(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

(light upbeat music) >> Hey, everyone, welcome back to theCUBE's day two live coverage of VMware Explore 2022 from Moscone Center in San Francisco. Lisa Martin here as your host with Dave Nicholson. We've got a couple of guests here and we have some props on set. Get a load of this Nature Fresh Farms produce. Keith Bradley joins us, the VP of IT from Nature Fresh Farms, and Alison Biers is back, as well, director of marketing at Edge Solutions for Dell. Guys, welcome back to the program and thanks for bringin' some food. >> Well, thank you, yeah. >> Thank you so much. >> So, Keith, talk to us a little bit about technology from Nature Fresh Farm's perspective. How do we look at this farming organization as a tech company? >> As technical, we're something that measures everything we grow. So, we're 200 acres of greenhouse, spanning probably about 3 or 400 acres of land. Everything's entirely environmentally controlled. So, the peppers that we have in front of you, the tomatoes, they're all grown and controlled from everything they get from light to moisture to irrigation and nutrients. So, we do all that. >> So, should I be able to taste the Dell goodness in these cucumbers, for example? >> I'd like to say Nature Fresh slash Dell good. >> Connect the dots for us. So, let's go through that sort of mental exercise of how are these end products for consumers better because of what you're doing in IT? >> So, one of the things that we've been able to do, and one of the transformations we made is we are now able to run our ETLs. So, analyze the data realtime at the Edge. So, making decisions which used to be only once a day based on analytics to now multiple times a day. Our ETLs used to take 8 to 10 hours to run. Now they run- >> So, extraction, transformation and load. >> Yep, yep. >> Okay. So, we consider it a party foul if you use a TLA and you don't find it the first time. >> Okay. >> But you get a pass 'cause you're an actual and real person. >> I'll give you that one. >> I already had a claim laid on that. I'm sorry, so continue. >> Yeah, yeah. So, it allowed now the growers to make multiple decisions and then you start adding the next layer. As we expanded our technology base, we started introducing AI into it. So now, AI is even starting to make decisions before the grower even knows to make them based on historical data. So, it's allowed us to become more proactive in protecting the health and longevity and even taste of that plant and the product coming out to you. >> That's awesome. Alison, talk to us about from Dell's perspective how is it helping Nature Fresh to simplify the Edge which there's a lot of complexity there? You talked about the size of the organization but how do you help simplify it? >> I think Nature Fresh had a lot of common problems that we see customers have. So, they had some really interesting ambitions to improve their produce and do it in a GMO free way and really bring a quality product to their customer. But yet, they were each solving their problems on their individual farms in different ways. And so, one of the ways that we were able to help was to consolidate a lot of those silos as they were expanding the scope and scale of what they really wanted to do from a technology perspective. And then being able to do that in a secure way that's delivering the insights they need when they need them right there at the Edge is really critical. >> I think it's wonderful that we have the actual stuff here. Because we often talk in these abstract terms about outcomes. There's your outcome right there. >> Yeah. >> Right. >> But talk about this growing in the soil somewhere. You have growers. It's not an abstraction. These are actual actual people. Where does the technology organism interface occur here? You have organically grown crops. Where's that interface? Where's the first technology involved in this process? Literally physically. >> Physically. >> Yeah, yeah, yeah. Is there a shack with a server in it somewhere? >> So, we actually have, we have a core data center at the center of Nature Fresh set up basically where everything ends up. We have our Edge. So, we have computers, we're at the Edge analyzing stuff. But if you want to go right back to the grassroots of where it actually is, is it's right at, not dirt, but a ground up coconut husk. That is what the plants are grown in. And we analyze the data right there, 'cause that is our first Edge. And people think that's static for us. The Edge isn't static. 'Cause the Edge now moves. We have a plant that grows. Then we pick it. And then we have to store it and then we have to ship it. So, our Edge actually does move from area to area to area. So, statically one thing isn't the same all the time. It's a hard thing to say how it all starts but it's just a combination of everything from natural gas to everything. >> Okay, then are those, 'cause we think of things in terms of like internet of things and these sensors. >> Oh yeah. >> Things are being gathered. So, you've got stuff happily growing in husks and then being picked. What's the next step there? Where is that aggregated? Where does that go? Is that all going straight back to your data center or are there sort of intermediate steps in the process? >> So, what we do is we actually store everything at the Edge, and we do daily processes right there. And then it aggregates that data and it drops it down from a large number to a smaller number to go to the core. >> Got it. >> And then that way, at the core, it does the long term analysis. 'Cause again, a lot of the data that we collect, we don't need to keep. A lot of it is the temperature was X, the temperature was X, the temperature, we don't need that. So, it aggregates it all down. So, that way the information coming to the core doesn't overwhelm it. Because we do store enough information. And to give you an idea of how our 1.8 million plants are living and breathing. We actually have estimated 1.8 million plants throughout our 200 acres. >> At any moment. >> Yeah. >> That's how many plants they're tracking. And so, that realtime information is helping to make sure that they water the plants precisely with the amount that they need, that they're fertilizing them. And you were telling me about how the life of a plant, you're really maintaining that plant over the life of 12 months. So, if you make a mistake at any point along the line, then you're dealing with that in terms of their yield throughout the life of the plant. But you aggregate a lot of that data right there on site so that you're not having to send so much back to the cloud or to the core. And you do that a lot with VxRail as well as other technology you have on site. Right? >> Yeah. Our VxRail is the center of the core of how we process things. It allowed us to even expand, not even just for compute but GPUs for our AIs to do it. So, it's what we did. And it allowed us to mold how we do things. >> Alison, question for you, this sounds like a dynamic Edge the way that you described it, Keith, and you described it so eloquently. How does the partnership that Dell has with Nature Fresh, how is Dell enabling and accelerating and advancing its Edge solutions based on what you're seeing here and this need for realtime data analytics. >> Well, we spend a lot of time with customers like Keith and also across all kinds of other industries. And what we see is that they have a really common set of problems. They're all trying to derive realtime data right then and there so that they can make business decisions that impact their profitability and their competitiveness and all of their customers experience their product quality. And what we see a lot of times is that they have a common set of concerns around security. How to manage all of the hardware that they're implementing. And at the same time, they really want to be an enabler for the business outcome. So, people have creative ideas and they come to IT hoping for support in that journey. If you're managing everything as a snowflake, it becomes really hard and untenable. So, I think one of the things that we have as our mission is to help customers simplify their Edge so that they can be the enabler that's helping the business to transform and modernize. One of the things I really admire about Nature Fresh Farms is that they decided it from a full organization perspective. So, everybody from the operational technologists to the IT to the business decision makers and leaders at the company, they all decided to modernize together. And so, I think from a partnership perspective, too, that's one of the areas that we try to work with our customers on is really talking about total transformation and modernization. >> So, it sounds like, Keith, there was an appetite there as Alison was saying for a digital transformation and IT transformation. Talk to me a little bit about from a historical perspective, how old Nature Fresh is and how did you get the team on board sounds so eloquent. How did you get the team on board to go, "This is what we need to do and technology needs to fuel our business because it's going to impact the end user, consumer of our fabulous English cucumbers." >> So, it's actually really neat. Our owner, Pete Quiring, when he first started out he really wanted to embrace technology. And this is going back right to 2000. 2000 is when we first had our first planting. And he was actually a builder by nature. He actually was a builder and fabricator and he built greenhouses for other companies. But he said they're getting a little bigger and it's the labor amount, and the number of growers he needed for a range was getting exponentially higher. So, he was one of the first ones that said, "I'm going to put a computer right in the middle and control this 16 acre range." >> It's a pretty visionary view when you really think about it. He's trying to operate his farm. >> Yeah. >> Right? >> From one single computer. >> Operationalize it. It's really cool. >> So, it was neat concept and it was actually very much not a normal concept then. You go back to 2000, people weren't talking about internet of things. They didn't talk about automation. It wasn't there. And he basically said, this is the way to go. And unfortunately, he thought, "I'll sell it to somebody. I'll grow it, I'll put a product in for a year and I'll sell it." And then guess what happened? He didn't sell it. He says, "Ah, it's not big enough. I'll build another phase two." And then his comment to me was after he built the fourth phase, he says, "I guess I'm in the pepper and cucumber business now." And that's what he is just grown. But he said it was a great relationship we had and it's a great concept. And it even goes back, and I know we talked about before, is the computer allowed one senior grower to control large number of acreages. Where before, you'd need multiple growers that know exactly what to do, 'cause they'd have to manually change all these things. Now, from a single computer they can see everything that's going on in the entire range. >> You mentioned temperature and water. And this is kind of out of the blue question, but how have global circumstances and increases in the cost of fertilizer affected you? Or is that fertilizer that's not the type that you use in your operation? You have any insight into that. >> Yeah, everything has, the global change in cost has changed everybody. I don't think there's anybody that's exempt from it. The only thing that we've been able to do is we're able to control it. We don't need to rely on, I guess you can say, rely on the weather to help us do things. We can control how much is. And we recycle all of our water. So, what the plant doesn't absorb today for nutrients, we'll put it back in the system, sterilize- >> Wait, when you say 200 acres, it's all enclosed? >> Yep, 200 acres. >> 200 acres of greenhouse. >> Yep, at 200 acres of greenhouse entirely enclosed. >> Okay, okay. >> There is not a single portion of our greenhouse that's actually gets exposed to the outside. And if you ever see a picture of a greenhouse and you see one of these lovely plants here wet, that's not true. That's just a nice to make it look better. >> Spray it for the photo. >> Yeah, yeah. They spray it for the photo. But actually everything is dry. That water goes directly to the roots and we monitor how much we put in and how much comes out. And then we recycle it. We even get so much recycling, we run natural gas generators to heat the water to heat the greenhouse. We take the burn-off of natural gas, the CO2, and funnel that into the greenhouse to give it natural stimulant. >> So, this is starting to remind me of "The Martian", if you read the book or if you seen the movie. >> Oh yeah. >> But planting the potatoes inside the hab, in the habitat. >> Yeah, and you cut 'em in half and the little ones grow with that next ones. But yep, we recycle everything that we do. And that's what we do. >> That's amazing. >> And all that information at their fingertips. Really, I think what technology is enabling you all to do is focus on what you all are good at, which is focusing on your farming operation and not necessarily the technology. So, one of the places I think we deliver some value is in validating a lot of the solutions so that customers don't have to figure that all out themselves. >> Yeah, 'cause I'm not a security expert. I don't always understand the true depth of security, but that's where that relationship is. We need this and we need that. And we need a secure way to let those communicate. And we can hand that off to the experts at Dell and let us do what we do best. >> What have been some of the changes? In the last couple of years, we've seen the security elevate skyrocket to a board level conversation. Ransomware is a when, not if, we get attacked. How does Dell help you from a security perspective ensure that what you're able to do ultimately gets these products to market in a secure fashion so that all that data that you're generating isn't exposed? >> So, like I said, I agree 100%. It's not matter of if it's going to happen, it's when it's going to happen. So, one of the things that we've actually done is we started to use Dell solution, the PowerProtect Data Manager to back up our solutions on the VxRail. And it actually did twofold for us. It allowed us to do a lot of database manipulation from restores and stuff like that. But we're now actually even investing in the cyber recovery vault that gives us that protection. And it allows us to now look at how long will it take us to get back up. And we're doing some tests right now and the last test we did is we're able to get back up going as a company from a full attack in about an hour. >> Wow. >> We've actually done a few simulations now. So, we are able to recover what our core needs are within an hour. >> Which is a very different metric than simply saying, "Oh, the data's available." >> Yeah. >> No, no, no, no, no, no, no, no. You get zero credit for that. We need our operations to be back up and running. >> Even that hour is stressful to our growers. >> Sure. >> It's a variable within a variable because if you go in the summer when it's super hot, they'll be very stressed out within an hour. And then you got nice calm weather day, it's not as bad. But the weather can change in how they have to close the vents. And you're not just closing one vent, you're closing 32, 64, 100 acres of vents. And you're changing irrigation cycle. You need that automation to do it for you. >> How do you let people eat these things after all the care that goes into it? I'm going to feel mildly guilty for just about a second and a half before I sink my teeth into the cucumber. >> Oh, but that's the joy of it. That's one of the things that I love. >> This is serious. You're proud of this, aren't you? >> Oh yeah. You know what? There's not single person at Nature Fresh that isn't proud of what we do each day. We enjoy what we do and it's a culture that makes us strive to do better every day. It's just a great feeling to be there every day and to just enjoy what you're doing. >> And see, it's real. It's real. Isn't it great? Isn't it great to be a part of? My background's in economics. I think of these things in terms of driving efficiency. And this is just a beautiful thing. When you control those variables, you leverage the technology and what's the end result? You're essentially uplifting everything in the world. >> Yeah, so true. >> Not to get philosophical on ya. >> Right, and feeding the world, especially during the last couple of years, that access. One of the things we learned in the pandemic, one of many, is access to realtime data isn't a nice to have anymore, it's essential. >> Yeah. >> So true. >> And so, the story that you're telling here, the impact to the growers, enabling them to focus what you were saying, Alison, on what they do best, Dell Technologies, VxRail enabling Nature Fresh to focus on what it does best, ultimately delivering food to people during the last couple of years was huge. >> Yeah, and allowing even at a reduced labor number for us to keep growing and doing things by automation. We still need labor in the greenhouse to pick, prune and do stuff like that. But again, we're looking into technologies to help offset that. But again, it was one of those things that we just had to be efficient at everything we do. And we drove that through everything we have. >> Well, and you guys haven't stopped. Right? >> Yeah. >> You're continuing to figure out, he was just telling me a little bit about what their next step is. So, just getting more and more accurate, more intelligence as they grow. So, it's the possibilities, that's what's exciting to me about Edge. I think this example is great, 'cause it's so relatable. Everybody can understand what the Edge is in this context. And it's really driven by the fact that you can put compute into so many different places now. It's more though a matter about how do you gather it? How do you do it in a way where you can actually understand and glean information and insights from it? And that, I think, is what you all are really focused on. >> Yeah, yeah, information is key. >> It is key. What's next from Dell's perspective for Edge computing technologies? what are some of the things you guys got cooking? >> Yeah, we're going to try to help customers to continue to simplify their Edge. So, to deliver those insights that they need where they need them, to do it in a really secure way. I know we talked about security but to do it in really a zero trust fashion. And to help customers to do it also in a zero IT fashion. Because in this example, it's the growers that are out there in the fields, or in your greenhouse in this sense, helping people that aren't necessarily IT specialists to be able to get all the benefits from the technology. >> So, do you think that VxRail technology could be used to optimize say the production of olive oil? I'm looking here and we have the makings of a pretty good salad. >> Yeah, you do. >> There you go. >> It obviously doesn't just apply to food production. >> Yeah, it really goes across the board. Whether we're talking about manufacturing or retail or energy, putting technology right there at the point of data creation and being able to figure out how to manage that inflow of data, be able to figure out which portion of the data is really valuable, and then driving decisions and being able to understand and intelligently make decisions for your business based on that data is really important. >> Keith, what's next? Give us, as we wrap out this segment here, what's next from a technology perspective? You mentioned a couple things you're looking into. >> Yeah, so I think automation is really going to change the way we do things. And automation within the greenhouse is truly just becoming a reality. It's funny we go back and we say, can we do this stuff? And now it's like, oh, even three years ago, I don't think we were quite ready for it, but now it's right there. So, I see us doing a lot more work with vendors like Dell and to do automatic picking, automatic scouting, all that stuff that we do by hand, do it in an automated fashion. >> And at scale, right? >> Yeah. >> That's the important part. I think when you're managing a snowflake, you can only do it to some level, and to be able to automate it and to be able to break down those silos, you're going to be able to apply it to so many parts of your business. >> Yeah, wide applicability. Guys, thank you so much for joining us, sharing the Nature Fresh, Dell story, bringing us actual product. This is so exciting. We congratulate you on how you're leveraging technology in a really innovative way. And we look forward to hearing what's next. Maybe we'll see you at Dell Technologies World next year. >> Sounds great. >> Sounds great. >> Thank you so much. >> All right, our pleasure, guys. >> Thank you. >> For our guests and Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live from VMware Explorer 2022. Dave and I will be right back with our next guest. So, stick around. (light upbeat music)

>>Hello, everyone. Welcome to the cubes coverage here. New York city for AWS Amazon web services summit 2022. I'm John furrier, host of the cube with Dave ante. My co-host. We are breaking it down, getting an update on the ecosystem. As the GDP drops, inflations up gas prices up the enterprise continues to grow. We're seeing exceptional growth. We're here on the ground floor. Live at the Summit's packed house, 10,000 people. Eric Bradley's here. Chief STR at ETR, one of the premier enterprise research firms out there, partners with the cube and powers are breaking analysis that Dave does check that out as the hottest podcast in enterprise. Eric. Great to have you on the cube. Thanks for coming on. >>Thank you so much, John. I really appreciate the collaboration always. >>Yeah. Great stuff. Your data's amazing ETR folks watching check out ETR. They have a unique formula, very accurate. We love it. It's been moving the market. Congratulations. Let's talk about the market right now. This market is booming. Enterprise is the hottest thing, consumers kind of in the toilet. Okay. I said that all right, back out devices and, and, and consumer enterprise is still growing. And by the way, this first downturn, the history of the world where hyperscalers are on full pumping on all cylinders, which means they're still powering the revolution. >>Yeah, it's true. The hyperscalers were basically at this two sun system when Microsoft and an AWS first came around and everything was orbiting around it. And we're starting to see that sun cool off a little bit, but we're talking about a gradient here, right? When we say cool off, we're not talking to shutdown, it's still burning hot. That's for sure. And I can get it to some of the macro data in a minute, if that's all right. Or do you want me to go right? No, go go. Right. Yeah. So right now we just closed our most recent survey and that's macro and vendor specific. We had 1200 people talk to us on the macro side. And what we're seeing here is a cool down in spending. We originally had about 8.5% increase in budgets. That's cool down is 6.5 now, but I'll say with the doom and gloom and the headlines that we're seeing every day, 6.5% growth coming off of what we just did the last couple of years is still pretty fantastic as a backdrop. >>Okay. So you, you started to see John mentioned consumer. We saw that in Snowflake's earnings. For example, we, we certainly saw, you know, Walmart, other retailers, the FA Facebooks of the world where consumption was being dialed down, certain snowflake customers. Not necessarily, they didn't have mentioned any customers, but they were able to say, all right, we're gonna dial down, consumption this quarter, hold on until we saw some of that in snowflake results and other results. But at the same time, the rest of the industry is booming. But your data is showing softness within the fortune 500 for AWS, >>Not only AWS, but fortune 500 across the board. Okay. So going back to that larger macro data, the biggest drop in spending that we captured is fortune 500, which is surprising. But at the same time, these companies have a better purview into the economy. In general, they tend to see things further in advance. And we often remember they spend a lot of money, so they don't need to play catch up. They'll easily more easily be able to pump the brakes a little bit in the fortune 500. But to your point, when we get into the AWS data, the fortune 500 decrease seems to be hitting them a little bit more than it is Azure and GCP. I >>Mean, we're still talking about a huge business, right? >>I mean, they're catching up. I mean, Amazon has been transforming from owning the developer cloud startup cloud decade ago to really putting a dent on the enterprise as being number one cloud. And I still contest that they're number one by a long ways, but Azure kicking ass and catching up. Okay. You seeing people move to Azure, you got Charlie bell over there, Sean, by former Amazonians, Theresa Carlson, people are going over there, there there's lift over at Azure. >>There certainly is. >>Is there kinks in the arm or for AWS? There's >>A couple of kinks, but I think your point is really good. We need to take a second there. If you're talking about true pass or infrastructure is a service true cloud compute. I think AWS still is the powerhouse. And a lot of times the, the data gets a little muddied because Azure is really a hosted platform for applications. And you're not really sure where that line is drawn. And I think that's an important caveat to make, but based on the data, yes, we are seeing some kinks in the armor for AWS. Yes. Explain. So right now, a first of all caveat, 40% net score, which is our proprietary spending metric across the board. So we're not like raising any alarms here. It's still strong that said there are declines and there are declines pretty much across the board. The only spot we're not seeing a decline at all is in container, spend everything else is coming down specifically. We're seeing it come down in data analytics, data warehousing, and M I, which is a little bit of a concern because that, that rate of decline is not the same with Azure. >>Okay. So I gotta ask macro, I see the headwinds on the macro side, you pointed that out. Is there any insight into any underlying conditions that might be there on AWS or just a chronic kind of situational thing >>Right now? It seems situational. Other than that correlation between their big fortune 500, you know, audience and that being our biggest decline. The other aspect of the macro survey is we ask people, if you are planning to decline spend, how do you plan on doing it? And the number two answer is taking a look at our cloud spend and auditing it. So they're kind say, all right, you know, for the last 10 years it's been drunken, sail or spend, I >>Was gonna use that same line, you know, >>Cloud spend, just spend and we'll figure it out later, who cares? And then right now it's time to tighten the belts a little bit, >>But this is part of the allure of cloud at some point. Yeah. You, you could say, I'm gonna, I'm gonna dial it down. I'm gonna rein it in. So that's part of the reason why people go to the cloud. I want to, I wanna focus in on the data side of things and specifically the database. Let, just to give some context if, and correct me if I'm, I'm a little off here, but snowflake, which hot company, you know, on the planet, their net score was up around 80% consistently. It it's dropped down the last, you know, quarter, last survey to 60%. Yeah. So still highly, highly elevated, but that's relative to where Amazon is much larger, but you're saying they're coming down to the 40% level. Is that right? >>Yeah, they are. And I remember, you know, when I first started doing this 10 years ago, AWS at a 70%, you know, net score as well. So what's gonna happen over time is those adoptions are gonna get less and you're gonna see more flattening of spend, which ultimately is going to lower the score because we're looking for expansion rates. We wanna see adoption and increase. And when you see flattening a spend, it starts to contract a little bit. And you're right. Snowflake also was in the stratosphere that cooled off a little bit, but still, you know, very strong and AWS is coming down. I think the reason why it's so concerning is because a it's within the fortune 500 and their rate of decline is more than Azure right >>Now. Well, and, and one of the big trends you're seeing in database is this idea of converging function. In other words, bringing transaction and analytics right together at snowflake summit, they added the capability to handle transaction data, Mongo DB, which is largely mostly transactions added the capability in June to bring in analytic data. You see data bricks going from data engineering and data science now getting into snowflake space and analytics. So you're seeing that convergence Oracle is converging with my SQL heat wave and their core databases, couch base couch base is doing the same. Maria do virtually all these database companies are, are converging their platforms with the exception of AWS. AWS is still the right tool for the right job. So they've got Aurora, they've got RDS, they've got, you know, a dynamo DV, they've got red, they've got, you know, going on and on and on. And so the question everybody's asking is will that change? Will they start to sort of cross those swim lanes? We haven't seen it thus far. How is that affecting the data >>Performance? I mean, that's fantastic analysis. I think that's why we're seeing it because you have to be in the AWS ecosystem and they're really not playing nicely with others in the sandbox right now that now I will say, oh, Amazon's not playing nicely. Well, no, no. Simply to your point though, that there, the other ones are actually bringing in others at consolidating other different vendor types. And they're really not. You know, if you're in AWS, you need to stay within AWS. Now I will say their tools are fantastic. So if you do stay within AWS, they have a tool for every job they're advanced. And they're incredible. I think sometimes the complexity of their tools hurts them a little bit. Cause to your point earlier, AWS started as a developer-centric type of cloud. They have moved on to enterprise cloud and it's a little bit more business oriented, but their still roots are still DevOps friendly. And unless you're truly trained, AWS can be a little scary. >>So a common use case is I'm gonna be using Aurora for my transaction system and then I'm gonna ETL it into Redshift. Right. And, and I, now I have two data stores and I have two different sets of APIs and primitives two different teams of skills. And so that is probably causing some friction and complexity in the customer base that again, the question is, will they begin to expand some of those platforms to minimize some of that friction? >>Well, yeah, this is the question I wanted to ask on that point. So I've heard from people inside Amazon don't count out Redshift, we're making, we're catching up. I think that's my word, but they were kind of saying that right. Cuz Redshift is good, good database, but they're adding a lot more. So you got snowflake success. I think it's a little bit of a jealousy factor going on there within Redshift team, but then you got Azure synapse with the Synap product synapse. Yep. And then you got big query from Google big >>Query. Yep. >>What's the differentiation. What are you seeing for the data for the data warehouse or the data clouds that are out there for the customers? What's the data say, say to us? >>Yeah, unfortunately the data's showing that they're dropping a little bit whose day AWS is dropping a little bit now of their data products, Redshift and RDS are still the two highest of them, but they are starting to decline. Now I think one of the great data points that we have, we just closed the survey is we took a comparison of the legacy data. Now please forgive me for the word legacy. We're gonna anger a few people, but we Gotter data Oracle on-prem, we've got IBM. Some of those more legacy data warehouse type of names. When we look at our art survey takers that have them where their spend is going, that spends going to snowflake first, and then it's going to Google and then it's going to Microsoft Azure and, and AWS is actually declining in there. So when you talk about who's taking that legacy market share, it's not AWS right now. >>So legacy goes to legacy. So Microsoft, >>So, so let's work through in a little context because Redshift really was the first to take, you know, take the database to the cloud. And they did that by doing a one time license deal with par XL, which was an on-prem database. And then they re-engineered it, they did a fantastic job, but it was still engineered for on-prem. Then you along comes snowflake a couple years later and true cloud native, same thing with big query. Yep. True cloud native architecture. So they get a lot of props. Now what, what Amazon did, they took a page outta of the snowflake, for example, separating compute from storage. Now of course what's what, what Amazon did is actually not really completely separating like snowflake did they couldn't because of the architecture, they created a tearing system that you could dial down the compute. So little nuances like that. I understand. But at the end of the day, what we're seeing from snowflake is the gathering of an ecosystem in this true data cloud, bringing in different data types, they got to the public markets, data bricks was not able to get to the public markets. Yeah. And think is, is struggling >>And a 25 billion evaluation. >>Right. And so that's, that's gonna be dialed down, struggling somewhat from a go to market standpoint where snowflake has no troubles from a go to market. They are the masters at go to market. And so now they've got momentum. We talked to Frank sluman at the snowflake. He basically said, I'm not taking the foot off the gas, no way. Yeah. We, few of our large, you know, consumer customers dialed things down, but we're going balls to the >>Wall. Well, if you look at their show before you get in the numbers, you look at the two shows. Snowflake had their summit in person in Vegas. Data bricks has had their show in San Francisco. And if you compare the two shows, it's clear, who's winning snowflake is blew away from a, from a market standpoint. And we were at snowflake, but we weren't at data bricks, but there was really nothing online. I heard from sources that it was like less than 3000 people. So >>Snowflake was 1900 people in 2019, nearly 10,000. Yeah. In 2020, >>It's gonna be fun to sort of track that as a, as an odd caveat to say, okay, let's see what that growth is. Because in fairness, data, bricks, you know, a little bit younger, Snowflake's had a couple more years. So I'd be curious to see where they are. Their, their Lakehouse paradigm is interesting. >>Yeah. And I think it's >>And their product first company, yes. Their go to market might be a little bit weak from our analysis, but that, but they'll figure it out. >>CEO's pretty smart. But I think it's worth pointing out. It's like two different philosophies, right? It is. Snowflake is come into our data cloud. That's their proprietary environment. They're the, they think of the iPhone, right? End to end. We, we guarantee it's all gonna work. And we're in control. Snowflake is like, Hey, open source, no, bring in data bricks. I mean data bricks, open source, bring in this tool that too, now you are seeing snowflake capitulate a little bit. They announce, for instance, Apache iceberg support at their, at the snowflake summit. So