survey, ETS, which is this diamond in a rough that I found a couple quarters ago, and it's ripe with companies that are candidates for M&A. Many would've liked, many of these companies would've liked to, gotten to the public markets during the pandemic, but they, you know, couldn't get there. They weren't ready. So the graph, you know, similar to the previous one, but different, it shows net sentiment on the vertical axis and that's a measurement of, of, of intent to adopt against a mind share on the X axis, which measures, measures the awareness of the vendor in the community. So this is specifically a survey that ETR goes out and, and, and fields only to track those emerging tech companies that are private companies. Now, some of the standouts in Mindshare, are OneTrust, BeyondTrust, Tanium and Endpoint, Net Scope, which we've talked about in previous Breaking Analysis. 1Password, which has been acquisitive on its own. In identity, the managed security service provider, Arctic Wolf Network, a company we've also covered, we've had their CEO on. We've talked about MSSPs as a real trend, particularly in small and medium sized business, we'll come back to that, Sneek, you know, kind of high flyer in both app security and containers, and you can just see the number of companies in the space this huge and it just keeps growing. Now, just to make it a bit easier on the eyes we filtered the data on these companies with with those, and isolated on those with more than a hundred responses only within the survey. And that's what we show here. Some of the names that we just mentioned are a bit easier to see, but these are the ones that really stand out in ERT, ETS, survey of private companies, OneTrust, BeyondTrust, Taniam, Netscope, which is in Cloud, 1Password, Arctic Wolf, Sneek, BitSight, SecurityScorecard, HackerOne, Code42, and Exabeam, and Sim. All of these hit the ETS survey with more than a hundred responses by, by the IT practitioners. Okay, so these firms, you know, maybe they do some M&A on their own. We've seen that with Sneek, as I said, with 1Password has been inquisitive, as have others. Now these companies with the larger footprint, these private companies, will likely be candidate for both buying companies and eventually going public when the markets settle down a bit. So again, no shortage of players to affect consolidation, both buyers and sellers. Okay, so let's finish with some key questions that we're watching. CrowdStrike in particular on its earnings calls cited softness from smaller buyers. Is that because these smaller buyers have stopped adopting? If so, are they more at risk, or are they tactically moving toward the easy button, aka, Microsoft's good enough approach. What does that mean for the market if smaller company cohorts continue to soften? How about MSSPs? Will companies continue to outsource, or pause on on that, as well as try to free up, to try to free up some budget? Adam Celiski at Reinvent last week said, "If you want to save money the Cloud's the best place to do it." Is the cloud the best place to save money in cyber? Well, it would seem that way from the standpoint of controlling budgets with lots of, lots of optionality. You could dial up and dial down services, you know, or does the Cloud add another layer of complexity that has to be understood and managed by Devs, for example? Now, consolidation should favor the likes of Palo Alto and CrowdStrike, cause they're platform players, and some of the larger players as well, like Cisco, how about IBM and of course Microsoft. Will that happen? And how will economic uncertainty impact the risk equation, a particular concern is increase of tax on vulnerable sectors of the population, like the elderly. How will companies and governments protect them from scams? And finally, how many cybersecurity companies can actually remain independent in the slingshot economy? In so many ways the market is still strong, it's just that expectations got ahead of themselves, and now as earnings forecast come, come, come down and come down to earth, it's going to basically come down to who can execute, generate cash, and keep enough runway to get through the knothole. And the one certainty is nobody really knows how tight that knothole really is. All right, let's call it a wrap. Next week we dive deeper into Palo Alto Networks, and take a look at how and why that company has held up so well and what to expect at Ignite, Palo Alto's big user conference coming up later this month in Las Vegas. We'll be there with theCube. Okay, many thanks to Alex Myerson on production and manages the podcast, Ken Schiffman as well, as our newest edition to our Boston studio. Great to have you Ken. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Silicon Angle. He does some great editing for us. Thank you to all. Remember these episodes are all available as podcasts. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibond.com and siliconangle.com, or you can email me directly David.vellante@siliconangle.com or DM me @DVellante, or comment on our LinkedIn posts. Please do checkout etr.ai, they got the best survey data in the enterprise tech business. This is Dave Vellante for theCube Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis. (upbeat music)

>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube at ETR. This is "Breaking Analysis" with Dave Vellante. >> The reverse momentum in tech stocks caused by rising interest rates, less attractive discounted cash flow models, and more tepid forward guidance, can be easily measured by public market valuations. And while there's lots of discussion about the impact on private companies and cash runway and 409A valuations, measuring the performance of non-public companies isn't as easy. IPOs have dried up and public statements by private companies, of course, they accentuate the good and they kind of hide the bad. Real data, unless you're an insider, is hard to find. Hello and welcome to this week's "Wikibon Cube Insights" powered by ETR. In this "Breaking Analysis", we unlock some of the secrets that non-public, emerging tech companies may or may not be sharing. And we do this by introducing you to a capability from ETR that we've not exposed you to over the past couple of years, it's called the Emerging Technologies Survey, and it is packed with sentiment data and performance data based on surveys of more than a thousand CIOs and IT buyers covering more than 400 companies. And we've invited back our colleague, Erik Bradley of ETR to help explain the survey and the data that we're going to cover today. Erik, this survey is something that I've not personally spent much time on, but I'm blown away at the data. It's really unique and detailed. First of all, welcome. Good to see you again. >> Great to see you too, Dave, and I'm really happy to be talking about the ETS or the Emerging Technology Survey. Even our own clients of constituents probably don't spend as much time in here as they should. >> Yeah, because there's so much in the mainstream, but let's pull up a slide to bring out the survey composition. Tell us about the study. How often do you run it? What's the background and the methodology? >> Yeah, you were just spot on the way you were talking about the private tech companies out there. So what we did is we decided to take all the vendors that we track that are not yet public and move 'em over to the ETS. And there isn't a lot of information out there. If you're not in Silicon (indistinct), you're not going to get this stuff. So PitchBook and Tech Crunch are two out there that gives some data on these guys. But what we really wanted to do was go out to our community. We have 6,000, ITDMs in our community. We wanted to ask them, "Are you aware of these companies? And if so, are you allocating any resources to them? Are you planning to evaluate them," and really just kind of figure out what we can do. So this particular survey, as you can see, 1000 plus responses, over 450 vendors that we track. And essentially what we're trying to do here is talk about your evaluation and awareness of these companies and also your utilization. And also if you're not utilizing 'em, then we can also figure out your sales conversion or churn. So this is interesting, not only for the ITDMs themselves to figure out what their peers are evaluating and what they should put in POCs against the big guys when contracts come up. But it's also really interesting for the tech vendors themselves to see how they're performing. >> And you can see 2/3 of the respondents are director level of above. You got 28% is C-suite. There is of course a North America bias, 70, 75% is North America. But these smaller companies, you know, that's when they start doing business. So, okay. We're going to do a couple of things here today. First, we're going to give you the big picture across the sectors that ETR covers within the ETS survey. And then we're going to look at the high and low sentiment for the larger private companies. And then we're going to do the same for the smaller private companies, the ones that don't have as much mindshare. And then I'm going to put those two groups together and we're going to look at two dimensions, actually three dimensions, which companies are being evaluated the most. Second, companies are getting the most usage and adoption of their offerings. And then third, which companies are seeing the highest churn rates, which of course is a silent killer of companies. And then finally, we're going to look at the sentiment and mindshare for two key areas that we like to cover often here on "Breaking Analysis", security and data. And data comprises database, including data warehousing, and then big data analytics is the second part of data. And then machine learning and AI is the third section within data that we're going to look at. Now, one other thing before we get into it, ETR very often will include open source offerings in the mix, even though they're not companies like TensorFlow or Kubernetes, for example. And we'll call that out during this discussion. The reason this is done is for context, because everyone is using open source. It is the heart of innovation and many business models are super glued to an open source offering, like take MariaDB, for example. There's the foundation and then there's with the open source code and then there, of course, the company that sells services around the offering. Okay, so let's first look at the highest and lowest sentiment among these private firms, the ones that have the highest mindshare. So they're naturally going to be somewhat larger. And we do this on two dimensions, sentiment on the vertical axis and mindshare on the horizontal axis and note the open source tool, see Kubernetes, Postgres, Kafka, TensorFlow, Jenkins, Grafana, et cetera. So Erik, please explain what we're looking at here, how it's derived and what the data tells us. >> Certainly, so there is a lot here, so we're going to break it down first of all by explaining just what mindshare and net sentiment is. You explain the axis. We have so many evaluation metrics, but we need to aggregate them into one so that way we can rank against each other. Net sentiment is really the aggregation of all the positive and subtracting out the negative. So the net sentiment is a very quick way of looking at where these companies stand versus their peers in their sectors and sub sectors. Mindshare is basically the awareness of them, which is good for very early stage companies. And you'll see some names on here that are obviously been around for a very long time. And they're clearly be the bigger on the axis on the outside. Kubernetes, for instance, as you mentioned, is open source. This de facto standard for all container orchestration, and it should be that far up into the right, because that's what everyone's using. In fact, the open source leaders are so prevalent in the emerging technology survey that we break them out later in our analysis, 'cause it's really not fair to include them and compare them to the actual companies that are providing the support and the security around that open source technology. But no survey, no analysis, no research would be complete without including these open source tech. So what we're looking at here, if I can just get away from the open source names, we see other things like Databricks and OneTrust . They're repeating as top net sentiment performers here. And then also the design vendors. People don't spend a lot of time on 'em, but Miro and Figma. This is their third survey in a row where they're just dominating that sentiment overall. And Adobe should probably take note of that because they're really coming after them. But Databricks, we all know probably would've been a public company by now if the market hadn't turned, but you can see just how dominant they are in a survey of nothing but private companies. And we'll see that again when we talk about the database later. >> And I'll just add, so you see automation anywhere on there, the big UiPath competitor company that was not able to get to the public markets. They've been trying. Snyk, Peter McKay's company, they've raised a bunch of money, big security player. They're doing some really interesting things in developer security, helping developers secure the data flow, H2O.ai, Dataiku AI company. We saw them at the Snowflake Summit. Redis Labs, Netskope and security. So a lot of names that we know that ultimately we think are probably going to be hitting the public market. Okay, here's the same view for private companies with less mindshare, Erik. Take us through this one. >> On the previous slide too real quickly, I wanted to pull that security scorecard and we'll get back into it. But this is a newcomer, that I couldn't believe how strong their data was, but we'll bring that up in a second. Now, when we go to the ones of lower mindshare, it's interesting to talk about open source, right? Kubernetes was all the way on the top right. Everyone uses containers. Here we see Istio up there. Not everyone is using service mesh as much. And that's why Istio is in the smaller breakout. But still when you talk about net sentiment, it's about the leader, it's the highest one there is. So really interesting to point out. Then we see other names like Collibra in the data side really performing well. And again, as always security, very well represented here. We have Aqua, Wiz, Armis, which is a standout in this survey this time around. They do IoT security. I hadn't even heard of them until I started digging into the data here. And I couldn't believe how well they were doing. And then of course you have AnyScale, which is doing a second best in this and the best name in the survey Hugging Face, which is a machine learning AI tool. Also doing really well on a net sentiment, but they're not as far along on that access of mindshare just yet. So these are again, emerging companies that might not be as well represented in the enterprise as they will be in a couple of years. >> Hugging Face sounds like something you do with your two year old. Like you said, you see high performers, AnyScale do machine learning and you mentioned them. They came out of Berkeley. Collibra Governance, InfluxData is on there. InfluxDB's a time series database. And yeah, of course, Alex, if you bring that back up, you get a big group of red dots, right? That's the bad zone, I guess, which Sisense does vis, Yellowbrick Data is a NPP database. How should we interpret the red dots, Erik? I mean, is it necessarily a bad thing? Could it be misinterpreted? What's your take on that? >> Sure, well, let me just explain the definition of it first from a data science perspective, right? We're a data company first. So the gray dots that you're seeing that aren't named, that's the mean that's the average. So in order for you to be on this chart, you have to be at least one standard deviation above or below that average. So that gray is where we're saying, "Hey, this is where the lump of average comes in. This is where everyone normally stands." So you either have to be an outperformer or an underperformer to even show up in this analysis. So by definition, yes, the red dots are bad. You're at least one standard deviation below the average of your peers. It's not where you want to be. And if you're on the lower left, not only are you not performing well from a utilization or an actual usage rate, but people don't even know who you are. So that's a problem, obviously. And the VCs and the PEs out there that are backing these companies, they're the ones who mostly are interested in this data. >> Yeah. Oh, that's great explanation. Thank you for that. No, nice benchmarking there and yeah, you don't want to be in the red. All right, let's get into the next segment here. Here going to look at evaluation rates, adoption and the all important churn. First new evaluations. Let's bring up that slide. And Erik, take us through this. >> So essentially I just want to explain what evaluation means is that people will cite that they either plan to evaluate the company or they're currently evaluating. So that means we're aware of 'em and we are choosing to do a POC of them. And then we'll see later how that turns into utilization, which is what a company wants to see, awareness, evaluation, and then actually utilizing them. That's sort of the life cycle for these emerging companies. So what we're seeing here, again, with very high evaluation rates. H2O, we mentioned. SecurityScorecard jumped up again. Chargebee, Snyk, Salt Security, Armis. A lot of security names are up here, Aqua, Netskope, which God has been around forever. I still can't believe it's in an Emerging Technology Survey But so many of these names fall in data and security again, which is why we decided to pick those out Dave. And on the lower side, Vena, Acton, those unfortunately took the dubious award of the lowest evaluations in our survey, but I prefer to focus on the positive. So SecurityScorecard, again, real standout in this one, they're in a security assessment space, basically. They'll come in and assess for you how your security hygiene is. And it's an area of a real interest right now amongst our ITDM community. >> Yeah, I mean, I think those, and then Arctic Wolf is up there too. They're doing managed services. You had mentioned Netskope. Yeah, okay. All right, let's look at now adoption. These are the companies whose offerings are being used the most and are above that standard deviation in the green. Take us through this, Erik. >> Sure, yet again, what we're looking at is, okay, we went from awareness, we went to evaluation. Now it's about utilization, which means a survey respondent's going to state "Yes, we evaluated and we plan to utilize it" or "It's already in our enterprise and we're actually allocating further resources to it." Not surprising, again, a lot of open source, the reason why, it's free. So it's really easy to grow your utilization on something that's free. But as you and I both know, as Red Hat proved, there's a lot of money to be made once the open source is adopted, right? You need the governance, you need the security, you need the support wrapped around it. So here we're seeing Kubernetes, Postgres, Apache Kafka, Jenkins, Grafana. These are all open source based names. But if we're looking at names that are non open source, we're going to see Databricks, Automation Anywhere, Rubrik all have the highest mindshare. So these are the names, not surprisingly, all names that probably should have been public by now. Everyone's expecting an IPO imminently. These are the names that have the highest mindshare. If we talk about the highest utilization rates, again, Miro and Figma pop up, and I know they're not household names, but they are just dominant in this survey. These are applications that are meant for design software and, again, they're going after an Autodesk or a CAD or Adobe type of thing. It is just dominant how high the utilization rates are here, which again is something Adobe should be paying attention to. And then you'll see a little bit lower, but also interesting, we see Collibra again, we see Hugging Face again. And these are names that are obviously in the data governance, ML, AI side. So we're seeing a ton of data, a ton of security and Rubrik was interesting in this one, too, high utilization and high mindshare. We know how pervasive they are in the enterprise already. >> Erik, Alex, keep that up for a second, if you would. So yeah, you mentioned Rubrik. Cohesity's not on there. They're sort of the big one. We're going to talk about them in a moment. Puppet is interesting to me because you remember the early days of that sort of space, you had Puppet and Chef and then you had Ansible. Red Hat bought Ansible and then Ansible really took off. So it's interesting to see Puppet on there as well. Okay. So now let's look at the churn because this one is where you don't want to be. It's, of course, all red 'cause churn is bad. Take us through this, Erik. >> Yeah, definitely don't want to be here and I don't love to dwell on the negative. So we won't spend as much time. But to your point, there's one thing I want to point out that think it's important. So you see Rubrik in the same spot, but Rubrik has so many citations in our survey that it actually would make sense that they're both being high utilization and churn just because they're so well represented. They have such a high overall representation in our survey. And the reason I call that out is Cohesity. Cohesity has an extremely high churn rate here about 17% and unlike Rubrik, they were not on the utilization side. So Rubrik is seeing both, Cohesity is not. It's not being utilized, but it's seeing a high churn. So that's the way you can look at this data and say, "Hm." Same thing with Puppet. You noticed that it was on the other slide. It's also on this one. So basically what it means is a lot of people are giving Puppet a shot, but it's starting to churn, which means it's not as sticky as we would like. One that was surprising on here for me was Tanium. It's kind of jumbled in there. It's hard to see in the middle, but Tanium, I was very surprised to see as high of a churn because what I do hear from our end user community is that people that use it, like it. It really kind of spreads into not only vulnerability management, but also that endpoint detection and response side. So I was surprised by that one, mostly to see Tanium in here. Mural, again, was another one of those application design softwares that's seeing a very high churn as well. >> So you're saying if you're in both... Alex, bring that back up if you would. So if you're in both like MariaDB is for example, I think, yeah, they're in both. They're both green in the previous one and red here, that's not as bad. You mentioned Rubrik is going to be in both. Cohesity is a bit of a concern. Cohesity just brought on Sanjay Poonen. So this could be a go to market issue, right? I mean, 'cause Cohesity has got a great product and they got really happy customers. So they're just maybe having to figure out, okay, what's the right ideal customer profile and Sanjay Poonen, I guarantee, is going to have that company cranking. I mean they had been doing very well on the surveys and had fallen off of a bit. The other interesting things wondering the previous survey I saw Cvent, which is an event platform. My only reason I pay attention to that is 'cause we actually have an event platform. We don't sell it separately. We bundle it as part of our offerings. And you see Hopin on here. Hopin raised a billion dollars during the pandemic. And we were like, "Wow, that's going to blow up." And so you see Hopin on the churn and you didn't see 'em in the previous chart, but that's sort of interesting. Like you said, let's not kind of dwell on the negative, but you really don't. You know, churn is a real big concern. Okay, now we're going to drill down into two sectors, security and data. Where data comprises three areas, database and data warehousing, machine learning and AI and big data analytics. So first let's take a look at the security sector. Now this is interesting because not only is it a sector drill down, but also gives an indicator of how much money the firm has raised, which is the size of that bubble. And to tell us if a company is punching above its weight and efficiently using its venture capital. Erik, take us through this slide. Explain the dots, the size of the dots. Set this up please. >> Yeah. So again, the axis is still the same, net sentiment and mindshare, but what we've done this time is we've taken publicly available information on how much capital company is raised and that'll be the size of the circle you see around the name. And then whether it's green or red is basically saying relative to the amount of money they've raised, how are they doing in our data? So when you see a Netskope, which has been around forever, raised a lot of money, that's why you're going to see them more leading towards red, 'cause it's just been around forever and kind of would expect it. Versus a name like SecurityScorecard, which is only raised a little bit of money and it's actually performing just as well, if not better than a name, like a Netskope. OneTrust doing absolutely incredible right now. BeyondTrust. We've seen the issues with Okta, right. So those are two names that play in that space that obviously are probably getting some looks about what's going on right now. Wiz, we've all heard about right? So raised a ton of money. It's doing well on net sentiment, but the mindshare isn't as well as you'd want, which is why you're going to see a little bit of that red versus a name like Aqua, which is doing container and application security. And hasn't raised as much money, but is really neck and neck with a name like Wiz. So that is why on a relative basis, you'll see that more green. As we all know, information security is never going away. But as we'll get to later in the program, Dave, I'm not sure in this current market environment, if people are as willing to do POCs and switch away from their security provider, right. There's a little bit of tepidness out there, a little trepidation. So right now we're seeing overall a slight pause, a slight cooling in overall evaluations on the security side versus historical levels a year ago. >> Now let's stay on here for a second. So a couple things I want to point out. So it's interesting. Now Snyk has raised over, I think $800 million but you can see them, they're high on the vertical and the horizontal, but now compare that to Lacework. It's hard to see, but they're kind of buried in the middle there. That's the biggest dot in this whole thing. I think I'm interpreting this correctly. They've raised over a billion dollars. It's a Mike Speiser company. He was the founding investor in Snowflake. So people watch that very closely, but that's an example of where they're not punching above their weight. They recently had a layoff and they got to fine tune things, but I'm still confident they they're going to do well. 