>> theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hey everyone, guys and gals, good to see you. It's theCUBE live in Barcelona at MWC23. Lisa Martin here with Dave Vellante on day one of four days of wall to wall CUBE coverage. Dave, today is ecosystem day. We've had some great conversations about why the open ecosystem is so important and some of the key players in it. >> Well and I'm in search of disruptors, so I'm looking for, okay, who are the network operators that are going to actually lean into the future and drive it and challenge the existing incumbents. We'll talk about that today. >> And we're going to be talking about that next. We've got one of our alumni back with us. Satish Iyer is here, the Vice President of Emerging Services at Dell. Great to have you back on the program. >> Thank you. >> Richard Leitao is with us as well, the Vice President of National Development at DISH Network. Welcome. >> Pleasure to be here. >> So, lots of, this is day one, the theme is velocity. I feel like the day has gone by so quickly. But Dell and DISH have partnered together on a multi-year initiative to build your nationwide cloud-native 5G network that's going to cover a lot of the US. Talk a little bit about that partnership, we'll get both of your perspectives. Richard, we'll start with you. >> Sure. So thank you again for having me. So DISH had the opportunity of, of going through this experience, of innovating once more. For the ones that know DISH, DISH is a company that was founded in 1980 by an innovator, a disruptor. Of course, in the course of the next 40 years, we had the opportunities of even disrupting ourselves. We launched our first satellite TV service. We then launched the first streaming, video streaming platform, disrupting our own satellite business. And since 2008, we have been acquiring Spectrum and, you know, Spectrum, the most valuable asset of a wireless operator. We felt that this was the right opportunity, having 5G , having O-RAN, and we decided to go full in in a greenfield project building national network, 5G O-RAN cloud-based network, one of a kind network in in the US and, and most of all, using O-RAN, it's very important to us, what, what it can bring and it can bring to DISH but to the entire ecosystem of, of this sector in the US. >> Satish, talk a little bit about the partnership from Dell's perspective and some of the unique advantages that Dell is delivering to DISH. >> Oh absolutely. Again, like Richard was saying, I mean the telecom network is being desegregated as we speak. You know, companies like DISH and everybody else is looking at what are the best-in-class technologies we can bring to the table. I would like to say that, you know, the cloud is coming to the telco world, right? A lot of us have seen the tremendous transformation in the cloud world in the last few years. Now, you know, DISH is a big enterprise company. As you know, you know, we are pretty strong within the cloud space and enterprise space. So what we try to work with DISH is Dell, is to bring to DISH is, you know, that notion of cloud scale and the cloud ecosystem into telecom, right? By means best-in-class infrastructure products, best-in-class software products, to allow somebody like DISH to innovate and incre, you know, basically expand and build their O-RAN network. So it's absolutely important for us as we build and get into the telecom space to work with somebody like DISH who's also disrupting as a carrier in that space. >> So it's early days for Open RAN but you've decided, "okay, we're all in". >> Yeah. >> Right? So (chuckling) you burn the bridge, as they say, "go for it". (Lisa chuckles) So when you talk to most people, they say, "okay, it's, it's, it's, it's immature." It's got to be able to get to the levels of, of the, the the hardened stack reliability. But of course it brings the advantage of flexibility and speed. Are you optimizing for one or the other right now? How are you dealing with that balance? >> Well, it, it's, it's not mature in the sense that most of operators that think about it, they have a legacy network. And in order to go full in on the O-RAN side, they need to scrap a lot of things that they have and honestly, they don't want, and it doesn't make sense. So being a greenfield operator, give us that advantage. Give us the advantage and, and desegregation, it's all about chip sets, boxes and software and the chip sets part and what I like the most in desegregation is the time of innovation. The time that we can use new chip sets coming into the market, the size of the boxes that we are using. Obviously our footprint onsite is much smaller than traditional carriers or proprietary systems. So all of that Dell has been critical in supporting us. Supporting us having the best chip sets, having the smallest footprint and, you know, the software, the cycle of innovation is much faster than in proprietary systems. So ma-, it's maturing. I'm glad to say that probably two years ago here O-RAN was more like a, a pilot type of technology. It is not, we are live, we are live for more than 30 million customers in the US and, you know, the performance levels are very similar to traditional networks. >> So you don't just buy a nationwide cloud-native 5G network out of the box, you got to- >> No, you don't. >> You got to build it. So I'm curious as to what Dell's role is in that, in that build out. >> Right? >> How and how, I'm really curious how to, how you would grade Dell but we'll get there. >> Yeah, I mean, look, yes, you don't. So I think the, the, the first and foremost is again, as, as we, Dell, comes into the telco space, one of the things we have to look at is to understand what makes Dell better in the enterprise space, right? It is the best-in-class infrastructure. It is the software ties together. As you talk about desegregated networks, it's important to understand lot of these piece parts have to still be touched together, right? So I think the integration and integration aspects becomes really key which is really Dell is very good at. So one of the things we are working really closely with DISH Tech, you know Richard was alluding to, is bringing all, not just bringing all the software and hardware assets together, but how do you continuously innovate and keep fixing things faster, right? So in the old days, traditional ways, you have a software stack, it takes you 18 months, 20 months to actually get an upgrade done. Here we have continuously CI/CD pipelines where if you want to a change done within, within a week's or within a few days, where we can actually go and test and make sure these things work. So I think a lot of the best enterprise software practices, cloud practices, combined with whatever needs for telco, actually is what makes it very unique. >> I, I saw that this started out as an FCC compliance initiative that turned into a partnership, obviously a very successful one. Richard, talk about what DISH saw in Dell that really made it the right choice, knowing you have choices, you have options. >> You know, we saw the capability to execute, but we also saw the capability to innovate. From an execution level, at the end of the day, like we were talking, we started the project in the middle of COVID, and we had the first mandate to cover 20% of the US population by June, 2022. And now we have a second one, 70% of US population by June 2023. At the beginning of the project, it was all about availability of materials, logistics, how to distribute, how to transport material. So Dell has a world-class supply chain, we felt that working with Dell through all these challenges made things easier. So from an execution perspective, whenever you need to build a network and you, you are building thousands of sites, you need to have materials, you need to distribute them and you need to install them. Dell helped us across the board. Our expectations obviously will change. We have a network, we want to cooperate with Dell in many other areas. We want to, you know, leverage on Dell ability to reach the enterprise market, to have private 5G offers. So hopefully this collaboration will endure in time and, and, you know, will change and evolve in time. >> And it's a big bet. I mean, it's not like a single, it's not like a little transaction that you guys are doing. I feel like, you know Michael Dell and Eric Carlson had dinner and they said, "okay, we're going to, we're going to partner up and this is going to be a multi-decade partnership. You had to be transparent, "Hey, we're new at this, even though we're really good at enterprise tech and so you're going to, obviously if you take a chance on us, here's what we promise you." >> Absolutely. >> And vice versa, you guys had to say, "all right, hey, we're willing to roll the dice because we're trying to change the world." So what was that dynamic like? I mean, how did, I'm curious as to this has to be a lot of different levels, engineering, senior management, board level discussions. >> You know, we felt a huge buy-in from Dell on the Open RAN concept. >> Right. >> Yeah, okay. >> And, you know, edge computing and, and the ability to get us the best product and evolve the best product, Intel is is critical in all these offerings. Intel has a great relationship with Dell. Dell helped us. Dell sponsored the DISH program and some of these suppliers, So it was definitely good to have their support and the buy-in on the O-RAN concept. We felt it from day one and we felt secure on that. >> Yeah, I mean, I, to add to that, I mean, you know DISH was very instrumental in driving, dictating and executing to our roadmap, right? They're one of the key, I mean, since they are out there and they're really turning in a way, it's important that a customer who's actually at the out front of innovation, helps us drive our own roadmap. So to Richard's point, a lot of our product roadmaps, in terms of what have you built and all that, was based on what DISH thinks as going to be market-based requirements. They also helped us a lot in the integration aspects. Like I said, one of the things about open desegregation of these networks is there is a lot of integration because, you know, there is, it's not a one, one monolithic pipe smokestack anymore. You are picking up best-in-class pieces, bits and pieces and tying it together. And it's important to understand when you tie it together things will go wrong, right? So there is a lot of learnings from an integration standpoint. Supportability, deployment, one of the things Richard talked about was supply chain, you know. Other Dell's ability to, lot of these deployments, a lot of these configs in the factory, right, in the second part. So especially a lot of these partnerships started during COVID time and as you all know, you know what we went through two years ago. So we had to make sure that lot of these things are done in one place and a factory, and not done in the field because we couldn't do a lot of these things. So there's a lot of, lot of experimentation, lot of, lot, lot of innovation on that. >> So it's 2030, what's this look like? What's the vision if we can work backwards from there? Well, a, a great network coverage to the entire country, bringing new services to enterprises, to verticals, bringing value add to customers and, you know, technology cycles, they are lasting much less than they were. I cannot even say what will happen in three years. 2030, I mean, I know, I know somebody has a vision for 2030. That's another thing. (everyone laughs) >> A lot of it is "build it and they will come", right? >> Yeah. >> I mean it really is right? You put that network in place and then innovation happens on top. That's the best thing. >> Yeah. And look and and I think the biggest people think about Open RAN in terms of cost, which, you know, you, you have some things in cost that you appreciate in Open RAN. The footprint, the the possibility to diversify suppliers and and have more competition. But for me, Open RAN is about innovation and cycles of innovation. I used to work for Nokia, I used to work for Alcatel. I knew from the generation of an idea to an execution and having a feature delivered to a certain customer, it, it took months. We want innovation to take weeks. We are innovating at the speed, speed of the cloud. We are cooperating with new players, players on the cloud and, and we expect things to happen much faster than they traditionally happen on the telecom sector. >> Move fast and break things. >> Well, we also expect that speed- >> Break and fix. (everyone laughs) >> Yeah, thank you for that. >> But speaking of speed, your customers expect that, right? They expect the service to be up 24/7. They expect to be able to access whatever content they want, whenever they want from wherever they are. So comment, Richard, in our last few minutes here of, of how the, the Dell partnership is helping DISH to really deliver the excellent customer experience that your customers just expect that you're going to deliver. >> Well by setting up the system, number one, we are leveraging on a number of services. And I mentioned the supply chain, but in reality Dell made much more than that for our 20% milestone and is supporting our 70% milestone by installing, testing, verifying most of our data center equipment. We found that this offering from Dell was really addressing some of our needs because, you know, we, we believe they know a lot in this area and they, they can provide the best advice and the best speed to market in, in terms of having this equipment. Because we are working on a time clock, we need to have this done as soon as possible. You know for the future, I hope that they can help us in driving more services. I hope they can bring all the infrastructure that we need to offer to our customers. And, you know, we keep committed to O-RAN. O-RAN is really important. We are not compromising that. And I think the future is bright for both of us. >> Yeah, and Dell learns from the experience. >> Exactly. >> Absolutely. >> There's got to be a catalyst for expanding your roadmap and vision in telecom. >> Yeah, I mean, like you said, I mean, you asked a 2030 question and I think that, you know, know six, seven years from now I think people should look at what DISH and Dell and say they were the trailblazers of make, bringing Open RAN to the market and making 5G a reality. I mean, you talk about 5G, but every 5G is on a different stages. I do think that this combination, this partnership has the best chance to be the first ones to actually have a truly Open RAN network to be successful in commercial. >> Awesome guys. Trailblazers, Dell and DISH. Well, we look forward to watching this story unfold. Thank you- >> Thank you. >> for joining Dave and me on the program today talking about what you're doing together. We appreciate it. >> Thanks for having us. >> Our pleasure. >> Thank you, bye. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE live from Barcelona at MWC23. We'll be back after a short break, so we'll see you soon.

>> 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.

(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)

>> 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)

(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase. Topic is MarTech: Emerging Cloud-Scale Experience. This is season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. Talk about their value proposition and their company and all the good stuff that's going on. I'm your host, John Furrier. And today we're excited to be joined by Manyam Mallela who's the co-founder and head of AI at Blueshift. Great to have you on here to talk about the Blueshift-Intelligent Customer Engagement, Made Simple. Thanks for joining us today. >> Thank you, John. Thank you for having me. >> So last time we did our intro video. We put it out in the web. Got great feedback. One of the things that we talked about, which is resonating out there in the viral Twitter sphere and in the thought leadership circles is this concept that you mentioned called 10X marketer. That idea that you have a solution that can provide 10X value. Kind of a riff on the 10X engineer in the DevOps cloud world. What does it mean? And how does someone get there? >> Yeah, fantastic. I think that's a great way to start our discussion. I think a lot of organizations, especially as of this current economic environment are looking to say, I have limited resources, limited budgets, how do I actually achieve digital and customer engagement that helps move the needle for my key metrics, whether it's average revenue per user, lifetime value of the user and frequent interactions. Above all, the more frequently a brand is able to interact with their customers, the better they understand them, the better they can actually engage them. And that usually leads to long term good outcomes for both customer and the brand and the organizations. So the way I see 10X marketer is that you need to have tools that give you that speed and agility without hindering your ability to activate any of the campaigns or experience that you want to create. And I see the roadblocks usually for many organizations, is that kind of threefold. One is your data silos. Usually data that is on your sites, does not talk to your app data, does not talk to your social data, does not talk to your CRM data and so forth. So how do I break those silos? The second is channel silos. I actually have customers who are only engaging on email or some are on email and mobile apps. Some are on email and mobile apps and maybe the OTT TV in a Roku or one of the connected TV experiences, or maybe in the future, another Web3 environments. How do I actually break those channel silos so that I get a comprehensive view of the customer and my marketing team can engage with all of them in respect to the channel? So break the channel silos. And the last part, what I call like some of the little talked about is I call the inside silo, which is that, not only do you need to have the data, but you also have to have a common language to share and talk about within your organizations. What are we learning from our customers? What do we translate our learning and insight on this common data platform or fabric into an action? And that requires the shared language of how do I actually know my customers and what do I do with them? Like either the inside silo as well. I think a lot of times organizations do get into this habit like each one speaks their own language, but they don't actually are talking the common language of what did we actually know about the real customer there. >> Yeah, and I think that's a great conversation because there's two, when you hear 10X marketer or 10X conversations, it implies a couple things. One is you're breaking an old way and bringing in something new. And the new is a force multiplier, in this case, 10X marketer. But this is the cloud scale so marketing executives, chiefs, staffs, chiefs of staffs of CMOs and their staffs. They want to get that scale. So marketing at scale is now the table stakes. Now budget constraints are there as well. So you're starting to see, okay, I need to do more with less. Now the big question comes up is ROI. So I want to have AI. I want to have all these force multipliers. What do I got to do with the old? How do I handle that? How do I bring the new in and operationalize it? And if that's the case, I'm making a change. So I have to ask you, what's your view on the ROI of AI marketing, because this is a key component 'cause you've got scale factor here. You've got to force multiplier opportunity. How do you get that ROI on the table? >> I think that as you rightly said, it's table stakes. And I think the ROI of AI marketing starts with one very key simple premise that today some of the tools allow you to do things one at a time. So I can actually say, "can I run this campaign today?" And you can scramble your team, hustle your way, get everybody involved and run that campaign. And then tomorrow I'd say like, Hey, I looked at the results. Can I do this again? And they're like, oh, we just asked for all of us to get that done. How do I do it tomorrow? How do I do it next week? How do I do it for every single week for the rest of the year? That's where I think the AI marketing is essentially taking your insight, taking your creativity, and creating a platform and a tool that allows you to run this every single day. And that's agility at scale. That is not only a scale of the customer base, but scale across time. And that AI-based automation is the key ROI piece for a lot of AI marketing practitioners. So Forrester, for example, did a comprehensive total economic impact study with our customers. And what they found out was actually the 781% ROI that they reported in that particular report is based on three key factors. One is being able to do experiences that are intelligent at scale, day in and day out. So do your targeting, do your recommendations. Not just one day, but do it every single day. And don't hold back yourself on being able to do that. >> I think they got to get the return. They got to get the sales too. This is the numbers. >> That's right. They actually have real dollars, real numbers attached to it. They have a calculator. You can actually go in and plug your own numbers and get what you might expect from your existing customer base. The second is that once you have a unified platform like ours, the 10X marketer that we're talking about is actually able to do more. It's sometimes actually, it's kind of counterintuitive to think that a smaller team does more. But in reality, what we have seen, that is the case. When you actually have the right tools, the smaller teams actually achieve more. And that's the redundant operations, conflicting insights that go away into something more coherent and comprehensive. And that's the second insight that they found. And the third is just having reporting and all of the things in one place means that you can amplify it. You can amplify it across your paid media channels. You can amplify it across your promotions programs and other partnerships that you're running. >> That's the key thing about platforms that people don't understand is that you have a platform and it enables a lot of value. In this case, force multiplier value. It enables more value than you pay for it. But the key is it enables customers to do things without a line of code, meaning it's a platform. They're innovating on top of it. And that's, I think, where the ROI comes in and this leads me where the next question is. I wanted to ask you is, not to throw a wet blanket on the MarTech industry, but I got to think of when I hear marketing automation, I kind of think old. I think old, inadequate antiquated technologies. I think email blasting and just some boring stuff that just gets siloed or it's bespoke from something else. Are marketing automation tools created equal? Does something like, what you guys are doing with SmartHub? Change that, and can you just talk about that 'cause it's not going to go away. It's just another level that's going to be abstracted away under the coverage. >> Yeah, great question. Certainly, email marketing has been practiced for two or three decades now and in some form or another. I think we went from essentially what people call list-based marketing. I have a list, let me keep blasting the same message to everybody and then hopefully something will come out of it. A little bit more of saying, then they can, okay, maybe now I have CRM database and can I do database marketing, which they will call like, "Hey, Hi John. Hi Manyam", which is the first name. And that's all they think will get the customer excited about because you'll call them by name, which is certainly helpful, but not enough. I think now what we call like, the new age that we live in is that we call it graph-based marketing. And the way we materialize that is that every single user is interacting with a brand with their offerings. So that this interaction graph that's happening across millions of customers, across thousands of content articles, videos, shows, products, items, and that graph actually has much richer knowledge of what the customer wants than the first names or list-based ones. So I think the next evolution of marketing automation, even though the industry has been there a while, there is a step change in what can actually be done at scale. And which is taking that interaction graph and making that a part of the experience for the customer, and that's what we enable. That's why we do think of that as a big step change from how people are being practicing list-based marketing. And within that, certainly there is a relation of curve as to how people approach AI marketing and they are in a different spectrum. Some people are still at list-based marketing. Some people are database marketing. And hopefully will move them to this new interaction graph-based marketing. >> Yeah and I think the context is key. I like how you bring up the graph angle on this because the graph databases imply there's a lot of different optionality around what's happened contextually both over time and currently and it adds to it. Makes it smarter. It's not just siloed, just one dimensional. It feels like it's got a lot there. This is clearly I'm a big fan of and I think this is the way to go. As you get more personalization, you get more data. Graphic database makes a lot of sense. So I have to ask you, this is a really cutting edge value proposition, who are the primary buyers and users in an organization that you guys are working with? >> Yeah, great question. So we typically have CMO organizations approaching us with this problem and they usually talk to their CIO organizations, their counterparts, and the chief information officers have been investing in data fabrics, data lakes, data warehouses for the better part of last decade or two, and have some very cutting edge technology that goes into organizing all this data. But that doesn't still solve the problem of how do I take this data and make a meaningful, relevant, authentic experience for the customer. That's the CMO problem. And CMO are now challenge with creating product level experience with every interaction and that's where we coming. So the CMO are the buyers of our SmartHub CDP platform. And we're looking for consolidating hundreds of tools that they had in the past and making that one or two channel marketers. Actually, the 10X marketer that we talk about. And you need the right tool on top of your data lakes and data warehouses to be able to do that. So CMO are also the real drivers of using this technology. >> I think that also place the ROI equation around ROI and having that unified platform. Great call out there. I got to ask you the question here 'cause this comes up a lot and when I hear you talking, I think, okay, all the great stuff you guys have there. But if I'm a company, I want to make my core competencies mine. I don't really want to outsource or buy something that's going to be core to my business. But at the same time as market shifts, the business changes. And sometimes people don't even know what business they're in at the end of the day. And as it gets more complicated too, by the way. So the question comes up with companies and I can see this clearly, do I buy it? Do I build it? When it comes to AI because that's a core competency. Wait a minute, AI. I'm going to maybe buy some chatbot technology. That's not really AI, but it feels like AI, but I'm a company, I want to buy it or build it. That's a choice. What do you see there? 