they're tipping their cap to open source. But at the end of the day, they're gonna market and sell the fact that it's gonna run better in native snowflake. Whereas data bricks, they're coming at it from much more of an open source, a mantra. So that's gonna, you know, we'll see who look at, you had windows and you had apple, >>You got, they both want, you got Cal and you got Stanford. >>They both >>Consider, I don't think it's actually there yet. I, I find the more interesting dynamic right now is between AWS and snowflake. It's really a fun tit for tat, right? I mean, AWS has the S three and then, you know, snowflake comes right on top of it and announces R two, we're gonna do one letter, one number better than you. They just seem to have this really interesting dynamic. And I, and it is SLT and no one's betting against him. I mean, this guy's fantastic. So, and he hasn't used his war chest yet. He's still sitting on all that money that he raised to your point, that data bricks five, their timing just was a little off >>5 billion in >>Capital when Slootman hasn't used that money yet. So what's he gonna do? What can he do when he turns that on? He finds the right. >>They're making some acquisitions. They did the stream lit acquisitions stream. >>Fantastic >>Problem. With data bricks, their valuation is underwater. Yes. So they're recruiting and their MNAs. Yes. In the toilet, they cannot make the moves because they don't have the currency until they refactor the multiple, let the, this market settle. I I'm, I'm really nervous that they have to over factor the >>Valuation. Having said that to your point, Eric, the lake house architecture is definitely gaining traction. When you talk to practitioners, they're all saying, yeah, we're building data lakes, we're building lake houses. You know, it's a much, much smaller market than the enterprise data warehouse. But nonetheless, when you talk to practitioners that are actually doing things like self serve data, they're building data lakes and you know, snow. I mean, data bricks is right there. And as a clear leader in, in ML and AI and they're ahead of snowflake, right. >>And I was gonna say, that's the thing with data bricks. You know, you're getting that analytics at M I built into it. >>You know, what's ironic is I remember talking to Matt Carroll, who's CEO of auDA like four or five years ago. He came into the office in ma bro. And we were in temporary space and we were talking about how there's this new workload emerging, which combines AWS for cloud infrastructure, snowflake for the simple data warehouse and data bricks for the ML AI, and then all now all of a sudden you see data bricks yeah. And snowflake going at it. I think, you know, to your point about the competition between AWS and snowflake, here's what I think, I think the Redshift team is, you know, doesn't like snowflake, right. But I think the EC two team loves it. Loves it. Exactly. So, so I think snowflake is driving a lot of, >>Yeah. To John's point, there is plenty to go around. And I think I saw just the other day, I saw somebody say less than 40% of true global 2000 organizations believe that they're at real time data analytics right now. They're not really there yet. Yeah. Think about how much runway is left and how many tools you need to get to real time streaming use cases. It's complex. It's not easy. >>It's gonna be a product value market to me, snowflake in data bricks. They're not going away. Right. They're winning architectures. Yeah. In the cloud, what data bricks did would spark and took over the Haddo market. Yeah. To your point. Now that big data, market's got two players, in my opinion, snow flicking data, bricks converging. Well, Redshift is sitting there behind the curtain, their wild card. Yeah. They're wild card, Dave. >>Okay. I'm gonna give one more wild card, which is the edge. Sure. Okay. And that's something that when you talk about real time analytics and AI referencing at the edge, there aren't a lot of database companies in a position to do that. You know, Amazon trying to put outposts out there. I think it runs RDS. I don't think it runs any other database. Right. Snowflake really doesn't have a strong edge strategy when I'm talking the far edge, the tiny edge. >>I think, I think that's gonna be HPE or Dell's gonna own the outpost market. >>I think you're right. I'll come back to that. Couch base is an interesting company to watch with Capella Mongo. DB really doesn't have a far edge strategy at this point, but couch base does. And that's one to watch. They're doing some really interesting things there. And I think >>That, but they have to leapfrog bongo in my >>Opinion. Yeah. But there's a new architecture emerging at the edge and it's gonna take a number of years to develop, but it could eventually from an economic standpoint, seep back into the enterprise arm base, low end, take a look at what couch base is >>Doing. They hired an Amazon guard system. They have to leapfrog though. They need to, they can't incrementally who's they who >>Couch >>Base needs to needs to make a big move in >>Leap frog. Well, think they're trying to, that's what Capella is all about was not only, you know, their version of Atlas bringing to the cloud couch base, but it's also stretching it out to the edge and bringing converged database analytics >>Real quick on the numbers. Any data on CloudFlare, >>I was, I've been sitting here trying to get the word CloudFlare out my mouth the whole time you guys were talking, >>Is this another that's innovated in the ecosystem. So >>Platform, it was really simple for them early on, right? They're gonna get that edge network out there and they're gonna steal share from Akamai. Then they started doing exactly what Akamai did. We're gonna start rolling out some security. Their security is fantastic. Maybe some practitioners are saying a little bit too much, cuz they're not focused on one thing or another, but they are doing extremely well. And now they're out there in the cloud as well. You >>Got S3 compare. They got two, they got an S3 competitor. >>Exactly. So when I'm listening to you guys talk about, you know, a, a couch base I'm like, wow, those two would just be an absolute fantastic, you know, combination between the two of them. You mean >>CloudFlare >>Couch base. Yeah. >>I mean you got S3 alternative, right? You got a Mongo alternative basically in my >>Opinion. And you're going and you got the edge and you got the edge >>Network with security security, interesting dynamic. This brings up the super cloud date. I wanna talk about Supercloud because we're seeing a trend on we're reporting this since last year that basically people don't have to spend the CapEx to be cloud scale. And you're seeing Amazon enable that, but snowflake has become a super cloud. They're on AWS. Now they're on Azure. Why not tan expansion expand the market? Why not get that? And then it'll be on Google next, all these marketplaces. So the emergence of this super cloud, and then the ability to make that across a substrate across multiple clouds is a strategy we're seeing. What do you, what do you think? >>Well, honestly, I'm gonna be really Frank here. The, everything I know about the super cloud I know from this guy. So I've been following his lead on this and I'm looking forward to you guys doing that conference and that summit coming up from a data perspective. I think what you're saying is spot on though, cuz those are the areas we're seeing expansion in without a doubt. >>I think, you know, when you talk about things like super cloud and you talk about things like metaverse, there's, there's a, there, there look every 15 or 20 years or so this industry reinvents itself and a new disruption comes out and you've got the internet, you've got the cloud, you've got an AI and VR layer. You've got, you've got machine intelligence. You've got now gaming. There's a new matrix, emerging, super cloud. Metaverse there's something happening out there here. That's not just your, your father's SAS or is or pass. Well, >>No, it's also the spend too. Right? So if I'm a company like say capital one or Goldman Sachs, my it spend has traditionally been massive every year. Yes. It's basically like tons of CapEx comes the cloud. It's an operating expense. Wait a minute, Amazon has all the CapEx. So I'm not gonna dial down my budget. I want a competitive advantage. So next thing they know they have a super cloud by default because they just pivoted their, it spend into new capabilities that they then can sell to the market in FinTech makes total sense. >>Right? They're building out a digital platform >>That would, that was not possible. Pre-cloud >>No, it wasn't cause you weren't gonna go put all that money into CapEx expenditure to build that out. Not knowing whether or not the market was there, but the scalability, the ability to spend, reduce and be flexible with it really changes that paradigm entire. >>So we're looking at this market now thinking about, okay, it might be Greenfield in every vertical. It might have a power law where you have a head of the long tail. That's a player like a capital one, an insurance. It could be Liberty mutual or mass mutual that has so much it and capital that they're now gonna scale it into a super cloud >>And they have data >>And they have the data tools >>And the tools. And they're gonna bring that to their constituents. Yes, yes. And scale it using >>Cloud. So that means they can then service the entire vertical as a service provider. >>And the industry cloud is becoming bigger and bigger and bigger. I mean, that's really a way that people are delivering to market. So >>Remember in the early days of cloud, all the banks thought they could build their own cloud. Yeah. Yep. Well actually it's come full circle. They're like, we can actually build a cloud on top of the cloud. >>Right. And by the way, they can have a private cloud in their super cloud. Exactly. >>And you know, it's interesting cause we're talking about financial services insurance, all the people we know spend money in our macro survey. Do you know the, the sector that's spending the most right now? It's gonna shock you energy utilities. Oh yeah. I was gonna, the energy utilities industry right now is the one spending the most money I saw largely cuz they're playing ketchup. But also because they don't have these type of things for their consumers, they need the consumer app. They need to be able to do that delivery. They need to be able to do metrics. And they're the they're, they're the one spending right >>Now it's an arms race, but the, the vector shifts to value creation. So >>It's it just goes back to your post when it was a 2012, the trillion dollar baby. Yeah. It's a multi-trillion dollar baby that they, >>The world was going my chassis post on Forbes, headline trillion dollar baby 2012. You know, I should add it's happening. That's >>On the end. Yeah, exactly. >>Trillions of babies, Eric. Great to have you on the key. >>Thank you so much guys. >>Great to bring the data. Thanks for sharing. Check out ETR. If you're into the enterprise, want to know what's going on. They have a unique approach, very accurate in their survey data. They got a great market basket of, of, of, of, of data questions and people and community. Check it out. Thanks for coming on and sharing with. >>Thank you guys. Always enjoy. >>We'll be back with more coverage here in the cube in New York city live at summit 22. I'm John fur with Dave ante. We'll be right back.

thecube presents dell technologies world brought to you by dell good afternoon everyone welcome back to thecube's third day of coverage live from the show floor at dell technologies world 2022 lisa martin here with dave vellante we've been having lots of great conversations the last day and a half one of the things we love to do is really hear from the voice of dell's customers and we're going to do that next please welcome jonathan suckler the senior director of product marketing for dell and keith bradley the vp of i.t at nature fresh farms guys welcome hey great to be here thank you great thank you for letting us be here of course thanks for joining us so jonathan we're going to start with you we've been hearing a lot about we've been talking about ai for decades we've been hearing a lot about ai at the show it's it's so it's pervasive right it's in our refrigerators and our thermostats and our cars and that hockey puck thing that's in the kitchen that plays music when you're cooking right what's going on what is do you think from dell's perspective is fueling the adoption of ai now you know there's it i think that there's this huge interest in ai right now and you and you you're definitely pointed out a lot of the great success stories around ai but the the real benefit of is that you know with with with artificial intelligence applied to a lot of business problems you can solve them in ways that are that are much quicker than you would expect you know and you can solve them in ways you wouldn't have expected uh uh you know then than than you do what's really surprising though is as a as many as many people are interested in in using it and and all of the benefits that come from it though is that we really don't see the adoption being as quick as we would like to right i mean i want to say that like 80 percent of companies out there want to use ai they're testing ai you know they're they're they're planning uh projects around ai applications but when you ask them what's in production it really is still it's an innovator's game like you know companies like like nature fresh farms with uh what they're doing is truly at the tip of the spear what are some of the challenges jonathan that you're seeing from an adoption perspective of 80 say we want to actually be able to leverage this emerging technology in production the challenges are i think the pers it's a perceived challenge issue right i think there's like three big issues that people perceive as being uh barriers to adoption um the first one is pretty obvious it's cost right they they see artificial intelligence you they hear about all of the uh you know specialized hardware and and the software and the new and the people and the talent you've got to acquire to uh as being a barrier to that and they don't see the benefit or they they balance that against the benefit i think there's an issue also with uh complexity right because at the same time that you know you're building these these infrastructures around what you need to do for an artificial intelligence-enabled application there's this expectation that it needs to be separate and different and special and that becomes an issue from a management perspective right uh and i think finally uh it's uh it's change right i mean you you're you're bringing in new talent new new skill sets you're bringing in new technology and i think a lot of companies still today you know look at that as being like well what if if i do this am i really going to see the benefit if i am i stuck going down a path that i that i'm going to change later on and i think that's really the issue uh you know those but they're all perceived issues they're they're in in reality they're really not that true i mean keith has this done that nature fresh farms has done some incredible stuff right with with ai in an area that i i would never have guessed being a ripe for that kind of innovation you know so lisa keith knows that i love you know fresh tomatoes i live in the northeast where it's cold six months a year so we plant our tomatoes at memorial day weekend yeah right and then maybe you're lucky if you get tomatoes late august september and then you're done however you and i met a couple years ago you sent me all these vegetables i think i was popping the tomatoes like candy and then i interviewed you you were live in the giant greenhouse and it's just amazing what you guys have going to jonathan's point you're using ai to really create you know sustainable continuing flow of awesome vegetables tell us more about nature fresh so at nature fresh farms we're a 200 acre greenhouse just shy of 200 acres growing bell peppers and tomatoes and one of the biggest use cases for us in our ai is everything we do we need to be proactive so we need that ai to not be reactive to climate change to what happens to the weather to be proactive so it changes before the plant reacts because every time the plant will doesn't do as great we've lost production from it so we're always using our ai to help increase the yield per square meter inside of our greenhouses so everything from the growth the length the weight of the plant we monitor everything we want to know every aspect of that plant's life it's almost like doing an ekg on a plant 24 by 7 and wanting to know everything out of it how old is is the company nature fresh farms started in 1999 so we're just hitting 23 years now so we started off as a 16 acre little greenhouse our owner kind of got into it saying i think this is going to be new and he was one of the first ones to say i want to be all computers i want to do it culturally this is this was not an upsell or a hard sell for you from the vp of i.t perspective no no he's always been one saying that technology will change the greenhouse industry and that by adding technology the expertise is in the growers and letting technology help them do more because when we first started in the greenhouse industry you'd need a grower for every range so every 16 acre range would need a very senior grower now we have one grower that does 64 or almost 100 acres of greenhouse he'll have junior growers but he's able to do so much more so where do you specifically apply the ai can you talk about that uh so we talk specifically we apply the ai in almost all areas anything from picking the plant to the climate of the plant we'll do all those areas even on the packing line we actually have uh one robot well not a robot story a machine that looks at a box of tomatoes and basically tells us which one doesn't match the proper red because how you see red how you guys see red is slightly different so it'll tell us that this red tomato doesn't match so change out the right one so when it goes down the line into the consumers they're all exactly the same so it looks unified it looks beautiful like that how about that you're sending out red tomatoes yeah yeah that's what we do now what is dell's role in all this so dell's role has helped us grow what we do we started off with power scale and vxrail and stuff like that so everything's hosted on that and they have been a great partner at finding that solution to them i've been able to go to them and say hey i'm running into a storage problem i'm running into a compute problem they've been able to find a validated solution for us to use and to put out there and help us grow and then the next part that was really great that we've really now done is it's scalable as we're growing we've been able to community add more compute and more storage but not have to take things down to do it and that's what we really wanted to do yeah no i i think and i think what you're talking about there is really the one of the big issues that i was talking about earlier which is around complexity and cost right you know one of the answers to doing artificial intelligence in the enterprise is making sure that you can maintain and have an infrastructure that scales that's part of everything else and and to do that you've got to virtualize it and you know with power uh with a dell vxrail and power scale which it's all running vmware uh with with the uh with the containers and the vms on top of that actually managing you know and running those applications it takes a lot of the complexity of of worrying about where you're going to how you're going to manage that infrastructure and who's going to do it who's going to back it up how are you going to how you're going to you know keep costs down so it really really helps i think yeah yep and we just love it because we're able to take that solution make it better and make it do more and more every day and it's it's allowed our growers to see exponential time where they did it years ago it used to be overnight to get results sometimes from our system doing it now we're seeing it in real time and that's where i it really got to that point now where we're being reactive proactive to the to the plant the weather to stuff we know exactly what needs to happen before happens and that makes the plant grow more and that's what we're always aiming to do you know if you don't mind one of the things that i you were telling me about i think is really fascinating so is this idea that you know you need to have a data scientist you need a whole new staff to manage these applications these these technologies but you were talking about your growers are actually yeah they're actually data scientists that way right that's what we like to call them we call them grower scientists right now green sciences data scientists yeah because they've researched this data they know what the plant does and it's it's been a neat transition we talked about that how they went from being out in the greenhouse so much to being in front of the computer now but now with the help of ai they're more able to get back out into the greenhouse to now watch the plants see what's going on and be a part of the growth again and they said it's been great but they're the ones that are looking at these numbers every day every second if it's not remotely from home it's remote on the greenhouse they're launching everything because yeah think about they're watching 64 acres of land and making sure that does everything it needs to do so lisa this is a really good example of sort of distributed data at work right about this whole notion of data mesh where you have domain experts actually own the data you know they know they can bring context to the data it's not somebody who's just oh it's just data i don't really know what to do with it it's somebody who actually knows what it what it means that to me is a future use case that's going to explode yep it's like me i i look at their data and they always tease me because i'll look at it and i'll go yeah i have no idea but it's giving you numbers so are they right or not and it's a it's always a joke in the in the plant that i like ah you don't got question marks so it's working and then i'll go to them and say is this right and then they'll say yep we're on we're getting what we need i love the idea that you know we've we've heard of this term citizens citizen scientists or citizen data scientists and you have a grower data scientist yeah and i think that eliminates you talk again those problems like or challenges i mentioned earlier that kind of eliminates the complexity issue you know the uncertainty issue the fear of change when you've got your own uh teams who are who know what they need to do and they have the data to do it it just changes the game right yeah and the other two we found is i've always believed in it myself if you love what you do yeah you commit so much more to it and our growers they love what they do so their passion just exudes into the data and then it comes right back into the product well the technology is an enabler of their passion really i'm curious keith how the obviously the events of the last two years have been quite challenging how has ai been a facilitator of what seems like a competitive differentiation for your company uh it actually really accelerated it because we really had to invest in it that's when we started the the big journey to the vx rail the power protect data management we really had to invest in and then we heavily invested in the ai we've always had some lingerie in the background and it's always been there and we've been using it for years and years now but it really brought it right to the forefront though we have to do this better and we had to really push everything and as we grew it became more and more apparent that we were taking that road that investment was paying off for us now yeah how do i buy ai from you so you know it's interesting like i said we want to make it easy for for customers to implement an ai solution at dell and it's not so much that you go out and you buy an ai right or something like that what you're doing is is you're you're making your infrastructure ready for the applications that you need to run right and so at dell we have this uh these predefined uh architectures that we call validated designs they're validated uh to work in you know in a co in any a common environment we take the you know we take the guesswork out of uh how to put these systems together uh and in the case of artificial intelligence you know we we validate with our partners like uh uh vmware and like nvidia to make sure that the technologies work together so that they fit into the existing infrastructure they already have and uh you know in a way it's i think of it as virtualized ai but i think even more importantly it's it's ai for for any company it's not not for the not for the special scientists and you know not for the not for the uh the researcher at the university it's it's for you know it's for nature fresh farms with vxrail it's software defined you're able to bring in a gpu you've got the flexibility to do that for example yeah whereas with the traditional you know the old days you wouldn't be able to do that you'd be you'd have a lot of time on your hands and a lot of compute power you spent a lot of money doing what you need to do yeah oh yeah we'd be spending all the time working at it growing it and doing more and it just made our life easier not to manage the life the managed life cycle of the ai systems that we have is so much easier now because it's all predefined it's all it's all ready to go upgrade process all that is built into it yeah so life cycle is much easier from the i.t side so keith talk to talk to those folks in the audience who might have those those perceived challenges or limitations that jonathan was talking about because you're making it sound like this has been such an enabler of a business that's 23 years old we're taking growers who are experts at growing and they're playing and loving playing with data and ai how do you how do you advise folks to really eliminate some of those preconceived challenges that are out there i would say you have to sit there and just dive in you have to actually start to do it but you have to think about not where you the first two steps say where we want to be five steps from now and then say talk to a partner like dell with us and say this is where we want to get to this is and then figure out a way how to get there and committing to that path you can't get frustrated the first few times ai is very flustering sometimes the first few pass don't work and just saying going back to the drawing board each time we'll do it we've had a couple experiments where it didn't work and we didn't get the results we wanted and we had to just say let's change our thought process and how do we optimize this ai and then all of a sudden we started getting the right results but that it's it's like uh falling over the first time you fall over as a child it's gonna hurt but each time he gets a little less each time failure is progress yeah that's right that's right fail fast yeah failure can be a good f word yeah if you but you have to be open-minded yep oh yes every minute every minute you have to be open-minded and you have to you have to think outside the box too and that's the biggest part of things it's just not accepting things and just saying we have to do it but you have to have the culture that will embrace that and it sounds like the growers these are people that are expert and growing how it sounds like it wasn't an uphill battle to get them to come on board and become these citizen growers data scientists well you know it was funny because with the technology it kind of gave them that work-life balance that they didn't have before their life was inside the greenhouse because the plants grow 24 by 7. so now all of a sudden they just kept growing they could they could go home they kept doing their thing they could go home at five o'clock and because of the vdi solutions and stuff like that and the ai that's helping them grow they can kind of turn off and instead of having to come in sunday morning and that the the one joke we used to have is that on sundays if you're in church and there's clouds had come rolling out all the growers would stand up and leave because they had to go to their church they had to go back to their farm now the system does that automatically for them so they're able to get their work life home balance back so it was different for them it was a jump for them anybody that's not used to technology and jumping into it is hard but once they started to see the benefits and what more yield they can get and the home work life balance it was amazing there's no i can't underestimate the work-life balance enough i think it's challenge it's a very challenging thing for people in any industry to achieve we've we've seen that in the last two years with you know do i live at work do i work from home so achieving that is kudos to you and for del for enabling that because that's that's big that that affects everybody guys thank you so much for joining us talking about ai what you're doing at nature fresh the future what's possible yeah and how you buy ai from dell no i think it's great i think you know nature fresh farms is a great euro you've been a great like a great partner for sure but also this great kind of beacon to show people how it can be done and i think it's just a thank you very much we really enjoyed it excellent well thanks for thanks for bringing the beacon on the show we appreciate it we want to thank you for watching for our guests i'm lisa martin for dave vellante i'm lisa martin i should say you're watching thecube day three of our coverage live from the show floor of dell tech world 2022 stick around we'll be right back with our next guest after a short break [Music] you

>>Oh, welcome to this cube unstoppable domain showcase. I'm John for your host of the cube and showcasing all the great content about web three. And what's around the corner for web. For of course, stoppable domains is one of the big growth stories in the business bread. Can the co-founders here with me have ensembles mains break. Great to see you. Thanks for coming on the showcase. >>So you have a lot of history in the, in the web three, they're calling it net, but it's basically crypto and blockchain. You know, the white paper came out and then, you know how it developed was organically. We saw how that happened. Now, the co-founder was titled domains. You seeing the mainstream, I would say main street scene, super bowl commercials. Okay. You're seeing it everywhere. So it is, it is here. Stadiums are named after cryptos companies. It's here. Hey, it's no longer a fringe. It is reality. You guys are in the middle of it. What's what's going on with the trend. And where does unstoppable fit in? Where do you guys tie in here? >>I mean, I think that what's been happening in general, this whole revolution around cryptocurrencies and then in FTEs and what unstoppable domains is doing, it's all around creating this idea that people can own something that's digital. And this hasn't really been possible before Bitcoin Bitcoin was the first case. You could own money. You don't need a bank. No one else. You can completely control it. No one else can turn you off. Then there was this next phase of the revolution, which is assets beyond just currencies. So, and if T is digital art, what we're working on is like a decentralized identity, like a username for web three and each individual domain name is a is an NFT. But yeah, it's a, it's been a, it's been a, it's been a crazy ride over the past. >>It's fun because you on siliconangle.com, which we founded, we were covering early days of crypto. In fact, our first website, the developer want to be paid in crypto is interesting price of Bitcoin. I won't say that how low it was, but then you saw, you saw the, you know, the ICO way, the token started coming in, you started seeing much more engineering, focused, a lot of white papers coming out, a lot of cool ideas. And then now you got this mainstream of it. So I had to ask you, what are the coolest things you guys are working on because ensemble has a solution that solves a problem today, and that people are facing at the same time. It is part of this new architecture. What problem do you guys solve right now? That's in market that you're seeing the most traction on. >>Yeah. So it's really about, so whenever you inter interact with a blockchain, you wind up having to deal with one of these really, really crazy public keys, public addresses. And they're like anywhere from 20 to 40 characters, long they're random, they're impossible to memorize. And going back to even early days in crypto, I think if people knew that this tech was not going to go mainstream, if you have to copy and paste these things around, if I'm getting to send you like a million dollars, I'm going to copy and paste some random string of numbers and letters. I'm going to have no confirmations about who I'm sending it to. And I'm going to hope that it works out. It's just not practical people. Who've kind of always known there was going to be a solution. And one of the more popular ideas was doing kind of like what DNS did, which is instead of having to deal with these crazy IP addresses this long, random string of numbers to find a website, you have a name, like a keyword, something that's easy to remember, you know, like a hotels.com or something like that. And so what NFT domains are, is basically the same thing, but for blockchain addresses and yeah, it's just, it's just better and easier. There's this joke that everybody, if you want to send me money, you're going to send me a test transaction of, you know, like a dollar first, just to make sure that I get it, call me up and make sure that I get it before you go and send the big amount. I'm just not the way moving, you know, billions of dollars of value is going to work in the future. >>Yeah. And I think one of the things you just pointed out, make it easier. One of these, when you have these new waves, these shifts we saw with the web web pages, more and more web pages were coming on more online users, they call the online population is growing here, the same thing's happening. And the focus is on ease of use, making things simple, to understand and reducing the step it takes to do things, right. This is kind of, kind of what is going on and with the developer community and what a theory has done really well is brought in the developers. So that's the, that's the convergence of all the action. And so when you, so that's where you're at right now, how do you go forward from here? Obviously see this business development deals to do. You guys are partnering a lot. What's the strategy? What are some of the things that you can share about some of your business activity that points to how mainstream it is and where it's going? Okay. >>So I think the, the, the, the way to, the way to think about, and, and T domain name is that it's meant to be like your identity on web three. So it's gonna have a lot of different contexts. It's kind of like your, your Venmo account, where you could send me money to Brad dot crypto can be your decentralized website, where you can check out my content at Brad dot crypto. It can also be my like login kind of like a decentralized Facebook OAuth, where I can log into ADAPs and share information about myself and bring my data along with me. So it's got all of these, all of these different, all these different things