'Cause they're approaching security as a data problem, which is probably people having trouble getting their arms around that. And then again, I see Arctic Wolf. They're not red, they're not green, but they've raised fair amount of money, but it's showing up to the right and decent level there. And a couple of the other ones that you mentioned, Netskope. Yeah, they've raised a lot of money, but they're actually performing where you want. What you don't want is where Lacework is, right. They've got some work to do to really take advantage of the money that they raised last November and prior to that. >> Yeah, if you're seeing that more neutral color, like you're calling out with an Arctic Wolf, like that means relative to their peers, this is where they should be. It's when you're seeing that red on a Lacework where we all know, wow, you raised a ton of money and your mindshare isn't where it should be. Your net sentiment is not where it should be comparatively. And then you see these great standouts, like Salt Security and SecurityScorecard and Abnormal. You know they haven't raised that much money yet, but their net sentiment's higher and their mindshare's doing well. So those basically in a nutshell, if you're a PE or a VC and you see a small green circle, then you're doing well, then it means you made a good investment. >> Some of these guys, I don't know, but you see these small green circles. Those are the ones you want to start digging into and maybe help them catch a wave. Okay, let's get into the data discussion. And again, three areas, database slash data warehousing, big data analytics and ML AI. First, we're going to look at the database sector. So Alex, thank you for bringing that up. Alright, take us through this, Erik. Actually, let me just say Postgres SQL. I got to ask you about this. It shows some funding, but that actually could be a mix of EDB, the company that commercializes Postgres and Postgres the open source database, which is a transaction system and kind of an open source Oracle. You see MariaDB is a database, but open source database. But the companies they've raised over $200 million and they filed an S-4. So Erik looks like this might be a little bit of mashup of companies and open source products. Help us understand this. >> Yeah, it's tough when you start dealing with the open source side and I'll be honest with you, there is a little bit of a mashup here. There are certain names here that are a hundred percent for profit companies. And then there are others that are obviously open source based like Redis is open source, but Redis Labs is the one trying to monetize the support around it. So you're a hundred percent accurate on this slide. I think one of the things here that's important to note though, is just how important open source is to data. If you're going to be going to any of these areas, it's going to be open source based to begin with. And Neo4j is one I want to call out here. It's not one everyone's familiar with, but it's basically geographical charting database, which is a name that we're seeing on a net sentiment side actually really, really high. When you think about it's the third overall net sentiment for a niche database play. It's not as big on the mindshare 'cause it's use cases aren't as often, but third biggest play on net sentiment. I found really interesting on this slide. >> And again, so MariaDB, as I said, they filed an S-4 I think $50 million in revenue, that might even be ARR. So they're not huge, but they're getting there. And by the way, MariaDB, if you don't know, was the company that was formed the day that Oracle bought Sun in which they got MySQL and MariaDB has done a really good job of replacing a lot of MySQL instances. Oracle has responded with MySQL HeatWave, which was kind of the Oracle version of MySQL. So there's some interesting battles going on there. If you think about the LAMP stack, the M in the LAMP stack was MySQL. And so now it's all MariaDB replacing that MySQL for a large part. And then you see again, the red, you know, you got to have some concerns about there. Aerospike's been around for a long time. SingleStore changed their name a couple years ago, last year. Yellowbrick Data, Fire Bolt was kind of going after Snowflake for a while, but yeah, you want to get out of that red zone. So they got some work to do. >> And Dave, real quick for the people that aren't aware, I just want to let them know that we can cut this data with the public company data as well. So we can cross over this with that because some of these names are competing with the larger public company names as well. So we can go ahead and cross reference like a MariaDB with a Mongo, for instance, or of something of that nature. So it's not in this slide, but at another point we can certainly explain on a relative basis how these private names are doing compared to the other ones as well. >> All right, let's take a quick look at analytics. Alex, bring that up if you would. Go ahead, Erik. >> Yeah, I mean, essentially here, I can't see it on my screen, my apologies. I just kind of went to blank on that. So gimme one second to catch up. >> So I could set it up while you're doing that. You got Grafana up and to the right. I mean, this is huge right. >> Got it thank you. I lost my screen there for a second. Yep. Again, open source name Grafana, absolutely up and to the right. But as we know, Grafana Labs is actually picking up a lot of speed based on Grafana, of course. And I think we might actually hear some noise from them coming this year. The names that are actually a little bit more disappointing than I want to call out are names like ThoughtSpot. It's been around forever. Their mindshare of course is second best here but based on the amount of time they've been around and the amount of money they've raised, it's not actually outperforming the way it should be. We're seeing Moogsoft obviously make some waves. That's very high net sentiment for that company. It's, you know, what, third, fourth position overall in this entire area, Another name like Fivetran, Matillion is doing well. Fivetran, even though it's got a high net sentiment, again, it's raised so much money that we would've expected a little bit more at this point. I know you know this space extremely well, but basically what we're looking at here and to the bottom left, you're going to see some names with a lot of red, large circles that really just aren't performing that well. InfluxData, however, second highest net sentiment. And it's really pretty early on in this stage and the feedback we're getting on this name is the use cases are great, the efficacy's great. And I think it's one to watch out for. >> InfluxData, time series database. The other interesting things I just noticed here, you got Tamer on here, which is that little small green. Those are the ones we were saying before, look for those guys. They might be some of the interesting companies out there and then observe Jeremy Burton's company. They do observability on top of Snowflake, not green, but kind of in that gray. So that's kind of cool. Monte Carlo is another one, they're sort of slightly green. They are doing some really interesting things in data and data mesh. So yeah, okay. So I can spend all day on this stuff, Erik, phenomenal data. I got to get back and really dig in. Let's end with machine learning and AI. Now this chart it's similar in its dimensions, of course, except for the money raised. We're not showing that size of the bubble, but AI is so hot. We wanted to cover that here, Erik, explain this please. Why TensorFlow is highlighted and walk us through this chart. >> Yeah, it's funny yet again, right? Another open source name, TensorFlow being up there. And I just want to explain, we do break out machine learning, AI is its own sector. A lot of this of course really is intertwined with the data side, but it is on its own area. And one of the things I think that's most important here to break out is Databricks. We started to cover Databricks in machine learning, AI. That company has grown into much, much more than that. So I do want to state to you Dave, and also the audience out there that moving forward, we're going to be moving Databricks out of only the MA/AI into other sectors. So we can kind of value them against their peers a little bit better. But in this instance, you could just see how dominant they are in this area. And one thing that's not here, but I do want to point out is that we have the ability to break this down by industry vertical, organization size. And when I break this down into Fortune 500 and Fortune 1000, both Databricks and Tensorflow are even better than you see here. So it's quite interesting to see that the names that are succeeding are also succeeding with the largest organizations in the world. And as we know, large organizations means large budgets. So this is one area that I just thought was really interesting to point out that as we break it down, the data by vertical, these two names still are the outstanding players. >> I just also want to call it H2O.ai. They're getting a lot of buzz in the marketplace and I'm seeing them a lot more. Anaconda, another one. Dataiku consistently popping up. DataRobot is also interesting because all the kerfuffle that's going on there. The Cube guy, Cube alum, Chris Lynch stepped down as executive chairman. All this stuff came out about how the executives were taking money off the table and didn't allow the employees to participate in that money raising deal. So that's pissed a lot of people off. And so they're now going through some kind of uncomfortable things, which is unfortunate because DataRobot, I noticed, we haven't covered them that much in "Breaking Analysis", but I've noticed them oftentimes, Erik, in the surveys doing really well. So you would think that company has a lot of potential. But yeah, it's an important space that we're going to continue to watch. Let me ask you Erik, can you contextualize this from a time series standpoint? I mean, how is this changed over time? >> Yeah, again, not show here, but in the data. I'm sorry, go ahead. >> No, I'm sorry. What I meant, I should have interjected. In other words, you would think in a downturn that these emerging companies would be less interesting to buyers 'cause they're more risky. What have you seen? >> Yeah, and it was interesting before we went live, you and I were having this conversation about "Is the downturn stopping people from evaluating these private companies or not," right. In a larger sense, that's really what we're doing here. How are these private companies doing when it comes down to the actual practitioners? The people with the budget, the people with the decision making. And so what I did is, we have historical data as you know, I went back to the Emerging Technology Survey we did in November of 21, right at the crest right before the market started to really fall and everything kind of started to fall apart there. And what I noticed is on the security side, very much so, we're seeing less evaluations than we were in November 21. So I broke it down. On cloud security, net sentiment went from 21% to 16% from November '21. That's a pretty big drop. And again, that sentiment is our one aggregate metric for overall positivity, meaning utilization and actual evaluation of the name. Again in database, we saw it drop a little bit from 19% to 13%. However, in analytics we actually saw it stay steady. So it's pretty interesting that yes, cloud security and security in general is always going to be important. But right now we're seeing less overall net sentiment in that space. But within analytics, we're seeing steady with growing mindshare. And also to your point earlier in machine learning, AI, we're seeing steady net sentiment and mindshare has grown a whopping 25% to 30%. So despite the downturn, we're seeing more awareness of these companies in analytics and machine learning and a steady, actual utilization of them. I can't say the same in security and database. They're actually shrinking a little bit since the end of last year. >> You know it's interesting, we were on a round table, Erik does these round tables with CISOs and CIOs, and I remember one time you had asked the question, "How do you think about some of these emerging tech companies?" And one of the executives said, "I always include somebody in the bottom left of the Gartner Magic Quadrant in my RFPs. I think he said, "That's how I found," I don't know, it was Zscaler or something like that years before anybody ever knew of them "Because they're going to help me get to the next level." So it's interesting to see Erik in these sectors, how they're holding up in many cases. >> Yeah. It's a very important part for the actual IT practitioners themselves. There's always contracts coming up and you always have to worry about your next round of negotiations. And that's one of the roles these guys play. You have to do a POC when contracts come up, but it's also their job to stay on top of the new technology. You can't fall behind. Like everyone's a software company. Now everyone's a tech company, no matter what you're doing. So these guys have to stay in on top of it. And that's what this ETS can do. You can go in here and look and say, "All right, I'm going to evaluate their technology," and it could be twofold. It might be that you're ready to upgrade your technology and they're actually pushing the envelope or it simply might be I'm using them as a negotiation ploy. So when I go back to the big guy who I have full intentions of writing that contract to, at least I have some negotiation leverage. >> Erik, we got to leave it there. I could spend all day. I'm going to definitely dig into this on my own time. Thank you for introducing this, really appreciate your time today. >> I always enjoy it, Dave and I hope everyone out there has a great holiday weekend. Enjoy the rest of the summer. And, you know, I love to talk data. So anytime you want, just point the camera on me and I'll start talking data. >> You got it. I also want to thank the team at ETR, not only Erik, but Darren Bramen who's a data scientist, really helped prepare this data, the entire team over at ETR. I cannot tell you how much additional data there is. We are just scratching the surface in this "Breaking Analysis". So great job guys. I want to thank Alex Myerson. Who's on production and he manages the podcast. Ken Shifman as well, who's just coming back from VMware Explore. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some great editing for us. Thank you. All of you guys. Remember these episodes, they're all available as podcast, wherever you listen. All you got to do is just search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com. Or you can email me to get in touch david.vellante@siliconangle.com. You can DM me at dvellante or comment on my LinkedIn posts and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for Erik Bradley and The Cube Insights powered by ETR. Thanks for watching. Be well. And we'll see you next time on "Breaking Analysis". (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Cybersecurity stocks have been sending mixed signals as of late, mostly negative like much of tech, but some such as Palo Alto Networks, despite a tough go of it recently have held up better than most tech names. Others like CrowdStrike, had been out performing Broader Tech in March, but then flipped in May. Okta's performance was pretty much tracking along with CrowdStrike for most of the past several months, a little bit below, but then the Okta hack changed the trajectory of that name. Zscaler has crossed the critical billion dollar ARR revenue milestone, and now sees a path to five billion dollars in revenue, but the company stock fell sharply after its last earnings report and has been on a down trend since last November. Meanwhile, CyberArk's recent beat and raise, was encouraging and the stock acted well after its last report. Security remains the number one initiative priority amongst IT organizations and the spending momentum for many high flying cyber names remain strong. So what gives in cyber security? Hello, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we focus on security and will update you on the latest data from ETR to try to make sense out of the market and read into what this all means in both the near and long term, for some of our favorite names in cyber. First, the news. There's always something happening in security news cycles. The big recent news is new President Rodrigo Chavez declared a national emergency in Costa Rica due to the preponderance of Russian cyber attacks on the country's critical infrastructure. Such measures are normally reserved for natural disasters like earthquakes, but this move speaks to the nature of today's cyber threats. Of no surprise is modern superpower warfare even for a depleted power like Russia almost certainly involves cyber warfare as we continue to see in Ukraine. Privately held Arctic Wolf Networks hired Dustin Williams as its new CFO. Williams has taken three companies to IPO, including Nutanix in 2016, a very successful IPO for that company. Whether AWN chooses to pull the trigger this year or will wait until markets are less choppy or obviously remains to be seen. But it's a pretty clear sign the company is headed to IPO at some point. Now, big point of discussion this week at Red Hat Summit in Boston and the prior week at Dell technologies world was security. In the case of Red Hat, securing the digital supply chain was the main theme. And from Dell building, many security features into its storage arrays and cyber resilience services into its as a service offering called Apex. And we're seeing a trend where buyers want to reduce the number of bespoke tools they use if they, in fact can. Here's IDC's Jim Mercer, sharing data from a recent survey they conducted on the topic. Play the clip. >> Interestingly, we did a survey, I think around last August or something. And one of the questions was around where do you want your security, right? Where do you want to get your DevSecOps security from? Do you want to get it from individual vendors, right? Or do you want to get it from like your platforms that you're using and deploying changes in Kubernetes? >> Great question. What did they say? >> The majority of them, they're hoping they can get it built into the platform. That's really what they want-- >> Now, whether that's actually achievable is debatable because you have so much innovation and investment going on from the likes of startups and for instance, lace work or sneak and security companies that you see even trying to build platforms, you've got CrowdStrike, Okta, Zscaler and many others, trying to build security platforms and put it all under their umbrella. Now the last point will hit here is there was a lot of buzz in the news about Okta. The reaction to what was a relatively benign hack was pretty severe and probably overblown, but Okta's stock is paying the price of what is generally considered a blown communications plan versus a technical failure. Remember, identity is not an easy thing to rip and replace and Okta remains a best-of-breed player and leader in the space. So we're going to look at some ETR data later in this segment to try and make sense of the recent action in the market and certain names. Speaking of which let's take a look at how some of the names in cybersecurity have fared relative to some of the indices and relative indicators that we like to look at. Here's a Google finance comparison for a number of stocks and names in the bottom there you can see we plot the hack ETF which tracks security stocks. This is a year to date view. And so we don't show it here but the tech heavy NASDAQ is off around 26% year to date whereas the cyber ETF that we're showing is down 18%, okay. So cyber holding up a little bit better than broader tech as we've reported earlier, was actually much better and still seems to be a gap there, but the data are mixed. You can see Okta is way off relative to its peers. That's a combination of the breach that we talked about but also the run up in the stock since COVID. CrowdStrike was actually faring better but broke this month, we'll see how it's upcoming earnings announcements are received when it announces on June 2nd after the close. Palo Alto in the light blue has done better than most and until recently was holding up quite well. And of course, Sailpoint is another identity specialist, it is kind of off the charts here because it's going private with the acquisition by Thoma Bravo at nearly seven billion dollars. So you see some mixed signals in cyber these past several months and weeks. And so we're trying to understand what that all means. So let's take a look at the survey data and see how spending momentum is holding up. As we've reported IT spending forecast, at the macro level, they've come off their 8% highs from the end of the year, the ETRS December survey, but robust tech spending is still there. It's expected at nearly seven percent and this is amongst 1200 ETR respondents. Here's a picture from the ETR survey of the cybersecurity landscape. That y-axis that's net score or a measure of spending momentum and that horizontal access is overlap. We used to talk about it as a market share which is a measure of pervasiveness in the data set. That dotted red line at 40% indicates an elevated spending momentum level on the vertical axis and we filter the names and limited to only those with a hundred or more responses in the ETR survey. Then the pictures still pretty crowded as you can see. You got lots of companies above the red dotted line, including Microsoft which is up into the right, they're so far off the chart, it's just amazing. But also Palo Alto and Okta, Auth0, which of course is now owned by Okta, Zscaler, CyberArk is making moves. Sailpoint and Cloudflare, they're all above that magic 40% line. Now, you look at Cisco, it shows a very large presence in the horizontal axis in the data set. And it's got pretty respectable momentum and you see Splunk doing okay, no before and tenable just below that 40% line and a lot of names in the very respectable 20% zone. And we've included some legacy names just for context that fall below the zero percent line with a negative net score. And that means a larger proportion, that negative net score means a larger proportion of their customers in the survey are spending less than those that are spending more. Now, typically for these legacy names you're going to have a huge proportion of customers who have flat spending that kind of fat middle and that's why they sort of don't have that highly elevated score, but they're still viable as they get the recurring revenue each year. But the bottom line is that spending remains robust for some of the top names that we've talked about earlier despite their rocky stock performance. Now, let's filter this data a bit more to make it a little bit easier to read. So to do that, we take out Microsoft because they're just so dominant and we cherry pick some names to make the data more consumable and scannable. The other data point we've added is Okta's net score breakdown, the multicolored rows there, that row in the bottom right. Net score, it measures the percent of customers that are adding the platform new, that's the lime green, at 18% for Okta. The forest green is at 42%. That's the percent of customers in the survey that are spending six percent or more. The gray is flat spending. That's 32% for Okta, this past survey. The pink is customers that are spending less, that's three percent. They're spending six percent or worse in the survey, so only three percent for Okta. And the bright red at three percent is decommissioning the platform. You subtract the reds from the greens and you get a net score, well, into the 50s for Okta and you can see. We highlight Okta here because it's a name that we've been following for quite some time and customers have given us really solid feedback on the technology and up until the hack, they're affinity to Okta, but that seems to be continuing. We'll talk more about that. This recent breach to Okta has caused us to take a closer look. And you may recall, we reported with our ETR colleague, Eric Bradley. The breach was announced right in the middle of ETR collecting data in the last survey. And while we did see a noticeable downtick right after the announcement, the exposure of the hack and Okta's net score just after the breach was disclosed, you can see the combination of Okta and Auth0 remains very strong. I asked Eric Bradley this morning what he thought about Okta, and he pointed out that you can't evaluate this company on its price to earnings ratio. But it's forward sales multiple is now below 7X. And while attractive, these high flyers at some point, Eric says, they got to start making a profit. So you going to hold that thought, we'll come back to that. Now, another cut of the ETR data to look at our four star security names here. A while back we developed a methodology to try and cut through the noise of the crowded security sector using the ETR data to evaluate two key metrics; net score and shared N. Net score again is, spending momentum, the latter is an indicator of presence in the data set which is a proxy for market presence. Okay, we assigned those companies that cracked the top 10 in both net score and shared N, we give them four stars, okay, if they make the top 10. This chart here shows the April survey data for those companies with an N that's greater than, equal to a hundred responses. So again, we're filtering on those with a hundred or more responses. The table on the left that you see there, that's sorted by net score, okay. So we're sorting by spending momentum. And then the one on the right is sorted by shared N, so their presence in the data set. Seven companies hit the top 10 for both categories; Palo Alto Network, Splunk, CrowdStrike Okta, Proofpoint, Fortinet and Zscaler. Now, remember, take a look, Okta excludes Auth0, in this little methodology that we came up with. Auth0 didn't make the cuts but it hits the top 10 for net score. So if you add in Auth0's 112 N there that you see on the right. You add that into Okta, we put Okta in the number two spot in the survey on the right most table with the shared N of 354. Only Cisco has a higher presence in the data set. And you can see Cisco in the left lands just below that red dotted line. That's the top 10 in security. So if we were to combine Okta and Auth0 as one, Cisco would make the cut and earn four stars. Now, some other notables are CyberArk, which is just below the red line on the right most chart with an impressive 177 shared N. Again, if you combine Auth0 and Okta, CyberArk makes the four star grade because it's in the top 10 for net score on the left. And Sailpoint is another notable with a net score above 50% and it's got a shared N of 122, which is respectable. So despite the market's choppy waters, we're seeing some positive signs in the survey data for some of the more prominent names that we've been following for the last couple of years. So what does this mean for the markets going forward? As always, when we see these confusing signs we like to reach out to the network and one of the sharpest traders out there is Chip Simonton. We've quoted him before and we like to share some of his insights. And so we're going to highlight some of that here. So technically, almost every good tech stock is oversold. And as such, he suggested we might see a bounce here. We certainly are seeing that on this Friday, the 13th. But the right call tactically has been to sell into the rally these past several months, so we'll see what happens on Monday. The key issue with the name like Okta and some other momentum names like CrowdStrike and Zscaler is that when money comes back into tech, it's likely going to go to the FAANG stocks, the Facebook, Apple, Amazon, Netflix, Google, and of course, you put Microsoft in there as well. And we'll see about Amazon, by the way, it's kind of out of favor right now, as everyone's focused on the retail side of the business meanwhile it's cloud business is booming and that's where all the profit is. We think that should be the real focus for Amazon. But the point is, for these momentum names in cybersecurity that don't make money, they face real headwinds, as growth is slowing overall and interest rates rise, that makes the net present value of these investments much less attractive. We've talked about that before. But longer term, we agree with Chip Simonton that these are excellent companies and they will weather the storm and we think they're going to lead their respective markets. And in cyber, we would expect continued M&A activity, which could act as a booster shot in the arms of these names. Now in 2019, we saw the ETR data, it pointed to CrowdStrike, Zscaler, Okta and others in the security space. Some of those names that really looked to us like they were moving forward and the pandemic just created a surge in these names and admittedly they got out over their skis. But the data suggests that these leading companies have continued momentum and the potential for stay in power. Unlike the SolarWinds hack, it seems at this point anyway that Okta will recover in the market. For the reasons that we cited, investors, they might stay away for some time but longer term, there's a shift in CSO security strategies that appear to be permanent. They're really valuing cloud-based modern platforms, these platforms will likely continue to gain share and carry their momentum forward. Okay, that's it for now, thanks to Stephanie Chan, who helps with the background research and with social, Kristen Martin and Cheryl Knight help get the word out and do some great work as well. Alex Morrison is on production and handles all of our podcast. Alex, thank you. And Rob Hof is our Editor in Chief at SiliconANGLE. Remember, all these episodes, they're available as podcast, you can pop in the headphones and listen, just search "Breaking Analysis Podcast." I publish each week on wikibon.com and SiliconANGLE.com. Don't forget to check out etr.ai, best in the business for real customer data. It's an awesome platform. You can reach me at dave.vellante@siliconangle.com or @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for the CUBEinsights powered by ETR. Thanks for watching. And we'll see you next time. (bright upbeat music)