'Cause you guys have a very comprehensive platform. It's hard to replicate, imitates, inimitable. So what's your customers doing with respect buy and build? And where do they get the core competency? What do they get to have as a core competency? >> Fantastic. I think certainly, AI as it applies to at the organization level, I've seen this at my previous organization that I was part of, and there will be product and financial applications that are using AI for the service of that organization. So we do see, depending upon the size of the organization having in-house AI and data science teams. They are focused on these long term problems that they are doing as part of their product itself. Adjacent to that, the CMO organization gets some resources, but not certainly a lot. I think the CMO organization is usually challenged with the task, but not given the hundred people data science and engineering team to be able to go solve that. So what we see among our customer base is that they need agile platform to do most of the things that they need to do on a day to day basis, but augmented with what our in-house data science they have. So we are an extensible platform. What we have seen is that half of our customers use us solely for the AI needs. The other half certainly uses both AI modules that we provide and are actually augmented with things that they've already built. And we do not have a fight in that ring. But we do acknowledge and we do provide the right hooks for getting the data out of our system and bringing their AI back into our system. And we think that at the end of the day, if you want agility for the CMO, there should not be any barriers. >> It's like they're in the data business and that's the focus. So I think with what I hear you saying is that with your technology and platform, you're enabling to get them to be in the data business as fast as possible. >> That's right. >> Versus algorithm business, which they could add to over time. >> Certainly they could add to. But I think the bulk of competencies for the CMO are on the creative side. And certainly wrangling with data pipelines day in and day out and wondering what actually happened to a pipeline in the middle of the night is not probably what they would want to focus on. >> Not their core confidence. Yeah, I got that. >> That's right. >> You can do all the heavy lifting. I love that. I got to ask you on the Blueshift side on customer experience consumption. how can someone experience the product before buying? Is there a trial or POC? What's the scale and scope of operationalizing and getting the Blueshift value proposition in them? >> Yeah, great. So we actually recently released a fantastic way to experience our product. So if you go to our website, there's only one call-to-action saying, explore Blueshift. And if you click on that, without asking, anything other than your business email address, you're shown the full product. You're given a guided tour of all the possibilities. So you can actually experience what your marketing team would be doing in the product. And they call it Project Rover. We launched it very recently and we are seeing fantastic reception to that. I think a lot of times, as you said, there is that question mark of like, I have a marketing team that is already doing X, Y, Z. Now you are asking me to implement Blueshift. How would they actually experience the product? And now they can go in and experience the product. It's a great way to get the gist of the product in 10 clicks. Much more than going through any number of videos or articles. I think people really want to say, let me do those 10 clicks. And I know what impression that I can get from platform. So we do think that's a great way to experience the product and it's easily available from the main website. >> It's in the value proposition. It isn't always a straight line. And you got that technology. And I got to ask from between your experience with the customers that you're talking to, prospects, and customers, where do you see yourself winning deals on Customer Engagement, Made Simple because the word customer engagement's been around for a while, and it's become, I won't say cliche, but there's been different generational evolutions of technology that made that possible. Obviously, we're living in an era of high velocity Omni-Channel, a lot of data, the graph databases you mentioned are in there, big part of it. Where are you winning deals? Where are customers pain points where you are solving that specifically? >> Yeah, great question. So the organizations that come to us usually have one of the dimensions of either they have offering complexity, which is what catalog of content or videos or items do they offer to the customers. And on the data complexity on the other side is to what the scale of customer base that I usually target. And that problem has not gone away. I think the customer engagement, even though has been around for a while, the problem of engaging those customers at scale hasn't gone away and it only is getting harder and harder and organizations that have, especially on what we call the business-to-consumer side where the bulk of what marketing organizations in a B2C segments are doing. I have tens to millions of customers and how do I engage them day in and day out. And I think that all that problem is only getting harder because consumer preferences keeps shifting all the time. >> And where's your sweet spot for your customer? What size? Can you just share the target organization? Is it medium enterprise, large B2C, B2B2C? What's the focus area? >> Yeah, great question. So we have seen like startups that are in Silicon Valley. I have now half a million monthly active users, how do I actually engage them to customers and clients like LendingTree and PayPal and Discovery and BBC who have been in the business for multiple decades, have tens of millions of customers that they're engaging with. So that's kind of our sweet spot. We are certainly not maybe for small shop with maybe a hundred plus customers. But as you reach the scale of tens of thousands of customers, you start seeing this problem. And then you start to look out for solutions that are beyond, especially list-based marketing and email blast. >> So as the scale, you can dial up and down, but you have to have some enough scale to get the data pattern. >> That's right. >> If I can connect the dots there. >> I would probably say, looking at a hundred thousand or more monthly active customer base, and then you're trying to ramp up your own growth based on what you're learning and to engage those customers. >> It's like a bulldozer. You need the heavy equipment. Great conversation. For the last minute we have here Manyam, give you a plug for the company. What's going on? What are you guys doing? What's new? Give some success stories, your latest achievements. Take a minute to give a plug for the company. >> Yeah, great. We have been recognized by Deloitte as the fastest growth startup two years in a row and continuing to be on that streak. We have released currently integrations with AWS partners and Snowflake partners and data lake partners that allow implementing Blueshift a much streamlined experience with bidirectional integrations. We have now hundred plus data connectors and data integrations in our system and that takes care of many of our needs. And now, I think organizations that have been budget constraint and are trying to achieve a lot with a small team are actually going to look at these solutions and say, "Can I get there?" and "Can I become that 10X marketing organization? And as you have said, agility at scale is very, very hard to achieve. Being able to take your marketing team and achieve 10X requires the right platform and the right solution. We are ready for it. >> And every company's in the data business that's the asset. You guys make that sing for them. It's good stuff. Love the 10X. Love the scale. Manyam Mallela, thanks for coming on. Co-founder, Head of AI at Blueshift. This is the AWS Startup Showcase season two, episode three of the ongoing series covering the exciting startups from the AWS ecosystem. I'm John Furrier, your host. Thanks for watching. >> Thank you, John. (upbeat music)

(introductory riff) >> Hey everyone. Welcome to theCUBE's presentation of the "AWS Startup Showcase." This is Season 2, Episode 3 of our ongoing series that features great partners in the massive AWS partner ecosystem. This series is focused on, "MarTech, Emerging Cloud-Scale Customer Experiences." I'm Lisa Martin, and I've got two guests here with me to talk about this. Please welcome Daisy Urfer, Cloud Alliance Sales Director at Algolia, and Jason Lang, the Head of Product for Apply Digital. These folks are here to talk with us today about how Algolia's Search and Discovery enables customers to create dynamic realtime user experiences for those oh so demanding customers. Daisy and Jason, it's great to have you on the program. >> Great to be here. >> Thanks for having us. >> Daisy, we're going to go ahead and start with you. Give the audience an overview of Algolia, what you guys do, when you were founded, what some of the gaps were in the market that your founders saw and fixed? >> Sure. It's actually a really fun story. We were founded in 2012. We are an API first SaaS solution for Search and Discovery, but our founders actually started off with a search tool for mobile platforms, so just for your phone and it quickly expanded, we recognize the need across the market. It's been a really fun place to grow the business. And we have 11,000 customers today and growing every day, with 30 billion searches a week. So we do a lot of business, it's fun. >> Lisa: 30 billion searches a week and I saw some great customer brands, Locost, NBC Universal, you mentioned over 11,000. Talk to me a little bit about some of the technologies, I see that you have a search product, you have a recommendation product. What are some of those key capabilities that the products deliver? 'Cause as we know, as users, when we're searching for something, we expect it to be incredibly fast. >> Sure. Yeah. What's fun about Algolia is we are actually the second largest search engine on the internet today to Google. So we are right below the guy who's made search of their verb. So we really provide an overall search strategy. We provide a dashboard for our end users so they can provide the best results to their customers and what their customers see. Customers want to see everything from Recommend, which is our recommended engine. So when you search for that dress, it shows you the frequently bought together shoes that match, things like that, to things like promoted items and what's missing in the search results. So we do that with a different algorithm today. Most in the industry rank and they'll stack what you would want to see. We do kind of a pair for pair ranking system. So we really compare what you're looking for and it gives a much better result. >> And that's incredibly critical for users these days who want results in milliseconds. Jason, you, Apply Digital as a partner of Algolia, talk to us about Apply Digital, what it is that you guys do, and then give us a little bit of insight on that partnership. >> Sure. So Apply Digital was originally founded in 2016 in Vancouver, Canada. And we have offices in Vancouver, Toronto, New York, LA, San Francisco, Mexico city, Sao Paulo and Amsterdam. And we are a digital experiences agency. So brands and companies, and startups, and all the way from startups to major global conglomerates who have this desire to truly create these amazing digital experiences, it could be a website, it could be an app, it could be a full blown marketing platform, just whatever it is. And they lack either the experience or the internal resources, or what have you, then they come to us. And and we are end-to-end, we strategy, design, product, development, all the way through the execution side. And to help us out, we partner with organizations like Algolia to offer certain solutions, like an Algolia's case, like search recommendation, things like that, to our various clients and customers who are like, "Hey, I want to create this experience and it's going to require search, or it's going to require some sort of recommendation." And we're like, "Well, we highly recommend that you use Algolia. They're a partner of ours, they've been absolutely amazing over the time that we've had the partnership. And that's what we do." And honestly, for digital experiences, search is the essence of the internet, it just is. So, I cannot think of a single digital experience that doesn't require some sort of search or recommendation engine attached to it. So, and Algolia has just knocked it out of the park with their experience, not only from a customer experience, but also from a development experience. So that's why they're just an amazing, amazing partner to have. >> Sounds like a great partnership. Daisy, let's point it back over to you. Talk about some of those main challenges, Jason alluded to them, that businesses are facing, whether it's e-commerce, SaaS, a startup or whatnot, where search and recommendations are concerned. 'Cause we all, I think I've had that experience, where we're searching for something, and Daisy, you were describing how the recommendation engine works. And when we are searching for something, if I've already bought a tent, don't show me more tent, show me things that would go with it. What are some of those main challenges that Algolia solution just eliminates? >> Sure. So I think, one of the main challenges we have to focus on is, most of our customers are fighting against the big guides out there that have hundreds of engineers on staff, custom building a search solution. And our consumers expect that response. You expect the same search response that you get when you're streaming video content looking for a movie, from your big retailer shopping experiences. So what we want to provide is the ability to deliver that result with much less work and hassle and have it all show up. And we do that by really focusing on the results that the customers need and what that view needs to look like. We see a lot of our customers just experiencing a huge loss in revenue by only providing basic search. And because as Jason put it, search is so fundamental to the internet, we all think it's easy, we all think it's just basic. And when you provide basic, you don't get the shoes with the dress, you get just the text response results back. And so we want to make sure that we're providing that back to our customers. What we see average is even, and everybody's going mobile. A lot of times I know I do all my shopping on my phone a lot of the time, and 40%-50% better relevancy results for our customers for mobile users. That's a huge impact to their use case. >> That is huge. And when we talked about patients wearing quite thin the last couple of years. But we have this expectation in our consumer lives and in our business lives if we're looking for SaaS or software, or whatnot, that we're going to be able to find what we want that's relevant to what we're looking for. And you mentioned revenue impact, customer churn, brand reputation, those are all things that if search isn't done well, to your point, Daisy, if it's done in a basic fashion, those are some of the things that customers are going to experience. Jason, talk to us about why Algolia, what was it specifically about that technology that really led Apply Digital to say, "This is the right partner to help eliminate some of those challenges that our customers could face?" >> Sure. So I'm in the product world. So I have the wonderful advantage of not worrying about how something's built, that is left, unfortunately, to the poor, poor engineers that have to work with us, mad scientist, product people, who are like, "I want, make it do this. I don't know how, but make it do this." And one of the big things is, with Algolia is the lift to implement is really, really light. Working closely with our engineering team, and even with our customers/users and everything like that, you kind of alluded to it a little earlier, it's like, at the end of the day, if it's bad search, it's bad search. It just is. It's terrible. And people's attention span can now be measured in nanoseconds, but they don't care how it works, they just want it to work. I push a button, I want something to happen, period. There's an entire universe that is behind that button, and that's what Algolia has really focused on, that universe behind that button. So there's two ways that we use them, on a web experience, there's the embedded Search widget, which is really, really easy to implement, documentation, and I cannot speak high enough about documentation, is amazing. And then from the web aspect, I'm sorry, from the mobile aspect, it's very API fort. And any type of API implementation where you can customize the UI, which obviously you can imagine our clients are like, "No we want to have our own front end. We want to have our own custom experience." We use Algolia as that engine. Again, the documentation and the light lift of implementation is huge. That is a massive, massive bonus for why we partnered with them. Before product, I was an engineer a very long time ago. I've seen bad documentation. And it's like, (Lisa laughing) "I don't know how to imple-- I don't know what this is. I don't know how to implement this, I don't even know what I'm looking at." But with Algolia and everything, it's so simple. And I know I can just hear the Apply Digital technology team, just grinding sometimes, "Why is a product guy saying that (mumbles)? He should do it." But it is, it just the lift, it's the documentation, it's the support. And it's a full blown partnership. And that's why we went with it, and that's what we tell our clients. It's like, listen, this is why we chose Algolia, because eventually this experience we're creating for them is theirs, ultimately it's theirs. And then they are going to have to pick it up after a certain amount of time once it's theirs. And having that transition of, "Look this is how easy it is to implement, here is all the documentation, here's all the support that you get." It just makes that transition from us to them beautifully seamless. >> And that's huge. We often talk about hard metrics, but ease of use, ease of implementation, the documentation, the support, those are all absolutely business critical for the organization who's implementing the software, the fastest time to value they can get, can be table stakes, and it can be on also a massive competitive differentiator. Daisy, I want to go back to you in terms of hard numbers. Algolia has a recent force or Total Economic Impact, or TEI study that really has some compelling stats. Can you share some of those insights with us? >> Yeah. Absolutely. I think that this is the one of the most fun numbers to share. We have a recent report that came out, it shared that there's a 382% Return on Investment across three years by implementing Algolia. So that's increase to revenue, increased conversion rate, increased time on your site, 382% Return on Investment for the purchase. So we know our pricing's right, we know we're providing for our customers. We know that we're giving them the results that we need. I've been in the search industry for long enough to know that those are some amazing stats, and I'm really proud to work for them and be behind them. >> That can be transformative for a business. I think we've all had that experience of trying to search on a website and not finding anything of relevance. And sometimes I scratch my head, "Why is this experience still like this? If I could churn, I would." So having that ability to easily implement, have the documentation that makes sense, and get such high ROI in a short time period is hugely differentiated for businesses. And I think we all know, as Jason said, we measure response time in nanoseconds, that's how much patience and tolerance we all have on the business side, on the consumer side. So having that, not just this fast search, but the contextual search is table stakes for organizations these days. I'd love for you guys, and on either one of you can take this, to share a customer example or two, that really shows the value of the Algolia product, and then also maybe the partnership. >> So I'll go. We have a couple of partners in two vastly different industries, but both use Algolia as a solution for search. One of them is a, best way to put this, multinational biotech health company that has this-- We built for them this internal portal for all of their healthcare practitioners, their HCPs, so that they could access information, data, reports, wikis, the whole thing. And it's basically, almost their version of Wikipedia, but it's all internal, and you can imagine the level of of data security that it has to be, because this is biotech and healthcare. So we implemented Algolia as an internal search engine for them. And the three main reasons why we recommended Algolia, and we implemented Algolia was one, HIPAA compliance. That's the first one, it's like, if that's a no, we're not playing. So HIPAA compliance, again, the ease of search, the whole contextual search, and then the recommendations and things like that. It was a true, it didn't-- It wasn't just like a a halfhearted implementation of an internal search engine to look for files thing, it is a full blown search engine, specifically for the data that they want. And I think we're averaging, if I remember the numbers correctly, it's north of 200,000 searches a month, just on this internal portal specifically for their employees in their company. And it's amazing, it's absolutely amazing. And then conversely, we work with a pretty high level adventure clothing brand, standard, traditional e-commerce, stable mobile application, Lisa, what you were saying earlier. It's like, "I buy everything on my phone," thing. And so that's what we did. We built and we support their mobile application. And they wanted to use for search, they wanted to do a couple of things which was really interesting. They wanted do traditional search, search catalog, search skews, recommendations, so forth and so on, but they also wanted to do a store finder, which was kind of interesting. So, we'd said, all right, we're going to be implementing Algolia because the lift is going to be so much easier than trying to do everything like that. And we did, and they're using it, and massively successful. They are so happy with it, where it's like, they've got this really contextual experience where it's like, I'm looking for a store near me. "Hey, I've been looking for these items. You know, I've been looking for this puffy vest, and I'm looking for a store near me." It's like, "Well, there's a store near me but it doesn't have it, but there's a store closer to me and it does have it." And all of that wraps around what it is. And all of it was, again, using Algolia, because like I said earlier, it's like, if I'm searching for something, I want it to be correct. And I don't just want it to be correct, I want it to be relevant. >> Lisa: Yes. >> And I want it to feel personalized. >> Yes. >> I'm asking to find something, give me something that I am looking for. So yeah. >> Yeah. That personalization and that relevance is critical. I keep saying that word "critical," I'm overusing it, but it is, we have that expectation that whether it's an internal portal, as you talked about Jason, or it's an adventure clothing brand, or a grocery store, or an e-commerce site, that what they're going to be showing me is exactly what I'm looking for, that magic behind there that's almost border lines on creepy, but we want it. We want it to be able to make our lives easier whether we are on the consumer side, whether we on the business side. And I do wonder what the Go To Market is. Daisy, can you talk a little bit about, where do customers go that are saying, "Oh, I need to Algolia, and I want to be able to do that." Now, what's the GTM between both of these companies? >> So where to find us, you can find us on AWS Marketplace which another favorite place. You can quickly click through and find, but you can connect us through Apply Digital as well. I think, we try to be pretty available and meet our customers where they are. So we're open to any options, and we love exploring with them. I think, what is fun and I'd love to talk about as well, in the customer cases, is not just the e-commerce space, but also the content space. We have a lot of content customers, things about news, organizations, things like that. And since that's a struggle to deliver results on, it's really a challenge. And also you want it to be relevant, so up-to-date content. So it's not just about e-commerce, it's about all of your solution overall, but we hope that you'll find us on AWS Marketplace or anywhere else. >> Got it. And that's a great point, that it's not just e-commerce, it's content. And that's really critical for some industry, businesses across industries. Jason and Daisy, thank you so much for joining me talking about Algolia, Apply Digital, what you guys are doing together, and the huge impact that you're making to the customer user experience that we all appreciate and know, and come to expect these days is going to be awesome. We appreciate your insights. >> Thank you. >> Thank you >> For Daisy and Jason, I'm Lisa Martin. You're watching "theCUBE," our "AWS Startup Showcase, MarTech Emerging Cloud-Scale Customer Experiences." Keep it right here on "theCUBE" for more great content. We're the leader in live tech coverage. (ending riff)

>> theCUBE presents Dell Technologies World, brought to you by Dell. >> Hey everyone. Happy afternoon. Welcome back to theCUBE. This is Lisa Martin with Dave Vallante. We are on day three of our coverage of Dell Technologies World live from Las Vegas with about 7,000- 8,000 people here. It's been a great two and a half days. Lots of people are still here. We're going to be talking more about Dell Services. I got a couple of guys from Dell Technologies joining us next. Please welcome Patrick Mooney, Senior Vice President of Services Product Management at Dell and Satish Iyer, Vice President of Emerging Services at Dell. Guys, welcome to the program. >> Thank you. Good evening. Great to be here to you. >> Happy to be here. >> So isn't it great to be back in person? >> So great. >> Those hallway conversations you just can't replicate it for video conferencing, right? >> Yeah. >> Priceless. >> It is priceless, I agree. Patrick, let's start with you. Talk to us about from a customer's perspective. What are some of the key services they've been looking for the last couple of years particularly, and how has Dell changed its strategic direction to deliver? >> Great question. Customers want outcomes and services are at the heart of outcomes. So when we look at customers transforming we're continually transforming and modernizing what we do and everything we're doing is centered around making it easy to buy, easy to consume and just centered around the customer. >> What are people looking for these days, Satish? I mean, what's the top three or four priorities. And we know cyber's up there. The cloud. One is when customers are consuming cloud, now there is more and more what we call as customers are looking for full stack solutions. So they start with giving me the best infrastructure on the platforms. Now they're saying, "I'm going to use those infrastructure to drive X, Y, and Z. "Now Mr. Dell, can you come and gimme those tags? "So I don't need to worry about anything "and I can actually consume it in the cloud like way." That's been massive for us. >> So, how do you guys respond to that? I mean, things in our little business things change so fast. And we can, but we're little. We can move fast. Customers are saying, okay, pandemic forced match to digital and now we got to figure it out. And now we got to modernize our HQ. How are you able to keep up? How are you changing your strategy as your customers pull you in different directions? What's going on inside the organization to enable that? >> Yeah. I think the key is that we meet customers where they are and help them plot out where they want to be. And then bring them along that journey. And we've really spent a lot of time developing four practices to help get there. One's around data and applications another around multi-cloud, another around workforce and another around security and resiliency. And no matter where they want to be, whether they want to do it themselves. They want us to help them do it or they want us to do it for them, we're there for them and we'll help them get where they want to be. >> Do you have like formal customer councils or how do you actually, especially the last couple years staying engaged with those customers? >> Absolutely. We're always talking to customers. It is critical to the model and we got a lot of ideas and customers have a lot of ideas and we want to vet those and talk through them. So no matter what point we're at in our product development cycle, we're always talking with customers, "Hey, do we hear you right? "Is this the value you're looking for?" And as we're developing it, can you help us test it? And so on. And we do that through regular conversations, field testing, customer insight councils, and it just feels so great to be having face to face conversations again as well. >> What is- >> Oh, go ahead. >> I was going to say, what are some of the things that you've heard face to face this week in terms of the direction, what Dell Services is delivering? >> Well, one big one for sure is that remote workforce is here to stay. And in our workforce pillar we spent a lot of time around how do we make it easy for customers to manage a remote workforce? It's a big challenge. So we've recently we announced here at Dell World, Lifecycle Hub Services where we it's a managed service where we're helping customers manage their entire device lifecycle around their PC. So imagine this you have a new hire joint or somebody leaves, how do you get 'em that PC? Have it ready? Let Dell take care of all the logistics, we'll we'll store it. We'll configure it. We'll send it to 'em we'll take the old machines back, we'll kit it for 'em anything that's needed and fully integrated it from the customer system into our system. So it's all automated. >> Okay. And all the patching, et cetera, >> Everything. Okay. So you got four pillars, data and apps multi-cloud, workforce and resiliency. What you just described, the automation, does IP and what's the IP portfolio look like? How does it map into those four pillars? >> Sure, you want to take that? >> Sure, so obviously when you look at growth areas and services, it's absolutely important for us to develop sustainable IP. If you look at one of the areas where we have invested and we are growing is cloud managed services platform. So Dell is unique in terms of managing our customer services. We actually do full lifecycle management of the customers. So we invested quite a bit of, I would say time and energy and engineering efforts to basically solve problems in engineered way. So the customer cloud managed services platform allows us to actually bring both, you talked about apex before to our other colleagues. So it allows us to both bring apex services to our customers and also allows us to bring non apex services in terms of fully managed to our customers. >> So multi-cloud must be a rich opportunity's probably almost infinite. There's a lot of gaps there for IP development. What are you seeing and hearing from customer with regard to those gaps? >> So one of the key areas when you talk about multi-cloud is we talk to customers about is the solution things we talked about. So we launched, we announced three solutions one we already launched. And the two of them will be announced is customers want that end-to-end outcome, right? 