>> Hello friends and welcome back to Fabulous Las Vegas, Nevada. We are here at AWS re:Invent in the heat of day three. Very exciting time. My name is Savannah Peterson, joined with John Furrier here on theCUBE. John, what's your, what's your big hot take from the day? Just from today. >> So right now the velocity of content is continuing to flow on theCUBE. Thank you, everyone, for watching. The security conversations. Also, the cost tuning of the cloud kind of vibe is going on. You're hearing that with the looming recession, but if you look at the show it's the bulk of the keynote time spent talking is on data and security together. So Security, Security Lake, Amazon, they continue to talk about security. This next segment's going to be awesome. We have a multi-, eight-time CUBE alumni coming back and great conversation about security. I'm looking forward to this. >> Alumni VIP, I know, it's so great. Actually, both of these guests have been on theCUBE before so please welcome Dan and Haiyan. Thank you both for being here from F5. How's the show going? You're both smiling and we're midway through day three. Good? >> It's so exciting to be here with you all and it's a great show. >> Awesome. Dan, you having a good time too? >> It's wearing me out. I'm having a great time. (laughter) >> It's okay to be honest. It's okay to be honest. It's wearing out our vocal cords for sure up here, but it is definitely a great time. Haiyan, can you tell me a little bit about F5 just in case the audience isn't familiar? >> Sure, so F5 we specialize in application delivery and security. So our mission is to deliver secure and optimize any applications, any APIs, anywhere. >> I can imagine you have a few customers in the house. >> Absolutely. >> Yeah, that's awesome. So in terms of a problem that, well an annoyance that we've all had, bots. We all want the anti-bots. You have a unique solution to this. How are you helping AWS customers with bots? Let's send it to you. >> Well we, we collect client side signals from all devices. We might study how it does floating point math or how it renders emojis. We analyze those signals and we can make a real time determination if the traffic is from a bot or not. And if it's from a bot, we could take mitigating action. And if it's not, we just forward it on to origin. So client side signals are really important. And then the second aspect of bot protection I think is understanding that bot's retool. They become more sophisticated. >> Savannah: They learn. >> They learn. >> They unfortunately learn as well. >> Exactly, yeah. So you have to have a second stage what we call retrospective analysis where you're looking over all the historical transactions, looking for anything that may have been missed by a realtime defense and then updating that stage one that real time defense to deal with the newly discovered threat. >> Let's take a step back for a second. I want to just set the table in the context for the bot conversation. Bots, automation, that's, people know like spam bots but Amazon has seen the bot networks develop. Can you scope the magnitude and the size of the problem of bots? What is the problem? And give a size of what this magnitude of this is. >> Sure, one thing that's important to realize is not all bots are bad. Okay? Some bots are good and you want to identify the automation from those bots and allow listed so you don't interfere with what they're doing. >> I can imagine that's actually tricky. >> It is, it is. Absolutely. Yeah. >> Savannah: Nuanced. >> Yeah, but the bad bots, these are the ones that are attempting credential stuffing attacks, right? They're trying username password pairs against login forms. And because of consumer habits to reuse usernames and passwords, they end up taking over a lot of accounts. But those are the bookends. There are all sorts of types of bots in between those two bookends. Some are just nuisance, like limited time offer bots. You saw some of this in the news recently with Ticketmaster. >> That's a spicy story. >> Yeah, it really is. And it's the bots that is causing that problem. They use automation to buy all these concert tickets or sneakers or you know, any limited time offer project. And then they resell those on the secondary market. And we've done analysis on some of these groups and they're making millions of dollars. It isn't something they're making like 1200 bucks on. >> I know Amazon doesn't like to talk about this but the cloud for its double edged sword that it is for all the greatness of the agility spinning up resources bots have been taking advantage of that same capability to hide, change, morph. You've seen the matrix when the bots attacked the ship. They come out of nowhere. But Amazon actually has seen the bot problem for a long time, has been working on it. Talk about that kind of evolution of how this problem's being solved. What's Amazon doing about, how do you guys help out? >> Yeah, well we have this CloudFront connector that allows all Amazon CloudFront customers to be able to leverage this technology very, very quickly. So what historically was available only to like, you know the Fortune 500 at most of the global 2000 is now available to all AWS customers who are using CloudFront just by really you can explain how do they turn it on in CloudFront? >> Yeah. So I mean CloudFront technologies like that is so essential to delivering the digital experience. So what we do is we do a integration natively. And so if your CloudFront customers and you can just use our bot defense solution by turning on, you know, that traffic. So go through our API inspection, go through our bot inspection and you can benefit from all the other efficiencies that we acquired through serving the highest and the top institutions in the world. >> So just to get this clarification, this is a super important point. You said it's native to the service. I don't have to bolt it on? Is it part of the customer experience? >> Yeah, we basically built the integration. So if you're already a CloudFront customer and you have the ability to turn on our bot solutions without having to do the integration yourself. >> Flick a switch and it's on. >> Haiyan: Totally. >> Pretty much. >> Haiyan: Yeah. >> That's how I want to get rid of all the spam in my life. We've talked a lot about the easy button. I would also like the anti-spam button if we're >> Haiyan: 100% >> Well we were talking before you came on camera that there's a potentially a solution you can sit charge. There are techniques. >> Yeah. Yeah. We were talking about the spam emails and I thought they just charge, you know 10th of a penny for every sent email. It wouldn't affect me very much. >> What's the, are people on that? You guys are on this but I mean this is never going to stop. We're going to see the underbelly of the web, the dark web continue to do it. People are harvesting past with the dark web using bots that go in test challenge credentials. I mean, it's just happening. It's never going to stop. What's, is it going to be that cat and mouse game? Are we going to see solutions? What's the, when are we going to get some >> Well it's certainly not a cat and mouse game for F5 customers because we win that battle every time. But for enterprises who are still battling the bots as a DIY project, then yes, it's just going to be a cat and mouse. They're continuing to block by IP, you know, by rate limiting. >> Right, which is so early 2000's. >> Exactly. >> If we're being honest. >> Exactly. And the attackers, by the way, the attackers are now coming from hundreds of thousands or even millions of IP addresses and some IPs are using one time. >> Yeah, I mean it seems like such an easy problem to circumnavigate. And still be able to get in. >> What are I, I, let's stick here for a second. What are some of the other trends that you're seeing in how people are defending if they're not using you or just in general? >> Yeah, maybe I'll add to to that. You know, when we think about the bot problem we also sort of zoom out and say, Hey, bot is only one part of the problem when you think about the entire digital experience the customer experiencing, right? So at F5 we actually took a more holistic sort of way to say, well it's about protecting the apps and applications and the APIs that's powering all of those. And we're thinking not only the applications APIs we're thinking the infrastructure that those API workloads are running. So one of the things we're sharing since we acquired Threat Stack, we have been busy doing integrations with our distributed cloud services and we're excited. In a couple weeks you will hear announcement of the integrated solution for our application infrastructure protection. So that's just another thing. >> On that Threat Stack, does that help with that data story too? Because it's a compliance aspect as well. >> Yeah, it helps with the telemetries, collecting more telemetries, the data story but is also think about applications and APIs. You can only be as secure as the infrastructure you're running on it, right? So the infrastructure protection is a key part of application security. And the other dimension is not only we can help with the credentials, staffing and, and things but it's actually thinking about the customer's top line. Because at the end of the day when all this inventory are being siphoned out the customer won't be happy. So how do we make sure their loyal customers have the right experience so that can improve their top line and not just sort of preventing the bots. So there's a lot of mission that we're on. >> Yeah, that surprise and delight in addition to that protection. >> 100% >> If I could talk about the evolution of an engagement with F5. We first go online, deploy the client side signals I described and take care of all the bad bots. Okay. Mitigate them. Allow list all the good bots, now you're just left with human traffic. We have other client side signals that'll identify the bad humans among the good humans and you could deal with them. And then we have additional client side signals that allow us to do silent continuous authentication of your good customers extending their sessions so they don't have to endure the friction of logging in over and over and over. >> Explain that last one again because I think that was, that's, I didn't catch that. >> Yeah. So right now we require a customer to enter in their username and password before we believe it's them. But we had a customer who a lot of their customers were struggling to log in. So we did analysis and we realized that our client side signals, you know of all those that are struggling to log in, we're confident like 40% of 'em are known good customers based on some of these signals. Like they're doing floating point math the way they always have. They're rendering emojis the way they always have all these clients that signals are the same. So why force that customer to log in again? >> Oh yeah. And that's such a frustrating user experience. >> So true. >> I actually had that thought earlier today. How many time, how much of my life am I going to spend typing my email address? Just that in itself. Then I could crawl back under the covers but >> With the biometric Mac, I forget my passwords. >> Or how about solving CAPTCHA's? How fun is that? >> How many pictures have a bus? >> I got one wrong the other day because I had to pick all the street signs. I got it wrong and I called a Russian human click farm and figured out why was I getting it wrong? And they said >> I love that you went down this rabbit hole deeply. >> You know why that's not a street sign. That's a road sign, they told me. >> That's the secret backdoor. >> Oh well yeah. >> Talk about your background because you have fascinating background coming from law enforcement and you're in this kind of role. >> He could probably tell us about our background. >> They expunge those records. I'm only kidding. >> 25, 30 years in working in local, state and federal law enforcement and intelligence among those an FBI agent and a CIA cyber operations officer. And most people are drawn to that because it's interesting >> Three letter agencies can get an eyebrow raise. >> But I'll be honest, my early, early in my career I was a beat cop and that changed my life. That really did, that taught me the importance of an education, taught me the criminal mindset. So yeah, people are drawn to the FBI and CIA background, but I really value the >> So you had a good observation eye for kind of what, how this all builds out. >> It all kind of adds up, you know, constantly fighting the bad guys, whether they're humans, bots, a security threat from a foreign nation. >> Well learning their mindset and learning what motivates them, what their objectives are. It is really important. >> Reading the signals >> You don't mind slipping into the mind of a criminal. It's a union rule. >> Right? It actually is. >> You got to put your foot and your hands in and walk through their shoes as they say. >> That's right. >> The bot networks though, I want to get into, is not it sounds like it's off the cup but they're highly organized networks. >> Dan: They are. >> Talk about the aspect of the franchises or these bots behind them, how they're financed, how they use the money that they make or ransomware, how they collect, what's the enterprise look like? >> Unfortunately, a lot of the nodes on a botnet are now just innocent victim computers using their home computers. They can subscribe to a service and agree to let their their CPU be used while they're not using it in exchange for a free VPN service, say. So now bad actors not, aren't just coming from you know, you know, rogue cloud providers who accept Bitcoin as payment, they're actually coming from residential IPs, which is making it even more difficult for the security teams to identify. It's one thing when it's coming from- >> It's spooky. I'm just sitting here kind of creeped out too. It's these unknown hosts, right? It's like being a carrier. >> You have good traffic coming from it during the day. >> Right, it appears normal. >> And then malicious traffic coming from it. >> Nefarious. >> My last question is your relationship with Amazon. I'll see security center piece of this re:Invent. It's always been day zero as they say but really it's the security data lake. A lot of gaps are being filled in the products. You kind of see that kind of filling out. Talk about the relationship with F5 and AWS. How you guys are working together, what's the status? >> We've been long-term partners and the latest release the connector for CloudFront is just one of the joint work that we did together and try to, I think, to Dan's point, how do we make those technology that was built for the very sophisticated big institutions to be available for all the CloudFront customers? So that's really what's exciting. And we also leverage a lot of the technology. You talked about the data and our entire solution are very data driven, as you know, is automation. If you don't use data, you don't use analytics, you don't use AI, it's hard to really sort of win that war. So a lot of our stuff, it's very data driven >> And the benefit to customers is what? Access? >> The customer's access, the customer's top line. We talked about, you know, like how we're really bringing better experiences at the end of the day. F5's mission is try to bring a better digital world to life. >> And it's also collaborative. We've had a lot of different stories here on on the set about companies collaborating. You're obviously collaborating and I also love that we're increasing access, not just narrowing this focus for the larger companies at scale already, but making sure that these companies starting out, a lot of the founders probably milling around on the floor right now can prevent this and ensure that user experience for their customers. throughout the course of their product development. I think it's awesome. So we have a new tradition here on theCUBE at re:Invent, and since you're alumni, I feel like you're maybe going to be a little bit better at this than some of the rookies. Not that rookies can't be great, but you're veterans. So I feel strong about this. We are looking for your 30-second Instagram reel hot take. Think of it like your sizzle of thought leadership from the show this year. So eventually eight more visits from now we can compile them into a great little highlight reel of all of your sound bites over the evolution of time. Who wants to give us their hot take first? >> Dan? >> Yeah, sure. >> Savannah: You've been elected, I mean you are an agent. A former special agent >> I guess I want everybody to know the bot problem is much worse than they think it is. We go in line and we see 98, 99% of all login traffic is from malicious bots. And so it is not a DIY project. >> 98 to 99%? That means only 1% of traffic is actually legitimate? >> That's right. >> Holy moly. >> I just want to make sure that everybody heard you say that. >> That's right. And it's very common. Didn't happen once or twice. It's happened a lot of times. And when it's not 99 it's 60 or it's 58, it's high. >> And that's costing a lot too. >> Yes, it is. And it's not just in fraud, but think about charges that >> Savannah: I think of cloud service providers >> Cost associated with transactions, you know, fraud tools >> Savannah: All of it. >> Yes. Sims, all those things. There's a lot of costs associated with that much automation. So the client side signals and multi-stage defense is what you need to deal with it. It's not a DIY project. >> Bots are not DIY. How would you like to add to that? >> It's so hard to add to that but I would say cybersecurity is a team sport and is a very data driven solution and we really need to sort of team up together and share intelligence, share, you know, all the things we know so we can be better at this. It's not a DIY project. We need to work together. >> Fantastic, Dan, Haiyan, so great to have you both back on theCUBE. We look forward to seeing you again for our next segment and I hope that the two of you have really beautiful rest of your show. Thank you all for tuning into a fantastic afternoon of coverage here from AWS re:Invent. We are live from Las Vegas, Nevada and don't worry we have more programming coming up for you later today with John Furrier. I'm Savannah Peterson. This is theCUBE, the leader in high tech coverage.