that it can do, but where it's starting is inside of crypto wallets and crypto apps, and they are adopting it for this identity, this identity idea. And it's the same identity across all your apps. >>That's the thing that's kinda, that's new here. So, so yeah, that's the, that's the really, that's the really big and profound shift that's happening. And the reason why this is going to be maybe even more important, a lot of, you know, your, your listeners thing is that everyone's going to have a crypto wallet. Every person in the world is going to have a crypto wallet. Every app, every consumer app that you use is going to build one in Twitter, just launched, just built one. Reddit is building one. You're seeing it across all the consumer finance apps. So it's not just the crypto companies that you're thinking of. Every app is going to have a wallet, and it's going to really, it's going to really change the way that we use the internet. >>I think there's a couple of things you pointed. I want to get your reaction to and thoughts more on this constant adapts or decentralized applications or dimension when you call it, this is applications and that take advantage of, of the architecture and then this idea of users owning their own data. And this absolutely reverses the script today. Today, you see Facebook, you see LinkedIn, all these silos, they own the data. The, you are the product here. The users are in control. They have their data, but the apps are being built for it for the paradigm shift here. Right. That's what's happening. Is that right now? >>Totally, totally. And, and so it all starts, I mean, DAP is just this crazy term. It feels like it's this like really foreign, weird thing. All it means is that you sign in with your wallet instead of signing in with a username and password where the data is stored inside of that app, like inside of Facebook. So that's, that's the only real, like core underneath difference to keep in mind signing in with a wallet. But that is like a complete sea change in the way the internet works, because I have this, this key, this private key it's on my phone or my device or whatever. And I'm the only one that has it. So if somebody wanted to hack me, they need to go get access to my device. Two years ago, when Twitter got hacked, Barack Obama and Elon Musk were tweeting the same stuff. >>That's because Twitter had all the data. And so you needed to hack Twitter instead of each individual person, it's a completely different security model. It's, it's way better for users to have that. But if you're thinking from the user perspective what's going to happen is, is that instead of Facebook storing all of my data, and then me being trapped inside of Facebook, I'm going to store it. And I'm gonna move around on the internet, logging in with my web three username, my, my, my NFT domain name. And I'm going to have all my data with me. And then I could use a hundred different Facebooks all in one day. And it would be effortless for me to go and move from one to the other. So the monopoly situation that we exist in as a society is because of the way data storage works. >>So that's the huge point. So let's just, let's double down on that for one more. Second, this is huge point. I want to get your thoughts. I think people don't understand that in the mainstream having that horizontal traversal or, or, or the ability to move around with your identity in this case, your unstoppable domain and your data allows the user to take it from place to place. It's like going to other apps that could be Facebook where the user's in charge. And they're either deciding whether to share their data or not, or are certainly continually their data. And this allows for more of a horizontal scalability for the user, not for a company. >>Yeah. And what's going to happen is, is users are building up their reputation. They're building up their identity in web three. So you have your username and you have your, your profile and you have certain badges of, you know, activities that you've done. And you're building up this reputation. And now apps are looking at that and they're starting to create social networks and other things to provide me services because I, it started with the user as, or the user is starting to collect all this valuable data. And then apps are saying, well, Hey, let me give you a special experience based on that, but the real thing, and this is like, this is like the core mean, this is just like a core capitalist idea. In general, you have more competition, you get a better experience for users. We have not had competition on, on, in web two for decades because these companies have become monopolies. And what web three is really allowing is this wide open competition. And, and that is what, that's the core thing. Like, it's not like, you know, it's going to take time for, for, for web three to get better than web two. You know, it's very, very early days, but the reason why it's going to work is because of the competitive aspect here. Like you can just, it's just so much better for consumers when this happened. >>I would also add to that, first of all, great point, great insight. I would also add that the web presence technology based upon DNS specifically is first of all, it's asking, so it's not foreign characters. It's not union code for, for the geeks out there, but that's limiting to its limits you to be on a site. And so I think the combination of kind of inadequate or antiquated DNS has limitations. So if, and that doesn't help communities, right? So when you're in the communities, you have potentially marketplaces, that could be anywhere. So if you have a ID and just kind of thinking it forward here, but if you have your own data and your own ID, you can jump into a marketplace two-sided marketplace anywhere. And app can provide that if the community is robust, this is kind of where I see the use case going. How do you guys, do you guys agree with that statement and how do you see that ability for the user to take advantage of other competitive or new emerging communities or marketplace? >>So I think it all comes down. So I identity is just this huge problem in web two. And part of the reason why it's very, very hard for new marketplaces and new communities to emerge is because you need all kinds of trust and reputation. And it's very hard to get, to get real information about the users that you're interacting with. If you're, if you're in the web three paradigm, then what happens is, is you can go and check certain things on the blockchain to see if they're true. And you can know that they're true. A hundred percent. You can know that I have used unit swab in the past 30 days and open, see in the past 30 days, you can know for sure that this wallet is mine. The same owner of this wallet also owns this other wallet, owns this certain asset. So all of having the ability to know certain things about a stranger is really what's going to change behavior. >>And one of the things that we're really excited about is being able to prove information about yourself without sharing it. So I can tell you, Hey, I'm a unique person. I'm an American, I'm not an American, but I don't have to tell you who I am. And, and you can still know that it's true. And, and that is that concept is going to be what enables, what you're talking about. I'm going to be able to show up in some new community that was created two hours ago, and we can all trust each other that a certain set of facts are true. And that's possible because of >>Exchange and exchange value with smart contracts and other no middlemen involved activities, which is the promise of the new decentralized web. All right. So let me ask you a question on that, because I think this is key. The anonymous point is huge. If you look at any kind of abstraction layers or any evolution in technology over the years, it's always been about cleaning up the mess or the, or extending capabilities of something that was inadequate. We mentioned DNS. Now you got this, there's a lot of problems with web two, 2.0, social bots. You mentioned bots, bots are anonymous and they don't have a lot of time in market. So it's easy to start bots and everyone who does either scraping bots, everyone knows this. What you just pointed out was an ops environment that was user choice, but has all the data that could be verified. So it's almost like a blue check mark on Twitter without your name, >>Kind of, it's good. It's going to be hundreds of check marks, but exactly, because there's so many different things that you're going to want to be, you're going to want to communicate to strangers, but that's exactly the right. That's exactly the right mental model. It's going to be these check marks for all kinds of different contexts. And that's, what's going to enable people to trust that they're, you know, you're talking to a real person or you're talking to the type of person you thought you were talking to, et cetera. But yeah, it's, it's, you know, I, I think that the issues that we have with bots today are because a web tool has failed at solving identity. I think Facebook at one point was deleting half a billion fake accounts per quarter. Something like the entire number of user profiles. They were deleting per you know, per year. So it's just a total. >>They spring up like mushrooms. They just pop up the thing. This is the problem. I mean, the data that you acquire in new siloed platforms is used by them, the company. So you don't own the data. So you become the product as the cliche goes. But what you're saying is if you have an identity and you pop around to multiple sites, you also have your digital footprints and your exhaust that you own. Okay. That's time. That's reputation data. I mean, you can cut it any way you want, but the point is, it's your stuff over time, that's yours and that's immutable. It's on the blockchain. You can store it and make that permanent and add to it. Exactly. That's, that's a time-based thing versus today, bots that are spreading misinformation can, can get popped up when they get killed. They just start another one. So time actually is a metric for quality here. >>Absolutely. And people already use it in the crypto world to say like, Hey, this wallet was created greater than two years ago. This wallet has had, you know, head has had transactions for at least three or four years. Like this is probably a real, you know, this is probably a legit legitimate user and anybody can look that up. I mean, we could go look it up together right now on, on ether scan. It would take, you know, a minute. >>Yeah. It's awesome. Yeah. I'm a big fan. I can tell, I love this product. I think you guys are gonna do really well. Congratulations. I'm a big fan. I think this is needed. What are some of the deals you've done? blockchain.com has won an opera. Can you take us through those deals and why they're working with you? We'll start with blockchain.com. >>Yeah. So the whole thing here is that this identity standard for web three apps need to choose to support it. So we spent several years as a company working to get as many crypto wallets and browsers and crypto exchanges to support this, to support this identity standard. Some of the, some of the, the, the largest, and probably, you know, most, most popular companies to have done. This are blockchain.com. For example, blockchain.com, one of the largest crypto wallets in the world. And you can use your domain names instead of crypto addresses. And, and, and this is, this is, this is super cool because blockchain.com in particular focuses on onboarding new users. So they're very focused on how we're going to get the next 4 billion internet users to use this tech. And they said, you know, usernames are going to be essential. Like, how can we onboard this next several billion people? If we have to explain to them about all these crazy addresses, and it's not just one, like we want to give you 10 40 character addresses for all these different contexts. Like, it's just, it's just, it's just no way people are gonna be able to do that without, without having a username. So that's why we're really excited about, about what blockchain that comes through. And they, they, they want to train users that this is the way you should use it. >>Yeah. And certainly no one wants to remember. I remember writing down all my writing. I, I'm not, I was never a big wallet fan cause all the hacks, I used to write it down and store it in my safe. But if the house burns down or I, I kick the can I'm, who's going to find it. Right? So again, these are all important things, your key storing it, securing it, super important. Talk about opera. And that's an interesting partnership because it's got a browser and people know what it is, what are they doing? Different almost imagine they're innovating around the identity and what people's experiences with, what they touch. >>So this is, this is one of those things. That's a little bit easier. And I strongly encourage everybody to go and try dApps after this. Cause this is going to be one of those concepts to be a little easier. If you, if you try it, then if you hear about it, but the concept of a wallet and a browser are kind of merging. So it makes sense to have a wallet inside of your browser. Because when you go to a website, the website is going to want you to sign in with your wallet. So having that be in one app is quite convenient for users. And so opera was one of the trailblazers, a traditional browser that added a crypto wallet so that you can store money in there. And then also added support for domain names, for payments and for websites. So you can type in Brad dot crypto and you can send me money or you can type in Brad dot crypto into the browser and you can check out my website. I've got a little NFT gallery. You can see my collection up there right now. So that's the, that's the idea is that browsers have this kind of super power in a web three. And what I think is going to happen opera and brave have been kind of the trailblazers here. But I think is going to happen is that these traditional browsers are going to wake up and they're going to see that integrating a wallet is critical for them to be able to provide services to consumers. >>I mean, it is an app. I mean, why not make it a D app as well? Because why wouldn't I want to just send you crypto, like Venmo, you mentioned earlier, which people can understand that concept. Ben, let me make my cash. Same concept here, but built in to the browser, which is not a browser anymore. It's a, a reader, a D app reader, basically with a wallet. All right. So, so what does this mean for you guys in the marketplace? You've got opera pushing the envelope on browsing, changing the experience, enabling the applications to be discovered and navigated and consumed. You got blockchain.com, blockchain.com with the wallets and being embedded there. Good distribution. How, what, who are you looking for for partners? How do people partner? Let's just say the cube wants to do NFTs and we want to have a login for our communities, which are all open. How do we partner with you? Or do we have to wait? Or is there a, I mean, take us through the partnership strategy. How do we, how do people engage with unstoppable Dwayne's >>Yeah, so, I mean, I think that if you're, you know, if you're a wallet or a crypto exchange, it's super easy, we would love to have you support being able to send money using domains. We also have all sorts of different kind of marketing activities we can do together. We can give out free stuff to, to your communities. We have a bunch of education that we do. We're really trying to be this onboarding point to web three. So there's, I think a lot of, a lot of cool stuff we can do together on the commercial side and on the, the, the marketing side. And then the other category that we didn't talk about was dabs. And we now have this login with unstoppable domains, which you kind of alluded to there. And so you can log in with your domain name and then you can give the app permission to get certain information about you or proof of information about you, not the actual information, if you don't want to share it because it's your choice and you're in control. And so that would be, that would be another thing. Like if you all launch a DAP, we should absolutely have log-in with unstoppable. >>Yeah. There's so much headroom here. You've got a short-term solution with exchange. Get that distribution. I get that that's early days of the foundation, push the distribution, get you guys everywhere. But the real success comes in for the login. I mean, the sign-on single sign-on concept. I think that's going to be powerful, great stuff. Okay. Future, tell us something we don't know about ensemble domains that people might be interested in. >>I think it's really, I think the thing that you're going to hear about a lot from us in the future is going to be around this idea of identity, of being able to prove that you're a human and be able to tell apps that and apps are going to give you all kinds of special access and rewards and all kinds of other things, because, because you gave them that information. So that's the that's, that's probably, that's the hint I'm going to drop. >>Yeah. It's interesting. Brad, you bring trust, you bring quality verified data to intelligence, software, and machine learning, AI and access to distributed communities and distributed applications. Interesting to see what the software does, what that, cause it traditionally didn't have that before. I mean just in mindblowing, I mean, it's pretty crazy great stuff, Brad. Thanks for coming on. Thanks for sharing the insight. Co-founder unstoppable domains, Brad camp. Thanks for stopping by the cubes. Showcase with unstoppable domains.

>> From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> In our 2020 predictions post, we said that organizations would begin to operationalize their digital transformation experiments and POCs. We also said that based on spending data that cybersecurity companies like CrowdStrike and Okta were poised to rise above the rest in 2020, and we even said the S&P 500 would surpass 3,700 this year. Little did we know that we'd have a pandemic that would make these predictions a virtual lock, and, of course, COVID did blow us out of the water in some other areas, like our prediction that IT spending would increase plus 4% in 2020, when in reality, we have a dropping by 4%. We made a number of other calls that did pretty well, but I'll let you review last year's predictions at your leisure to see how we did. Hello, everyone. This is Dave Vellante and welcome to this week's Wikibon CUBE Insights powered by ETR. Erik Bradley of ETR is joining me again for this Breaking Analysis, and we're going to lay out our top picks for 2021. Erik, great to see you. Welcome back. Happy to have you on theCUBE, my friend. >> Always great to see you too, Dave. I'm excited about these picks this year. >> Well, let's get right into it. Let's bring up the first prediction here. Tech spending will rebound in 2021. We expect a 4% midpoint increase next year in spending. Erik, there are a number of factors that really support this prediction, which of course is based on ETR's most recent survey work, and we've listed a number of them here in this slide. I wonder if we can talk about that a little bit, the pace of the vaccine rollout. I've called this a forced march to COVID, but I can see people doubling down on things that are working. Productivity improvements are going to go back into the business. People are going to come back to the headquarters and that maybe is going to spur infrastructure on some pent-up demand, and work from home, we're going to talk about that. What are your thoughts on this prediction? >> Well, first of all, you weren't wrong last year. You were just, (laughs) you were just delayed. Just delayed a little bit, that's all. No, very much so. Early on, just three months ago, we were not seeing this optimism. The most recent survey, however, is capturing 4%. I truly believe that still might be a little bit mild. I think it can go even higher, and that's going to be driven by some of the things you've said about. This is a year where a lot of spending was paused on machine learning, on automation, on some of these projects that had to be stopped because of what we all went through. Right now, that is not a nice to have, it's a must have, and that spending is going quickly. There's a rapid pace on that spending, so I do think that's going to push it and, of course, security. We're going to get to this later on so I don't want to bury the lede, but with what's happening right now, every CISO I speak to is not panicked, but they are concerned and there will definitely be increased security spending that might push this 4% even higher. >> Yeah, and as we've reported as well, the survey data shows that there's less freezing of IT, there are fewer layoffs, there's more hiring, we're accelerating IT deployments, so that, I think, 34% last survey, 34% of organizations are accelerating IT deployments over the next three months, so that's great news. >> And also your point too about hiring. I was remiss in not bringing that up because we had layoffs and we had freezes on hiring. Both of that is stopping. As you know, as more head count comes in, whether that be from home or whether that be in your headquarters, both of those require support and require spending. >> All right, let's bring up the next prediction. Remote worker trends are going to become fossilized, settling in at an average of 34% by year-end 2021. Now, I love this chart, you guys. It's been amazingly consistent to me, Erik. We're showing data here from ETR's latest COVID survey. So it shows that prior to the pandemic, about 15 to 16% of employees on average worked remotely. That jumped to where we are today and well into the 70s, and we're going to stay close to that, according to the ETR data, in the first half of 2021, but by the end of the year, it's going to settle in at around 34%. Erik, that's double the pre-pandemic numbers and that's been consistent in your surveys over the past six month, and even within the sub-samples. >> Yeah, super surprised by the consistency, Dave. You're right about that. We were expecting the most recent data to kind of come down, right? We see the vaccines being rolled out. We kind of thought that that number would shift, but it hasn't, it has been dead consistent, and that's just from the data perspective. What we're hearing from the interviews and the feedback is that's not going to change, it really isn't, and there's a main reason for that. Productivity is up, and we'll talk about that in a second, but if you have productivity up and you have employees happy, they're not commuting, they're working more, they're working effectively, there is no reason to rush. And now imagine if you're a company that's trying to hire the best talent and attract the best talent but you're also the only company telling them where they have to live. I mean, good luck with that, right? So even if a few of them decide to make this permanent, that's something where you're going to really have to follow suit to attract talent. >> Yeah, so let's talk about that. Productivity leads us to our next prediction. We can bring that up. Number three is productivity increases are going to lead organizations to double down on the successes of 2020 and productivity apps are going to benefit. Now, of course, I'm always careful to cautious to interpret when you ask somebody by how much did productivity increase. It's a very hard thing to estimate depending on how you measure it. Is it revenue per employee? Is it profit? But nonetheless, the vast majority of people that we talk to are seeing productivity is going up. The productivity apps are really the winners here. Who do you see, Erik, as really benefiting from this trend? This year we saw Zoom, Teams, even Webex benefit, but how do you see this playing out in 2021? >> Well, first of all, the real beneficiaries are the companies themselves because they are getting more productivity, and our data is not only showing more productivity, but that's continuing to increase over time, so that's number one. But you're 100% right that the reason that's happening is because of the support of the applications and what would have been put in place. Now, what we do expect to see here, early on it was a rising tide lifted all boats, even Citrix got pulled up, but over time you realize Citrix is really just about legacy applications. Maybe that's not really the virtualization platform we need or maybe we just don't want to go that route at all. So the ones that we think are going to win longer term are part of this paradigm shift. The easiest one to put out as example is DocuSign. Nobody is going to travel and sit in an office to sign a paper ever again. It's not happening. I don't care if you go back to the office or you go back to headquarters. This is a paradigm shift that is not temporary. It is permanent. Another one that we're seeing is Smartsheet. Early on it started in. I was a little concerned about it 'cause it was a shadow IT type of a company where it was just spreading and spreading and spreading. It's turned out that this, the data on Smartsheet is continuing to be strong. It's an effective tool for project management when you're remotely working, so that's another one I don't see changing anytime. The other one I would call out would be Twilio. Slightly different, yes. It's more about the customer experience, but when you look at how many brick and mortar or how many in-person transactions have moved online and will stay there, companies like Twilio that support that customer experience, I'll throw out a Qualtrics out there as well, not a name we hear about a lot, but that customer experience software is a name that needs to be watched going forward. >> What do you think's going to happen to Zoom and Teams? Certainly Zoom just escalated this year, a huge ascendancy, and Teams I look at a little differently 'cause it's not just video conferencing, and both have done really, really well. How do you interpret the data that you're seeing there? >> There's no way around it, our data is decelerating quickly, really quickly. We were kind of bullish when Zoom first came out on the IPO prospects. It did very well. Obviously what happened in this remote shift turned them into an absolute overnight huge success. I don't see that continuing going forward, and there's a reason. What we're seeing and hearing from our feedback interviews is that now that people recognize this isn't temporary and they're not scrambling and they need to set up for permanency, they're going to consolidate their spend. They don't need to have Teams and Zoom. It's not necessary. They will consolidate where they can. There's always going to be the players that are going to choose Slack and Zoom 'cause they don't want to be on Microsoft architecture. That's fine, but you and I both know that the majority of large enterprises have Microsoft already. It's bundled in in pricing. I just don't see it happening. There's going to be M&A out there, which we can talk about again soon, so maybe Zoom, just like Slack, gets to a point where somebody thinks it's worthwhile, but there's a lot of other video conferencing out there. They're trying to push their telephony. They're trying to push their mobile solutions. There's a lot of companies out there doing it, so we'll see, but the current market cap does not seem to make sense in a permanent remote work situation. >> I think I'm inferring Teams is a little different because it's Microsoft. They've got this huge software estate they can leverage. They can bundle. Now, it's going to be interesting to see how and if Zoom can then expand its TAM, use its recent largesse to really enter potentially new markets. >> It will be, but listen, just the other day there was another headline that one of Zoom's executives out in China was actually blocking content as per directed by the Chinese government. Those are the kind of headlines that just really just get a little bit difficult when you're running a true enterprise size. Zoom is wonderful in the consumer space, but what I do is I research enterprise technology, and it's going to be really, really difficult to make inroads there with Microsoft. >> Yep. I agree. Okay, let's bring up number four, prediction number four. Permanent shifts in CISO strategies lead to measurable share shifts in network security. So the remote work sort of hyper-pivot, we'll call it, it's definitely exposed us. We've seen recent breaches that underscore the need for change. They've been well-publicized. We've talked a lot about identity access management, cloud security, endpoint security, and so as a result, we've seen the upstarts, and just a couple that we called, CrowdStrike, Okta, Zscaler has really benefited and we expect them to continue to show consistent growth, some well over 50% revenue growth. Erik, you really follow this space closely. You've been focused on microsegmentation and other, some of the big players. What are your thoughts here? >> Yeah, first of all, security, number one in spending overall when we started looking and asking people what their priority is going to be. That's not changing, and that was before the SolarWinds breach. I just had a great interview today with a CISO of a global hospitality enterprise to really talk about the implications of this. It is real. Him and his peers are not panicking but pretty close, is the way he put it, so there is spend happening. So first of all, to your point, continued on Okta, continued on identity access. See no reason why that changes. CrowdStrike, continue. What this is going to do is bring in some new areas, like we just mentioned, in network segmentation. Illumio is a pure play in that name that doesn't have a lot of citations, but I have watched over the last week their net spending score go from about 30 to 60%, so I am watching in real time, as this data comes in in the later part of our survey, that it's really happening Forescout is another one that's in there. We're seeing some of the zero trust names really picking up in the last week. Now, to talk about some of the more established names, yeah, Cisco plays in this space and we can talk about Cisco and what they're doing in security forever. They're really reinventing themselves and doing a great job. Palo Alto was in this space as well, but I do believe that network and microsegmentation is going to be something that's going to continue. The other one I'm going to throw out that I'm hearing a lot about lately is user behavior analytics. People need to be able to watch the trends, compare them to past trends, and catch something sooner. Varonis is a name in that space that we're seeing get a lot of adoptions right now. It's early trend, but based on our data, Varonis is a name to watch in that area as well. >> Yeah, and you mentioned Cisco transitioning, reinventing themselves toward a SaaS player. Their subscription, Cisco's security business is a real bright spot for them. Palo Alto, every time I sit in on a VENN, which is ETR's proprietary roundtable, the CISOs, they love Palo Alto. They want to work, many of them, anyway, want to work with Palo Alto. They see them as a thought leader. They seem to be getting their cloud act together. Fortinet has been doing a pretty good job there and especially for mid-market. So we're going to see this equilibrium, best of breed versus the big portfolio companies, and I think 2021 sets up as a really interesting battle for those guys with momentum and those guys with big portfolios. >> I completely agree and you nailed it again. Palo Alto has this perception that they're really thought leaders in the space and people want to work with them, but let's not rule Cisco out. They have a much, much bigger market cap. They are really good at acquisitions. In the past, they maybe didn't integrate them as well, but it seems like they're getting their act together on that. And they're pushing now what they call SecureX, which is sort of like their own full-on platform in the cloud, and they're starting to market that, I'm starting to hear more about it, and I do think Cisco is really changing people's perception of them. We shall see going forward because in the last year, you're 100% right, Palo Alto definitely got a little bit more of the sentiment, of positive sentiment. Now, let's also realize, and we'll talk about this again in a bit, there's a lot of players out there. There will probably be continued consolidation in the security space, that we'll see what happens, but it's an area where spending is increasing, there is a lot of vendors out there to play with, and I do believe we'll see consolidation in that space. >> Yes. No question. A highly fragmented business. A lack of skills is a real challenge. Automation is a big watch word and so I would expect, which brings us, Erik, to prediction number five. Can be hard to do prediction posts without talking about M&A. We see the trend toward increased tech spending driving more IPOs, SPACs and M&A. We've seen some pretty amazing liquidity events this year. Snowflake, obviously a big one. Airbnb, DoorDash, outside of our enterprise tech but still notable. Palantir, JFrog, number of others. UiPath just filed confidentially and their CEO said, "Over the next 12 to 18 months, I would think Automation Anywhere is going to follow suit at some point." Hashicorp was a company we called out in our 2020 predictions as one to watch along with Snowflake and some others, and, Erik, we've seen some real shifts in observability. The ELK Stack gaining prominence with Elastic, ChaosSearch just raised 40 million, and everybody's going after 5G. Lots of M&A opportunities. What are your thoughts? >> I think if we're going to make this a prediction show, I'm going to say that was a great year, but we're going to even have a better year next year. There is a lot of cash on the balance sheet. There are low interest rates. There is a lot of spending momentum in enterprise IT. The three of those set up for a perfect storm of more liquidity events, whether it be continued IPOs, whether it could be M&A, I do expect that to continue. You mentioned a lot of the names. I think you're 100% right. Another one I would throw out there in that observability space, is it's Grafana along with the ELK Stack is really making changes to some of the pure plays in that area. I've been pretty vocal about how I thought Splunk was having some problems. They've already made three acquisitions. They are trying really hard to get back up and keep that growth trajectory and be the great company they always have been, so I think the observability area is certainly one. We have a lot of names in that space that could be taken out. The other one that wasn't mentioned, however, that I'd like to mention is more in the CDN area. Akamai being the grandfather there, and we'll get into it a little bit too, but CloudFlare has a huge market cap, Fastly running a little bit behind that, and then there's Limelight, and there's a few startups in that space and the CDN is really changing. It's not about content delivery as much as it is about edge compute these days, and they would be a real easy takeout for one of these large market cap names that need to get into that spot. >> That's a great call. All right, let's bring up number six, and this is one that's near and dear to my heart. It's more of a longer-term prediction and that prediction is in the 2020s, 75% of large organizations are going to re-architect their big data platforms, and the premise here is we're seeing a rapid shift to cloud database and cross-cloud data sharing and automated governance. And