'Cause they are saying, well we are currently where we started today. We announced cyber security as a service. As you guys know, within the current geopolitical climate, cyber attacks are common, ransomware is common. So, and this is something which we are doing today to customers. What customers want is the simplicity of offering. They're like, you can help us with cyber security when something happens I have an insurance policy, so I can actually go I know where my data sets are. I can record from it, but can you streamline it for me? I don't want all the headaches. Can you make sure that it's easily consumable and Dell can take care of everything for me. And we are also investing on other LED solutions like machine learning, high performance compute. And we are also looking at vertical areas. So our customers, especially in telco, Edge and enterprise applications. So we are looking at those as a full stack offerings so that we can actually educate and take our customers on the journey on our MacCloud platforms. >> I going to talk about Dell Services as a facilitator of multi-cloud Chuck Whitton was on stage, He was here yesterday talking about multi-cloud is here by default. Well, Dell wants to change that to multi-cloud by design. How can Dell Services be a facilitator of that transformation that customers in telco or whatever industry have going from, We've got it by default to now it's actually by design, facilitating that? >> Yeah. I'll jump in and let you take it, we have a a robust consulting practice which can help you come in and understand where you're at and where you want to be and design that future. So that it's not, as you said by default, it's absolutely multi-cloud by design. Anything you want to add? >> Yeah. I mean, look again Dell has been doing multi-cloud for a long time. We just didn't call it multi-cloud. I would probably say 2014, 2015, Dell's been there. We know our customers have a choice. We want to operationalize. We want to help our customers run workloads wherever they want to run. Now, we have a term for it. We have a dedicated way of talking about it. And again, more automation more IP development, more software. And again, taking a lot of the people part away from services and driving more innovation, more IPs where we are going to be able to differentiate. >> So you're a large and pretty sophisticated services organization. We've talked about some of your IP. You now bring that to your customers. What are some of the adoption barriers that they have? How are you addressing those, in terms of taking your IP and your ideas? And you probably say, "Hey, we got this, you can apply this". What are they not ready for? That you sort of advise them, okay you got to do, these are some maybe, some out scope things that you haven't talked about or thought about. >> Yeah. I mean, I'll take one. And I know Patrick will probably touch on, I would say two big ones. I can think about the one is data. One is on security, right? I'll give you the data use case. So data has gravity, right? When customers think about, multi-cloud think about solution, think about these services. It's not easy to take petabytes and terabytes of data and shift all over the place. It's very, very expensive. So a lot of their cloud strategy really hinges on where the data is, and how they're going to optimize those data for the outcomes they want to decide. And that's something a lot of our customers initially don't think about it as we actually go and talk to them about this specific use case and application that actually becomes forefront of the discussion. >> Yeah. On the security front, customers are just overwhelmed with the number of options in a very fragmented, extremely important space. So we've tried to make that very easy for them with our managed detection and response services, bringing the best of the industry and Dell Services together to give them a one stop shop managed service, let us watch for you so that you can run your business. And when we detect something, we'll advise you and help you respond. >> What's the tooling like there. I mean, you have, do you have your preferred tooling? Are the customers saying, well we got to use this vendor or that vendor, how do you manage all that complex? >> Of course we have our preferred tooling and we partner greatly with secure works to do it as well as some other company, but that said what's important to us with the service is that a customer meets specific, they're green in five different categories. And if they're green in those categories, then we're good to help them. And if they don't know how to do that, then we'll come in and do a security assessment to help them get there. And just taking what's very complicated and making it easy. >> On the security front. We've been talking about the cyber skills gap, massive skills gap that's been around for years. How is Dell Services facilitator of organizations being able to close that gap? >> Sure. In a few ways, one, we can just do it for you, right? Two, if you want to do it yourself, we can supplement you with security residents to help you manage through the complexity and cross train while as part of your staff. And then three, we have our Dell Education Services where we can come in and train you as well. So lots of different options on how you want to do it. >> Yeah. >> No matter what you choose, we're here for you. (panelists laughing) >> That people option's important. I mean, people being the biggest threat factor that there is, right. >> Absolutely. >> For sure. >> That's probably one of the hardest ones to augment. >> Yeah. I mean, that's the reason why when you look at cyber security customers, want somebody else to manage it because you don't want the same folks making the same mistake on an insurance policy. So they're like Dell, you manage it for me. So I don't have the same actor is doing same things. So I have somebody managing my data but somebody managing my record option. So in case something goes wrong I know it's a different handset different people who are much more relaxed when things go back >> That's always nice to have somebody that's relaxed in a crisis. >> Absolutely. And I think I'll take that in my personal life too. Guys thank you for joining Dave and me talking about what's new with Dell Services the modernization that you're undergoing and how your customers are really helping to evolve this strategy. We appreciate your insight. >> Thank you, Lisa. >> Thank you so much for your time. Great seeing you. >> Right. Likewise for Dave Vallante, I'm Lisa Martin. You're watching theCUBE. This is day three of our coverage of Dell Technologies World, live from Las Vegas, stick around Dave and I will be right back with our next guest. (bright music)

>> theCUBE presents Dell technologies World, brought to you by Dell. >> Hey everyone. Welcome back to theCUBE's live coverage of Dell Technologies World 2022, from the show floor, the Venetian in lively Las Vegas. Lisa Martin here with Dave Vellante. We're having a little reunion with our guests that we haven't seen in a couple years. Please welcome back to theCUBE, Doug Schmitt, President of Dell Technologies and Services. Alex Barretto joins us as well, the Senior Vice President at Emerging Services and Technology. Guys, it's great to see you in 3D. >> I know great to be back. >> Yes. >> Its Awesome to be back. >> Isn't it great? >> And fantastic. >> It is. >> We were talking about how we have to get our sea legs back about, even just interacting with in life. >> That's exactly right. Being able to see everybody be back in person at these events. And it's great to see everybody it's like coming back to family. >> It is, it's been a reunion since Sunday. One of the, obviously the last two years have been quite challenging for everybody, for customers. Dell is coming off it's best year ever in FY22, over 100 billion in revenues, 17% growth year over year, astounding growth. The voice of the customer is always strong here at Dell technologies. But Doug, talk to us about some of the things that have been going on services perspective and how you really stepped in to help customers across industries succeed in the dynamic times we've been living in. >> Well. Yeah, thank you, and you're right. Coming off a very great, great year. And I think as you can see behind us and in the room here just great solutions for our customers. And that's what it's about, delivering the outcomes. And service is a huge piece of that, of making sure we bring all that together, deliver the outcomes our customers are looking for. If you look at the overall services organization just to take a step back just a little bit, we are a team around over 60,000 folks in 170 countries. And look, it's about this life cycle of services we provide. Everything from consulting to deployment to our support, manage services, security, education services, residency services, all the way to asset sustainability and recovery. So we can get all of the material back in and recycle it. So we have a great suite of services, and it's bringing all that together for the customer again to deliver with the products and the solutions and the software, the outcomes they're looking for. You asked a little bit about just to kind of double click that, about what our customers really saying, kind of what they're hearing, what we're hearing. I think there's three things. When I think about what they're looking for, one is the trusted advisor. You heard this during Michael's keynotes speech, that is key. They're navigating through the digital transformation, hybrid cloud, all of these things. Determining what they need to do to deliver their outcomes. And Dell can bring that trusted advisor status to them. So we can consult with them professional services, help bring that. The second thing is really around that life cycle services I talked about, all those different services that we bring. We allow our customers clearly the choice to say what pieces of the services do they need. Now we think we can bring everything together into a managed solution for them, but if there's certain pieces that they need to just, double click on, we can help with that. And then look, the third item that I'm hearing and that we can bring and that we have for them is flexible consumption. They can choose the way they want to consume the technology. You consume it by usage. You can consume by month, by quarter, or if you want the stability of long term contracts one, two, three years we'll do that. So really it's about trusted advisor and choice to help them deliver their outcomes. >> So a lot changed during the isolation economy. You guys obviously had to support new initiatives. First of all, budgets got squeezed in 2020. Then boom back, so they sort of slingshot it, real focus on obviously client solutions, remote work, endpoint security, identity access, VDI. Now in the post isolation economy, it's like, okay, some of the stuff at HQ you maybe needs to be updated, maybe we're rethinking the network. So, what are you hearing from customers? Where are they in their digital transformations, Alex? You know, what's hot. >> Yeah, so we actually recently created an emerging services group. And the reason for that is exactly what you're alluding today. So we actually talked in that group everything in this emerging. So APEX, telco, edge, data management, all the things our customers are asking for and we are convening new solutions, new services to meet their needs, and all that is housing in one unit, and we're thinking about the product management, the technology that goes with it, and we're working partnership with our customers to actually build and develop solutions that they're looking for. >> Yeah, there was no as a service really. I mean, you could do it with financial machinations before, now it's becoming much more mainstream. I mean, I know it's not a hundred percent of your business and maybe never will be. >> Yeah. >> But that's a whole new mindset. What else is changing in the business that you guys see? >> Well, yeah, I think there's, I think that's what comes back to what we saw, first of all we listen to the customers, follow what their needs are, and you're right. As far as the, as a service, I think it's back to that choice. If they want to purchase or consume as flexible or as needed, we'll do that. They want the contracts, the standard CapEx model, we'll do that as well. Look, there's three things. Professional services is really changing as well. We're seeing the needs again for going in and being able to deliver the services to customers, but also manage that in a lot of cases, they're asking us to take the workloads from them so that they can go and change their transformation, and their digitalization is one of the things that we're clearly hearing. And I know you're hearing the second one, security. I mean that is top of mind for everyone. And I, we have launched a lot of services around this. Some of those like MDR or Managed Detection Response our cyber vault, as well as our APEX cyber recovery services as well that we've announced here. So security's number two. And then the third one is this sustainability, again very important for us and our customers, is we have a 2030 goal around this as I'm sure or you've heard, but more importantly, that's something I know my team and I and everyone at Dell, that's a great personal feeling too. When you're getting up and you're doing something that you know, is right, really just doing it to help the customers as well is just an extra added benefit. So those would be the three things professional services changing, doing more and more of the manage take workloads off, two is the security, and the third is the sustainability clearly. >> We talked with JJ Davis yesterday, and we're talking a lot about ESG and how a tremendous percentage of RFPs come in wanting to know what is Dell technologies doing from an environmental, social, governance perspective. That it's really your customers wanting to work with companies like Dell who have a focused clear agenda on ESG. One thing that I'm curious when you talk about the increase in advantage services, the great resignation. We've all, that's been happening now for a couple years. It's probably going to persist for a while. Customers suddenly, labor shortages and the supply chain issues. How have you helped organizations deal with some of the challenges that they're going through from a labor perspective is that why one of the reasons the managed services is we're seeing an increase there. >> Yeah. I'm sure that can be and I wouldn't doubt that, you mean in terms of our customer is wanting more and more the managed and the professional. Yeah, I think that is a piece of it, but I also think part of that is that speed matters and customers are looking for the additional assistance to take things off, that they may have traditionally done so that they can, they can really get this transformation, this hybrid cloud, getting things moving very, very quickly. There's just so much to be done in terms of data management and bringing information to their end user customers. And they want to spend more time doing that. And so I'm hearing that more, but you are right. There's absolutely, there's absolutely the times where we have a residency service, we, and that has been growing very, very fast. And that tends to be why they ask for it, is because people have either left or are leaving >> Alex, Doug really kind of alluded to an area that I want to probe a little bit. And it's that's, I was talking to Jen Felch recently she's going to be on soon. And the, you mentioned security, Doug, as the top initiative clearly. And the distance between number two is widening, but number two is cloud migration. Now I asked Jen about that, because internally Dell has its own cloud. And I said, how do you interpret that? Or how do you, what's your second priority? She goes, well, I would translate that into modernization. So we're essentially building our own cloud is how I interpreted it. So my question to you is, are you seeing that with customers, how closely do you work with your own IT to take those learnings to your customers? And what does modernization actually mean to your customers? >> Yeah, that's a great question. It's actually the essence of why we're here. Talking to our customers and showcasing what we do within services, what we do within IT. Jen and I talk very often about her roadmap, our roadmap, and we want to showcase that to our customers because it's a proof point, it's a proof point of how they can do the transformation on their own. Do we have a whole slue of products from a services standpoint that are tied with what Jen is doing as well? And that's what we bring to market. So whether that's on APEX, that we announced right here two days ago, the cyber recovery services available now, that's working very closely with our IT counterparts. And we have a whole slue of roadmap with high performance computing, to be announced soon and machine learning operations, all that is to meet the customer needs, and what they're asking for. And if you look at the emergence of needs from a customer standpoint, it goes in a multitude of uses. We have telco customers, they have very specific needs and we're looking to meet those needs. We have the traditional customers, which may be going at a slower speed in their adoption of the cloud, we're there to help them. And we're all about to hybrid cloud. Hybrid cloud is a hundred percent of our strategy. So whether you want to go cloud based, whether you want to be OnPrem or you want to be hybrid, we're there to solve your needs. >> What's the partner story in terms of delivering services, we know that the Dell technologies' partner ecosystem is massive. We know how important partners are to the growth. I think I saw 59 billion in revenue came through the channel last year alone. How do you enable partners to deliver some of those key services that you talked about? >> To leverage the partners for the, on the broader ecosystem for that? >> Yes. >> Yes, well, you're right. We do have a very large partner network and we're very flexible on that. Again, it sounds like we are flexible in everything and we are by the way, for our customers and our partners, 'cause look it is about delivering first of all, how our customers want their service. I do like this idea and we talk about modernization, transformation, digitalization all these things are kind of the same thing about going in and looking about how we're improving the overall infrastructure and these outcomes. And to that end, we work with the customer on what they're looking for. And then we'll either do a couple things with working with the partners. Either we take prime and we'll take that and take the pieces that they can deliver and we can deliver together. But again, it's with the customer in mind of how they want to do that, working with the customer. We do have code delivery services as well. And look, we're very open with our partners about if they want to be prime and then leverage those same lifecycle services we have. What this is about is about getting this transformation and this technology and these so into the hands of the customers in the best way possible. >> So, I could white label as a partner. Could I white label your services? >> We don't have the white label. >> Okay. >> We do have co-delivery. >> Okay. So that's what I could do. I can say, okay, I'm bringing this value. Dell's bringing that value. You're visible to the customer. >> That's correct. >> Which is I presume a benefit to the customer. >> Correct, correct. >> The trust that you've built up. >> Now that gets, just the white label you would say like our ProSeries, ProSupport, ProDeploy, ProManage, all of those things. Isn't a white label, but at the same time our customers especially in the professional service side of it could be the prime, which would be the same thing as a label. >> How are client? This is kind of interesting thought I had the other day. How are client services changing? Do you see the point where, I mean, maybe you're doing it already. It's just a full manage all my client devices and just take that away from me, and Dell you take care of that and I'll pay you a monthly fee. >> Well, yeah, we are seeing that. And one of the things that they like the best about is doing that management, is bringing kind of the AI and the BI to it that we can with our support assist and all of the data that we give back, we're actually able to help manage those environments much better. And in terms of an end to end, keep things updated, upgraded, manage it. But more importantly, what we see when we do have those client managed services end to end, the customers are actually coming back and asking us to help improve their operational performance. And, and what I mean by that is, all of a sudden you'll see things where the trouble tickets are coming in 'cause we're seeing that. And we're actually going back in with that information to help alleviate or improve their operational processes, so that they're able to function and spend more time on their business outcomes >> And reduce that complexity, sorry, Dave. >> No worries. How about the tip of the spear, the consulting piece? What are you seeing there? Are we going through and as we modernize, are we going through another wave of application rationalization, people trying to figure out their digital transformation, what to double down on? What to retire? What to sun set? What's that like? >> Yeah, I think it's similar to the managed service conversation we just had. It's really pivoting to technology. Even in the services space, it was all about our physical footprint. Five, six years ago, our physical capabilities, the number of people, depots et cetera that we had, right now, our customers and even internally what we're pivoting towards is technology. They want to know how are you going to do is solve our problems, whether it's consulting or managed services using technology. Precisely to the point that Doug was making, because they want insights, value add from the services we provide, not just consult for me, not just manage my service, but provide me value added service on top of that so that I can actually differentiate my services, my solutions and that's where we're building, that's what delivering really leveraging technology. You look at the number of software engineers we have, data scientists, the algorithms we're building now inside services. It's really become a technology hub, whereas it used to be a physical hub. >> I'm just going to, oh, I'm sorry please. >> No, go ahead. >> Follow up. >> Where it's really headed is, if you look at this it's going to become this outcome based services. When I talk about outcome based services, it's not managing just the IT infrastructure, that you have to do, you have to modernize and transform. However you want to say that to customers. But in addition to that, they're looking for us to take that information and help change their business models as well, with the data and the and the insights we're getting back. >> Their operating model. >> Absolutely. >> But changing that in the last couple years and pivoting over and over again, to survive and to thrive, talk to us, Alex about the emerging services and how you've maybe a particular customer example of how you've helped an organization radically transform in the last two years to be competitive and to be thriving in this new economy in which we're living. >> Yeah. I think a great example is Dish. If you look at Dish, they're actually launching one of the first Open RAN networks. Leveraging the power of 5G. And we're working very closely with them on the services and solutions to enable them to deliver that service to their customers. And that's a new area for us, a new area for them. So we're actually working together in innovating and coming up with solutions and bringing those to the market. It's a great example. >> Lot of collaboration guys, thank you so much for joining us. Great to see you back in person again after couple years, probably three. We appreciate your time and your insights. >> Thanks guys. >> Thanks for having us. >> Our pleasure. Dave Vellante, Lisa Martin here, you're watching theCUBE's live from Dell Technologies World 2022. Stick around. Be right back with our next guest. (gentle music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data driven insights from theCUBE in ETR, this is Breaking Analysis with Dave Vellante. >> The introduction in socialization of data mesh has caused practitioners, business technology executives, and technologists to pause, and ask some probing questions about the organization of their data teams, their data strategies, future investments, and their current architectural approaches. Some in the technology community have embraced the concept, others have twisted the definition, while still others remain oblivious to the momentum building around data mesh. Here we are in the early days of data mesh adoption. Organizations that have taken the plunge will tell you that aligning stakeholders is a non-trivial effort, but necessary to break through the limitations that monolithic data architectures and highly specialized teams have imposed over frustrated business and domain leaders. However, practical data mesh examples often lie in the eyes of the implementer, and may not strictly adhere to the principles of data mesh. Now, part of the problem is lack of open technologies and standards that can accelerate adoption and reduce friction, and that's what we're going to talk about today. Some of the key technology and architecture questions around data mesh. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR, and in this Breaking Analysis, we welcome back the founder of data mesh and director of Emerging Technologies at Thoughtworks, Zhamak Dehghani. Hello, Zhamak. Thanks for being here today. >> Hi Dave, thank you for having me back. It's always a delight to connect and have a conversation. Thank you. >> Great, looking forward to it. Okay, so before we get into it in the technology details, I just want to quickly share some data from our friends at ETR. You know, despite the importance of data initiative since the pandemic, CIOs and IT organizations have had to juggle of course, a few other priorities, this is why in the survey data, cyber and cloud computing are rated as two most important priorities. Analytics and machine learning, and AI, which are kind of data topics, still make the top of the list, well ahead of many other categories. And look, a sound data architecture and strategy is fundamental to digital transformations, and much of the past two years, as we've often said, has been like a forced march into digital. So while organizations are moving forward, they really have to think hard about the data architecture decisions that they make, because it's going to impact them, Zhamak, for years to come, isn't it? >> Yes, absolutely. I mean, we are moving really from, slowly moving from reason based logical algorithmic to model based computation and decision making, where we exploit the patterns and signals within the data. So data becomes a very important ingredient, of not only decision making, and analytics and discovering trends, but also the features and applications that we build for the future. So we can't really ignore it, and as we see, some of the existing challenges around getting value from data is not necessarily that no longer is access to computation, is actually access to trustworthy, reliable data at scale. >> Yeah, and you see these domains coming together with the cloud and obviously it has to be secure and trusted, and that's why we're here today talking about data mesh. So let's get into it. Zhamak, first, your new book is out, 'Data Mesh: Delivering Data-Driven Value at Scale' just recently published, so congratulations on getting that done, awesome. Now in a recent presentation, you pulled excerpts from the book and we're going to talk through some of the technology and architectural considerations. Just quickly for the audience, four principles of data mesh. Domain driven ownership, data as product, self-served data platform and federated computational governance. So I want to start with self-serve platform and some of the data that you shared recently. You say that, "Data mesh serves autonomous domain oriented teams versus existing platforms, which serve a centralized team." Can you elaborate? >> Sure. I mean the role of the platform is to lower the cognitive load for domain teams, for people who are focusing on the business outcomes, the technologies that are building the applications, to really lower the cognitive load for them, to be able to work with data. Whether they are building analytics, automated decision making, intelligent modeling. They need to be able to get access to data and use it. So the role of the platform, I guess, just stepping back for a moment is to empower and enable these teams. Data mesh by definition is a scale out model. It's a decentralized model that wants to give autonomy to cross-functional teams. So it is core requires a set of tools that work really well in that decentralized model. When we look at the existing platforms, they try to achieve this similar outcome, right? Lower the cognitive load, give the tools to data practitioners, to manage data at scale because today centralized teams, really their job, the centralized data teams, their job isn't really directly aligned with a one or two or different, you know, business units and business outcomes in terms of getting value from data. Their job is manage the data and make the data available for then those cross-functional teams or business units to use the data. So the platforms they've been given are really centralized around or tuned to work with this structure as a team, structure of centralized team. Although on the surface, it seems that why not? Why can't I use my, you know, cloud storage or computation or data warehouse in a decentralized way? You should be able to, but some changes need to happen to those online platforms. As an example, some cloud providers simply have hard limits on the number of like account storage, storage accounts that you can have. Because they never envisaged you have hundreds of lakes. They envisage one or two, maybe 10 lakes, right. They envisage really centralizing data, not decentralizing data. So I think we see a shift in thinking about enabling autonomous independent teams versus a centralized team. >> So just a follow up if I may, we could be here for a while. But so this assumes that you've sorted out the organizational considerations? That you've defined all the, what a data product is and a sub product. And people will say, of course we use the term monolithic as a pejorative, let's face it. But the data warehouse crowd will say, "Well, that's what data march did. So we got that covered." But Europe... The primest of data mesh, if I understand it is whether it's a data march or a data mart or a data warehouse, or a data lake or whatever, a snowflake warehouse, it's a node on the mesh. Okay. So don't build your organization around the technology, let the technology serve the organization is that-- >> That's a perfect way of putting it, exactly. I mean, for a very long time, when we look at decomposition of complexity, we've looked at decomposition of complexity around technology, right? So we have technology and that's maybe a good segue to actually the next item on that list that we looked at. Oh, I need to decompose based on whether I want to have access to raw data and put it on the lake. Whether I want to have access to model data and put it on the warehouse. You know I need to have a team in the middle to move the data around. And then try to figure organization into that model. So data mesh really inverses that, and as you said, is look at the organizational structure first. Then scale boundaries around which your organization and operation can scale. And then the second layer look at the technology and how you decompose it. >> Okay. So let's go to that next point and talk about how you serve and manage autonomous interoperable data products. Where code, data policy you say is treated as one unit. Whereas your contention is existing platforms of course have independent management and dashboards for catalogs or storage, et cetera. Maybe we double click on that a bit. >> Yeah. So if you think about that functional, or technical decomposition, right? Of concerns, that's one way, that's a very valid way of decomposing, complexity and concerns. And then build solutions, independent solutions to address them. That's what we see in the technology landscape today. We will see technologies that are taking care of your management of data, bring your data under some sort of a control and modeling. You'll see technology that moves that data around, will perform various transformations and computations on it. And then you see technology that tries to overlay some level of meaning. Metadata, understandability, discovery was the end policy, right? So that's where your data processing kind of pipeline technologies versus data warehouse, storage, lake technologies, and then the governance come to play. And over time, we decomposed and we compose, right? Deconstruct and reconstruct back this together. But, right now that's where we stand. I think for data mesh really to become a reality, as in independent sources of data and teams can responsibly share data in a way that can be understood right then and there can impose policies, right then when the data gets accessed in that source and in a resilient manner, like in a way that data changes structure of the data or changes to the scheme of the data, doesn't have those downstream down times. We've got to think about this new nucleus or new units of data sharing. And we need to really bring back transformation and governing data and the data itself together around these decentralized nodes on the mesh. So that's another, I guess, deconstruction and reconstruction that needs to happen around the technology to formulate ourselves around the domains. And again the data and the logic of the data itself, the meaning of the data itself. >> Great. Got it. And we're going to talk more about the importance of data sharing and the implications. But the third point deals with how operational, analytical technologies are constructed. You've got an app DevStack, you've got a data stack. You've made the point many times actually that we've contextualized our operational systems, but not our data systems, they remain separate. Maybe you could elaborate on this point. >> Yes. I think this is, again, has a historical background and beginning. For a really long time, applications have dealt with features and the logic of running the business and encapsulating the data and the state that they need to run that feature or run that business function. And then we had for anything analytical driven, which required access data across these applications and across the longer dimension of time around different subjects within the organization. This analytical data, we had made a decision that, "Okay, let's leave those applications aside. Let's leave those databases aside. We'll extract the data out and we'll load it, or we'll transform it and put it under the analytical kind of a data stack and then downstream from it, we will have analytical data users, the data analysts, the data sciences and the, you know, the portfolio of users that are growing use that data stack. And that led to this really separation of dual stack with point to point integration. So applications went down the path of transactional databases or urban document store, but using APIs for communicating and then we've gone to, you know, lake storage or data warehouse on the other side. If we are moving and that again, enforces the silo of data versus app, right? So if we are moving to the world that our missions that are ambitions around making applications, more intelligent. Making them data driven. These two worlds need to come closer. As in ML Analytics gets embedded into those app applications themselves. And the data sharing, as a very essential ingredient of that, gets embedded and gets closer, becomes closer to those applications. So, if you are looking at this now cross-functional, app data, based team, right? Business team, then the technology stacks can't be so segregated, right? There has to be a continuum of experience from app delivery, to sharing of the data, to using that data, to embed models back into those applications. And that continuum of experience requires well integrated technologies. I'll give you an example, which actually in some sense, we are somewhat moving to that direction. But if we are talking about data sharing or data modeling and applications use one set of APIs, you know, HTTP compliant, GraQL or RAC APIs. And on the other hand, you have proprietary SQL, like connect to my database and run SQL. Like those are very two different models of representing and accessing data. So we kind of have to harmonize or integrate those two worlds a bit more closely to achieve that domain oriented cross-functional teams. >> Yeah. We are going to talk about some of the gaps later and actually you look at them as opportunities, more than barriers. But they are barriers, but they're opportunities for more innovation. Let's go on to the fourth one. The next point, it deals with the roles that the platform serves. Data mesh proposes that domain experts own the data and take responsibility for it end to end and are served by the technology. Kind of, we referenced that before. Whereas your contention is that today, data systems are really designed for specialists. I think you use the term hyper specialists a lot. I love that term. And the generalist are kind of passive bystanders waiting in line for the technical teams to serve them. >> Yes. I mean, if you think about the, again, the intention behind data mesh was creating a responsible data sharing model that scales out. And I challenge any organization that has a scaled ambitions around data or usage of data that relies on small pockets of very expensive specialists resources, right? So we have no choice, but upscaling cross-scaling. The majority population of our technologists, we often call them generalists, right? That's a short hand for people that can really move from one technology to another technology. Sometimes we call them pandric people sometimes we call them T-shaped people. But regardless, like we need to have ability to really mobilize our generalists. And we had to do that at Thoughtworks. We serve a lot of our clients and like many other organizations, we are also challenged with hiring specialists. So we have tested the model of having a few specialists, really conveying and translating the knowledge to generalists and bring them forward. And of course, platform is a big enabler of that. Like what is the language of using the technology? What are the APIs that delight that generalist experience? This doesn't mean no code, low code. We have to throw away in to good engineering practices. And I think good software engineering practices remain to exist. Of course, they get adopted to the world of data to build resilient you know, sustainable solutions, but specialty, especially around kind of proprietary technology is going to be a hard one to scale. >> Okay. I'm definitely going to come back and pick your brain on that one. And, you know, your point about scale out in the examples, the practical examples of companies that have implemented data mesh that I've talked to. I think in all cases, you know, there's only a handful that I've really gone deep with, but it was their hadoop instances, their clusters wouldn't scale, they couldn't scale the business and around it. So that's really a key point of a common pattern that we've seen now. I think in all cases, they went to like the data lake model and AWS. And so that maybe has some violation of the principles, but we'll come back to that. But so let me go on to the next one. Of course, data mesh leans heavily, toward this concept of decentralization, to support domain ownership over the centralized approaches. And we certainly see this, the public cloud players, database companies as key actors here with very large install bases, pushing a centralized approach. So I guess my question is, how realistic is this next point where you have decentralized technologies ruling the roost? >> I think if you look at the history of places, in our industry where decentralization has succeeded, they heavily relied on standardization of connectivity with, you know, across different components of technology. And I think right now you are right. The way we get value from data relies on collection. At the end of the day, collection of data. Whether you have a deep learning machinery model that you're training, or you have, you know, reports to generate. Regardless, the model is bring your data to a place that you can collect it, so that we can use it. And that leads to a naturally set of technologies that try to operate as a full stack integrated proprietary with no intention of, you know, opening, data for sharing. Now, conversely, if you think about internet itself, web itself, microservices, even at the enterprise level, not at the planetary level, they succeeded as decentralized technologies to a large degree because of their emphasis on open net and openness and sharing, right. API sharing. We don't talk about, in the API worlds, like we don't say, you know, "I will build a platform to manage your logical applications." Maybe to a degree but we actually moved away from that. We say, "I'll build a platform that opens around applications to manage your APIs, manage your interfaces." Right? Give you access to API. So I think the shift needs to... That definition of decentralized there means really composable, open pieces of the technology that can play nicely with each other, rather than a full stack, all have control of your data yet being somewhat decentralized within the boundary of my platform. That's just simply not going to scale if data needs to come from different platforms, different locations, different geographical locations, it needs to rethink. >> Okay, thank you. And then the final point is, is data mesh favors technologies that are domain agnostic versus those that are domain aware. And I wonder if you could help me square the circle cause it's nuanced and I'm kind of a 100 level student of your work. But you have said for example, that the data teams lack context of the domain and so help us understand what you mean here in this case. >> Sure. Absolutely. So as you said, we want to take... Data mesh tries to give autonomy and decision making power and responsibility to people that have the context of those domains, right? The people that are really familiar with different business domains and naturally the data that that domain needs, or that naturally the data that domains shares. So if the intention of the platform is really to give the power to people with most relevant and timely context, the platform itself naturally becomes as a shared component, becomes domain agnostic to a large degree. Of course those domains can still... The platform is a (chuckles) fairly overloaded world. As in, if you think about it as a set of technology that abstracts complexity and allows building the next level solutions on top, those domains may have their own set of platforms that are very much doing agnostic. But as a generalized shareable set of technologies or tools that allows us share data. So that piece of technology needs to relinquish the knowledge of the context to the domain teams and actually becomes domain agnostic. >> Got it. Okay. Makes sense. All right. Let's shift gears here. Talk about some of the gaps and some of the standards that are needed. You and I have talked about this a little bit before, but this digs deeper. What types of standards are needed? Maybe you could walk us through this graphic, please. >> Sure. So what I'm trying to depict here is that if we imagine a world that data can be shared from many different locations, for a variety of analytical use cases, naturally the boundary of what we call a node on the mesh will encapsulates internally a fair few pieces. It's not just the boundary of that, not on the mesh, is the data itself that it's controlling and updating and maintaining. It's of course a computation and the code that's responsible for that data. And then the policies that continue to govern that data as long as that data exists. So if that's the boundary, then if we shift that focus from implementation details, that we can leave that for later, what becomes really important is the scene or the APIs and interfaces that this node exposes. And I think that's where the work that needs to be done and the standards that are missing. And we want the scene and those interfaces be open because that allows, you know, different organizations with different boundaries of trust to share data. Not only to share data to kind of move that data to yes, another location, to share the data in a way that distributed workloads, distributed analytics, distributed machine learning model can happen on the data where it is. So if you follow that line of thinking around the centralization and connection of data versus collection of data, I think the very, very important piece of it that needs really deep thinking, and I don't claim that I have done that, is how do we share data responsibly and sustainably, right? That is not brittle. If you think about it today, the ways we share data, one of the very common ways is around, I'll give you a JDC endpoint, or I give you an endpoint to your, you know, database of choice. And now as technology, whereas a user actually, you can now have access to the schema of the underlying data and then run various queries or SQL queries on it. That's very simple and easy to get started with. That's why SQL is an evergreen, you know, standard or semi standard, pseudo standard that we all use. But it's also very brittle, because we are dependent on a underlying schema and formatting of the data that's been designed to tell the computer how to store and manage the data. So I think that the data sharing APIs of the future really need to think about removing this brittle dependencies, think about sharing, not only the data, but what we call metadata, I suppose. Additional set of characteristics that is always shared along with data to make the data usage, I suppose ethical and also friendly for the users and also, I think we have to... That data sharing API, the other element of it, is to allow kind of computation to run where the data exists. So if you think about SQL again, as a simple primitive example of computation, when we select and when we filter and when we join, the computation is happening on that data. So maybe there is a next level of articulating, distributed computational data that simply trains models, right? Your language primitives change in a way to allow sophisticated analytical workloads run on the data more responsibly with policies and access control and force. So I think that output port that I mentioned simply is about next generation data sharing, responsible data sharing APIs. Suitable for decentralized analytical workloads. >> So I'm not trying to bait you here, but I have a follow up as well. So you schema, for all its good creates constraints. No schema on right, that didn't work, cause it was just a free for all and it created the data swamps. But now you have technology companies trying to solve that problem. Take Snowflake for example, you know, enabling, data sharing. But it is within its proprietary environment. Certainly Databricks doing something, you know, trying to come at it from its angle, bringing some of the best to data warehouse, with the data science. Is your contention that those remain sort of proprietary and defacto standards? And then what we need is more open standards? Maybe you could comment. >> Sure. I think the two points one is, as you mentioned. Open standards that allow... Actually make the underlying platform invisible. I mean my litmus test for a technology provider to say, "I'm a data mesh," (laughs) kind of compliant is, "Is your platform invisible?" As in, can I replace it with another and yet get the similar data sharing experience that I need? So part of it is that. Part of it is open standards, they're not really proprietary. The other angle for kind of sharing data across different platforms so that you know, we don't get stuck with one technology or another is around APIs. It is around code that is protecting that internal schema. So where we are on the curve of evolution of technology, right now we are exposing the internal structure of the data. That is designed to optimize certain modes of access. We're exposing that to the end client and application APIs, right? So the APIs that use the data today are very much aware that this database was optimized for machine learning workloads. Hence you will deal with a columnar storage of the file versus this other API is optimized for a very different, report type access, relational access and is optimized around roles. I think that should become irrelevant in the API sharing of the future. Because as a user, I shouldn't care how this data is internally optimized, right? The language primitive that I'm using should be really agnostic to the machine optimization underneath that. And if we did that, perhaps this war between warehouse or lake or the other will become actually irrelevant. So we're optimizing for that human best human experience, as opposed to the best machine experience. We still have to do that but we have to make that invisible. Make that an implementation concern. So that's another angle of what should... If we daydream together, the best experience and resilient experience in terms of data usage than these APIs with diagnostics to the internal storage structure. >> Great, thank you for that. We've wrapped our ankles now on the controversy, so we might as well wade all the way in, I can't let you go without addressing some of this. Which you've catalyzed, which I, by the way, I see as a sign of progress. So this gentleman, Paul Andrew is an architect and he gave a presentation I think last night. And he teased it as quote, "The theory from Zhamak Dehghani versus the practical experience of a technical architect, AKA me," meaning him. And Zhamak, you were quick to shoot back that data mesh is not theory, it's based on practice. And some practices are experimental. Some are more baked and data mesh really avoids by design, the specificity of vendor or technology. Perhaps you intend to frame your post as a technology or vendor specific, specific implementation. So touche, that was excellent. (Zhamak laughs) Now you don't need me to defend you, but I will anyway. You spent 14 plus years as a software engineer and the better part of a decade consulting with some of the most technically advanced companies in the world. But I'm going to push you a little bit here and say, some of this tension is of your own making because you purposefully don't talk about technologies and vendors. Sometimes doing so it's instructive for us neophytes. So, why don't you ever like use specific examples of technology for frames of reference? >> Yes. My role is pushes to the next level. So, you know everybody picks their fights, pick their battles. My role in this battle is to push us to think beyond what's available today. Of course, that's my public persona. On a day to day basis, actually I work with clients and existing technology and I think at Thoughtworks we have given the talk we gave a case study talk with a colleague of mine and I intentionally got him to talk about (indistinct) I want to talk about the technology that we use to implement data mesh. And the reason I haven't really embraced, in my conversations, the specific technology. One is, I feel the technology solutions we're using today are still not ready for the vision. I mean, we have to be in this transitional step, no matter what we have to be pragmatic, of course, and practical, I suppose. And use the existing vendors that exist and I wholeheartedly embrace that, but that's just not my role, to show that. I've gone through this transformation once before in my life. When microservices happened, we were building microservices like architectures with technology that wasn't ready for it. Big application, web application servers that were designed to run these giant monolithic applications. And now we're trying to run little microservices onto them. And the tail was riding the dock, the environmental complexity of running these services was consuming so much of our effort that we couldn't really pay attention to that business logic, the business value. And that's where we are today. The complexity of integrating existing technologies is really overwhelmingly, capturing a lot of our attention and cost and effort, money and effort as opposed to really focusing on the data product themselves. So it's just that's the role I have, but it doesn't mean that, you know, we have to rebuild the world. We've got to do with what we have in this transitional phase until the new generation, I guess, technologies come around and reshape our landscape of tools. >> Well, impressive public discipline. Your point about microservice is interesting because a lot of those early microservices, weren't so micro and for the naysayers look past this, not prologue, but Thoughtworks was really early on in the whole concept of microservices. So be very excited to see how this plays out. But now there was some other good comments. There was one from a gentleman who said the most interesting aspects of data mesh are organizational. And that's how my colleague Sanji Mohan frames data mesh versus data fabric. You know, I'm not sure, I think we've sort of scratched the surface today that data today, data mesh is more. And I still think data fabric is what NetApp defined as software defined storage infrastructure that can serve on-prem and public cloud workloads back whatever, 2016. But the point you make in the thread that we're showing you here is that you're warning, and you referenced this earlier, that the segregating different modes of access will lead to fragmentation. And we don't want to repeat the mistakes of the past. >> Yes, there are comments around. Again going back to that original conversation that we have got this at a macro level. We've got this tendency to decompose complexity based on technical solutions. And, you know, the conversation could be, "Oh, I do batch or you do a stream and we are different."' They create these bifurcations in our decisions based on the technology where I do events and you do tables, right? So that sort of segregation of modes of access causes accidental complexity that we keep dealing with. Because every time in this tree, you create a new branch, you create new kind of new set of tools and then somehow need to be point to point integrated. You create new specialization around that. So the least number of branches that we have, and think about really about the continuum of experiences that we need to create and technologies that simplify, that continuum experience. So one of the things, for example, give you a past experience. I was really excited around the papers and the work that came around on Apache Beam, and generally flow based programming and stream processing. Because basically they were saying whether you are doing batch or whether you're doing streaming, it's all one stream. And sometimes the window of time, narrows and sometimes the window of time over which you're computing, widens and at the end of today, is you are just getting... Doing the stream processing. So it is those sort of notions that simplify and create continuum of experience. I think resonate with me personally, more than creating these tribal fights of this type versus that mode of access. So that's why data mesh naturally selects kind of this multimodal access to support end users, right? The persona of end users. >> Okay. So the last topic I want to hit, this whole discussion, the topic of data mesh it's highly nuanced, it's new, and people are going to shoehorn data mesh into their respective views of the world. And we talked about lake houses and there's three buckets. And of course, the gentleman from LinkedIn with Azure, Microsoft has a data mesh community. See you're going to have to enlist some serious army of enforcers to adjudicate. And I wrote some of the stuff down. I mean, it's interesting. Monte Carlo has a data mesh calculator. Starburst is leaning in, chaos. Search sees themselves as an enabler. Oracle and Snowflake both use the term data mesh. And then of course you've got big practitioners J-P-M-C, we've talked to Intuit, Orlando, HelloFresh has been on, Netflix has this event based sort of streaming implementation. So my question is, how realistic is it that the clarity of your vision can be implemented and not polluted by really rich technology companies and others? (Zhamak laughs) >> Is it even possible, right? Is it even possible? That's a yes. That's why I practice then. This is why I should practice things. Cause I think, it's going to be hard. What I'm hopeful, is that the socio-technical, Leveling Data mentioned that this is a socio-technical concern or solution, not just a technology solution. Hopefully always brings us back to, you know, the reality that vendors try to sell you safe oil that solves all of your problems. (chuckles) All of your data mesh problems. It's just going to cause more problem down the track. So we'll see, time will tell Dave and I count on you as one of those members of, (laughs) you know, folks that will continue to share their platform. To go back to the roots, as why in the first place? I mean, I dedicated a whole part of the book to 'Why?' Because we get, as you said, we get carried away with vendors and technology solution try to ride a wave. And in that story, we forget the reason for which we even making this change and we are going to spend all of this resources. So hopefully we can always come back to that. >> Yeah. And I think we can. I think you have really given this some deep thought and as we pointed out, this was based on practical knowledge and experience. And look, we've been trying to solve this data problem for a long, long time. You've not only articulated it well, but you've come up with solutions. So Zhamak, thank you so much. We're going to leave it there and I'd love to have you back. >> Thank you for the conversation. I really enjoyed it. And thank you for sharing your platform to talk about data mesh. >> Yeah, you bet. All right. And I want to thank my colleague, Stephanie Chan, who helps research topics for us. Alex Myerson is on production and Kristen Martin, Cheryl Knight and Rob Hoff on editorial. Remember all these episodes are available as podcasts, wherever you listen. And all you got to do is search Breaking Analysis Podcast. Check out ETR's website at etr.ai for all the data. And we publish a full report every week on wikibon.com, siliconangle.com. You can reach me by email david.vellante@siliconangle.com or DM me @dvellante. Hit us up on our LinkedIn post. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, stay safe, be well. And we'll see you next time. (bright 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. >> Recent survey data from ETR shows that enterprise tech spending is tracking with projected US GDP growth at six to 7% this year. Many markers continue to point the way to a strong recovery, including hiring trends and the loosening of frozen IT Project budgets. However skills shortages are blocking progress at some companies which bodes well for an increased reliance on external IT services. Moreover, while there's much talk about the rotation out of work from home plays and stocks such as video conferencing, VDI, and other remote worker tech, we see organizations still trying to figure out the ideal balance between funding headquarter investments that have been neglected and getting hybrid work right. In particular, the talent gap combined with a digital mandate, means companies face some tough decisions as to how to fund the future while serving existing customers and transforming culturally. Hello everyone, and welcome to this week's Wikibon CUBE's Insights powered by ETR. In this "Breaking Analysis", we welcome back Erik Porter Bradley of ETR who will share fresh data, perspectives and insights from the latest survey data. Erik, great to see you. Welcome. >> Thank you very much, Dave. Always good to see you and happy to be on the show again. >> Okay, we're going to share some macro data and then we're going to dig into some highlights from ETR's most recent March COVID survey and also the latest April data. So Erik, the first chart that we want to show, it shows CIO and IT buyer responses to expected IT spend for each quarter of 2021 versus 2020, and you can see here a steady quarterly improvement. Erik, what are the key takeaways, from your perspective? >> Sure, well, first of all, for everyone out there, this particular survey had a record-setting number of participation. We had a 1,500 IT decision makers participate and we had over half of the Fortune 500 and over a fifth of the Global 1000. So it was a really good survey. This is seventh iteration of the COVID Impact Survey specifically, and this is going to transition to an overlarge macro survey going forward so we can continue it. And you're 100% right, what we've been tracking here since March of last year was, how is spending being impacted because of COVID? Where is it shifting? And what we're seeing now finally is that there is a real re-acceleration in spend. I know we've been a little bit more cautious than some of the other peers out there that just early on slapped an eight or a 9% number, but what we're seeing is right now, it's at a midpoint of over six, about 6.7% and that is accelerating. So, we are still hopeful that that will continue, and really, that spending is going to be in the second half of the year. As you can see on the left part of this chart that we're looking at, it was about 1.7% versus 3% for Q1 spending year-over-year. So that is starting to accelerate through the back half. >> I think it's prudent to be cautious (indistinct) 'cause normally you'd say, okay, tech is going to grow a couple of points higher than GDP, but it's really so hard to predict this year. Okay, the next chart here that we want to show you is we asked respondents to indicate what strategies they're employing in the short term as a result of coronavirus and you can see a few things that I'll call out and then I'll ask Erik to chime in. First, there's been no meaningful change of course, no surprise in tactics like remote work and holding travel, however, we're seeing very positive trends in other areas trending downward, like hiring freezes and freezing IT deployments, a downward trend in layoffs, and we also see an increase in the acceleration of new IT deployments and in hiring. Erik, what are your key takeaways? >> Well, first of all, I think it's important to point out here that we're also capturing that people believe remote work productivity is still increasing. Now, the trajectory might be coming down a little bit, but that is really key, I think, to the backdrop of what's happening here. So people have a perception that productivity of remote work is better than hybrid work and that's from the IT decision makers themselves, but what we're seeing here is that, most importantly, these organizations are citing plans to increase hiring, and that's something that I think is really important to point out. It's showing a real following, and to your point right in the beginning of the intro, we are seeing deployments stabilize versus prior survey levels, which means early on, they had no plans to launch new tech deployments, then they said, "Nope, we're going to start." and now that stalling, and I think it's exactly right, what you said, is there's an IT skills shortage. So people want to continue to do IT deployments 'cause they have to support work from home and a hybrid back return to the office, but they just don't have the skills to do so, and I think that's really probably the most important takeaway from this chart, is that stalling and to really ask why it's stalling. >> Yeah, so we're going to get into that for sure, and I think that's a really key point, is that accelerating IT deployments, it looks like it's hit a wall in the survey, but before we get deep into the skills, let's take a look at this next chart, and we're asking people here how our return to the new normal, if you will, and back to offices is going to change spending with on-prem architectures and applications. And so the first two bars, they're Cloud-friendly, if you add them up, it's 63% of the respondents, say that either they'll stay in the Cloud for the most part, or they're going to lower their on-prem spend when they go back to the office. The next three bars are on-prem friendly. If you add those up it's 29% of the respondents say their on-prem spend is going to bounce back to pre-COVID levels or actually increase, and of course, 12% of that number, by the way, say they've never altered their on-prem spend. So Erik, no surprise, but this bodes well for Cloud, but isn't it also a positive for on-prem? We've had this dual funding premise, meaning Cloud continues to grow, but neglected data center spend also gets a boost. What's your thoughts? >> Really, it's interesting. It's people are spending on all fronts. You and I were talking in the prep, it's like we're in battle and I've got naval, I've got air, I've got land, I've got to spend on Cloud and digital transformation, but I also have to spend for on-prem. The hybrid work is here and it needs to be supported. So this is spending is going to increase. When you look at this chart, you're going to see though, that roughly 36% of all respondents say that their spending is going to remain mostly on Cloud. So that is still the clear direction, digital transformation is still happening, COVID accelerated it greatly, you and I, as journalists and researchers already know this is where the puck is going, but spend has always lagged a little bit behind 'cause it just takes some time to get there. Inversely, 27% said that their on-prem spending will decrease. So when you look at those two, I still think that the trend is the friend for Cloud spending, even though, yes, they do have to continue spending on hybrid, some of it's been neglected, there are refresh cycles coming up, so, overall it just points to more and more spending right now. It really does seem to be a very strong backdrop for IT growth. >> So I want to talk a little bit about the ETR taxonomy before we bring up the next chart. We get a lot of questions about this, and of course, when you do a massive survey like you're doing, you have to have consistency for time series, so you have to really think through what the buckets look like, if you will. So this next chart takes a look at the ETR taxonomy and it breaks it down into simple-to-understand terms. So the green is the portion of spending on a vendor's tech within a category that is accelerating, and the red is the portion that is decelerating. So Erik, what are the key messages in this data? >> Well, first of all, Dave, thank you so much for pointing that out. We used to do, just what we call a Net score. It's a proprietary formula that we use to determine the overall velocity of spending. Some people found it confusing. Our data scientists decided to break this sector, break down into what you said, which is really more of a mode analysis. In that sector, how many of the vendors are increasing versus decreasing? So again, I just appreciate you bringing that up and allowing us to explain the reasoning behind our analysis there. But what we're seeing here goes back to something you and I did last year when we did our predictions, and that was that IT services and consulting was going to have a true rebound in 2021, and that's what this is showing right here. So in this chart, you're going to see that consulting and services are really continuing their recovery, 2020 had a lot of the clients and they have the biggest sector year-over-year acceleration sector wise. The other thing to point out on this, which we'll get to again later, is that the inverse analysis is true for video conferencing. We will get to that, so I'm going to leave a little bit of ammunition behind for that one, but what we're seeing here is IT consulting services being the real favorable and video conferencing having a little bit more trouble. >> Great, okay, and then let's take a look at that services piece, and this next chart really is a drill down into that space and emphasizes, Erik, what you were just talking about. And we saw this in IBM's earnings, where still more than 60% of IBM's business comes from services and the company beat earnings, in part, due to services outperforming expectations, I think it had a somewhat easier compare and some of this pent-up demand that we've been talking about bodes well for IBM and other services companies, it's not just IBM, right, Erik? >> No, it's not, but again, I'm going to point out that you and I did point out IBM in our predictions when we did in late December, so, it is nice to see. One of the reasons we don't have a more favorable rating on IBM at the moment is because they are in the process of spinning out this large unit, and so there's a little bit of a corporate action there that keeps us off on the sideline. But I would also want to point out here, Tata, Infosys and Cognizant 'cause they're seeing year-over-year acceleration in both IT consulting and outsourced IT services. So we break those down separately and those are the three names that are seeing acceleration in both of those. So again, at the Tata, Infosys and Cognizant are all looking pretty well positioned as well. >> So we've been talking a little bit about this skills shortage, and this is what's, I think, so hard for forecasters, is that in the one hand, There's a lot of pent up demand, Scott Gottlieb said it's like Woodstock coming out of the COVID, but on the other hand, if you have a talent gap, you've got to rely on external services. So there's a learning curve, there's a ramp up, it's an external company, and so it takes time to put those together. So this data that we're going to show you next, is really important in my view and ties what we were saying at the top. It asks respondents to comment on their staffing plans. The light blue is "We're increasing staff", the gray is "No change" and the magenta or whatever, whatever color that is that sort of purplish color, anyway, that color is decreasing, and the picture is very positive across the board. Full-time staff, offshoring, contract employees, outsourced professional services, all up trending upwards, and this Erik is more evidence of the services bounce back. >> Yeah, it's certainly, yes, David, and what happened is when we caught this trend, we decided to go one level deeper and say, all right, we're seeing this, but we need to know why, and that's what we always try to do here. Data will tell you what's happening, it doesn't always tell you why, and that's one of the things that ETR really tries to dig in with through the insights, interviews panels, and also going direct with these more custom survey questions. So in this instance, I think the real takeaway is that 30% of the respondents said that their outsourced and managed services are going to increase over the next three months. That's really powerful, that's a large portion of organizations in a very short time period. So we're capturing that this acceleration is happening right now and it will be happening in real time, and I don't see it slowing down. You and I are speaking about we have to increase Cloud spend, we have to increase hybrid spend, there are refresh cycles coming up, and there's just a real skills shortage. So this is a long-term setup that bodes very well for IT services and consulting. >> You know, Erik, when I came out of college, somebody told me, "Read, read, read, read as much as you can." And then they said, "Read the Wall Street Journal every day." and so I did it, and I would read the tech magazines and back then it was all paper, and what happens is you begin to connect the dots. And so the reason I bring that up is because I've now taken a bath in the ETR data for the better part of two years and I'm beginning to be able to connect the dots. The data is not always predictive, but many, many times it is. And so this next data gets into the fun stuff where we name names. A lot of times people don't like it because they're either marketing people at organizations, say, "Well, data's wrong." because that's the first thing they do, is attack the data. But you and I know, we've made some really great calls, work from home, for sure, you're talking about the services bounce back. We certainly saw the rise of CrowdStrike, Okta, Zscaler, well before people were talking about that, same thing with video conferencing. And so, anyway, this is the fun stuff and it looks at positive versus negative sentiment on companies. So first, how does ETR derive this data and how should we interpret it, and what are some of your takeaways? >> Sure, first of all, how we derive the data, are systematic survey responses that we do on a quarterly basis, and we standardize those responses to allow for time series analysis so we can do trend analysis as well. We do find that our data, because it's talking about forward-looking spending intentions, is really more predictive because we're talking about things that might be happening six months, three months in the future, not things that a lot of other competitors and research peers are looking at things that already happened, they're looking in the past, ETR really likes to look into the future and our surveys are set up to do so. So thank you for that question, It's a enjoyable lead in, but to get to the fun stuff, like you said, what we do here is we put ratings on the datasets. I do want to put the caveat out there that our spending intentions really only captures top-line revenue. It is not indicative of profit margin or any other line items, so this is only to be viewed as what we are rating the data set itself, not the company, that's not what we're in the game of doing. So I think that's very important for the marketing and the vendors out there themselves when they take a look at this. We're just talking about what we can control, which is our data. We're going to talk about a few of the names here on this highlighted vendors list. One, we're going to go back to that you and I spoke about, I guess, about six months ago, or maybe even earlier, which was the observability space. You and I were noticing that it was getting very crowded, a lot of new entrants, there was a lot of acquisition from more of the legacy or standard players in the space, and that is continuing. So I think in a minute, we're going to move into that observability space, but what we're seeing there is that it's becoming incredibly crowded and we're possibly seeing signs of them cannibalizing each other. We're also going to move on a little bit into video conferencing, where we're capturing some spend deceleration, and then ultimately, we're going to get into a little bit of a storage refresh cycle and talk about that. But yeah, these are the highlighted vendors for April, we usually do this once a quarter and they do change based on the data, but they're not usually whipsawed around, the data doesn't move that quickly. >> Yeah, so you can see some of the big names in the left-hand side, some of the SAS companies that have momentum. Obviously, ServiceNow has been doing very, very well. We've talked a lot about Snowflake, Okta, CrowdStrike, Zscaler, all very positive, as well as several others. I guess I'd add some things. I mean, I think if thinking about the next decade, it's Cloud, which is not going to be like the same Cloud as the last decade, a lot of machine learning and deep learning and AI and the Cloud is extending to the edge and the data center. Data, obviously, very important, data is decentralized and distributed, so data architectures are changing. A lot of opportunities to connect across Clouds and actually create abstraction layers, and then something that we've been covering a lot is processor performance is actually accelerating relative to Moore's law. It's probably instead of doubling every two years, it's quadrupling every two years, and so that is a huge factor, especially as it relates to powering AI and AI inferencing at the edge. This is a whole new territory, custom Silicon is really becoming in vogue and so something that we're watching very, very closely. >> Yeah, I completely, agree on that and I do think that the next version of Cloud will be very different. Another thing to point out on that too, is you can't do anything that you're talking about without collecting the data and organizations are extremely serious about that now. It seems it doesn't matter what industry they're in, every company is a data company, and that also bodes well for the storage goal. We do believe that there is going to just be a huge increase in the need for storage, and yes, hopefully that'll become portable across multi-Cloud and hybrid as well. >> Now, as Erik said, the ETR data, it's really focused on that top-line spend. So if you look on the right side of that chart, you saw NetApp was kind of negative, was very negative, right? But it is a company that's in transformation now, they've lowered expectations and they've recently beat expectations, that's why the stock has been doing better, but at the macro, from a spending standpoint, it's still stout challenged. So you have big footprint companies like NetApp and Oracle is another one. Oracle's stock is at an all time high, but the spending relative to sort of previous cycles are relative to, like for instance, Snowflake, much, much smaller, not as high growth, but they're managing expectations, they're managing their transition, they're managing profitability. Zoom is another one, Zoom looking negative, but Zoom's got to use its market cap now to transform and increase its TAM. And then Splunk is another one we're going to talk about. Splunk is in transition, it acquired SignalFX, It just brought on this week, Teresa Carlson, who was the head of AWS Public Sector. She's the president and head of sales, so they've got a go-to-market challenge and they brought in Teresa Carlson to really solve that, but Splunk has been trending downward, we called that several quarters ago, Erik, and so I want to bring up the data on Splunk, and this is Splunk, Erik, in analytics, and it's not trending in the right direction. The green is accelerating spend, the red is in the bars is decelerating spend, the top blue line is spending velocity or Net score, and the yellow line is market share or pervasiveness in the dataset. Your thoughts. >> Yeah, first I want to go back. There's a great point, Dave, about our data versus a disconnect from an equity analysis perspective. I used to be an equity analyst, that is not what we do here. And the main word you said is expectations, right? Stocks will trade on how they do compare to the expectations that are set, whether that's buy-side expectations, sell-side expectations or management's guidance themselves. We have no business in tracking any of that, what we are talking about is the top-line acceleration or deceleration. So, that was a great point to make, and I do think it's an important one for all of our listeners out there. Now, to move to Splunk, yes, I've been capturing a lot of negative commentary on Splunk even before the data turns. So this has been a about a year-long, our analysis and review on this name and I'm dating myself here, but I know you and I are both rock and roll fans, so I'm going to point out a Led Zeppelin song and movie, and say that the song remains the same for Splunk. We are just seeing recent spending attentions are taking yet another step down, both from prior survey levels, from year ago levels. This, we're looking at in the analytics sector and spending intentions are decelerating across every single group, and we went to one of our other slide analysis on the ETR+ platform, and you do by customer sub-sample, in analytics, it's dropping in every single vertical. It doesn't matter which one. it's really not looking good, unfortunately, and you had mentioned this is an analytics and I do believe the next slide is an information security. >> Yeah, let's bring that up. >> And unfortunately it's not doing much better. So this is specifically Fortune 500 accounts and information security. There's deep pockets in the Fortune 500, but from what we're hearing in all the insights and interviews and panels that I personally moderate for ETR, people are upset, that they didn't like the strong tactics that Splunk has used on them in the past, they didn't like the ingestion model pricing, the inflexibility, and when alternatives came along, people are willing to look at the alternatives, and that's what we're seeing in both analytics and big data and also for their SIM and security. >> Yeah, so I think again, I pointed Teresa Carlson. She's got a big job, but she's very capable. She's going to meet with a lot of customers, she's a go-to-market pro, she's going to to have to listen hard, and I think you're going to see some changes there. Okay, so sorry, there's more bad news on Splunk. So (indistinct) bring this up is Net score for Splunk and Elastic accounts. This is for analytics, so there's 106 Elastic accounts in the dataset that also have Splunk and it's trending downward for Splunk, that's why it's green for Elastic. And Erik, the important call out from ETR here is how Splunk's performance in Elastic accounts compares with its performance overall. The ELK stack, which obviously Elastic is a big part of that, is causing pain for Splunk, as is Datadog, and you mentioned the pricing issue, well, is it pricing in your assessment or is it more fundamental? >> It's multi-level based on the commentary we get from our ITDMs teams that take the survey. So yes, you did a great job with this analysis. What we're looking at is the spending within shared accounts. So if I have Splunk already, how am I spending? I'm sorry if I have Elastic already, how am I spending on Splunk? And what you're seeing here is it's down to about a 12% Net score, whereas Splunk overall, has a 32% Net score among all of its customers. So what you're seeing there is there is definitely a drain that's happening where Elastic is draining spend from Splunk and usage from them. The reason we used Elastic here is because all observabilities, the whole sector seems to be decelerating. Splunk is decelerating the most, but Elastic is the only one that's actually showing resiliency, so that's why we decided to choose these two, but you pointed out, yes, it's also Datadog. Datadog is Cloud native. They're more dev ops-oriented. They tend to be viewed as having technological lead as compared to Splunk. So a really good point. Dynatrace also is expanding their abilities and Splunk has been making a lot of acquisitions to push their Cloud services, they are also changing their pricing model, right? They're trying to make things a little bit more flexible, moving off ingestion and moving towards consumption. So they are trying, and the new hires, I'm not going to bet against them because the one thing that Splunk has going for them is their market share in our survey, they're still very well entrenched. So they do have a lot of accounts, they have their foothold. So if they can find a way to make these changes, then they will be able to change themselves, but the one thing I got to say across the whole sector is competition is increasing, and it does appear based on commentary and data that they're starting to cannibalize themselves. It really seems pretty hard to get away from that, and you know there are startups in the observability space too that are going to be even more disruptive. >> I think I want to key on the pricing for a moment, and I've been pretty vocal about this. I think the old SAS pricing model where you essentially lock in for a year or two years or three years, pay up front, or maybe pay quarterly if you're lucky, that's a one-way street and I think it's a flawed model. I like what Snowflake's doing, I like what Datadog's doing, look at what Stripe is doing, look at what Twilio is doing, you mentioned it, it's consumption-based pricing, and if you've got a great product, put it out there and damn, the torpedoes, and I think that is a game changer. I look at, for instance, HPE with GreenLake, I look at Dell with Apex, they're trying to mimic that model and apply it to infrastructure, it's much harder with infrastructure 'cause you've got to deploy physical infrastructure, but that is a model that I think is going to change, and I think all of the traditional SAS pricing is going to come under disruption over the next better part of the decades, but anyway, let's move on. We've been covering the APM space pretty extensively, application performance management, and this chart lines up some of the big players here. Comparing Net