(upbeat music) >> Hello, everyone and welcome to theCUBE presentation of the AWS startup showcase, data as code. This is season two, episode two of the ongoing series covering the exciting startups from the AWS ecosystem. Here we're talking about operationalizing the data lake. I'm your host, John Furrier, and my guest here is Mark Lyons, VP of product management at Dremio. Great to see you, Mark. Thanks for coming on. >> Hey John, nice to see you again. Thanks for having me. >> Yeah, we were talking before we came on camera here on this showcase we're going to spend the next 20 minutes talking about the new architectures of data lakes and how they expand and scale. But we kind of were reminiscing by the old big data days, and how this really changed. There's a lot of hangovers from (mumbles) kind of fall through, Cloud took over, now we're in a new era and the theme here is data as code. Really highlights that data is now in the developer cycles of operations. So infrastructure is code-led DevOps movement for Cloud programmable infrastructure. Now you got data as code, which is really accelerating DataOps, MLOps, DatabaseOps, and more developer focus. So this is a big part of it. You guys at Dremio have a Cloud platform, query engine and a data tier innovation. Take us through the positioning of Dremio right now. What's the current state of the offering? >> Yeah, sure, so happy to, and thanks for kind of introing into the space that we're headed. I think the world is changing, and databases are changing. So today, Dremio is a full database platform, data lakehouse platform on the Cloud. So we're all about keeping your data in open formats in your Cloud storage, but bringing that full functionality that you would want to access the data, as well as manage the data. All the functionality folks would be used to from NC SQL compatibility, inserts updates, deletes on that data, keeping that data in Parquet files in the iceberg table format, another level of abstraction so that people can access the data in a very efficient way. And going even further than that, what we announced with Dremio Arctic which is in public preview on our Cloud platform, is a full get like experience for the data. So just like you said, data as code, right? We went through waves and source code and infrastructure as code. And now we can treat the data as code, which is amazing. You can have development branches, you can have staging branches, ETL branches, which are separate from production. Developers can do experiments. You can make changes, you can test those changes before you merge back to production and let the consumers see that data. Lots of innovation on the platform, super fast velocity of delivery, and lots of customers adopting it in just in the first month here since we announced Dremio Cloud generally available where the adoption's been amazing. >> Yeah, and I think we're going to dig into the a lot of the architecture, but I want to highlight your point you made about the branching off and taking a branch of Git. This is what developers do, right? The developers use GitHub, Git, they bake branches from code. They build on top of other code. That's open source. This is what's been around for generations. Now for the first time we're seeing data sets being taken out of production to be worked on and coded and tested and even doing look backs or even forward looking analysis. This is data being programmed. This is data as code. This is really, you couldn't get any closer to data as code. >> Yeah. It's all done through metadata by the way. So there's no actual copying of these data sets 'cause in these big data systems, Cloud data lakes and stuff, and these tables are billions of records, trillions of records, super wide, hundreds of columns wide, thousands of columns wide. You have to do this all through metadata operations so you can control what version of the data basically a individual's working with and which version of the data the production systems are seeing because these data sets are too big. You don't want to be moving them. You can't be moving them. You can't be copying them. It's all metadata and manifest files and pointers to basically keep track of what's going on. >> I think this is the most important trend we've seen in a long time, because if you think about what Agile did for developers, okay, speed, DevOps, Cloud scale, now you've got agility in the data side of it where you're basically breaking down the old proprietary, old ways of doing data warehousing, but not killing the functionality of what data warehouses did. Just doing more volume data warehouses where proprietary, not open. They were different use cases. They were single application developers when used data warehouse query, not a lot of volume. But as you get volume, these things are inadequate. And now you've got the new open Agile. Is this Agile data engineering at play here? >> Yeah, I think it totally is. It's bringing it as far forward in as possible. We're talking about making the data engineering process easier and more productive for the data engineer, which ultimately makes the consumers of that data much happier as well as way more experiments can happen. Way more use cases can be tried. If it's not a burden and it doesn't require building a whole new pipeline and defining a schema and adding columns and data types and all this stuff, you can do a lot more with your data much faster. So it's really going to be super impactful to all these businesses out there trying to be data driven, especially when you're looking at data as a code and branching, a branch off, you can de-risk your changes. You're not worried about messing up the production system, messing up that data, having it seen by end user. Some businesses data is their business so that data would be going all the way to a consumer, a third party. And then it gets really scary. There's a lot of risk if you show the wrong credit score to a consumer or you do something like that. So it's really de-risking... >> Even updating machine learning algorithms. So for instance, if the data sets change, you can always be iterating on things like machine learning or learning algorithms. This is kind of new. This is awesome, right? >> I think it's going to change the world because this stuff was so painful to do. The data sets had gotten so much bigger as you know, but we were still doing it in the old way, which was typically moving data around for everyone. It was copying data down, sampling data, moving data, and now we're just basically saying, hey, don't do that anymore. We got to stop moving the data. It doesn't make any sense. >> So I got to ask you Mark, data lakes are growing in popularity. I was originally down on data lakes. I called them data swamps. I didn't think they were going to be as popular because at that time, distributed file systems like Hadoop, and object store in the Cloud were really cool. So what happened between that promise of distributed file systems and object store and data lakes? What made data lakes popular? What made that work in your opinion? >> Yeah, it really comes down to the metadata, which I already mentioned once. But we went through these waves. John you saw we did the EDWs to the data lakes and then the Cloud data warehouses. I think we're at the start of a cycle back to the data lake. And it's because the data lakes this time around with the Apache iceberg table format, with project (mumbles) and what Dremio's working on around metadata, these things aren't going to become data swamps anymore. They're actually going to be functional systems that do inserts updates into leads. You can see all the commits. You can time travel them. And all the files are actually managed and optimized so you have to partition the data. You have to merge small files into larger files. Oh, by the way, this is stuff that all the warehouses have done behind the scenes and all the housekeeping they do, but people weren't really aware of it. And the data lakes the first time around didn't solve all these problems so that those files landing in a distributed file system does become a mess. If you just land JSON, Avro or Parquet files, CSV files into the HDFS, or in S3 compatible, object store doesn't matter, if you're just parking files and you're going to deal with it as schema and read instead of schema and write, you're going to have a mess. If you don't know which tool changed the files, which user deleted a file, updated a file, you will end up with a mess really quickly. So to take care of that, you have to put a table format so everyone's looking at Apache iceberg or the data bricks Delta format, which is an interesting conversation similar to the Parquet and org file format that we saw play out. And then you track the metadata. So you have those manifest files. You know which files change when, which engine, which commit. And you can actually make a functional system that's not going to become a swamp. >> Another trend that's extending on beyond the data lake is other data sources, right? So you have a lot of other data, not just in data lakes so you have to kind of work with that. How do you guys answer the question around some of the mission critical BI dashboards out there on the latency side? A lot of people have been complaining that these mission critical BI dashboards aren't getting the kind of performance as they add more data sources and they try to do more. >> Yeah, that's a great question. Dremio does actually a bunch of interesting things to bring the performance of these systems up because at the end of the day, people want to access their data really quickly. They want the response times of these dashboards to be interactive. Otherwise the data's not interesting if it takes too long to get it. To answer a question, yeah, a couple of things. First of all, from a data source's side, Dremio is very proficient with our Parquet files in an object store, like we just talked about, but it also can access data in other relational systems. So whether that's a Postgres system, whether that's a Teradata system or an Oracle system. That's really useful if you have dimensional data, customer data, not the largest data set in the world, not the fastest moving data set in the world, but you don't want to move it. We can query that where it resides. Bringing in new sources is definitely, we all know that's a key to getting better insights. It's in your data, is joining sources together. And then from a query speed standpoint, there's a lot of things going on here. Everything from kind of Apache, the Apache Avro project, which is in memory format of Parquet and not kind of serialize and de-serialize the data back and forth. As well as what we call reflection, which is basically a re-indexing or pre-computing of the data, but we leave it in Parquet format, in a open format in the customer's account so that you can have aggregates and other things that are really popular in these dashboards pre-computed. So millisecond response, lightning fast, like tricks that a warehouse would do that the warehouses have been doing forever. Right? >> Yeah, more deals coming in. And obviously the architecture we'll get into that now has to handle the growth. And as your customers and practitioners see the volume and the variety and the velocity of the data coming in, how are they adjusting their data strategies to respond to this? Again, Cloud is clearly the answer, not the data warehouse, but what are they doing? What's the strategy adjustment? >> It's interesting when we start talking to folks, I think sometimes it's a really big shift in thinking about data architectures and data strategies when you look at the Dremio approach. It's very different than what most people are doing today around ETL pipelines and then bringing stuff into a warehouse and oh, the warehouse is too overloaded so let's build some cubes and extracts into the next tier of tools to speed up those dashboards for those tools. And Dremio has totally flipped this on a sentence and said, no, let's not do all those things. That's time consuming. It's brittle, it breaks. And actually your agility and the scope of what you can do with your data decreases. You go from all your data and all your data sources to smaller and smaller. We actually call it the perimeter doom and a lot of people look at this and say, yeah, that kind of looks like how we're doing things today. So from a Dremio perspective, it's really about no copy, try to keep as much data in one place, keep it in one open format and less data movement. And that's a very different approach for people. I think they don't realize how much you can accomplish that way. And your latency shrinks down too. Your actual latency from data created to insight is much shorter. And it's not because of the query response time, that latency is mostly because of data movement and copy and all these things. So you really want to shrink your time to insight. It's not about getting a faster query from a few seconds down, it's about changing the architecture. >> The data drift as they say, interesting there. I got to ask you on the personnel side, team side, you got the technical side, you got the non-technical consumers of the data, you got the data science or data engineering is ramping up. We mentioned earlier data engineering being Agile, is a key innovation here. As you got to blend the two personas of technical and non-technical people playing with data, coding with data, we're the bottlenecks in this process today. How can data teams overcome these bottlenecks? >> I think we see a lot of bottlenecks in the process today, a lot of data movement, a lot of change requests, update this dashboard. Oh, well, that dashboard update requires an ETL pipeline update, requires a column to be added to this warehouse. So then you've got these personas, like you said, some more technical, less technical, the data consumers, the data engineers. Well, the data engineers are getting totally overloaded with requests and work. And it's not even super value-add work to the business. It's not really driving big changes in their culture and insights and new new use cases for data. It's turning through kind of small changes, but it's taking too much time. It's taking days, if not weeks for these organizations to manage small changes. And then the data consumers, the less technical folks, they can't get the answers that they want. They're waiting and waiting and waiting and they don't understand why things are so challenging, how things could take so much time. So from a Dremio perspective, it's amazing to watch these organizations unleash their data. Get the data engineers, their productivity up. Stop dealing with some of the last mile ETL and small changes to the data. And Dremio actually says, hey, data consumers, here's a really nice gooey. You don't need to be a SQL expert, well, the tool will write the joints for you. You can click on a column and say, hey, I want to calculate a new field and calculate that field. And it's all done virtually so it's not changing the physical data sets. The actual data engineering team doesn't even really need to care at that point. So you get happier data consumers at the end of the day. They're doing things more self-service. They're learning about the data and the data engineering teams can go do value-add things. They can re-architecture the platform for the future. They can do POCs to test out new technologies that could support new use cases and bring those into the organization. Things that really add value, instead of just churning through backlogs of, hey, can we get a column added or we change... Everyone's doing app development, AB testing, and those developers are king. Those pipelines stream all this data down when the JSON files change. You need agility. And if you don't have that agility, you just get this endless backlog that you never... >> This is data as code in action. You're committing data back into the main brand that's been tested. That's what developers do. So this is really kind of the next step function. I got to put the customer hat on for a second and ask you kind of the pessimist question. Okay, we've had data lakes, I've got data lakes, it's been data lakes around, I got query engines here and there, they're all over the place, what's missing? What's been missing from the architecture to fully realize the potential of a data lakehouse? >> Yeah, I think that's a great question. The customers say exactly that John. They say, "I've got 22 databases, you got to be kidding me. You showed up with another database." Or, hey, let's talk about a Cloud data lake or a data lake. Again, I did the data lake thing. I had a data lake and it wasn't everything I thought it was going to be. >> It was bad. It was data swamp. >> Yeah, so customers really think this way, and you say, well, what's different this time around? Well, the Cloud in the original data lake world, and I'm just going to focus on data lakes, so the original data lake worlds, everything was still direct attached storage, so you had to scale your storage and compute out together. And we built these huge systems. Thousands of thousands of HDFS nodes and stuff. Well, the Cloud brought the separated compute and storage, but data lakes have never seen separated compute and storage until now. We went from the data lake with directed tap storage to the Cloud data warehouse with separated compute and storage. So the Cloud architecture and getting compute and storage separated is a huge shift in the data lake world. And that agility of like, well, I'm only going to apply it, the compute that I need for this question, for this answer right now, and not get 5,000 servers of compute sitting around at some peak moment. Or just 5,000 compute servers because I have five petabytes or 50 petabytes of data that need to be stored in the discs that are attached to them. So I think the Cloud architecture and separating compute and storage is the first thing that's different this time around about data lakes. But then more importantly than that is the metadata tier. Is the data tier and having sufficient metadata to have the functionality that people need on the data lake. Whether that's for governance and compliance standpoints, to actually be able to do a delete on your data lake, or that's for productivity and treating that data as code, like we're talking about today, and being able to time travel it, version it, branch it. And now these data lakes, the data lakes back in the original days were getting to 50 petabytes. Now think about how big these Cloud data lakes could be. Even larger and you can't move that data around so we have to be really intelligent and really smart about the data operations and versioning all that data, knowing which engine touch the data, which person was the last commit and being able to track all that, is ultimately what's going to make this successful. Because if you don't have the governance in place these days with data, the projects are going to fail. >> Yeah, and I think separating the query layer or SQL layer and the data tier is another innovation that you guys have. Also it's a managed Cloud service, Dremio Cloud now. And you got the open source angle too, which is also going to open up more standardization around some of these awesome features like you mentioned the joints, and I think you guys built on top of Parquet and some other cool things. And you got a community developing, so you get the Cloud and community kind of coming together. So it's the real world that is coming to light saying, hey, I need real world applications, not the theory of old school. So what use cases do you see suited for this kind of new way, new architecture, new community, new programability? >> Yeah, I see people doing all sorts of interesting things and I'm sure with what we've introduced with Dremio Arctic and the data is code is going to open up a whole new world of things that we don't even know about today. But generally speaking, we have customers doing very interesting things, very data application things. Like building really high performance data into use cases whether that's a supply chain and manufacturing use case, whether that's a pharma or biotech use case, a banking use case, and really unleashing that data right into an application. We also see a lot of traditional data analytics use cases more in the traditional business intelligence or dashboarding use cases. That stuff is totally achievable, no problems there. But I think the most interesting stuff is companies are really figuring out how to bring that data. When we offer the flexibility that we're talking about, and the agility that we're talking about, you can really start to bring that data back into the apps, into the work streams, into the places where the business gets more value out of it. Not in a dashboard that some person might have access to, or a set of people have access to. So even in the Dremio Cloud announcement, the press release, there was a customer, they're in Europe, it's called Garvis AI and they do AI for supply chains. It's an intelligent application and it's showing customers transparently how they're getting to these predictions. And they stood this all up in a very short period of time, because it's a Cloud product. They don't have to deal with provisioning, management, upgrades. I think they had their stuff going in like 30 minutes or something, like super quick, which is amazing. The data was already there, and a lot of organizations, their data's already in these Cloud storages. And if that's the case... >> If they have data, they're a use case. This is agility. This is agility coming to the data engineering field, making data programmable, enabling the data applications, the data ops for everybody, for coding... >> For everybody. And for so many more use cases at these companies. These data engineering teams, these data platform teams, whether they're in marketing or ad tech or Fiserv or Telco, they have a list. There's a list about a roadmap of use cases that they're waiting to get to. And if they're drowning underwater in the current tooling and barely keeping that alive, and oh, by the way, John, you can't go higher 30 new data engineers tomorrow and bring on the team to get capacity. You have to innovate at the architecture level, to unlock more data use cases because you're not going to go triple your team. That's not possible. >> It's going to unlock a tsunami of value. Because everyone's clogged in the system and it's painful. Right? >> Yeah. >> They've got delays, you've got bottlenecks. you've got people complaining it's hard, scar tissue. So now I think this brings ease of use and speed to the table. >> Yeah. >> I think that's what we're all about, is making the data super easy for everyone. This should be fun and easy, not really painful and really hard and risky. In a lot of these old ways of doing things, there's a lot of risk. You start changing your ETL pipeline. You add a column to the table. All of a sudden, you've got potential risk that things are going to break and you don't even know what's going to break. >> Proprietary, not a lot of volume and usage, and on-premises, open, Cloud, Agile. (John chuckles) Come on, which path? The curtain or the box, what are you going to take? It's a no brainer. >> Which way do you want to go? >> Mark, thanks for coming on theCUBE. Really appreciate it for being part of the AWS startup showcase data as code, great conversation. Data as code is going to enable a next wave of innovation and impact the future of data analytics. Thanks for coming on theCUBE. >> Yeah, thanks John and thanks to the AWS team. A great partnership between AWS and Dremio too. Talk to you soon. >> Keep it right there, more action here on theCUBE. As part of the showcase, stay with us. This is theCUBE, your leader in tech coverage. I'm John Furrier, your host, thanks for watching. (downbeat music)

(bright upbeat music) >> Hey everyone. Welcome to this "CUBE Conversation" featuring Dremio. I'm your host, Lisa Martin. And I'm excited today to be joined by Mark Lyons the VP of product management at Dremio. Mark thanks for joining us today. >> Hey Lisa, thank you for having me. Looking forward to the top. >> Yeah. Talk to me about what's going on at Dremio. I had the chance to talk to your chief product officer Tomer Shiran in a couple months ago but talk to us about what's going on. >> Yeah, I remember that at re:Invent it's been an exciting few months since re:Invent here at Dremio and just in the new year we raised our Series E since then we ran into our subsurface event which we had over seven, 8,000 registrants and attendees. And then we announced our Dremio cloud product generally available including Dremio Sonar, which is SQL query engine and Dremio Arctic in public preview which is a better store for the lakehouse. >> Great. And we're going to dig into both of those. I saw that over 400 million raised in that Series E raising the valuation of Dremio to 2 billion. So a lot of growth and momentum going on at the company I'm sure. If we think about businesses in any industry they've made large investments in data warehouses, proprietary data warehouses. Talk to me about historically what they've been able to achieve, but then what some those bottlenecks are that they're running into. >> Yeah, for sure. My background is actually in the data warehouse space. I spent over the last eight, maybe close to 10 years and we've seen this shift go on from the traditional enterprise data warehouse to the data lake to the the last couple years is really been the time of the cloud data warehouse. And there's been a large amount of adoption of cloud data warehouses, but fundamentally they still come with a lot of the same challenges that have always existed with the data warehouse, which is first of all you have to load your data into it. So that data's coming from lots of different sources. In many cases, it's landing in a files in the data lake like a repository like S3 first. And then there's a loading process, right? An ETL process. And those pipelines have to be maintained and stay operational. And typically as the data warehouse life cycle of processing moves on the scope of the data that consumers get to access gets smaller and smaller. The control of that data gets tighter and change process gets heavier, and it goes from quick changes of adding a column or adding a field to a file to days if not weeks for businesses to modify their data pipelines and test new scenarios offer new features in the application or answer new questions that the business is interested you know, from an analytics standpoint. So typically we see the same thing even with these cloud data warehouses, the scope of the data shrinks, the time to get answers gets longer. And when new engines come along the same story we see, and this is going on right now in the data warehouse space there's new data that are coming and they say, well we're a thousand faster times faster than the last data warehouse. And then it's like, okay, great. But what's the process? The process is to migrate all your data to the new data warehouse, right? And that comes with all the same baggage. Again, it's a proprietary format that you load your data into. So I think people are ready for a change from that. >> People are not only ready for a change, but as every company has to become a data company these days and access to real time data is no longer a nice to have. It's absolutely essential. The ability to scale the ability to harness the value from as much data as possible and to do so fast is real really table stakes for any organization. How is Dremio helping customers in that situation to operationalize their data? >> Yeah, so that's why I was so intrigued and loved about Dremio when I joined three, four, five months back. Coming from the warehouse space, when I first saw the product I was just like, oh my gosh, this is so much easier for folks. They can access a larger scope of their data faster, which to your point, like is table stakes for all organizations these days they need to be able to analyze data sooner. Sooner is the better. Data has a halflife, right? Like it decays. The value of data decays over time. So typically the most valuable data is the newest data. And that all depends on what we're the industries we're talking about the types of data and the use cases, but it's always basically true that newer data is more valuable and they need to be able to analyze as much of it as possible. The story can't be, no, we have to wait weeks or months to get a new data source or the story can't be you know, that data that includes seasonality. You know, we weren't able to keep in the same location because it's too expensive to keep it in the warehouse or whatever. So for Dremio and our customers our story is simple, is leverage the data where it is so access data in all sorts of sources, whether it's a post press database or an S3 bucket, and don't move the data don't copy the data, analyze it in place. And don't limit the scope of the data you're trying to analyze. If you have new use cases you have additional data sets that you want to add to those use cases, just bring them in, into S3 and you are off to the races and you can easily analyze more data and give more power to the end user. So if there's a field that they want to calculate the simple change convert this miles field, the kilometers well, the end users should be empowered to just make a calculation on the data like that. That should not require an entire cycle through a data engineering team and a backlog and a ticket and pushing that to production and so forth which in many cases it does at many organizations. It's a lot of effort to make new calculations on the data or derive new fields, add a new column and so forth. So Dremio makes the data engineers life easier and more productive. It also makes the data consumers life much easier and happier, and they can just do their job without worrying about and waiting. >> Not only can they do their job but from a business, a high level perspective the business is probably has the opportunity to be far more competitive because it's got a bigger scope of data, as you mentioned, access to it more widely faster and those are only good things in terms of- >> More use cases, more experiments, right? So what I've seen a lot is like there's no shortage of ideas of what people can do with the data. And projects that might be able to be undertaken but no one knows exactly how valuable that will be. How whether that's something that should be funded or should not be funded. So like more use cases, more experiments try more things. Like if it's cheap to try these data problems and see if it's valuable to the business then that's better for the business. Ultimately the business will be more competitive. We'll be able to try more new products we'll be able to have better operational kind of efficiencies, lower risk all those things. >> Right. What about data governance? Talk to me about how the Lakehouse enables that across all these disparate data volumes. >> I think this is where things get really interesting with the Lakehouse concept relative to where we used to be with a data lake, which was a parking ground for just lots of files. And that came with a lot of challenges when you just had a lot of files out there in a data lake, whether that was HDFS, right. I do data lake back in the day or now a cloud storage object, storage data lake. So historically I feel like governance, access authentication, auditing all were extremely challenging with the data lake but now in the modern kind of lake in the modern lakehouse world, all those challenges have been solved. You have great everything from the front of the house with all and access policies and data masking everything that you would expect through commits and tables and transactions and inserts and updates and deletes, and auditing of that data able to see, well who made the changes to the data, which engine, which user when were they made and seeing the whole history of a table and not just one, not just a mess of files in a file store. So it's really come a long way. I feel like where the renaissance stage of the 2.0 data lakes or lakehouses as people call them. But basically what you're seeing is a lot of functionality from the traditional warehouse, all available in the lake. And warehouses had a lot of governance built in. And whether that is encryption and column access policies and row access policies. So only the right user saw the right data or some data masking. So that like the social security was masked out but the analyst knew it was a social security number. That was all there. Now that's all available on the lakehouse and you don't need to copy data into a data warehouse just to meet those type of requirements. Huge one is also deletes, right? Like I feel like deletes were one of the Achilles heels of the original data lake when there was no governance. And people were just copying data sets around modifying data sets for whatever their analytics use case was. If someone said, "Hey, go delete the right. To be forgotten GDPR." Now you've got Californias CCPA and others all coming online. If you said, go delete this per you know, this records or set of records from there from a lake original lake. I think that was impossible, probably for many people to do it with confidence, like to say that like I fully deleted this. Now with the Apache like iceberg cable format that is stores in the lakehouse architecture, you actually have delete functionality, right? Which is a key component that warehouses are traditionally brought to the table. >> That's a huge component from a compliance perspective. You mentioned GDPR, CCPA, which is going to be CPRA in less than a year, but there's so many other regulations data privacy regulations that are coming up that the ability to delete that is going to be table stakes for organizations, something that you guys launched. And we just have a couple minutes left, but you launched I love the name, the forever free data Lakehouse platform. That sounds great. Forever Free. Talk to me about what that really means is consisting of two products the Sonar and Arctic that you mentioned, but talk to me about this Forever Free data Lakehouse. >> Yeah. I feel like this is an amazing step forward in this, in the industry. And because of the Dremio cloud architecture, where the execution and data lives in the customer's cloud account we're able to basically say, hey, the Dremio software the Dremio service side of this platform is Forever Free for users. Now there is a paid tier but there's a standard tier that is truly forever free. Now that that still comes with infrastructure bills from like your cloud provider, right? So if you use AWS, you still have an S3 bill like for your data sets because we're not moving them. They're staying in your Amazon account in your S3 bucket. You still do still have to pay for right. The infrastructure, the EC2 and the compute to do the data analytics but the actual softwares is free forever. And there's no one else in our space offering that at in our space, everything's a free trial. So here's your $500 of credit. Come try my product. And what we're saying is with this kind of our unique architectural approach and this is what I think is preferred by customers too. You know, we take care of all the query planning all the engine management, all the administrative the platform, the upgrades fully available zero downtime platform. So they get all the benefits of SaaS as well as the benefits of maintaining control over their data. And because that data staying in their account and the execution of the analytics is staying in their account. We don't incur that infrastructure bill. So we can have a free forever tier a forever free tier of our platform. And we've had tremendous adoption. I think we announced this beginning of March first week of March. So it's not even the end of March. Hundreds and hundreds of signups and many customers actively are users actively on the platform now live querying their data >> Just kind of summarizes the momentum that Dremio we seeing. Mark, thank you so much. We're out of time, but thanks for talking to me- >> Thank you. >> About what's new at Dremio. What you guys are doing. Next time, we'll have to unpack this even more. I'm sure there's loads more we could talk about but we appreciate that. >> Yeah, this was great. Thank you, Lisa. Thank you. >> My pleasure for Mark Lyons. I'm Lisa Martin. Keep it right here on theCUBE your leader in high tech hybrid event coverage. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> The pandemic has changed the way we think about and predict the future. As we enter the third year of a global pandemic, we see the significant impact that it's had on technology strategy, spending patterns, and company fortunes Much has changed. And while many of these changes were forced reactions to a new abnormal, the trends that we've seen over the past 24 months have become more entrenched, and point to the way that's coming ahead in the technology business. Hello and welcome to this week's Wikibon CUBE Insights powered by ETR. In this Breaking Analysis, we welcome our partner and colleague and business friend, Erik Porter Bradley, as we deliver what's becoming an annual tradition for Erik and me, our predictions for Enterprise Technology in 2022 and beyond Erik, welcome. Thanks for taking some time out. >> Thank you, Dave. Luckily we did pretty well last year, so we were able to do this again. So hopefully we can keep that momentum going. >> Yeah, you know, I want to mention that, you know, we get a lot of inbound predictions from companies and PR firms that help shape our thinking. But one of the main objectives that we have is we try to make predictions that can be measured. That's why we use a lot of data. Now not all will necessarily fit that parameter, but if you've seen the grading of our 2021 predictions that Erik and I did, you'll see we do a pretty good job of trying to put forth prognostications that can be declared correct or not, you know, as black and white as possible. Now let's get right into it. Our first prediction, we're going to go run into spending, something that ETR surveys for quarterly. And we've reported extensively on this. We're calling for tech spending to increase somewhere around 8% in 2022, we can see there on the slide, Erik, we predicted spending last year would increase by 4% IDC. Last check was came in at five and a half percent. Gardner was somewhat higher, but in general, you know, not too bad, but looking ahead, we're seeing an acceleration from the ETR September surveys, as you can see in the yellow versus the blue bar in this chart, many of the SMBs that were hard hit by the pandemic are picking up spending again. And the ETR data is showing acceleration above the mean for industries like energy, utilities, retail, and services, and also, notably, in the Forbes largest 225 private companies. These are companies like Mars or Koch industries. They're predicting well above average spending for 2022. So Erik, please weigh in here. >> Yeah, a lot to bring up on this one, I'm going to be quick. So 1200 respondents on this, over a third of which were at the C-suite level. So really good data that we brought in, the usual bucket of, you know, fortune 500, global 2000 make up the meat of that median, but it's 8.3% and rising with momentum as we see. What's really interesting right now is that energy and utilities. This is usually like, you know, an orphan stock dividend type of play. You don't see them at the highest point of tech spending. And the reason why right now is really because this state of tech infrastructure in our energy infrastructure needs help. And it's obvious, remember the Florida municipality break reach last year? When they took over the water systems or they had the ability to? And this is a real issue, you know, there's bad nation state actors out there, and I'm no alarmist, but the energy and utility has to spend this money to keep up. It's really important. And then you also hit on the retail consumer. Obviously what's happened, the work from home shift created a shop from home shift, and the trends that are happening right now in retail. If you don't spend and keep up, you're not going to be around much longer. So I think the really two interesting things here to call out are energy utilities, usually a laggard in IT spend and it's leading, and also retail consumer, a lot of changes happening. >> Yeah. Great stuff. I mean, I recall when we entered the pandemic, really ETR was the first to emphasize the impact that work from home was going to have, so I really put a lot of weight on this data. Okay. Our next prediction is we're going to get into security, it's one of our favorite topics. And that is that the number one priority that needs to be addressed by organizations in 2022 is security and you can see, in this slide, the degree to which security is top of mind, relative to some other pretty important areas like cloud, productivity, data, and automation, and some others. Now people may say, "Oh, this is obvious." But I'm going to add some context here, Erik, and then bring you in. First, organizations, they don't have unlimited budgets. And there are a lot of competing priorities for dollars, especially with the digital transformation mandate. And depending on the size of the company, this data will vary. For example, while security is still number one at the largest public companies, and those are of course of the biggest spenders, it's not nearly as pronounced as it is on average, or in, for example, mid-sized companies and government agencies. And this is because midsized companies or smaller companies, they don't have the resources that larger companies do. Larger companies have done a better job of securing their infrastructure. So these mid-size firms are playing catch up and the data suggests cyber is even a bigger priority there, gaps that they have to fill, you know, going forward. And that's why we think there's going to be more demand for MSSPs, managed security service providers. And we may even see some IPO action there. And then of course, Erik, you and I have talked about events like the SolarWinds Hack, there's more ransomware attacks, other vulnerabilities. Just recently, like Log4j in December. All of this has heightened concerns. Now I want to talk a little bit more about how we measure this, you know, relatively, okay, it's an obvious prediction, but let's stick our necks out a little bit. And so in addition to the rise of managed security services, we're calling for M&A and/or IPOs, we've specified some names here on this chart, and we're also pointing to the digital supply chain as an area of emphasis. Again, Log4j really shone that under a light. And this is going to help the likes of Auth0, which is now Okta, SailPoint, which is called out on this chart, and some others. We're calling some winners in end point security. Erik, you're going to talk about sort of that lifecycle, that transformation that we're seeing, that migration to new endpoint technologies that are going to benefit from this reset refresh cycle. So Erik, weigh in here, let's talk about some of the elements of this prediction and some of the names on that chart. >> Yeah, certainly. I'm going to start right with Log4j top of mind. And the reason why is because we're seeing a real paradigm shift here where things are no longer being attacked at the network layer, they're being attacked at the application layer, and in the application stack itself. And that is a huge shift left. And that's taking in DevSecOps now as a real priority in 2022. That's a real paradigm shift over the last 20 years. That's not where attacks used to come from. And this is going to have a lot of changes. You called out a bunch of names in there that are, they're either going to work. I would add to that list Wiz. I would add Orca Security. Two names in our emerging technology study, in addition to the ones you added that are involved in cloud security and container security. These names are either going to get gobbled up. So the traditional legacy names are going to have to start writing checks and, you know, legacy is not fair, but they're in the data center, right? They're, on-prem, they're not cloud native. So these are the names that money is going to be flowing to. So they're either going to get gobbled up, or we're going to see some IPO's. And on the other thing I want to talk about too, is what you mentioned. We have CrowdStrike on that list, We have SentinalOne on the list. Everyone knows them. Our data was so strong on Tanium that we actually went positive for the first time just today, just this morning, where that was released. The trifecta of these are so important because of what you mentioned, under resourcing. We can't have security just tell us when something happens, it has to automate, and it has to respond. So in this next generation of EDR and XDR, an automated response has to happen because people are under-resourced, salaries are really high, there's a skill shortage out there. Security has to become responsive. It can't just monitor anymore. >> Yeah. Great. And we should call out too. So we named some names, Snyk, Aqua, Arctic Wolf, Lacework, Netskope, Illumio. These are all sort of IPO, or possibly even M&A candidates. All right. Our next prediction goes right to the way we work. Again, something that ETR has been on for awhile. We're calling for a major rethink in remote work for 2022. We had predicted last year that by the end of 2021, there'd be a larger return to the office with the norm being around a third of workers permanently remote. And of course the variants changed that equation and, you know, gave more time for people to think about this idea of hybrid work and that's really come in to focus. So we're predicting that is going to overtake fully remote as the dominant work model with only about a third of the workers back in the office full-time. And Erik, we expect a somewhat lower percentage to be fully remote. It's now sort of dipped under 30%, at around 29%, but it's still significantly higher than the historical average of around 15 to 16%. So still a major change, but this idea of hybrid and getting hybrid right, has really come into focus. Hasn't it? >> Yeah. It's here to stay. There's no doubt about it. We started this in March of 2020, as soon as the virus hit. This is the 10th iteration of the survey. No one, no one ever thought we'd see a number where only 34% of people were going to be in office permanently. That's a permanent number. They're expecting only a third of the workers to ever come back fully in office. And against that, there's 63% that are saying their permanent workforce is going to be either fully remote or hybrid. And this, I can't really explain how big of a paradigm shift this is. Since the start of the industrial revolution, people leave their house and go to work. Now they're saying that's not going to happen. The economic impact here is so broad, on so many different areas And, you know, the reason is like, why not? Right? The productivity increase is real. We're seeing the productivity increase. Enterprises are spending on collaboration tools, productivity tools, We're seeing an increased perception in productivity of their workforce. And the CFOs can cut down an expense item. I just don't see a reason why this would end, you know, I think it's going to continue. And I also want to point out these results, as high as they are, were before the Omicron wave hit us. I can only imagine what these results would have been if we had sent the survey out just two or three weeks later. >> Yeah. That's a great point. Okay. Next prediction, we're going to look at the supply chain, specifically in how it's affecting some of the hardware spending and cloud strategies in the future. So in this chart, ETRS buyers, have you experienced problems procuring hardware as a result of supply chain issues? And, you know, despite the fact that some companies are, you know, I would call out Dell, for example, doing really well in terms of delivering, you can see that in the numbers, it's pretty clear, there's been an impact. And that's not not an across the board, you know, thing where vendors are able to deliver, especially acute in PCs, but also pronounced in networking, also in firewall servers and storage. And what's interesting is how companies are responding and reacting. So first, you know, I'm going to call the laptop and PC demand staying well above pre-COVID norms. It had peaked in 2012. Pre-pandemic it kept dropping and dropping and dropping, in terms of, you know, unit volume, where the market was contracting. And we think can continue to grow this year in double digits in 2022. But what's interesting, Erik, is when you survey customers, is despite the difficulty they're having in procuring network hardware, there's as much of a migration away from existing networks to the cloud. You could probably comment on that. Their networks are more fossilized, but when it comes to firewalls and servers and storage, there's a much higher propensity to move to the cloud. 30% of customers that ETR surveyed will replace security appliances with cloud services and 41% and 34% respectively will move to cloud compute and storage in 2022. So cloud's relentless march on traditional on-prem models continues. Erik, what do you make of this data? Please weigh in on this prediction. >> As if we needed another reason to go to the cloud. Right here, here it is yet again. So this was added to the survey by client demand. They were asking about the procurement difficulties, the supply chain issues, and how it was impacting our community. So this is the first time we ran it. And it really was interesting to see, you know, the move there. And storage particularly I found interesting because it correlated with a huge jump that we saw on one of our vendor names, which was Rubrik, had the highest net score that it's ever had. So clearly we're seeing some correlation with some of these names that are there, you know, really well positioned to take storage, to take data into the cloud. So again, you didn't need another reason to, you know, hasten this digital transformation, but here we are, we have it yet again, and I don't see it slowing down anytime soon. >> You know, that's a really good point. I mean, it's not necessarily bad news for the... I mean, obviously you wish that it had no change, would be great, but things, you know, always going to change. So we'll talk about this a little bit later when we get into the Supercloud conversation, but this is an opportunity for people who embrace the cloud. So we'll come back to that. And I want to hang on cloud a bit and share some recent projections that we've made. The next prediction is the big four cloud players are going to surpass 167 billion, an IaaS and PaaS revenue in 2022. We track this. Observers of this program know that we try to create an apples to apples comparison between AWS, Azure, GCP and Alibaba in IaaS and PaaS. So we're calling for 38% revenue growth in 2022, which is astounding for such a massive market. You know, AWS is probably not going to hit a hundred billion dollar run rate, but they're going to be close this year. And we're going to get there by 2023, you know they're going to surpass that. Azure continues to close the gap. Now they're about two thirds of the size of AWS and Google, we think is going to surpass Alibaba and take the number three spot. Erik, anything you'd like to add here? >> Yeah, first of all, just on a sector level, we saw our sector, new survey net score on cloud jumped another 10%. It was already really high at 48. Went up to 53. This train is not slowing down anytime soon. And we even added an edge compute type of player, like CloudFlare into our cloud bucket this year. And it debuted with a net score of almost 60. So this is really an area that's expanding, not just the big three, but everywhere. We even saw Oracle and IBM jump up. So even they're having success, taking some of their on-prem customers and then selling them to their cloud services. This is a massive opportunity and it's not changing anytime soon, it's going to continue. >> And I think the operative word there is opportunity. So, you know, the next prediction is something that we've been having fun with and that's this Supercloud becomes a thing. Now, the reason I say we've been having fun is we put this concept of Supercloud out and it's become a bit of a controversy. First, you know, what the heck's the Supercloud right? It's sort of a buzz-wordy term, but there really is, we believe, a thing here. We think there needs to be a rethinking or at least an evolution of the term multi-cloud. And what we mean is that in our view, you know, multicloud from a vendor perspective was really cloud compatibility. It wasn't marketed that way, but that's what it was. Either a vendor would containerize its legacy stack, shove it into the cloud, or a company, you know, they'd do the work, they'd build a cloud native service on one of the big clouds and they did do it for AWS, and then Azure, and then Google. But there really wasn't much, if any, leverage across clouds. Now from a buyer perspective, we've always said multicloud was a symptom of multi-vendor, meaning I got different workloads, running in different clouds, or I bought a company and they run on Azure, and I do a lot of work on AWS, but generally it wasn't necessarily a prescribed strategy to build value on top of hyperscale infrastructure. There certainly was somewhat of a, you know, reducing lock-in and hedging the risk. But we're talking about something more here. We're talking about building value on top of the hyperscale gift of hundreds of billions of dollars in CapEx. So in addition, we're not just talking about transforming IT, which is what the last 10 years of cloud have been like. And, you know, doing work in the cloud because it's cheaper or simpler or more agile, all of those things. So that's beginning to change. And this chart shows some of the technology vendors that are leaning toward this Supercloud vision, in our view, building on top of the hyperscalers that are highlighted in red. Now, Jerry Chan at Greylock, they wrote a piece called Castles in the Cloud. It got our thinking going, and he and the team at Greylock, they're building out a database of all the cloud services and all the sub-markets in cloud. And that got us thinking that there's a higher level of abstraction coalescing in the market, where there's tight integration of services across clouds, but the underlying complexity is hidden, and there's an identical experience across clouds, and even, in my dreams, on-prem for some platforms, so what's new or new-ish and evolving are things like location independence, you've got to include the edge on that, metadata services to optimize locality of reference and data source awareness, governance, privacy, you know, application independent and dependent, actually, recovery across clouds. So we're seeing this evolve. And in our view, the two biggest things that are new are the technology is evolving, where you're seeing services truly integrate cross-cloud. And the other big change is digital transformation, where there's this new innovation curve developing, and it's not just about making your IT better. It's about SaaS-ifying and automating your entire company workflows. So Supercloud, it's not just a vendor thing to us. It's the evolution of, you know, the, the Marc Andreessen quote, "Every company will be a SaaS company." Every company will deliver capabilities that can be consumed as cloud services. So Erik, the chart shows spending momentum on the y-axis and net score, or presence in the ETR data center, or market share on the x-axis. We've talked about snowflake as the poster child for this concept where the vision is you're in their cloud and sharing data in that safe place. Maybe you could make some comments, you know, what do you think of this Supercloud concept and this change that we're sensing in the market? >> Well, I think you did a great job describing the concept. So maybe I'll support it a little bit on the vendor level and then kind of give examples of the ones that are doing it. You stole the lead there with Snowflake, right? There is no better example than what we've seen with what Snowflake can do. Cross-portability in the cloud, the ability to be able to be, you know, completely agnostic, but then build those services on top. They're better than anything they could offer. And it's not just there. I mean, you mentioned edge compute, that's a whole nother layer where this is coming in. And CloudFlare, the momentum there is out of control. I mean, this is a company that started off just doing CDN and trying to compete with Okta Mite. And now they're giving you a full soup to nuts with security and actual edge compute layer, but it's a fantastic company. What they're doing, it's another great example of what you're seeing here. I'm going to call out HashiCorp as well. They're more of an infrastructure services, a little bit more of an open-source freemium model, but what they're doing as well is completely cloud agnostic. It's dynamic. It doesn't care if you're in a container, it doesn't matter where you are. They recently IPO'd and they're down 25%, but their data looks so good across both of our emerging technology and TISA survey. It's certainly another name that's playing on this. And another one that we mentioned as well is Rubrik. If you need storage, compute, and in the cloud layer and you need to be agnostic to it, they're another one that's really playing in this space. So I think it's a great concept you're bringing up. I think it's one that's here to stay and there's certainly a lot of vendors that fit into what you're describing. >> Excellent. Thank you. All right, let's shift to data. The next prediction, it might be a little tough to measure. Before I said we're trying to be a little black and white here, but it relates to Data Mesh, which is, the ideas behind that term were created by Zhamak Dehghani of ThoughtWorks. And we see Data Mesh is really gaining momentum in 2022, but it's largely going to be, we think, confined to a more narrow scope. Now, the impetus for change in data architecture in many companies really stems from the fact that their Hadoop infrastructure really didn't solve their data problems and they struggle to get more value out of their data investments. Data Mesh prescribes a shift to a decentralized architecture in domain ownership of data and a shift to data product thinking, beyond data for analytics, but data products and services that can be monetized. Now this a very powerful in our view, but they're difficult for organizations to get their heads around and further decentralization creates the need for a self-service platform and federated data governance that can be automated. And not a lot of standards around this. So it's going to take some time. At our power panel a couple of weeks ago on data management, Tony Baer predicted a backlash on Data Mesh. And I don't think it's going to be so much of a backlash, but rather the adoption will be more limited. Most implementations we think are going to use a starting point of AWS and they'll enable domains to access and control their own data lakes. And while that is a very small slice of the Data Mesh vision, I think it's going to be a starting point. And the last thing I'll say is, this is going to take a decade to evolve, but I think it's the right direction. And whether it's a data lake or a data warehouse or a data hub or an S3 bucket, these are really, the concept is, they'll eventually just become nodes on the data mesh that are discoverable and access is governed. And so the idea is that the stranglehold that the data pipeline and process and hyper-specialized roles that they have on data agility is going to evolve. And decentralized architectures and the democratization of data will eventually become a norm for a lot of different use cases. And Erik, I wonder if you'd add anything to this. >> Yeah. There's a lot to add there. The first thing that jumped out to me was that that mention of the word backlash you said, and you said it's not really a backlash, but what it could be is these are new words trying to solve an old problem. And I do think sometimes the industry will notice that right away and maybe that'll be a little pushback. And the problems are what you already mentioned, right? We're trying to get to an area where we can have more assets in our data site, more deliverable, and more usable and relevant to the business. And you mentioned that as self-service with governance laid on top. And that's really what we're trying to get to. Now, there's a lot of ways you can get there. Data fabric is really the technical aspect and data mesh is really more about the people, the process, and the governance, but the two of those need to meet, in order to make that happen. And as far as tools, you know, there's even cataloging names like Informatica that play in this, right? Istio plays in this, Snowflake plays in this. So there's a lot of different tools that will support it. But I think you're right in calling out AWS, right? They have AWS Lake, they have AWS Glue. They have so much that's trying to drive this. But I think the really important thing to keep here is what you said. It's going to be a decade long journey. And by the way, we're on the shoulders of giants a decade ago that have even gotten us to this point to talk about these new words because this has been an ongoing type of issue, but ultimately, no matter which vendors you use, this is going to come down to your data governance plan and the data literacy in your business. This is really about workflows and people as much as it is tools. So, you know, the new term of data mesh is wonderful, but you still have to have the people and the governance and the processes in