>>Good evening everyone and welcome back to Sparkly Sin City, Las Vegas, Nevada, where we are here with the cube covering AWS Reinvent for the 10th year in a row. John Furrier has been here for all 10. John, we are in our last session of day one. How does it compare? >>I just graduated high school 10 years ago. It's exciting to be, here's been a long time. We've gotten a lot older. My >>Got your brain is complex. You've been a lot in there. So fast. >>Graduated eight in high school. You know how it's No. All good. This is what's going on. This next segment, wrapping up day one, which is like the the kickoff. The Mondays great year. I mean Tuesdays coming tomorrow big days. The announcements are all around the kind of next gen and you're starting to see partnering and integration is a huge part of this next wave cuz API's at the cloud, next gen cloud's gonna be deep engineering integration and you're gonna start to see business relationships and business transformation scale a horizontally, not only across applications but companies. This has been going on for a while, covering it. This next segment is gonna be one of those things that we're gonna look at as something that's gonna happen more and more on >>Yeah, I think so. It's what we've been talking about all day. Without further ado, I would like to welcome our very exciting guest for this final segment, trust from single store. Thank you for being here. And we also have him on from IBM Data and ai. Y'all are partners. Been partners for about a year. I'm gonna go out on a limb only because their legacy and suspect that a few people, a few more people might know what IBM does versus what a single store does. So why don't you just give us a little bit of background so everybody knows what's going on. >>Yeah, so single store is a relational database. It's a foundational relational systems, but the thing that we do the best is what we call us realtime analytics. So we have these systems that are legacy, which which do operations or analytics. And if you wanted to bring them together, like most of the applications want to, it's really a big hassle. You have to build an ETL pipeline, you'd have to duplicate the data. It's really faulty systems all over the place and you won't get the insights really quickly. Single store is trying to solve that problem elegantly by having an architecture that brings both operational and analytics in one place. >>Brilliant. >>You guys had a big funding now expanding men. Sequel, single store databases, 46 billion again, databases. We've been saying this in the queue for 12 years have been great and recently not one database will rule the world. We know that. That's, everyone knows that databases, data code, cloud scale, this is the convergence now of all that coming together where data, this reinvent is the theme. Everyone will be talking about end to end data, new kinds of specialized services, faster performance, new kinds of application development. This is the big part of why you guys are working together. Explain the relationship, how you guys are partnering and engineering together. >>Yeah, absolutely. I think so ibm, right? I think we are mainly into hybrid cloud and ai and one of the things we are looking at is expanding our ecosystem, right? Because we have gaps and as opposed to building everything organically, we want to partner with the likes of single store, which have unique capabilities that complement what we have. Because at the end of the day, customers are looking for an end to end solution that's also business problems. And they are very good at real time data analytics and hit staff, right? Because we have transactional databases, analytical databases, data lakes, but head staff is a gap that we currently have. And by partnering with them we can essentially address the needs of our customers and also what we plan to do is try to integrate our products and solutions with that so that when we can deliver a solution to our customers, >>This is why I was saying earlier, I think this is a a tell sign of what's coming from a lot of use cases where people are partnering right now you got the clouds, a bunch of building blocks. If you put it together yourself, you can build a durable system, very stable if you want out of the box solution, you can get that pre-built, but you really can't optimize. It breaks, you gotta replace it. High level engineering systems together is a little bit different, not just buying something out of the box. You guys are working together. This is kind of an end to end dynamic that we're gonna hear a lot more about at reinvent from the CEO ofs. But you guys are doing it across companies, not just with aws. Can you guys share this new engineering business model use case? Do you agree with what I'm saying? Do you think that's No, exactly. Do you think John's crazy, crazy? I mean I all discourse, you got out of the box, engineer it yourself, but then now you're, when people do joint engineering project, right? They're different. Yeah, >>Yeah. No, I mean, you know, I think our partnership is a, is a testament to what you just said, right? When you think about how to achieve realtime insights, the data comes into the system and, and the customers and new applications want insights as soon as the data comes into the system. So what we have done is basically build an architecture that enables that we have our own storage and query engine indexing, et cetera. And so we've innovated in our indexing in our database engine, but we wanna go further than that. We wanna be able to exploit the innovation that's happening at ibm. A very good example is, for instance, we have a native connector with Cognos, their BI dashboards right? To reason data very natively. So we build a hyper efficient system that moves the data very efficiently. A very other good example is embedded ai. >>So IBM of course has built AI chip and they have basically advanced quite a bit into the embedded ai, custom ai. So what we have done is, is as a true marriage between the engineering teams here, we make sure that the data in single store can natively exploit that kind of goodness. So we have taken their libraries. So if you have have data in single store, like let's imagine if you have Twitter data, if you wanna do sentiment analysis, you don't have to move the data out model, drain the model outside, et cetera. We just have the pre-built embedded AI libraries already. So it's a, it's a pure engineering manage there that kind of opens up a lot more insights than just simple analytics and >>Cost by the way too. Moving data around >>Another big theme. Yeah. >>And latency and speed is everything about single store and you know, it couldn't have happened without this kind of a partnership. >>So you've been at IBM for almost two decades, don't look it, but at nearly 17 years in how has, and maybe it hasn't, so feel free to educate us. How has, how has IBM's approach to AI and ML evolved as well as looking to involve partnerships in the ecosystem as a, as a collaborative raise the water level together force? >>Yeah, absolutely. So I think when we initially started ai, right? I think we are, if you recollect Watson was the forefront of ai. We started the whole journey. I think our focus was more on end solutions, both horizontal and vertical. Watson Health, which is more vertically focused. We were also looking at Watson Assistant and Watson Discovery, which were more horizontally focused. I think it it, that whole strategy of the world period of time. Now we are trying to be more open. For example, this whole embedable AI that CICE was talking about. Yeah, it's essentially making the guts of our AI libraries, making them available for partners and ISVs to build their own applications and solutions. We've been using it historically within our own products the past few years, but now we are making it available. So that, how >>Big of a shift is that? Do, do you think we're seeing a more open and collaborative ecosystem in the space in general? >>Absolutely. Because I mean if you think about it, in my opinion, everybody is moving towards AI and that's the future. And you have two option. Either you build it on your own, which is gonna require significant amount of time, effort, investment, research, or you partner with the likes of ibm, which has been doing it for a while, right? And it has the ability to scale to the requirements of all the enterprises and partners. So you have that option and some companies are picking to do it on their own, but I believe that there's a huge amount of opportunity where people are looking to partner and source what's already available as opposed to investing from the scratch >>Classic buy versus build analysis for them to figure out, yeah, to get into the game >>And, and, and why reinvent the wheel when we're all trying to do things at, at not just scale but orders of magnitude faster and and more efficiently than we were before. It, it makes sense to share, but it's, it is, it does feel like a bit of a shift almost paradigm shift in, in the culture of competition versus how we're gonna creatively solve these problems. There's room for a lot of players here, I think. And yeah, it's, I don't >>Know, it's really, I wanted to ask if you don't mind me jumping in on that. So, okay, I get that people buy a bill I'm gonna use existing or build my own. The decision point on that is, to your point about the path of getting the path of AI is do I have the core competency skills, gap's a big issue. So, okay, the cube, if you had ai, we'd take it cuz we don't have any AI engineers around yet to build out on all the linguistic data we have. So we might use your ai but I might say this to then and we want to have a core competency. How do companies get that core competency going while using and partnering with, with ai? What you guys, what do you guys see as a way for them to get going? Because I think some people probably want to have core competency of >>Ai. Yeah, so I think, again, I think I, I wanna distinguish between a solution which requires core competency. You need expertise on the use case and you need expertise on your industry vertical and your customers versus the foundational components of ai, which are like, which are agnostic to the core competency, right? Because you take the foundational piece and then you further train it and define it for your specific use case. So we are not saying that we are experts in all the industry verticals. What we are good at is like foundational components, which is what we wanna provide. Got it. >>Yeah, that's the hard deep yes. Heavy lift. >>Yeah. And I can, I can give a color to that question from our perspective, right? When we think about what is our core competency, it's about databases, right? But there's a, some biotic relationship between data and ai, you know, they sort of like really move each other, right? You >>Need, they kind of can't have one without the other. You can, >>Right? And so the, the question is how do we make sure that we expand that, that that relationship where our customers can operationalize their AI applications closer to the data, not move the data somewhere else and do the modeling and then training somewhere else and dealing with multiple systems, et cetera. And this is where this kind of a cross engineering relationship helps. >>Awesome. Awesome. Great. And then I think companies are gonna want to have that baseline foundation and then start hiring in learning. It's like driving the car. You get the keys when you're ready to go. >>Yeah, >>Yeah. Think I'll give you a simple example, right? >>I want that turnkey lifestyle. We all do. Yeah, >>Yeah. Let me, let me just give you a quick analogy, right? For example, you can, you can basically make the engines and the car on your own or you can source the engine and you can make the car. So it's, it's basically an option that you can decide. The same thing with airplanes as well, right? Whether you wanna make the whole thing or whether you wanna source from someone who is already good at doing that piece, right? So that's, >>Or even create a new alloy for that matter. I mean you can take it all the way down in that analogy, >>Right? Is there a structural change and how companies are laying out their architecture in this modern era as we start to see this next let gen cloud emerge, teams, security teams becoming much more focused data teams. Its building into the DevOps into the developer pipeline, seeing that trend. What do you guys see in the modern data stack kind of evolution? Is there a data solutions architect coming? Do they exist yet? Is that what we're gonna see? Is it data as code automation? How do you guys see this landscape of the evolving persona? >>I mean if you look at the modern data stack as it is defined today, it is too detailed, it's too OSes and there are way too many layers, right? There are at least five different layers. You gotta have like a storage you replicate to do real time insights and then there's a query layer, visualization and then ai, right? So you have too many ETL pipelines in between, too many services, too many choke points, too many failures, >>Right? Etl, that's the dirty three letter word. >>Say no to ETL >>Adam Celeste, that's his quote, not mine. We hear that. >>Yeah. I mean there are different names to it. They don't call it etl, we call it replication, whatnot. But the point is hassle >>Data is getting more hassle. More >>Hassle. Yeah. The data is ultimately getting replicated in the modern data stack, right? And that's kind of one of our thesis at single store, which is that you'd have to converge not hyper specialize and conversation and convergence is possible in certain areas, right? When you think about operational analytics as two different aspects of the data pipeline, it is possible to bring them together. And we have done it, we have a lot of proof points to it, our customer stories speak to it and that is one area of convergence. We need to see more of it. The relationship with IBM is sort of another step of convergence wherein the, the final phases, the operation analytics is coming together and can we take analytics visualization with reports and dashboards and AI together. This is where Cognos and embedded AI comes into together, right? So we believe in single store, which is really conversions >>One single path. >>A shocking, a shocking tie >>Back there. So, so obviously, you know one of the things we love to joke about in the cube cuz we like to goof on the old enterprise is they solve complexity by adding more complexity. That's old. Old thinking. The new thinking is put it under the covers, abstract the way the complexities and make it easier. That's right. So how do you guys see that? Because this end to end story is not getting less complicated. It's actually, I believe increasing and complication complexity. However there's opportunities doing >>It >>More faster to put it under the covers or put it under the hood. What do you guys think about the how, how this new complexity gets managed or in this new data world we're gonna be coming in? >>Yeah, so I think you're absolutely right. It's the world is becoming more complex, technology is becoming more complex and I think there is a real need and it's not just from coming from us, it's also coming from the customers to simplify things. So our approach around AI is exactly that because we are essentially providing libraries, just like you have Python libraries, there are libraries now you have AI libraries that you can go infuse and embed deeply within applications and solutions. So it becomes integrated and simplistic for the customer point of view. From a user point of view, it's, it's very simple to consume, right? So that's what we are doing and I think single store is doing that with data, simplifying data and we are trying to do that with the rest of the portfolio, specifically ai. >>It's no wonder there's a lot of synergy between the two companies. John, do you think they're ready for the Instagram >>Challenge? Yes, they're ready. Uhoh >>Think they're ready. So we're doing a bit of a challenge. A little 32nd off the cuff. What's the most important takeaway? This could be your, think of it as your thought leadership sound bite from AWS >>2023 on Instagram reel. I'm scrolling. That's the Instagram, it's >>Your moment to stand out. Yeah, exactly. Stress. You look like you're ready to rock. Let's go for it. You've got that smile, I'm gonna let you go. Oh >>Goodness. You know, there is, there's this quote from astrophysics, space moves matter, a matter tells space how to curve. They have that kind of a relationship. I see the same between AI and data, right? They need to move together. And so AI is possible only with right data and, and data is meaningless without good insights through ai. They really have that kind of relationship and you would see a lot more of that happening in the future. The future of data and AI are combined and that's gonna happen. Accelerate a lot faster. >>Sures, well done. Wow. Thank you. I am very impressed. It's tough hacks to follow. You ready for it though? Let's go. Absolutely. >>Yeah. So just, just to add what is said, right, I think there's a quote from Rob Thomas, one of our leaders at ibm. There's no AI without ia. Essentially there's no AI without information architecture, which essentially data. But I wanna add one more thing. There's a lot of buzz around ai. I mean we are talking about simplicity here. AI in my opinion is three things and three things only. Either you use AI to predict future for forecasting, use AI to automate things. It could be simple, mundane task, it would be complex tasks depending on how exactly you want to use it. And third is to optimize. So predict, automate, optimize. Anything else is buzz. >>Okay. >>Brilliantly said. Honestly, I think you both probably hit the 32nd time mark that we gave you there. And the enthusiasm loved your hunger on that. You were born ready for that kind of pitch. I think they both nailed it for the, >>They nailed it. Nailed it. Well done. >>I I think that about sums it up for us. One last closing note and opportunity for you. You have a V 8.0 product coming out soon, December 13th if I'm not mistaken. You wanna give us a quick 15 second preview of that? >>Super excited about this. This is one of the, one of our major releases. So we are evolving the system on multiple dimensions on enterprise and governance and programmability. So there are certain features that some of our customers are aware of. We have made huge performance gains in our JSON access. We made it easy for people to consume, blossom on OnPrem and hybrid architectures. There are multiple other things that we're gonna put out on, on our site. So it's coming out on December 13th. It's, it's a major next phase of our >>System. And real quick, wasm is the web assembly moment. Correct. And the new >>About, we have pioneers in that we, we be wasm inside the engine. So you could run complex modules that are written in, could be C, could be rushed, could be Python. Instead of writing the the sequel and SQL as a store procedure, you could now run those modules inside. I >>Wanted to get that out there because at coupon we covered that >>Savannah Bay hot topic. Like, >>Like a blanket. We covered it like a blanket. >>Wow. >>On that glowing note, Dre, thank you so much for being here with us on the show. We hope to have both single store and IBM back on plenty more times in the future. Thank all of you for tuning in to our coverage here from Las Vegas in Nevada at AWS Reinvent 2022 with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage. We'll see you tomorrow.

(upbeat music) >> Welcome back to Vegas. It's theCUBE live at AWS re:Invent 2022. We're hearing up to 50,000 people here. It feels like if the energy at this show is palpable. I love that. Lisa Martin here with Dave Vellante. Dave, we had the keynote this morning that Adam Selipsky delivered lots of momentum in his first year. One of the things that you said that you were looking in your breaking analysis that was released a few days ago, four trends and one of them, he said under Selipsky's rule in the 2020s, there's going to be a rush of data that will dwarf anything we have ever seen. >> Yeah, it was at least a quarter, maybe a third of his keynote this morning was all about data and the theme is simplifying data and doing better data integration, integrating across different data platforms. And we're excited to talk about that. Always want to simplify data. It's like the rush of data is so fast. It's hard for us to keep up. >> It is hard to keep that up. We're going to be talking with an alumni next about how his company is helping organizations like Cisco Meraki keep up with that data explosion. Please welcome back to the program, Matthew Scullion, the CEO of Matillion and how Hoshang Chenoy joins us, data scientist at Cisco Meraki. Guys, great to have you on the program. >> Thank you. >> Thank you for having us. >> So Matthew, we last saw you just a few months ago in Vegas at Snowflake Summits. >> Matthew: We only meet in Vegas. >> I guess we do, that's okay. Talk to us about some of the things, I know that Matillion is a data transformation solution that was originally introduced for AWS for Redshift. But talk to us about Matillion. What's gone on since we've seen you last? >> Well, I mean it's not that long ago but actually quite a lot. And it's all to do with exactly what you guys were just talking about there. This almost hard to comprehend way the world is changing with the amounts of data that we now can and need to put to work. And our worldview is there's no shortage of data but the choke points certainly one of the choke points. Maybe the choke point is our ability to make that data useful, to make it business ready. And we always talk about the end use cases. We talk about the dashboard or the AI model or the data science algorithm. But until before we can do any of that fun stuff, we have to refine raw data into business ready, usable data. And that's what Matillion is all about. And so since we last met, we've made a couple of really important announcements and possibly at the top of the list is what we call the data productivity cloud. And it's really squarely addressed this problem. It's the results of many years of work, really the apex of many years of the outsize engineering investment, Matillion loves to make. And the Data Productivity Cloud is all about helping organizations like Cisco Meraki and hundreds of others enterprise organizations around the world, get their data business ready, faster. >> Hoshang talk to us a little bit about what's going on at Cisco Meraki, how you're leveraging Matillion from a productivity standpoint. >> I've really been a Matillion fan for a while, actually even before Cisco Meraki at my previous company, LiveRamp. And you know, we brought Matillion to LiveRamp because you know, to Matthew's point, there is a stage in every data growth as I want to call it, where you have different companies at different stages. But to get data, data ready, you really need a platform like Matillion because it makes it really easy. So you have to understand Matillion, I think it's designed for someone that uses a lot of code but also someone that uses no code because the UI is so good. Someone like a marketer who doesn't really understand what's going on with that data but wants to be a data driven marketer when they look at the UI they immediately get it. They're just like, oh, I get what's happening with my data. And so that's the brilliance of Matillion and to get data to that data ready part, Matillion does a really, really good job because what we've been able to do is blend so many different data sources. So there is an abundance of data. Data is siloed though. And the connectivity between different data is getting harder and harder. And so here comes the Matillion with it's really simple solution, easy to use platform, powerful and we get to use all of that. So to really change the way we've thought about our analytics, the way we've progressed our division, yeah. >> You're always asking about superpowers and that is a superpower of Matillion 'cause you know, low-code, no-code sounds great but it only gets you a quarter of the way there, maybe 50% of the way there. You're kind of an "and" not an "or." >> That's a hundred percent right. And so I mentioned the Data Productivity Cloud earlier which is the name of this platform of technology we provide. That's all to do with making data business ready. And so I think one of the things we've seen in this industry over the past few years is a kind of extreme decomposition in terms of vendors of making data business ready. You've got vendors that just do loading, you've got vendors that just do a bit of data transformation, you've got vendors that do data ops and orchestration, you've got vendors that do reverse ETL. And so with the data productivity platform, you've got all of that. And particularly in this kind of, macroeconomic heavy weather that we're now starting to face, I think companies are looking for that. It's like, I don't want to buy five things, five sets of skills, five expensive licenses. I want one platform that can do it. But to your point David, it's the and not the or. We talk about the Data Productivity Cloud, the DPC, as being everyone ready. And what we mean by that is if you are the tech savvy marketer who wants to get a particular insight and you understand what a Rowan economy is, but you're not necessarily a hardcore super geeky data engineer then you can visual low-code, no-code, your data to a point where it's business ready. You can do that really quick. It's easy to understand, it's faster to ramp people onto those projects cause it like explains itself, faster to hand it over cause it's self-documenting. But, they'll always be individuals, teams, "and", "or" use cases that want to high-code as well. Maybe you want to code in SQL or Python, increasingly of course in DBT and you can do that on top of the Data Productivity Cloud as well. So you're not having to make a choice, but is that right? >> So one of the things that Matillion really delivers is speed to insight. I've always said that, you know, when you want to be business ready you want to make fast decisions, you want to act on data quickly, Matillion allows you to, this feed to insight is just unbelievably fast because you blend all of these different data sources, you can find the deficiencies in your process, you fix that and you can quickly turn things around and I don't think there's any other platform that I've ever used that has that ability. So the speed to insight is so tremendous with Matillion. >> The thing I always assume going on in our customers teams, like you run Hoshang is that the visual metaphor, be it around the orchestration and data ops jobs, be it around the transformation. I hope it makes it easier for teams not only to build it in the first place, but to live with it, right? To hand it over to other people and all that good stuff. Is that true? >> Let me highlight that a little bit more and better for you. So, say for example, if you don't have a platform like Matillion, you don't really have a central repository. >> Yeah. >> Where all of your codes meet, you could have a get repository, you could do all of those things. But, for example, for definitions, business definitions, any of those kind of things, you don't want it to live in just a spreadsheet. You want it to have a central platform where everybody can go in, there's detailed notes, copious notes that you can make on Matillion and people know exactly which flow to go to and be part of, and so I kind of think that that's really, really important because that's really helped us in a big, big way. 'Cause when I first got there, you know, you were pulling code from different scripts and things and you were trying to piece everything together. But when you have a platform like Matillion and you actually see it seamlessly across, it's just so phenomenal. >> So, I want to pick up on something Matthew said about, consolidating platforms and vendors because we have some data from PTR, one of our survey partners and they went out, every quarter they do surveys and they asked the customers that were going to decrease their spending in the quarter, "How are you going to do it?" And number one, by far, like, over a third said, "We're going to consolidate redundant vendors." Way ahead of cloud, we going to optimize cloud resource that was next at like 15%. So, confirms what you were saying and you're hearing that a lot. Will you wait? And I think we never get rid of stuff, we talk about it all the time. We call it GRS, get rid of stuff. Were you able to consolidate or at least minimize your expense around? >> Hoshang: Yeah, absolutely. >> What we were able to do is identify different parts of our tech stack that were just either deficient or duplicate, you know, so they're just like, we don't want any duplicate efforts, we just want to be able to have like, a single platform that does things, does things well and Matillion helped us identify all of those different and how do we choose the right tech stack. It's also about like Matillion is so easy to integrate with any tech stack, you know, it's just they have a generic API tool that you can log into anything besides all of the components that are already there. So it's a great platform to help you do that. >> And the three things we always say about the Data Productivity Cloud, everyone ready, we spoke about this is whether low-code, no-code, quasi-technical, quasi-business person using it, through to a high-end data engineer. You're going to feel at home on the DPC. The second one, which Hoshang was just alluding to there is stack ready, right? So it is built for AWS, built for Snowflake, built for Redshift, pure tight integration, push down ELT better than you could write yourself by hand. And then the final one is future ready, which is this idea that you can start now super easy. And we buy software quickly nowadays, right? We spin it up, we try it out and before we know it, the whole organization is using it. And so the future ready talks about that continuum of being able to launch in five minutes, learn it in five hours, deliver your first project in five days and yet still be happy that it's an enterprise scalable platform, five years down track including integrating with all the different things. So Matillion's job holding up the end of the bargain that Hoshang was just talking about there is to ensure we keep putting the features integrations and support into the Data Productivity Cloud to make sure that Hoshang's team can continue to live inside it and do all the things they need to do. >> Hoshang, you talked about the speed to insight being tremendously fast, but if I'm looking at Cisco Meraki from a high level business outcome perspective, what are some of those outcomes that a Matillion is helping Cisco Meraki to achieve. >> So I can just talk in general, not giving you like any specific numbers or anything, but for example, we were trying to understand how well our small and medium business campaigns were doing and we had to actually pull in data from multiple different sources. So not just, our instances of Marketo and Salesforce, we had to look at our internal databases. So Matillion helped us blend all of that together. Once I had all of that data blended, it was then ready to be analyzed. And once we had that analysis done, we were able to confirm that our SMB campaigns were doing well but these the things that we need to do to improve them. When we did that and all of that happened so quickly because they were like, well you need to get data from here, you need to get data from there. And we're like, great, we'll just plug, plug, plug. We put it all together, build transformations and you know we produced this insight and then we were able to reform, refine, and keep getting better and better at it. And you know, we had a 40X return on SMB campaigns. It's unbelievable. >> And there's the revenue tie in right there. >> Hoshang: Yeah. >> Matthew, I know you've been super busy, tons of meetings, you didn't get to see the whole keynote, but one of the themes of Adam Selipsky's keynote was, you know, the three letter word of ETL, they laid out a vision of zero ETL and then they announced zero ETL for Aurora and Redshift. And you think about ETL, I remember the days they said, "Okay, we're going to do ELT." Which is like, raising the debt ceiling, we're just going to kick the can down the road. So, what do you think about that vision? You know, how does it relate to what you guys are doing? >> So there was a, I don't know if this only works in the UK or it works globally. It was a good line many years ago. Rumors of my death are premature or so I think it was an obituary had gone out in the times by accident and that's how the guy responded to it. Something like that. It's a little bit like that. The announcement earlier within the AWS space of zero ETL between platforms like Aurora and Redshift and perhaps more over time is really about data movement, right? So it's about do I need to do a load of high cost in terms of coding and compute, movement of data between one platform, another. At Matillion, we've always seen data movement as an enabling technology, which gets you to the value add of transformation. My favorite metaphor to bring this to life is one of iron. So the world's made of iron, right? The world is literally made of iron ore but iron ore isn't useful until you turn it to steel. Loading data is digging out iron ore from the ground and moving it to the refinery. Transformation of data is turning iron ore into steel and what the announcements you saw earlier from AWS are more about the quarry to the factory bit than they are about the iron ore to the steel bit. And so, I think it's great that platforms are making it easier to move data between them, but it doesn't change the need for Hoshang's business professionals to refine that data into something useful to drive their marketing campaigns. >> Exactly, it's quarry to the factory and a very Snowflake like in a way, right? You make it easy to get in. >> It's like, don't get me wrong, I'm great to see investment going into the Redshift business and the AWS data analytics stack. We do a lot of business there. But yes, this stuff is also there on Snowflake, already. >> I mean come on, we've seen this for years. You know, I know there's a big love fest between Snowflake and AWS 'cause they're selling so much business in the field. But look that we saw it separating computing from storage, then AWS does it and now, you know, why not? It's good sense. That's what customers want. The customer obsessed data sharing is another thing. >> And if you take data sharing as an example from our friends at Snowflake, when that was announced a few people possibly, yourselves, said, "Oh, Matthew what do you think about this? You're in the data movement business." And I was like, "Ah, I'm not really actually, some of my competitors are in the data movement business. I have data movement as part of my platform. We don't charge directly for it. It's just part of the platform." And really what it's to do is to get the data into a place where you can do the fun stuff with it of refining into steel. And so if Snowflake or now AWS and the Redshift group are making that easier that's just faster to fun for me really. >> Yeah, sure. >> Last question, a question for both of you. If you had, you have a brand new shiny car, you got a bumper sticker that you want to put on that car to tell everyone about Matillion, everyone about Cisco Meraki, what does that bumper sticker say? >> So for Matillion, it says Matillion is the Data Productivity Cloud. We help you make your data business ready, faster. And then for a joke I'd write, "Which you are going to need in the face of this tsunami of data." So that's what mine would say. >> Love it. Hoshang, what would you say? >> I would say that Cisco makes some of the best products for IT professionals. And I don't think you can, really do the things you do in IT without any Cisco product. Really phenomenal products. And, we've gone so much beyond just the IT realm. So you know, it's been phenomenal. >> Awesome. Guys, it's been a pleasure having you back on the program. Congrats to you now Hoshang, an alumni of theCUBE. >> Thank you. >> But thank you for talking to us, Matthew, about what's going on with Matillion so much since we've seen you last. I can imagine how much worse going to go on until we see you again. But we appreciate, especially having the Cisco Meraki customer example that really articulates the value of data for everyone. We appreciate your insights and we appreciate your time. >> Thank you. >> Privilege to be here. Thanks for having us. >> Thank you. >> Pleasure. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage.