score or spending momentum from the April 20th survey, the gray is, sorry, the gray is the April 20th survey, the blue is Jan 21 and the yellow is April 21, and not only are Elastic and Datadog doing well relative to Splunk, Erik, but everything is down from last year. So this space, as you point out, is undergoing a transformation. >> Yeah, the pressures are real and it's sort of that perfect storm where it's not only the data that's telling us that, but also the direct feedback we get from the community. Pretty much all the interviews I do, I've done a few panels specifically on this topic, for anyone who wants to dive a little bit deeper. We've had some experts talk about this space and there really is no denying that there is a deceleration in spend and it's happening because that spend is getting spread out among different vendors. People are using a Datadog for certain aspects, they are using Elastic where they can 'cause it's cheaper. They're using Splunk because they have to, but because it's so expensive, they're cutting some of the things that they're putting into Splunk, which is dangerous, particularly on the security side. If I have to decide what to put in and whatnot, that's not really the right way to have security hygiene. So this space is just getting crowded, there's disruptive vendors coming from the emerging space as well, and what you're seeing here is the only bit of positivity is Elastic on a survey-over-survey basis with a slight, slight uptick. Everywhere else, year-over-year and survey-over-survey, it's showing declines, it's just hard to ignore. >> And then you've got Dynatrace who, based on the interviews you do in the (indistinct), one-on-one, or one-on-five, the private interviews that I've been invited to, Dynatrace gets very high scores for their roadmap. You've got New Relic, which has been struggling financially, but they've got a really good product and a purpose-built database just for this APM space, and then of course, you've got Cisco with AppD, which is a strong business for them, and then as you mentioned, you've got startups coming in, you got ChaosSearch, which Ed Walsh is now running, leave the data in place in AWS and really interesting model, Honeycomb is getting really disruptive, Jeremy Burton's company, Observed. So this space is it's becoming jumped ball. >> Yeah, there's a great line that came out of one of them, and that was that the lines are blurring. It used to be that you knew exactly that AppDynamics, what they were doing, it was APM only, or it was logging and monitoring only, and a lot of what I'm hearing from the ITDM experts is that the lines are blurring amongst all of these names. They all have functionality that kind of crosses over each other. And the other interesting thing is it used to be application versus infrastructure monitoring, but as you know, infrastructure is becoming code more and more and more, and as infrastructure becomes code, there's really no difference between application and infrastructure monitoring. So we're seeing a convergence and a blurring of the lines in this space, which really doesn't bode well, and a great point about New Relic, their tech gets good remarks. I just don't know if their enterprise level service and sales is up to snuff right now. As one of my experts said, a CTO of a very large public online hospitality company essentially said that he would be shocked that within 18 months if all of these players are still standalone, that there needs to be some M and A or convergence in this space. >> Okay, now we're going to call out some of the data that really has jumped out to ETR in the latest survey, and some of the names that are getting the most queries from ETR clients, many of which are investor clients. So let's start by having a look at one of the most important and prominent work from home names, Zoom. Let's look at this. Erik is the ride over for Zoom? >> Ah, I've been saying it for a little bit of a time now actually. I do believe it is, and we'll get into it, but again, pointing out, great, Dave, the reason we're presenting today Splunk, Elastic and Zoom, they are the most viewed on the ETR+ platform. Trailing behind that only slightly is F5, I decided not to bring F5 to the table today 'cause we don't have a rating on the data set. So then I went one deep, one below that and it's pure. So the reason we're presenting these to you today is that these are the ones that our clients and our community are most interested in, which is hopefully going to gain interest to your viewers as well. So to get to Zoom, yeah, I call Zoom the pandemic bull market baby. This was really just one that had a meteoric ride. You look back, January in 2020, the stock was at $60 and 10 months later, it was like 580, that's in 10 months. That's cooled down a little bit into the mid-300s, and I believe that cooling down should continue, and the reason why is because we are seeing huge deceleration in our spending intentions. They're hitting all-time lows, it's really just a very ugly dataset. More importantly than the spending intentions, for the first time, we're seeing customer growth in our survey flatten. In the past, we knew that the deceleration of spend was happening, but meanwhile, their new customer growth was accelerating, so it was kind of hard to really make any call based on that. This is the first time we're seeing flattening customer growth trajectory, and that in tandem with just dominance from Microsoft in every sector they're involved in, I don't care if it's IP telephony, productivity apps or the core video conferencing, Microsoft is just dominating. So there's really just no way to ignore this anymore. The data and the commentary state that Zoom is facing some headwinds. >> Well, plus you've pointed out to me that a lot of your private conversations with buyers says that, "Hey, we're, we're using the freebie version of Zoom, and we're not paying them." And that combined with Teams, I mean, it's... I think, look, Zoom, they've got to figure out how to use their elevated market cap to transform and expand their TAM, but let's move on. Here's the data on Pure Storage and we've highlighted a number of times this company is showing elevated spending intentions. Pure announced it's earnings in May, IBM just announced storage, it was way down actually. So still, Pure, more positive, but I'll on that comment in a moment, but what does this data tell you, Erik? >> Yeah, right now we started seeing this data last survey in January, and that was the first time we really went positive on the data set itself, and it's just really continuing. So we're seeing the strongest year-over-year acceleration in the entire survey, which is a really good spot to be. Pure is also a leading position among its sector peers, and the other thing that was pretty interesting from the data set is among all storage players, Pure has the highest positive public Cloud correlation. So what we can do is we can see which respondents are accelerating their public Cloud spend and then cross-reference that with their storage spend and Pure is best positioned. So as you and I both know, digital transformation Cloud spending is increasing, you need to be aligned with that. And among all storage sector peers, Pure is best positioned in all of those, in spending intentions and adoptions and also public Cloud correlation. So yet again, to start another really strong dataset, and I have an anecdote about why this might be happening, because when I saw the data, I started asking in my interviews, what's going on here? And there was one particular person, he was a director of Cloud operations for a very large public tech company. Now, they have hybrid, but their data center is in colo, So they don't own and build their own physical building. He pointed out that during COVID, his company wanted to increase storage, but he couldn't get into his colo center due to COVID restrictions. They weren't allowed. You had 250,000 square feet, right, but you're only allowed to have six people in there. So it's pretty hard to get to your rack and get work done. He said he would buy storage, but then the colo would say, "Hey, you got to get it out of here. It's not even allowed to sit here. We don't want it in our facility." So he has all this pent up demand. In tandem with pent up demand, we have a refresh cycle. The SSD depreciation cycle is ending. SSDs are moving on and we're starting to see a new technology in that space, NVMe sorry, technology increasing in that space. So we have pent up demand and we have new technology and that's really leading to a refresh cycle, and this particular ITDM that I spoke to and many of his peers think this has a long tailwind that storage could be a good sector for some time to come. >> That's really interesting, thank you for that extra metadata. And I want to do a little deeper dive on storage. So here's a look at storage in the industry in context and some of the competitive. I mean, it's been a tough market for the reasons that we've highlighted, Cloud has been eating away that flash headroom. It used to be you'd buy storage to get more spindles and more performance and we're sort of forced to buy more, flash, gave more headroom, but it's interesting what you're saying about the depreciation cycle. So that's good news. So ETR combines, just for people's benefit here, combines primary and secondary storage into a single category. So you have companies like Pure and NetApp, which are really pure play primary storage companies, largely in the sector, along with Veeam, Cohesity and Rubrik, which are kind of secondary data or data protection. So my quick thoughts here that Pure is elevated and remains what I call the one-eyed man in the land of the blind, but that's positive tailwinds there, so that's good news. Rubrik is very elevated but down, it's big competitor, Cohesity is way off its highs, and I have to say to me, Veeam is like the Steady Eddy consistent player here. They just really continue to do well in the data protection business, and the highs are steady, the lows are steady. Dell is also notable, they've been struggling in storage. Their ISG business, which comprises servers and storage, it's been softer in COVID, and during even this new product rollout, so it's notable with this new mid range they have in particular, the uptick in Dell, this survey, because Dell is so large, a small uptick can be very good for Dell. HPE has a big announcement next month in storage, so that might improve based on a product cycle. Of course, the Nimble brand continues to do well, IBM, as I said, just announced a very soft quarter, down double digits again, and they're in a product cycle shift. And NetApp, it looks bad in the ETR data from a spending momentum standpoint, but their management team is transforming the company into a Cloud play, which Erik is why it was interesting that Pure has the greatest momentum in Cloud accounts, so that is sort of striking to me. I would have thought it would be NetApp, so that's something that we want to pay attention to, but I do like a lot of what NetApp is doing, and other than Pure, they're the only big kind of pure play in primary storage. So long-winded, intro there, Erik, but anything you'd add? >> No, actually I appreciate it as long-winded. I'm going to be honest with you, storage is not my best sector as far as a researcher and analyst goes, but I actually think that a lot of what you said is spot on. We do capture a lot of large organizations spend, we don't capture much mid and small, so I think when you're talking about these large, large players like NetApp not looking so good, all I would state is that we are capturing really big organization spending attention, so these are names that should be doing better to be quite honest, in those accounts, and at least according to our data, we're not seeing it in. It's longterm depression, as you can see, NetApp now has a negative spending velocity in this analysis. So, I can go dig around a little bit more, but right now the names that I'm hearing are Pure, Cohesity. I'm hearing a little bit about Hitachi trying to reinvent themselves in the space, but I'll take a wait-and-see approach on that one, but pure Cohesity are the ones I'm hearing a lot from our community. >> So storage is transforming to Cloud as a service. You've seen things like Apex in GreenLake from Dell and HPE and container storage. A little, so not really a lot of people paying attention to it, but Pure bought a company called Portworx which really specializes in container storage, and there's many startups there, they're trying to really change the way. David Flynn, has a startup in that space, he's the guy who started Fusion-io. So a lot of transformations happening here. Okay, I know it's been a long segment, we have to summarize, and let me go through a summary and then I'll give you the last word, Erik. So tech spending appears to be tracking US GDP at 6 to 7%. This talent shortage could be a blocker to accelerating IT deployments, so that's kind of good news actually for services companies. Digital transformation, it remains a priority, and that bodes, well, not only for services, but automation. UiPath went public this week, we profiled that extensively, that went public last Wednesday. Organizations that sit at the top face some tough decisions on how to allocate resources. They're running the business, growing the business, transforming the business, and we're seeing a bifurcation of spending and some residual effects on vendors, and that remains a theme that we're watching. Erik, your final thoughts. >> Yeah, I'm going to go back quickly to just the overall macro spending, 'cause there's one thing I think is interesting to point out and we're seeing a real acceleration among mid and small. So it seems like early on in the COVID recovery or COVID spending, it was the deep pockets that moved first, right? Fortune 500 knew they had to support remote work, they started spending first. Around that in the Fortune 500, we're only seeing about 5% spend, but when you get into mid and small organizations, that's creeping up to eight, nine. So I just think it's important to point out that they're playing catch up right now. I also would point out that this is heavily skewed to North America spending. We're seeing laggards in EMEA, they just don't seem to be spending as much. They're in a very different place in their recovery, and I do think that it's important to point that out. Lastly, I also want to mention, I know you do such a great job on following a lot of the disruptive vendors that you just pointed out, with Pure doing container storage, we also have another bi-annual survey that we do called Emerging Technology, and that's for the private names. That's going to be launching in May, for everyone out there who's interested in not only the disruptive vendors, but also private equity players. Keep an eye out for that. We do that twice a year and that's growing in its respondents as well. And then lastly, one comment, because you mentioned the UiPath IPO, it was really hard for us to sit on the sidelines and not put some sort of rating on their dataset, but ultimately, the data was muted, unfortunately, and when you're seeing this kind of hype into an IPO like we saw with Snowflake, the data was resoundingly strong. We had no choice, but to listen to what the data said for Snowflake, despite the hype. We didn't see that for UiPath and we wanted to, and I'm not making a large call there, but I do think it's interesting to juxtapose the two, that when snowflake was heading to its IPO, the data was resoundingly positive, and for UiPath, we just didn't see that. >> Thank you for that, and Erik, thanks for coming on today. It's really a pleasure to have you, and so really appreciate the collaboration and look forward to doing more of these. >> Yeah, we enjoy the partnership greatly, Dave. We're very happy to have you on the ETR family and looking forward to doing a lot, lot more with you in the future. >> Ditto. Okay, that's it for today. Remember, these episodes are all available as podcasts wherever you listen. All you have to do is search "Breaking Analysis" podcast, and please subscribe to the series. Check out ETR website it's etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can email me, david.vellante@siliconangle.com, you can DM me on Twitter @dvellante or comment on our LinkedIn posts. I could see you in Clubhouse. This is Dave Vellante for Erik Porter Bradley for the CUBE Insights powered by ETR. Have a great week, stay safe, be well and we'll see you next time. (bright music)

>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS Reinvent Executive Summit 2020. Sponsored by Accenture and AWS. >> Welcome everyone to theCUBE virtual coverage of the Accenture Executive Summit part of AWS Re-invent 2020. I'm your host, Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First, we have Johan Krebbers. He is the GM Digital Emerging Technologies and VP of IT Innovation at Shell. Thank you so much for coming on the show, Johan. >> You're welcome. >> Rebecca: And next we have Liz Dennett. She is the Lead Solution Architect for OSDU on AWS. Thank you so much Liz. >> Happy to be here. >> So I want to start our conversation by talking about OSDU. Like so many great innovations, it started with a problem. Johann, what was the problem you were trying to solve at Shell? >> Yeah, let's go back a couple of the years. We started summer 2017, where we had a meeting with the guys from exploration in Shell. And the main problem they had of course they got lots and lots of data, but aren't unable to find the right data they need to work from. Well the data was scattered and is scattered, it was scattered it's all over the place. And so the real problem trying to solve is how that person working in exploration could find their proper data, not just the data also the data really needed. That's what we probably talked about in summer 2017. And we said, "Okay, the only way we see this moving forward is to start pulling that data into a single data platform." And that was at the time that we called it OSDU, the Open Subsurface Data Universe, and that was what the Shell name was. So, in January 2018, we start a project with Amazon to start creating and confronting the building that OSDU environment, that subservient the universe. So that single data platform to put all your exploration and wealth data into a single environment that was the intent. And then we said, already in March of that same year, we said, 'Well, from a Shell point of view, we would be far better off if we could make this an industry solution and not just a Shell solution." Because Shell will be, if you can make this an industry solution, but people start developing applications for it also, it's far better than for Shell to say, we have it Shell special solution. Because we don't make money out of how we store the data we can make money out of we have access to the data, we can exploit the data. So storing the data, we should do as efficiently possibly can. So in March we reached out to about eight or nine other large oil and gas operators, like the ECONOS, like the Totals, like the Chevrons of this world they said, "Hey, we in Shell are doing this, do you want to join this effort?" And to our surprise, they all said yes. And then in September 2018 we had our kick-off meeting with the open group, where we said, "Okay, if you want to work together with lots of other companies, we also need to look a bit at how we organize that." Because if you start working with lots of large companies you need to have some legal framework around it. So that's why, we went to the open group and said," Okay, let's form the OSDU forum." As we call it at the time. So in September, 2018 where I had a Galleria in Houston we had a kick off meeting for the OSDU forum with about 10 members at the time. So there's, just over two years ago, we started to exercise formally we called it OSDU, we kicked it off. And so that's really where we coming from and how we got there also. >> The origin story. >> Yes. >> What, so what, digging a little deeper there, what were some of the things you were trying to achieve with the OSDU? >> Well, a couple of things we've tried to achieve with OSDU. First is really separating data from applications. But what is the biggest problem we have in the subsurface space that the data and applications are all interlinked. They are all tied together and if you have then a new company coming along and say, "I have this new application, and needs access to the data." That is not possible because the data often interlinked with the application. The first thing we did is, really breaking the link between the application and the data. So that was the first thing we did. Secondly, put all the data to a single data platform, take the silos out because what was happening in the subsurface space I mean, they got all the data in what we call silos, in small little islands out there. So we try to do is, first, break the link. Two, create, put the data in a single data platform. And then third part, put a standard layer on top of that the same API layer on top of the created platform so we could create an ecosystem out of companies to start developing software applications on top of that data platform. Because you might have a data platform, but you aren't successful if you have a rich ecosystem of people start developing applications on top of that. And then you can exploit the data like small companies, large companies, universities, you name it. But you have to create an ecosystem out of there. So the three things was, first break the link between the application data, just break it and put data at the center. And also make sure that data, this data structure would not be managed by one company. But it would be managed the data structures, by the OSDU forum. Secondly then, put the data, single data platform. Thirdly then, have an API layer on top and then create an ecosystem, really go for people, say, "Please start developing applications." Because now you have access to the data, because the data is no longer linked to somebody's application was all freely available for an API layer. That was all September, 2018, more or less. >> Liz I want to bring you, in here a little bit. >> Yeah. >> Can you talk a little bit some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? >> Yeah, absolutely. And this whole thing is Johan said, started with a challenge that was really brought out at Shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out, how we could address that one problem, we worked together to really understand the root cause of these challenges. And working backwards from that use case, OSDU and OSDU on AWS has really enabled customers to create solutions that span not just this in particular problem. But can really scale to be inclusive of the entire energy value chain and deliver value from these used cases to the energy industry and beyond. >> Thank you. Johan, so talk a little bit about Accenture's Cloud First approach and how it has helped Shell work faster and better with speed. >> Well, of course Accenture Cloud First approach, really works together with Amazon environment, AWS environment. So we really look at Accenture and Amazon together, helping Shell in this space. Now the combination of the two is what we're really looking at where access of course can bring business knowledge to that environment, operate support knowledge to an environment and of course Amazon will be bring that to this environment, that underpinning services, et cetera. So we would expect of that combination, a lot of goods when we started rolling out in production, the other two or three environment. And probably our aim is, when a release fee comes to the market, in Q1 next year of OSDU have already started going out in production inside Shell. But as the first OSDU release which is ready for prime time production across an enterprise. Well we have released our one just before Christmas, last year, released two in May of this year. But release three is the first release we want to use for full scale production and deployment inside Shell and also all the operators around the world. And there is what Amazon, sorry and there when Accenture can play a role in the ongoing, in the deployment building up, but also support environment. >> So one of the other things that we talk a lot about here on theCUBE is sustainability and this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSDU, help organizations become how is this a greener solution for companies? >> Well, first we make, it's a great solution because you start making a much more efficient use of your resources, which is a really important one. The second thing we're doing is also we started with OSDU in very much in the oil and gas space, within the export development space. We've grown OSDU but in our strategy, we've grown OSDU now also to an alternative energy source. So obviously we'll all start supporting next year things like solar farms, wind farms, the geothermal environment, hydrogen. So it becomes an open energy data platform not just for the oil and gas industry, but for any type of industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources together into a single data platform. You're going to use AI and other technology on top of that, to exploit the data to be together into a single data platform. >> Liz, I want to ask you about security, because security is such a big concern when it comes to data. How secure is the data on OSDU? >> Actually, can I talk, can I do a follow-up on the sustainability talking? >> Absolutely by all means. >> I mean, I want to interject, though security is absolutely our top priority I don't mean to move away from that but with sustainability, in addition to the benefits of the OSDU data platform. When a company moves from on-prem to the cloud they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical on-prem data center. Now, a recent study by 451 research found that, AWS's infrastructure, is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to a higher server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases 451 found that, AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSDU are working to support our customers as they seek to better understand their workflows and make their legacy businesses less carbon intensive. >> That's, those statistics are incredible. Do you want to talk a little bit now about security? >> Absolutely yeah. Security will always be AWS's top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy the security requirements for the military, global banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's had hit service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features. As well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. >> Johann, I want you to talk a little bit about how OSDU you can be used today. Does it only handle subsurface data? >> Today is 100 subsets of wells data we go to add that to that production around the middle of next year. That means that the whole upstream business we got included every piece goes from exploration all the way to production, you bring it together into a single data platform. So production will be added around Q3 of next year. Then in principle, we have a typical elder data, a single environment and we're going to extend them to other data sources or energy sources like solar farms, wind farms, hydrogen, hydro, et cetera. So we're going to add a whole list of other day energy source to that and bring all the data together into a single data platform. So we move from an oil and gas data platform to an energy data platform. That's really what our objective is because the whole industry if you look at our companies all moving in that same direction of course are very strong in oil and gas but also increasingly go into other energy sources like solar, like wind, like hydrogen et cetera. So we move exactly with the same method, that the whole OSDU, can really support that whole energy spectrum of energy sources, of course. >> And Liz and Johan, I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSDU. We'll start with you, Liz. What do you see as the future holding for this platform? >> Honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers wherever their OSDU journeys, take them whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges. >> Johan. >> Yeah, first nobody can look that far ahead anymore nowadays, especially 10 years. I mean, who knows what happens in 10 years? But if you look what our objective is that really in the next five years, OSDU will become the key backbone for energy companies for storing your data, new artificial intelligence and optimize the whole supply, the energy supply chain in this world out here. >> Johan Krebbers, Liz Dennett thank you so much for coming on theCUBE virtual. >> Thank you. >> Thank you. >> I'm Rebecca Knight stay tuned for more of our coverage of the Accenture Executive Summit. (tranquil music).