place to get there. >> Great, thank you for that, Erik. Some great points. All right, for the next prediction, we're going to shine the spotlight on two of our favorite topics, Snowflake and Databricks, and the prediction here is that, of course, Databricks is going to IPO this year, as expected. Everybody sort of expects that. And while, but the prediction really is, well, while these two companies are facing off already in the market, they're also going to compete with each other for M&A, especially as Databricks, you know, after the IPO, you're going to have, you know, more prominence and a war chest. So first, these companies, they're both looking pretty good, the same XY graph with spending velocity and presence and market share on the horizontal axis. And both Snowflake and Databricks are well above that magic 40% red dotted line, the elevated line, to us. And for context, we've included a few other firms. So you can see kind of what a good position these two companies are really in, especially, I mean, Snowflake, wow, it just keeps moving to the right on this horizontal picture, but maintaining the next net score in the Y axis. Amazing. So, but here's the thing, Databricks is using the term Lakehouse implying that it has the best of data lakes and data warehouses. And Snowflake has the vision of the data cloud and data sharing. And Snowflake, they've nailed analytics, and now they're moving into data science in the domain of Databricks. Databricks, on the other hand, has nailed data science and is moving into the domain of Snowflake, in the data warehouse and analytics space. But to really make this seamless, there has to be a semantic layer between these two worlds and they're either going to build it or buy it or both. And there are other areas like data clean rooms and privacy and data prep and governance and machine learning tooling and AI, all that stuff. So the prediction is they'll not only compete in the market, but they'll step up and in their competition for M&A, especially after the Databricks IPO. We've listed some target names here, like Atscale, you know, Iguazio, Infosum, Habu, Immuta, and I'm sure there are many, many others. Erik, you care to comment? >> Yeah. I remember a year ago when we were talking Snowflake when they first came out and you, and I said, "I'm shocked if they don't use this war chest of money" "and start going after more" "because we know Slootman, we have so much respect for him." "We've seen his playbook." And I'm actually a little bit surprised that here we are, at 12 months later, and he hasn't spent that money yet. So I think this prediction's just spot on. To talk a little bit about the data side, Snowflake is in rarefied air. It's all by itself. It is the number one net score in our entire TISA universe. It is absolutely incredible. There's almost no negative intentions. Global 2000 organizations are increasing their spend on it. We maintain our positive outlook. It's really just, you know, stands alone. Databricks, however, also has one of the highest overall net sentiments in the entire universe, not just its area. And this is the first time we're coming up positive on this name as well. It looks like it's not slowing down. Really interesting comment you made though that we normally hear from our end-user commentary in our panels and our interviews. Databricks is really more used for the data science side. The MLAI is where it's best positioned in our survey. So it might still have some catching up to do to really have that caliber of usability that you know Snowflake is seeing right now. That's snowflake having its own marketplace. There's just a lot more to Snowflake right now than there is Databricks. But I do think you're right. These two massive vendors are sort of heading towards a collision course, and it'll be very interesting to see how they deploy their cash. I think Snowflake, with their incredible management and leadership, probably will make the first move. >> Well, I think you're right on that. And by the way, I'll just add, you know, Databricks has basically said, hey, it's going to be easier for us to come from data lakes into data warehouse. I'm not sure I buy that. I think, again, that semantic layer is a missing ingredient. So it's going to be really interesting to see how this plays out. And to your point, you know, Snowflake's got the war chest, they got the momentum, they've got the public presence now since November, 2020. And so, you know, they're probably going to start making some aggressive moves. Anyway, next prediction is something, Erik, that you and I have talked about many, many times, and that is observability. I know it's one of your favorite topics. And we see this world screaming for more consolidation it's going all in on cloud native. These legacy stacks, they're fighting to stay relevant, but the direction is pretty clear. And the same XY graph lays out the players in the field, with some of the new entrants that we've also highlighted, like Observe and Honeycomb and ChaosSearch that we've talked about. Erik, we put a big red target around Splunk because everyone wants their gold. So please give us your thoughts. >> Oh man, I feel like I've been saying negative things about Splunk for too long. I've got a bad rap on this name. The Splunk shareholders come after me all the time. Listen, it really comes down to this. They're a fantastic company that was designed to do logging and monitoring and had some great tool sets around what you could do with it. But they were designed for the data center. They were designed for prem. The world we're in now is so dynamic. Everything I hear from our end user community is that all net new workloads will be going to cloud native players. It's that simple. So Splunk has entrenched. It's going to continue doing what it's doing and it does it really, really well. But if you're doing something new, the new workloads are going to be in a dynamic environment and that's going to go to the cloud native players. And in our data, it is extremely clear that that means Datadog and Elastic. They are by far number one and two in net score, increase rates, adoption rates. It's not even close. Even New Relic actually is starting to, you know, entrench itself really well. We saw New Relic's adoption's going up, which is super important because they went to that freemium model, you know, to try to get their little bit of an entrenched customer base and that's working as well. And then you made a great list here, of all the new entrants, but it goes beyond this. There's so many more. In our emerging technology survey, we're seeing Century, Catchpoint, Securonix, Lucid Works. There are so many options in this space. And let's not forget, the biggest data that we're seeing is with Grafana. And Grafana labs as yet to turn on their enterprise. Elastic did it, why can't Grafana labs do it? They have an enterprise stack. So when you look at how crowded this space is, there has to be consolidation. I recently hosted a panel and every single guy on that panel said, "Please give me a consolidation." Because they're the end users trying to actually deploy these and it's getting a little bit confusing. >> Great. Thank you for that. Okay. Last prediction. Erik, might be a little out of your wheelhouse, but you know, you might have some thoughts on it. And that's a hybrid events become the new digital model and a new category in 2022. You got these pure play digital or virtual events. They're going to take a back seat to in-person hybrids. The virtual experience will eventually give way to metaverse experiences and that's going to take some time, but the physical hybrid is going to drive it. And metaverse is ultimately going to define the virtual experience because the virtual experience today is not great. Nobody likes virtual. And hybrid is going to become the business model. Today's pure virtual experience has to evolve, you know, theCUBE first delivered hybrid mid last decade, but nobody really wanted it. We did Mobile World Congress last summer in Barcelona in an amazing hybrid model, which we're showing in some of the pictures here. Alex, if you don't mind bringing that back up. And every physical event that we're we're doing now has a hybrid and virtual component, including the pre-records. You can see in our studios, you see that the green screen. I don't know. Erik, what do you think about, you know, the Zoom fatigue and all this. I know you host regular events with your round tables, but what are your thoughts? >> Well, first of all, I think you and your company here have just done an amazing job on this. So that's really your expertise. I spent 20 years of my career hosting intimate wall street idea dinners. So I'm better at navigating a wine list than I am navigating a conference floor. But I will say that, you know, the trend just goes along with what we saw. If 35% are going to be fully remote. If 70% are going to be hybrid, then our events are going to be as well. I used to host round table dinners on, you know, one or two nights a week. Now those have gone virtual. They're now panels. They're now one-on-one interviews. You know, we do chats. We do submitted questions. We do what we can, but there's no reason that this is going to change anytime soon. I think you're spot on here. >> Yeah. Great. All right. So there you have it, Erik and I, Listen, we always love the feedback. Love to know what you think. Thank you, Erik, for your partnership, your collaboration, and love doing these predictions with you. >> Yeah. I always enjoy them too. And I'm actually happy. Last year you made us do a baker's dozen, so thanks for keeping it to 10 this year. >> (laughs) We've got a lot to say. I know, you know, we cut out. We didn't do much on crypto. We didn't really talk about SaaS. I mean, I got some thoughts there. We didn't really do much on containers and AI. >> You want to keep going? I've got another 10 for you. >> RPA...All right, we'll have you back and then let's do that. All right. All right. Don't forget, these episodes are all available as podcasts, wherever you listen, all you can do is search Breaking Analysis podcast. Check out ETR's website at etr.plus, they've got a new website out. It's the best data in the industry, and we publish a full report every week on wikibon.com and siliconangle.com. You can always reach out on email, David.Vellante@siliconangle.com I'm @DVellante on Twitter. Comment on our LinkedIn posts. This is Dave Vellante for the Cube Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (mellow music)

[Music] welcome to thecube's coverage of vmworld 2021 i'm lisa martin pleased to welcome back to the program the cto of vmware kit kohlberg welcome back to the program and congrats on your new role thank you yeah i'm really excited to be here so you've been at vmware for a long time you started as an intern i read yeah yeah it's been uh 18 years as a full-timer but i guess 19 if you count my internship so quite a while it's many lifetimes in silicon valley right many lifetimes in silicon valley well we've seen a lot of innovation from vmware in its 23 years you've been there the vast majority of that we've seen a lot of successful big tech waves ridden by vmware in april vmware pulled tanzu and vmware cloud foundation together vmware cloud you've got some exciting news with respect to that what are you announcing today well we got a lot of exciting announcements happening at vmworld this week but one of the ones i'm really excited about is vmware cloud with tons of services so let me talk about what these things are so we have vmware cloud which is really us taking our vmware cloud foundation technology and delivering that as a service in partnership with our public cloud providers but in particular this one with aws vmware cloud on aws we're combining that with our tanzu portfolio of technologies and these are really technologies focused at developers at folks driving devops building and operating modern applications and what we're doing is really bringing them together to simplify customers moving from their data centers into the cloud and then modernizing their applications it's a pattern that we see very very often this notion of migrate and then modernize right once you're on a modern cloud infrastructure makes it much easier to modernize your applications talk to me about some of the catalysts for this change and this offering of services was it you know catalyzed by some of the events we've seen in the world in the last 18 months and this acceleration of digital adoption yeah absolutely and we saw this across our customer base across many many different industries although as you can imagine those industries that that were really considered essential uh were the ones where we saw the biggest sorts of accelerations we saw a tremendous amount of people needing to support remote workers overnight right and cloud is a perfect use case for that but the challenge a lot of customers had was that they couldn't take the time to retool that they had to use what they already had and so something like vmware cloud was perfect for that because it allowed them to take what they were doing on-prem and seamlessly extend it into the cloud without any changes able to do that you know almost overnight right but at the same time what we also saw was the acceleration of their digital transformation people are now online they're needing to interact with an app over their phone to get something you know remotely delivered or to schedule maybe um an appointment for their pet because you know a lot of people got pets during the pandemic and so you just saw this rush toward digitization and these new applications need to be created and so as customers move their application estate into the cloud with vmware cloud and aws they then had this need to modernize those applications to be able to deliver them faster to respond fast to the very dynamic nature of what was happening during the pandemic so let's talk about uh some of the opportunities and the advantages that vmware cloud with tanzania service is going to deliver to those it admins who have to deliver things even faster yep so let me talk a bit about the tech and then talk about how that fits into uh what the users will experience so vmware cloud with tons of services is really two key components uh the first of which is the tanzu kubernetes grid service the tkg service as we call it so what this is is actually a deep integration of tonsil kubernetes grid with vmware cloud and and the kubernetes we've actually integrated into vmware cloud foundation folks who are familiar with vmware may remember that a couple of years ago we announced project pacific which was a deep integration of kubernetes into vsphere essentially enabling vsphere to have a kubernetes interface to be natively kubernetes and what that did was it enabled the i.t admins to have direct insight inside of kubernetes clusters to understand what was happening in terms of the containers and pods that that their developers were running it also allowed them to leverage uh their existing vsphere and vmware cloud foundation tooling on those workloads so fast forward today we we have this built in now and what we're doing is actually offering that as a service so that the customer doesn't need to deal with managing it installing it updating any of that stuff instead they can just leverage it they can start creating kubernetes clusters and upstream conformant kubernetes clusters to allow their developers to take advantage of those capabilities but also be able to use their native tooling on it so i think that's really really important is that the it admin really can enable their developers to seamlessly start to build and operate modern applications on top of vmware cloud got it and talk to me about how this is going to empower those it admins to become kubernetes operators yeah well i think that's exactly it you know we talk to a lot of these admins and and they're seeing the desire for kubernetes uh from their lines of business from you know from the app teams and the idea is that when you look start looking at the kubernetes ecosystem there's a whole bunch of new tooling and technology out there we find that people have to spend a lot of time figuring out what the right thing to use is and for a lot of these folks they say hey i've already figured out how to operate applications in production i've got the tooling i've got the standardization i got things like security figured out right super important and so the real benefit of this approach and this deep integration is it allows them to take those those tools those operational best practices that they already have and now apply them to these new workloads fairly seamlessly and so this is really about the power of leveraging all the investments they've made to take those forward with modern applications and the total adjustable market here is pretty big i heard your cto referring to that in an interview in september and i was looking at some recent vmware survey numbers where 80 of customers say they're deploying applications in highly distributed environments that include their own data center multiple clouds uh edge and also customers said hey 90 of our application initiatives are focused on modernization so vmware clearly sees the big tam here yeah it's absolutely massive um you know we see uh many customers the vast majority something like 75 percent are using multiple clouds or on-prem in the cloud we have some customers using even more than that and you see this very large application estate that's spread out across this and so you know i think what we're really looking at is how do we enable uh the right sorts of consistency both from an infrastructure perspective enabling things like security but also management across all these environments and by the way it's another exciting thing neglected to mention about this announcement vmware cloud with tonsil services not only includes the tonsil kubernetes grid service giving you that sort of kubernetes uh cluster as a service if you will but it also includes tons of mission control essentials and this is really the next generation of management when you start looking at modern applications and what tons of mission control focuses on is enabling managing kubernetes consistently across clouds and so this is the other really important point is that yes we want to make vmware cloud vmware cloud infrastructure the best place to build and operate applications especially modern ones but we also realize that you know customers are doing all sorts of things right they're in the native cloud whether that's aws or azure or google and they want ways of managing more consistently across all these environments in addition to their vmware environments both in the cloud and on-prem and so tons of mission control really enables that as well and that's another really powerful aspect of this is that it's built in to enable that next level of administration and management that consistency is critical right i mean that's probably one of the biggest benefits that customers are getting is that familiarity with the console the consistency of being able to manage so that they can deploy apps faster um that as businesses are still pivoting and changing direction in light of the pandemics i imagine that that is a huge uh from a business outcomes perspective the workforce productivity there is probably pretty pretty big yeah and i think it's also about managing risk as well you know one of the the biggest worries that we hear from many of the cios uh ctos executives that we talk to at our customers is this uh software supply chain risk like what is it exactly like what are the exact bits that they're running out there right in their applications because the reality is that um those apps are composed of many open source technologies and you know as we saw with solarwinds it's very possible for someone to get in and you know plant malicious code into their source repository such that as it gets built and flows out it'll you know just go out and customers will start using it and it's a huge huge security vulnerability and one thing on that note that customers are particularly worried about is the lack of consistency across their cloud environments that because things are done different ways and the different teams have different processes across different clouds it's easy for small mistakes to creep in there for little openings right that a hacker might be able to go and exploit and so i think this gets back to that notion of consistency and that you're right it's great for productivity but the one i think that's almost in some ways you might say uh for many of these folks more important for is from a security standpoint that they can validate and ensure they're in compliance with their security standards and by the way you know this is uh for most companies a board level discussion right the board is saying hey like do we have the right controls in place because it is um such an important thing and such a critical risk factor it is a critical risk factor we saw you mentioned solar winds but just in the last 18 months the the massive changes to the threat landscape the huge rise in ransomware and ddos attacks you know we had this scatterer everybody went home and you've got you know the edge is booming and you've got folks using uh you know not using their vpns and things when they should be so that the fact that that's a board level discussion and that this is going to help from a risk mitigation perspective that consistency that you talked about is huge i think for a customer in any industry yep yeah and it's pretty interesting as well like you mentioned ransomware so we're doing some work on that one as well actually not specifically with this announcement but it's another vmware cloud service that plugs into this uh seamlessly vmware cloud disaster recovery and one of the really cool features that we're announcing at vmworld this week is the ability to actually support and and maybe uh handle ransomware attacks and so the idea there is that if you do get compromised and what typically happens is that the hackers come in and they encrypt you know some of your data and they say hey if you want to get access to it you got to pay us and we'll decrypt it for you but if you have the right dr solution um that's backing up on a fairly continuous basis it means that whatever data might be encrypted you know would only be a small delta like the last let's say hour or two of data right and so what we're looking at is leveraging that dr solution to be able to very rapidly restore specific individual files uh that may have been compromised and so this is like one way that we're helping customers deal with that like obviously we want to put a whole bunch of other security protections in place and we do when we enable them to do that but one thing when you think about security is that it's very much defense in depth that you have multiple layers of the fail-safes there and so this one being kind of like the end result that hackers do get in they do manage to compromise it they do manage to get a hold of it and encrypt it well you still got unencrypted backups that you control and that you have um a very clean delineation and separation from just like kind of an architectural standpoint that the hackers won't be able to get at right so that you can control that and restore it so again you know this is something very top of mind for us and it's funny because we don't always lead with the security angle maybe we should as i'm saying it here but uh but it's something that's very very top of mind for a lot of our customers it's something that's also top of mind for us and that we're focused on it is because it's no longer if we get attacked it's one and they've got to be able to have the right recovery strategy so that they don't have to pay those ransoms and of course we only hear about the big ones like the solar winds and the colonial pipelines and there's many more going on when i get back to vmware cloud with tanzania services talk to me about how this fits into vmware's bigger picture yeah yeah yeah great question thanks for bringing me back i'd love to geek out on some of these things so um but when you take a step back so what we're really doing uh with vmware cloud is trying to provide this really powerful infrastructure layer uh that is available anywhere customers want to run applications and that could be in the public cloud it could be in the data center it could be at the edge it could be at all those locations and you know you mentioned edge earlier and i think we're seeing explosive growth there as well and so what we're really doing is driving uh broad optionality in terms of how customers want to adopt these technologies and then as i said we're sort of you know we're kind of going broad many locations we're also building up in each of those locations this notion of ponzu services being seamlessly integrated in doing that uh you know starting now with vmware cloud aws but expanding that to every every location that we have in addition you know we're also really excited another thing we're announcing this week called project arctic now the idea with arctic is really to start driving more choice and flexibility into how customers consume vmware cloud do they consume it as software or as a service and where do they do that so traditionally the only way to get it delivered as a service would be in the public cloud right vmware cloud aws you can click a few buttons and you get a software defined data center set up for you automatically now traditionally on-prem we haven't had that we we did do something pretty powerful uh a year or two back with the release of vmware cloud on dell emc we can deliver a service there but that often required new hardware you know new setup for customers and customers are coming back to us and saying hey like we've got these really large vsphere deployments how do we enable them to take advantage of all this great vmware cloud functionality from where they are today right they say hey we can't rebuild all these overnight but we want to take advantage of vmware cloud today so that's what really what project arctic is focused on it's focused on connecting into these brownfield existing vsphere environments and delivering some of the vmware cloud benefits there things like being able to easily well first of all be able to manage those environments through the vmware cloud console so now you have one place where you can see your on-prem deployments your cloud deployments everything being able to really easily move uh applications between on-prem and the cloud leveraging some of the vmware cloud disaster recovery capabilities i just mentioned like the ransomware example you can now do that even on prem as well because keep in mind it's people aren't attacking you know the hackers aren't attacking just the public cloud they're attacking data centers or anywhere else where these applications might be running and so arctic's a great example of where we're saying hey there's a bunch of cool stuff happening here but let's really meet customers where they're at and many of our customers still have a very large data center footprint still want to maintain that that's really strategic for them or as i said may even want to be extending to the edge so it's really about giving them more of that flexibility so in terms of meeting customers where they are i know vmware has been focused on that for probably its entire history we talk about that on the cube in every vmworld where can customers go like what's the right starting point is this targeted for vmware cloud on aws current customers what's kind of the next steps for customers to learn more about this yeah absolutely so there's a bunch of different ways so first of all there's a tremendous amount of activity happening here at vmworld um just all sorts of breakout sessions like you know detailed demos like all sorts of really cool stuff just a ton of content i'm actually kind of i'm in this new role i'm super excited about it but one thing i'm kind of bummed out about is i don't have as much time to go look at all these cool sessions so i highly recommend going and checking those out um you know we have hands-on labs as well which is another great way to test out and try vmware products so hold.vmware.com uh you can go and spin those things up and just kind of take them for a test drive see what they're all about and then if you go to vmc.vmware.com that is vmware cloud right we want to make it very easy to get started whether you're in just a vsphere on-prem customer or whether you already have vmware cloud and aws what you can see is that it's really easy to get started in that there's a ton of value-add services on top of our core infrastructure so it's all about making it accessible making it easy and simple to consume and get started with so there's a ton of options out there and i highly recommend folks go and check out all the things i just mentioned excellent kit thank you for joining me today talking about vmware cloud with tons of services what's new what's exciting the opportunities in it for customers from the i.t admin folks to be empowered to be kubernetes operators to those businesses being able to do essential services in a changing environment and again congratulations on your promotion that's very exciting awesome thank you lisa thank you for having me our pleasure for kit colbert i'm lisa martin you're watching thecube's coverage of vmworld 2021 [Music] you