>>Hello, fabulous cloud community and welcome to Las Vegas. We are the Cube and we will be broadcasting live from the AWS Reinvent Show floor for the next four days. This is our first opening segment. I am joined by the infamous John Furrier. John, it is your 10th year being here at Reinvent. How does >>It feel? It's been a great to see you. It feels great. I mean, just getting ready for the next four days. It's, this is the marathon of all tech shows. It's, it's busy, it's crowd, it's loud and the content and the people here are really kind of changing the game and the stories are always plentiful and deep and just it's, it really is one of those shows you kind of get intoxicated on the show floor and in the event and after hours people are partying. I mean it is like the big show and 10 years been amazing run People getting bigger. You're seeing the changing ecosystem Next Gen Cloud and you got the Classics Classic still kind of doing its thing. So getting a lot data, a lot of data stories. And our guests here are gonna talk more about that. This is the year the cloud kind of goes next gen and you start to see the success Gen One cloud players go on the next level. It's gonna be really fun. Fun week. >>Yes, I'm absolutely thrilled and you can certainly feel the excitement. The show floor doors just opened, people pouring in the drinks are getting stacked behind us. As you mentioned, it is gonna be a marathon and very exciting. On that note, fantastic interview to kick us off here. We're starting the day with Stripe. Please welcome nor and Brian, how are you both doing today? Excited to be here. >>Really happy to be here. Nice to meet you guys. Yeah, >>Definitely excited to be here. Nice to meet you. >>Yeah, you know, you were mentioning you could feel the temperature and the energy in here. It is hot, it's a hot show. We're a hot crew. Let's just be honest about that. No shame in that. No shame in that game. But I wanna, I wanna open us up. You know, Stripe serving 2 million customers according to the internet. AWS with 1 million customers of their own, both leading companies in your industries. What, just in case there's someone in the audience who hasn't heard of Stripe, what is Stripe and how can companies use it along with AWS nor, why don't you start us off? >>Yeah, so Stripe started back in 2010 originally as a payments company that helped businesses accept and process their payments online. So that was something that traditionally had been really tedious, kind of difficult for web developers to set up. And what Stripe did was actually introduce a couple of lines of code that developers could really easily integrate into their websites and start accepting those payments online. So payments is super core to who Stripe is as a company. It's something that we still focus on a lot today, but we actually like to think of ourselves now as more than just a payments company but rather financial infrastructure for the internet. And that's just because we have expanded into so many different tools and technologies that are beyond payments and actually help businesses with just about anything that they might need to do when it comes to the finances of running an online company. So what I mean by that, couple examples being setting up online marketplaces to accept multi-party payments, running subscriptions and recurring payments, collecting sales tax accurately and compliantly revenue recognition and data and analytics. Importantly on all of those things, which is what Brian and I focus on at Stripe. So yeah, since since 2010 Stripes really grown to serve millions of customers, as you said, from your small startups to your large multinational companies, be able to not only run their payments but also run complex financial operations online. >>Interesting. Even the Cube, the customer of Stripe, it's so easy to integrate. You guys got your roots there, but now as you guys got bigger, I mean you guys have massive traction and people are doing more, you guys are gonna talk here on the data pipeline in front you, the engineering manager. What has it grown to, I mean, what are some of the challenges and opportunities your customers are facing as they look at that data pipeline that you guys are talking about here at Reinvent? >>Yeah, so Stripe Data Pipeline really helps our customers get their data out of Stripe and into, you know, their data warehouse into Amazon Redshift. And that has been something that for our customers it's super important. They have a lot of other data sets that they want to join our Stripe data with to kind of get to more complex, more enriched insights. And Stripe data pipeline is just a really seamless way to do that. It lets you, without any engineering, without any coding, with pretty minimal setup, just connect your Stripe account to your Amazon Redshift data warehouse, really secure. It's encrypted, you know, it's scalable, it's gonna meet all of the needs of kind of a big enterprise and it gets you all of your Stripe data. So anything in our api, a lot of our reports are just like there for you to take and this just overcomes a big hurdle. I mean this is something that would take, you know, multiple engineers months to build if you wanted to do this in house. Yeah, we give it to you, you know, with a couple clicks. So it's kind of a, a step change for getting data out of Stripe into your data work. >>Yeah, the topic of this chat is getting more data outta your data from Stripe with the pipelining, this is kind of an interesting point, I want to get your thoughts. You guys are in the, in the front lines with customers, you know, stripes started out with their roots line of code, get up and running, payment gateway, whatever you wanna call it. Developers just want to get cash on the door. Thank you very much. Now you're kind of turning in growing up and continue to grow. Are you guys like a financial cloud? I mean, would you categorize yourself as a, cuz you're on top of aws? >>Yeah, financial infrastructure of the internet was a, was a claim I definitely wanna touch on from your, earlier today it was >>Powerful. You guys are super financial cloud basically. >>Yeah, super cloud basically the way that AWS kind of is the superstar in cloud computing. That's how we feel at Stripe that we want to put forth as financial infrastructure for the internet. So yeah, a lot of similarities. Actually it's funny, we're, we're really glad to be at aws. I think this is the first time that we've participated in a conference like this. But just to be able to participate and you know, be around AWS where we have a lot of synergies both as companies. Stripe is a customer of AWS and you know, for AWS users they can easily process payments through Stripe. So a lot of synergies there. And yeah, at a company level as well, we find ourselves really aligned with AWS in terms of the goals that we have for our users, helping them scale, expand globally, all of those good things. >>Let's dig in there a little bit more. Sounds like a wonderful collaboration. We love to hear of technology partnerships like that. Brian, talk to us a little bit about the challenges that the data pipeline solves from Stripe for Redshift users. >>Yeah, for sure. So Stripe Data Pipeline uses Amazon RedShift's built in data sharing capabilities, which gives you kind of an instant view into your Stripe data. If you weren't using Stripe data pipeline, you would have to, you know, ingest the state out of our api, kind of pull yourself manually. And yeah, I think that's just like a big part of it really is just the simplicity with what you can pull the data. >>Yeah, absolutely. And I mean the, the complexity of data and the volume of it is only gonna get bigger. So tools like that that can make things a lot easier are what we're all looking for. >>What's the machine learning angle? Cause I know there's lots of big topic here this year. More machine learning, more ai, a lot more solutions on top of the basic building blocks and the primitives at adds, you guys fit right into that. Cause developers doing more, they're either building their own or rolling out solutions. How do you guys see you guys connecting into that with the pipeline? Because, you know, data pipelining people like, they like that's, it feels like a heavy lift. What's the challenge there? Because when people roll their own or try to get in, it's, it's, it could be a lot of muck as they say. Yeah. What's the, what's the real pain point that you guys solve? >>So in terms of, you know, AI and machine learning, what Stripe Data Pipeline is gonna give you is it gives you a lot of signals around your payments that you can incorporate into your models. We actually have a number of customers that use Stripe radar data, so our fraud product and they integrate it with their in-house data that they get from other sources, have a really good understanding of fraud within their whole business. So it's kind of a way to get that data without having to like go through the process of ingesting it. So like, yeah, your, your team doesn't have to think about the ingestion piece. They can just think about, you know, building models, enriching the data, getting insights on top >>And Adam, so let's, we call it etl, the nasty three letter word in my interview with them. And that's what we're getting to where data is actually connecting via APIs and pipelines. Yes. Seamlessly into other data. So the data mashup, it feels like we're back into in the old mashup days now you've got data mashing up together. This integration's now a big practice, it's a becoming an industry standard. What are some of the patterns and matches that you see around how people are integrating their data? Because we all know machine learning works better when there's more data available and people want to connect their data and integrate it without the hassle. What's the, what's some of the use cases that >>Yeah, totally. So as Brian mentioned, there's a ton of use case for engineering teams and being able to get that data reported over efficiently and correctly and that's, you know, something exactly like you touched on that we're seeing nowadays is like simply having access to the data isn't enough. It's all about consolidating it correctly and accurately and effectively so that you can draw the best insights from that. So yeah, we're seeing a lot of use cases for teams across companies, including, a big example is finance teams. We had one of our largest users actually report that they were able to close their books faster than ever from integrating all of their Stripe revenue data for their business with their, the rest of their data in their data warehouse, which was traditionally something that would've taken them days, weeks, you know, having to do the manual aspect. But they were able to, to >>Simplify that, Savannah, you know, we were talking at the last event we were at Supercomputing where it's more speeds and feeds as people get more compute power, right? They can do more at the application level with developers. And one of the things we've been noticing I'd love to get your reaction to is as you guys have customers, millions of customers, are you seeing customers doing more with Stripe that's not just customers where they're more of an ecosystem partner of Stripe as people see that Stripe is not just a, a >>More comprehensive solution. >>Yeah. What's going on with the customer base? I can see the developers embedding it in, but once you get Stripe, you're like a, you're the plumbing, you're the financial bloodline if you will for the all the applications. Are your customers turning into partners, ecosystem partners? How do you see that? >>Yeah, so we definitely, that's what we're hoping to do. We're really hoping to be everything that a user needs when they wanna run an online business, be able to come in and maybe initially they're just using payments or they're just using billing to set up subscriptions but down the line, like as they grow, as they might go public, we wanna be able to scale with them and be able to offer them all of the products that they need to do. So Data Pipeline being a really important one for, you know, if you're a smaller company you might not be needing to leverage all of this big data and making important product decisions that you know, might come down to the very details, but as you scale, it's really something that we've seen a lot of our larger users benefit from. >>Oh and people don't wanna have to factor in too many different variables. There's enough complexity scaling a business, especially if you're headed towards IPO or something like that. Anyway, I love that the Stripe data pipeline is a no code solution as well. So people can do more faster. I wanna talk about it cuz it struck me right away on our lineup that we have engineering and product marketing on the stage with us. Now for those who haven't worked in a very high growth, massive company before, these teams can have a tiny bit of tension only because both teams want a lot of great things for the end user and their community. Tell me a little bit about the culture at Stripe and what it's like collaborating on the data pipeline. >>Yeah, I mean I, I can kick it off, you know, from, from the standpoint like we're on the same team, like we want to grow Stripe data pipeline, that is the goal. So whatever it takes to kind of get that job done is what we're gonna do. And I think that is something that is just really core to all of Stripe is like high collaboration, high trust, you know, this is something where we can all win if we work together. You don't need to, you know, compete with like products for like resourcing or to get your stuff done. It's like no, what's the, what's the, the team goal here, right? Like we're looking for team wins, not, you know, individual wins. >>Awesome. Yeah. And at the end of the day we have the same goal of connecting the product and the user in a way that makes sense and delivering the best product to that target user. So it's, it's really, it's a great collaboration and as Brian mentioned, the culture at Stripe really aligns with that as >>Well. So you got the engineering teams that get value outta that you guys are dealing with, that's your customer. But the security angle really becomes a big, I think catalyst cuz not just engineering, they gotta build stuff in so they're always building, but the security angle's interesting cuz now you got that data feeding security teams, this is becoming very secure security ops oriented. >>Yeah, you know, we are really, really tight partners with our internal security folks. They review everything that we do. We have a really robust security team. But I think, you know, kind of tying back to the Amazon side, like Amazon, Redshift is a very secure product and the way that we share data is really secure. You know, the, the sharing mechanism only works between encrypted clusters. So your data is encrypted at rest, encrypted and transit and excuse me, >>You're allowed to breathe. You also swallow the audience as well as your team at Stripe and all of us here at the Cube would like your survival. First and foremost, the knowledge we'll get to the people. >>Yeah, for sure. Where else was I gonna go? Yeah, so the other thing like you kind of mentioned, you know, there are these ETLs out there, but they, you know that that requires you to trust your data to a third party. So that's another thing here where like your data is only going from stripe to your cluster. There's no one in the middle, no one else has seen what you're doing, there's no other security risks. So security's a big focus and it kind of runs through the whole process both on our side and Amazon side. >>What's the most important story for Stripe at this event? You guys hear? How would you say, how would you say, and if you're on the elevator, what's going on with Stripe? Why now? What's so important at Reinvent for Stripe? >>Yeah, I mean I'm gonna use this as an opportunity to plug data pipelines. That's what we focus on. We're here representing the product, which is the easiest way for any user of aws, a user of Amazon, Redshift and a user of Stripe be able to connect the dots and get their data in the best way possible so that they can draw important business insights from that. >>Right? >>Yeah, I think, you know, I would double what North said, really grow Stripe data pipeline, get it to more customers, get more value for our customers by connecting them with their data and with reporting. I think that's, you know, my goal here is to talk to folks, kind of understand what they want to see out of their data and get them onto Stripe data pipeline. >>And you know, former Mike Mikela, former eight executive now over there at Stripe leading the charge, he knows a lot about Amazon here at aws. The theme tomorrow, Adams Leslie keynote, it's gonna be a lot about data, data integration, data end to end Lifeing, you see more, we call it data as code where engineering infrastructure as code was cloud was starting to see a big trend towards data as code where it's more of an engineering opportunity and solution insights. This data as code is kinda like the next evolution. What do you guys think about that? >>Yeah, definitely there is a ton that you can get out of your data if it's in the right place and you can analyze it in the correct ways. You know, you look at Redshift and you can pull data from Redshift into a ton of other products to like, you know, visualize it to get machine learning insights and you need the data there to be able to do this. So again, Stripe Data Pipeline is a great way to take your data and integrate it into the larger data picture that you're building within your company. >>I love that you are supporting businesses of all sizes and millions of them. No. And Brian, thank you so much for being here and telling us more about the financial infrastructure of the internet. That is Stripe, John Furrier. Thanks as always for your questions and your commentary. And thank you to all of you for tuning in to the Cubes coverage of AWS Reinvent Live here from Las Vegas, Nevada. I'm Savannah Peterson and we look forward to seeing you all week.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante the ascendancy of AWS under the leadership of Andy jassy was marked by a tsunami of data and corresponding cloud services to leverage that data now those Services they mainly came in the form of Primitives I.E basic building blocks that were used by developers to create more sophisticated capabilities AWS in the 2020s being led by CEO Adam solipski will be marked by four high-level Trends in our opinion one A Rush of data that will dwarf anything we've previously seen two a doubling or even tripling down on the basic elements of cloud compute storage database security Etc three a greater emphasis on end-to-end integration of AWS services to simplify and accelerate customer adoption of cloud and four significantly deeper business integration of cloud Beyond it as an underlying element of organizational operations hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we extract and analyze nuggets from John furrier's annual sit-down with the CEO of AWS we'll share data from ETR and other sources to set the context for the market and competition in cloud and we'll give you our glimpse of what to expect at re invent in 2022. now before we get into the core of our analysis Alibaba has announced earnings they always announced after the big three you know a month later and we've updated our Q3 slash November hyperscale Computing forecast for the year as seen here and we're going to spend a lot of time on this as most of you have seen the bulk of it already but suffice to say alibaba's cloud business is hitting that same macro Trend that we're seeing across the board but a more substantial slowdown than we expected and more substantial than its peers they're facing China headwinds they've been restructuring its Cloud business and it's led to significantly slower growth uh in in the you know low double digits as opposed to where we had it at 15 this puts our year-end estimates for 2022 Revenue at 161 billion still a healthy 34 growth with AWS surpassing 80 billion in 2022 Revenue now on a related note one of the big themes in Cloud that we've been reporting on is how customers are optimizing their Cloud spend it's a technique that they use and when the economy looks a little shaky and here's a graphic that we pulled from aws's website which shows the various pricing plans at a high level as you know they're much more granular than that and more sophisticated but Simplicity we'll just keep it here basically there are four levels first one here is on demand I.E pay by the drink now we're going to jump down to what we've labeled as number two spot instances that's like the right place at the right time I can use that extra capacity in the moment the third is reserved instances or RIS where I pay up front to get a discount and the fourth is sort of optimized savings plans where customers commit to a one or three year term and for a better price now you'll notice we labeled the choices in a different order than AWS presented them on its website and that's because we believe that the order that we chose is the natural progression for customers this started on demand they maybe experiment with spot instances they move to reserve instances when the cloud bill becomes too onerous and if you're large enough you lock in for one or three years okay the interesting thing is the order in which AWS presents them we believe that on-demand accounts for the majority of AWS customer spending now if you think about it those on-demand customers they're also at risk customers yeah sure there's some switching costs like egress and learning curve but many customers they have multiple clouds and they've got experience and so they're kind of already up to a learning curve and if you're not married to AWS with a longer term commitment there's less friction to switch now AWS here presents the most attractive plan from a financial perspective second after on demand and it's also the plan that makes the greatest commitment from a lock-in standpoint now In fairness to AWS it's also true that there is a trend towards subscription-based pricing and we have some data on that this chart is from an ETR drill down survey the end is 300. pay attention to the bars on the right the left side is sort of busy but the pink is subscription and you can see the trend upward the light blue is consumption based or on demand based pricing and you can see there's a steady Trend toward subscription now we'll dig into this in a later episode of Breaking analysis but we'll share with you a little some tidbits with the data that ETR provides you can select which segment is and pass or you can go up the stack Etc but so when you choose is and paths 44 of customers either prefer or are required to use on-demand pricing whereas around 40 percent of customers say they either prefer or are required to use subscription pricing again that's for is so now the further mu you move up the stack the more prominent subscription pricing becomes often with sixty percent or more for the software-based offerings that require or prefer subscription and interestingly cyber security tracks along with software at around 60 percent that that prefer subscription it's likely because as with software you're not shutting down your cyber protection on demand all right let's get into the expectations for reinvent and we're going to start with an observation in data in this 2018 book seeing digital author David michella made the point that whereas most companies apply data on the periphery of their business kind of as an add-on function successful data companies like Google and Amazon and Facebook have placed data at the core of their operations they've operationalized data and they apply machine intelligence to that foundational element why is this the fact is it's not easy to do what the internet Giants have done very very sophisticated engineering and and and cultural discipline and this brings us to reinvent 2022 in the future of cloud machine learning and AI will increasingly be infused into applications we believe the data stack and the application stack are coming together as organizations build data apps and data products data expertise is moving from the domain of Highly specialized individuals to Everyday business people and we are just at the cusp of this trend this will in our view be a massive theme of not only re invent 22 but of cloud in the 2020s the vision of data mesh We Believe jamachtagani's principles will be realized in this decade now what we'd like to do now is share with you a glimpse of the thinking of Adam solipsky from his sit down with John Furrier each year John has a one-on-one conversation with the CEO of AWS AWS he's been doing this for years and the outcome is a better understanding of the directional thinking of the leader of the number one Cloud platform so we're now going to share some direct quotes I'm going to run through them with some commentary and then bring in some ETR data to analyze the market implications here we go this is from solipsky quote I.T in general and data are moving from departments into becoming intrinsic parts of how businesses function okay we're talking here about deeper business integration let's go on to the next one quote in time we'll stop talking about people who have the word analyst we inserted data he meant data data analyst in their title rather will have hundreds of millions of people who analyze data as part of their day-to-day job most of whom will not have the word analyst anywhere in their title we're talking about graphic designers and pizza shop owners and product managers and data scientists as well he threw that in I'm going to come back to that very interesting so he's talking about here about democratizing data operationalizing data next quote customers need to be able to take an end-to-end integrated view of their entire data Journey from ingestion to storage to harmonizing the data to being able to query it doing business Intelligence and human-based Analysis and being able to collaborate and share data and we've been putting together we being Amazon together a broad Suite of tools from database to analytics to business intelligence to help customers with that and this last statement it's true Amazon has a lot of tools and you know they're beginning to become more and more integrated but again under jassy there was not a lot of emphasis on that end-to-end integrated view we believe it's clear from these statements that solipsky's customer interactions are leading him to underscore that the time has come for this capability okay continuing quote if you have data in one place you shouldn't have to move it every time you want to analyze that data couldn't agree more it would be much better if you could leave that data in place avoid all the ETL which has become a nasty three-letter word more and more we're building capabilities where you can query that data in place end quote okay this we see a lot in the marketplace Oracle with mySQL Heatwave the entire Trend toward converge database snowflake [ __ ] extending their platforms into transaction and analytics respectively and so forth a lot of the partners are are doing things as well in that vein let's go into the next quote the