(upbeat music) >> Narrator: From around the globe, it's theCUBE with digital coverage of AWS Public Sector Online brought to you by Amazon Web Services. >> Welcome back to theCUBE's coverage of AWS Public Sector Summit Online. I'm John Furrier, your host of theCUBE. I wish we could be there in person, but we're doing remote because of the COVID and the pandemic. We've got a great guest, Paul Grist. Worldwide Public Sector, Head of Education International for AWS. Paul, thank you for coming on remotely. >> Great to be here, John. >> There's a lot of disruption in the education space this year with universities and schools still uncertain about what the future will look like. What are some of the biggest trends you're seeing? >> John, what we've seen is the rapid adoption of technology and the growth of flexible online learning, learning that can take place anytime, anywhere. What we've seen is universities, national education systems, and schools rapidly migrating systems and content to the cloud, spinning up new applications. And we've seen companies that provide technology and content and platforms, the ed techs and publishers of the world, increasing their capacity, increasing their capability to deliver new applications to education. >> What is some of this research that you're finding out there? >> Yeah. You know, a time of much change and things happening very, very fast. We responded fast to the changes, John. Got a load of customer conversations together, looking at speeches by educationalists who were responding to the changes at some of the online events that spun up very quickly at places like the University of Buckingham, ASU, JSV, Inside Higher Education, places like Blackboard World. And really just talked to those leaders about their responses to the change, what kinds of things they were doing, and brought that together into the research. It's underpinned by some in-depth research and insights from education reports and articles too. >> Thanks Paul, really appreciate it. Having that research is critical. I know you guys do a lot of work on that. I know you got some news, take a quick plug for the new research that's coming out. You guys just put out today, just take a minute to quickly explain what it's about and how to find it. >> We're publishing today some new research that shows the seven key emerging trends in this new world of education. Check it out on the AWS website. Two key trends, flexible learning and the new world of employability. >> So you guys got a lot of data. It's great with Amazon, got a lot of customers. Good to see you guys getting that research. The question I have for you Paul is, what amount of the research shows really the COVID situation? Because there's before COVID, there's kind of during, and then there's going to be a post-COVID mode. Was that prior research in place with COVID or after COVID? Can you share kind of the update on the relevance of your research? >> Yeah, I think the sector has changed. The sector has gone through the fastest change it's ever gone through. And undoubtedly most of the issues, most of the challenges and opportunities in the sector, predate the pandemic. But what we've seen is COVID accelerate many of the challenges and the opportunities, but also bring new opportunities. >> Yeah, one of the things we've seen with education is the disruption, and the forcing function with COVID. There's a problem, we all know what it is. It's important, there's consequences for those. And you can quantify the disruption with real business value and certainly student impact. There's been downsides with remote education. More teacher-parent involvement and students having to deal with isolation, less social interaction. How do you guys see that? Or what is Amazon doing to solve these problems? Can you talk about that? >> Yeah. I think you know, education is very much a people business. And what we've been trying to do is partner with organizations to ensure that the people are kept at the center of the business. So working with organizations such as LS, sorry, Los Angeles United School District in the US to spin up a call center to allow students to contact their tutors. And parents to interact with tutors, to get questions answered. >> So one of the challenges these academic institutions are facing is speed, it's pace of change. What's going on with competition? How are they competing? How are universities and colleges staying relevant? Obviously there's a financial crisis involved. There's also the actual delivery aspect of it. More and more mergers. You're starting to see ecosystem changes. Can you talk about what's going on in the educational ecosystem? >> Yeah I mean, educational institutions are being forced to rethink their business models. It's an international marketplace in higher education. It's been a growing marketplace for many, many years. That suddenly stopped overnight, so every university has had to rethink about where their revenues are coming from, where the students are coming from. There's been some surprises too. I mean in the UK, actually international enrollments are up post-COVID because one of the strange side effects of COVID is without being able to travel, there's actually a cost saving for students. And so we've seen universities in the UK benefit from students who want to study, perhaps travel and the cost of study was too high previously. Now being able to study remotely. It's an unexpected and unintended consequence. But it kind of shows how there are opportunities for all organizations during this time. >> Many countries had to cancel exams altogether this year, which has been a big, huge problem. I mean people are outraged and people want to learn. It's been, you know, the silver lining in all this is that you have the internet (laughs). You have the cloud. I want to get your thoughts. How are universities and schools dealing with this challenge? Because you have a multi-sided marketplace. You've got the institutions, you've got the students, you got the educators, they all have to be successful. How are universities dealing with this challenge? >> Yeah I think, you know, teaching and learning has been online for 20, 30 years. And I think a lot of organizations have adopted online teaching and learning. But I think assessment is the one big area of education that remains to be made available at scale at low cost. So most assessment is still a pen-and-paper-based. There's big trust and identity issues. And what we're seeing through this COVID change is organizations really getting to grip with both of those issues. So, having the confidence to put assessment online, to make it available at scale, and then also having the confidence to tackle trust and identity questions. So who is taking the exam, where are they sitting? Can we be sure that it's actually that person taking that exam? So you know, the rise of things like proctoring technologies giving organizations the opportunity to assess remotely. >> How has this crisis affected research at academic institutions? Because certainly we know that if you need a lab or something, certainly we're seeing students need to be physically in person. But with remote and all those changes going on with the scale and the pace of change, how has research at academic institutions been impacted? >> Yeah I mean, research has always been a really collaborative activity, but we've seen that collaboration increase. It's had to increase. Researchers have had to go remote. Many of them work in labs. They haven't been able to do that. They've needed to spin up applications and new technologies in the cloud to continue working. But what we're seeing is governments taking an increased interest in the research being applicable, making sure that it leads to innovation which is meaningful. Getting much more involved and insisting that the research is made available now. And of course there's no place that that's clearer than in health research and trying to find a cure for COVID. And then secondly, we're seeing that research is becoming much more collaborative not just across institutions but also countries. So one of the great projects we're involved in at the moment is with the University of Adelaide who are collaborating with researchers from the Breeding and Acclimatization Institute in Poland on a project to study the increase in crop yield of wheat. >> One of the things that's coming out of this, whether it's research or students is open online courses, virtual capabilities. But a concept called stackable learning. Can you explain what that is? >> Yeah. We're in a global marketplace in education and there's increased competition between universities and education providers to make new types of certificates and online badges available. We know that employers are looking for ever more agile methods of scaling and upskilling. And stackable learning is a concept that's been around for a couple of decades now, where learning is broken down into smaller chunks, put together in a more personalized way from a number of different providers. Spun up very, very quickly to respond to need and then delivered to students. We're seeing some of the big providers like edX and Coursera who, again have been around for over a decade become really prominent in the provision of some of these stackable credentials. Their systems run on the cloud. They're easy to access, in many, many cases they're free. We're seeing an increasing number of employers and education institutions adopt and embed these types of delivery systems into their curriculum. >> Totally a fan of stackable learning, it's called the Lego model, whatever I call it. But also online brings the nonlinear progressions. The role of data is super important. So I'm very bullish on education being disrupted by cloud providers and new apps. So you know, I wanted to call that out because I think it's super important. Let me get to a really important piece that it has to be addressed, and I want to get your thoughts on. Cyber security. Okay, cyber attacks and privacy of students are two areas that are super important for institutions to address. What's your reaction to that? >> Yeah, I mean the use of more technology becomes, you know again, a target for cyber attack and unfortunately it's an increasing phenomenon. Simply put, every organization needs to put security first. Needs to operate as a security-first organization. They need to adopt technologies, people and processes that can protect their investments. And work with data management vendors, cloud vendors who've got the compliances and the common privacy and security frameworks such as GDPR in place to make sure that they provide secure services. AWS's security offerings include auditing, login and identity management, data encryption capabilities that offer more transparency and control, to allow institutions protect student data. >> Super important, thanks for sharing. Finally, what's the steps institutions can take to close the digital divide because now some people are taking gap years. Research is changing. People might not even have PCs or internet connections. There's still, this exposes the haves and have nots. What steps can institutions take to do their part? >> Yeah, digital learning is here to stay, John. We've learned that many learners do not have access to technology necessary for online learning. Whether those are devices or a reliable internet connection. But again, you know governments, states, educational authorities have all turned their attention to these issues over the last few months. And we're seeing organizations partner with technology providers that can provide internet connections. Partners in AWS, such as Kajeet who've installed hotspot devices on buses to deploy in areas with no connectivity. You know whether that's a place like Denver, Colorado or whether it's a place, you know, in Nigeria in Africa, remote connection remains a problem everywhere. And we're seeing everybody addressing that issue now. >> Paul, great to have you on theCUBE and sharing your insights on what's going on in international education. Final question for you. In your own words, why is this year at the AWS Public Sector Summit Online important? What's the most important story that people should walk away in this educational industry? >> The most important story, John, is it's a time of incredible change but also incredible opportunity. And we're seeing organizations who have wanted to change, who've wanted to deliver more to their students, who want to deliver a greater experience, who want to access more students and have much greater reach. Now with the appetite to do that. re:Invent is a great opportunity to work with AWS, to understand what's going on with our partners, with our customers. And look at some of the common solutions for the challenges that they're looking to solve. >> Paul Grist, thank you for coming on theCUBE. Really appreciate it. Worldwide Head of Education for International AWS. Thank you for sharing. >> Thanks John, great to be here. >> Okay, this is theCUBE's coverage of AWS Public Sector Online Summit. Remote, virtual, this is theCUBE virtual. I'm John Furrier, your host. Thanks for watching. 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>> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the CloudNative Computing Foundation, and Ecosystem Partners. >> Hi and welcome back to theCUBE's coverage of KubeCon, CloudNativeCon 2020 in Europe, of course the virtual edition. I'm Stu Miniman and happy to welcome back to the program one of the keynote speakers, he's also a board member of the CNCF, Vijoy Pandey who is the vice president and chief technology officer for Cloud at Cisco. Vijoy, nice to see you and thanks so much for joining us. >> Thank you Stu, and nice to see you again. It's a strange setting to be in but as long as we are both health, everything is good. >> Yeah, it's still a, we still get to be together a little bit even though while we're apart, we love the engagement and interaction that we normally get through the community but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Network, Please Evolve", been watching that journey. But why don't we start it first, you know, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so that, yeah let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports into Chuck. The role, the charter for this team, this new team, is to incubate the next bets for Cisco. And, if you can imagine, it's natural for Cisco to start with bets which are closer to its core business, but the charter for this group is to mover further and further out from Cisco's core business and takes this core into newer markets, into newer products, and newer businesses. I am running the engineering and research for that group. And, again, the whole deal behind this is to be a little bit nimble, to be a little startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast and you throw out 80% of those and concentrate on the 20% that make sense to take forward as a venture. >> Interesting. So it reminds me a little bit, but different, I remember John Chambers a number of years back talking about various adjacencies, trying to grow those next, you know, multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for, you know, driving innovation, giving engineering 20% of their time to work on things. Give us a little bit of insight. What's kind of an example of a bet that you might be looking at in the space? Bring us inside a little bit. >> Well that's actually a good question and I think a little bit of that comparison is, are those conversations that taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets. And, yes, my previous employer, I mean Google X actually goes pretty far out when it comes to incubations. The core business being primarily around ads, now Google Cloud as well, but you have things like Verily and Calico and others which are pretty far out from where Google started. And the way we are looking at these things within Cisco is, it's a new muscle for Cisco so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to go-to-market alignment or business alignment. So while the first bets that we are taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure's code, but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I talked a lot about this in the past couple of keynotes where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, whatever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets that we are going after is around connecting and securing API endpoints wherever they happen to be of whatever type they happen to be. And so API networking, or app networking, is one big bet that we're going after. Our other big bet is around API security and that has a bunch of other connotations to it where we think about security moving from runtime security where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security which is only under the developer pipeline and higher up in the stack. So those are two big bets that we're going after and as you can see, they're pretty close to Cisco's core business but also very differentiated from where Cisco is today. And once when you prove some of these bets out, you can walk further and further away or a few degrees away from Cisco's core as it exists today. >> All right, well Vijoy, I mentioned you're also on the board for the CNCF, maybe let's talk a little bit about open source. How does that play into what you're looking at for emerging technologies and these bets, you know, so many companies, that's an integral piece, and we've watched, you know really, the maturation of Cisco's journey, participating in these open source environments. So help us tie in where Cisco is when it comes to open source. >> So, yeah, so I think we've been pretty deeply involved in open source in our past. We've been deeply involved in Linux foundational networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack. We are big supporters of OpenStack. We have a couple of products that are on the OpenStack offering. And as you all know, we've been involved in CNCF right from the get go as a foundational member. We brought NSM as a project. It's sandbox currently. We're hoping to move it forward. But even beyond that, I mean we are big users of open source. You know a lot of us has offerings that we have from Cisco and you would not know this if you're not inside of Cisco, but Webex, for example, is a big, big user of linger D right from the get go from version 1.0. But we don't talk about it, which is sad. I think for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise site. We use Kubernetes very deeply in our security platforms. So we are pretty deep users internally in all our SAS products. But we want to press the accelerator and accelerate this whole journey towards open source quite a bit moving forward as part of ET&I, Emerging Tech and Incubation as well. So you will see more of us in open source forums, not just the NCF but very recently we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative and we actually are big believers in handling data in ethical and privacy preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health and we will be working very closely with Dan and the foundational companies there to, not just bring open source, but also evangelize and use what comes out of that forum. >> All right. Well, Vijoy, I think it's time for us to dig into your keynote. We've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on, and big focus you talked about was SD-WAN. Of course anybody that been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling Multicloud, so help us, you know, help explain to our audience a little bit, you know, what do you mean when you talk about things like CloudNative, SD-WAN, and how that helps people really enable their applications in the modern environment? >> Yeah, so, well we we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actual data connectivity across to your enterprise or branch and SD-WAN came in and changed the game there. But I think SD-WAN as it exists today is application-alaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM, or network service mesh, has actually helped us simplify operational complexities, simplify the ticketing and process hell that any developer needs to go through just to get a multicloud, multicluster app up and running. So the keynote actually talked about bringing those two things together where we've talked about using NSM in the past, in chapter one and chapter two, ah chapter two, no this is chapter three and at some point I would like to stop the chapters. I don't want this to be like, like an encyclopedia of networking (mumbling) But we are at chapter three and we are talking about how you can take the same consumption models that I talked about in chapter two which is just adding a simple annotation in your CRD and extending that notion of multicloud, multicluster wires within the components of our application but extending it all the way down to the user in an enterprise. And as you saw an example, Gavin Russom is trying to give a keynote holographically and he's suffering from SD-WAN being application alaware. And using this construct of a simple annotation, we can actually make SD-WAN CloudNative. We can make it application-aware, and we can guarantee the SLOs that Gavin is looking for in terms of 3D video, in terms of file access or audio just to make sure that he's successful and Ross doesn't come in and take his place. >> Well I expect Gavin will do something to mess things up on his own even if the technology works flawly. You know, Vijoy the modernization journey that customers are on is a neverending story. I understand the chapters need to end on the current volume that you're working on. But, you know, we'd love to get your view point. You talk about things like service mesh. It's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the the kind of real challenges but opportunities that they see in today's CloudNative space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree and we are seeing a lot of that happening where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've got linger D, you've got various proprietary notions around control planes like App Mesh from Amazon. There's Console which is an open source project But not part of (mumbles) today. So there's a whole bunch of service meshes in terms of control planes coming in on volumes becoming a de facto side car data plane, whatever you would like to call it, de facto standard there which is good for the community I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment. And that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for. Like API Gate was in the past. And those functions are actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of some service meshes is here to stay. And so some work has to be done in bringing these things together and that's something that we are trying to focus in on all as well because that's something that our customers are asking for. >> Yeah, actually you connected for me something I wanted to get your viewpoint on. Dial back you know 10, 15 years ago and everybody would say, "Ah, you know, I really want to have single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, you know, not that long before this event, Google had their Google Cloud show talking about the partnership that you have with Cisco with Google. They have Anthos. You look at Azure has Arc. You know, VMware has Tanzu. Everybody's talking about, really, kind of this multicluster management type of solution out there. And just want to get your viewpoint on this Vijoy is to, you know, how are we doing on the management plane and what do you think we need to do as a industry as a whole to make things better for customers? >> Yeah, but I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all of these things together. And I think the SMI apropos from Microsoft is bang on on that front where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes. As you saw in the SD-WAN and also going back in the Google discussion that you just, or Google conference that we just offered It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a CloudNative environment in the keynote. But I think the bigger problem here is how do we manage this complexity of disparate stacks, whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And, single pane of glass is over loaded as a term because it brings in these notions of big, monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, you know, the API economy should be able to help on these, you know, multi, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco and congratulations on the new role. >> Thank you Stu. It was a pleasure to be here. >> All right, and stay tuned for much more coverage of theCUBE at KubeCon, CloudNativeCon. I'm Stu Miniman and thanks for watching. (light digital music)

(upbeat music) >> From around the globe, it's theCUBE with coverage of KubeCon and CloudNativeCon Europe 2020 Virtual brought to you by Red Hat, the Cloud Native Computing Foundation, and the ecosystem partners. >> Hi, and welcome back to theCUBE's coverage of KubeCon + CloudNativeCon 2020 in Europe, of course, the virtual edition. I'm Stu Miniman, and happy to welcome you back to the program. One of the keynote speakers is also a board member of the CNCF, Vijoy Pandey, who is the Vice President and Chief Technology Officer for Cloud at Cisco. Vijoy, nice to see you, thanks so much for joining us. >> Hi there, Stu, so nice to see you again. It's a strange setting to be in, but as long as we are both healthy, everything's good. >> Yeah, we still get to be together a little bit even though while we're apart. We love the the engagement and interaction that we normally get to the community, but we just have to do it a little bit differently this year. So we're going to get to your keynote. We've had you on the program to talk about "Networking, Please Evolve". I've been watching that journey. But why don't we start at first, you've had a little bit of change in roles and responsibility. I know there's been some restructuring at Cisco since the last time we got together. So give us the update on your role. >> Yeah, so let's start there. So I've taken on a new responsibility. It's VP of Engineering and Research for a new group that's been formed at Cisco. It's called Emerging Tech and Incubation. Liz Centoni leads that and she reports on to Chuck. The charter for the team, this new team, is to incubate the next bets for Cisco. And if you can imagine, it's natural for Cisco to start with bets which are closer to its core business. But the charter for this group is to move further and further out from Cisco's core business and take Cisco into newer markets, into newer products, and newer businesses. I'm running the engineering and resource for that group. And again, the whole deal behind this is to be a little bit nimble, to be a little bit, to startupy in nature, where you bring ideas, you incubate them, you iterate pretty fast, and you throw out 80% of those, and concentrate on the 20% that makes sense to take forward as a venture. >> Interesting. So it reminds me a little bit but different, I remember John Chambers, a number of years back, talking about various adjacencies trying to grow those next multi-billion dollar businesses inside Cisco. In some ways, Vijoy, it reminds me a little bit of your previous company, very well known for driving innovation, giving engineers 20% of their time to work on things, maybe give us a little bit insight, what's kind of an example of a bet that you might be looking at in this space, bring us in tight a little bit. >> Well, that's actually a good question. And I think a little bit of that comparison is all those conversations are taking place within Cisco as well as to how far out from Cisco's core business do we want to get when we're incubating these bets? And yes, my previous employer, I mean, Google X actually goes pretty far out when it comes to incubations, the core business being primarily around ads, now Google Cloud as well. But you have things like Verily and Calico, and others, which are pretty far out from where Google started. And the way we're looking at the these things within Cisco is, it's a new muscle for Cisco, so we want to prove ourselves first. So the first few bets that we are betting upon are pretty close to Cisco's core but still not fitting into Cisco's BU when it comes to, go to market alignment or business alignment. So one of the first bets that we're taking into account is around API being the queen when it comes to the future of infrastructure, so to speak. So it's not just making our infrastructure consumable as infrastructure as code but also talking about developer relevance, talking about how developers are actually influencing infrastructure deployments. So if you think about the problem statement in that sense, then networking needs to evolve. And I've talked a lot about this in the past couple of keynotes, where Cisco's core business has been around connecting and securing physical endpoints, physical I/O endpoints, wherever they happen to be, of whatever type they happen to be. And one of the bets that we are, actually two of the bets, that we're going after is around connecting and securing API endpoints, wherever they happen to be, of whatever type they happen to be. And so API networking or app networking is one big bet that we're going after. Another big bet is around API security. And that has a bunch of other connotations to it, where we think about security moving from runtime security, where traditionally Cisco has played in that space, especially on the infrastructure side, but moving into API security, which is earlier in the development pipeline, and higher up in the stack. So those are two big bets that we're going after. And as you can see, they're pretty close to Cisco's core business, but also are very differentiated from where Cisco is today. And once you prove some of these bets out, you can walk further and further away, or a few degrees away from Cisco's core. >> All right, Vijoy, why don't you give us the update about how Cisco is leveraging and participating in open source? >> So I think we've been pretty, deeply involved