>> Viewers of our breaking analysis series know that we've been following the developments in cybersecurity for a number of years and of course, throughout the pandemic. Focusing on the permanent shifts that we see in cyber from remote work, distributed computing and technology advancements. We've reported how the adversaries are highly capable they're well-funded and they're motivated. And how they're constantly upping their game on defenders, island hopping, stealthily living off the land, planting self forming malware at various points in the digital supply chain, offering advanced ransomware as a service of the dark web to any disreputable individual with or without a high school diploma that may have access to a server and is brazen enough to steal from their company. We've also shared this chart from Optiv many, many times, it's a taxonomy of the cybersecurity landscape, and it is meant to make your eyes bleed, ask any CSO and they'll tell you they're drowning in fragmented tooling, technical debt, and their number one challenge is lack of talent. Not that their people aren't capable, they are, but CSOs just don't have enough of them. They can't hire fast enough or they can't retain qualified people with the talent war that's going on. Or they can't train people fast enough, or they just don't have the budget. Hello everyone, this is Dave Vellante and welcome to this video exclusive with Nick Schneider, president and CEO of Arctic Wolf Networks, Nick, so good to see you. Thanks for coming on the cube. >> Thanks for having me, Dave. >> That's our pleasure. So Arctic Wolf networks, let's talk about the company, the problem, you heard my little narrative upfront. What are you guys all about? >> Yeah, so at its core, we're a cybersecurity technology company. You know, it's our belief that we've really pioneered the first full scale cloud native security operations platform and at its core, what we're trying to do as a business is make security operations something that's fast, easy and economical for really a company of any size and scale to implement with really two key components, one we're agnostic to the technology and the landscape of the technology that they have already implemented within their environment, and two, we can feather into really any organization, regardless of the skill set they have from a cybersecurity standpoint in house. And really the problem that we're setting out to solve, I think you illustrated well at the beginning of the show here is that it's our belief that the cybersecurity industry in a sense has failed the end user or failed the customer by throwing, you know, a myriad of different tools at them. And it's really, you know, our mission here as a company to end cyber risk. And it's our belief that through the cloud native platform that we've bought in the cybersecurity security operations cloud that we've built, that we can deliver the outcomes that have been promised over time to these customers, which at the end of the day, is really just to be safe and have their customer and have their business protected. >> So you guys are the experts. You can kind of provide a white glove service that essentially plugs in to my business. Is that right? And how easy is that to do, what do I have to do to, to set it up? How complicated is that for me, the customer? >> Yeah, so it's, it's very straightforward. We can implement our security operations platform, you know, in as short as a week and generally speaking, you know, about a month and we plug in really to the infrastructure that the customer has in place. And for some of our customers, that's very little and for some of our customers, most of our customers, that's quite a bit of technology. And the beauty of the way that we've built the platform is that we're really agnostic to that tech. So, we can take feeds from kind of any technology that are in place, that helps to augment the platform that we've built. And then we feather in kind of the technologies that we've built within the platform, into their existing infrastructure. And at the end of the day, what we're trying to do is give the customer visibility, you know, into the tools that they have, the gaps that they might have as a result of the tools, you know, in some cases, the duplication of efforts that they have, you know, between these tools and then deliver a security outcome or a protection that maybe they haven't otherwise felt as a business. And then outside of kind of the technology platform, we add what we call our concierge security team as a layer to the deliverable that we give to the customer. And why that's important is that not all customers are created equal and with regard to the skillset that they have in house, in that that concierge security platform allows us to kind of work with a customer at any kind of, you know, point along their security journey, regardless of the in-house technology talent that they have. >> Now, so I got to ask you, our largest footprint for the cube is in the heart of Silicon Valley. We love the valley, but I also love stories of high growth companies that are outside of Silicon Valley. You guys are in the Midwest in Minnesota, it's got some Compellent DNA in there. And I remember my, so my business friends, Phil Soren, and Larry Yasmin, you know them, Phil used to tell me, Dave, this is actually an advantage for us to be in the middle of the part of the country. There's a talent war going on, which back then was a lot less than it is today, even. So how do you see that? Are there advantages to you and being in that part of the country, or does it not matter because you're so distributed around the world? >> Yeah, I mean, I would follow a similar tune to Phil, right. I, you know, obviously worked at Compellent early and, you know, historically I've worked at other Minneapolis based technology companies and the reality is there's a really strong technology ecosystem in Minneapolis. And a lot of the, of the talent, you know, is not just in sales and marketing or just on the technical side, but it's in building high growth technology companies kind of from the ground up into, you know, large scale. And now we've seen not only the fortune 500 kind of base that we have here in Minneapolis, but also a growing contingency of larger technology companies using Minneapolis as at least, you know, one of the spokes against their hub, if not the hub themselves. And clearly my pedigree in history was out of Minneapolis based tech, you know, and I've moved to other locations throughout the country, but as we started to build out, you know, Arctic Wolf and what we wanted Artic Wolf's culture to look like, and as we started to lay out the foundation for what we wanted our growth to look like, it became very clear to myself, you know, our chairman and co-founder Brian Nesmith, that Minneapolis would be a great home for us as Arctic Wolf. And then we would continue to invest in some of the locations that we have, you know, both across the country and now across the globe. >> So there are a lot of companies that are doing managed security services, but if I got it right, you guys specifically target smaller and midsize companies, is that correct? And why is that? >> Yeah, so I would say that that would be correct as of a few years ago, the dynamic has changed quite a bit. And I think it's a result of the dynamic of the market. First and foremost, we are a technology company. We have this concierge layer on top, which is really what the customers are looking for, but it's all powered by the platform. So the platform kind of allows us to do what we've done as a business, into both small organizations, which is, you know, where we probably got our start, but over the last few years, we've seen tremendous growth up market, you know, so for example, we as a business have grown, you know, over a hundred percent now for eight years in a row and now on a much larger denominator, but our upmarket business is growing at four to 500%. And I think that's a result of really two things. I think, A, customers of that size and scale have realized that cyber security and cybersecurity operations as a problem is something that's really hard to accomplish in-house regardless of your size and complexity. And then two, I think what happened over the past year, year and a half is that we saw a lot of organizations move from a centralized I.T or a centralized, you know, security function where they could all operate within an office and all operate in a centralized environment, all of a sudden becoming very disparate in their geography. And that led to a lot more interest in what we did with larger customers, because we could deploy a security operation effectively, remotely in a really short amount of time. And we could do it more effectively and economically than, than they could do on their own. And then we also solve for a component of the human aspect of what a security operation means, right. And what I mean by that is these larger organizations can take their highly skilled cybersecurity talent and focus them on the strategic initiatives within the company. Whereas a lot of the security work or risk is in kind of the day to day, right? The dieting that takes place within an organization. And that's where a lot of the breaches take place is in making sure that you're actually paying attention to, you know, the alerts that you're getting and paying attention to the telemetry and the tools that you've made investments in. And we augment that portion of a cybersecurity operation really, really well for larger organizations and for smaller organizations, we are that security operation. So it's kind of dependent on the way in which they're set up. >> Okay. So it's a mix of both well augmenting, and basically you take the whole thing and so, so your ideal customer profile, your ICP is anybody with a security problem. I mean, that's everybody, well, maybe you could describe paint a picture of your perfect customer, if you would. >> Yeah, so, and you, I know you said that somewhat jokingly, but it, but it is true. We have customers of all sizes, you know, so I, I bet our smallest customer is under 10 employees. Our largest customer is over 50,000 employees. We have customers in every vertical of the market, you know, mostly centralized in healthcare, financial organizations, manufacturing, but, you know, the largest swath of customers by industry would probably not top 10%. So, we service really any account that's looking to develop and invest in a security operation and has the support of their organization and the support of their board and their leadership teams to make that investment. And then where we, where we fall within the account is really dependent on the way in which their current operation is set up. And certainly, you know, the massive organizations that have, you know, 50 people within their cybersecurity team, and they have a hundred different tools. They're probably not the best target for us, but if they have security awareness, if they have a security as a top need or a top priority within their business, and they're looking for a way to build out a true security operation within their account, whether that be wholesale through a third-party or in part through a third-party, we're a perfect fit for all those accounts, which makes our addressable market massive. >> Yeah, so what's unique about you guys, I mean, this may be not the right analogy, but you're kind of like the easy button for cyber. I mean, there's nothing easy about cyber., I get that, but you, you do make it easy, especially for companies that don't have any cyber expertise to engage and get up to speed fast, and certainly be more protected. That's one aspect of your uniqueness. The other is, I think, is your tech stack. I'm hearing, you've got a platform. I know you're focused on network detection and fast response. Maybe you could talk a little bit about what's unique about Arctic Wolf. >> Yeah, so the platform itself is really what we founded the company on. So we spent the first few years of our organization in really building out this cloud scale, multitenant cloud, native platform, understanding that the volume of data and the amount of sophistication that we would need to deliver the security operation in the long run was going to be massive. So the platforms really kind of, you know, set on a few different founding principles. One, the platform needs to work for any organization regardless of their size, regardless of their underlying tech and regardless of the skill set within their account. And that's really important. A lot of the tools in the market today require certain things of the, of the customer. And it's our premise, regardless of the customer that we won't require anything from the customers themselves. It's up to them to tell us which portions of the experience they want to own, verse Artic Wolf owning. The second would be that we need to be able to ingest a vast amount of data, and we need to be able to make intelligent decisions with that data, in a short amount of time. And as we've built out our machine learning and our AR algorithms, what we've been able to do is leverage a tool set that allows us to ingest. I think we're up to now 1.5 approaching 2 trillion observations a week, right. Which might equate to a few hundred alerts within our SOC on a per customer basis. But we're only bringing one or two things to a customer on a weekly basis that really need attention. And that's all about the platform kind of curating, cultivating the vast amount of data that we've brought into it. And then, how do we explain and how do we sell that platform with this concierge later into the customer base is also important. And we've done that through what we call modules. So we kind of founded the company on MDR managed detection and response, but we are not a managed detection and response company. It's one of our modules. We've then added manage risk, which competes kind of in the vulnerability management space. We've added a SAS and IAS monitoring, which is really cloud security. We've added what we call log search, which is really our first foray into collaboration. And then we just recently launched a quarter ago, what we call managed security awareness training, which is, you know, training the human aspect of the company on the threats of cybersecurity. And we actually just announced another acquisition in the managed security space today with habituate, which is going to give us, you know, kind of a Hollywood style approach to content within managed awareness training. But tying all those together is very unique in the market. So generally speaking, you'll see a company focused on a specific attack surface, or a specific threat. And what we're trying to say is, look, you're not a hundred percent protected as a business, or you don't have a robust security operation unless you're bringing together all aspects of cybersecurity under one umbrella. And that's really our goal as a company. >> Okay. So you got all these different modules and you may not want to go here cause you're in the cyber business and you're, you're prudently secretive, but, but I'm interested in kind of what's underneath. I presume you're using best of breed tooling underneath, but unlike, you know, the hosting company of the past or those, you know, a big, you know, integrator who could do this, but they've got one of everything and it's sort of, kind of a mess. You're building a scalable business, but you're not, you're not developing, you know, best of breed, identity access products for the marketplace. You're I presume you're buying those in integrating them and working through whatever APIs and making it all work across your stack. Can you talk a little bit about your tech stack? >> Yeah, so the technology stack has been built from the ground up by Arctic Wolf. So certainly we're using, you know, various technologies or open source technologies from within the ecosystem, but the technology and the platform itself is Arctic Wolf. So we're not beholden to any third parties for what we deliver to the customer. And that makes us very nimble in a few areas. One, it makes us very nimble in the way that we price the solution to the customer, which for us is a very predictable model. And then two, it allows us to be nimble with customer needs as to what they want from us, both of the existing modules that we have, but also additional modules or, you know, additional solutions that we might bring to the market. So a lot of vendors that have historically kind of lived within the MDR space and certainly vendors that have lived in the managed, you know, the MSSP or MSP space, which we are certainly not, they're generally leveraging third-party technologies. They're generally buying and implementing or white labeling third-party technologies. And then they're layering kind of a services component on top. And we are not doing that. We've built the technology ourselves and don't get me wrong. That was a massive investment in both time and resources. But I think in the end, what it'll allow us to do is be very nimble with the market and most importantly, be very nimble with the customer's requirements and requests. >> Right. Okay. So let's talk about your market opportunity. I mean, the cyberspace, I mean, I got it well over a hundred billion, I don't know, maybe it's 110, 120 billion. That's kind of your tan, you may be not serving that entire market today. Although you said you started in small and mid-size, you're targeting now your enterprise, your higher end businesses growing, you talked about, I think you said a hundred percent growth, like eight quarters in a row. And so there's no shortage of opportunity for you. How do you think about your total available market? Maybe you could add some color to that. >> Yeah. Yeah. So it's been eight years of a hundred percent growth. >> Eight years, not eight quarter, I apologize. >> It's been going really well for us. And it's a reflection on the market itself and the approach we're taking. So in our view, security operations is really the opportunity to unify all these disparate markets in cybersecurity. And, when I walk into a customer account, if I had to use two words to describe how they're feeling, one would be confused, the other would be frustrated. Sometimes they're both. Sometimes they're only one, but generally speaking, one of those two words comes out of their mouth. And the reason for it is at the end of the day, they just want to be protected. They want the outcome. And all of these disparate markets are promising the same outcome, but they're just promising it on the endpoint or just on the network or just in cloud or just an IOT or just an OT, or just in fill in the blank. And it's our view that it's our opportunity as a company to really fill that void for the customer, which is to unify all of these different technologies and spaces into one security operation. And sometimes that means that we're delivering our own end point. And sometimes that means that we're leveraging an end point or an end point solution that the customer has in house. And we're ingesting that data into our platform and we're making sense of it to the end user. But when you put that market together, you know, it's a hundred, I think Gartner's recent numbers there are 150 plus billion dollar market. And in 2021, I think it's growing at, you know, 12 to 15%. And it's our view that we can service the majority of that market, you know, I think on a conservative measure, you know, 90 to a hundred billion is the, is the Tam that we're addressing. And we're now starting to go, not only scaling out from the number of products for the markets that we service, and you can see that through managed security awareness training, but also the geographies we service, the segments of the market we service, specialization within verticals. And, for us, that is the opportunity at the end here. >> I wonder if you could help us squint through some of the data you hear in the industry, some of the trends you see in the press, certainly this came up in the, in the solar winds hack. We were seeing, I mentioned upfront, the adversaries are very capable. They're able to get in, live off the land, live stealthily, they're island hopping into the supply chain. You know, oftentimes you don't know, more than often, you don't know they're there, I've heard stats like, and we look at the solar winds hack, we saw that it was, you know, 300 days or over a year that they were inside the company. And you've heard, you know, average statistics from, you know, whatever that it's hundreds of days are those, are you able to compress those? Can you talk about that a little bit in terms of where you see your customers and how you're helping them, you know, respond? >> Yeah, so at the end of the day, you know, cybersecurity, the industry is really about limiting the volume of incidents within a customer account and then limiting the impact. And what you're talking about is the impact. And the impact as these threat actors have become, you know, more sophisticated is larger as they're in the environment for a longer period of time. So the faster you can get to an attack or the faster you can detect an attack, the better off you'll be as a business. And that is the core of what we do as a company. And, and certainly, you know, managed detection response or MDR, our first offering was all about that. It's all about detecting early and responding early to a threat so that you can get anything that has gotten through your perimeter defenses out of your systems, as fast as humanly possible. And then we feathered in, you know, manage risk, which is more about the front end. So how do we make sure that we have everything configured properly? How do we make sure that we, you know, fill any holes that are in the current environment so that we don't even get to a point where we have to manage the time with which an attack has had to live within your environment? So, it's all about kind of those two things, reduce the frequency and reduce the impact. And we're, we're focused on both, both the, kind of the proactive measures, which would be more on the front end and then the reactive measures, which is what do you do and how can you act as quickly as possible within your environment to ensure that, you know, they're not getting into the crown jewels of the business. >> We've seen lately where the, the attackers have. I mean, it's really insidious, right Nick, they, they will exfiltrate, they'll get in they'll exfiltrate stealthily and they'll be ready to attack from a ransomware standpoint. And then they, you know, maybe they're hitting the bank and they're scouring to see what the Chief Information Officer is going to invest in. And they're actually making trades ahead of that. They're making more money, you know, snooping than from the ransomware. And then when the company realizes and they respond, then they get them in a headlock and say, okay, now, now that you're going to stop us from making all this money through exfiltration, we're going to hit you with ransomware. So it's just, it's a really awful situation. So my point being that, or we've said, organizations have to be stealthy in their response. Have you seen that as a trend? Am I overstating that? >> No, no. I mean, customers are, you know, good news, bad news customers are very aware of the threats in particular ransomware, data exfiltration and all the other trends in the market. And I think they become more sophisticated in the way in which they respond. And I think as a result, we've seen both changes in the way customers kind of set up their environment technologically, but we've also seen a pretty dramatic shift recently with the way in which they view insurance and the way in which, you know, carriers, view insurance, and how that plays a role in, you know, cybersecurity in their cybersecurity operation. And for a lot of customers, I think recent trends are that the carriers are struggling to, you know, make money on their cyber books. And the reason for that is because they need to make sure that the customer's environment is truly secure, or they're kind of flying blind on what their book looks like. And we've started to see that both on the end-user side, we've seen that through the carriers themselves, and that also has played an integral role in the way in which the customer views risk. And I think that dynamics changing. And I think what the result of that will be is that customers are going to be looking more and more towards how they solve this problem by alleviating risk in-house, as opposed to transferring some of that risk to an insurance carrier or a third party. And what I hope that means for customers is that they'll have the proper investment. They'll have the proper tooling, they'll have the proper operations around how to react and how to respond in the quickest possible manner, which at the end of the day, the faster you can react to an incident, the smaller the impact will be and the smaller of a financial burden it will be. And they'll do that through vendors like Arctic Wolf, you know, tools that are best of breed within their infrastructure. And then a really well thought out plan about how to respond to anything that, that you know, happens within their environment. >> Yeah. I mean, if I'm an insurance company, I give a discount to somebody who's got an alarm in their house and they use it. Maybe I'll give a discount if they're working with a company like Arctic Wolf. >> Exactly. >> What percent, do you have a census to what percent of enterprises actually have a SOC? >> Yeah, we actually did a, some homework here and there's kind of two stats that jump out. And these are through a few different surveys through very well-known organizations in the cybersecurity market. But one is that last year, which would have been, you know, 2020, about 60% of organizations said that they suffered some semblance of a breach, 60%, you know, think about how many tools and how much money these organizations are investing in protecting their businesses. And over half are suffering some semblance of a breach. When those same customers are asked whether or not they felt like they have a security operation, over 99% answered no. >> Wow. >> Right. So they have a bunch of tools they're investing a ton of money, but at the end of the day, when asked, hey, do you feel like you have an operation that can protect your business? Their answer is no. And that's really the void we're trying to. >> And you and I both know that 60%, okay. But then the other 40%, they've been hacked. They just don't know it. So, all right. Let's wrap with the sub stats on the company. I think you've raised nearly half a million, half a billion dollars to date $500 million to date. So that's, I can infer from that some pretty lofty numbers, but where are you in funding with that kind of growth? I got to believe IPO is and you and your future. What can you tell, what metrics can you share? What can you tell us about where you want to take this thing? >> Yeah, so I'll give you a few metrics on the platform and a few metrics on the company. So the platform itself, you know, we're observing over 1.5 trillion observations a week, we have 10,000 plus sensors in the field. You know, we're ingesting coming from a, you know, Compellent infrastructure guy. You know, we're in ingesting over a petabyte and a half a data week. I would have loved to have been that sales guy in the glory days, you know, but the platforms, you know, operating at massive scale, we've grown the business eight years in a row, over a hundred percent. We've talked about that. Our subscription gross margins are very software-like. We have over 2000 customers. You know, our customers are really happy with an NPS score, you know, approaching 70, you know, over a million licensed users. So we're, we're doing very, very well as a business. And as a result, we've raised money to invest in that growth, which is to the tune of about a half a billion dollars and our path here, and we've stated this publicly now is that, you know, next summer give or take a quarter is really the timeframe that we're marching towards for an IPO. If I'm being honest, given the metrics that we have as a business, we could be a publicly traded company today, especially with the way the market's operating in the valuations of some of the businesses that have gone out. There might be some, even some pressure to do so, but we want to make sure that we are ready to go from a systems and an operation standpoint to not just be, you know, a flashing the pan awesome IPO, but a company that's really kind of the backbone of cybersecurity for years to come. >> Well, obviously a hot space. What we've been covering for a couple of years now, Okta, CrowdStrike, Zscaler, we've seen what's happened in the action in the market there. I mean, what are your comps? I mean, I know, I think dark trace is getting ready to go. I don't think they've gone yet. I know Sentinel One went out. How should we think about you? You're not an Okta or I don't think well, CrowdStrike, but you know, those are pure play product companies. How should we think about you guys? >> Yeah, I mean, companies that were on a similar trajectory as us at our size, Sentinel One's a very good example. And you can kind of look across all the core business metrics on that. And clearly those will all be public here in under a year. CrowdStrike's a great example. If you go, you know, reel back the tape to when they were, you know, our size we're right in line with them Zscaler, Okta, you know, I joke with our board and investors and our CFO, that the number of companies that we benchmark ourselves against is starting to become a very small number, given you know, our growth at the scale that we're at. >> Well, that's an awesome story, Nick. We're really excited that you could make some time to come on the Cube and we want to follow your progress. Welcome you back anytime. Really appreciate your time. >> Yeah. Great. Thanks for having me, Dave, and looking forward to continuing the conversation at some point. >> Excellent and thank you for watching everybody. This is Dave Vellante for the Cube and we'll see you next time.