other phenomenon is infusing machine learning into all those capabilities yes the comments from the michelleographic come into play here infusing Ai and machine intelligence everywhere next one quote it's not a data Cloud it's not a separate Cloud it's a series of broad but integrated capabilities to help you manage the end-to-end life cycle of your data there you go we AWS are the cloud we're going to come back to that in a moment as well next set of comments around data very interesting here quote data governance is a huge issue really what customers need is to find the right balance of their organization between access to data and control and if you provide too much access then you're nervous that your data is going to end up in places that it shouldn't shouldn't be viewed by people who shouldn't be viewing it and you feel like you lack security around that data and by the way what happens then is people overreact and they lock it down so that almost nobody can see it it's those handcuffs there's data and asset are reliability we've talked about that for years okay very well put by solipsky but this is a gap in our in our view within AWS today and we're we're hoping that they close it at reinvent it's not easy to share data in a safe way within AWS today outside of your organization so we're going to look for that at re invent 2022. now all this leads to the following statement by solipsky quote data clean room is a really interesting area and I think there's a lot of different Industries in which clean rooms are applicable I think that clean rooms are an interesting way of enabling multiple parties to share and collaborate on the data while completely respecting each party's rights and their privacy mandate okay again this is a gap currently within AWS today in our view and we know snowflake is well down this path and databricks with Delta sharing is also on this curve so AWS has to address this and demonstrate this end-to-end data integration and the ability to safely share data in our view now let's bring in some ETR spending data to put some context around these comments with reference points in the form of AWS itself and its competitors and partners here's a chart from ETR that shows Net score or spending momentum on the x-axis an overlap or pervasiveness in the survey um sorry let me go back up the net scores on the y-axis and overlap or pervasiveness in the survey is on the x-axis so spending momentum by pervasiveness okay or should have share within the data set the table that's inserted there with the Reds and the greens that informs us to how the dots are positioned so it's Net score and then the shared ends are how the plots are determined now we've filtered the data on the three big data segments analytics database and machine learning slash Ai and we've only selected one company with fewer than 100 ends in the survey and that's databricks you'll see why in a moment the red dotted line indicates highly elevated customer spend at 40 percent now as usual snowflake outperforms all players on the y-axis with a Net score of 63 percent off the charts all three big U.S cloud players are above that line with Microsoft and AWS dominating the x-axis so very impressive that they have such spending momentum and they're so large and you see a number of other emerging data players like rafana and datadog mongodbs there in the mix and then more established players data players like Splunk and Tableau now you got Cisco who's gonna you know it's a it's a it's a adjacent to their core networking business but they're definitely into you know the analytics business then the really established players in data like Informatica IBM and Oracle all with strong presence but you'll notice in the red from the momentum standpoint now what you're going to see in a moment is we put red highlights around databricks Snowflake and AWS why let's bring that back up and we'll explain so there's no way let's bring that back up Alex if you would there's no way AWS is going to hit the brakes on innovating at the base service level what we call Primitives earlier solipsky told Furrier as much in their sit down that AWS will serve the technical user and data science Community the traditional domain of data bricks and at the same time address the end-to-end integration data sharing and business line requirements that snowflake is positioned to serve now people often ask Snowflake and databricks how will you compete with the likes of AWS and we know the answer focus on data exclusively they have their multi-cloud plays perhaps the more interesting question is how will AWS compete with the likes of Specialists like Snowflake and data bricks and the answer is depicted here in this chart AWS is going to serve both the technical and developer communities and the data science audience and through end-to-end Integrations and future services that simplify the data Journey they're going to serve the business lines as well but the Nuance is in all the other dots in the hundreds or hundreds of thousands that are not shown here and that's the AWS ecosystem you can see AWS has earned the status of the number one Cloud platform that everyone wants to partner with as they say it has over a hundred thousand partners and that ecosystem combined with these capabilities that we're discussing well perhaps behind in areas like data sharing and integrated governance can wildly succeed by offering the capabilities and leveraging its ecosystem now for their part the snowflakes of the world have to stay focused on the mission build the best products possible and develop their own ecosystems to compete and attract the Mind share of both developers and business users and that's why it's so interesting to hear solipski basically say it's not a separate Cloud it's a set of integrated Services well snowflake is in our view building a super cloud on top of AWS Azure and Google when great products meet great sales and marketing good things can happen so this will be really fun to watch what AWS announces in this area at re invent all right one other topic that solipsky talked about was the correlation between serverless and container adoption and you know I don't know if this gets into there certainly their hybrid place maybe it starts to get into their multi-cloud we'll see but we have some data on this so again we're talking about the correlation between serverless and container adoption but before we get into that let's go back to 2017 and listen to what Andy jassy said on the cube about serverless play the clip very very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top of AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with Lambda which is I think if Amazon were starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on on our serverless capabilities now we still have plenty of capabilities and features and functionality we need to add to to Lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of Lambda and lots of real applications you know finra has built a good chunk of their market watch application on top of Lambda and Thompson Reuters has built you know one of their key analytics apps like people are building real serious things on top of Lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two so years ago when Jesse gave a road map that serverless was going to be a key developer platform going forward and so lipsky referenced the correlation between serverless and containers in the Furrier sit down so we wanted to test that within the ETR data set now here's a screen grab of The View across 1300 respondents from the October ETR survey and what we've done here is we've isolated on the cloud computing segment okay so you can see right there cloud computing segment now we've taken the functions from Google AWS Lambda and Microsoft Azure functions all the serverless offerings and we've got Net score on the vertical axis we've got presence in the data set oh by the way 440 by the way is highly elevated remember that and then we've got on the horizontal axis we have the presence in the data center overlap okay that's relative to each other so remember 40 all these guys are above that 40 mark okay so you see that now what we're going to do this is just for serverless and what we're going to do is we're going to turn on containers to see the correlation and see what happens so watch what happens when we click on container boom everything moves to the right you can see all three move to the right Google drops a little bit but all the others now the the filtered end drops as well so you don't have as many people that are aggressively leaning into both but all three move to the right so watch again containers off and then containers on containers off containers on so you can see a really major correlation between containers and serverless okay so to get a better understanding of what that means I call my friend and former Cube co-host Stu miniman what he said was people generally used to think of VMS containers and serverless as distinctly different architectures but the lines are beginning to blur serverless makes things simpler for developers who don't want to worry about underlying infrastructure as solipsky and the data from ETR indicate serverless and containers are coming together but as Stu and I discussed there's a spectrum where on the left you have kind of native Cloud VMS in the middle you got AWS fargate and in the rightmost anchor is Lambda AWS Lambda now traditionally in the cloud if you wanted to use containers developers would have to build a container image they have to select and deploy the ec2 images that they or instances that they wanted to use they have to allocate a certain amount of memory and then fence off the apps in a virtual machine and then run the ec2 instances against the apps and then pay for all those ec2 resources now with AWS fargate you can run containerized apps with less infrastructure management but you still have some you know things that you can you can you can do with the with the infrastructure so with fargate what you do is you'd build the container images then you'd allocate your memory and compute resources then run the app and pay for the resources only when they're used so fargate lets you control the runtime environment while at the same time simplifying the infrastructure management you gotta you don't have to worry about isolating the app and other stuff like choosing server types and patching AWS does all that for you then there's Lambda with Lambda you don't have to worry about any of the underlying server infrastructure you're just running code AS functions so the developer spends their time worrying about the applications and the functions that you're calling the point is there's a movement and we saw in the data towards simplifying the development environment and allowing the cloud vendor AWS in this case to do more of the underlying management now some folks will still want to turn knobs and dials but increasingly we're going to see more higher level service adoption now re invent is always a fire hose of content so let's do a rapid rundown of what to expect we talked about operate optimizing data and the organization we talked about Cloud optimization there'll be a lot of talk on the show floor about best practices and customer sharing data solipsky is leading AWS into the next phase of growth and that means moving beyond I.T transformation into deeper business integration and organizational transformation not just digital transformation organizational transformation so he's leading a multi-vector strategy serving the traditional peeps who want fine-grained access to core services so we'll see continued Innovation compute storage AI Etc and simplification through integration and horizontal apps further up to stack Amazon connect is an example that's often cited now as we've reported many times databricks is moving from its stronghold realm of data science into business intelligence and analytics where snowflake is coming from its data analytics stronghold and moving into the world of data science AWS is going down a path of snowflake meet data bricks with an underlying cloud is and pass layer that puts these three companies on a very interesting trajectory and you can expect AWS to go right after the data sharing opportunity and in doing so it will have to address data governance they go hand in hand okay price performance that is a topic that will never go away and it's something that we haven't mentioned today silicon it's a it's an area we've covered extensively on breaking analysis from Nitro to graviton to the AWS acquisition of Annapurna its secret weapon new special specialized capabilities like inferential and trainium we'd expect something more at re invent maybe new graviton instances David floyer our colleague said he's expecting at some point a complete system on a chip SOC from AWS and maybe an arm-based server to eventually include high-speed cxl connections to devices and memories all to address next-gen applications data intensive applications with low power requirements and lower cost overall now of course every year Swami gives his usual update on machine learning and AI building on Amazon's years of sagemaker innovation perhaps a focus on conversational AI or a better support for vision and maybe better integration across Amazon's portfolio of you know large language models uh neural networks generative AI really infusing AI everywhere of course security always high on the list that reinvent and and Amazon even has reinforce a conference dedicated to it uh to security now here we'd like to see more on supply chain security and perhaps how AWS can help there as well as tooling to make the cio's life easier but the key so far is AWS is much more partner friendly in the security space than say for instance Microsoft traditionally so firms like OCTA and crowdstrike in Palo Alto have plenty of room to play in the AWS ecosystem we'd expect of course to hear something about ESG it's an important topic and hopefully how not only AWS is helping the environment that's important but also how they help customers save money and drive inclusion and diversity again very important topics and finally come back to it reinvent is an ecosystem event it's the Super Bowl of tech events and the ecosystem will be out in full force every tech company on the planet will have a presence and the cube will be featuring many of the partners from the serial floor as well as AWS execs and of course our own independent analysis so you'll definitely want to tune into thecube.net and check out our re invent coverage we start Monday evening and then we go wall to wall through Thursday hopefully my voice will come back we have three sets at the show and our entire team will be there so please reach out or stop by and say hello all right we're going to leave it there for today many thanks to Stu miniman and David floyer for the input to today's episode of course John Furrier for extracting the signal from the noise and a sit down with Adam solipski thanks to Alex Meyerson who was on production and manages the podcast Ken schiffman as well Kristen Martin and Cheryl Knight helped get the word out on social and of course in our newsletters Rob hoef is our editor-in-chief over at siliconangle does some great editing thank thanks to all of you remember all these episodes are available as podcasts wherever you listen you can pop in the headphones go for a walk just search breaking analysis podcast I published each week on wikibon.com at siliconangle.com or you can email me at david.valante at siliconangle.com or DM me at di vallante or please comment on our LinkedIn posts and do check out etr.ai for the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thanks for watching we'll see it reinvent or we'll see you next time on breaking analysis [Music]

(lively music) >> Welcome back everyone to theCUBE's live coverage in San Francisco for VMware Explorer 22 formerly VMworld, Dave 12 years we've been covering VMware's annual conference. Going next level explores bigger theme, Multi-cloud another inflection point for VMware. And again at the center of it is the partners Zia Yusuf is here senior vice president strategic ecosystem and industry solutions. You're the, you're, you got the keys to the kingdom for VMware, welcome to theCube. >> It's a pleasure, I mean, you guys are a legend here. This is my first time here. So, it's a pleasure and excited to chat with you. >> Well, great to have you, every single year, since 2010 we've always had great commentary and discussion and sometimes contentious discussion around the role of partners. Visa V, VMware's value proposition, VMware dominant and the enterprise data center, everyone knows that. Dominant and hybrid was first there, everyone knows that. Now going to the next level, the customer stay, they stay with VMware, they don't really leave. They still got a great loyal base but now the enterprise is going NextGen cloud native. The partners are energized with the conversations we're hearing is huge. There's changes of roles is clarity on value proposition. Monetization is hoppin'. It's great stuff, what's going on? You're new, but you have a view of this before. Take us through your what's going on in the partner network, what's the state of the union? >> Yeah, I think, thanks for the question. I think maybe just step back a second right, the word partners is a big word. It covers all kinds of things. VMware has had a rich history of partnerships you know, mostly technology related partnerships. So much of our products depend on other partners, OEM partners, and so on. We've also had a rich history of our channel. So, as you look at different channel partners as you look at going through different parts of the segment SMB and so on, in a cloud context, based on what's happening we needed to take an integrated ecosystem approach. That's the word I use, right. And for me it's, it's a little bit like a spider's web. Like no single strand in the web is that strong but when you put it together thoughtfully in a very deliberate way. That's what an integrated ecosystem strategy. And so we've got our VCP partners, longstanding history that machine continues. We've got our channel partners and OEM partners that machinery continues obviously Dell strategic partner, significant business. The parts of the puzzle that I've been focusing on is five other different pieces. So first of course, is our hyper scale partnerships long history with AWS, very successful history. We have GCVE with GCP. We announced, I think three, four months ago that GCP was joining our VMware cloud universal and a big announcement yesterday about Microsoft doing the same. And hopefully we extend that. So, as we work with this hyper scaler six or seven of these partners, it's a, as you can imagine kind of a multidimensional chess game, if you will a little bit competitive mostly cooperative and stuff, right. The GSI is very exciting piece of it. The essentials that Deloitte, Deloitte announced a new business unit on VMware, ACL did the same. That energy level has really gone up. You see it at the show here as well. We recognize that these significant SI's play a huge role in the decision making process with customers. And we want to enable them to build significant VMware businesses. It's a different game from that perspective. Last thing I'm point out is, industry and verticals. Right I mean, this is not being necessarily an area because of the layer of the stack we've been in. Obviously Telco is an end to end business unit for us. We have products, we have a go to market on Telco, public sector to some degree because you need all these three letter agencies and the security and compliance. But as you look at financial services as you look at retail, as you look at healthcare we need to be aware of the workload we need especially on modern apps, especially on the edge. So we kind of doubling down on some of our vertical capabilities. So, all of those things are connected as well, right. The SI to the hyper scale partners in a vertical context. >> What's the biggest change that you've seen? Because we've observed some partners are leaning out as they change their business. And VMware has got new partners coming in, leaning in. So you got mentioned, Dave mentioned Telco and you got new use cases with edge and multi-cloud so you know, some people kind of maybe age out or change their strategy, some double down the core partner network, and then new ones come in. What's been the biggest change, if you can look at that holistically? >> Yeah, it's a great question, right? Because it's so multidimensional and there is no such thing as a GSI global system because they build products. Sometimes they act as a reseller, they're a solution provider. Also they provide services. So as their business model changes, we have to adjust how we engage with them. We can't put them in nice clean buckets. And that's what I'm doing with my colleagues here is how do we really enable them? And one of the things, I mean, I've done this type of stuff, I was at SAP for many years. We need to figure out how do we make them successful? Not just, this is what VMware wants you to do. We need to understand their business model and how do we fit into that? 'Cause if they grow, then we grow with that. And that is honestly a little, it's a subtle point, but it's a little bit of a nuanced. >> Yeah, it's very nuanced, but you have to nail that. You got to overlay. >> 100% >> The strategy where the enablement is technically or product wise, economics and conflict. (John laughing) >> And profitably, if they're profitably is important to us it's not just their growth. >> So Zia, I want to test the premise on you, something, John and I have been working on this notion of super cloud. And we did an event earlier this month, but one of the aspects that's kind of nuance and futuristic is if I'm a, let's say a financial services company and I'm going through a digital transformation I would be looking strategically at what, say Amazon did taking it's internal IT and then pointing at the world. I would say, I have data. I have tools, I have software, I have expertise that's really unique and could be value add. And I would be thinking, how do I monetize that, create my own cloud. And I'm actually just going to throw it into a public cloud to do that. I've got mainframes running, I've got Oracle stuff on Prem. I'm not going to shift that stuff into the cloud and maybe some of it, but I've got transaction systems and proprietary data. And a lot of it is running on VMware and I've got cloud stuff too. I would be looking at, okay, how do I build my own cloud and put my data, my tooling, my software in front of a new ecosystem, my own ecosystem that I can you know monetize. Are you seeing- >> Without spending the CapEx. >> Yeah, without having to build data centers? Right, exactly. I want to take advantage of the gift that the hyper scalers are given. Are you seeing any activity bubbling up in that regard? >> It's a really, it's a really interesting question. And I think the terminology that we've used around cloud smart kind of goes into that. So let me take what you said. >> Okay please, yeah. >> And frame it in a slightly different way. You can standardize on public clouds and everybody's using the same thing. You're using the same services, and so on. Theoretically that could lose some of your differentiation. Right, I mean, especially for financial services companies that have built so much of their you know, trading test down to the milli, milli, millisecond and how do they do that, and so on. So, I think you have something there right. So, as they look at their technology and software strategy, yes there's cost reduction aspects of it. There's refactoring aspects of it that hygiene that needs to be done as Rughu talked about from this cloud chaos to cloud smart, if you will but then how do you differentiate on the business processes? How do you differentiate that then down into the workloads? And I think that's where to use an old term. It takes a village, right, you've got the system integrator that's providing this stuff. You've got other strategy firms like the BCGs and McKinseys of the world that have huge influence now. Then you've got technology players that are coming into that. And I think the cloud smart approach is to do exactly what you're saying. It's not just the refactoring, it's not just movement to the cloud. How do you retain your competitive edge from the processes the models, the thinking that you've built up over many years. So, I don't know if it's super cloud or what that means, but that at the end of the day, this is about business processes. At the end of the day, this is about having a competitive edge in the market and I think you could do it. >> It's industry cloud, right? >> It's, that's a good way to put it. >> Yeah. >> I think Industry cloud is a good way. >> Why is there security cloud, Why isn't there an insurance cloud? Why's there a FinTech cloud? So I mean if you look at Goldman Sachs capital one. >> Right. >> There, CapEx is handled by AWS. Snowflake built their entire business on AWS. Didn't spend the dime on CapEx. Well, they spent a lot of operating expense for that CapEx and the fees, but still they became successful. And then the rest is history. So, I think people are seeing this idea of I'll ride that back on the CapEx of the hyper scalers and then use the tooling from the partner network and what's available. To then, cobble together in an architectural engineered way, distributed computing way, a new way to do things. Okay, so if you believe that, which we do, then you say, oh, it's on the balance sheet. So, what we've been hearing from companies is like, "Hey it's going to be on the balance sheet", I better have an income statement impact on the top line. So, you start to see behavior change at the customers not IT powering the business and the back office and terminals and some app. >> Crosscutting. >> It's like, no, no, no this is a digital business. So, the integration of balance sheet income statement on the economics is driving a lot of the behavior at the customers. So we see customers thinking this way and it's like we've never seen this level of business model refactoring as well as partner vendor selection, product technology mix at the same time. >> And VMware. >> At this level. >> Need the connective tissue between the hyper scalers in the ecosystem and actually provide those cross cloud connections. >> Yeah. >> You know, to the extent there's a business case there, that's what we're trying to of squint through. Is it going to be hybrid with on-prem in one cloud or is there an advantage of going cross clouds beyond just avoiding lock in you know, to take advantage of global infrastructure? >> So and then the next question is the Tam then bigger which means the partners are better? >> Yeah right. >> Participate in that. >> Yeah, I think, and we look at economics of this, right? I mean, there's a huge emphasis on cost, right. Cost, and I completely get that. I think, as I've talked to customers both now that I'm here but before advising a range of companies the innovation process, the time to impact is equally important all right as you compete. There's no point in just getting your cost down. If you're then getting beaten up in the market and you're not able to differentiate