in open source in our past. We've been deeply involved in Linux Foundation Networking. We've actually chartered FD.io as a project there and we still are. We've been involved in OpenStack, we have been supporters of OpenStack. We have a couple of products that are around the OpenStack offering. And as you all know, we've been involved in CNCF, right from the get-go, as a foundation member. We brought NSM as a project. I had Sandbox currently, but we're hoping to move it forward. But even beyond that, I mean, we are big users of open source, a lot of those has offerings that we have from Cisco, and you will not know this if you're not inside of Cisco. But Webex, for example, is a big, big user of Linkerd, right from the get-go, from version 1.0, but we don't talk about it, which is sad. I think, for example, we use Kubernetes pretty deeply in our DNAC platform on the enterprise side. We use Kubernetes very deeply in our security platforms. So we're pretty good, pretty deep users internally in our SaaS products. But we want to press the accelerator and accelerate this whole journey towards open source, quite a bit moving forward as part of ET&I, Emerging Tech and Incubation, as well. So you will see more of us in open source forums, not just CNCF, but very recently, we joined the Linux Foundation for Public Health as a premier foundational member. Dan Kohn, our old friend, is actually chartering that initiative, and we actually are big believers in handling data in ethical and privacy-preserving ways. So that's actually something that enticed us to join Linux Foundation for Public Health, and we will be working very closely with Dan and foundational companies that do not just bring open source but also evangelize and use what comes out of that forum. >> All right, well, Vijoy, I think it's time for us to dig into your keynote. We've we've spoken with you in previous KubeCons about the "Network, Please Evolve" theme that you've been driving on. And big focus you talked about was SD-WAN. Of course, anybody that's been watching the industry has watched the real ascension of SD-WAN. We've called it one of those just critical foundational pieces of companies enabling multi-cloud. So help explain to our audience a little bit, what do you mean when you talk about things like Cloud Native SD-WAN and how that helps people really enable their applications in the modern environment? >> Yes, well, I mean, we've been talking about SD-WAN for a while. I mean, it's one of the transformational technologies of our time where prior to SD-WAN existing, you had to stitch all of these MPLS labels and actually get your connectivity across to your enterprise or branch. And SD-WAN came in and changed the game there, but I think SD-WAN, as it exists today, is application-unaware. And that's one of the big things that I talk about in my keynote. Also, we've talked about how NSM, the other side of the spectrum, is how NSM or Network Service Mesh has actually helped us simplify operational complexities, simplify the ticketing and process health that any developer needs to go through just to get a multi-cloud, multi-cluster app up and running. So the keynote actually talked about bringing those two things together, where we've talked about using NSM in the past in chapter one and chapter two. And I know this is chapter three, and at some point, I would like to stop the chapters. I don't want this like an encyclopedia of "Networking, Please Evolve". But we are at chapter three, and we are talking about how you can take the same consumption models that I talked about in chapter two, which is just adding a simple annotation in your CRD, and extending that notion of multi-cloud, multi-cluster wires within the components of our application, but extending it all the way down to the user in an enterprise. And as we saw an example, Gavin Belson is trying to give a keynote holographically and he's suffering from SD-WAN being application-unaware. And using this construct of a simple annotation, we can actually make SD-WAN cloud native, we can make it application-aware, and we can guarantee the SLOs, that Gavin is looking for, in terms of 3D video, in terms of file access for audio, just to make sure that he's successful and Ross doesn't come in and take his place. >> Well, I expect Gavin will do something to mess things up on his own even if the technology works flawlessly. Vijoy, the modernization journey that customers are on is a never-ending story. I understand the chapters need to end on the current volume that you're working on, but we'd love to get your viewpoint. You talk about things like service mesh, it's definitely been a hot topic of conversation for the last couple of years. What are you hearing from your customers? What are some of the kind of real challenges but opportunities that they see in today's cloud native space? >> In general, service meshes are here to stay. In fact, they're here to proliferate to some degree, and we are seeing a lot of that happening, where not only are we seeing different service meshes coming into the picture through various open source mechanisms. You've got Istio there, you've Linkerd, you've got various proprietary notions around control planes like App Mesh, from Amazon, there's Consul, which is an open source project, but not part of CNCF today. So there's a whole bunch of service meshes in terms of control planes coming in. Envoy is becoming a de facto sidecar data plane, whatever you would like to call it, de facto standard there, which is good for the community, I would say. But this proliferation of control planes is actually a problem. And I see customers actually deploying a multitude of service meshes in their environment, and that's here to stay. In fact, we are seeing a whole bunch of things that we would use different tools for, like API gateways in the past, and those functions actually rolling into service meshes. And so I think service meshes are here to stay. I think the diversity of service meshes is here to stay. And so some work has to be done in bringing these things together. And that's something that we are trying to focus in on as well. Because that's something that our customers are asking for. >> Yeah, actually, you connected for me something I wanted to get your viewpoint on, go dial back, 10, 15 years ago, and everybody would say, "Oh, I really want to have a single pane of glass "to be able to manage everything." Cisco's partnering with all of the major cloud providers. I saw, not that long before this event, Google had their Google Cloud Show, talking about the partnership that you have with, Cisco with Google. They have Anthos, you look at Azure has Arc, VMware has Tanzu. Everybody's talking about really the kind of this multi-cluster management type of solution out there, and just want to get your viewpoint on this Vijoy as to how are we doing on the management plane, and what do you think we need to do as an industry as a whole to make things better for customers? >> Yeah, I think this is where I think we need to be careful as an industry, as a community and make things simpler for our customers. Because, like I said, the proliferation of all of these control planes begs the question, do we need to build something else to bring all these things together? I think the SMI proposal from Microsoft is bang on on that front, where you're trying to unify at least the consumption model around how you consume these service meshes. But it's not just a question of service meshes as you saw in the SD-WAN announcement back in the Google discussion that we just, Google conference that you just referred. It's also how SD-WANs are going to interoperate with the services that exist within these cloud silos to some degree. And how does that happen? And there was a teaser there that you saw earlier in the keynote where we are taking those constructs that we talked about in the Google conference and bringing it all the way to a cloud native environment in the keynote. But I think the bigger problem here is how do we manage this complexity of this pallet stacks? Whether it's service meshes, whether it's development stacks, or whether it's SD-WAN deployments, how do we manage that complexity? And single pane of glass is overloaded as a term, because it brings in these notions of big monolithic panes of glass. And I think that's not the way we should be solving it. We should be solving it towards using API simplicity and API interoperability. And I think that's where we as a community need to go. >> Absolutely. Well, Vijoy, as you said, the API economy should be able to help on these, the service architecture should allow things to be more flexible and give me the visibility I need without trying to have to build something that's completely monolithic. Vijoy, thanks so much for joining. Looking forward to hearing more about the big bets coming out of Cisco, and congratulations on the new role. >> Thank you, Stu. It was a pleasure to be here. >> All right, and stay tuned for lots more coverage of theCUBE at KubeCon + CloudNativeCon. I'm Stu Miniman. Thanks for watching. (upbeat music)

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> As you may recall, coming into the second part of 2019 we reported, based on ETR Survey data, that there was a narrowing of spending on emerging tech and an unplugging of a lot of legacy systems. This was really because people were going from experimentation into operationalizing their digital initiatives. When COVID hit, conventional wisdom suggested that there would be a flight to safety. Now, interestingly, we reported with Eric Bradley, based on one of the Venns, that a lot of CIOs were still experimenting with emerging vendors. But this was very anecdotal. Today, we have more data, fresh data, from the ETR Emerging Technology Study on private companies, which really does suggest that there's a notable decline in experimentation, and that's affecting emerging technology vendors. Hi, everybody, this is Dave Vellante, and welcome to this week's Wikibon Cube Insights, powered by ETR. Once again, Sagar Kadakia is joining us. Sagar is the Director of Research at ETR. Sagar, good to see you. Thanks for coming on. >> Good to see you again. Thanks for having me, Dave. >> So, it's really important to point out, this Emerging Tech Study that you guys do, it's different from your quarterly Technology Spending Intention Survey. Take us through the methodology. Guys, maybe you could bring up the first chart. And, Sagar, walk us through how you guys approach this. >> No problem. So, a lot of the viewers are used to seeing a lot of the results from the Technology Spending Intention Survey, or the TSIS, as we call it. That study, as the title says, it really tracks spending intentions on more pervasive vendors, right, Microsoft, AWS, as an example. What we're going to look at today is our Emerging Technology Study, which we conduct biannually, in May and November. This study is a little bit different. We ask CIOs around evaluations, awareness, planned evaluations, so think of this as pre-spend, right. So that's a major differentiator from the TSIS. That, and this study, really focuses on private emerging providers. We're really only focused on those really emerging private companies, say, like your Series B to Series G or H, whatever it may be, so, two big differences within those studies. And then today what we're really going to look at is the results from the Emerging Technology Study. Just a couple of quick things here. We had 811 CIOs participate, which represents about 380 billion in annual IT spend, so the results from this study matter. We had almost 75 Fortune 100s take it. So, again, we're really measuring how private emerging providers are doing in the largest organizations. And so today we're going to be reviewing notable sectors, but largely this survey tracks roughly 356 private technologies and frameworks. >> All right, guys, bring up the pie chart, the next slide. Now, Sagar, this is sort of a snapshot here, and it basically says that 44% of CIOs agree that COVID has decreased the organization's evaluation and utilization of emerging tech, despite what I mentioned, Eric Bradley's Venn, which suggested one CIO in particular said, "Hey, I always pick somebody in the lower left "of the magic quadrant." But, again, this is a static view. I know we have some other data, but take us through this, and how this compares to other surveys that you've done. >> No problem. So let's start with the high level takeaways. And I'll actually kind of get into to the point that Eric was debating, 'cause that point is true. It's just really how you kind of slice and dice the data to get to that. So, what you're looking at here, and what the overall takeaway from the Emerging Technology Study was, is, you know, you are going to see notable declines in POCs, of proof-of-concepts, any valuations because of COVID-19. Even though we had been communicating for quite some time, you know, the last few months, that there's increasing pressure for companies to further digitize with COVID-19, there are IT budget constraints. There is a huge pivot in IT resources towards supporting remote employees, a decrease in risk tolerance, and so that's why what you're seeing here is a rather notable number of CIOs, 44%, that said that they are decreasing their organization's evaluation and utilization of private emerging providers. So that is notable. >> Now, as you pointed out, you guys run this survey a couple of times a year. So now let's look at the time series. Guys, if you bring up the next chart. We can see how the sentiment has changed since last year. And, of course, we're isolating here on some of larger companies. So, take us through what this data means. >> No problem. So, how do we quantify what we just saw in the prior slide? We saw 44% of CIOs indicating that they are going to be decreasing their evaluations. But what exactly does that mean? We can pretty much determine that by looking at a lot of the data that we captured through our Emerging Technology Study. There's a lot going on in this slide, but I'll walk you through it. What you're looking at here is Fortune 1000 organizations, so we've really isolated the data to those organizations that matter. So, let's start with the teal, kind of green line first, because I think it's a little bit easier to understand. What you're looking at, Fortune 1000 evaluations, both planned and current, okay? And you're looking at a time series, one year ago and six months ago. So, two of the answer options that we provide CIOs in this survey, right, think about the survey as a grid, where you have seven answer options going horizontally, and then 300-plus vendors and technologies going vertically. For any given vendor, they can essentially indicate one of these options, two of them being on currently evaluating them or I plan to evaluate them in six months. So what you're looking at here is effectively the aggregate number, or the average number of Fortune 1000 evaluations. So if you look into May 2019, all the way on the left of that chart, that 24% roughly means that a quarter of selections made by Fortune 1000 of the survey, they selected plan to evaluate or currently evaluating. If you fast-forward six months, to the middle of the chart, November '19, it's roughly the same, one in four technologies that are Fortune 1000 selected, they indicated that I plan or am currently evaluating them. But now look at that big drop off going into May 2020, the 17%, right? So now one out of every six technologies, or one out of every selections that they made was an evaluation. So a very notable drop. And then if you look at the blue line, this is another answer option that we provided CIOs: I'm aware of the technology but I have no plans to evaluate. So this answer option essentially tracks awareness levels. If you look at the last six months, look at that big uptick from 44% to over 50%, right? So now, essentially one out of every two technologies, or private technologies that a CIO is aware of, they have no plans to evaluate. So this is going to have an impact on the general landscape, when we think about those private emerging providers. But there is one caveat, and, Dave, this is what you mentioned earlier, this is what Eric was talking about. The providers that are doing well are the ones that are work-from-home aligned. And so, just like a few years ago, we were really analyzing results based on are you cloud-native or are you Cloud-aligned, because those technologies are going to do the best, what we're seeing in the emerging space is now the same thing. Those emerging providers that enable organizations to maintain productivity for their employees, essentially allowing their employees to work remotely, those emerging providers are still doing well. And that is probably the second biggest takeaway from this study. >> So now what we're seeing here is this flight to perceive safety, which, to your point, Sagar, doesn't necessarily mean good news for all enterprise tech vendors, but certainly for those that are positioned for the work-from-home pivot. So now let's take a look at a couple of sectors. We'll start with information security. We've reported for years about how the perimeter's been broken down, and that more spend was going to shift from inside the moat to a distributed network, and that's clearly what's happened as a result of COVID. Guys, if you bring up the next chart. Sagar, you take us through this. >> No problem. And as you imagine, I think that the big theme here is zero trust. So, a couple of things here. And let me just explain this chart a little bit, because we're going to be going through a couple of these. What you're seeing on the X-axis here, is this is effectively what we're classifying as near term growth opportunity from all customers. The way we measure that effectively is we look at all the evaluations, current evaluations, planned evaluations, we look at people who are evaluated and plan to utilize these vendors. The more indications you get on that the more to the top right you're going to be. The more indications you get around I'm aware of but I don't plan to evaluate, or I'm replacing this early-stage vendor, the further down and on the left you're going to be. So, on the X-axis you have near term growth opportunity from all customers, and on the Y-axis you have near term growth opportunity from, really, the biggest shops in the world, your Global 2000, your Forbes Private 225, like Cargill, as an example, and then, of course, your federal agencies. So you really want to be positioned up and to the right here. So, the big takeaway here is zero trust. So, just a couple of things on this slide when we think about zero trust. As organizations accelerate their Cloud and Saas spend because of COVID-19, and, you know, what we were talking about earlier, Dave, remote work becomes the new normal, that perimeter security approach is losing appeal, because the perimeter's less defined, right? Apps and data are increasingly being stored in the Cloud. That, and employees are working remotely from everywhere, and they're accessing all of these items. And so what we're seeing now is a big move into zero trust. So, if we look at that chart again, what you're going to see in that upper right quadrant are a lot of identity and access management players. And look at the bifurcation in general. This is what we were talking about earlier in terms of the landscape not doing well. Most security vendors are in that red area, you know, in the middle to the bottom. But if you look at the top right, what are you seeing here? Unify ID, Auth0, WSO2, right, all identity and access management players. These are critical in your zero trust approach, and this is one of the few area where we are seeing upticks. You also see here BitSight, Lucideus. So that's going to be security assessment. You're seeing VECTRA and Netskope and Darktrace, and a few others here. And Cloud Security and IDPS, Intrusion Detection and Prevention System. So, very few sectors are seeing an uptick, very few security sectors actually look pretty good, based on opportunities that are coming. But, essentially, all of them are in that work-from-home aligned security stack, so to speak. >> Right, and of course, as we know, as we've been reporting, buyers have options, from both established companies and these emerging companies that are public, Okta, CrowdStrike, Zscaler. We've seen the work-from-home pivot benefit those guys, but even Palo Alto Networks, even CISCO, I asked (other speaker drowns out speech) last week, I said, "Hey, what about this pivot to work from home? "What about this zero trust?" And he said, "Look, the reality is, yes, "a big part of our portfolio is exposed "to that traditional infrastructure, "but we have options for zero trust as well." So, from a buyer's standpoint, that perceived flight to safety, you have a lot of established vendors, and that clearly is showing up in your data. Now, the other sector that we want to talk about is database. We've been reporting a lot on database, data warehouse. So, why don't you take us through the next graphic here, if you would. >> Sagar: No problem. So, our theme here is that Snowflake is really separating itself from the pack, and, again, you can see that here. Private database and data warehousing vendors really continue to impact a lot of their public peers, and Snowflake is leading the way. We expect Snowflake to gain momentum in the next few years. And, look, there's some rumors that IPOing soon. And so when we think about that set-up, we like it, because as organizations transition away from hybrid Cloud architectures to 100% or near-100% public Cloud, Snowflake is really going to benefit. So they look good, their data stacks look pretty good, right, that's resiliency, redundancy across data centers. So we kind of like them as well. Redis Labs bring a DB and they look pretty good here on the opportunity side, but we are seeing a little bit of churn, so I think probably Snowflake and DataStax are probably our two favorites here. And again, when you think about Snowflake, we continue to think more pervasive vendors, like Paradata and Cloudera, and some of the other larger database firms, they're going to continue seeing wallet and market share losses due to some of these emerging providers. >> Yeah. If you could just keep that slide up for a second, I would point out, in many ways Snowflake is kind of a safer bet, you know, we talk about flight to safety, because they're well-funded, they're established. You can go from zero to Snowflake very quickly, that's sort of their mantra, if you will. But I want to point out and recognize that it is somewhat oranges and tangerines here, Snowflake being an analytical database. You take MariaDB, for instance, I look at that, anyway, as relational and operational. And then you mentioned DataStax. I would say Couchbase, Redis Labs, Aerospike. Cockroach is really a... EValue Store. You've got some non-relational databases in there. But we're looking at the entire sector of databases, which has become a really interesting market. But again, some of those established players are going to do very well, and I would put Snowflake on that cusp. As you pointed out, Bloomberg broke the story, I think last week, that they were contemplating an IPO, which we've known for a while. >> Yeah. And just one last thing on that. We do like some of the more pervasive players, right. Obviously, AWS, all their products, Redshift and DynamoDB. Microsoft looks really good. It's just really some of the other legacy ones, like the Teradatas, the Oracles, the Hadoops, right, that we are going to be impacted. And so the claw providers look really good. >> So, the last decade has really brought forth this whole notion of DevOps, infrastructure as code, the whole API economy. And that's the piece we want to jump into now. And there are some real stand-outs here, you know, despite the early data that we showed you, where CIOs are less prone to look at emerging vendors. There are some, for instance, if you bring up the next chart, guys, like Hashi, that really are standing out, aren't they? >> That's right, Dave. So, again, what you're seeing here is you're seeing that bifurcation that we were talking about earlier. There are a lot of infrastructure software vendors that are not positioned well, but if you look at the ones at the top right that are positioned well... We have two kind of things on here, starting with infrastructure automation. We think a winner here is emerging with Terraform. Look all the way up to the right, how well-positioned they are, how many opportunities they're getting. And for the second straight survey now, Terraform is leading along their peers, Chef, Puppet, SaltStack. And they're leading their peers in so many different categories, notably on allocating more spend, which is obviously very important. For Chef, Puppet and SaltStack, which you can see a little bit below, probably a little bit higher than the middle, we are seeing some elevator churn levels. And so, really, Terraform looks like they're kind of separating themselves. And we've got this great quote from the CIO just a few months ago, on why Terraform is likely pulling away, and I'll read it out here quickly. "The Terraform tool creates "an entire infrastructure in a box. "Unlike vendors that use procedural languages, "like Ants, Bull and Chef, "it will show you the infrastructure "in the way you want it to be. "You don't have to worry about "the things that happen underneath." I know some companies where you can put your entire Amazon infrastructure through Terraform. If Amazon disappears, if your availability drops, load balancers, RDS, everything, you just run Terraform and everything will be created in 10 to 15 minutes. So that shows you the power of Terraform and why we think it's ranked better than some of the other vendors. >> Yeah, I think that really does sum it up. And, actually, guys, if you don't mind bringing that chart back up again. So, a point out, so, Mitchell Hashimoto, Hashi, really, I believe I'm correct, talking to Stu about this a little bit, he sort of led the Terraform project, which is an Open Source project, and, to your point, very easy to deploy. Chef, Puppet, Salt, they were largely disrupted by Cloud, because they're designed to automate deployment largely on-prem and DevOps, and now Terraform sort of packages everything up into a platform. So, Hashi actually makes money, and you'll see it on this slide, and things, Vault, which is kind of their security play. You see GitLab on here. That's really application tooling to deploy code. You see Docker containers, you know, Docker, really all about open source, and they've had great adoption, Docker's challenge has always been monetization. You see Turbonomic on here, which is application resource management. You can't go too deep on these things, but it's pretty deep within this sector. But we are comparing different types of companies, but just to give you a sense as to where the momentum is. All right, let's wrap here. So maybe some final thoughts, Sagar, on the Emerging Technology Study, and then what we can expect in the coming month here, on the update in the Technology Spending Intention Study, please. >> Yeah, no problem. One last thing on the zero trust side that has been a big issue that we didn't get to cover, is VPN spend. Our data is pointing that, yes, even though VPN spend did increase the last few months because of remote work, we actually think that people are going to move away from that as they move onto zero trust. So just one last point on that, just in terms of overall thoughts, you know, again, as we cover it, you can see how bifurcated all these spaces are. Really, if we were to go sector by sector by sector, right, storage and block chain and MLAI and all that stuff, you would see there's a few or maybe one or two vendors doing well, and the majority of vendors are not seeing as many opportunities. And so, again, are you work-from-home aligned? Are you the best vendor of all the other emerging providers? And if you fit those two criteria then you will continue seeing POCs and evaluations. And if you don't fit that criteria, unfortunately, you're going to see less opportunities. So think that's really the big takeaway on that. And then, just in terms of next steps, we're already transitioning now to our next Technology Spending Intention Survey. That launched last week. And so, again, we're going to start getting a feel for how CIOs are spending in 2H-20, right, so, for the back half of the year. And our question changes a little bit. We ask them, "How do you plan on spending in the back half year "versus how you actually spent "in the first half of the year, or 1H-20?" So, we're kind of, tighten the screw, so to speak, and really getting an idea of what's spend going to look like in the back half, and we're also going to get some updates as it relates to budget impacts from COVID-19, as well as how vendor-relationships have changed, as well as business impacts, like layoffs and furloughs, and all that stuff. So we have a tremendous amount of data that's going to be coming in the next few weeks, and it should really prepare us for what to see over the summer and into the fall. >> Yeah, very excited, Sagar, to see that. I just wanted to double down on what you said about changes in networking. We've reported with you guys on NPLS networks, shifting to SD-WAN. But even VPN and SD-WAN are being called into question as the internet becomes the new private network. And so lots of changes there. And again, very excited to see updated data, return of post-COVID, as we exit this isolation economy. Really want to point out to folks that this is not a snapshot survey, right? This is an ongoing exercise that ETR runs, and grateful for our partnership with you guys. Check out ETR.plus, that's the ETR website. I publish weekly on Wikibon.com and SiliconANGLE.com. Sagar, thanks so much for coming on. Once again, great to have you. >> Thank you so much, for having me, Dave. I really appreciate it, as always. >> And thank you for watching this episode of theCube Insights, powered by ETR. This Dave Vellante. We'll see you next time. (gentle music)