>> Hi, I'm Natalie Ehrlich and welcome to the AWS startup showcase presented by The Cube. We have an amazing lineup of great guests who will share their insights on the latest innovations and solutions and leveraging cloud scale data in AI, security and life sciences. And now we're joined by the co-founders and co-CEOs of The Cube, Dave Vellante and John Furrier. Thank you gentlemen for joining me. >> Hey Natalie. >> Hey Natalie. >> How are you doing. Hey John. >> Well, I'd love to get your insights here, let's kick it off and what are you looking forward to. >> Dave, I think one of the things that we've been doing on the cube for 11 years is looking at the signal in the marketplace. I wanted to focus on this because AI is cutting across all industries. So we're seeing that with cybersecurity and life sciences, it's the first time we've had a life sciences track in the showcase, which is amazing because it shows that growth of the cloud scale. So I'm super excited by that. And I think that's going to showcase some new business models and of course the keynotes Ali Ghodsi, who's the CEO Data bricks pushing a billion dollars in revenue, clear validation that startups can go from zero to a billion dollars in revenues. So that should be really interesting. And of course the top venture capitalists coming in to talk about what the enterprise dynamics are all about. And what about you, Dave? >> You know, I thought it was an interesting mix and choice of startups. When you think about, you know, AI security and healthcare, and I've been thinking about that. Healthcare is the perfect industry, it is ripe for disruption. If you think about healthcare, you know, we all complain how expensive it is not transparent. There's a lot of discussion about, you know, can everybody have equal access that certainly with COVID the staff is burned out. There's a real divergence and diversity of the quality of healthcare and you know, it all results in patients not being happy, and I mean, if you had to do an NPS score on the patients and healthcare will be pretty low, John, you know. So when I think about, you know, AI and security in the context of healthcare in cloud, I ask questions like when are machines going to be able to better meet or make better diagnoses than doctors? And that's starting. I mean, it's really in assistance putting into play today. But I think when you think about cheaper and more accurate image analysis, when you think about the overall patient experience and trust and personalized medicine, self-service, you know, remote medicine that we've seen during the COVID pandemic, disease tracking, language translation, I mean, there are so many things where the cloud and data, and then it can help. And then at the end of it, it's all about, okay, how do I authenticate? How do I deal with privacy and personal information and tamper resistance? And that's where the security play comes in. So it's a very interesting mix of startups. I think that I'm really looking forward to hearing from... >> You know Natalie one of the things we talked about, some of these companies, Dave, we've talked a lot of these companies and to me the business model innovations that are coming out of two factors, the pandemic is kind of coming to an end so that accelerated and really showed who had the right stuff in my opinion. So you were either on the wrong side or right side of history when it comes to the pandemic and as we look back, as we come out of it with clear growth in certain companies and certain companies that adopted let's say cloud. And the other one is cloud scale. So the focus of these startup showcases is really to focus on how startups can align with the enterprise buyers and create the new kind of refactoring business models to go from, you know, a re-pivot or refactoring to more value. And the other thing that's interesting is that the business model isn't just for the good guys. If you look at say ransomware, for instance, the business model of hackers is gone completely amazing too. They're kicking it but in terms of revenue, they have their own they're well-funded machines on how to extort cash from companies. So there's a lot of security issues around the business model as well. So to me, the business model innovation with cloud-scale tech, with the pandemic forcing function, you've seen a lot of new kinds of decision-making in enterprises. You seeing how enterprise buyers are changing their decision criteria, and frankly their existing suppliers. So if you're an old guard supplier, you're going to be potentially out because if you didn't deliver during the pandemic, this is the issue that everyone's talking about. And it's kind of not publicized in the press very much, but this is actually happening. >> Well thank you both very much for joining me to kick off our AWS startup showcase. Now we're going to go to our very special guest Ali Ghodsi and John Furrier will seat with him for a fireside chat and Dave and I will see you on the other side. >> Okay, Ali great to see you. Thanks for coming on our AWS startup showcase, our second edition, second batch, season two, whatever we want to call it it's our second version of this new series where we feature, you know, the hottest startups coming out of the AWS ecosystem. And you're one of them, I've been there, but you're not a startup anymore, you're here pushing serious success on the revenue side and company. Congratulations and great to see you. >> Likewise. Thank you so much, good to see you again. >> You know I remember the first time we chatted on The Cube, you weren't really doing much software revenue, you were really talking about the new revolution in data. And you were all in on cloud. And I will say that from day one, you were always adamant that it was cloud cloud scale before anyone was really talking about it. And at that time it was on premises with Hadoop and those kinds of things. You saw that early. I remember that conversation, boy, that bet paid out great. So congratulations. >> Thank you so much. >> So I've got to ask you to jump right in. Enterprises are making decisions differently now and you are an example of that company that has gone from literally zero software sales to pushing a billion dollars as it's being reported. Certainly the success of Data bricks has been written about, but what's not written about is the success of how you guys align with the changing criteria for the enterprise customer. Take us through that and these companies here are aligning the same thing and enterprises want to change. They want to be in the right side of history. What's the success formula? >> Yeah. I mean, basically what we always did was look a few years out, the how can we help these enterprises, future proof, what they're trying to achieve, right? They have, you know, 30 years of legacy software and, you know baggage, and they have compliance and regulations, how do we help them move to the future? So we try to identify those kinds of secular trends that we think are going to maybe you see them a little bit right now, cloud was one of them, but it gets more and more and more. So we identified those and there were sort of three or four of those that we kind of latched onto. And then every year the passes, we're a little bit more right. Cause it's a secular trend in the market. And then eventually, it becomes a force that you can't kind of fight anymore. >> Yeah. And I just want to put a plug for your clubhouse talks with Andreessen Horowitz. You're always on clubhouse talking about, you know, I won't say the killer instinct, but being a CEO in a time where there's so much change going on, you're constantly under pressure. It's a lonely job at the top, I know that, but you've made some good calls. What was some of the key moments that you can point to, where you were like, okay, the wave is coming in now, we'd better get on it. What were some of those key decisions? Cause a lot of these startups want to be in your position, and a lot of buyers want to take advantage of the technology that's coming. They got to figure it out. What was some of those key inflection points for you? >> So if you're just listening to what everybody's saying, you're going to miss those trends. So then you're just going with the stream. So, Juan you mentioned that cloud. Cloud was a thing at the time, we thought it's going to be the thing that takes over everything. Today it's actually multi-cloud. So multi-cloud is a thing, it's more and more people are thinking, wow, I'm paying a lot's to the cloud vendors, do I want to buy more from them or do I want to have some optionality? So that's one. Two, open. They're worried about lock-in, you know, lock-in has happened for many, many decades. So they want open architectures, open source, open standards. So that's the second one that we bet on. The third one, which you know, initially wasn't sort of super obvious was AI and machine learning. Now it's super obvious, everybody's talking about it. But when we started, it was kind of called artificial intelligence referred to robotics, and machine learning wasn't a term that people really knew about. Today, it's sort of, everybody's doing machine learning and AI. So betting on those future trends, those secular trends as we call them super critical. >> And one of the things that I want to get your thoughts on is this idea of re-platforming versus refactoring. You see a lot being talked about in some of these, what does that even mean? It's people trying to figure that out. Re-platforming I get the cloud scale. But as you look at the cloud benefits, what do you say to customers out there and enterprises that are trying to use the benefits of the cloud? Say data for instance, in the middle of how could they be thinking about refactoring? And how can they make a better selection on suppliers? I mean, how do you know it used to be RFP, you deliver these speeds and feeds and you get selected. Now I think there's a little bit different science and methodology behind it. What's your thoughts on this refactoring as a buyer? What do I got to do? >> Well, I mean let's start with you said RFP and so on. Times have changed. Back in the day, you had to kind of sign up for something and then much later you're going to get it. So then you have to go through this arduous process. In the cloud, would pay us to go model elasticity and so on. You can kind of try your way to it. You can try before you buy. And you can use more and more. You can gradually, you don't need to go in all in and you know, say we commit to 50,000,000 and six months later to find out that wow, this stuff has got shelf where it doesn't work. So that's one thing that has changed it's beneficial. But the second thing is, don't just mimic what you had on prem in the cloud. So that's what this refactoring is about. If you had, you know, Hadoop data lake, now you're just going to have an S3 data lake. If you had an on-prem data warehouse now you just going to have a cloud data warehouse. You're just repeating what you did on prem in the cloud, architected for the future. And you know, for us, the most important thing that we say is that this lake house paradigm is a cloud native way of organizing your data. That's different from how you would do things on premises. So think through what's the right way of doing it in the cloud. Don't just try to copy paste what you had on premises in the cloud. >> It's interesting one of the things that we're observing and I'd love to get your reaction to this. Dave a lot** and I have been reporting on it is, two personas in the enterprise are changing their organization. One is I call IT ops or there's an SRE role developing. And the data teams are being dismantled and being kind of sprinkled through into other teams is this notion of data, pipelining being part of workflows, not just the department. Are you seeing organizational shifts in how people are organizing their resources, their human resources to take advantage of say that the data problems that are need to being solved with machine learning and whatnot and cloud-scale? >> Yeah, absolutely. So you're right. SRE became a thing, lots of DevOps people. It was because when the cloud vendors launched their infrastructure as a service to stitch all these things together and get it all working you needed a lot of devOps people. But now things are maturing. So, you know, with vendors like Data bricks and other multi-cloud vendors, you can actually get much higher level services where you don't need to necessarily have lots of lots of DevOps people that are themselves trying to stitch together lots of services to make this work. So that's one trend. But secondly, you're seeing more data teams being sort of completely ubiquitous in these organizations. Before it used to be you have one data team and then we'll have data and AI and we'll be done. ' It's a one and done. But that's not how it works. That's not how Google, Facebook, Twitter did it, they had data throughout the organization. Every BU was empowered. It's sales, it's marketing, it's finance, it's engineering. So how do you embed all those data teams and make them actually run fast? And you know, there's this concept of a data mesh which is super important where you can actually decentralize and enable all these teams to focus on their domains and run super fast. And that's really enabled by this Lake house paradigm in the cloud that we're talking about. Where you're open, you're basing it on open standards. You have flexibility in the data types and how they're going to store their data. So you kind of provide a lot of that flexibility, but at the same time, you have sort of centralized governance for it. So absolutely things are changing in the market. >> Well, you're just the professor, the masterclass right here is amazing. Thanks for sharing that insight. You're always got to go out of date and that's why we have you on here. You're amazing, great resource for the community. Ransomware is a huge problem, it's now the government's focus. We're being attacked and we don't know where it's coming from. This business models around cyber that's expanding rapidly. There's real revenue behind it. There's a data problem. It's not just a security problem. So one of the themes in all of these startup showcases is data is ubiquitous in the value propositions. One of them is ransomware. What's your thoughts on ransomware? Is it a data problem? Does cloud help? Some are saying that cloud's got better security with ransomware, then say on premise. What's your vision of how you see this ransomware problem being addressed besides the government taking over? >> Yeah, that's a great question. Let me start by saying, you know, we're a data company, right? And if you say you're a data company, you might as well just said, we're a privacy company, right? It's like some people say, well, what do you think about privacy? Do you guys even do privacy? We're a data company. So yeah, we're a privacy company as well. Like you can't talk about data without talking about privacy. With every customer, with every enterprise. So that's obviously top of mind for us. I do think that in the cloud, security is much better because, you know, vendors like us, we're investing so much resources into security and making sure that we harden the infrastructure and, you know, by actually having all of this infrastructure, we can monitor it, detect if something is, you know, an attack is happening, and we can immediately sort of stop it. So that's different from when it's on prem, you have kind of like the separated duties where the software vendor, which would have been us, doesn't really see what's happening in the data center. So, you know, there's an IT team that didn't develop the software is responsible for the security. So I think things are much better now. I think we're much better set up, but of course, things like cryptocurrencies and so on are making it easier for people to sort of hide. There decentralized networks. So, you know, the attackers are getting more and more sophisticated as well. So that's definitely something that's super important. It's super top of mind. We're all investing heavily into security and privacy because, you know, that's going to be super critical going forward. >> Yeah, we got to move that red line, and figure that out and get more intelligence. Decentralized trends not going away it's going to be more of that, less of the centralized. But centralized does come into play with data. It's a mix, it's not mutually exclusive. And I'll get your thoughts on this. Architectural question with, you know, 5G and the edge coming. Amazon's got that outpost stringent, the wavelength, you're seeing mobile world Congress coming up in this month. The focus on processing data at the edge is a huge issue. And enterprises are now going to be commercial part of that. So architecture decisions are being made in enterprises right now. And this is a big issue. So you mentioned multi-cloud, so tools versus platforms. Now I'm an enterprise buyer and there's no more RFPs. I got all this new choices for startups and growing companies to choose from that are cloud native. I got all kinds of new challenges and opportunities. How do I build my architecture so I don't foreclose a future opportunity. >> Yeah, as I said, look, you're actually right. Cloud is becoming even more and more something that everybody's adopting, but at the same time, there is this thing that the edge is also more and more important. And the connectivity between those two and making sure that you can really do that efficiently. My ask from enterprises, and I think this is top of mind for all the enterprise architects is, choose open because that way you can avoid locking yourself in. So that's one thing that's really, really important. In the past, you know, all these vendors that locked you in, and then you try to move off of them, they were highly innovative back in the day. In the 80's and the 90's, there were the best companies. You gave them all your data and it was fantastic. But then because you were locked in, they didn't need to innovate anymore. And you know, they focused on margins instead. And then over time, the innovation stopped and now you were kind of locked in. So I think openness is really important. I think preserving optionality with multi-cloud because we see the different clouds have different strengths and weaknesses and it changes over time. All right. Early on AWS was the only game that either showed up with much better security, active directory, and so on. Now Google with AI capabilities, which one's going to win, which one's going to be better. Actually, probably all three are going to be around. So having that optionality that you can pick between the three and then artificial intelligence. I think that's going to be the key to the future. You know, you asked about security earlier. That's how people detect zero day attacks, right? You ask about the edge, same thing there, that's where the predictions are going to happen. So make sure that you invest in AI and artificial intelligence very early on because it's not something you can just bolt on later on and have a little data team somewhere that then now you have AI and it's one and done. >> All right. Great insight. I've got to ask you, the folks may or may not know, but you're a professor at Berkeley as well, done a lot of great work. That's where you kind of came out of when Data bricks was formed. And the Berkeley basically was it invented distributed computing back in the 80's. I remember I was breaking in when Unix was proprietary, when software wasn't open you actually had the deal that under the table to get code. Now it's all open. Isn't the internet now with distributed computing and how interconnects are happening. I mean, the internet didn't break during the pandemic, which proves the benefit of the internet. And that's a positive. But as you start seeing edge, it's essentially distributed computing. So I got to ask you from a computer science standpoint. What do you see as the key learnings or connect the dots for how this distributed model will work? I see hybrids clearly, hybrid cloud is clearly the operating model but if you take it to the next level of distributed computing, what are some of the key things that you look for in the next five years as this starts to be completely interoperable, obviously software is going to drive a lot of it. What's your vision on that? >> Yeah, I mean, you know, so Berkeley, you're right for the gigs, you know, there was a now project 20, 30 years ago that basically is how we do things. There was a project on how you search in the very early on with Inktomi that became how Google and everybody else to search today. So workday was super, super early, sometimes way too early. And that was actually the mistake. Was that they were so early that people said that that stuff doesn't work. And then 20 years later you were invented. So I think 2009, Berkeley published just above the clouds saying the cloud is the future. At that time, most industry leaders said, that's just, you know, that doesn't work. Today, recently they published a research paper called, Sky Computing. So sky computing is what you get above the clouds, right? So we have the cloud as the future, the next level after that is the sky. That's one on top of them. That's what multi-cloud is. So that's a lot of the research at Berkeley, you know, into distributed systems labs is about this. And we're excited about that. Then we're one of the sky computing vendors out there. So I think you're going to see much more innovation happening at the sky level than at the compute level where you needed all those DevOps and SRE people to like, you know, build everything manually themselves. I can just see the memes now coming Ali, sky net, star track. You've got space too, by the way, space is another frontier that is seeing a lot of action going on because now the surface area of data with satellites is huge. So again, I know you guys are doing a lot of business with folks in that vertical where you starting to see real time data acquisition coming from these satellites. What's your take on the whole space as the, not the final frontier, but certainly as a new congested and contested space for, for data? >> Well, I mean, as a data vendor, we see a lot of, you know, alternative data sources coming in and people aren't using machine learning< AI to eat out signal out of the, you know, massive amounts of imagery that's coming out of these satellites. So that's actually a pretty common in FinTech, which is a vertical for us. And also sort of in the public sector, lots of, lots of, lots of satellites, imagery data that's coming. And these are massive volumes. I mean, it's like huge data sets and it's a super, super exciting what they can do. Like, you know, extracting signal from the satellite imagery is, and you know, being able to handle that amount of data, it's a challenge for all the companies that we work with. So we're excited about that too. I mean, definitely that's a trend that's going to continue. >> All right. I'm super excited for you. And thanks for coming on The Cube here for our keynote. I got to ask you a final question. As you think about the future, I see your company has achieved great success in a very short time, and again, you guys done the work, I've been following your company as you know. We've been been breaking that Data bricks story for a long time. I've been excited by it, but now what's changed. You got to start thinking about the next 20 miles stair when you look at, you know, the sky computing, you're thinking about these new architectures. As the CEO, your job is to one, not run out of money which you don't have to worry about that anymore, so hiring. And then, you got to figure out that next 20 miles stair as a company. What's that going on in your mind? Take us through your mindset of what's next. And what do you see out in that landscape? >> Yeah, so what I mentioned around Sky company optionality around multi-cloud, you're going to see a lot of capabilities around that. Like how do you get multi-cloud disaster recovery? How do you leverage the best of all the clouds while at the same time not having to just pick one? So there's a lot of innovation there that, you know, we haven't announced yet, but you're going to see a lot of it over the next many years. Things that you can do when you have the optionality across the different parts. And the second thing that's really exciting for us is bringing AI to the masses. Democratizing data and AI. So how can you actually apply machine learning to machine learning? How can you automate machine learning? Today machine learning is still quite complicated and it's pretty advanced. It's not going to be that way 10 years from now. It's going to be very simple. Everybody's going to have it at their fingertips. So how do we apply machine learning to machine learning? It's called auto ML, automatic, you know, machine learning. So that's an area, and that's not something that can be done with, right? But the goal is to eventually be able to automate a way the whole machine learning engineer and the machine learning data scientist altogether. >> You know it's really fun and talking with you is that, you know, for years we've been talking about this inside the ropes, inside the industry, around the future. Now people starting to get some visibility, the pandemics forced that. You seeing the bad projects being exposed. It's like the tide pulled out and you see all the scabs and bad projects that were justified old guard technologies. If you get it right you're on a good wave. And this is clearly what we're seeing. And you guys example of that. So as enterprises realize this, that they're going to have to look double down on the right projects and probably trash the bad projects, new criteria, how should people be thinking about buying? Because again, we talked about the RFP before. I want to kind of circle back because this is something that people are trying to figure out. You seeing, you know, organic, you come in freemium models as cloud scale becomes the advantage in the lock-in frankly seems to be the value proposition. The more value you provide, the more lock-in you get. Which sounds like that's the way it should be versus proprietary, you know, protocols. The protocol is value. How should enterprises organize their teams? Is it end to end workflows? Is it, and how should they evaluate the criteria for these technologies that they want to buy? >> Yeah, that's a great question. So I, you know, it's very simple, try to future proof your decision-making. Make sure that whatever you're doing is not blocking your in. So whatever decision you're making, what if the world changes in five years, make sure that if you making a mistake now, that's not going to bite you in about five years later. So how do you do that? Well, open source is great. If you're leveraging open-source, you can try it out already. You don't even need to talk to any vendor. Your teams can already download it and try it out and get some value out of it. If you're in the cloud, this pay as you go models, you don't have to do a big RFP and commit big. You can try it, pay the vendor, pay as you go, $10, $15. It doesn't need to be a million dollar contract and slowly grow as you're providing value. And then make sure that you're not just locking yourself in to one cloud or, you know, one particular vendor. As much as possible preserve your optionality because then that's not a one-way door. If it turns out later you want to do something else, you can, you know, pick other things as well. You're not locked in. So that's what I would say. Keep that top of mind that you're not locking yourself into a particular decision that you made today, that you might regret in five years. >> I really appreciate you coming on and sharing your with our community and The Cube. And as always great to see you. I really enjoy your clubhouse talks, and I really appreciate how you give back to the community. And I want to thank you for coming on and taking the time with us today. >> Thanks John, always appreciate talking to you. >> Okay Ali Ghodsi, CEO of Data bricks, a success story that proves the validation of cloud scale, open and create value, values the new lock-in. So Natalie, back to you for continuing coverage. >> That was a terrific interview John, but I'd love to get Dave's insights first. What were your takeaways, Dave? >> Well, if we have more time I'll tell you how Data bricks got to where they are today, but I'll say this, the most important thing to me that Allie said was he conveyed a very clear understanding of what data companies are outright and are getting ready. Talked about four things. There's not one data team, there's many data teams. And he talked about data is decentralized, and data has to have context and that context lives in the business. He said, look, think about it. The way that the data companies would get it right, they get data in teams and sales and marketing and finance and engineering. They all have their own data and data teams. And he referred to that as a data mesh. That's a term that is your mock, the Gany coined and the warehouse of the data lake it's merely a node in that global message. It meshes discoverable, he talked about federated governance, and Data bricks, they're breaking the model of shoving everything into a single repository and trying to make that the so-called single version of the truth. Rather what they're doing, which is right on is putting data in the hands of the business owners. And that's how true data companies do. And the last thing you talked about with sky computing, which I loved, it's that future layer, we talked about multi-cloud a lot that abstracts the underlying complexity of the technical details of the cloud and creates additional value on top. I always say that the cloud players like Amazon have given the gift to the world of 100 billion dollars a year they spend in CapEx. Thank you. Now we're going to innovate on top of it. Yeah. And I think the refactoring... >> Hope by John. >> That was great insight and I totally agree. The refactoring piece too was key, he brought that home. But to me, I think Data bricks that Ali shared there and why he's been open and sharing a lot of his insights and the community. But what he's not saying, cause he's humble and polite is they cracked the code on the enterprise, Dave. And to Dave's points exactly reason why they did it, they saw an opportunity to make it easier, at that time had dupe was the rage, and they just made it easier. They was smart, they made good bets, they had a good formula and they cracked the code with the enterprise. They brought it in and they brought value. And see that's the key to the cloud as Dave pointed out. You get replatform with the cloud, then you refactor. And I think he pointed out the multi-cloud and that really kind of teases out the whole future and landscape, which is essentially distributed computing. And I think, you know, companies are starting to figure that out with hybrid and this on premises and now super edge I call it, with 5G coming. So it's just pretty incredible. >> Yeah. Data bricks, IPO is coming and people should know. I mean, what everybody, they created spark as you know John and everybody thought they were going to do is mimic red hat and sell subscriptions and support. They didn't, they developed a managed service and they embedded AI tools to simplify data science. So to your point, enterprises could buy instead of build, we know this. Enterprises will spend money to make things simpler. They don't have the resources, and so this was what they got right was really embedding that, making a building a managed service, not mimicking the kind of the red hat model, but actually creating a new value layer there. And that's big part of their success. >> If I could just add one thing Natalie to that Dave saying is really right on. And as an enterprise buyer, if we go the other side of the equation, it used to be that you had to be a known company, get PR, you fill out RFPs, you had to meet all the speeds. It's like going to the airport and get a swab test, and get a COVID test and all kinds of mechanisms to like block you and filter you. Most of the biggest success stories that have created the most value for enterprises have been the companies that nobody's understood. And Andy Jazz's famous quote of, you know, being misunderstood is actually a good thing. Data bricks was very misunderstood at the beginning and no one kind of knew who they were but they did it right. And so the enterprise buyers out there, don't be afraid to test the startups because you know the