with new digital services. And this is where call it super cloud, call it industry cloud. We need to connect up to the business processes and the business impact and not just in my view the cost infrastructure piece of it. >> Yeah. And that we can't do on our own, we're not an apps company. So we're, you're not SAP, we're not Oracle, but we need to work with those players to make sure that their workloads are optimized in the right cloud in the right configuration. And that is a job to be done as opposed to just let's take it to town. >> And there's clearly a technology business case, especially if we're working with companies like VMware who's going to help me you know, simplify. >> Right. >> My move to the multi-cloud but there's also a business and economic impact in that. Even if it's not, if it could be simple as if I partner with Microsoft I'm going to do more business right if I'm one of these industry clouds. So I see that as another potential tailwind, it's really, it's like when Dreesen says all your companies are software companies, to me all companies are cloud companies, now increasingly. >> Look the difference between cloud and apps and then stuff, I mean like. >> Yeah, it's all. >> It's like you know there's used to be infrastructure and then apps company and so on. We need to deliver with our ecosystem partners and integrated solution and solution with a big S not just the technology solution but the broader, I mean look at the change management. >> Yeah, yeah. >> We talked about culture, I mean, if you don't get that piece right and the change management piece. >> Everything, yeah. >> You know the rest of it is history. >> Well and it's got to be delivered as a service, >> It has to be. >> Which is huge implications as to how you deal with change management. >> And this goes back to my kind of first comment is I really try and think of this by architecting the ecosystem. I don't like the word alliances. Right I mean, let's say kind of a one to one relationship. You know, let's do an agreement, let's go have dinner, but architecting the ecosystem the spiders web, who are the different players how can we compliment each other? And if it, Deloitte and a Microsoft want to do amazing business together related to VMware technology I want to encourage that. And so those third party Connections. >> You guys your contextualizing the ecosystem, basically. And I think from a customers standpoint that's a benefit to them, in my opinion in fact, Dave, remember at our supercloud.world event URL supercloud.world is the plug for the site. They can check it out. One of the comments from the cloudarati panel was we had a title this session called the innovators dilemma you know question mark you know . >> Best book ever written. >> Yeah, yeah. And so the, one of the panels said, it shouldn't be, we should change it to the integrators dilemma because what's happening is that integration is now standard table stakes and, but integrating the right things now matters, right? So, integration for integration sake isn't necessarily the end game anymore. >> And this is where. >> And this kind of where you're getting at with the spider's web is that integrating properly is a solution mindset. >> And look, I'm integrating also, you know have to bring in data from that perspective. Right, at the end of the day data being the new oil, if you will, the integration allows that data to flow to the right place at the right time to make the right decision. Now, we are not doing all of those pieces but we are certainly enabling that. And as you especially start looking at what we can do on the edge and what we can do in a retail store and a factory and so on those kinds of things come together. >> Okay, Zia take some time. We got a couple minutes left, only two minutes left, I want you to get some commentary directly to the audience around what specifically you're doubling down on. That's new that you're investing in on the partner network or your partner strategy. What is a steady state that's being nurtured and farmed or whatever word you want to use, but here's our core thing. Here's the area of improvement we're going to be in you know, cranking the handle on take us through that. >> Sure. >> I know you got OAM, got telco, got new things going on. >> Yeah so, maybe a couple of things right. >> lay it all out. >> First of all it has to be linked to VMware strategy. So as we transition on this journey to subscription saas ARR, we need to bring our ecosystem along to do that. That has business model implications that has implications on how we engage with them, how we define success how we value things. So that's an important journey. Secondly, is we need to do a better job of enabling our partners. Right, I mean, we have our partner connected. We do a pretty good job on the channel side. We need to do a better job on the GSIs is really understanding their business model, how they're engaging with their customers and provide them the technology the support, the financial resources, so that they can be successful. That's very important. Third is, to connect the dots on the ecosystem, right? I mean it's a, I've spent a lot of time in this event as well in joint meetings between system integrators and hyper scalers with our technology colleagues on Intel or NetApp or AMD. And these are companies that we have a rich history with. We're trying to connect, because that's how customers look at it. So, connecting the dots between the ecosystem super important to us, and then look, there's a change management journey within VMware. We also need to understand how we can engage with partners in a more productive, effective way. How do we scale this up? I believe, I think our leadership in Raghu and Sumit we are not going to succeed unless we have a profitable, engaged, passionate ecosystem around. >> Yeah I mean, they got to make money. They got to. >> Exactly. >> Be successful, have successful customers, their end customers your customers. Well, all good, question of where you're investing the most right now. If you had to put a kind of the pie chart together, I mean some of it's steady state like it's a machine, some of it's new like Telco for instance I mean here's. >> I think again, rich history on the channel side, we continue to invest there. Very valuable to go do that. I think some of these newer areas around the system integrators, especially the large ones, the Whipple's the HCLs, Deloittes essentials of the world, very important. The hyper scaler relationships directly leads into ARR. You saw the VMC cloud Universal will continue. >> We have Google on great props from Google. >> Yeah, We love it you guys. >> Yeah, and so look, I think we are not multi-cloud unless we go do this. Right I mean, Raghuram made a joke about this. We were single cloud and now we're multi-cloud, we want our customers to be able to procure these integrated solutions through VMware and our hyper scaler partners will continue to do that's when multi-cloud really become. And so the GTM motion, the discounting the commission structure all of that machinery is an important radio for me. >> Zia thank you so much for coming on theCube. I know you've been super busy. You got to go out and hit all the partners say hello, compressing you know, got to hit the pavement, say hello to everyone. >> It's been fantastic, the partners have too many, too many parties and so. (Interviewers laughing) But that's a fun part of my job, but appreciate your time. >> You got good stamina. >> Thanks Zia. >> So you got to have that in this game. Not about the faint of heart here at VMware. Zia thank you for coming on. >> Of course. >> This is the cube coverage, back after lunch. After the short break day two of three days of live coverage here in Moscone West on the street floor level of the event I'm John Furrier with Dave Alante. We'll be right back. (lively music)

(upbeat music) >> Hey everyone. Welcome back to San Francisco, VMware Explorer 2022, Lisa Martin and Dave Nicholson here. We've been having some great conversations today. Lots of news coming out about VMware and its partner ecosystem. We're going to have another conversation about that next. Please welcome two guests to the program, Chance Bingen, technical marketing engineer at NetApp and Jason Massae, staff technical marketing architect, storage and vVols at VMware. Guys, welcome to the program. >> Thanks. >> Glad to be here. >> It's nice to be back in person. >> It is. It's very nice. Oh my gosh. >> And we're hearing there about 7,000 to 10,000 people here, when I was in the Keynote, this morning it was definitely standing room only. >> Yeah, yeah. You've definitely seen the numbers ticked up at the last minute. It was good to see that. It's good, I think a lot of people have really wanted to get back, get that one on one that face to face. There's nothing like being able to, you know, talk to, the experts, talk to the vendors, you know, see your comrades. I mean, that's the thing. I mean, we've seen people that I haven't seen for years, even on my own team, so really good to be back into it. >> It is and it was lots of news coming out this morning during the Keynote. My goodness. But Jason, talk to me, the NetApp and VMware folks had been in tight partnership for a long time. Talk to me about, get both of your perspective from a technical perspective about the depth of the partnership. >> Yeah, so actually NetApp was one of the original design partners for vVols. And with that, now with some of the stuff we're doing with more current stuff with virtual volumes is, NetApp is back and we've got some pretty neat stuff that we've been working on with vVols. And NetApp's got some pretty neat stuff that they've been working on to enable the customers with more features, more functionality with the virtual volume functionality. >> Yeah, absolutely. >> Give us a quick primer on what is a vVol? What is a virtual volume? How does it fit into the, into this stack of stuff that we do in IT? >> Yeah. So the easiest way to kind of think of what a vVol is or a virtual volume is you can think of it kind of like an RDM, those row device map, which is kind of a four letter word. We don't really like those, but the idea is that object, that virtual volume is native on the array and presented directly to the VM. But now what we do is we're presenting all of the storage array features up to vSphere and we're managing those storage features via policy based management. But instead of applying storage capabilities at a data store level, we're now applying them at a VM or an application level. So you can have one data store and multiple VMs, and every VM can have a different storage capability managed by a policy that the VI admin gets to manage now. So he doesn't have to go to the storage admin to say, I need a new line, or I need a new volume. He can just go in and create a policy or change a policy. And now that storage capability is applied to the VM or the application. >> Yeah. One thing I'd like to add to that is you can mentioned the word capabilities. >> So we look at the actual data protocols, whether they're file based or block based, you know, I-scuzzy, fiber channel, whatever the case might be. Those protocols have defined sets of capabilities and attributes and things they can expose. What vVols along with the VASA protocol brings to the table is the ability to expose things that are just impossible to expose via the data protocols themselves. So that the, actual nature of the array, what kind of array is it? What's it capable of doing? What is the nature of, you know, encryption? You know, is this going to be a secure, encrypted data store? Is it going to be something else? It just allows you to do so much more with the advanced capabilities that modern storage arrays have than you could ever do if you were just using the data protocols by themselves. >> Right? Yeah. Kind of under that same context. If you think about before with traditional storage, the vSphere or the array really doesn't understand what's going on underlying storage, but with vVols the array and vSphere completely understand at a disc level even, how that VM should be treated. So that helps the storage admin. Storage admin can now go in and see a specific disc of a VM and see the performance on the array. They can go in the array and see, oh, this disc on this VM has got performance issues or needs to be encrypted, or here's the size of that disc. And you couldn't easily see that with your traditional storage. So there's really a lot of benefits and it frees up a lot of time for the storage administrator and enables the VI admin to be able to do a lot of the storage management. >> So there have been, there been a lot of movements over the last decade in the realm of software defined storage. Where essentially all of the things that you are talking about are completely abstracted from the underlying hardware. In this case, you're leveraging the horsepower, if you will and the intelligence of a storage array that has a lot of horsepower and intelligence, and you're accessing those features. You mentioned encryption, whether if you're doing a snapshot or something like that, what's interesting here is it kind of maps to what we're looking at now, which is the trend in the direction of things like DPUs. >> If you go back in history long enough, we had the, you know, the TOE, NIC, TCP offload, you know, the idea of, hey, you know what, what if we had a smart device with its own brain power and we leveraged it. Well, you guys have been doing that from a vVols all perspective with NetApp filers, for lack of better term. For how long now, when did, when were they originally? >> 6.0 it was so it's been what? 11, 12 years. Something like that. >> It's been a while. So yeah, but it's been a decade or so. >> Mm-hmm >> So what's on the frontier. What's the latest there in terms of, in terms of cool stuff that's coming out. >> So actually today, in one of the things that we worked with NetApp that was part of the design partnership was, you know, the NVMe over Fabric protocol has become very popular to extend that functionality of all flash to the, an external array. And now we announce today, in including with that NVMe over Fabrics, you can now do vVols with NVMe over Fabrics. And again, that was something that we worked with NetApp to be a design partner for them. >> That's right. We're very excited about it. We've always been, you know, NVMe been something we've been very proud of for a while. Delivering the first end to end NVMe stack from inside the host, through the fabric, to the array, with the arrays front ports, all the way to the disc on the backend. So we're very excited about that. >> So target market joint NetApp, VMware customers, I presume. >> Really it's, the key here that I like to make sure customers understand is to see that vVols are on the leading edge of VMware's storage design. Some tend to think that maybe vVols wasn't the primary focus, but actually now it is the primary focus. Now I always like to give the caveat that VMFS and NFS are not going away. Those are still very much stuff that we work on. It's just that most of the engineering focus is on virtual volumes or vVols. >> Yeah. Similarly, when you talk about and you're sort of alluding to vSAN when we start talking about VMFS and things like that. >> Yeah. >> Architecturally, we've been talking to folks about the recent announcements with capabilities within AWS. You know, NetApp in AWS for VMware environments. Breaking out of the stranglehold that the, oh, you want more storage, you must buy more CPU and memory, building block process entails. The reality is no matter what you do with vSAN, you're going to have certain constraints that go away when now you have the option to leverage storage from the NetApp filers. >> Yeah, absolutely. >> So how does, how do vVols play in the cloud strategy moving forward? >> Well, so one of the things that we do with, vVols currently is mostly On-prem. But when you have the storage architecture, that vVols gives you as far as individual objects, it makes it much easier to migrate up into the cloud because you're not trying to migrate individual VMs that are on another type of system, whatever it might be, those objects are already their own entity. Right, so cloud, Tanzu, those type of things, those vVol objects are already their own entity. So it makes it very easy to migrate them on and off prem. >> So Chance talk to us a little bit about this from NetApp's perspective. You're in customer conversations, who are you talking to? Is this primarily an engineering conversation? Has this gone up the stack in terms of customers are finding themselves in this default multi-cloud environment? >> Yeah, so interestingly, when I talk to customers these days they are almost all either on a journey to a hybrid multi-cloud or they're in some kind of phase of transforming themselves into their own hyperscaler, right? They're be adopting a cloud service provider model and vVols is a perfect fit for that kind of model, because you have the ability to offer different tiers of service, different qualities of service with VM granular controls or VMDK granular controls, even. And even if you look at First Class Disc, right? Which is something that came out largely to support Tanzu, I think which fantastic use case for vVols as well there, but that gives you the ability to offer something like Amazon EBS, right? You can offer Amazon EBS in a native VMware stack using First Class Discs and vVols. And you're able to apply things like quality of service with that granular control that allows you to guarantee that customer the disc that they bought and paid for. They're going to get the IOPS that they're paying for because you're applying those QoS policies directly to that object on the array. And instead of having to worry about is the array going to be able to handle it? Are you going to have one VM that consumes all your IO, you know? You don't have to worry about that with vVols because you've got that integration with the array's native quality controls. >> And Chance what's in this for me as a customer? I'm hearing productivity, I'm hearing cost savings, control efficiency. Talk to me about the benefits in it for the folks that you're talking to. >> Yeah, absolutely. A lot of times it comes down to, you know I mentioned like the cloud service provider model, right? When you're looking to build a robust service catalog and you're able, you want to be able to meet all these like, we mentioned Tanzu, right? Containers as a service, you're able to provide the persistent volumes for your Kubernetes containers that are again, these native objects on the array and you have these fine grain controls, but it's handled at massive scale because it's all handled by storage policies, Kubernetes storage classes, which are natively mapped to VM storage policies through Tanzu. So it just, it gives you the ability to offer all of these services in a, again a rich and robust contents catalog. >> So what are you doing? So you mentioned a couple of things in terms of using array based quality of service. So give me an example of how you're avoiding issues of contention and over subscription in an environment where I'm an administrator and I've got this virtual volume that's servicing this VM or this app on this VM. What kind of visibility do I have down into the actual resources because look at the end of that chain there's a physical resource. And that physical resource represents, what? IOPS and bandwidth and latency and throughput and all of this bundle of things. So how do you avoid colliding with others who are trying to carve vVols out of this world? >> You mean like a noisy neighbor type of thing? >> Yeah. Yeah. >> So that's actually one of the big benefits that you get with vVols is that because those vial objects are native on the array, they're not sharing a loan or a volume. They're not sharing a resource. The only resource they're actually sharing is the array itself. So you don't get that typical noisy neighbor where this one's using all the resources of that volume because really you're looking out at the all encompassing array. And so a storage administrator and the VI admin have a lot more insight. The VI admin can now go to the storage admin if there's say a debugging issue, they want to find a problem. The storage admin now can see those individual objects and say, oh, well this VM, it's not really this, it's not all the discs. It's just disc number two or disc number three or they can actually see at a single disc level on the array, the performance, the latency, you know, the QS, all that stuff. >> Oh, absolutely. >> And that really is what, it frees up at the storage admin's time because the debugging is so much more simple. And it also allows the storage admin a lot more insight. Right? They know those, what's the problem. If you were typically looking at a loaner volume, they don't really know what's going on inside that and neither does the array. But with vVols, the array knows what each disc and how it's supposed to be treated based on the policies that the customer defines. So if one VM is supposed to have a certain QS and another VM isn't. The array knows that that VM, if it goes above it, it's going to be like, nope, you can't have those resources. You weren't granted those resources, but this one was. So you have much more control. And again, it's at an application or a VM level. >> And it's still, it's fairly dynamically configurable. I spoke to a customer just the other day. They are a cloud service provider. And what they do is their customers are able to go in and change their quality of service. So they go into that service portal and they say, okay, I'm paying for gold and I want platinum and they'll go in. They know that they've got a certain time where they need more IO capacity. So they'll go in, they'll pay the fee, increase that capability. And then when they don't need it anymore, they'll downgrade again. >> Okay, so that assumes some ability at the array level to do some sort of resource sharing and balancing to be able to go out and get, say more IO. Because again, fundamentally, if you have a virtual volume, that's drawing its resources from five storage devices, whether those are SSD based or NVMe or spinning disc that represents a finite it amount of resource. The assumption is if you're saying that the array is the pool that you need to worry about, that assumes the array has the ability to go beyond here, based on a policy. >> So that's how it works. It does... >> Well, essentially. I mean, you can't outrun physics. So if the array can't go faster, but the idea is that you understand the performance profile of your array and then you create your service tiers appropriately. >> Okay. >> Yeah. And one of the big benefits is like Chance was saying, if you want to change a profile that used to be a Storage vMotion to a different data store. Now it's just a policy change. The storage admin doesn't have to do anything. The VI admin just changes the policy. And then the array understands, oh, I now need to treat that different. And that's exactly what Chance was talking about in that cloud provider situation, where today I'm using a 100,000 IOPS. I need to use 200,000 tomorrow for special, whatever it is, but I only need to use it for tomorrow. So they don't have to move anything. They just change the policy for that time. And then they change it back. They don't have to do anything on the array itself. They don't have to change anything physically on the VM. It's just a policy change. And that's really where you get that dynamic control of the storage capability. >> So as business dynamics are changing and I'm thinking of like black Friday or Prime day, being able to dial things up and dial it down, they have the ability to do that with a policy. >> Yes. >> Exactly. >> So huge time savings there. >> Oh, it's huge. Yeah. >> Yeah. >> And it simplifies because now, I don't have to have multiple data stores. You can have one data store, all your VMs in there. You can limit test and dev and you can maximize business critical applications. Again, all via policy. So you've simplified your infrastructure. You've gone to more of a programmatic approach of managing your storage capabilities. But you're now managing at the VM level. >> So we mentioned that the cloud chaos (indistinct) that was mentioned this morning during the Keynote and we're saying a lot of customers are still in this cloud chaos phase. They want to get to Cloud Smart. How is this going to be one of those tools that helps customers pull the levers, dial the knobs, to be able to get to eventually, Cloud Smart. >> I could go on for this for hours. (Lisa Laughs) (Chance chuckles) This is really what simplifies storage. Because typically when you use traditional storage, you're going to have to figure out that this data store has this capability or another example, as you mentioned was Tanzu. If you're managing persistent volumes and you're not using something like vVols, if you want to get a certain storage capability, you have to either tag it or you have to create that data store with that capability. All of that goes away when you use vVols. So now that chaos of multiple data stores, multiple lines or multiple volumes, all that stuff goes away. So now you're simplifying your infrastructure, you have a programmatic approach to managing your storage and you can use it for all of your different types of workloads. So cloud, Kubernetes, persistent volumes, all that type of stuff. And again, all being managed via a simple and again, programmatic approach. So you could automate this. You know today, like you said, black Friday. Okay, Black, Friday's coming up. I want to change the policy. You could automate that. So you don't even have to go in and physically make the change of the policy now. You just say on Fridays, change it to this policy on Sunday night, change it back. >> Yep. >> Again, that's not something you can do with traditional storage. >> Okay. >> And I think from a simplification standpoint as well, you know, I was telling you about that other customer a couple days ago, they were running into the inability to grow beyond the bounds of VMFS file systems for very, very large VMs. And so what I talked to them about was look, if you go to vVols, you're not bound by file systems anymore. You have the capacity of the array and you can have VM discs up to 62 terabytes, you know, as many as you want. And it doesn't matter what they fit in because we can fit them all. So it's, to be able to, and that's some of our largest customers, the reason they go with vVols is to be able to grow beyond the bounds of traditional storage, anything like path limits, you know. That's something you have to contend with. >> Path limits, line limits, all that stuff. Typically just disappears with vVols. >> All those limits go away. Guys- >> They go away. >> Amazing. Congratulations on the work that you guys have done. Thank you so much for joining us on theCUBE talking about the value in it for customers and obviously the technical depths of the NetApp, VMware relationship. Guys, we appreciate your time. >> Yeah, thanks for having us on. >> Our pleasure. For my 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. (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.