the prediction is that because big data platforms are fundamentally flawed and are not going to be corrected by incremental improvements in data lakes and data warehouses and data hubs, we're going to see a shift toward a domain-centric ownership of the data pipeline where data teams are going to be organized around data product or data service builders and embedded into lines of business. And in this scenario, the technology details and complexity will become abstracted. You've got hyper-specialized data teams today. They serve multiple business owners. There's no domain context. Different data agendas. Those, we think, are going to be subsumed within the business lines, and in the future, the primary metric is going to shift from the cost and the quality of the big data platform outputs to the time it takes to go from idea to revenue generation, and this change is going to take four to five years to coalesce, but it's going to begin in earnest in 2021. Erik, anything you'd add to this? >> I'm going to let you kind of own that one 'cause I completely agree, and for all the listeners out there, that was Dave's original thought and I think it's fantastic and I want to get behind it. One of the things I will say to support that is big data analytics, which is what people are calling it because they got over the hype of machine learning, they're sick of vendors saying machine learning, and I'm hearing more and more people just talk about it as we need big data analytics, we need 'em at the edge, we need 'em faster, we need 'em in real time. That's happening, and what we're seeing more is this is happening with vendor-agnostic tools. This isn't just AWS-aligned. This isn't just GCP-aligned or Azure-aligned. The winners are the Snowflakes. The winners are the Databricks. The winners are the ones that are allowing this interoperability, the portability, which fully supports what you're saying. And then the only other comment I would make, which I really like about your prediction, is about the lines of business owning it 'cause I think this is even bigger. Right now, we track IT spending through the CIO, through the CTO, through IT in general. IT spending is actually becoming more diversified. IT spending is coming under the purview of marketing, it's coming under the purview of sales, so we're seeing more and more IT spending, but it's happening with the business user or the business lines and obviously data first, so I think you're 100% right. >> Yeah, and if you think about it, we've contextualized our operational systems, whether it's the CRM or the supply chain, the logistics, the business lines own their respective data. It's not true for the analytics systems, and we talked about Snowflake and Databricks. I actually see these two companies who were sort of birds of a feather in the early days together, applying Databricks machine learning on top of Snowflake, I actually see them going in diverging places. I see Databricks trying to improve on the data lake. I see Snowflake trying to reinvent the concept of data warehouse to this global mesh, and it's going to be really interesting to see how that shakes out. The data behind Snowflake, obviously very, very exciting. >> Yeah, it's just, real quickly to add on that if we have time, Dave. >> Yeah, sure. >> We all know the valuation of Snowflake, one of the most incredible IPOs I've seen in a long time. The data still supports it. It still supports that growth. Unfortunately for Databricks, their IPO has been a little bit more volatile. If you look at their stock chart every time they report, it's got a little bit of a roller coaster ride going on, and our most recent data for Databricks is actually decelerating, so again, I'm going to use the caveat that we only have about 950 survey responses in. We'll probably get that up to 1,300 or so, so it's not done yet, but right now we are putting Databricks into a category where we're seeing it decelerate a little bit, which is surprising for a company that's just right out of the gate. >> Well, it's interesting because I do see Databricks as more incremental on data lakes and I see Snowflake as more transformative, so at least from a vision standpoint, we'll see if they can execute on that. All right, number seven, let's bring up number seven. This is talking about the cloud, hybrid cloud, multi-cloud. The battle to define hybrid and multi-cloud is going to escalate in 2021. It's already started and it's going to create bifurcated CIO strategies. And, Erik, spending data clearly shows that cloud is continuing its steady margin share gains relative to on-prem, but the definitions of the cloud, they're shifting. Just a couple of years ago, AWS, they never talk about hybrid, just like they don't talk about multi-cloud today, yet AWS continues now to push into on-prem. They treat on-prem as just another node at the edge and they continue to win in the marketplace despite their slower growth rates. Still, they're so large now. 45 billion or so this year. The data is mixed. This ETR data shows that just under 50% of buyers are consolidating workloads, and then a similar, in the cloud workloads, and a similar percentage of customers are spreading evenly across clouds, so really interesting dynamic there. Erik, how do you see it shaking out? >> Yeah, the data is interesting here, and I would actually state that overall spend on the cloud is actually flat from last year, so we're not seeing a huge increase in spend, and coupled with that, we're seeing that the overall market share, which means the amount of responses within our survey, is increasing, certainly increasing. So cloud usage is increasing, but it's happening over an even spectrum. There's no clear winner of that market share increase. So they really, according to our data, the multi-cloud approach is happening and not one particular winner over another. That's just from the data perspective that various do point on AWS. Let's be honest, when they first started, they wanted all the data. They just want to take it from on-prem, put it in their data center. They wanted all of it. They never were interested in actually having interoperability. Then you look at an approach like Google. Google was always about the technology, but not necessarily about the enterprise customer. They come out with Anthos which is allowing you to have interoperability in more cloud. They're not nearly as big, but their growth rate is much higher. Law of numbers, of course. But it really is interesting to see how these cloud players are going to approach this because multi-cloud is happening whether they like it or not. >> Well, I'm glad you brought up multi-cloud in a context of what the data's showing 'cause I would agree we're, and particularly two areas that I would call out in ETR data, VMware Cloud on AWS as well as VM Cloud Foundation are showing real momentum and also OpenStack from Red Hat is showing real progress here and they're making moves. They're putting great solutions inside of AWS, doing some stuff on bare metal, and it's interesting to see. VMware, basically it's the VMware stack. They want to put that everywhere. Whereas Red Hat, similarly, but Red Hat has the developer angle. They're trying to infuse Red Hat in throughout everybody's stack, and so I think Red Hat is going to be really interesting to, especially to the extent that IBM keeps them, sort of lets them do their own thing and doesn't kind of pollute them. So, so far so good there. >> Yeah, I agree with that. I think you brought up the good point about it being developer-friendly. It's a real option as people start kicking a little bit more of new, different developer ways and containers are growing, growing more. They're not testing anymore, but they're real workloads. It is a stack that you could really use. Now, what I would say to caveat that though is I'm not seeing any net new business go to IBM Red Hat. If you were already aligned with that, then yes, you got to love these new tools they're giving you to play with, but I don't see anyone moving to them that wasn't already net new there and I would say the same thing with VMware. Listen, they have a great entrenched base. The longer they can kick that can down the road, that's fantastic, but I don't see net new customers coming onto VMware because of their alignment with AWS. >> Great, thank you for that. That's a good nuance. Number eight, cloud, containers, AI and ML and automation are going to lead 2021 spending velocity, so really is those are the kind of the big four, cloud, containers, AI, automation, And, Erik, this next one's a bit nuanced and it supports our first prediction of a rebound in tech spending next year. We're seeing cloud, containers, AI and automation, in the form of RPA especially, as the areas with the highest net scores or spending momentum, but we put an asterisk around the cloud because you can see in this inserted graphic, which again is preliminary 'cause the survey's still out in the field and it's just a little tidbit here, but cloud is not only above that 40% line of net score, but it has one of the higher sector market shares. Now, as you said, earlier you made a comment that you're not necessarily seeing the kind of growth that you saw before, but it's from a very, very large base. Virtually every sector in the ETR dataset with the exception of outsourcing and IT consulting is seeing meaningful upward spending momentum, and even those two, we're seeing some positive signs. So again, with what we talked about before, with the freezing of the IT projects starting to thaw, things are looking much, much better for 2021. >> I'd agree with that. I'm going to make two quick comments on that, one on the machine learning automation. Without a doubt, that's where we're seeing a lot of the increase right now, and I've had a multiple number of people reach out or in my interviews say to me, "This is very simple. These projects were slated to happen in 2020 and they got paused. It's as simple as that. The business needs to have more machine learning, big data analytics, and it needs to have more automation. This has just been paused and now it's coming back and it's coming back rapidly." Another comment, I'm actually going to post an article on LinkedIn as soon as we're done here. I did an interview with the lead technology director, automation director from Disney, and this guy obviously has a big budget and he was basically saying UiPath and Automation Anywhere dominate RPA, and that on top of it, the COVID crisis greatly accelerated automation, greatly accelerated it because it had to happen, we needed to find a way to get rid of these mundane tasks, we had to put them into real workloads. And another aspect you don't think about, a lot of times with automation, there's people, employees that really have friction. They don't want to adopt it. That went away. So COVID really pushed automation, so we're going to see that happening in machine learning and automation without a doubt. And now for a fun prediction real quick. You brought up the IT outsourcing and consulting. This might be a little bit more out there, the dark horse, but based on our data and what we're seeing and the COVID information about, you said about new projects being unwrapped, new hiring happening, we really do believe that this might be the bottom on IT outsourcing and consulting. >> Great, thank you for that, and then that brings us to number nine here. The automation mandate is accelerating and it will continue to accelerate in 2021. Now, you may say, "Okay, well, this is a lay-up," but not necessarily. UiPath and Automation Anywhere go public and Microsoft remains a threat. Look, UiPath, I've said UiPath and Automation Anywhere, if they were ready to go public, they probably would have already this year, so I think they're still trying to get their proverbial act together, so this is not necessarily a lay-up for them from an operational standpoint. They probably got some things to still clean up, but I think they're going to really try to go for it. If the markets stay positive and tech spending continues to go forward, I think we can see that. And I would say this, automation is going mainstream. The benefits of taking simple RPA tools to automate mundane tasks with software bots, it's both awakened organizations to the possibilities of automation, and combined with COVID, it's caused them to get serious about automation. And we think 2021, we're going to see organizations go beyond implementing point tools, they're going to use the pandemic to restructure their entire business. Erik, how do you see it, and what are the big players like Microsoft that have entered the market? What kind of impact do you see them having? >> Yeah, completely agree with you. This is a year where we go from small workloads into real deployment, and those two are the leader. In our data, UiPath by far the clear leader. We are seeing a lot of adoptions on Automation Anywhere, so they're getting some market sentiment. People are realizing, starting to actually adopt them. And by far, the number one is Microsoft Power Automate. Now, again, we have to be careful because we know Microsoft is entrenched everywhere. We know that they are good at bundling, so if I'm in charge of automation for my enterprise and I'm already a Microsoft customer, I'm going to use it. That doesn't mean it's the best tool to use for the right job. From what I've heard from people, each of these have a certain area where they are better. Some can get more in depth and do heavier lifting. Some are better at doing a lot of projects at once but not in depth, so we're going to see this play out. Right now, according to our data, UiPath is still number one, Automation Anywhere is number two, and Microsoft just by default of being entrenched in all of these enterprises has a lot of market share or mind share. >> And I also want to do a shout out to, or a call out, not really a shout out, but a call out to Pegasystems. We put them in the RPA category. They're covered in the ETR taxonomy. I don't consider them an RPA vendor. They're a business process vendor. They've been around for a long, long time. They've had a great year, done very, very well. The stock has done well. Their spending momentum, the early signs in the latest survey are just becoming, starting to moderate a little bit, but I like what they've done. They're not trying to take UiPath and Automation Anywhere head-on, and so I think there's some possibilities there. You've also got IBM who went to the market, SAP, Infor, and everybody's going to hop on the bandwagon here who's a software player. >> I completely agree, but I do think there's a very strong line in the sand between RPA and business process. I don't know if they're going to be able to make that transition. Now, business process also tends to be extremely costly. RPA came into this with trying to be, prove their ROI, trying to say, "Yeah, we're going to cost a little bit of money, but we're going to make it back." Business process has always been, at least the legacies, the ones you're mentioning, the Pega, the IBMs, really expensive. So again, I'm going to allude to that article I'm about to post. This particular person who's a lead tech automation for a very large company said, "Not only are UiPath and AA dominating RPA, but they're likely going to evolve to take over the business process space as well." So if they are proving what they can do, he's saying there's no real reason they can't turn around and take what Appian's doing, what IBM's doing and what Pega's doing. That's just one man's opinion. Our data is not actually tracking it in that space, so we can't back that, but I did think it was an interesting comment for and an interesting opportunity for UiPath and Automation Anywhere. >> Yeah, it's always great to hear directly from the mouths of the practitioners. All right, brings us to number 10 here. 5G rollouts are going to push new edge IoT workloads and necessitate new system architectures. AI and real-time inferencing, we think, require new thinking, particularly around processor and system design, and the focus is increasingly going to be on efficiency and at much, much lower costs versus what we've known for decades as general purpose workloads accommodating a lot of different use cases. You're seeing alternative processors like Nvidia, certainly the ARM acquisition. You've got companies hitting the market like Fungible with DPAs, and they're dominating these new workloads in the coming decade, we think, and they continue to demonstrate superior price performance metrics. And over the next five years they're going to find their way, we think, into mainstream enterprise workloads and put continued pressure on Intel general purpose microprocessors. Erik, look, we've seen cloud players. They're diversifying their processor suppliers. They're developing their own in-house silicon. This is a multi-year trend that's going to show meaningful progress next year, certainly if you measure it in terms of innovations, announcements and new use cases and funding and M&A activity. Your thoughts? >> Yeah, there's a lot there and I think you're right. It's a big trend that's going to have a wide implication, but right now, it's there's no doubt that the supply and demand is out of whack. You and I might be the only people around who still remember the great chip famine in 1999, but it seems to be happening again and some of that is due to just overwhelming demand, like you mentioned. Things like IoT. Things like 5G. Just the increased power of handheld devices. The remote from work home. All of this is creating a perfect storm, but it also has to do with some of the chip makers themselves kind of misfired, and you probably know the space better than me, so I'll leave you for that on that one. But I also want to talk a little bit, just another aspect of this 5G rollout, in my opinion, is we have to get closer to the edge, we have to get closer to the end consumer, and I do believe the CDN players have an area to play in this. And maybe we can leave that as there and we could do this some other time, but I do believe the CDN players are no longer about content delivery and they're really about edge compute. So as we see IoT and 5G roll out, it's going to have huge implications on the chip supply. No doubt. It's also could have really huge implications for the CDN network. >> All right, there you have it, folks. Erik, it's great working with you. It's been awesome this year. I hope we can do more in 2021. Really been a pleasure. >> Always. Have a great holiday, everybody. Stay safe. >> Yeah, you too. Okay, so look, that's our prediction for 2021 and the coming decade. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast. You'll find it. We publish each week on wikibon.com and siliconangle.com, and you got to check out etr.plus. It's where all the survey action is. Definitely subscribe to their services if you haven't already. You can DM me @dvellante or email me at david.vellante@siliconangle.com. This is Dave Vellante for Erik Bradley for theCUBE Insights powered by ETR. Thanks for watching, everyone. Be well and we'll see you next time. (relaxing music)

(upbeat music) >> From the Cube studios in Palo Alto in Boston connecting with thought leaders all around the world. This is the CUBE Conversation. >> Hey everybody this is Dave Vellante and welcome to the special CUBE Conversation. I'm really excited to have Keith Bradley here he's the Vice President of IT at Nature Fresh Farms. Keith good to see you. >> Hey, good to see you too there Dave. >> All right, first of all I got to thank you for sending me these awesome veggies. I got these wonderful peppers. I got red, orange. I got the yellow. I got to tell you Keith these tomatoes almost didn't make it. It's my last one on the vine. >> (Laughs) >> These guys are like candy. It's amazing. >> Yap. They are the tasty thing. >> Wonderful. >> You know what, I'll probably just join you right here now too. I'll have one right here right now and I'll join you right now. >> My kids love these but I'm not bringing them home. And then I got these other grape tomatoes and then I've got these mini pepper poppers that are so sweet. You know which one I'm talking about here. And then we've got the tomatoes on the vine. I mean, it's just unbelievable that you guys are able to do this in a greenhouse. Big cukes, little cukes. Wow. Thank you so much for sending these. Delicious. Really appreciate it. >> Yeah. Well thank you for having them. It's a great little tree and it's something that I know you're going to enjoy. And I love for everybody to have it and there's not a person I haven't seen that hasn't enjoyed our tomatoes and peppers. >> Now tell me more about Nature Fresh Farms. Let's talk about your business I want to spend some time on that. We've got IoT, we got a data lifecycle. All kinds of cool stuff, scanners. Paint a picture for us. >> I like to even go... If you don't mind. I like to even go back to where our roots actually came from. So Peter Quiring, our owner actually was a builder by nature and he was actually back in the year 2000 really wanted to get into the greenhouse because he was a manufacturer. And he built our phase one facility back in 2000 under the concept that he said, "there's computers out there." And Peter will be the first one to say, "I don't know how to use them, "but I know that it can do a lot for us." So even back in 2000, we were starting to experiment with using the computers back then to control the greenhouse, to do much of the functionality. Then he bought it under the concept as our sister company, South Essex Fabricating that he would sell the greenhouse turnkey to somebody else. Well, talking to him and I've been around since about phase two. He basically said, "when I built phase three, "which is our first 32 acre range, I realized that is actually in the pepper business now," and he realized he was a grower and then he fell in love with the industry. And again, kept pushing how we can do things automated? How do we can do things? How do we get more yield, more everything out of what we do? And as a lover of technology he made it a great environment for everybody including the growers to work in and to just do something new. >> Well, I mean the thing that we know that as populations grow we're not getting more land. Okay (laughs). So, you have to get better yield and the answer is not to just pound vegetables with pesticides. So maybe talk about how you guys are different from sort of a conventional farming approach, just in terms of maybe your yield, how you treat the plants, how you're able to pick throughout the year, give us some insight there. >> So basically I'll start with through the lifecycle of a pepper. So it's basically planted at a propagator and then it comes to our facility and it comes in the little white boxes here behind me. And they actually are usually about that tall. They're about a foot tall. Maybe a little more when they come to us. And right from that point in time, we start keeping track of everything. How much we put water, how much water it doesn't take, what nutrients it takes, how much it weighs. We actually weigh the vines to know how much they are in real time. We do everything top to bottom. So we actually control the life cycle of the plant. On top of that, we also look and have a whole bio scout division. So it's a group of people that are starting to use AI to actually look at how the bugs are attacking the plants. And then at the same time, we release a good bug that will eventually die off to kill the bugs that are starting to harm the plant. So it basically allows us to basically do as close to natural way of growing a plant as possible without spraying or doing anything like that at night. It's actually funny 'cause there's a lot pictures out there and you think that a greenhouse, it's going to be wet in here. And actually for the most part, it is dry all the time. Like I'm very hot, it's very dry and it's just how we work. We don't let anything inside. We control everything in that plant's life. And now with our newest range, we even control how much light it gets. So we basically give it light all night too. And even some nights when it's a little days out, not like today, but when it's a little dark out and the sun's not up there, we'll actually make sure it gets more light to get that more yield out of it. So we can grow 24/7 12 months a year. >> Okay Keith. So it sounds like you're using data and AI to really inform you as to nature's best formula for the good bugs, the bad bugs, the lighting to really drive yields and quality. >> Yeah, we analyze, like I said, everything from the edge that we collect, like I said, we have over 2000 sensors out in the greenhouse and we keep expanding it more and more every year to collect everything from the length of the vine, the weight of the vine in real time. And we basically collect it from the day the plant is born to the day that we actually take it all out to be composted. We know how much light it got. Does it need to get light that day? We analyze everything in general and it allows us to take that data back in real time to make it better and to look at the past data to do better again. Like you hear, some times we have actually have a cart going by here now. That data from that cart, we'll go back to our growers and they will know how much weight they got out of that row in the next 15 to 20 minutes. So they can actually look, okay, how did that plant react to the sun, how's tomorrow? Does it need more nutrients? Does it need a little less? They take all that data from the core and make sure it's all accurate and as up to date as possible. >> So Keith, and maybe even you can give us approximations, but so how much acreage do you have? And how much acreage would you need with conventional farming techniques to get the kind of yields and quality that you guys are able to achieve? >> So we own 160 acres of greenhouse that's actually under glass. It's actually 200 acres total of land but what's 160 acres approximately of greenhouse that's actually under glass. 'A' we're always constantly growing. Our demand is up that that's why we grow so fast. Usually you're looking at both 12 to one. So for every foot squared of space, you're looking for equivalent is about 12 feet squared for a conventional farm. That's the general average. Mostly because we can harvest year round, we can continually harvest. We maximize the harvest amount and everything total. >> I'm also interested in your regime, your team. So obviously you're supporting from an IT perspective, but you've got all this AI going on. You've got this data life cycle. So what does the data team look like? >> We're actually... I always laugh though. I like to call our growers are basically data analysts. They're not really part of my IT team, but they basically have learned the role of how to analyze data. So we'll have basically one or two junior growers, per range. So probably about, I'd say about, we have about 10 to 12 junior growers and then one senior grower per whole farm. So probably about three or four senior growers at any one time. But my IT staff is actually about a team of four, five, including myself. And we are always constantly looking at how to improve data and how to automate the process. That's what drives us to do more. And that's where the robots even come in is every time we look at something, it's not even from an IT perspective, but even just from a picking perspective, how do we automate this? How do we do a better tomorrow? How do we continually clean this up? And it just never ends. And every year we look back, okay, it cost us a dollar per meter squared or per foot square for the people down South in America there now. We look at that and how do we do that better next year? How do we do better the next day? And it's a constant looking and it's something we look at refining and now that's why we're going so much into AI 'cause we want to not look at the data and decide what to do. We want the data to tell us what to do. >> You guys are on the cutting edge. I mean this is the future of farming. I wonder if we could talk about the IT, what does the IT group look like in the future of farming? I mean you guys, what's your infrastructure look like? Are you all in the cloud or you can't be in the cloud because this is really an extent of an IoT or an edge use case. Paint a picture of the IT infrastructure for us if you would. >> So the IT infrastructure it's a very large amount at the edge. We take a lot of the information from the edge and we bring it back to our core to do our analyzing. But for the most part, we don't really leverage the cloud much yet and most of it is on-prem. We are starting to experiment with moving out to the cloud. And a lot of it is, you'll laugh though, is because the farming and agriculture industry really was stagnant for a long time and not really stagnant, but just didn't really progress as fast as the rest of the world. So now they're just starting to catch up and realizing, wow, this is a growing industry. We can do a lot of cool things with technology in this range. And now it's just exploded. So I'm going to say in the next five to 10 years, you're going to see a lot more private clouds and things like that happening with us. I know we're right now starting to just look at creating with the VxRail, a private cloud, and a concept like that to start to test that water again of how to analyze and how to do more things onsite and in the cloud and leverage everything top to bottom. >> So you've got your own servers at the edge... So Intel based servers, what's your storage infrastructure look like? Maybe describe the network a little bit. >> Yap. Okay. So we are basically, I'll admit here, we are a Dell factory. We're basically everything top to bottom. Right now we're on an FX2, Dell FX2 platform. It's basically our core platform we've been using for the last five years. It does all of our analitics and stuff like that. And we have just transformed our unstructured data to Isilon. It's been one of the best things for us to clean that up and make things move forward. It was actually one of those things that management actually looked at me and kind of looked at me and said, "what are you nuts?" Because we basically bought our first Isilon and then four months later, I said, "I love this. I got to have more," because everybody loved it so much in the way of store things. So we actually doubled the size of it within four months, which was a great... It was actually very seamless to do, but we're now also in a position where the FX2 in that stage type of situation didn't quite work for us to expand it. It wasn't as easy to expand. So we wanted to get away that we could expand at a moment's notice. We can change, we can scale out much faster and do things easier. So that's why we're transforming to a VxRail to basically clean that up and allow us to expand as we grow. >> So you're essentially trying to replicate the agility and speed of the cloud but like you say, you're an edge use case. So you can't do everything in cloud. Is that the right way to think about it? You mentioned private cloud but just sort of cloud experience, but at the edge. >> Yeah. We try to keep everything at the edge. It just makes it a lot easier to control. Because we're so big. Think about it like you are bringing all this information back from everywhere. It's a lot of data to come back to one spot. So we're trying to push that more, to keep it at the edge so that we can analyze it right there in the moment instead of having to come back and do it but yeah. And I think you'll see in the next few years, a lot of change to the cloud, I think it'll start to be there, but again, like I said, the private cloud will probably be the way most will go. >> Okay. So I got to ask you then, I mean, you've really tested that agility over the last 60 days with this COVID pandemic. How were you able to respond? What role did data play? You had supply chain considerations. Obviously, you got a lot of online ordering going on. You got to get produce out. You've got social distancing. How were you able to handle that crisis? >> Well it was a really great thing for our team. Our team really came together in a great way. We had a lot of people that did have to go home and we started because we had so many ranges all over, already about a year and a half ago we started implementing an SD-WAN solution to allow us to connect to different areas and to do all kinds of stuff. So it was actually very quick for us to be able to send the others home. We used our VeloCloud SD-WAN to expand it. It was very seamless and we just started sending people home left, right and center. The staff that had to stay here, like the workers out in the greenhouse here now are offshore labor as we call it. They work great. They worked with at every moment of the day and they dug right in. We haven't lost heartbeat. Like actually our orders have gone up in the last... Through this COVID experience more than anything else. And it's really learned... It really helped from an IT perspective and I laugh about this and it's one of the greatest things about what I do, I love this moment, is where sometimes we were very hesitant to jump on this video collaboration. I said, "hey, that's a great way of doing this." But sometimes people they're very stuck in their ways and they love it and they're like, "I don't know about this whole team Zoom "and all that fun stuff," but because of this, they've now embraced it and it's actually really changed the way even they've worked. So in a way, it kind of sped up the processes of us becoming more agile that way in a way that would've taken a long time. They now love teams. They love being able to communicate that way. They love being able to just do a quick call. All that functionality has changed and even made us more efficient that way. (mumbles) >> How does this all affect your IT budget allocation? Did you get more budget? Was it flat budget? Did you have to shift budget to sort of work from home and securing the remote workers? Can you sort of describe that dynamic? >> So it did, I'll be true, there's no way around it to not up my budge. They basically said, "yep, "you have to do what you have to do. "We have to continue to function, "we cannot let our greenhouse go down "and what do you need to do to make it happen?" So I quickly contacted Dell and got things coming and improve our infrastructure as much as we could to get ready. I contacted (mumbles). I basically made it so that my team can support every single part of our facet from home if they actually had to go home. So for example, if I had to get stuck at home, I could do every single part of my job from home, including the growers as much as possible. So say our senior grower had to get home. I locked him up. He has to be able to see everything and do everything. So we actually expanded that very quickly and it was a cost to us. But again, there's no technology we didn't implement that we hadn't talked about before. We just hadn't said, "you know what? It's just not the right time to try that." And now we just went ahead and we just said, we got to do it now. And there's not one part of our aspect that we don't reuse. >> Was Dell able to deliver? Did they have supply constraint issues? I mean, I know there's been huge demand for that whole remote worker. Were able to get what you needed in time? >> Yeah. You know what, I think that we hit it a little ahead of the scope of when things started to go bad, our senior management, our president and all that. He basically said, "you know Keith, "we got to get ready on this. "We got to get some stuff coming." We never ran out of some things. The quirkiest thing and it is just a reality, the biggest thing was webcams was to kind of trying to get webcams. Other than that, there was issues with UPS and Purolator and FedEx because they were just inundated too. But for the most part, we kept everything moving. There wasn't a time that I was actually really waiting on something that we had to have. One of the other great things of our senior team that's here is they've really given me the latitude to say, "what do you need and how do you need to do it?" And so I have my own basically storage area of stuff everywhere. And my team does laugh at me 'cause they call me a hoarder and I basically have too much. And we were able to use either some older stuff or some newer stuff and combine it and we got everything running. There was only a little hiccups here and there but nothing ever is going to go perfect. >> Yeah. But it's enabling business results. We've asked a lot of it pros like yourself like what do you expect the shape of the recovery? And obviously our hearts go out to those small businesses that have been decimated. You're clearly seeing industries like airlines and hospitality and restaurants are obviously in rough shape, but there is a bifurcated story here. Some businesses and it sounds like in this camp where the pandemic was actually a tailwind, your online demand is up, food, vegetables, people... There were a lot of meat shortages. So people really turn to vegetables, is that right? Is that the shape of the recovery actually, is maybe not even V-shape, it's been a tailwind for Nature Fresh Farms. >> Yeah. You know what? It has been a tailwind and that's the right way to say it. We've just increased our yieldage. We've increased that, it's not unnew for us, that's been the biggest driving force for us is basically the demand for our product and building fast enough to keep up to that demand. Like we continually build and expand. We've got more ranges being built in the coming years like looking towards the 21, 22, 23 year. It's just going to just continue to expand and that is purely because of demand. And this COVID just again, escalated that little bit 'cause everybody's like, I really want the peppers and like you learned, we actually do have some tasty peppers and tomatoes. So it does make it a nice little treat to have at home for the kids. >> Well, it's an amazing story of tech meets farming. And as you said for years your industry kind of became quiet when it came to tech, but this is the future of farming, in my opinion. And Keith, thanks so much for coming on the CUBE and sharing the story of Nature Fresh Farms. >> Well, thank you for having me. It's been a great pleasure. >> Alright. Thank you for watching everybody this is Dave Vellante for the CUBE and we'll see you next time. (upbeat music)