next Data bricks is out there. And I think that's where I see the psychology changing from the old IT buyers, Dave. It's like, okay, let's let's test this company. And there's plenty of ways to do that. He illuminated those premium, small pilots, you don't need to go on these big things. So I think that is going to be a shift in how companies going to evaluate startups. >> Yeah. Think about it this way. Why should the large banks and insurance companies and big manufacturers and pharma companies, governments, why should they burn resources managing containers and figuring out data science tools if they can just tap into solutions like Data bricks which is an AI platform in the cloud and let the experts manage all that stuff. Think about how much money in time that saves enterprises. >> Yeah, I mean, we've got 15 companies here we're showcasing this batch and this season if you call it. That episode we are going to call it? They're awesome. Right? And the next 15 will be the same. And these companies could be the next billion dollar revenue generator because the cloud enables that day. I think that's the exciting part. >> Well thank you both so much for these insights. Really appreciate it. AWS startup showcase highlights the innovation that helps startups succeed. And no one knows that better than our very next guest, Jeff Barr. Welcome to the show and I will send this interview now to Dave and John and see you just in the bit. >> Okay, hey Jeff, great to see you. Thanks for coming on again. >> Great to be back. >> So this is a regular community segment with Jeff Barr who's a legend in the industry. Everyone knows your name. Everyone knows that. Congratulations on your recent blog posts we have reading. Tons of news, I want to get your update because 5G has been all over the news, mobile world congress is right around the corner. I know Bill Vass was a keynote out there, virtual keynote. There's a lot of Amazon discussion around the edge with wavelength. Specifically, this is the outpost piece. And I know there is news I want to get to, but the top of mind is there's massive Amazon expansion and the cloud is going to the edge, it's here. What's up with wavelength. Take us through the, I call it the power edge, the super edge. >> Well, I'm really excited about this mostly because it gives a lot more choice and flexibility and options to our customers. This idea that with wavelength we announced quite some time ago, at least quite some time ago if we think in cloud years. We announced that we would be working with 5G providers all over the world to basically put AWS in the telecom providers data centers or telecom centers, so that as their customers build apps, that those apps would take advantage of the low latency, the high bandwidth, the reliability of 5G, be able to get to some compute and storage services that are incredibly close geographically and latency wise to the compute and storage that is just going to give customers this new power and say, well, what are the cool things we can build? >> Do you see any correlation between wavelength and some of the early Amazon services? Because to me, my gut feels like there's so much headroom there. I mean, I was just riffing on the notion of low latency packets. I mean, just think about the applications, gaming and VR, and metaverse kind of cool stuff like that where having the edge be that how much power there. It just feels like a new, it feels like a new AWS. I mean, what's your take? You've seen the evolutions and the growth of a lot of the key services. Like EC2 and SA3. >> So welcome to my life. And so to me, the way I always think about this is it's like when I go to a home improvement store and I wander through the aisles and I often wonder through with no particular thing that I actually need, but I just go there and say, wow, they've got this and they've got this, they've got this other interesting thing. And I just let my creativity run wild. And instead of trying to solve a problem, I'm saying, well, if I had these different parts, well, what could I actually build with them? And I really think that this breadth of different services and locations and options and communication technologies. I suspect a lot of our customers and customers to be and are in this the same mode where they're saying, I've got all this awesomeness at my fingertips, what might I be able to do with it? >> He reminds me when Fry's was around in Palo Alto, that store is no longer here but it used to be back in the day when it was good. It was you go in and just kind of spend hours and then next thing you know, you built a compute. Like what, I didn't come in here, whether it gets some cables. Now I got a motherboard. >> I clearly remember Fry's and before that there was the weird stuff warehouse was another really cool place to hang out if you remember that. >> Yeah I do. >> I wonder if I could jump in and you guys talking about the edge and Jeff I wanted to ask you about something that is, I think people are starting to really understand and appreciate what you did with the entrepreneur acquisition, what you do with nitro and graviton, and really driving costs down, driving performance up. I mean, there's like a compute Renaissance. And I wonder if you could talk about the importance of that at the edge, because it's got to be low power, it has to be low cost. You got to be doing processing at the edge. What's your take on how that's evolving? >> Certainly so you're totally right that we started working with and then ultimately acquired Annapurna labs in Israel a couple of years ago. I've worked directly with those folks and it's really awesome to see what they've been able to do. Just really saying, let's look at all of these different aspects of building the cloud that were once effectively kind of somewhat software intensive and say, where does it make sense to actually design build fabricate, deploy custom Silicon? So from putting up the system to doing all kinds of additional kinds of security checks, to running local IO devices, running the NBME as fast as possible to support the EBS. Each of those things has been a contributing factor to not just the power of the hardware itself, but what I'm seeing and have seen for the last probably two or three years at this point is the pace of innovation on instance types just continues to get faster and faster. And it's not just cranking out new instance types because we can, it's because our awesomely diverse base of customers keeps coming to us and saying, well, we're happy with what we have so far, but here's this really interesting new use case. And we needed a different ratio of memory to CPU, or we need more cores based on the amount of memory, or we needed a lot of IO bandwidth. And having that nitro as the base lets us really, I don't want to say plug and play, cause I haven't actually built this myself, but it seems like they can actually put the different elements together, very very quickly and then come up with new instance types that just our customers say, yeah, that's exactly what I asked for and be able to just do this entire range of from like micro and nano sized all the way up to incredibly large with incredible just to me like, when we talk about terabytes of memory that are just like actually just RAM memory. It's like, that's just an inconceivably large number by the standards of where I started out in my career. So it's all putting this power in customer hands. >> You used the term plug and play, but it does give you that nitro gives you that optionality. And then other thing that to me is really exciting is the way in which ISVs are writing to whatever's underneath. So you're making that, you know, transparent to the users so I can choose as a customer, the best price performance for my workload and that that's just going to grow that ISV portfolio. >> I think it's really important to be accurate and detailed and as thorough as possible as we launch each one of these new instance types with like what kind of processor is in there and what clock speed does it run at? What kind of, you know, how much memory do we have? What are the, just the ins and outs, and is it Intel or arm or AMD based? It's such an interesting to me contrast. I can still remember back in the very very early days of back, you know, going back almost 15 years at this point and effectively everybody said, well, not everybody. A few people looked and said, yeah, we kind of get the value here. Some people said, this just sounds like a bunch of generic hardware, just kind of generic hardware in Iraq. And even back then it was something that we were very careful with to design and optimize for use cases. But this idea that is generic is so, so, so incredibly inaccurate that I think people are now getting this. And it's okay. It's fine too, not just for the cloud, but for very specific kinds of workloads and use cases. >> And you guys have announced obviously the performance improvements on a lamb** does getting faster, you got the per billing, second billings on windows and SQL server on ECE too**. So I mean, obviously everyone kind of gets that, that's been your DNA, keep making it faster, cheaper, better, easier to use. But the other area I want to get your thoughts on because this is also more on the footprint side, is that the regions and local regions. So you've got more region news, take us through the update on the expansion on the footprint of AWS because you know, a startup can come in and these 15 companies that are here, they're global with AWS, right? So this is a major benefit for customers around the world. And you know, Ali from Data bricks mentioned privacy. Everyone's a privacy company now. So the huge issue, take us through the news on the region. >> Sure, so the two most recent regions that we announced are in the UAE and in Israel. And we generally like to pre-announce these anywhere from six months to two years at a time because we do know that the customers want to start making longer term plans to where they can start thinking about where they can do their computing, where they can store their data. I think at this point we now have seven regions under construction. And, again it's all about customer trice. Sometimes it's because they have very specific reasons where for based on local laws, based on national laws, that they must compute and restore within a particular geographic area. Other times I say, well, a lot of our customers are in this part of the world. Why don't we pick a region that is as close to that part of the world as possible. And one really important thing that I always like to remind our customers of in my audience is, anything that you choose to put in a region, stays in that region unless you very explicitly take an action that says I'd like to replicate it somewhere else. So if someone says, I want to store data in the US, or I want to store it in Frankfurt, or I want to store it in Sao Paulo, or I want to store it in Tokyo or Osaka. They get to make that very specific choice. We give them a lot of tools to help copy and replicate and do cross region operations of various sorts. But at the heart, the customer gets to choose those locations. And that in the early days I think there was this weird sense that you would, you'd put things in the cloud that would just mysteriously just kind of propagate all over the world. That's never been true, and we're very very clear on that. And I just always like to reinforce that point. >> That's great stuff, Jeff. Great to have you on again as a regular update here, just for the folks watching and don't know Jeff he'd been blogging and sharing. He'd been the one man media band for Amazon it's early days. Now he's got departments, he's got peoples on doing videos. It's an immediate franchise in and of itself, but without your rough days we wouldn't have gotten all the great news we subscribe to. We watch all the blog posts. It's essentially the flow coming out of AWS which is just a tsunami of a new announcements. Always great to read, must read. Jeff, thanks for coming on, really appreciate it. That's great. >> Thank you John, great to catch up as always. >> Jeff Barr with AWS again, and follow his stuff. He's got a great audience and community. They talk back, they collaborate and they're highly engaged. So check out Jeff's blog and his social presence. All right, Natalie, back to you for more coverage. >> Terrific. Well, did you guys know that Jeff took a three week AWS road trip across 15 cities in America to meet with cloud computing enthusiasts? 5,500 miles he drove, really incredible I didn't realize that. Let's unpack that interview though. What stood out to you John? >> I think Jeff, Barr's an example of what I call direct to audience a business model. He's been doing it from the beginning and I've been following his career. I remember back in the day when Amazon was started, he was always building stuff. He's a builder, he's classic. And he's been there from the beginning. At the beginning he was just the blog and it became a huge audience. It's now morphed into, he was power blogging so hard. He has now support and he still does it now. It's basically the conduit for information coming out of Amazon. I think Jeff has single-handedly made Amazon so successful at the community developer level, and that's the startup action happened and that got them going. And I think he deserves a lot of the success for AWS. >> And Dave, how about you? What is your reaction? >> Well I think you know, and everybody knows about the cloud and back stop X** and agility, and you know, eliminating the undifferentiated, heavy lifting and all that stuff. And one of the things that's often overlooked which is why I'm excited to be part of this program is the innovation. And the innovation comes from startups, and startups start in the cloud. And so I think that that's part of the flywheel effect. You just don't see a lot of startups these days saying, okay, I'm going to do something that's outside of the cloud. There are some, but for the most part, you know, if you saw in software, you're starting in the cloud, it's so capital efficient. I think that's one thing, I've throughout my career. I've been obsessed with every part of the stack from whether it's, you know, close to the business process with the applications. And right now I'm really obsessed with the plumbing, which is why I was excited to talk about, you know, the Annapurna acquisition. Amazon bought and a part of the $350 million, it's reported, you know, maybe a little bit more, but that isn't an amazing acquisition. And the reason why that's so important is because Amazon is continuing to drive costs down, drive performance up. And in my opinion, leaving a lot of the traditional players in their dust, especially when it comes to the power and cooling. You have often overlooked things. And the other piece of the interview was that Amazon is actually getting ISVs to write to these new platforms so that you don't have to worry about there's the software run on this chip or that chip, or x86 or arm or whatever it is. It runs. And so I can choose the best price performance. And that's where people don't, they misunderstand, you always say it John, just said that people are misunderstood. I think they misunderstand, they confused, you know, the price of the cloud with the cost of the cloud. They ignore all the labor costs that are associated with that. And so, you know, there's a lot of discussion now about the cloud tax. I just think the pace is accelerating. The gap is not closing, it's widening. >> If you look at the one question I asked them about wavelength and I had a follow up there when I said, you know, we riff on it and you see, he lit up like he beam was beaming because he said something interesting. It's not that there's a problem to solve at this opportunity. And he conveyed it to like I said, walking through Fry's. But like, you go into a store and he's a builder. So he sees opportunity. And this comes back down to the Martine Casada paradox posts he wrote about do you optimize for CapEx or future revenue? And I think the tell sign is at the wavelength edge piece is going to be so creative and that's going to open up massive opportunities. I think that's the place to watch. That's the place I'm watching. And I think startups going to come out of the woodwork because that's where the action will be. And that's just Amazon at the edge, I mean, that's just cloud at the edge. I think that is going to be very effective. And his that's a little TeleSign, he kind of revealed a little bit there, a lot there with that comment. >> Well that's a to be continued conversation. >> Indeed, I would love to introduce our next guest. We actually have Soma on the line. He's the managing director at Madrona venture group. Thank you Soma very much for coming for our keynote program. >> Thank you Natalie and I'm great to be here and will have the opportunity to spend some time with you all. >> Well, you have a long to nerd history in the enterprise. How would you define the modern enterprise also known as cloud scale? >> Yeah, so I would say I have, first of all, like, you know, we've all heard this now for the last, you know, say 10 years or so. Like, software is eating the world. Okay. Put it another way, we think about like, hey, every enterprise is a software company first and foremost. Okay. And companies that truly internalize that, that truly think about that, and truly act that way are going to start up, continue running well and things that don't internalize that, and don't do that are going to be left behind sooner than later. Right. And the last few years you start off thing and not take it to the next level and talk about like, not every enterprise is not going through a digital transformation. Okay. So when you sort of think about the world from that lens. Okay. Modern enterprise has to think about like, and I am first and foremost, a technology company. I may be in the business of making a car art, you know, manufacturing paper, or like you know, manufacturing some healthcare products or what have you got out there. But technology and software is what is going to give me a unique, differentiated advantage that's going to let me do what I need to do for my customers in the best possible way [Indistinct]. So that sort of level of focus, level of execution, has to be there in a modern enterprise. The other thing is like not every modern enterprise needs to think about regular. I'm competing for talent, not anymore with my peers in my industry. I'm competing for technology talent and software talent with the top five technology companies in the world. Whether it is Amazon or Facebook or Microsoft or Google, or what have you cannot think, right? So you really have to have that mindset, and then everything flows from that. >> So I got to ask you on the enterprise side again, you've seen many ways of innovation. You've got, you know, been in the industry for many, many years. The old way was enterprises want the best proven product and the startups want that lucrative contract. Right? Yeah. And get that beach in. And it used to be, and we addressed this in our earlier keynote with Ali and how it's changing, the buyers are changing because the cloud has enabled this new kind of execution. I call it agile, call it what you want. Developers are driving modern applications, so enterprises are still, there's no, the playbooks evolving. Right? So we see that with the pandemic, people had needs, urgent needs, and they tried new stuff and it worked. The parachute opened as they say. So how do you look at this as you look at stars, you're investing in and you're coaching them. What's the playbook? What's the secret sauce of how to crack the enterprise code today. And if you're an enterprise buyer, what do I need to do? I want to be more agile. Is there a clear path? Is there's a TSA to let stuff go through faster? I mean, what is the modern playbook for buying and being a supplier? >> That's a fantastic question, John, because I think that sort of playbook is changing, even as we speak here currently. A couple of key things to understand first of all is like, you know, decision-making inside an enterprise is getting more and more de-centralized. Particularly decisions around what technology to use and what solutions to use to be able to do what people need to do. That decision making is no longer sort of, you know, all done like the CEO's office or the CTO's office kind of thing. Developers are more and more like you rightly said, like sort of the central of the workflow and the decision making process. So it'll be who both the enterprises, as well as the startups to really understand that. So what does it mean now from a startup perspective, from a startup perspective, it means like, right. In addition to thinking about like hey, not do I go create an enterprise sales post, do I sell to the enterprise like what I might have done in the past? Is that the best way of moving forward, or should I be thinking about a product led growth go to market initiative? You know, build a product that is easy to use, that made self serve really works, you know, get the developers to start using to see the value to fall in love with the product and then you think about like hey, how do I go translate that into a contract with enterprise. Right? And more and more what I call particularly, you know, startups and technology companies that are focused on the developer audience are thinking about like, you know, how do I have a bottom up go to market motion? And sometime I may sort of, you know, overlap that with the top down enterprise sales motion that we know that has been going on for many, many years or decades kind of thing. But really this product led growth bottom up a go to market motion is something that we are seeing on the rise. I would say they're going to have more than half the startup that we come across today, have that in some way shape or form. And so the enterprise also needs to understand this, the CIO or the CTO needs to know that like hey, I'm not decision-making is getting de-centralized. I need to empower my engineers and my engineering managers and my engineering leaders to be able to make the right decision and trust them. I'm going to give them some guard rails so that I don't find myself in a soup, you know, sometime down the road. But once I give them the guard rails, I'm going to enable people to make the decisions. People who are closer to the problem, to make the right decision. >> Well Soma, what are some of the ways that startups can accelerate their enterprise penetration? >> I think that's another good question. First of all, you need to think about like, Hey, what are enterprises wanting to rec? Okay. If you start off take like two steps back and think about what the enterprise is really think about it going. I'm a software company, but I'm really manufacturing paper. What do I do? Right? The core thing that most enterprises care about is like, hey, how do I better engage with my customers? How do I better serve my customers? And how do I do it in the most optimal way? At the end of the day that's what like most enterprises really care about. So startups need to understand, what are the problems that the enterprise is trying to solve? What kind of tools and platform technologies and infrastructure support, and, you know, everything else that they need to be able to do what they need to do and what only they can do in the most optimal way. Right? So to the extent you are providing either a tool or platform or some technology that is going to enable your enterprise to make progress on what they want to do, you're going to get more traction within the enterprise. In other words, stop thinking about technology, and start thinking about the customer problem that they want to solve. And the more you anchor your company, and more you anchor your conversation with the customer around that, the more the enterprise is going to get excited about wanting to work with you. >> So I got to ask you on the enterprise and developer equation because CSOs and CXOs, depending who you talk to have that same answer. Oh yeah. In the 90's and 2000's, we kind of didn't, we throttled down, we were using the legacy developer tools and cloud came and then we had to rebuild and we didn't really know what to do. So you seeing a shift, and this is kind of been going on for at least the past five to eight years, a lot more developers being hired yet. I mean, at FinTech is clearly a vertical, they always had developers and everyone had developers, but there's a fast ramp up of developers now and the role of open source has changed. Just looking at the participation. They're not just consuming open source, open source is part of the business model for mainstream enterprises. How is this, first of all, do you agree? And if so, how has this changed the course of an enterprise human resource selection? How they're organized? What's your vision on that? >> Yeah. So as I mentioned earlier, John, in my mind the first thing is, and this sort of, you know, like you said financial services has always been sort of hiring people [Indistinct]. And this is like five-year old story. So bear with me I'll tell you the firewall story and then come to I was trying to, the cloud CIO or the Goldman Sachs. Okay. And this is five years ago when people were still like, hey, is this cloud thing real and now is cloud going to take over the world? You know, am I really ready to put my data in the cloud? So there are a lot of questions and conversations can affect. The CIO of Goldman Sachs told me two things that I remember to this day. One is, hey, we've got a internal edict. That we made a decision that in the next five years, everything in Goldman Sachs is going to be on the public law. And I literally jumped out of the chair and I said like now are you going to get there? And then he laughed and said like now it really doesn't matter whether we get there or not. We want to set the tone, set the direction for the organization that hey, public cloud is here. Public cloud is there. And we need to like, you know, move as fast as we realistically can and think about all the financial regulations and security and privacy. And all these things that we care about deeply. But given all of that, the world is going towards public load and we better be on the leading edge as opposed to the lagging edge. And the second thing he said, like we're talking about like hey, how are you hiring, you know, engineers at Goldman Sachs Canada? And he said like in hey, I sort of, my team goes out to the top 20 schools in the US. And the people we really compete with are, and he was saying this, Hey, we don't compete with JP Morgan or Morgan Stanley, or pick any of your favorite financial institutions. We really think about like, hey, we want to get the best talent into Goldman Sachs out of these schools. And we really compete head to head with Google. We compete head to head with Microsoft. We compete head to head with Facebook. And we know that the caliber of people that we want to get is no different than what these companies want. If you want to continue being a successful, leading it, you know, financial services player. That sort of tells you what's going on. You also talked a little bit about like hey, open source is here to stay. What does that really mean kind of thing. In my mind like now, you can tell me that I can have from given my pedigree at Microsoft, I can tell you that we were the first embraces of open source in this world. So I'll say that right off the bat. But having said that we did in our turn around and said like, hey, this open source is real, this open source is going to be great. How can we embrace and how can we participate? And you fast forward to today, like in a Microsoft is probably as good as open source as probably any other large company I would say. Right? Including like the work that the company has done in terms of acquiring GitHub and letting it stay true to its original promise of open source and community can I think, right? I think Microsoft has come a long way kind of thing. But the thing that like in all these enterprises need to think about is you want your developers to have access to the latest and greatest tools. To the latest and greatest that the software can provide. And you really don't want your engineers to be reinventing the wheel all the time. So there is something available in the open source world. Go ahead, please set up, think about whether that makes sense for you to use it. And likewise, if you think that is something you can contribute to the open source work, go ahead and do that. So it's really a two way somebody Arctic relationship that enterprises need to have, and they need to enable their developers to want to have that symbiotic relationship. >> Soma, fantastic insights. Thank you so much for joining our keynote program. >> Thank you Natalie and thank you John. It was always fun to chat with you guys. Thank you. >> Thank you. >> John we would love to get your quick insight on that. >> Well I think first of all, he's a prolific investor the great from Madrona venture partners, which is well known in the tech circles. They're in Seattle, which is in the hub of I call cloud city. You've got Amazon and Microsoft there. He'd been at Microsoft and he knows the developer ecosystem. And reason why I like his perspective is that he understands the value of having developers as a core competency in Microsoft. That's their DNA. You look at Microsoft, their number one thing from day one besides software was developers. That was their army, the thousand centurions that one won everything for them. That has shifted. And he brought up open source, and .net and how they've embraced Linux, but something that tele before he became CEO, we interviewed him in the cube at an Xcel partners event at Stanford. He was open before he was CEO. He was talking about opening up. They opened up a lot of their open source infrastructure projects to the open compute foundation early. So they had already had that going and at that price, since that time, the stock price of Microsoft has skyrocketed because as Ali said, open always wins. And I think that is what you see here, and as an investor now he's picking in startups and investing in them. He's got to read the tea leaves. He's got to be in the right side of history. So he brings a great perspective because he sees the old way and he understands the new way. That is the key for success we've seen in the enterprise and with the startups. The people who get the future, and can create the value are going to win. >> Yeah, really excellent point. And just really quickly. What do you think were some of our greatest hits on this hour of programming? >> Well first of all I'm really impressed that Ali took the time to come join us because I know he's super busy. I think they're at a $28 billion valuation now they're pushing a billion dollars in revenue, gap revenue. And again, just a few short years ago, they had zero software revenue. So of these 15 companies we're showcasing today, you know, there's a next Data bricks in there. They're all going to be successful. They already are successful. And they're all on this rocket ship trajectory. Ali is smart, he's also got the advantage of being part of that Berkeley community which they're early on a lot of things now. Being early means you're wrong a lot, but you're also right, and you're right big. So Berkeley and Stanford obviously big areas here in the bay area as research. He is smart, He's got a great team and he's really open. So having him share his best practices, I thought that was a great highlight. Of course, Jeff Barr highlighting some of the insights that he brings and honestly having a perspective of a VC. And we're going to have Peter Wagner from wing VC who's a classic enterprise investors, super smart. So he'll add some insight. Of course, one of the community session, whenever our influencers coming on, it's our beat coming on at the end, as well as Katie Drucker. Another Madrona person is going to talk about growth hacking, growth strategies, but yeah, sights Raleigh coming on. >> Terrific, well thank you so much for those insights and thank you to everyone who is watching the first hour of our live coverage of the AWS startup showcase for myself, Natalie Ehrlich, John, for your and Dave Vellante we want to thank you very much for watching and do stay tuned for more amazing content, as well as a special live segment that John Furrier is going to be hosting. It takes place at 12:30 PM Pacific time, and it's called cracking the code, lessons learned on how enterprise buyers evaluate new startups. Don't go anywhere.