(bright music) >> Welcome back to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, your host of theCUBE. We have Michael D´aniello, platform architect at VMware's Carbon Black. Michael, great to see you. We're here at re-Invent virtual hybrid in person. Great to have you on theCUBE. Thanks for coming on. >> Yeah, thanks a lot. Glad to be here. >> So one of the big stories that we're tracking, obviously, is workloads. All cloud for all workloads. Obviously the data is a big part of things, but under the covers and optimizing cloud for the application developers, this modern application movement is more and more at the top of the stack. People just wanting to code. Infrastructure as code. You've seen DevSecOps is a big trend that's driving all new microservices, all new greatness for developers, but still, there's an optimization question. I want to get your thoughts on this, is what you do. Take a minute to explain what your role is at Carbon Black around this cloud optimization. >> Yeah, absolutely. Yeah, so my name is Michael D'aniello. I am a platform architect of VMware Carbon Black. I work across all the different engineering teams. And our main objective is to develop scalable platform tools and that includes, yeah, cloud security, automation pieces, pipelines, cost optimization, like we'll be talking about today, developer enablement tooling and observability tooling. >> One of the big things about instances is that, you know, do I have enough instances? 'Cause honestly, the elastic cloud is amazing, all kinds of new resources there, but talk about the AMD portion of the instances. How do we identify these instances? How to developers understand it, what's in them, and what's the selection criteria? Take us through that whole process of the Amazon web service and the AMD instances. >> Yeah, sure. So essentially, we're leveraging a lot of our instances to run our EKS clusters, which is a managed service for me and for us to run our Kubernetes clusters. And we identify that we can take a bunch of those instances and gain some cost optimization benefits by selecting from Intel to AMD processors. And, you know, initially, we had measured out to be roughly a 10% reduction in cost just for selecting that instance type. But yeah, we actually learned we gained quite a bit more, so. >> John: You know, developers are always like, I want more power, and this is what, you know, the whole idea of Cloud is. Cloud scale has been a big competitive advantage, but also the cost aspect of it. What's the balance between maximizing performance and cost optimization? Because now, you know, people don't want to, you know, they want more power. They also don't want to have a lot of extra spend. And this is kind of one of those things they talk about in Cloud where it's been so successful, cost is important. >> Yeah, yeah, for sure. And it's got to be easy, too, to get that cost optimization benefit. Otherwise, you're spending all your cycles and burning that money there in the human capital and the team and the engineering effort. So luckily, this change is a one-line change. We use Terraform for our automated provisioning, a layer, and we were able to make that one line change and then developers didn't have to make any application changes, which was great. So it was a no-brainer for us to pursue this. >> Talk about the EC2 instances that leverage AMD based process for the EKS, you mentioned that earlier, what is that all about? What's the benefits, what's in it for you guys? >> Yeah, for sure. So essentially, the workloads that are running on these instance types are actual Carbon Black Cloud application. So, all the backend systems that support our customers. And so in that use case, we're, you know, we're spinning up all of our containers that are running our applications and essentially, that's our use case for those instance types. >> How did you come to use the AWS EC2 instances on the AMD? Did you have an evaluation process? Did you just go select it? I mean, take us through that migration aspect of it. >> Yeah, sure, yeah. So originally, we're looking across the board. How can we do better cost optimization, right? And that goes across every different AWS resource, but we targeted this one specifically. We worked alongside with their AWS TAMs and representatives to basically find out, "Hey, is this financially worth the effort?" And we did reach that conclusion with some analysis, basically targeting these instance types and doing some analysis on that cost optimization specifically. And it ended up, you know, being the right thing to target. >> What was the ease of use of the switch? Take us through that. Was it a heavy lift? Was it seamless? Take us through the impact, there, on the move over and what were the results of that? >> Yeah, so I mean, that's the greatest thing. Like I said before, I mean, we had to make just a single line change just to change that instance type in our config and then roll that out across our regions. We did slow roll that in order to make sure that those changes in our development environments didn't make any, you know, performance hits or we didn't run into any snags with the applications themselves. But yeah, I mean, that's the greatest part about the story from my perspective is the ease to migrate over and to switch to these instance types, and then you just immediately gain that cost optimization benefit. >> You know what I love about what your job is, platform architect, that word kind of had a lot of meaning even 10, 15 years ago, but now with the Cloud, it's almost like you're always finagling and managing and massaging and nurturing the infrastructure to enable it. More new things are coming online as well, more high level services. So you've got a fun job and it's always evolving. How do you stay on top of it? What's the impact been for your customers, too, as you start deploying some of these new instance capabilities? Take us through kind of a day in the life of what you do and then what's the impact of customers? >> Yeah, sure. So, you know, like you said, there's quite a bit now to look at. You know, you got to stay on top of different blogs and keep connected with your network to see what your other colleagues are doing across different companies. You know, you can go into conferences like AWS re:Invent, right, to keep on the cutting edge here. But yeah, that's essentially, you know, one of the key aspects is just trying to look at all the different aspects, all the new technologies that are coming out, making sure you're making the right choices there and trying to get the most bang for your buck while you're at it. >> What are some of the big factors that you see in cloud native as you start to look at what customers are doing? Obviously with Kubernetes, you're starting to see that platform develop inside the industry as well as de facto, kind of orchestration layer. But now as customers start to look at it, they want to have more ease of use there, too. At the same time, they don't want to have to do a lot of front end work. They want to get instant benefits in the Cloud, obviously, whether it's from a security standpoint or just rolling out a modern application. Okay, so as having all this infrastructure under the covers, how do you look at that problem and how do you capture that opportunity? >> Yeah, and I think that's why we're seeing a movement here on platform teams. It's kind of a newer terminology, usually a band of developers and SREs come together and say, "Well, we've got a lot of different things to look at. We're onboarding applications to Kubernetes, and we need to make tools so that developers don't have to think much about the transition and the underlying platform." And so that's one of our success metrics on the platform engineering team is just to almost, you know, be non-existent, right? To just have everything flow through our systems and then have just a high ease of use to onboard the applications to the new platform. >> You know, it looks like you have some great success with the AMD based instances. Can I ask you a question? 'Cause I wanted figure this out. How do you identify an AMD based instance when you're making the selections? >> Yeah, sure. It's as easy as just the A after the name. So for us, it was the C5.4XL. And if you want the AMD one, it's just the C5A.4XL. So I guess technically, instead of a one line change, it's actually a one letter change. So, quite easy there. >> Yeah, it's almost like back in the old glory days of command line, one quick update. The customer aspect of this is also important, too. If you don't mind, while I got you here, what are some of the things that you're hearing from your customers, from a performance standpoint, that they're looking for? Obviously, the cost optimization is key, but as they look to deploy more power and more performance, what are some of the things that your customers are looking for from Carbon Black? >> Yeah, so I mean, we are a security company, but we're really a data company because we have, you know, 8,000 customers, we processed over a trillion events per day, we ingress over a hundred terabytes of data per day. And so, our customers need high level performance. And if we can't provide that with low latency, we're not successful. So that's why, you know, performance on the underlying systems that are running our applications is super critical. >> Yeah, you're looking at trailblazer over there. I mean, the work that you guys are doing with the data is amazing. And that's a big theme at re:Invent this year is that data is a huge part. We look at the success of the cloud growth on this, I call gen-two cloud, happening. This whole modern movement is all about how people handle the data at scale, 'cause cloud scales here and now you've got processing all that data, The trailblazing that's going on, there's like this new wave of, I almost called it first-generation trailblazers, but you guys are doing that. What advice would you have for other architects out there and kind of the mainstream enterprises who are like, "Hey, I want to take advantage of the path that you guys have plowed through." What's your advice? >> Yeah, I think one of the key things in a place where we've had a lot of success is creating standards, making sure that we're choosing technology wisely, and making sure that your company isn't building the same solution in silos. And you know, that's a huge pattern that I've seen in my career. And if you can negate that, you're going to be in a great place. So, you know, choose the right technology, container first, cloud native first, push forward, and then make sure that everybody's kind of on that same ship running in the same direction. >> Well, great case study on this AMD based instance migration. Was there any uplift and experience that you've seen on the switch and the performance? Can you just talk about that? What does it mean to upgrade? What benefits are you seeing on the performance you have? >> Yeah, so I didn't hit on this yet and I really wanted to. Yeah, so upfront, the instance itself is 10% cheaper. However, we found out that we had to run far less instances because of that performance increase. So we ended up saving roughly 30% and we've continued to scale out. So at first, it was a couple of hundred instances. Now we're in the thousands and we're going to keep ramping up to over 10 thousands, tens of that. >> John: Let me get this right. So single line change, letter change, instance change. So you get not as many instances, and you save money, so you get cost optimization and higher performance. >> Yep. They say, if it's too good to be true, it's not. But in this case, it actually is. >> So why is it so good in your opinion? What did you discover? What was the big revelation that went down this path? Because that's good value proposition. >> Yeah, for sure. I mean, so initially, we were just chasing that initial BC to 10% and then as we kind of push it forward, we're looking at the metrics, month to month costs and we're actually saying, well, as we kind of swap over from one instance type to another, we're actually paying less. And then once we fully swapped over, it took five or six months to get to the same amount of costs as we continued to scale upward. So it's been a great story. >> It is a great story. It's super nuanced, but it's super important to know these platform benefits. I got to ask you on a personal question, if you don't mind. We love covering Cloud. We've been covering Amazon, it's our ninth year at re:Invent. Just love covering all the action and tech as this just total awesomeness environment. Cloud scale, innovation, capabilities, it's like surfing a big wave. But there's a bigger wave coming and we're seeing it now. I want to get your thoughts on this. As you look to the next big wave, beyond Cloud now, Cloud scale, data, new architecture is rolling out with Edge, basically distributing computing at large scale, and tons of security challenges, right? How do you look at this next big wave coming? Are you staring at it saying, wow, this is going to be huge? And how do you ride that wave? What's your mindset and how do you look at that? >> Well first of all, I'm extremely excited about it. Just the further this thing grows out, there's definitely more complexity, but just a whole slew of fun problems to solve. But when we look at these different problems and solving them at scale across multiple regions, it gets pretty exciting, right? So I can say one example of this is our security of our Cloud, not the security product, and we've developed automation for prevention and auto-remediation in our pipelines. It's been such a success story. And these type of technologies did not exist even a couple of years ago and we've been able to take advantage of them. So, there's going to be a lot more of that where that came from. So, yeah. >> Michael, great work. And again, you're truly a trailblazer, and this is, again, you got to do it. You got to screw your own cloud and stay on the cutting edge and ride that wave. Congratulations on the CostOp cloud optimization and the success with AMD based instances. Congratulations. Thanks. >> Thanks. >> Okay, this is theCUBEs coverage of AWS's re:Invent 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (inspirational music)

(bright music) >> Welcome back to theCUBE's coverage of AWS re:Invent 2021. I'm John Furrier, your host of theCUBE. We have Michael D´aniello, platform architect at VMware's Carbon Black. Michael, great to see you. We're here at re-Invent virtual hybrid in person. Great to have you on theCUBE. Thanks for coming on. >> Yeah, thanks a lot. Glad to be here. >> So one of the big stories that we're tracking, obviously, is workloads. All cloud for all workloads. Obviously the data is a big part of things, but under the covers and optimizing cloud for the application developers, this modern application movement is more and more at the top of the stack. People just wanting to code. Infrastructure as code. You've seen DevSecOps is a big trend that's driving all new microservices, all new greatness for developers, but still, there's an optimization question. I want to get your thoughts on this, is what you do. Take a minute to explain what your role is at Carbon Black around this cloud optimization. >> Yeah, absolutely. Yeah, so my name is Michael D'aniello. I am a platform architect of VMware Carbon Black. I work across all the different engineering teams. And our main objective is to develop scalable platform tools and that includes, yeah, cloud security, automation pieces, pipelines, cost optimization, like we'll be talking about today, developer enablement tooling and observability tooling. >> One of the big things about instances is that, you know, do I have enough instances? 'Cause honestly, the elastic cloud is amazing, all kinds of new resources there, but talk about the AMD portion of the instances. How do we identify these instances? How to developers understand it, what's in them, and what's the selection criteria? Take us through that whole process of the Amazon web service and the AMD instances. >> Yeah, sure. So essentially, we're leveraging a lot of our instances to run our EKS clusters, which is a managed service for me and for us to run our Kubernetes clusters. And we identify that we can take a bunch of those instances and gain some cost optimization benefits by selecting from Intel to AMD processors. And, you know, initially, we had measured out to be roughly a 10% reduction in cost just for selecting that instance type. But yeah, we actually learned we gained quite a bit more, so. >> John: You know, developers are always like, I want more power, and this is what, you know, the whole idea of Cloud is. Cloud scale has been a big competitive advantage, but also the cost aspect of it. What's the balance between maximizing performance and cost optimization? Because now, you know, people don't want to, you know, they want more power. They also don't want to have a lot of extra spend. And this is kind of one of those things they talk about in Cloud where it's been so successful, cost is important. >> Yeah, yeah, for sure. And it's got to be easy, too, to get that cost optimization benefit. Otherwise, you're spending all your cycles and burning that money there in the human capital and the team and the engineering effort. So luckily, this change is a one-line change. We use Terraform for our automated provisioning, a layer, and we were able to make that one line change and then developers didn't have to make any application changes, which was great. So it was a no-brainer for us to pursue this. >> Talk about the EC2 instances that leverage AMD based process for the EKS, you mentioned that earlier, what is that all about? What's the benefits, what's in it for you guys? >> Yeah, for sure. So essentially, the workloads that are running on these instance types are actual Carbon Black Cloud application. So, all the backend systems that support our customers. And so in that use case, we're, you know, we're spinning up all of our containers that are running our applications and essentially, that's our use case for those instance types. >> How did you come to use the AWS EC2 instances on the AMD? Did you have an evaluation process? Did you just go select it? I mean, take us through that migration aspect of it. >> Yeah, sure, yeah. So originally, we're looking across the board. How can we do better cost optimization, right? And that goes across every different AWS resource, but we targeted this one specifically. We worked alongside with their AWS TAMs and representatives to basically find out, "Hey, is this financially worth the effort?" And we did reach that conclusion with some analysis, basically targeting these instance types and doing some analysis on that cost optimization specifically. And it ended up, you know, being the right thing to target. >> What was the ease of use of the switch? Take us through that. Was it a heavy lift? Was it seamless? Take us through the impact, there, on the move over and what were the results of that? >> Yeah, so I mean, that's the greatest thing. Like I said before, I mean, we had to make just a single line change just to change that instance type in our config and then roll that out across our regions. We did slow roll that in order to make sure that those changes in our development environments didn't make any, you know, performance hits or we didn't run into any snags with the applications themselves. But yeah, I mean, that's the greatest part about the story from my perspective is the ease to migrate over and to switch to these instance types, and then you just immediately gain that cost optimization benefit. >> You know what I love about what your job is, platform architect, that word kind of had a lot of meaning even 10, 15 years ago, but now with the Cloud, it's almost like you're always finagling and managing and massaging and nurturing the infrastructure to enable it. More new things are coming online as well, more high level services. So you've got a fun job and it's always evolving. How do you stay on top of it? What's the impact been for your customers, too, as you start deploying some of these new instance capabilities? Take us through kind of a day in the life of what you do and then what's the impact of customers? >> Yeah, sure. So, you know, like you said, there's quite a bit now to look at. You know, you got to stay on top of different blogs and keep connected with your network to see what your other colleagues are doing across different companies. You know, you can go into conferences like AWS re:Invent, right, to keep on the cutting edge here. But yeah, that's essentially, you know, one of the key aspects is just trying to look at all the different aspects, all the new technologies that are coming out, making sure you're making the right choices there and trying to get the most bang for your buck while you're at it. >> What are some of the big factors that you see in cloud native as you start to look at what customers are doing? Obviously with Kubernetes, your starting to see that platform develop inside the industry as well as defacto, kind of orchestration layer. But now as customers start to look at it, they want to have more ease of use there, too. At the same time, they don't want to have to do a lot of front end work. They want to get instant benefits in the Cloud, obviously, whether it's from a security standpoint or just rolling out a modern application. Okay, so as having all this infrastructure under the covers, how do you look at that problem and how do you capture that opportunity? >> Yeah, and I think that's why we're seeing a movement here on platform teams. It's kind of a newer terminology, usually a band of developers and SREs come together and say, "Well, we've got a lot of different things to look at. We're onboarding applications to Kubernetes, and we need to make tools so that developers don't have to think much about the transition and the underlying platform." And so that's one of our success metrics on the platform engineering team is just to almost, you know, be non-existent, right? To just have everything flow through our systems and then have just a high ease of use to onboard the applications to the new platform. >> You know, it looks like you have some great success with the AMD based instances. Can I ask you a question? 