(upbeat music) >> From the Cube studios in Palo Alto in Boston connecting with thought leaders all around the world. This is the CUBE Conversation. >> Hey everybody this is Dave Vellante and welcome to the special CUBE Conversation. I'm really excited to have Keith Bradley here he's the Vice President of IT at Nature Fresh Farms. Keith good to see you. >> Hey, good to see you too there Dave. >> All right, first of all I got to thank you for sending me these awesome veggies. I got these wonderful peppers. I got red, orange. I got the yellow. I got to tell you Keith these tomatoes almost didn't make it. It's my last one on the vine. >> (Laughs) >> These guys are like candy. It's amazing. >> Yap. They are the tasty thing. >> Wonderful. >> You know what, I'll probably just join you right here now too. I'll have one right here right now and I'll join you right now. >> My kids love these but I'm not bringing them home. And then I got these other grape tomatoes and then I've got these mini pepper poppers that are so sweet. You know which one I'm talking about here. And then we've got the tomatoes on the vine. I mean, it's just unbelievable that you guys are able to do this in a greenhouse. Big cukes, little cukes. Wow. Thank you so much for sending these. Delicious. Really appreciate it. >> Yeah. Well thank you for having them. It's a great little tree and it's something that I know you're going to enjoy. And I love for everybody to have it and there's not a person I haven't seen that hasn't enjoyed our tomatoes and peppers. >> Now tell me more about Nature Fresh Farms. Let's talk about your business I want to spend some time on that. We've got IoT, we got a data lifecycle. All kinds of cool stuff, scanners. Paint a picture for us. >> I like to even go... If you don't mind. I like to even go back to where our roots actually came from. So Peter Quiring, our owner actually was a builder by nature and he was actually back in the year 2000 really wanted to get into the greenhouse because he was a manufacturer. And he built our phase one facility back in 2000 under the concept that he said, "there's computers out there." And Peter will be the first one to say, "I don't know how to use them, "but I know that it can do a lot for us." So even back in 2000, we were starting to experiment with using the computers back then to control the greenhouse, to do much of the functionality. Then he bought it under the concept as our sister company, South Essex Fabricating that he would sell the greenhouse turnkey to somebody else. Well, talking to him and I've been around since about phase two. He basically said, "when I built phase three, "which is our first 32 acre range, I realized that is actually in the pepper business now," and he realized he was a grower and then he fell in love with the industry. And again, kept pushing how we can do things automated? How do we can do things? How do we get more yield, more everything out of what we do? And as a lover of technology he made it a great environment for everybody including the growers to work in and to just do something new. >> Well, I mean the thing that we know that as populations grow we're not getting more land. Okay (laughs). So, you have to get better yield and the answer is not to just pound vegetables with pesticides. So maybe talk about how you guys are different from sort of a conventional farming approach, just in terms of maybe your yield, how you treat the plants, how you're able to pick throughout the year, give us some insight there. >> So basically I'll start with through the lifecycle of a pepper. So it's basically planted at a propagator and then it comes to our facility and it comes in the little white boxes here behind me. And they actually are usually about that tall. They're about a foot tall. Maybe a little more when they come to us. And right from that point in time, we start keeping track of everything. How much we put water, how much water it doesn't take, what nutrients it takes, how much it weighs. We actually weigh the vines to know how much they are in real time. We do everything top to bottom. So we actually control the life cycle of the plant. On top of that, we also look and have a whole bio scout division. So it's a group of people that are starting to use AI to actually look at how the bugs are attacking the plants. And then at the same time, we release a good bug that will eventually die off to kill the bugs that are starting to harm the plant. So it basically allows us to basically do as close to natural way of growing a plant as possible without spraying or doing anything like that at night. It's actually funny 'cause there's a lot pictures out there and you think that a greenhouse, it's going to be wet in here. And actually for the most part, it is dry all the time. Like I'm very hot, it's very dry and it's just how we work. We don't let anything inside. We control everything in that plant's life. And now with our newest range, we even control how much light it gets. So we basically give it light all night too. And even some nights when it's a little days out, not like today, but when it's a little dark out and the sun's not up there, we'll actually make sure it gets more light to get that more yield out of it. So we can grow 24/7 12 months a year. >> Okay Keith. So it sounds like you're using data and AI to really inform you as to nature's best formula for the good bugs, the bad bugs, the lighting to really drive yields and quality. >> Yeah, we analyze, like I said, everything from the edge that we collect, like I said, we have over 2000 sensors out in the greenhouse and we keep expanding it more and more every year to collect everything from the length of the vine, the weight of the vine in real time. And we basically collect it from the day the plant is born to the day that we actually take it all out to be composted. We know how much light it got. Does it need to get light that day? We analyze everything in general and it allows us to take that data back in real time to make it better and to look at the past data to do better again. Like you hear, some times we have actually have a cart going by here now. That data from that cart, we'll go back to our growers and they will know how much weight they got out of that row in the next 15 to 20 minutes. So they can actually look, okay, how did that plant react to the sun, how's tomorrow? Does it need more nutrients? Does it need a little less? They take all that data from the core and make sure it's all accurate and as up to date as possible. >> So Keith, and maybe even you can give us approximations, but so how much acreage do you have? And how much acreage would you need with conventional farming techniques to get the kind of yields and quality that you guys are able to achieve? >> So we own 160 acres of greenhouse that's actually under glass. It's actually 200 acres total of land but what's 160 acres approximately of greenhouse that's actually under glass. 'A' we're always constantly growing. Our demand is up that that's why we grow so fast. Usually you're looking at both 12 to one. So for every foot squared of space, you're looking for equivalent is about 12 feet squared for a conventional farm. That's the general average. Mostly because we can harvest year round, we can continually harvest. We maximize the harvest amount and everything total. >> I'm also interested in your regime, your team. So obviously you're supporting from an IT perspective, but you've got all this AI going on. You've got this data life cycle. So what does the data team look like? >> We're actually... I always laugh though. I like to call our growers are basically data analysts. They're not really part of my IT team, but they basically have learned the role of how to analyze data. So we'll have basically one or two junior growers, per range. So probably about, I'd say about, we have about 10 to 12 junior growers and then one senior grower per whole farm. So probably about three or four senior growers at any one time. But my IT staff is actually about a team of four, five, including myself. And we are always constantly looking at how to improve data and how to automate the process. That's what drives us to do more. And that's where the robots even come in is every time we look at something, it's not even from an IT perspective, but even just from a picking perspective, how do we automate this? How do we do a better tomorrow? How do we continually clean this up? And it just never ends. And every year we look back, okay, it cost us a dollar per meter squared or per foot square for the people down South in America there now. We look at that and how do we do that better next year? How do we do better the next day? And it's a constant looking and it's something we look at refining and now that's why we're going so much into AI 'cause we want to not look at the data and decide what to do. We want the data to tell us what to do. >> You guys are on the cutting edge. I mean this is the future of farming. I wonder if we could talk about the IT, what does the IT group look like in the future of farming? I mean you guys, what's your infrastructure look like? Are you all in the cloud or you can't be in the cloud because this is really an extent of an IoT or an edge use case. Paint a picture of the IT infrastructure for us if you would. >> So the IT infrastructure it's a very large amount at the edge. We take a lot of the information from the edge and we bring it back to our core to do our analyzing. But for the most part, we don't really leverage the cloud much yet and most of it is on-prem. We are starting to experiment with moving out to the cloud. And a lot of it is, you'll laugh though, is because the farming and agriculture industry really was stagnant for a long time and not really stagnant, but just didn't really progress as fast as the rest of the world. So now they're just starting to catch up and realizing, wow, this is a growing industry. We can do a lot of cool things with technology in this range. And now it's just exploded. So I'm going to say in the next five to 10 years, you're going to see a lot more private clouds and things like that happening with us. I know we're right now starting to just look at creating with the VxRail, a private cloud, and a concept like that to start to test that water again of how to analyze and how to do more things onsite and in the cloud and leverage everything top to bottom. >> So you've got your own servers at the edge... So Intel based servers, what's your storage infrastructure look like? Maybe describe the network a little bit. >> Yap. Okay. So we are basically, I'll admit here, we are a Dell factory. We're basically everything top to bottom. Right now we're on an FX2, Dell FX2 platform. It's basically our core platform we've been using for the last five years. It does all of our analitics and stuff like that. And we have just transformed our unstructured data to Isilon. It's been one of the best things for us to clean that up and make things move forward. It was actually one of those things that management actually looked at me and kind of looked at me and said, "what are you nuts?" Because we basically bought our first Isilon and then four months later, I said, "I love this. I got to have more," because everybody loved it so much in the way of store things. So we actually doubled the size of it within four months, which was a great... It was actually very seamless to do, but we're now also in a position where the FX2 in that stage type of situation didn't quite work for us to expand it. It wasn't as easy to expand. So we wanted to get away that we could expand at a moment's notice. We can change, we can scale out much faster and do things easier. So that's why we're transforming to a VxRail to basically clean that up and allow us to expand as we grow. >> So you're essentially trying to replicate the agility and speed of the cloud but like you say, you're an edge use case. So you can't do everything in cloud. Is that the right way to think about it? You mentioned private cloud but just sort of cloud experience, but at the edge. >> Yeah. We try to keep everything at the edge. It just makes it a lot easier to control. Because we're so big. Think about it like you are bringing all this information back from everywhere. It's a lot of data to come back to one spot. So we're trying to push that more, to keep it at the edge so that we can analyze it right there in the moment instead of having to come back and do it but yeah. And I think you'll see in the next few years, a lot of change to the cloud, I think it'll start to be there, but again, like I said, the private cloud will probably be the way most will go. >> Okay. So I got to ask you then, I mean, you've really tested that agility over the last 60 days with this COVID pandemic. How were you able to respond? What role did data play? You had supply chain considerations. Obviously, you got a lot of online ordering going on. You got to get produce out. You've got social distancing. How were you able to handle that crisis? >> Well it was a really great thing for our team. Our team really came together in a great way. We had a lot of people that did have to go home and we started because we had so many ranges all over, already about a year and a half ago we started implementing an SD-WAN solution to allow us to connect to different areas and to do all kinds of stuff. So it was actually very quick for us to be able to send the others home. We used our VeloCloud SD-WAN to expand it. It was very seamless and we just started sending people home left, right and center. The staff that had to stay here, like the workers out in the greenhouse here now are offshore labor as we call it. They work great. They worked with at every moment of the day and they dug right in. We haven't lost heartbeat. Like actually our orders have gone up in the last... Through this COVID experience more than anything else. And it's really learned... It really helped from an IT perspective and I laugh about this and it's one of the greatest things about what I do, I love this moment, is where sometimes we were very hesitant to jump on this video collaboration. I said, "hey, that's a great way of doing this." But sometimes people they're very stuck in their ways and they love it and they're like, "I don't know about this whole team Zoom "and all that fun stuff," but because of this, they've now embraced it and it's actually really changed the way even they've worked. So in a way, it kind of sped up the processes of us becoming more agile that way in a way that would've taken a long time. They now love teams. They love being able to communicate that way. They love being able to just do a quick call. All that functionality has changed and even made us more efficient that way. (mumbles) >> How does this all affect your IT budget allocation? Did you get more budget? Was it flat budget? Did you have to shift budget to sort of work from home and securing the remote workers? Can you sort of describe that dynamic? >> So it did, I'll be true, there's no way around it to not up my budge. They basically said, "yep, "you have to do what you have to do. "We have to continue to function, "we cannot let our greenhouse go down "and what do you need to do to make it happen?" So I quickly contacted Dell and got things coming and improve our infrastructure as much as we could to get ready. I contacted (mumbles). I basically made it so that my team can support every single part of our facet from home if they actually had to go home. So for example, if I had to get stuck at home, I could do every single part of my job from home, including the growers as much as possible. So say our senior grower had to get home. I locked him up. He has to be able to see everything and do everything. So we actually expanded that very quickly and it was a cost to us. But again, there's no technology we didn't implement that we hadn't talked about before. We just hadn't said, "you know what? It's just not the right time to try that." And now we just went ahead and we just said, we got to do it now. And there's not one part of our aspect that we don't reuse. >> Was Dell able to deliver? Did they have supply constraint issues? I mean, I know there's been huge demand for that whole remote worker. Were able to get what you needed in time? >> Yeah. You know what, I think that we hit it a little ahead of the scope of when things started to go bad, our senior management, our president and all that. He basically said, "you know Keith, "we got to get ready on this. "We got to get some stuff coming." We never ran out of some things. The quirkiest thing and it is just a reality, the biggest thing was webcams was to kind of trying to get webcams. Other than that, there was issues with UPS and Purolator and FedEx because they were just inundated too. But for the most part, we kept everything moving. There wasn't a time that I was actually really waiting on something that we had to have. One of the other great things of our senior team that's here is they've really given me the latitude to say, "what do you need and how do you need to do it?" And so I have my own basically storage area of stuff everywhere. And my team does laugh at me 'cause they call me a hoarder and I basically have too much. And we were able to use either some older stuff or some newer stuff and combine it and we got everything running. There was only a little hiccups here and there but nothing ever is going to go perfect. >> Yeah. But it's enabling business results. We've asked a lot of it pros like yourself like what do you expect the shape of the recovery? And obviously our hearts go out to those small businesses that have been decimated. You're clearly seeing industries like airlines and hospitality and restaurants are obviously in rough shape, but there is a bifurcated story here. Some businesses and it sounds like in this camp where the pandemic was actually a tailwind, your online demand is up, food, vegetables, people... There were a lot of meat shortages. So people really turn to vegetables, is that right? Is that the shape of the recovery actually, is maybe not even V-shape, it's been a tailwind for Nature Fresh Farms. >> Yeah. You know what? It has been a tailwind and that's the right way to say it. We've just increased our yieldage. We've increased that, it's not unnew for us, that's been the biggest driving force for us is basically the demand for our product and building fast enough to keep up to that demand. Like we continually build and expand. We've got more ranges being built in the coming years like looking towards the 21, 22, 23 year. It's just going to just continue to expand and that is purely because of demand. And this COVID just again, escalated that little bit 'cause everybody's like, I really want the peppers and like you learned, we actually do have some tasty peppers and tomatoes. So it does make it a nice little treat to have at home for the kids. >> Well, it's an amazing story of tech meets farming. And as you said for years your industry kind of became quiet when it came to tech, but this is the future of farming, in my opinion. And Keith, thanks so much for coming on the CUBE and sharing the story of Nature Fresh Farms. >> Well, thank you for having me. It's been a great pleasure. >> Alright. Thank you for watching everybody this is Dave Vellante for the CUBE and we'll see you next time. (upbeat music)

>> Live from Las Vegas. It's the queue covering Adobe Summit twenty nineteen brought to you by Adobe. >> Hello and welcome back to the keeps. Live coverage in Las Vegas for Adobe Summit. Twenty nineteen. I'm John for Jeffrey from the Cube. Our next guest, Bradley Jenkins, was the marketing CEO and vice president. Met Life, part of the global technology and operations group. Innovative title. But thank you, >> Yeah, thank you. Thanks for having me. >> So we're here to do the summit. A lot of things are happening. It's really interesting because you have a convergence of two worlds and it looks like a cloud world. It's it's it's the creative cloud. It's the experience Cloud now called The whole World shares a lot of devil's mindset in there. Got a platform? The whole world's changed. Now marketing has a full blown class, not just marketing class, so it's a whole system. So as a marketing seo, what does that mean? Is now a new role emerging in organizations? Is this where we're team? >> I think it's a It's an emerging role. I think it's one of those things where in the in the market and technology space, the lines are blurring, and part of the role of people like me are the ones you could be the bridge makers between the two functions and bring in products like we see all around us here today. Cloud based Solutions How do we activate marketing tactics faster, quicker on. Then combine things like experiences with tools and technologies in different ways. I think it's a specialty skill, and it's coming out now and emerging >> well. One of the patterns is that marketing departments that have a technical and also a relationship seems to be more agile, transformed faster. This seems to be the same thing you guys are looking at right? >> Exactly. It's all about speed to market. So agility is this one co looking and combining everything from creative to the developers, all in one Teo product resource person all the wine and we get in and try to solve business problems. Fastest possible. But you're almost kind of a personification of the story we hear all the time, which is? CEOs get a seat at the table right now. They're no longer just keeping the lights on in the system's lit. But it's a fundamental way the company goes the business of fundamental way the company interact with their customers. So to actually put a marketing CEO title. That's a pretty unique thing I don't think we've ever had one on. So you come at it, no doubt about it. I'm here about customer engagement, customer experience, not keeping the light on. That's right. That's right. First, one side, like a unicorn. >> How's it been? So tell us some of the things you do. I love how you're part of a global technology and operations group. Noticed the word operations and tech together again, back to this cloud theme of Dev ops, which changed the game on the world >> it has. >> So we're seeing that same thing happening playing out in the creative market, whether it's content for here, same thing. Explain some of the things you're doing. >> It's the same thing, and it is Everything's very cloud based today, obviously. So everything from building out content, platforms and services and kind of services framework switch, which is which is key to what what we want to do but also campaign and analytics and, uh, you know, social and what the emerging capabilities are in social. How do we tie all those together but do in a way, we're capturing data and insights across all of our channels in a more creative, quicker way, then activating that across new new experiences. >> You know, Bradley, one thing I wanted to ask you, And I'm glad you came on because I've been really kind of riffing on this idea and trying to get a date in actual year kind of a before cloud after cloud demarcation line because, you know, we're in Silicon Valley. We cover a lot of startups and literally ones go big or go home is kind of the mantra. But if you were born before Amazon, you're pretty much either aren't around or got acquired. If you're born after Amazon, where clouds scale and all this stuff happened, you tend to thrive in a whole new kind of shift. So in Martek, which is heavily funded, sector on the ecosystem map of pure play applications was pretty dense. >> Is very dense. Yeah. >> Did that live up to its name? Did it shift and shape? What's your thoughts on that mark Tech landscape could? Certainly, it's relevant when you're marking CEO. You want to put technology in place. Has the platform shifted? What's that? What's going on? Tell us. >> Yeah. So you know, I think has it lived up to his name? Uh, yes, and it's created challenges that the same thing at the same time. So what is still in the Martek landscape is seventeen thousand or whatever tens of thousands of products. Now Mr Wescott fingers latest one shows every year it doubles or quadruples in there. And I think one of the biggest challenges we have now is just navigating, never getting the landscape, but then be able to pick out and say, Here are the five things and you focus on Here is how I'm going to tie them together and in great demand. And there's a lot of noise and you have to break through a lot of that to build a craft. These solutions together. So in a lot of ways, I think it's lived up, Uh, a lot of ways. I think it's create a lot of new challenges that things like markets he has you to think about. Be aware of the bread, the people that are out there. But that's just the capabilities. How do you stitch them together and you become more of a weaver? Then thin a specific domain >> class early adopter proves the model. And now reality as operational izing things becomes clear. The wheat from the chaff, as they say, kind of get figured out >> exactly friendly. I want to get your kind of thoughts on a CZ. The relationship between the company and the customer has shifted from sitting down with an agent or maybe talking to it. Agent on the phone to really Elektronik means how you've been able to kind of continue a certain type of brand experience. And I'm also just curious your feedback on the theme here where it's not really the transaction. It's the experience of which the transaction is a piece of How are you seeing that play out in the way that you guys interact with your customers? Yeah, and I think for us we're in evolving state to we have agencies and brokers that we worked through, and so it's a bit of the model in some cases, in some cases it turns, and we're about to see targeting >> B to B >> group customers as an example, and so the experience is very a bit so for us, it's experience of the customer, and how do we service some? How do we treat them. What's the purchasing servicing capabilities look like? What's our customer service look like? But also the experience of agents and brokers. And are we providing the right service and products to them to build equipped them to go help in resell product? So we look at it from a couple different angles and depends a lot on context and where we're operating in product and servicing products at Is it easy to maintain kind of the voice of the brand, if you will, through these alternate channels or, you know, how do you kind of stay true to the brand? Yet go to market through these. He's a myriad of channels. Yeah, it's no Isaac, a question that we're really working through the same kind of things now of what can we What can we help provide agents and brokers with, and that helps with our brand? Our friend promised up. Some sell better. That it's it's a work in progress, but technical challenge? Yeah, I don't >> really have >> all the answers. >> Take a minute to explain the MetLife transformation. What you guys have done. Where are you now? In the jury? Your journey will be customer. You're here at their event. Where are you on that Progress bar? How far along are you? It seems to be a theme of transforming. Continue to transform is what successful company doing. Our iterating are raising the bar. Whatever term used where you guys at, Can you take us through? >> Yeah. So a few years ago, we we refreshed our enterprise strategy. We placed a customer in digital on data at the center of our enterprise strategy. And we have pillars around different transformation aspects that we're working on everything from customer service too. Right? Products simplifying our product messaging the way we talked about product specially in insurance can be complicated. And so we're trying to get a little a little more concise and clear and package things differently. But But at the core, our strategy now is placing digital placing diddle data at the center of it. Uh and then how do we enact data and new and different ways Everything from not only knowing customers, but how do we use data to great better and smarter products or even the risk different products that we have waken me price competitive in certain market areas. >> So Data's lifeblood of your transformation. It is. What's the strategy? How you guys enabling that internally? What some of the results will take us through experiences, zealously numbers. But I'm sure it's helping. If you do it right. It's challenging, though it's not easy. >> It is. Yeah, it's challenging, and it will take a while to sort it out. So we'LL say we've solved everything. Uh, but But I think we look at a few different things. What one is knowing the customer? And so you know, we're investing heavily and try and doing things like customer profile and a customer. Three sixty. Whatever you want to call it different in different, different areas. Uh, but how do we know them? And then how do we then act? There's the data's insights into different channels. So we've had a lot of a lot of good successes in there, in particular markets on creating more engaging experiences and lifting customer retention and loyalty. So we have good, good insights there. We're planets in different areas, so things like we go to bid for new products and or new new customers around a new product area. What can we do it for our pricing models on. How do we love its data around Where is geographic or whatever it might be? Or demographics and fly it to be more price competitive? And we're starting to see a lot of fruition there and how it gets applied. Tto win New business >> One of the things that we've been talking about on the Q through got a lot of events, and the theme that comes up all the time when you have these new shifts is new. Things are emerging. New capabilities, different economic points, scales different. So all good. Now the hard part is making it work. Operationalize ing Something new is a huge challenge. It is. Did you share your view on that? And reaction to that because this is seems to be not about the tech about either skills, gaps or culture gap. There's a lot of things in the way of operational izing, something new. What's what people do to operationalize something? >> Yeah, no, it's a good question. I'm glad you brought it up because that's actually one of the things that I have a caper. A lot is a lot of times we lead with the tech and then we place it And then we say, Well, now what? And then everything you know is what it comes to a standstill. And, yeah, you have to leave with people. Process so again in for a transformation, understand exactly what it is you're trying to solve. How are you going to solve it afterwards? Do you have the skill sets and place to do it and then follow up with the tech? And then I think a lot of a lot of companies do a little bit reverse where they go in acquiring, like we're going to solve this and bring the cheque in and in your little literally left standing at the end of day of How do you have the operational ises? So something we focus on a lot is it is the people process piece of enablement training, the skills that are required. How do you turn it into a machine after you bring the tech in to really start pumping up? Whether it's a growth objective or call status, I've never where the object it might be. But you have to you have to almost produce this into ah life machine of its own that cannon live and breathe after you bring the second. >> What should more marketing CEOs as it becomes a price? I think it will be. In my opinion, I think it will be a roll because it's really critical because of the opportunity. What should they be doing? That's this New persona evolves. You're pioneering it. What is the job function? What does it do in your opinion? Has this take shape? >> Yeah, I think Number one. Learn the business. And I think you have to speak the same language. And that's one of the biggest challenges translating so different languages across different groups. In the first thing, any market so you could do is go learn the business, speak the same language, then what company you know. We're in insurance company and a risk management companies. So understanding, finance, understanding, mark objectives. Your customer detectives is key and then figure out how to start mapping the solutions in. But, yeah, I think it's it's It's a fridge, a role. We have to be able to be a navigator in away across solution options, but always in context of understand the business and how you confessed, apply, and in a specific way, >> Data wrangler of course, because you're wrangling a lot >> of data. If I don't have a lot of intersection with, you know, kind of actuarial side of the house, which is, you know, kind of always been data driven, right since the early earliest days. But I mean, are you seeing you know, kind of that side of the house? Kayla, you know, can we get we get some of these new tools? Could we get some of these kind of new ways to approach the data problem than we historically did? I think now, now? Yes. I think it has been an evolution. I think in the early days of data, it was a bit more of a scary thing. And so I feel like we're, you know, as advocates in the sea of space that we were pushing a little more than, you know, being pulled in. And I think I think lately in the last couple of years. But I know at least until we've seen a shift of demand side of requests coming in, saying we need to partner way ideas of how to accelerate and be competitive, which is great. Now it's almost become a supply demand trick. Where you just can't keep up. Because the level of segmentation on kind of classy the insurance, you know, kind of breakdown is really high, right? Sex age, you know, a couple other factors. But you know, now that the amount of data that's available, that amount of real time data, it's available on changing, they've got to be going bananas over on that side. >> You know, one of the things that we've been seeing on the side again. I want to bring a question in the marking CEO piece is on. We've had many CEOs talk about this on the Cuba and direct interviews is they've outsourced everything, and they really had no core competency, had all the big size running stuff you had global outsourcing development. And as cloud became important, they had the build applications internally, didn't have the skills, so they had to quickly reset and rebuild and in house capability. And the result of that is ongoing and seen. The ones who've done that well with cloud are doing great. They still use outsourced off. Now, on the marketing side, you saw that same thing happen where agencies run everything. The agency does this, you got the creative agency, you got a PR firm, you all these things going on and some say that marketing has been outsource a lot. And so the question is, what mix of in house skill, an agency relationships? Because now you're gonna see that application developer. No problem. But core competency becomes a super important question. Yeah, And how are you funding it And what should be in house on what should be outsourced. >> Yeah. Yeah, and we have We're going to the same evolution. We had a position than a few years ago where it was almost entirely outsourced, and we in sourced a bunch of it. And now we're right sizing what's unsourced and not in sources. So I think one is Think about, uh, what your differentiation is. And how do you want to be competitively different competitively and having create advantage and then in source those things. And then you had to find a way. That's one thing. I think every year you talk to Rick Wright size and reassess. And so for us, we insourced a lot of things around. Um, first around, build side, so platforms being cloud. But then how do you enact and activate them? So we've brought some of those inside internally on we started marrying those up with creativity. This is just the last words of the great, But we were married them up and get these, uh, you know, more agile lean teams cross blended skill sets and go on, go to market quicker with new experiences. I think over time we'LL see a start and sourcing more of the agency side, maybe shedding some of the you know, the left side as we started becoming more pattern base and whatnot. So I think it's one of those things that you evolve every year as the right size. But the key is trying to tie it back to you. How do you wantto create differentiation? What, you're competitive advantage and then make sure that you have that internal first and foremost. And don't outsource here, your smarts to >> another. I think the key point is by re factoring or Ria's re sizing. That's the interest generation that you get with cloud and scale. If you don't do that, scale can also hurt. You >> can yeah, yeah, >> comes come back and impression. It's right, really. Thanks for coming on. Appreciate the insights from great to hear from Practitioner Love the new child. I think it's a game changer. I think it's going to be a standard final question to end the segment learnings over the over the past couple of years. What some key learnings that you take away from the process that you're going to carry forward. >> Yeah, I think one one is as a company being being a blend roll between marketing the technology. One is, uh, be willing to change and adapt and be willing to bring the rest of the company with you could You can't do everything yourself. So I think you have to be a change agent for the company. I figure out that that everybody is in the journey with you and then how do you create that scale to get the get the mass moving? Because it takes it takes a village thing. Get things done. >> Bradley. Jake is making history on the Cuba's, the first marketing CIA we've interviewed super excited, great insights. This is going to be a position we think's going around for a while, of course. The Cube coverage here on Adobe Summit. Jeffery, Jeffery Thanks for watching Stay with us from or Day one of two day coverage here in Las Vegas. After this short break