'Cause I wanted figure this out. How do you identify an AMD based instance when you're making the selections? >> Yeah, sure. It's as easy as just the A after the name. So for us, it was the C5.4XL. And if you want the AMD one, it's just the C5A.4XL. So I guess technically, instead of a one line change, it's actually a one letter change. So, quite easy there. >> Yeah, it's almost like back in the old glory days of command line, one quick update. The customer aspect of this is also important, too. If you don't mind, while I got you here, what are some of the things that you're hearing from your customers, from a performance standpoint, that they're looking for? Obviously, the cost optimization is key, but as they look to deploy more power and more performance, what are some of the things that your customers are looking for from Carbon Black? >> Yeah, so I mean, we are a security company, but we're really a data company because we have, you know, 8,000 customers, we processed over a trillion events per day, we ingress over a hundred terabytes of data per day. And so, our customers need high level performance. And if we can't provide that with low latency, we're not successful. So that's why, you know, performance on the underlying systems that are running our applications is super critical. >> Yeah, you're looking at trailblazer over there. I mean, the work that you guys are doing with the data is amazing. And that's a big theme at re:Invent this year is that data is a huge part. We look at the success of the cloud growth on this, I call gen-two cloud, happening. This whole modern movement is all about how people handle the data at scale, 'cause cloud scales here and now you've got processing all that data, The trailblazing that's going on, there's like this new wave of, I almost called it first-generation trailblazers, but you guys are doing that. What advice would you have for other architects out there and kind of the mainstream enterprises who are like, "Hey, I want to take advantage of the path that you guys have plowed through." What's your advice? >> Yeah, I think one of the key things in a place where we've had a lot of success is creating standards, making sure that we're choosing technology wisely, and making sure that your company isn't building the same solution in silos. And you know, that's a huge pattern that I've seen in my career. And if you can negate that, you're going to be in a great place. So, you know, choose the right technology, container first, cloud native first, push forward, and then make sure that everybody's kind of on that same ship running in the same direction. >> Well, great case study on this AMD based instance migration. Was there any uplift and experience that you've seen on the switch and the performance? Can you just talk about that? What does it mean to upgrade? What benefits are you seeing on the performance you have? >> Yeah, so I didn't hit on this yet and I really wanted to. Yeah, so upfront, the instance itself is 10% cheaper. However, we found out that we had to run far less instances because of that performance increase. So we ended up saving roughly 30% and we've continued to scale out. So at first, it was a couple of hundred instances. Now we're in the thousands and we're going to keep ramping up to over 10 thousands, tens of that. >> John: Let me get this right. So single line change, letter change, instance change. So you get not as many instances, and you save money, so you get cost optimization and higher performance. >> Yep. They say, if it's too good to be true, it's not. But in this case, it actually is. >> So why is it so good in your opinion? What did you discover? What was the big revelation that went down this path? Because that's good value proposition. >> Yeah, for sure. I mean, so initially, we were just chasing that initial BC to 10% and then as we kind of push it forward, we're looking at the metrics, month to month costs and we're actually saying, well, as we kind of swap over from one instance type to another, we're actually paying less. And then once we fully swapped over, it took five or six months to get to the same amount of costs as we continued to scale upward. So it's been a great story. >> It is a great story. It's super nuanced, but it's super important to know these platform benefits. I got to ask you on a personal question, if you don't mind. We love covering Cloud. We've been covering Amazon, it's our ninth year at re:Invent. Just love covering all the action and tech as this just total awesomeness environment. Cloud scale, innovation, capabilities, it's like surfing a big wave. But there's a bigger wave coming and we're seeing it now. I want to get your thoughts on this. As you look to the next big wave, beyond Cloud now, Cloud scale, data, new architecture is rolling out with Edge, basically distributing computing at large scale, and tons of security challenges, right? How do you look at this next big wave coming? Are you staring at it saying, wow, this is going to be huge? And how do you ride that wave? What's your mindset and how do you look at that? >> Well first of all, I'm extremely excited about it. Just the further this thing grows out, there's definitely more complexity, but just a whole slew of fun problems to solve. But when we look at these different problems and solving them at scale across multiple regions, it gets pretty exciting, right? So I can say one example of this is our security of our Cloud, not the security product, and we've developed automation for prevention and auto-remediation in our pipelines. It's been such a success story. And these type of technologies did not exist even a couple of years ago and we've been able to take advantage of them. So, there's going to be a lot more of that where that came from. So, yeah. >> Michael, great work. And again, you're truly a trailblazer, and this is, again, you got to do it. You got to screw your own cloud and stay on the cutting edge and ride that wave. Congratulations on the CostOp cloud optimization and the success with AMD based instances. Congratulations. Thanks. >> Thanks. >> Okay, this is theCUBEs coverage of AWS's re:Invent 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (inspirational music)

(uplifting music) >> Hello and welcome to this Cube Conversation. I'm John Furrier, host of theCube here in Palo Alto, California. We've got two great remote guests to talk about some big news hitting with Scality and Hewlett Packard Enterprise. Jerome Lecat CEO of Scality and Chris Tinker, Distinguished Technologist from HPE, Hewlett Packard Enterprise, Jerome, Chris, great to see you both Cube alumnis from an original gangster days as we'd say back then when we started almost 11 years ago. Great to see you both. >> It's great to be back. >> Good to see you John. >> So, really compelling news around kind of this next generation storage cloud native solution. Okay, it's really kind of an impact on the next gen, I call next gen, dev ops meets application, modern application world and something we've been covering heavily. There's some big news here around Scality and HPE offering a pretty amazing product. You guys introduced essentially the next gen piece of it, Artesca, we'll get into in a second, but this is a game-changing announcement you guys announced, this is an evolution continuing I think is more of a revolution, but I think, you know storage is kind of abstractionally of evolution to this app centric world. So talk about this environment we're in and we'll get to the announcement, which is object store for modern workloads, but this whole shift is happening Jerome. This is a game changer to storage and customers are going to be deploying workloads. >> Yeah, Scality really, I mean, I personally really started working on Scality more than 10 years ago, close to 15 now. And if we think about it I mean the cloud has really revolutionized IT. And within the cloud, we really see layers and layers of technology. I mean, it all start at around 2006 with Amazon and Google and Facebook finding ways to do initially what was consumer IT at very large scale, very low credible reliability and then slowly creeped into the enterprise. And at the very beginning, I would say that everyone was kind of wizards trying things and really coupling technologies together. And to some degree we were some of the first wizard doing this, but we, we're now close to 15 years later and there's a lot of knowledge and a lot of experience, a lot of tools. And this is really a new generation. I'll call it cloud native, or you can call it next gen whatever, but there is now enough experience in the world, both at the development level and at the infrastructure level to deliver truly distributed automated systems that run on industry standard servers. Obviously good quality server deliver a better service than others, but there is now enough knowledge for this to truly go at scale. And call this cloud or call this cloud native. Really the core concept here is to deliver scalable IT at very low cost, very high level of reliability, all based on software. And we've, we've been participated in this motion, but we feel that now the breadth of what's coming is at the new level, and it was time for us to think, develop and launch a new product that's specifically adapted to that. And Chris, I will let you comment on this because the customers or some of them, you can add a customer, you do that. >> Well, you know, you're right. You know, I've been in the, I've been like you I've been in this industry for a, well, along time. Give a long, 20 to 21 years in HPE in engineering. And look at the actual landscape has changed with how we're doing scale-out software-defined storage for particular workloads. And we're a catalyst has evolved here is an analytics normally what was only done in the three letter acronyms and massively scale-out parallel namespace file systems, parallel file systems. The application space has encroached into the enterprise world where the enterprise world needed a way to actually take a look at how to, how do I simplify the operations? How do I actually be able to bring about an application that can run in the public cloud or on premise or hybrid, be able to actually look at a workload optimized step that aligns the actual cost to the actual analytics that I'm going to be doing the workload that I'm going to be doing and be able to bridge those gaps and be able to spin this up and simplify operations. And you know, and if you, if you are familiar with these parallel processes which by the way we actually have on our truck, I, I do engineer those, but they are, they are, they are they have their own unique challenges, but in the world of enterprise where customers are looking to simplify operations, then take advantage of new application, analytic workloads whether it be smart, Mesa, whatever it might be, right. I mean, if I want to spin up a Mongo DB or maybe maybe a, you know, last a search capability how do I actually take those technologies, embrace a modern scale-out storage stack that without without breaking the bank, but also provide a simple operations. And that's, that's why we look for object storage capabilities because it brings us this massive parallelization. Back to you John. >> Well before we get into the product. I want to just touch on one thing Jerome you mentioned, and Chris, you, you brought up the DevOps piece next gen, next level, whatever term you use. It is cloud native, cloud native has proven that DevOps infrastructure is code is not only legit. It's being operationalized in all enterprises and add security in there, you have DevSecOps, this is the reality and hybrid cloud in particular has been pretty much the consensus is that standard. So our defacto center whatever you want to call it, that's happening. Multicloud are on the horizon. So these new workloads are have these new architectural changes, cloud on premises and edge. This is the number one story. And the number one challenge all enterprises are now working on. How do I build the architecture for the cloud on premises and edge? This is forcing the DevOps team to flex and build new apps. Can you guys talk about that particular trend? And is it, and is that relevant here? >> Yeah, I, I now talk about really storage anywhere and cloud anywhere and and really the key concept is edge to go to cloud. I mean, we all understand now that the edge will host a lot of that time and the edge is many different things. I mean, it's obviously a smartphone, whatever that is, but it's also factories, it's also production. It's also, you know, moving moving machinery, trains, planes, satellites that that's all the edge, cars obviously. And a lot of that I will be both produced and process there, but from the edge who will want to be able to send the data for analysis, for backup, for logging to a call, and that call could be regional, maybe not, you know, one call for the whole planet, but maybe one corporate region the state in the U.S. And then from there you will also want to push some of the data to public cloud. One of the thing that we see more and more is that the D.R that has centered the disaster recovery is not another physical data center. It's actually the cloud, and that's a very efficient infrastructure very cost efficient, especially. So really it, it, it's changing the paradigm on how you think about storage because you really need to integrate these three layers in a consistent approach especially around the topic of security because you want the data to be secure all along the way. And data is not just data, its data, and who can access the data, who can modify the data what are the conditions that allow modification all automatically erasure of the data? In some cases, it's super important that the data automatically erased after 10 years and all this needs to be transported from edge to core to cloud. So that that's one of the aspects. Another aspects that resonates for me with what you said is a word you didn't say, but it's actually crucial this whole revolution. It's Kubernetes I mean, Kubernetes is in now a mature technology, and it's, it's just, you know the next level of automatized operation for distributed system, which we didn't have 5 or 10 years ago. And that is so powerful that it's going to allow application developers to develop much faster system that can be distributed again edge to go to cloud, because it's going to be an underlying technology that spans the three layers. >> Chris, your thoughts hybrid cloud. I've been, I've been having questions with the HPE folks for God years and years on hybrid clouds, now here. >> Right (chuckles) >> Well, you know, and, and it's exciting in a layout right, so you look at like a, whether it be enterprise virtualization, that is a scale-out general purpose virtualization workloads whether it be analytic workloads, whether it be no data protection is a paramount to all of this, orchestration is paramount. If you look at that DevSecOps, absolutely. I mean, securing the actual data the digital last set is, is absolutely paramount. And if you look at how we do this look at the investments we're making, we're making enough and look at the collaborative platform development which goes to our partnership with Scality. It is, we're providing them an integral aspect of everything we do, whether we're bringing in Ezmeral which is our software we use for orchestration look at the veneer of its control plane, controlling Kubernetes. Being able to actually control the active clusters and the actual backing store for all the analytics that we just talked about. Whether it be a web-scale app that is traditionally using a politics namespace and now been modernized and take advantage of newer technologies running an NBME burst buffers or a hundred gig networks with Slingshot network of 200 and 400 gigabit looking at how do we actually get the actual analytics, the workload to the CPU and have it attached to the data at risk. Where's the data, how do we land the data? How do we actually align, essentially locality, locality of the actual asset to the computer. And this is where, you know, we can look leverage whether it be a Zair or Google or name your favorite hybrid, hyperscaler, leverage those technologies leveraging the actual persistent store. And this is where Scality is, with this object store capability has it been an industry trendsetter, setting the actual landscape of how provide an object store on premise and hybrid cloud run it in a public cloud, but being able to facilitate data mobility and tie it back to, and tie it back to an application. And this is where a lot of things have changed in the world of analytics, because the applications that you, the newer technologies that are coming on the market have taken advantage of this particular protocol as threes. So they can do web scale massively parallel concurrent workloads. >> You know what let's get into the announcement. I love cool and relevant products. And I think this hits the mark. Scality you guys have Artesca, which is just announced. And I think it, you know, we obviously we reported on it. You guys have a lightweight true enterprise grade object store software for Kubernetes. This is the announcement, Jerome, tell us about it. What's the big deal? Cool and relevant, come on, this is cool. Right, tell us. >> I'm super excited. I'm not sure, if you can see it as well on the screen, but I'm super, super excited. You know, we, we introduced the ring 11 years ago and they says our biggest announcements for the past 11 years. So yes, do pay attention. And, you know, after, after looking at, at all these trends and understanding where we see the future going. We decided that it was time to embark (indistinct) So there's not one line of code that's the same as our previous generation product. They will both exist, they both have a space in the market. And Artesca was specifically designed for this cloud native era. And what we see is that people want something that's lightweight especially because it had to go to the edge. They still want the enterprise grid that Scality is known for. And it has to be modern. What we really mean by modern is, we see object storage now being the primary storage for many application more and more applications. And so we have to be able to deliver the performance, that primary storage expects. This idea of a Scality of serving primary storage is actually not completely new. When we launched Scality 10 years ago, the first application that we were supporting was consumer email for which we were, and we are still today, the primary storage. So we have, we know what it is to be the primary store. We know what's the level of reliability you need to hit. We know what, what latency means and latency is different from throughput, you really need to optimize both. And I think that still today we're the only object storage company that protects data from both replication and original encoding Because we understand that replication is faster, but the original encoding is more better, and more, of file where fast internet latency doesn't matter so much. So we we've been being all that experience, but really rethinking of product for that new generation that really is here now. And so where we're truly excited, I guess people a bit more about the product. It's a software, Scality is a software company and that's why we love to partner with HPE who's producing amazing servers, you know for the record and the history. The very first deployment of Scality in 2010 was on the HP servers. So this is a long love story here. And so to come back to our desk is lightweight in the sense that it's easy to use. We can start small, we can start from just one server or one VM I mean, you would start really small, but he can grow infinitely. The fact that we start small, we didn't, you know limit the technology because of that. So you can start from one to many and it's cloud native in the sense that it's completely Kubernetes compatible it's Kubernetes office traded. It will deploy on many Kubernetes distributions. We're talking obviously with Ezmeral we're also talking with zoo and with the other all those of communities distribution it will also be able to be run in the cloud. Now, I'm not sure that there will be many true production deployment of Artesca going the cloud, because you already have really good object storage by the cloud providers but when you are developing something and you want to test that, you know just doing it in the cloud is very practical. So you'll be able to deploy our Kubernetes cloud distribution, and it's more than object storage in the sense that it's application centric. A lot of our work is actually validating that our storage is fit for this single purpose application. And making sure that we understand the requirement of these application, that we can guide our customers on how to deploy. And it's really designed to be the primary storage for these new workloads. >> The big part of the news is your relationship with Hewlett Packard Enterprise is some exclusivity here as part of this and as you mentioned the relationship goes back many, many years. We've covered the, your relationship in the past. Chris also, you know, we cover HP like a blanket. This is big news for HPE as well. >> This is very big news. >> What is the relationship, talk about this exclusivity Could you share about the partnership and the exclusivity piece? >> Well, there's the partnership expands into the pan HPE portfolio. we look, we made a massive investment in edge IOT device. So we actually have how did we align the cost to the demand. Our customers come to us, wanting to looking at think about what we're doing with Greenlake, like in consumption based modeling. They want to be able to be able to consume the asset without having to do a capital outlay out of the gate. Number two, look at, you know how do you deploy technology, really demand. It depends on the scale, right? So in a lot of your web skill, you know, scale out technologies, it putting them on a diet is challenging. Meaning how skinny can you get it. Getting it down into the 50 terabyte range and then the complexities of those technologies at as you take a day one implementation and scale it out over you know, you know, multiple iterations over quarters, the growth becomes a challenge so working with Scality we, we believe we've actually cracked this nut. We figured out how to a number one, how to start small, but not limit a customer's ability to scale it out incrementally or grotesquely. You can eat depending on the quarters, the month, whatever whatever the workload is, how do you actually align and be able to consume it? So now whether it be on our Edgeline products our DL products go right there, now what that Jerome was talking about earlier you know, we, we, we ship a server every few seconds. That won't be a problem. But then of course, into our density optimized compute with the Apollo products. And this where our two companies have worked in an exclusivity where they scale the software bonds on the HP ecosystem. And then we can, of course provide you, our customers the ability to consume that through our GreenLake financial models or through a CapEx partners. >> Awesome, so Jerome and, and Chris, who's the customer here obviously, there's an exclusive period. Talk about the target customer and how the customers get the product and how they get the software. And how does this exclusivity with HP fit into it? >> Yeah, so there there's really a three types of customers and we've really, we've worked a lot with a company called UseDesign to optimize the user interface for each the types of customers. So we really thought about each customer role and providing with each of them the best product. So the, the first type of customer are application owners who are deploying an application that requires an object storage in the backend, you typically want a simple object store for one application, they want it to be simple and work. Honestly they want no thrill, just want an object store that works. And they want to be able to start as small as they start with their application. Often it's, you know, the first deployment maybe a small deployment, you know applications like a backup like VML, Rubrik, or analytics like (indistinct), file system that now, now available as a software, you know like CGI does a really great departmental NAS that works very well that needs an object store in the backend. Or for high performance computing a wake-up house system is an amazing file system. We will also have vertical application like road peak, for example, who provides origin and the view of the software broadcasters. So all these are application, they request an object store in the backend and you just need a simple high-performance working well object store and I'll discuss perfect for that. Now, the second type of people that we think will be interested by Artesca are essentially developer who are currently developing some capabilities or cloud native application, your next gen. And as part of their development stack, it's getting better and better when you're developing a cloud native application to really target an object storage rather than NFS, as you're persistent. It just, you know, think about generations of technologies and NFS and filesystem were great 25 years ago. I mean, it's an amazing technology. Now, when you want to develop a distributed scalable application object storage is a better fit because it's the same generation. And so same thing, I mean, you know, they're developing something they need an object store that they can develop on. So they want it very lightweight, but they also want the product that their enterprise or their customers will be able to rely on for years and years on. And this guy's really great fit to do that. The third type of customer are more architects, I would say are the architects that are designing a system where they are going to have 50 factories, a thousand planes, a million cars, they are going to have some local storage which will they want to replicate to the core and possibly also to the cloud. And as the design is really new generation workloads that are incredibly distributed but with local storage Artesca are really great for that. >> And tell about the HPE exclusive Chris. What's the, how does that fit in? Do they buy through Scality? Can they get it for the HP? Are you guys working together on how customers can procure it? >> Both ways, yeah both ways they can procure it through Scality. They can secure it through HPE and it's, it's it's the software stack running on our density optimized compute platforms which you would choose and align those and to provide an enterprise quality. Cause if it comes back to it in all of these use cases is how do we align up into a true enterprise stack, bringing about multitenancy bringing about the, the, the fact that you know, if you look at like a local coding one of the things that they're bringing to it, so