>> Live from Toronto Canada, it's The Cube, covering Global Cloud and Blockchain Summit 2018, brought to you by The Cube. >> Hello, everyone welcome back to The Cube's live coverage here in Toronto for the first Global Cloud and Blockchain Summit in conjunction with the Blockchain futurist happening this week it's run. I'm John Fourier, my cohost Dave Vellante, we're here with Cube alumni, Bradley Rotter, pioneer Blockchain investor, seasoned pro was there in the early days as an investor in hedge funds, continuing to understand the impacts of cryptocurrency, and its impact for investors, and long on many of the crypto. Made some great predictions on The Cube last time at Polycon in the Bahamas. Bradley, great to see you, welcome back. >> Thank you, good to see both of you. >> Good to have you back. >> So I want to just get this out there because you have an interesting background, you're in the cutting edge, on the front lines, but you also have a history. You were early before the hedge fund craze, as a pioneer than. >> Yeah. >> Talk about that and than how it connects to today, and see if you see some similarities, talk about that. >> I actually had begun trading commodity futures contracts when I was 15. I grew up on a farm in Iowa, which is a small state in the Midwest. >> I've heard of it. >> And I was in charge of >> Was it a test market? (laughing) >> I was in charge of hedging our one corn contract so I learned learned the mechanisms of the market. It was great experience. I traded commodities all the way through college. I got to go to West Point as undergrad. And I raced back to Chicago as soon as I could to go to the University of Chicago because that's where commodities were trading. So I'd go to night school at night at the University of Chicago and listen to Nobel laureates talk about the official market theory and during the day I was trading on the floor of the the Chicago Board of Trade and the Chicago Mercantile Exchange. Grown men yelling, kicking, screaming, shoving and spitting, it was fabulous. (laughing) >> Sounds like Blockchain today. (laughing) >> So is that what the dynamic is, obviously we've seen the revolution, certainly of capital formation, capital deployment, efficiency, liquidity all those things are happening, how does that connect today? What's your vision of today's market? Obviously lost thirty billion dollars in value over the past 24 hours as of today and we've taken a little bit of a haircut, significant haircut, since you came on The Cube, and you actually were first to predict around February, was a February? >> February, yeah. >> You kind of called the market at that time, so props to that, >> Yup. >> Hope you're on the right >> Thank you. >> side of those shorts >> Thank you. >> But what's going on? What is happening in the capital markets, liquidity, why are the prices dropping? What's the shift? So just a recap, at the time in February, you said look I'm on short term bear, on Bitcoin, and may be other crypto because all the money that's been made. the people who made it didn't think they had to pay taxes. And now they're realizing, and you were right on. You said up and up through sort of tax season it's going to be soft and then it's going to come back and it's exactly what happened. Now it's flipped again, so your thoughts? >> So my epiphany was I woke up in the middle of the night and said oh my God, I've been to this rodeo before. I was trading utility tokens twenty years ago when they were called something else, IRUs, do you remember that term? IRU was the indefeasible right to use a strand of fiber, and as the internet started kicking off people were crazy about laying bandwidth. Firms like Global Crossing we're laying cable all over the ocean floors and they laid too much cable and the cable became dark, the fiber became dark, and firms like Global Crossing, Enron, Enron went under really as a result of that miss allocation. And so it occurred to me these utility tokens now are very similar in characteristic except to produce a utility token you don't have to rent a boat and lay cable on the ocean floor in order to produce one of these utility tokens, that everybody's buying, I mean it takes literally minutes to produce a token. So in a nutshell it's too many damn tokens. It was like the peak of the internet, which we were all involved in. It occurred to me then in January of 2000 the market was demanding internet shares and the market was really good at producing internet shares, too many of them, and it went down. So I think we're in a similar situation with cryptocurrency, the Wall Street did come in, there were a hundred plus hedge funds of all shapes and sizes scrambling and buying crypto in the fall of last year. It's kind of like Napoleon's reason for attacking Russia, seemed like a good idea at the time. (laughing) And so we're now in a corrective phase but literally there's been too many tokens. There are so many tokens that we as humans can't even deal with that. >> And the outlook, what's the outlook for you? I mean, I'll see there's some systemic things going to be flushed out, but you long on certain areas? What do you what do you see as a bright light at the end of the tunnel or sort right in front of you? What's happening from a market that you're excited about? >> At a macro scale I think it's apparent that the internet deserves its own currency, of course it does and there will be an internet currency. The trick is which currency shall that be? Bitcoin was was a brilliant construct, the the inventor of Bitcoin should get a Nobel Prize, and I hope she does. (laughing) >> 'Cause Satoshi is female, everyone knows that. (laughing) >> I got that from you actually. (laughing) But it may not be Bitcoin and that's why we have to be a little sanguine here. You know, people got a little bit too optimistic, Bitcoin's going to a hundred grand, no it's going to five hundred grand. I mean, those are all red flags based on my experience of trading on the floor and investing in hedge funds. Bitcoin, I think I'm disappointed in Bitcoins adoption, you know it's still very difficult to use Bitcoin and I was hoping by now that that would be a different scenario but it really isn't. Very few people use Bitcoin in their daily lives. I do, I've been paying my son his allowance for years in Bitcoin. Son of a bitch is rich now. (laughing) >> Damn, so on terms of like the long game, you seeing the developers adopted a theory and that was classic, you know the decentralized applications. We're here at a Cloud Blockchain kind of convergence conference where developers mattered on the Cloud. You saw a great developer, stakeholders with Amazon, Cloud native, certainly there's a lot of developers trying to make things easier, faster, smarter, with crypto. >> Yup. >> So, but all at the same time it's hard for developers. Hearing things like EOS coming on, trying to get developers. So there's a race for developer adoption, this is a major factor in some of the success and price drops too. Your thoughts on, you know the impact, has that changed anything? I mean, the Ethereum at the lowest it's been all year. >> Yup. Yeah well, that was that was fairly predictable and I've talked about that at number of talks I've given. There's only one thing that all of these ICOs have had in common, they're long Ethereum. They own Ethereum, and many of those projects, even out the the few ICO projects that I've selectively been advising I begged them to do once they raised their money in Ethereum is to convert it into cash. I said you're not in the Ethereum business, you're in whatever business that you're in. Many of them ported on to that stake, again caught up in the excitement about the the potential price appreciation but they lost track of what business they were really in. They were speculating in Ethereum. Yeah, I said they might as well been speculating in Apple stock. >> They could have done better then Ethereum. >> Much better. >> Too much supply, too many damn tokens, and they're easy to make. That's the issue. >> Yeah. >> And you've got lots of people making them. When one of the first guys I met in this space was Vitalik Buterin, he was 18 at the time and I remember meeting him I thought, this is one of the smartest guys I've ever met. It was a really fun meeting. I remember when the meeting ended and I walked away I was about 35 feet away and he LinkedIn with me. Which I thought was cute. >> That's awesome, talk about what you're investing-- >> But, now there's probably a thousand Vitalik Buterin's in the space. Many of them are at this conference. >> And a lot of people have plans. >> Super smart, great ideas, and boom, token. >> And they're producing new tokens. They're all better improved, they're borrowing the best attributes of each but we've got too many damn tokens. It's hard for us humans to be able to keep track of that. It's almost like requiring a complicated new browser download for every website you went to. We just can't do that. >> Is the analog, you remember the dot com days, you referred to it earlier, there was quality, and the quality lasted, sustained, you know, the Amazon's, the eBay's, the PayPal's, etc, are there analogs in this market, in your view, can you sniff out the sort of quality? >> There are definitely analogs, I think, but I think one of the greatest metrics that we can we can look at is that utility token being utilized? Not many of them are being utilized. I was giving a talk last month, 350 people in the audience, and I said show of hands, how many people have used a utility token this year? One hand went up. I go, Ethereum? Ethereum. Will we be using utility tokens in the future? Of course we will but it's going to have to get a whole lot easier for us humans to be able to deal with them, and understand them, and not lose them, that's the big issue. This is just as much a cybersecurity play as it is a digital currency play. >> Elaborate on that, that thought, why is more cyber security playing? >> Well, I've had an extensive background in cyber security as an investor, my mantra since 9/11 has been to invest in catalyze companies that impact the security of the homeland. A wide variety of security plays but primarily, cyber security. It occurred to me that the most valuable data in the world used to be in the Pentagon. That's no longer the case. Two reasons basically, one, the data has already been stolen. (laughing) Not funny. Two, if you steal the plans for the next generation F39 Joint Strike Force fighter, good for you, there's only two buyers. (laughing) The most valuable data in the world today, as we sit here, is a Bitcoin private key, and they're coming for them. Prominent Bitcoin holders are being hunted, kidnapped, extorted, I mean it's a rather extraordinary thing. So the cybersecurity aspect of if all of our assets are going to be digitized you better damn well keep those keys secure and so that's why I've been focused on the cybersecurity aspect. Rivets, one of the ICOs that I invested in is developing software that turns on the power of the hardware TPM, trusted execution environment, that's already on your phone. It's a place to hold keys in hardware. So that becomes fundamentally important in holding your keys. >> I mean certainly we heard stories about kidnapping that private key, I mean still how do you protect that? That's a good question, that's a really interesting question. Is it like consensus, do you have multiple people involved, do you get beaten up until you hand over your private key? >> It's been happening. It's been happening. >> What about the security token versus utility tokens? A lot of tokens now, so there's yeah, too many tokens on the utility side, but now there's a surge towards security tokens, and Greg Bettinger wrote this morning that the market has changed over and the investor side's looking more and more like traditional in structures and companies, raising money. So security token has been a, I think relief for some people in the US for sure around investing in structures they understand. Is that a real dynamic or is that going to sustain itself? How do you see security tokens? >> And we heard in the panel this morning, you were in there, where they were predicting the future of the valuation of the security tokens by the end of the year doubling, tripling, what ever it was, but what are your thoughts? >> I think security tokens are going to be the next big thing, they have so many advantages to what we now regard as share certificates. My most exciting project is that I'm heavily involved in is a project called the Entanglement Institute. That's going to, in the process of issuing security infrastructure tokens, so our idea is a public-private partnership with the US government to build the first mega quantum computing center in Newport, Rhode Island. Now the private part of the public-private partnership by the issuance of tokens you have tremendous advantages to the way securities are issued now, transparency, liquidity. Infrastructure investments are not very liquid, and if they were made more liquid more people would buy them. It occurred to me it would have been a really good idea if grandpa would have invested in the Hoover Dam. Didn't have the chance. We think that there's a substantial demand of US citizens that would love to invest in our own country and would do so if it were more liquid, if it was more transparent, if the costs were less of issuing those tokens. >> More efficient, yeah. >> So you see that as a potential way to fund public infrastructure build-outs? >> It will be helpful if infrastructure is financed in the future. >> How do you see the structure on the streets, this comes up all the time, there's different answers to this. There's not like there's one, we've seen multiple but I'm putting a security token, what am i securing against, cash flow, equity, right to convert to utility tokens? So we're starting to see a variety of mechanisms, 'cause you have to investor a security outcome. >> Yeah, so as an investor, what do you look for? >> Well, I think it's almost limitless of what these smart securities, you know can be capable of, for example one of the things that were that we're talking with various parts of the government is thinking about the tax credit. The tax credit that have been talked about at the Trump administration, that could be really changed on its head if you were able to use smart securities, if you will. Who says that the tax credit for a certain project has to be the same as all other projects? The president has promised a 1.5 trillion dollar infrastructure investment program and so far he's only 1.5 trillion away from the goal. It hasn't started yet. Wilbur Ross when, in the transition team, I had seen the white paper that he had written, was suggesting an 82% tax credit for infrastructure investment. I'm going 82%, oh my God, I've never. It's an unfathomable number. If it were 82% it would be the strongest fiscal stimulus of your lifetime and it's a crazy number, it's too big. And then I started thinking about it, maybe an 82% tax credit is warranted for a critical infrastructure as important as quantum computing or cyber security. >> Cyber security. >> Exactly, very good point, and maybe the tax credit is 15% for another bridge over the Mississippi River. We already got those. So a smart infrastructure token would allow the Larry Kudlow to turn the dial and allow economic incentive to differ based on the importance of the project. >> The value of the project. >> That is a big idea. >> That is a big idea. >> That is what we're working on. >> That is a big idea, that is a smart contract, smart securities that have allocations, and efficiencies, and incentives that aren't perverse or generic. >> It aligns with the value of the society he needs, right. Talk about quantum computing more, the potential, why quantum, what attracted you to quantum? What do you see as the future of quantum computing? >> You know, you don't you don't have to own very much Bitcoin before what wakes you up in the middle of the night is quantum computing. It's a hundred million times faster than computing as we know it today. The reason that I'm involved in this project, I believe it's a matter of national security that we form a national initiative to gain quantum supremacy, or I call it data supremacy. And right now we're lagging, the Chinese have focused on this acutely and are actually ahead, I believe of the United States. And it's going to take a national initiative, it's going to take a Manhattan Project, and that's that's really what Entanglement Institute is, is a current day Manhattan Project partnering with government and three-letter agencies, private industry, we have to hunt as a pack and focus on this or we're going to be left behind. >> And that's where that's based out of. >> Newport, Rhode Island. >> And so you got some DC presence in there too? >> Yes lots of DC presence, this is being called Quantum summer in Washington DC. Many are crediting the Entanglement Institute for that because they've been up and down the halls of Congress and DOD and other-- >> Love to introduce you to Bob Picciano, Cube alumni who heads up quantum computing for IBM, would be a great connection. They're doing trying to work their, great chips to building, open that up. Bradley thanks for coming on and sharing your perspective. Always great to see you, impeccable vision, you've got a great vision. I love the big ideas, smart securities, it's coming, that is, I think very clear. >> Thank you for sharing. >> Thank you. The Cube coverage here live in Toronto. The Cube, I'm John Furrier, Dave Vellante, more live coverage, day one of three days of wall-to-wall coverage of the Blockchain futurist conference. This is the first global Cloud Blockchain Summit here kicking off the whole week. Stay with us for more after this short break.

(upbeat music) >> Announcer: Live, from Nassau, in the Bahamas. It's theCUBE, covering Polycon '18, brought to you by Polymath. >> Hello everyone, welcome. We're live here in the Bahamas. This is theCUBE's exclusive coverage of the crypto-world, blockchain, bitcoin, all kinds of tokens, token economics. I'm John Furrier, with my co-host and co-founder of SiliconANGLE and theCUBE, Dave Vellante. We're here to cover the securitization of tokens, as well as all the action in the ecosystem. What's going on with token economics? What's going on in the ICO world? Who's investing in what? Who are the players? That's our job this week. We're going to get it done in two days. Our first guest to help us kick it off is Bradley Rotter. Crypto investor for five years, been in the securities, hedge funds, financing business, over the years great perspective to kick off, from an investor point of view, what's going on. Bradley, welcome to theCUBE. >> Thank you. >> Thanks for coming on. >> Thanks for being a guest analyst to help us break down what's going on, obviously, you've got a lot of investments. You've got portfolio companies, one which you wear on your shirt on Rivetz, they've done token sale around cyber security, but as an investor in general, you're long on this game. Are you long on crypto, are you doing deals? What's going on? >> I've been very long in crypto from a very early, early time, five years ago. I heard about crypto from a 15 year old, which got my interest. I had been one of the pioneers in an Aztec class that reminds a lot of bitcoin, and that was financial futures. Remember when those came out? It was controversial, people were saying, it'll never work. I was thrown out of some of the finest banks in Chicago and New York, trying to explain to those institutions how they could use financial futures to hedge interest rate risk. It kind of reminds me now of bitcoin, but you can see the tide turning now, and it's in all the headlines. >> Yeah, I mean, we, Dave and I talk all the time about this, and that is, is that, and I'll get your thoughts on this, and get your reaction. You're seeing startups, really startups, doing token raises, and ICOs, initial coin offerings, and they need to grow. They got to build their product, then there's a roadmap. Then you got the companies that are pivoting, hey, let's just reboot with crypto, and raise a bunch of cash, and hope for the best. And then you got businesses that are growing, that really are aligned with token economics, most of the investors we talk to say that's where the action is, that okay, if they're going to be startup, then go with a hedge fund, and that's more nurturing, a lot more of a classic, you know, venture, capital-backed investment, but it's the growth companies that they're looking for. >> Yes. >> Do you see it that way, too, and what's your reaction to that? >> I think the issuance of tokens as securities is going to be a pretty big deal. And it's primarily, what I'm extremely interested in is using tokenization for infrastructure, for gigantic projects. It hasn't happened, yet, but I think I have ideas on how very large projects could be tokenized, and that gives some real advantages to the individual investor. >> Dave: You mean, like, what big projects, smart cities? Give me some examples. >> Well, this is my favorite example is that someday you'll be able to buy, you'll be able to buy a three mile stretch of a toll road in Texas. And as the owner of that three mile stretch, you'll get 25 cents a car credited every minute of the cars that are going down your stretch of toll road. You see what I'm saying. If you tokenize that infrastructure, you can then, it makes it more available to individual investors, but if you tokenize it, you can borrow against your token, your shares, if you will, you could hypothecate it, borrow against it. The tax credits for your infrastructure investment, could be tied to the token itself, and vary depending on, on the need for that particular infrastructure project and I think this administration, more than any I've ever seen, you know, is going to be very open to those kinds of ideas, and I think it's transformational. >> So that is transformational, being able to address our infrastructure problems with blockchain, (laughs) right? That's your vision. >> Exactly. >> So I want to get, Dave, your reaction. You were just in the keynote. We're here at the Polycon '18, it's put on by Polymath and Grit Capital. Two Canadian organizations, but bringing kind of the world together. You were in the keynote, they're selling a security token platform, so people can raise money with security tokens, which is really good, because SEC regulation in the US, it's a lot cleaner than the utility token, and for folks who want to learn more, go to YouTube, watch some of the videos that we've done on ICO 101. But Dave, what did you see in there? And then, Bradley you're going to get your thoughts on how you see it. >> Well a couple things. One is, and now it's biased, but the consensus in that audience, was that security tokens are going to dwarf the value of utility tokens, over time. Like massive dwarfing, number one. Number two is you're seeing a real mix of companies that are tokenizing their business. New companies, companies trying to solve problems, you know, this new internet we're building out, existing companies that are looking to transform, and have a logical reason to tokenize their business, so there's a lot of diversity going on. >> Your perspective as an investor. Security tokenization as opportunity for businesses to use and raise money and use capital. I mean, you got to secure something, I mean, security token is (laughs) >> Well this market has been so hot that investors have swayed a little bit from their typical diligence, and so forth. I think they'll soon start to realize by buying these utility tokens. In many cases, there's not much utility. In fact, you know, I ask everybody I see, have you used a utility token today? No one's really using utility tokens now. And so, we've got to keep that in mind. The carts a little bit in front of the horse. Will we use them? You know, I believe so, but we're going to have to make it really easy to use. Do we need 2000 tokens? I don't think so, it's going to be complicated. >> Dave: So what do you look for as an investor? As a reasonable profile, or an attractive profile, is it equity in the company, is it a rev share, or is it the utility of the function? >> I have done both. My first utility token was a company called MaidSafe. And I heard about MaidSafe from a 14 year old bitcoin miner, I always listen to 14 year olds, also. (all laugh) This young man said, this young man had approached me after I was giving a speech on cryptocurrency. We went out for a drink, in this case Diet Coke, and he told me about this company called MaidSafe. I went home and started looking at it, I was up til 4:30 in the morning, and a week later I was climbing on a plane to Troon, Scotland to go meet the developers. What was MaidSafe, what caught my eye? MaidSafe was a distributed, decentralized, peer-to-peer, self-authenticating, self-managed network that runs on math and logic, all the data's encrypted, shard-ed, sent around to the nodes around the world, and then the map of where those shards go is then encrypted again. It's NSA-proof. >> Beautiful. Dave you brought this up the other day, and we talked about it at the pool, we did a segment on a kick off about this event. We've been talking about digital transformation, vis-a-vis some of the old guard companies, the either central authorities, and/or incumbent laggards, or leaders. This token economics is part of the digital transformation that a lot of people aren't seeing. Right, so, you know, you said you'd been kicked out of many banks, you've still got these crazy ideas that are actually the ones that might actually be the best. And we think they are. Your thoughts, Dave, as you look at, you know, the digital transformation. Oh you got to have a digital business. You need to use the power of data. Data's the new oil, you know, cloud computing. Now you got this new variable coming in, decentralized, distributed data, what's your thoughts? >> I mean, I see, you know, we talk on theCUBE, we talk about SAAS, and cloud, and mobile, and social, and big data, that's yesterday. That's yesterday's news. To me, the future is, you know, machine intelligence, it certainly starts with data, and it starts with, And crypto, launching it plays a key part of building out that next wave of technology. And I see every industry being disrupted at different paces, as a function of, maybe, the risk within that industry. You've certainly seen it publishing, media, music. You really haven't seen it yet in banking, healthcare, but these are the industries that need the most transformation. What are your thoughts, Bradley? >> Well the banks better be paying attention to this. I think, if we're right about cryptocurrency, banks will become as plentiful and as useful as Blockbuster Video stores. >> I mean, I got to tell you, in my experience, the old guard, the disruption is going to come really fast. I think, and my prediction is that, and again, this is based on my history in the computer industry, is if you look at the billion dollar ideas, they're the dumbest ideas, at first. >> Yeah (laughs) >> I mean you go down the line. Google, we don't need another search engine, we want portals. Keyword navigation, the one I did, no, who would ever pay for a link on a search result? That's the dumbest idea. Airbnb, you're going to sell out your home? That's the dumbest idea I ever heard of. The dumbest ideas actually might be the best if you look at them. And when I say dumbest, it might be ones that don't make sense. Like you mentioned that one about Scotland, that technically makes sense, I get that. But someone in the mainstream would be like, huh, what? I got to do all this stuff? It's just. So it's kind of what's going on right now, isn't it? >> And if there's any fabric that connects all of those different ecospheres that you were talking about, I think it's going to be cybersecurity is extremely important. It's not generally discussed at these kind of events, but I view this just as much as a cybersecurity play, as I do a digital currency play. And let me expand on that. The most valuable data in the world used to be in the Pentagon. No longer. Two reasons basically, one-- [John] They've been hacked (laughs) >> All the data's already gone. But, two, if you steal the plans for the next generation F-39 joint strike force fighter, good for you, there's only two buyers for that. I believe the most valuable data in the world right now is a bitcoin private key. And people are coming for them. Members of the bitcoin community are being hunted, singled out and hunted to try to get their bitcoins. It's a real distinct phenomena. >> I like that term you used, fabric, because we kind of envision this fabric emerging where you've got industries which are sort of vertical-sliced, and then you've got these horizontal technologies, whether it's cloud, security, there's a data layer, and people are building businesses on top of them, and obviously tokenizing those businesses. We talked last night a little bit, and you guys are networking guys. You understand the challenges of distributed apps, distributed database, the latency challenges. You're a little bit bearish on the market right now. Is it because of those technical challenges, is it because there's so much Bubbalicious, you know, attitude going on? What are your thoughts? >> I've been a little bit bearish on bitcoin for the very short run, and of course it's, it's been in the headlines. At year end, it was the front headline in every journal you read. The reason I've been a little bit negative is purely for a tax perspective. And these, Let me explain why, these millennials that I collect, and I keep them around me just to guide me and, and give me a glimpse of the future. Most of the people at this conference, believe that when they buy bitcoin and sell it, and buy Ethereum and sell Ethereum and buy Cardano, that those are all like kind exchanges and no tax will be due, until they ever come back into Fiat dollars. They're absolutely incorrect. Absolutely incorrect. And so-- >> So they're exposed? >> They're really exposed, that's why I believe cryptocurrencies in general, bitcoin specifically have been very weak this year and probably will remain weak until April 16th. People are getting their tax bill which is difficult to calculate with thousands of transactions, in some cases. They're getting their tax bill, and they're going to have to sell some of their crypto holdings to pay Uncle Sam. It's a US phenomena, but-- >> But it's like people who exercised their options in, you know, 2000-- >> Exactly. >> And held on to the shares and then got crushed. >> The tax liability is fixed at December 31, but now the value of their collateral has gone down. It's a problem. >> Bradley, thanks for coming on, kicking off the show with us, getting your vision on investing. Dave good to hear about the keynote. More live coverage coming here from Polycon '18. The stampede is on, this is the show around security tokens in the Bahamas, theCUBE. We'll be right back with more live coverage after this short break. (upbeat music)

>> Narrator: Live from San Francisco It's the Cube. Covering DevNet Create 2017. Brought to you by Cisco. >> Welcome back everyone. Live in San Francisco, this is the Cube's exclusive coverage of the inaugural event for Cisco systems DevNet Create. It's an extension or augmentation, a foot in the water of the new open source world for them. Cloud native DevOps infrastructure is code. It's Cisco's new mission, where applications meets infrastructure AKA infrastructure's code which is music to the ears of DevOps and all application developers. I'm John Furrier. My cohost Peter Burris, Head of Research at wikibon.com. Our next guest is Bradley Wong, Director of Product Management at Docker. Bradley welcome to the Cube. Good to see you again. >> Yeah, great, Thanks John. >> Docker, no other company to reference in terms of being a shining star in a paradigm shift or transformation where containers, Docker containers, and now containers and Kubernetes microservices has taken cloud and brought it into a whole nother dimension. We've been covering you guys at all your Dockercon events. It's been gray multiple years. Congratulations for your success. >> Bradley: Thank you. >> You got to be happy that you got Cisco coming out saying hey we're going to make the network programmable. Finally! You know, let's do it. Thoughts? >> Yeah, we're very excited about that. It's kind of interesting because we also found that networking is also one of those things that's quite difficult. And we saw this challenge probably about more than two years ago, after people started to get more comfortable with containers and they wanted to start doing some more interesting things with them and start getting the containers to talk to each other and the rest of the world. That's kind of really where we saw that networking could be improved upon. And I think maybe you remember, probably about two years ago now, maybe more actually, we made an acquisition company called SocketPlane? >> John: Yep. That really helped us define what it means to really do networking properly. And that was actually the genesis of where even the Cisco partnership also started devolving as well, because at Docker we really needed to build out a framework for how to do networking properly internally first. And we always followed a mantra, the mandate of batteries included but swappable. So, we built a reference implementation of what it meant to do networking properly for containers. But, in doing so we also then worked quite closely with Cisco to also bring their many, many years of expertise to the table as well. So, and you can probably see that now with the culmination of projects like Contiv, which is actually now a certified plug-in on Docker store. Cisco's really stepped it up and has really made lots of really great inroads and done a lot of good additions to Docker networking. >> It always seems that way. The conversation, we've been also following a lot of other communities, like OpenStack for instance, there's always debates but it always gets down to ay the network, network. I've had so many customers (mumbles) It's really hard. And also you see Cisco get pulled into conversations just but gravity pulling them in because they're the network guys. So now, it's nice to see that the executives at Cisco, led by Susie Wee and the team and Rick, not just puttin' their toe in the water, they're jumpin' in the deep end here with the cloud native approach by going to developers and outreaching to them in a different way and saying look it, we want to make your life easier. >> Bradley: Absolutely. >> That's what you guys have done. So certainly a success to you guys who are in Cisco, doing the work around the fringes but now that they're coming in, how do you, how would you tell someone, describe that move for Cisco? I mean, obviously Cisco has not been absent. They've been there with you guys. >> Bradley: Yeah. >> What does this really mean for them as they go fully committing here now? Right, that's a good question. Cisco is beyond just a, obviously, a networking company that's kind of' where it's roots came from. But we saw that there was some good opportunities to work with Cisco, not just on networking but a few other things. I think what a lot of people probably get familiar with Docker because it's a great development tool to start. And that's really where people's first interactions with Docker really is. It's really easy to get started, really easy to start building your applications in Docker, and start moving those applications into other environments, like going from Dev into Tes into Prod very, very seamlessly. So, Docker really becomes that sort of what we call a software supply chain that really enable Dev and Ops to use the same tooling, the same tool chain, end to end. And we feel that if we're able to use the same tool chain end to end, from Dev all the way through to Ops, we alleviate a lot of the challenges to deploying applications to production. Now, Cisco so far has been very, very strong in the Ops space, very strong in the infrastructure space, and we also come very, very strongly from the developer space as well. So, I think as we basically build out this software supply chain, there also is a need to make sure that there is this kind of underlying infrastructure that's also ready to run that software supply chain as well and to really harden it. And that's what, one of the first things that we really did with Cisco is to make sure that we have a very clear vision of how to make that operationalizable for the enterprise. >> Second time I've heard the word software supply chain. Peter's also used the word data supply chain. Data is asset (mumbles) software. Software is an asset. It's data as well. What is software supply chain mean? Describe that for a second. Take a minute to explain. >> So yeah, that's a good question. So in any supply chain I think there's sort of a progression of where there's inputs, where things come in and for us, we're on a mission to build tools of mass innovation. So, we really want to start with the developer and that's really where a lot of really good stuff comes from. Everyone's got great ideas and we piece those ideas together, give them the tools that they know how to use really well to develop them. But, it's not just good to have great applications, they need to be usable and they need to be able to be deployed. And what we believe the software supply chain is taking that development process and being able to have developers put their artifacts inside containers and then move those, because that's really what it is, it's actually moving those artifacts into places where they can be shared with greater teams to start testings those and to start iterating on those. And ultimately to move those into production whether it's on premise or whether it's in the cloud. And that's what we believe that we enable, is that movement of, and that >> John: Coding motion. >> Exactly. Exactly. And that doesn't stop there because, as you know, code is not stable. There's always iterative process and we enable that as well. So then , as we find issues or enhancements that we want to fix in production, we move that back to developer and that whole process starts again. Be able to do that really, really, quickly is what we want to do. >> So let's stay in that metaphor for a second. If we think about this as a software supply chain, Does that make Cisco a logistics supplier? >> I would say, with any supply chain, Cisco, once again, has lot's of different areas that they're focusing in and by no means am I speaking on behalf of Cisco where >> Peter: I understand. Just conceptually, are they the Ryder trucking, are they the ones responsible for moving things around? >> Yes, that's one of the places that Cisco does play very, very strongly in. For example, we identified that the computer platform that Cisco has, the UCS platform, is a great place to actually run Docker in production, especially on premise. And that's definitely one of the things that we needed to start validating, all these different infrastructures, that can actually have the right availability, the right performance characteristics, and things that then we can do together to make sure that these are essentially solid infrastructures to actually run these production environments on. Now, Cisco's been running solid enterprise infrastructure for many, many years. Docker's been running Dockerize applications also for many years as well. The marriage of the two, we hope and we believe that will culminate in a lot of the enterprises, which were very accountable at running enterprise applications on top of enterprise infrastructure, to now run Docker applications on enterprise infrastructure as well. So, just making sure that there is very, very good infrastructure that's in place to actually host that supply chain, I think that's definitely one of the key areas that we are hoping to get out of this partnership with Cisco. >> So now that we've talked about here in the last couple days (mumbles) is Conway's Law. And I'm sure you're familiar with Conway's Law. >> Bradley: Right. >> Which is basically the observation that the software that's generated is a reflection of the organization that generated it. You can use Docker or any other container technology to create really crappy software if you want to. >> Bradley: Yep. But one of the things that Docker does introduce is the idea of segmentation, compartmentalization, while at the same time simplified mechanics for how things work together. So talk a little bit about the expectations of people who get into the Docker and container world should have of the network. How should they think about, should they think about their software as essentially distributed elements that then require a network? What's your thoughts on that architecturally? How is it going to play out? >> It really depends on where their journey sits. Once again, I think we are the suppliers of these tools of innovation. But we want to also hold their hand as well through this journey. And that journey is not done day one. It's a step by step process as well. So, a good example is you can start off and build the greatest distributed microservice application and that might work well for certain parts of your company, but there's certainly many, many other applications that are already deployed out there, which it may not fit, at least not today, and there's a journey to take those existing, traditional applications along that journey as well. So, anything that basically requires interaction, with other components, any services that need to talk to each other, to the external world, obviously requires a network. Networking has been a very, very tough thing in the past. They're not always the simplest. Sometimes it could be over complicated. >> Peter: Sometimes? >> (laughs) Many, Many times. >> In all honesty, I do think that the network professionals have gone out of their way to make the network as obscure and abstract as possible. >> Bradley: You know, I think >> John: They're command line guys. Come on. (laughs) >> I've been in the networking world for a long time as well, before joining Docker. So, I see some of that. I think networking guys tend to, and girls, tend to really look at what are all the different things that we can do, all the different little knobs that we can actually tweak to squeeze every little bit of performance, convergence time, things like that, that might work well in some environments but may not others. That's why you needed so much variability, hence all these nerd knobs, so to speak. Docker comes from a very different place. If you look at the mentality of how we drive things, Usability is a very, very key thing for us. We talk about usable security, we talk about simple orchestrator, (mumbles) for example, We forgo the complex to focus on things that are usable. So, networking for us, we wanted to initially look at it and say, networking should be something that's simple and usable and essentially get out of the way of the developer. Developers shouldn't have to think about all these overcomplicated concepts. The network should be able to form its way around what the application needs and that's really what we're thinking about there. >> Peter: Make it simpler and no simpler than it needs to be. >> John: And make it programmable. >> Bradley: And make it programmable as well. Simple and programmable. And when I say programmable, we're not expecting Ops folks to have to learn how to code necessarily. I think if there's the right tools that are available, that should be a natural flow on. >> You have to enable it so that the app developer doesn't have to do all the hard stuff, like configuration management, all the hardware and the operational stuff that the networking guys have done for them. >> Bradley: Right. >> 'Cause they're not Ops guys right? They're Devs. >> That's a really good point because today, there is not really one single tool chain, and coming back to my earlier point, of what we're trying to solve for. There's not really one single tool chain that Ops folks use, and application developers use. They traditionally use different tooling. What we're trying to do is, first to have that common foundation of common tooling that people can converge on. And the second then is, if we provide all the right hooks, so, just enough hooks for the application developer to say, this is what my application looks like and then enough hooks for the operations folks then plug in and say hey, these are my security policies. These should talk to these and these shouldn't talk to these. And once we have the right ingestion points there, we should be able to take that end to end without having to manually ingest all these different after the fact concepts into that development process. It should be a natural flow on. We're not saying the work is done there. There's still a lot of things to do. But I think the first glimpse of what we have there is stunning. Docker, as you may know, has some great tools to define what an application is. Docker Compose, for example, you can see how a multi-service application is laid out. Cisco can actually then, provide plug-ins into that composed (mumbles) and say well, this web tier needs to talk to this application tier, and these are the basic premises of what networking security tools can then plug into to enforce policy. So, we feel that that can be a lot more automated. And we'll work towards that. >> Bradley, thanks so much for coming on the Cube. Really appreciate it. Great to see ya again. And Docker obviously continuing to do great and we'll continue to cover all your events. But my final question for you is, Take a minute to just explain quickly and succinctly for the audience, the Docker Cisco relationship. What is that? I mean, joint partnership? Is it, you guys just hi fivin' each other? You actually writin' code together? Is there a technology partnership? Give some details on the relationship. >> Yeah, sure. It's a strategic partnership, which basically means that it goes beyond just hi fiving each other. There's some of that as well but we believe that any relationship of this size needs to be built on solid attainable things. So, we worked on the Contiv project together, for example. We also worked together on what we call Cisco validated designs for Docker. >> John: Just joint engineering. >> Joint engineering work. We also work on joint marketing and joint go to market motions as well and joint support. So, you can actually call up Cisco for a Docker, Cisco solution that's deployed out there, you can call up Cisco support and they will hold that trouble ticket and if any troubles do arise, they take the call and then work on that on behalf of us. >> It's a nice relationship. It's a win-win. They get some cloud native mojo with Docker and this new app world. You guys get enterprise access to the huge amount of clients that they have. >> Bradley: Exactly. Alright, final, final question, Since one just popped in my head. It always happens that way when you're going to roll. But, what's on the roadmap for you guys with respect to the Cisco and this DevNet Create, obviously is going to their foray into this new world and bring in a new eco system with DevNet their core application, I mean, their core developer community, What's on the Docker roadmap? What can we expect to see that's going to be fruits of the labor? >> I think one of the things that we're definitely going to be focusing quite a lot on is to look at that first step of that journey, which is even taking, not just the microservices, that everyone loves to talk about, but even the traditional applications, those monolithic applications that are already deployed out there running mission critical enterprise workloads on there, We want to take those, together with partnerships, like Cisco, and Dockerize those. And eventually, modernize them and eventually evolve them into microservices. >> Yeah, might get those mission critical apps microservicized if that's a word. (laughs) Bradley Wong, Director of Product Management, Great to see you. Thanks for coming on the Cube. Live coverage at the Cube here at the Cisco's inaugural event. Again, great show. (mumbles) I'm John Furrier with Peter Burris. More analysis and commentary and interviews after this short break. (robotic music) >> Hi, I'm April Mitchell and I'm the Senior Director of Strategy

>> Narrator: From Austin, Texas, it's theCUBE covering DockerCon 2017, brought to you by Docker and support from it's ecosystem partners. (upbeat music) >> Hi, and we're back, I'm Stu Miniman, and this is SilconANGLES production of the Cube, here at DockerCon 2017, Austin, Texas. Happy to have on the program Kiran Kamity, who was CEO of ContainerX which was acquired by Cisco. And you're currently the senior director and head of container products at Cisco. And also joining us is Brad Wong, who is the director of product management at Docker. Gentlemen, thank you so much for joining us. >> Brad: Thanks for having us. [Kiran] Thank you, Stu. >> So Kiran, talk a little bit about ContainerX, you know, bring us back to, why containers, you know why you help start a company with containers, and when to be acquired by a big company like Cisco. >> Yeah, it was actually late 2014 is when Pradeep and I, my co-founder from ContainerX, we started brainstorming about, you know, what do we do in the space and the fact that the space was growing, and my previous company called RingCube, which has sold to Citrix, where we had actually built a container between 2006 and 2010. So we wanted to build a management platform for containers, and it was in a way there was little bit of an overlap with Docker Datacenter, but we were focusing on mostly tendency aspects of it. Bringing in concepts like viamordi rs into containers et cetera. And we were acquired by Cisco about eight months ago now, and the transition in the last eight months has been fantastic. >> Great, and Brad, you're first time on the cube, so give us your background, what brought you to Docker? >> Yeah, so actually before Docker I was at actually, a veteran of Cisco, interestingly enough. Many different ventures in Cisco, most recently I was actually part of the Insieme Networks team, focusing on the software defined networking, and Application Centric Infrastructure. Obviously I saw a pretty trend in the infrastructure space, that the future of infrastructure is being led by applications and developers. With that I actually got to start digging around with Docker quite a lot, found some good interest, and we started talking, and essentially that's how I ended up at Docker, to look at our partner ecosystem, how we can evolve that. Two years ago now, actually. >> I think two years ago Docker networking was a big discussion point. Cisco's been a partner there, but bring us up to speed if you would, both of you, on where you're engaging, on the engineering side, customer side, and the breadth and depth of what you're doing. >> You're right, two years ago, networking was in quite a different place. We kicked it off with acquiring a company back then called SocketPlane, which helped us really define-- >> Yeah and we know actually, ---- and ----, two alums, actually I know those guys, from the idea to starting the company, to doing acquisition was pretty quick for you and for them. >> Right, and we felt that we really needed to bring on board a good solid networking DNA into the company. We did that, and they helped us define what a successful model would be for networking which is why they came up with things like the container networking model, and live network, which then actually opened the door for our partners to then start creating extensions to that, and be able to ride on top of that to offer more advanced networking technologies like Contiv for example. >> Contiv was actually an open source project that was started within Cisco, even before the container was acquisitioned. Right after the acquisition happened, that team got blended into our team and we realized that there were some really crown jewels in Contiv that we wanted to productize. We've been working with Docker for the last six months now trying to productize that, and we went from alpha to beta to g a. Now Contiv is g a today, and it was announced in a blog post today, and it's actually 100% open-source networking product that Cisco TAC and Cisco advanced services have offered commercial support and services support. It's actually a unique moment, because this is the fist 100% open-source project that Cisco TAC has actually offered commercial support for, so it's a pretty interesting milestone I think. >> I think also with that, we also have it available on Docker store as well. It's actually the first Docker networking plug-in that it's been certified as well. We're pretty also happy to have that on there as well. >> Yeah. >> Anything else for the relationship we want to go in beyond those pieces? >> We also saw that there was a lot of other great synergies between the two companies as well. The first thing we wanted to do was to look at how we can also make it a lot better experience for joint customers to get Docker up and running, Docker Enterprise Edition up and running on infrastructure, specifically on Cisco infrastructure, so Cisco UCS. So we also kicked off a series of activities to test and validate and document how Docker Enterprise Edition can run on Cisco UCS, Nexus platforms, et cetera. We went ahead with that and a couple months later we brought out, jointly, to our Cisco validated designs for Docker Enterprise Edition. One on Cisco UCS infrastructure alone, and the other one jointly with NetApp as well, with the FlexPod Solution. So we're also very very happy with that as well. >> Great. Our community I'm sure knows the CVD's from what they are out there. UCS was originally designed to be the infrastructure for virtualized environments. Can you walk me through, what other significant differences there or anything kind of changing to move to containers versus what UCS for virtualized environment. >> The goal with that, UCS is esentially considered a premium kind of infrastructure server infrastructure for our customers. Not only can they run virtual environments today, but our goal is as containers become mainstreamed, containers evolved to being a first-class citizen alongside VM. We have to provide our customers with a solution that they need. And a turnkey solution from a Cisco standpoint is to take something like a Docker stack, or other stacks that our customer stopped, such as Kubernetes or other stacks as well, and offer them turnkey kind of experience. So with Docker Data Center what we have done is the CVD that we've announced so far has Docker Data Center, and the recipe provides an easy way for customers to get started with USC on Docker Data Center so that they get that turnkey experience. And with the MTA program that was announced, today at the key note. So that allows Cisco and Docker to work even more closely together to have not just the products, but also provide services to ensure that customers can completely sort of get started very very easily with support from advanced services and things like that. >> Great, I'm wondering if you have any customer examples that you can talk through. If you can't talk about a specific, logo, maybe you can talk about. Or if there are key verticals that you see that you're engaging first, or what can you share? >> We've been working joint customer evals, actually a couple of them. Once again I don't think we can point out the names yet. We haven't fully disclosed, or cleared it with their Prs Definitely into financials. Especially the online financials, a significant company that we've been working with jointly that has actually adopted both Contiv, and is actually seeing quite a lot of value in being able to take Docker, and also leverage the networking stack that Contiv provides. And be able to not just orchestrate networking policies for containers, but the other thing that they want to do is to have those same policies be able to run on cloud infrastructure, like EWS for example. So they obviously see that Docker is a great platform to be enable their affordability between on premises and also public cloud. But at the same time be able to leverage these kind of tools that makes that transition, and makes that move a lot easier so they don't have to re-think their security networking policies all over again. That's been actually a pretty used case I thought of the joint work that we did together with Contiv. >> Some of the customers that we've been talking to in fact we have one customer that I don't think I'm supposed say the name just yet, but we've drollled it out, has drolled out Contiv with the Docker on time. In five production data centers already. And these are the kind of customers that actually take to advanced networking capabilites that Contiv offers so that they can comprehensive L2 networking, L3 networking. Their monitoring pools that they currently use will be able to address the containers, because the L2, the L3 networking capabilities allows each container to have an IP address that is externally addressable, so that the current monitoring tools that you use for VMs et cetera can completely stay relevant, and be applicable in the container world. If you have an ACI fabric that continues to work with containers. So those are some of the reasons why these customers seem to like it. >> Kiran, you're relatively new into Cisco, and you were a software company. Many people they still think of Cisco as a networking company. I've heard people derogatory it's like, "Oh they made hardware define networking when they rolled out some of this stuff." Tell us about, you talk about an open source project that you guys are doing. I've talked to Lou Tucker a number of times. I know some of the software things you guys are doing. Give us your viewpoint as to your new employer, and how they might be different than people think of as the Cisco that we've known for decades. >> Cisco is, has of course it has, you know, several billion dollars of revenue coming in from hardware and infrastructure. And networking and security have been the bread and the butter for the company for many many years now But as the world moves to Cloud-Native becoming a first class citizen, the goal is really to provide complete solutions to our customers. And if you think of complete solutions, those solutions include things like networking, thing like security. Including analytics, and complete management platforms. At the same time, at the end of the day, the customers want to come to peace with the fact that this is a multi-cloud world Customers have data centers on premises, or on hosted private cloud environments. They have workloads that are running on public clouds. So with products like cloud center, our goal is to make sure that whatever they, the applications that they have, can be orchestrated across these multiple clouds. We want to make sure that the pain points the customers have around deploying whole solutions include easy set-up of products on infrastructure that they have, and that includes partnerships like UCS, or running on ACI or Nexus. We want to make sure that we give that turnkey experience to these customers. We want to make sure that those workloads can be moved across and run across these different clouds. That's where products like cloud center come in. We want to make sure that these customers have top grade analytics, which is completely software. That's were the app dynamics acquisition comes in. And we want to make sure that we provide that turnkey experience with support in terms of services. With our massive services organization, partners, et cetera. We view this as our job is to provide our customers what they need in terms of the end solution that they're looking for. And so it's not just hardware, it's just a part of it. Software, services, et cetera, complimented. >> Alright, Brad last question that I have for you in the keynote yesterday, I couldn't count how many times the word ecosystem was used. I think it was loud and clear that everybody there I think it was like, you know, Docker will not be successful unless it's partners are successful, kind of vice versa. When you look at kind of the product development piece of things, how does that resonate with you and the job that you're doing? >> We basically are seeing Docker become more of a, more and more of a platform as evidenced by yesterdays keynote. Every platform, the only way that platform's going to be successful is if we can do great, we have great options for our partners, like Cisco, to be able to integrate with us on multiple different levels, not just on one place. The networking plug-in is just one example. Many many other places as well Yesterday we announced two new open source initiatives. Lennox kit and also the movi project. You can imagine that there's probably lots of great places where partners like Cisco can actually play in there, not just only in the service fees, but maybe also in things like IOT as well, which is also a fast-emerging place for us to be. And all the way up until day two type of monitoring, type of environment as well where we think there's a lot of great places where once again, options like app dynamics, tetration analytics can fit in quite nicely with how do you take applications that have been migrated or modernized into containers, and start really tracking those using a common tool set. So we think that's really really good opportunities for our ecosystem partners to really innovate in those spaces, and to differentiate as well. >> Kiran, I want to give you the final word, take-aways that you want the users here, and those out watching the show to know about, you know, Cisco, and the Docker environment. >> I want to let everybody know that Cisco is not just hardware. Our goal is to provide turnkey complete solutions and experiences to our customers. And as they walk through this journey of embracing Cloud-Native workloads, and containerized workload there's various parts of the problem, that include all the way from hardware, to running analytics, to networking, to security, and services help, and Cisco as a company is here to offer that help, and make sure that the customers can walk away with turnkey solutions and experiences. >> Kiran and Brad, thank you so much for joining us. We'll be back with more coverage here. Day two, DockerCon 2017, you're watching theCube.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. 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 Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. 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 beginning) >> From the Cube Studios in Palo Alto and Boston, bringing you data-driven insights from the Cube and ETR, this is "Breaking Analysis" with Dave Vellante. >> Making predictions about the future of enterprise tech is more challenging if you strive to lay down forecasts that are measurable. In other words, if you make a prediction, you should be able to look back a year later and say, with some degree of certainty, whether the prediction came true or not, with evidence to back that up. Hello and welcome to this week's Wikibon Cube Insights, powered by ETR. In this breaking analysis, we aim to do just that, with predictions about the macro IT spending environment, cost optimization, security, lots to talk about there, generative AI, cloud, and of course supercloud, blockchain adoption, data platforms, including commentary on Databricks, snowflake, and other key players, automation, events, and we may even have some bonus predictions around quantum computing, and perhaps some other areas. To make all this happen, we welcome back, for the third year in a row, my colleague and friend Eric Bradley from ETR. Eric, thanks for all you do for the community, and thanks for being part of this program. Again. >> I wouldn't miss it for the world. I always enjoy this one. Dave, good to see you. >> Yeah, so let me bring up this next slide and show you, actually come back to me if you would. I got to show the audience this. These are the inbounds that we got from PR firms starting in October around predictions. They know we do prediction posts. And so they'll send literally thousands and thousands of predictions from hundreds of experts in the industry, technologists, consultants, et cetera. And if you bring up the slide I can show you sort of the pattern that developed here. 40% of these thousands of predictions were from cyber. You had AI and data. If you combine those, it's still not close to cyber. Cost optimization was a big thing. Of course, cloud, some on DevOps, and software. Digital... Digital transformation got, you know, some lip service and SaaS. And then there was other, it's kind of around 2%. So quite remarkable, when you think about the focus on cyber, Eric. >> Yeah, there's two reasons why I think it makes sense, though. One, the cybersecurity companies have a lot of cash, so therefore the PR firms might be working a little bit harder for them than some of their other clients. (laughs) And then secondly, as you know, for multiple years now, when we do our macro survey, we ask, "What's your number one spending priority?" And again, it's security. It just isn't going anywhere. It just stays at the top. So I'm actually not that surprised by that little pie chart there, but I was shocked that SaaS was only 5%. You know, going back 10 years ago, that would've been the only thing anyone was talking about. >> Yeah. So true. All right, let's get into it. First prediction, we always start with kind of tech spending. Number one is tech spending increases between four and 5%. ETR has currently got it at 4.6% coming into 2023. This has been a consistently downward trend all year. We started, you know, much, much higher as we've been reporting. Bottom line is the fed is still in control. They're going to ease up on tightening, is the expectation, they're going to shoot for a soft landing. But you know, my feeling is this slingshot economy is going to continue, and it's going to continue to confound, whether it's supply chains or spending. The, the interesting thing about the ETR data, Eric, and I want you to comment on this, the largest companies are the most aggressive to cut. They're laying off, smaller firms are spending faster. They're actually growing at a much larger, faster rate as are companies in EMEA. And that's a surprise. That's outpacing the US and APAC. Chime in on this, Eric. >> Yeah, I was surprised on all of that. First on the higher level spending, we are definitely seeing it coming down, but the interesting thing here is headlines are making it worse. The huge research shop recently said 0% growth. We're coming in at 4.6%. And just so everyone knows, this is not us guessing, we asked 1,525 IT decision-makers what their budget growth will be, and they came in at 4.6%. Now there's a huge disparity, as you mentioned. The Fortune 500, global 2000, barely at 2% growth, but small, it's at 7%. So we're at a situation right now where the smaller companies are still playing a little bit of catch up on digital transformation, and they're spending money. The largest companies that have the most to lose from a recession are being more trepidatious, obviously. So they're playing a "Wait and see." And I hope we don't talk ourselves into a recession. Certainly the headlines and some of their research shops are helping it along. But another interesting comment here is, you know, energy and utilities used to be called an orphan and widow stock group, right? They are spending more than anyone, more than financials insurance, more than retail consumer. So right now it's being driven by mid, small, and energy and utilities. They're all spending like gangbusters, like nothing's happening. And it's the rest of everyone else that's being very cautious. >> Yeah, so very unpredictable right now. All right, let's go to number two. Cost optimization remains a major theme in 2023. We've been reporting on this. You've, we've shown a chart here. What's the primary method that your organization plans to use? You asked this question of those individuals that cited that they were going to reduce their spend and- >> Mhm. >> consolidating redundant vendors, you know, still leads the way, you know, far behind, cloud optimization is second, but it, but cloud continues to outpace legacy on-prem spending, no doubt. Somebody, it was, the guy's name was Alexander Feiglstorfer from Storyblok, sent in a prediction, said "All in one becomes extinct." Now, generally I would say I disagree with that because, you know, as we know over the years, suites tend to win out over, you know, individual, you know, point products. But I think what's going to happen is all in one is going to remain the norm for these larger companies that are cutting back. They want to consolidate redundant vendors, and the smaller companies are going to stick with that best of breed and be more aggressive and try to compete more effectively. What's your take on that? >> Yeah, I'm seeing much more consolidation in vendors, but also consolidation in functionality. We're seeing people building out new functionality, whether it's, we're going to talk about this later, so I don't want to steal too much of our thunder right now, but data and security also, we're seeing a functionality creep. So I think there's further consolidation happening here. I think niche solutions are going to be less likely, and platform solutions are going to be more likely in a spending environment where you want to reduce your vendors. You want to have one bill to pay, not 10. Another thing on this slide, real quick if I can before I move on, is we had a bunch of people write in and some of the answer options that aren't on this graph but did get cited a lot, unfortunately, is the obvious reduction in staff, hiring freezes, and delaying hardware, were three of the top write-ins. And another one was offshore outsourcing. So in addition to what we're seeing here, there were a lot of write-in options, and I just thought it would be important to state that, but essentially the cost optimization is by and far the highest one, and it's growing. So it's actually increased in our citations over the last year. >> And yeah, specifically consolidating redundant vendors. And so I actually thank you for bringing that other up, 'cause I had asked you, Eric, is there any evidence that repatriation is going on and we don't see it in the numbers, we don't see it even in the other, there was, I think very little or no mention of cloud repatriation, even though it might be happening in this in a smattering. >> Not a single mention, not one single mention. I went through it for you. Yep. Not one write-in. >> All right, let's move on. Number three, security leads M&A in 2023. Now you might say, "Oh, well that's a layup," but let me set this up Eric, because I didn't really do a great job with the slide. I hid the, what you've done, because you basically took, this is from the emerging technology survey with 1,181 responses from November. And what we did is we took Palo Alto and looked at the overlap in Palo Alto Networks accounts with these vendors that were showing on this chart. And Eric, I'm going to ask you to explain why we put a circle around OneTrust, but let me just set it up, and then have you comment on the slide and take, give us more detail. We're seeing private company valuations are off, you know, 10 to 40%. We saw a sneak, do a down round, but pretty good actually only down 12%. We've seen much higher down rounds. Palo Alto Networks we think is going to get busy. Again, they're an inquisitive company, they've been sort of quiet lately, and we think CrowdStrike, Cisco, Microsoft, Zscaler, we're predicting all of those will make some acquisitions and we're thinking that the targets are somewhere in this mess of security taxonomy. Other thing we're predicting AI meets cyber big time in 2023, we're going to probably going to see some acquisitions of those companies that are leaning into AI. We've seen some of that with Palo Alto. And then, you know, your comment to me, Eric, was "The RSA conference is going to be insane, hopping mad, "crazy this April," (Eric laughing) but give us your take on this data, and why the red circle around OneTrust? Take us back to that slide if you would, Alex. >> Sure. There's a few things here. First, let me explain what we're looking at. So because we separate the public companies and the private companies into two separate surveys, this allows us the ability to cross-reference that data. So what we're doing here is in our public survey, the tesis, everyone who cited some spending with Palo Alto, meaning they're a Palo Alto customer, we then cross-reference that with the private tech companies. Who also are they spending with? So what you're seeing here is an overlap. These companies that we have circled are doing the best in Palo Alto's accounts. Now, Palo Alto went and bought Twistlock a few years ago, which this data slide predicted, to be quite honest. And so I don't know if they necessarily are going to go after Snyk. Snyk, sorry. They already have something in that space. What they do need, however, is more on the authentication space. So I'm looking at OneTrust, with a 45% overlap in their overall net sentiment. That is a company that's already existing in their accounts and could be very synergistic to them. BeyondTrust as well, authentication identity. This is something that Palo needs to do to move more down that zero trust path. Now why did I pick Palo first? Because usually they're very inquisitive. They've been a little quiet lately. Secondly, if you look at the backdrop in the markets, the IPO freeze isn't going to last forever. Sooner or later, the IPO markets are going to open up, and some of these private companies are going to tap into public equity. In the meantime, however, cash funding on the private side is drying up. If they need another round, they're not going to get it, and they're certainly not going to get it at the valuations they were getting. So we're seeing valuations maybe come down where they're a touch more attractive, and Palo knows this isn't going to last forever. Cisco knows that, CrowdStrike, Zscaler, all these companies that are trying to make a push to become that vendor that you're consolidating in, around, they have a chance now, they have a window where they need to go make some acquisitions. And that's why I believe leading up to RSA, we're going to see some movement. I think it's going to pretty, a really exciting time in security right now. >> Awesome. Thank you. Great explanation. All right, let's go on the next one. Number four is, it relates to security. Let's stay there. Zero trust moves from hype to reality in 2023. Now again, you might say, "Oh yeah, that's a layup." A lot of these inbounds that we got are very, you know, kind of self-serving, but we always try to put some meat in the bone. So first thing we do is we pull out some commentary from, Eric, your roundtable, your insights roundtable. And we have a CISO from a global hospitality firm says, "For me that's the highest priority." He's talking about zero trust because it's the best ROI, it's the most forward-looking, and it enables a lot of the business transformation activities that we want to do. CISOs tell me that they actually can drive forward transformation projects that have zero trust, and because they can accelerate them, because they don't have to go through the hurdle of, you know, getting, making sure that it's secure. Second comment, zero trust closes that last mile where once you're authenticated, they open up the resource to you in a zero trust way. That's a CISO of a, and a managing director of a cyber risk services enterprise. Your thoughts on this? >> I can be here all day, so I'm going to try to be quick on this one. This is not a fluff piece on this one. There's a couple of other reasons this is happening. One, the board finally gets it. Zero trust at first was just a marketing hype term. Now the board understands it, and that's why CISOs are able to push through it. And what they finally did was redefine what it means. Zero trust simply means moving away from hardware security, moving towards software-defined security, with authentication as its base. The board finally gets that, and now they understand that this is necessary and it's being moved forward. The other reason it's happening now is hybrid work is here to stay. We weren't really sure at first, large companies were still trying to push people back to the office, and it's going to happen. The pendulum will swing back, but hybrid work's not going anywhere. By basically on our own data, we're seeing that 69% of companies expect remote and hybrid to be permanent, with only 30% permanent in office. Zero trust works for a hybrid environment. So all of that is the reason why this is happening right now. And going back to our previous prediction, this is why we're picking Palo, this is why we're picking Zscaler to make these acquisitions. Palo Alto needs to be better on the authentication side, and so does Zscaler. They're both fantastic on zero trust network access, but they need the authentication software defined aspect, and that's why we think this is going to happen. One last thing, in that CISO round table, I also had somebody say, "Listen, Zscaler is incredible. "They're doing incredibly well pervading the enterprise, "but their pricing's getting a little high," and they actually think Palo Alto is well-suited to start taking some of that share, if Palo can make one move. >> Yeah, Palo Alto's consolidation story is very strong. Here's my question and challenge. Do you and me, so I'm always hardcore about, okay, you've got to have evidence. I want to look back at these things a year from now and say, "Did we get it right? Yes or no?" If we got it wrong, we'll tell you we got it wrong. So how are we going to measure this? I'd say a couple things, and you can chime in. One is just the number of vendors talking about it. That's, but the marketing always leads the reality. So the second part of that is we got to get evidence from the buying community. Can you help us with that? >> (laughs) Luckily, that's what I do. I have a data company that asks thousands of IT decision-makers what they're adopting and what they're increasing spend on, as well as what they're decreasing spend on and what they're replacing. So I have snapshots in time over the last 11 years where I can go ahead and compare and contrast whether this adoption is happening or not. So come back to me in 12 months and I'll let you know. >> Now, you know, I will. Okay, let's bring up the next one. Number five, generative AI hits where the Metaverse missed. Of course everybody's talking about ChatGPT, we just wrote last week in a breaking analysis with John Furrier and Sarjeet Joha our take on that. We think 2023 does mark a pivot point as natural language processing really infiltrates enterprise tech just as Amazon turned the data center into an API. We think going forward, you're going to be interacting with technology through natural language, through English commands or other, you know, foreign language commands, and investors are lining up, all the VCs are getting excited about creating something competitive to ChatGPT, according to (indistinct) a hundred million dollars gets you a seat at the table, gets you into the game. (laughing) That's before you have to start doing promotion. But he thinks that's what it takes to actually create a clone or something equivalent. We've seen stuff from, you know, the head of Facebook's, you know, AI saying, "Oh, it's really not that sophisticated, ChatGPT, "it's kind of like IBM Watson, it's great engineering, "but you know, we've got more advanced technology." We know Google's working on some really interesting stuff. But here's the thing. ETR just launched this survey for the February survey. It's in the field now. We circle open AI in this category. They weren't even in the survey, Eric, last quarter. So 52% of the ETR survey respondents indicated a positive sentiment toward open AI. I added up all the sort of different bars, we could double click on that. And then I got this inbound from Scott Stevenson of Deep Graham. He said "AI is recession-proof." I don't know if that's the case, but it's a good quote. So bring this back up and take us through this. Explain this chart for us, if you would. >> First of all, I like Scott's quote better than the Facebook one. I think that's some sour grapes. Meta just spent an insane amount of money on the Metaverse and that's a dud. Microsoft just spent money on open AI and it is hot, undoubtedly hot. We've only been in the field with our current ETS survey for a week. So my caveat is it's preliminary data, but I don't care if it's preliminary data. (laughing) We're getting a sneak peek here at what is the number one net sentiment and mindshare leader in the entire machine-learning AI sector within a week. It's beating Data- >> 600. 600 in. >> It's beating Databricks. And we all know Databricks is a huge established enterprise company, not only in machine-learning AI, but it's in the top 10 in the entire survey. We have over 400 vendors in this survey. It's number eight overall, already. In a week. This is not hype. This is real. And I could go on the NLP stuff for a while. Not only here are we seeing it in open AI and machine-learning and AI, but we're seeing NLP in security. It's huge in email security. It's completely transforming that area. It's one of the reasons I thought Palo might take Abnormal out. They're doing such a great job with NLP in this email side, and also in the data prep tools. NLP is going to take out data prep tools. If we have time, I'll discuss that later. But yeah, this is, to me this is a no-brainer, and we're already seeing it in the data. >> Yeah, John Furrier called, you know, the ChatGPT introduction. He said it reminded him of the Netscape moment, when we all first saw Netscape Navigator and went, "Wow, it really could be transformative." All right, number six, the cloud expands to supercloud as edge computing accelerates and CloudFlare is a big winner in 2023. We've reported obviously on cloud, multi-cloud, supercloud and CloudFlare, basically saying what multi-cloud should have been. We pulled this quote from Atif Kahn, who is the founder and CTO of Alkira, thanks, one of the inbounds, thank you. "In 2023, highly distributed IT environments "will become more the norm "as organizations increasingly deploy hybrid cloud, "multi-cloud and edge settings..." Eric, from one of your round tables, "If my sources from edge computing are coming "from the cloud, that means I have my workloads "running in the cloud. "There is no one better than CloudFlare," That's a senior director of IT architecture at a huge financial firm. And then your analysis shows CloudFlare really growing in pervasion, that sort of market presence in the dataset, dramatically, to near 20%, leading, I think you had told me that they're even ahead of Google Cloud in terms of momentum right now. >> That was probably the biggest shock to me in our January 2023 tesis, which covers the public companies in the cloud computing sector. CloudFlare has now overtaken GCP in overall spending, and I was shocked by that. It's already extremely pervasive in networking, of course, for the edge networking side, and also in security. This is the number one leader in SaaSi, web access firewall, DDoS, bot protection, by your definition of supercloud, which we just did a couple of weeks ago, and I really enjoyed that by the way Dave, I think CloudFlare is the one that fits your definition best, because it's bringing all of these aspects together, and most importantly, it's cloud agnostic. It does not need to rely on Azure or AWS to do this. It has its own cloud. So I just think it's, when we look at your definition of supercloud, CloudFlare is the poster child. >> You know, what's interesting about that too, is a lot of people are poo-pooing CloudFlare, "Ah, it's, you know, really kind of not that sophisticated." "You don't have as many tools," but to your point, you're can have those tools in the cloud, Cloudflare's doing serverless on steroids, trying to keep things really simple, doing a phenomenal job at, you know, various locations around the world. And they're definitely one to watch. Somebody put them on my radar (laughing) a while ago and said, "Dave, you got to do a breaking analysis on CloudFlare." And so I want to thank that person. I can't really name them, 'cause they work inside of a giant hyperscaler. But- (Eric laughing) (Dave chuckling) >> Real quickly, if I can from a competitive perspective too, who else is there? They've already taken share from Akamai, and Fastly is their really only other direct comp, and they're not there. And these guys are in poll position and they're the only game in town right now. I just, I don't see it slowing down. >> I thought one of your comments from your roundtable I was reading, one of the folks said, you know, CloudFlare, if my workloads are in the cloud, they are, you know, dominant, they said not as strong with on-prem. And so Akamai is doing better there. I'm like, "Okay, where would you want to be?" (laughing) >> Yeah, which one of those two would you rather be? >> Right? Anyway, all right, let's move on. Number seven, blockchain continues to look for a home in the enterprise, but devs will slowly begin to adopt in 2023. You know, blockchains have got a lot of buzz, obviously crypto is, you know, the killer app for blockchain. Senior IT architect in financial services from your, one of your insight roundtables said quote, "For enterprises to adopt a new technology, "there have to be proven turnkey solutions. "My experience in talking with my peers are, "blockchain is still an open-source component "where you have to build around it." Now I want to thank Ravi Mayuram, who's the CTO of Couchbase sent in, you know, one of the predictions, he said, "DevOps will adopt blockchain, specifically Ethereum." And he referenced actually in his email to me, Solidity, which is the programming language for Ethereum, "will be in every DevOps pro's playbook, "mirroring the boom in machine-learning. "Newer programming languages like Solidity "will enter the toolkits of devs." His point there, you know, Solidity for those of you don't know, you know, Bitcoin is not programmable. Solidity, you know, came out and that was their whole shtick, and they've been improving that, and so forth. But it, Eric, it's true, it really hasn't found its home despite, you know, the potential for smart contracts. IBM's pushing it, VMware has had announcements, and others, really hasn't found its way in the enterprise yet. >> Yeah, and I got to be honest, I don't think it's going to, either. So when we did our top trends series, this was basically chosen as an anti-prediction, I would guess, that it just continues to not gain hold. And the reason why was that first comment, right? It's very much a niche solution that requires a ton of custom work around it. You can't just plug and play it. And at the end of the day, let's be very real what this technology is, it's a database ledger, and we already have database ledgers in the enterprise. So why is this a priority to move to a different database ledger? It's going to be very niche cases. I like the CTO comment from Couchbase about it being adopted by DevOps. I agree with that, but it has to be a DevOps in a very specific use case, and a very sophisticated use case in financial services, most likely. And that's not across the entire enterprise. So I just think it's still going to struggle to get its foothold for a little bit longer, if ever. >> Great, thanks. Okay, let's move on. Number eight, AWS Databricks, Google Snowflake lead the data charge with Microsoft. Keeping it simple. So let's unpack this a little bit. This is the shared accounts peer position for, I pulled data platforms in for analytics, machine-learning and AI and database. So I could grab all these accounts or these vendors and see how they compare in those three sectors. Analytics, machine-learning and database. Snowflake and Databricks, you know, they're on a crash course, as you and I have talked about. They're battling to be the single source of truth in analytics. They're, there's going to be a big focus. They're already started. It's going to be accelerated in 2023 on open formats. Iceberg, Python, you know, they're all the rage. We heard about Iceberg at Snowflake Summit, last summer or last June. Not a lot of people had heard of it, but of course the Databricks crowd, who knows it well. A lot of other open source tooling. There's a company called DBT Labs, which you're going to talk about in a minute. George Gilbert put them on our radar. We just had Tristan Handy, the CEO of DBT labs, on at supercloud last week. They are a new disruptor in data that's, they're essentially making, they're API-ifying, if you will, KPIs inside the data warehouse and dramatically simplifying that whole data pipeline. So really, you know, the ETL guys should be shaking in their boots with them. Coming back to the slide. Google really remains focused on BigQuery adoption. Customers have complained to me that they would like to use Snowflake with Google's AI tools, but they're being forced to go to BigQuery. I got to ask Google about that. AWS continues to stitch together its bespoke data stores, that's gone down that "Right tool for the right job" path. David Foyer two years ago said, "AWS absolutely is going to have to solve that problem." We saw them start to do it in, at Reinvent, bringing together NoETL between Aurora and Redshift, and really trying to simplify those worlds. There's going to be more of that. And then Microsoft, they're just making it cheap and easy to use their stuff, you know, despite some of the complaints that we hear in the community, you know, about things like Cosmos, but Eric, your take? >> Yeah, my concern here is that Snowflake and Databricks are fighting each other, and it's allowing AWS and Microsoft to kind of catch up against them, and I don't know if that's the right move for either of those two companies individually, Azure and AWS are building out functionality. Are they as good? No they're not. The other thing to remember too is that AWS and Azure get paid anyway, because both Databricks and Snowflake run on top of 'em. So (laughing) they're basically collecting their toll, while these two fight it out with each other, and they build out functionality. I think they need to stop focusing on each other, a little bit, and think about the overall strategy. Now for Databricks, we know they came out first as a machine-learning AI tool. They were known better for that spot, and now they're really trying to play catch-up on that data storage compute spot, and inversely for Snowflake, they were killing it with the compute separation from storage, and now they're trying to get into the MLAI spot. I actually wouldn't be surprised to see them make some sort of acquisition. Frank Slootman has been a little bit quiet, in my opinion there. The other thing to mention is your comment about DBT Labs. If we look at our emerging technology survey, last survey when this came out, DBT labs, number one leader in that data integration space, I'm going to just pull it up real quickly. It looks like they had a 33% overall net sentiment to lead data analytics integration. So they are clearly growing, it's fourth straight survey consecutively that they've grown. The other name we're seeing there a little bit is Cribl, but DBT labs is by far the number one player in this space. >> All right. Okay, cool. Moving on, let's go to number nine. With Automation mixer resurgence in 2023, we're showing again data. The x axis is overlap or presence in the dataset, and the vertical axis is shared net score. Net score is a measure of spending momentum. As always, you've seen UI path and Microsoft Power Automate up until the right, that red line, that 40% line is generally considered elevated. UI path is really separating, creating some distance from Automation Anywhere, they, you know, previous quarters they were much closer. Microsoft Power Automate came on the scene in a big way, they loom large with this "Good enough" approach. I will say this, I, somebody sent me a results of a (indistinct) survey, which showed UiPath actually had more mentions than Power Automate, which was surprising, but I think that's not been the case in the ETR data set. We're definitely seeing a shift from back office to front soft office kind of workloads. Having said that, software testing is emerging as a mainstream use case, we're seeing ML and AI become embedded in end-to-end automations, and low-code is serving the line of business. And so this, we think, is going to increasingly have appeal to organizations in the coming year, who want to automate as much as possible and not necessarily, we've seen a lot of layoffs in tech, and people... You're going to have to fill the gaps with automation. That's a trend that's going to continue. >> Yep, agreed. At first that comment about Microsoft Power Automate having less citations than UiPath, that's shocking to me. I'm looking at my chart right here where Microsoft Power Automate was cited by over 60% of our entire survey takers, and UiPath at around 38%. Now don't get me wrong, 38% pervasion's fantastic, but you know you're not going to beat an entrenched Microsoft. So I don't really know where that comment came from. So UiPath, looking at it alone, it's doing incredibly well. It had a huge rebound in its net score this last survey. It had dropped going through the back half of 2022, but we saw a big spike in the last one. So it's got a net score of over 55%. A lot of people citing adoption and increasing. So that's really what you want to see for a name like this. The problem is that just Microsoft is doing its playbook. At the end of the day, I'm going to do a POC, why am I going to pay more for UiPath, or even take on another separate bill, when we know everyone's consolidating vendors, if my license already includes Microsoft Power Automate? It might not be perfect, it might not be as good, but what I'm hearing all the time is it's good enough, and I really don't want another invoice. >> Right. So how does UiPath, you know, and Automation Anywhere, how do they compete with that? Well, the way they compete with it is they got to have a better product. They got a product that's 10 times better. You know, they- >> Right. >> they're not going to compete based on where the lowest cost, Microsoft's got that locked up, or where the easiest to, you know, Microsoft basically give it away for free, and that's their playbook. So that's, you know, up to UiPath. UiPath brought on Rob Ensslin, I've interviewed him. Very, very capable individual, is now Co-CEO. So he's kind of bringing that adult supervision in, and really tightening up the go to market. So, you know, we know this company has been a rocket ship, and so getting some control on that and really getting focused like a laser, you know, could be good things ahead there for that company. Okay. >> One of the problems, if I could real quick Dave, is what the use cases are. When we first came out with RPA, everyone was super excited about like, "No, UiPath is going to be great for super powerful "projects, use cases." That's not what RPA is being used for. As you mentioned, it's being used for mundane tasks, so it's not automating complex things, which I think UiPath was built for. So if you were going to get UiPath, and choose that over Microsoft, it's going to be 'cause you're doing it for more powerful use case, where it is better. But the problem is that's not where the enterprise is using it. The enterprise are using this for base rote tasks, and simply, Microsoft Power Automate can do that. >> Yeah, it's interesting. I've had people on theCube that are both Microsoft Power Automate customers and UiPath customers, and I've asked them, "Well you know, "how do you differentiate between the two?" And they've said to me, "Look, our users and personal productivity users, "they like Power Automate, "they can use it themselves, and you know, "it doesn't take a lot of, you know, support on our end." The flip side is you could do that with UiPath, but like you said, there's more of a focus now on end-to-end enterprise automation and building out those capabilities. So it's increasingly a value play, and that's going to be obviously the challenge going forward. Okay, my last one, and then I think you've got some bonus ones. Number 10, hybrid events are the new category. Look it, if I can get a thousand inbounds that are largely self-serving, I can do my own here, 'cause we're in the events business. (Eric chuckling) Here's the prediction though, and this is a trend we're seeing, the number of physical events is going to dramatically increase. That might surprise people, but most of the big giant events are going to get smaller. The exception is AWS with Reinvent, I think Snowflake's going to continue to grow. So there are examples of physical events that are growing, but generally, most of the big ones are getting smaller, and there's going to be many more smaller intimate regional events and road shows. These micro-events, they're going to be stitched together. Digital is becoming a first class citizen, so people really got to get their digital acts together, and brands are prioritizing earned media, and they're beginning to build their own news networks, going direct to their customers. And so that's a trend we see, and I, you know, we're right in the middle of it, Eric, so you know we're going to, you mentioned RSA, I think that's perhaps going to be one of those crazy ones that continues to grow. It's shrunk, and then it, you know, 'cause last year- >> Yeah, it did shrink. >> right, it was the last one before the pandemic, and then they sort of made another run at it last year. It was smaller but it was very vibrant, and I think this year's going to be huge. Global World Congress is another one, we're going to be there end of Feb. That's obviously a big big show, but in general, the brands and the technology vendors, even Oracle is going to scale down. I don't know about Salesforce. We'll see. You had a couple of bonus predictions. Quantum and maybe some others? Bring us home. >> Yeah, sure. I got a few more. I think we touched upon one, but I definitely think the data prep tools are facing extinction, unfortunately, you know, the Talons Informatica is some of those names. The problem there is that the BI tools are kind of including data prep into it already. You know, an example of that is Tableau Prep Builder, and then in addition, Advanced NLP is being worked in as well. ThoughtSpot, Intelius, both often say that as their selling point, Tableau has Ask Data, Click has Insight Bot, so you don't have to really be intelligent on data prep anymore. A regular business user can just self-query, using either the search bar, or even just speaking into what it needs, and these tools are kind of doing the data prep for it. I don't think that's a, you know, an out in left field type of prediction, but it's the time is nigh. The other one I would also state is that I think knowledge graphs are going to break through this year. Neo4j in our survey is growing in pervasion in Mindshare. So more and more people are citing it, AWS Neptune's getting its act together, and we're seeing that spending intentions are growing there. Tiger Graph is also growing in our survey sample. I just think that the time is now for knowledge graphs to break through, and if I had to do one more, I'd say real-time streaming analytics moves from the very, very rich big enterprises to downstream, to more people are actually going to be moving towards real-time streaming, again, because the data prep tools and the data pipelines have gotten easier to use, and I think the ROI on real-time streaming is obviously there. So those are three that didn't make the cut, but I thought deserved an honorable mention. >> Yeah, I'm glad you did. Several weeks ago, we did an analyst prediction roundtable, if you will, a cube session power panel with a number of data analysts and that, you know, streaming, real-time streaming was top of mind. So glad you brought that up. Eric, as always, thank you very much. I appreciate the time you put in beforehand. I know it's been crazy, because you guys are wrapping up, you know, the last quarter survey in- >> Been a nuts three weeks for us. (laughing) >> job. I love the fact that you're doing, you know, the ETS survey now, I think it's quarterly now, right? Is that right? >> Yep. >> Yep. So that's phenomenal. >> Four times a year. I'll be happy to jump on with you when we get that done. I know you were really impressed with that last time. >> It's unbelievable. This is so much data at ETR. Okay. Hey, that's a wrap. Thanks again. >> Take care Dave. Good seeing you. >> All right, many thanks to our team here, Alex Myerson as production, he manages the podcast force. Ken Schiffman as well is a critical component of our East Coast studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hoof is our editor-in-chief. He's at siliconangle.com. He's just a great editing for us. Thank you all. Remember all these episodes that are available as podcasts, wherever you listen, podcast is doing great. Just search "Breaking analysis podcast." Really appreciate you guys listening. I publish each week on wikibon.com and siliconangle.com, or you can email me directly if you want to get in touch, david.vellante@siliconangle.com. That's how I got all these. I really appreciate it. I went through every single one with a yellow highlighter. It took some time, (laughing) but I appreciate it. You could DM me at dvellante, or comment on our LinkedIn post and please check out etr.ai. Its data is amazing. 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 beginning) (upbeat music ending)