that we can get down into the DL325. So with the exclusivity, you actually get choice. And that choice comes into our entire portfolio whether it be the Edgeline platform the DL325 AMD processing stack or the Intel 380, or whether it be the Apollos or like I said, there's, there's, there's so many ample choices there that facilitate this, and it's this allows us to align those two strategies. >> Awesome, and I think the Kubernetes piece is really relevant because, you know, I've been interviewing folks practitioners and Kubernetes is very much maturing fast. It's definitely the centerpiece of the cloud native both below the, the line, if you will below under the hood for the, for the infrastructure and then for apps, they want a program on top of it that's critical. I mean, Jerome, this is like, this is the future. >> Yeah, and if you don't mind like to come back to the myth on the exclusivity with HP. So we did a six month exclusive and the very reason we could do this is because HP has such breadth of server portfolio. And so we can go from, you know, really simple, very cheap you know, DL380, machine that we tell us for a few dollars. I mean, it's really like simple system, 50 terabyte. We can have the DL325 that Chris mentioned that is really a powerhouse all NVME, clash over storage is NVME, very fast processors you know, dense, large, large system, like the APOE 4,500. So it's a very large graph of portfolio. We support the whole portfolio and we work together on this. So I want to say that you know, one of the reason I want to send kudos to HP for the breadth of their server line really. As mentioned, Artesca can be ordered from either company. In hand-in-hand together, so anyway, you'll see both of us and our field working incredibly well together. >> Well, just on that point, I think just for clarification was this co-design by Scality and HPE, because Chris you mentioned, you know, the, the configuration of your systems. Can you guys, Chris quickly talk about the design. >> From, from, from the code base the software is entirely designed and developed by Scality, from testing and performance, so this really was a joint work with HP providing both a hardware and manpower so that we could accelerate the testing phase. >> You know, Chris HPE has just been doing such a great job of really focused on this. I know I've been covering it for years before it was fashionable. The idea of apps working no matter where it lives, public cloud, data center, edge. And you mentioned edge line's been around for awhile, you know, app centric, developer friendly, cloud first, has been an HPE kind of guiding first principle for many, many years. >> Well, it has. And, you know, as our CEO here intended, by 2022 everything will be able to be consumed as a service in our portfolio. And then this stack allows us the simplicity and the consumability of the technology and the granulation of it allows us to simplify the installation. Simplify the actual deployment bringing into a cloud ecosystem, but more importantly for the end customer. They simply get an enterprise quality product running on an optimized stack that they can consume through a orchestrated simplistic interface. That customers that's what they're wanting for today's but they come to me and ask, hey how do I need a, I've got this new app, new project. And, you know, it goes back to who's actually coming. It's no longer the IT people who are actually coming to us. It's the lines of business. It's that entire dimension of business owners coming to us, going this is my challenge. And how can you, HPE help us? And we rely on our breadth of technology, but also our breadth of partners to come together in our, of course Scality is hand in hand and our collaborative business unit our collaborative storage product engineering group that actually brought, brought this to market. So we're very excited about this solution. >> Chris, thanks for that input and great insight. Jerome, congratulations on a great partnership with HPE obviously great joint customer base. Congratulations on the product release here. Big moving the ball down the field, as they say. New functionality, clouds, cloud native object store. Phenomenal, so wrap, wrap, wrap up the interview. Tell us your vision for Scality and the future of storage. >> Yeah, I think I started in, Scality is going to be an amazing leader, it is already. But yeah, so, you know I have three things that I think will govern how storage is going. And obviously Marc Andreessen said it software is everywhere and software is eating the world. So definitely that's going to be true in the data center in storage in particular, but the three trends that are more specific are first of all, I think that security performance and agility is now basic expectation. It's, it's not, you know it's not like an additional feature. It's just the basic tables, security performance and our job. The second thing is, and we've talked about it during this conversation is edge to go. You need to think your platform with edge, core and cloud. You know, you, you don't want to have separate systems separate design interface point for edge and then think about the core and then think about cloud, and then think about the diverse power. All this needs to be integrated in a design. And the third thing that I see as a major trend for the next 10 years is data sovereignty. More and more, you need to think about where is the data residing? What are the legal challenges? What is the level of protection, against who are you protected? What is your independence strategy? How do you keep as a company being independent from the people you need to be in the band? And I mean, I say companies, but this is also true for public services. So these, these for me are the three big trends. And I do believe that software defined distributed architecture are necessary for these trends but you also need to think about being truly enterprise grade. and that has been one of our focus with design of Artesca. How do we combine a lightweight product with all of the security requirements and data sovereignty requirements that we expect to have in the next thing? >> That's awesome. Congratulations on the news Scality, Artesca. The big release with HPE exclusive for six months, Chris Tinker, Distinguished Engineer at HPE. Great to see you Jerome Lecat CEO of Scality, great to see you as well. Congratulations on the big news. I'm John Furrier from theCube. Thanks for watching. (uplifting music)

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

(digital music) >> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> The storage business as we know it has changed forever. On-prem storage was once a virtually unlimited and untapped bastion of innovation, VC funding and lucrative exits. Today it's a shadow of its former self and the glory days of storage will not return. Hello everyone, and welcome to this week's Wikibon CUBE Insights Powered by ETR. In this breaking analysis, we'll lay out our premise for what's happening in the storage industry, and share some fresh insights from our ETR partners, and data that supports our thinking. We've had three decades of tectonic shifts in the storage business. From the simplified history of this industry shows us there've been five major waves of innovation spanning five decades. The dominant industry model has evolved from what was first the mainframe centric vertically integrated business, but of course by IBM and it became a disintegrated business that saw between like 70 or 80 Winchester disk drive companies that rose and then fell. They served a booming PC industry in this way it was led by the likes of Seagate. Now Seagate supplied the emergence of an intelligent controller based external disc array business that drove huge margins for functions that while lucrative was far cheaper than captive storage from system vendors, this era of course was led by EMC and NetApp. And then this business was disrupted by a flash and software defined model that was led by Pure Storage and also VMware. Now the future of storage is being defined by cloud and intelligent data management is being led by AWS and a three letter company that we'll just call TBD, otherwise known as Jump Ball Incorporated. Now, let's get into it here, the impact of AWS cannot be overstated now while legacy storage players, they're sick and tired of talking about the cloud, the reality cannot be ignored. The cloud has been the most disruptive force in storage over the past 10 years, and we've reported on the spending impact extensively. But cloud is not the only factor pressuring the on-prem storage business, flash has killed what we call performance by spindles. In other words, the practice of adding more disk drives to keep performance from tanking. So much flash has been injected into the data center that that no longer is required. But now as you drill down into the cloud, AWS has been by far the most significant factor in our view. Lots of people talked about object storage before AWS, but there sure wasn't much spending going on, S3 changed that. AWS is getting much more aggressive about expanding its storage portfolio and its offerings. S3 came out in 2006 and it was the very first AWS service and then Elastic Block Service EBS came out a couple of years later, nobody really paid much attention. Well last fall at storage day, we saw AWS announce a number of services, many fire-related and this year we saw four new announcements of Amazon at re:Invent. We think AWS' storage revenue will surpass 8 billion this year and could be as high as 10 billion. There's not much data out there, but this would mean that AWS' storage biz is larger than that of a NetApp, which means AWS is larger than every traditional storage player with the exception of Dell. Here's a little glimpse of what's coming at the legacy storage business. It's a clip of the vice-president of AWS storage, her name is Mahlon Thompson Bukovec, watch this. Okay now, you may say Dave, what the heck does that have to do with anything? Yeah, I don't know, but as an older white guy, that's been in this business for awhile, I just think it's badass that this woman boxes and runs a business that we think is approaching $10 billion. Now let's take a quick look at the storage announcements AWS made at re:Invent. The company made four announcements this year, let me try to be brief, the first is EBS io2 Block Express Volumes, got to love the names. AWS was claims this is the first storage area network or sand for the cloud and it offers up to 256,000 IOPS and 4,000 megabytes per second throughput and 64 terabytes of capacity. Hey, sounds pretty impressive right, Well let's dig in a little bit okay, first of all, this is not the first sand in the cloud, at least in my view there may be others but Pure Storage announced cloud block store in 2019 at its annual accelerate customer conference and it's pretty comparable here. Maybe not so much in the speeds and feeds, but the concept of better block storage in the cloud with higher availability. Now, as you may also be saying, what's the big deal? The performance come on, we can smoke that we're on-prem vendor We can bury that. Compared to what we do, AWS' announcement is really not that impressive okay, let me give you a point of comparison there's a startup out there called VAST Data. Just there for you and closure with bundled storage and compute can do 400,000 IOPS and 40,000 megabytes per second and that can be scaled, so yeah, I get it. And AWS also announced that io2 two was priced at 20% less than previous generation volumes, which you might say is also no big deal and I would agree 20% is not as aggressive as the average price decline per gigabyte of any storage technology. AWS loves to make a big deal about its price declines, it's essentially following the industry trends but the point is that this feature will be great for a lot of workloads and it's fully integrated with AWS services meaning for example, it will be very convenient for AWS customers to invoke this capability for example Aurora and other AWS databases through its RDS service, just another easy button for developers to push. This is specially important as we see AWS rapidly expanding its machine learning in AI capabilities with SageMaker, it's embedding ML into things like Redshift and driving analytics, so integration is very key for its customers. Now, is Amazon retail going to run its business on io2 volumes? I doubt it. I believe they're running on Oracle and they need much better performance, but this is a mainstream service for the EBS masses to tap. Now, the other notable announcement was EBS Gp3 volumes. This is essentially a service that lets let you programmatically set SLAs for IOPS and throughput independently without needing to add additional storage. Again, you may be saying things like, well atleast I remember when SolidFire let me do this several years ago and gave me more than 3000 IOPS and 125 megabytes per a second performance, but look, this is great for mainstream customers that want more consistent and predictable performance and that want to set some kind of threshold or floor and it's integrated again into the AWS stack. Two other announcements were made, one that automatically tiers data to colder storage tiers and a replication service. On the former, data migrates to tier two after 90 days of inaccess and tier three, after 180 days. AWS remember, they hired a bunch of folks out of EMC years ago and they put them up in the Boston Seaport area, so they've acquired lots of expertise in a lot of different areas I'm not sure if tiering came out of that group but look, this stuff is not rocket science, but it saves customers money. So these are tried and true techniques that AWS is applying but the important thing is it's in the cloud. Now for sure we'd like to see more policy options than say for example, a fixed 90 day or 180 day policy and more importantly we'd like to see intelligent tiering where the machine is smart enough to elevate and promote certain datasets when they're needed for instance, at the end of a quarter for comparison purposes or at the end of the year, but as NFL Hall of Fame Coach Hank Stram would have said, AWS is matriculating the ball down the field. Okay, let's look at some of the data that supports what we're saying here in our premise today. This chart shows spending across the ETR taxonomy. It depicts the net score or spending velocity for different sectors. We've highlighted storage, now don't put too much weight on the January data because the survey was just launched, but you can see storage continues to be a back burner item relative to some other spending priorities. Now as I've reported, CIOs are really focused on cloud, containers, container orchestration, automation, productivity and other key areas like security. Now let's take a look at some of the financial data from the storage crowd. This chart shows data for eight leading names in storage and we put storage in quotes because as we said earlier, the market is shifting and for sure companies like Cohesity and Rubrik, they're not positioning as storage players in fact, that's the last thing they want to do. Rather they're category creators around data management or intelligent data management but their inadjacency to storage, they're partnering with all the primary storage companies and they're in the ETR taxonomy. Okay, so as you can see, we're showing the year over year, quarterly revenue growth for the leading storage companies. NetApp is a big winner, they're growing at a whopping 2%. They beat expectations, but expectations were way down so you can see in the right most column upper right, we've added the ETR net score from October and net score of 10% says that if you ask customers, are you spending more or less with a company, there are 10% of the customers that are essentially spending more than are spending less, get into that a little further later. For comparison, a company like Snowflake, it has a net score approaching 70% Pure Storage used to be that high several years ago or high sixties anyway. So 10% is in the red zone and yet NetApp, is the big winner this quarter. Now Nutanix isn't really again a storage company, but they're an adjacency and they sell storage and like many of these companies, it's transitioning to a subscription pricing model, so that puts pressure on the income statement, that's why they went out and did a deal with Bain, Bain put in $750 million to help Bridge that transition so that's kind of an interesting move. Every company in this chart is moving to an annual recurring revenue model and that as a service approach is going to be the norm by the end of the decade. HPE's doing it with GreenLake, Dell has announced Apex, virtually every company is headed in this direction. Now speaking of HPE, it's Nimble business that has momentum, but other parts of the storage portfolio are quite a bit softer. Dell continues to see pressure on its storage business although VxRail is a bright spot. Everybody's got a bright spot, everybody's got new stuff that's growing much faster than the old stuff, the problem is the old stuff is much much bigger than the new stuff. IBM's mainframe storage cycle, well that's seems to have run its course, they had been growing for the last several quarters that looks like it's over. And so very very cyclical businesses here now as you can see, The data protection data management companies, they are showing spending momentum but they're not public so we don't have revenue data. But you got to wonder with all the money these guys have raised and the red hot IPO and tech markets, why haven't these guys gone public? The answer has to be that they're either not ready or maybe their a numbers weren't where they want them to be, maybe they're not predictable enough, maybe they don't have their operational act together or maybe they need to you get that in order, some combination of those factors is likely. They'll tell you, they'll give other answers if you ask them, but if they had their stuff together they'd be going out right now. Now here's another look at the spending data in terms of net score, which is again spending velocity. The ETR here is measuring the percent of respondents that are adopting new, spending more, spending flat, spending less or retiring the platform. So net score is adoptions, which is the lime green plus the spending more, which is the forest green. Add those two and then subtract spending less, which is the pink and then leaving the platform, which is the bright red, what's left over is net score. So, let's look at the picture here, Cohesity leads all players in the storage taxonomy, the ETR storage taxonomy, again they don't position that way, but that's the way the customers are answering. They've got 55% net score which is really solid and you can see the data in the upper right-hand corner, it's followed by Nutanix. Now they're really not again in the scope of Pure play storage play but speaking of Pure, its net score has come down from its high of 73% in January, 2016. It's not going to climb back up there, but it's going to be interesting to see if Pure net scorecard rebound in a post COVID world. We're also watching what Pure does in terms of unifying file and object and how it's fairing in cloud and what it does with the Portworx acquisition which is really designed to bring forth a new programming model. Now, Dell is doing fine with VxRail, but VSAN is well off its net score highs which we're in the 60% plus range a couple of years ago, VSAN is definitely been a factor from VMware, but again that's come off its highs, HPE with Nimble still has some room to improve, I think it actually will I think that these figures that we're showing here they're are somewhat depressed by the COVID factor, I expect Nimble is going to bounce back in future surveys. Dell and NetApp are the big leaders in terms of presence or market share in the data other than VMware, 'cause VMware has a lot of instances, it's software defined that's why they're so prominent. And with VMware's large share you'd expect them to have net scores that are tepid and you can see a similar pattern with IBM. So Dell, NetApp, tepid net scores as is IBM because of their large market share VMware, kind of a newer entry into the play and so doing pretty well there from a net score standpoint. Now Commvault like Cohesity and Rubrik is really around intelligent data management, trying to go beyond backup into business recovery, data protection, DevOps, bringing that analytics, bringing that to the cloud, we didn't put Veeam in here and we probably should have. They had pre-COVID net scores well in to the thirties and they have a steadily increasing share of the market, so we expect good things from Veeam going forward. They were acquired earlier this year by Insight, capital private equity firm. So big changes there as well, that was their kind of near-term exit maybe more to come. But look, it's all relative, this is a large and mature market that is moving to the cloud and moving to other adjacencies. And the core is still primary storage, that's the main supreme prerequisite and everything else flows from there, data protection, replication, everything else. This chart gives you another view of the competitive landscape, it's that classic XY chart it plots net score in the vertical axis and market share on the horizontal axis, market share remember is a measure of presence in the dataset. Now think about this from the CIO's perspective, they have their on-prem estate, got all this infrastructure and they're putting a brick wall around their core systems. And what do they want out of storage for that class of workload? They want it to perform consistently, they want it to be efficient and they want it to be cost-effective, so what are they going to do? they're going to consolidate, They're going to consolidate the number of vendors, they're going to consolidate the storage, they're going to minimize complexity, yeah, they're going to worry about the blast radius, but there's ways to architect around that. The last thing they want to worry about is managing a zillion storage vendors this business is consolidating, it has been for some time, we've seen the number of independent storage players that are going public as consolidated over the years, and it's going to continue. so on-prem storage arrays are not giving CIOs the innovation and strategic advantage back when things like storage virtualization, space efficient snapshots, data de-duplication and other storage services were worth maybe taking a flyer on a feature product like for example, a 3PAR or even a Data Domain. Now flash gave the CIOs more headroom and better performance and so as I said earlier, they're not just buying spindles to increase performance, so as more and more work gets pushed to the cloud, you're seeing a bunkering in on these large scale mission-critical workloads. As you saw earlier, the legacy storage market is consolidating and has been for a while as I just said, it's essentially becoming a managed decline business where RnD is going to increasingly get squeezed and go to other areas, both from the vendor community and on the buy-side where they're investing on things like cloud, containers and in building new layers in their business and of course the DX, the Digital Transformation. I mentioned VAST Data before, it is a company that's growing and another company that's growing is Infinidat and these guys are traditional storage on-prem models they don't bristle If I say traditional they're nexgen if you will but they don't own a cloud, so they were selling to the data center. Now Infinidat is focused on petabyte scale and as they say, they're growing revenues, they're having success consolidating storage that thing that I just talked about. Ironically, these are two Israeli founder based companies that are growing and you saw earlier, this is a share shift the market is not growing overall the part of that's COVID, but if you exclude cloud, the market is under pressure. Now these two companies that I'm mentioning, they're kind of the exception to the rule here, they're tiny in the grand scheme of things, they're really not going to shift the market and their end game is to get acquired so they can still share, but they're not going to reverse these trends. And every one on this chart, every on-prem player has to have a cloud strategy where they connect into the cloud, where they take advantage of native cloud services and they help extend their respective install bases into the cloud, including having a capability that is physically proximate to the cloud with a colo like an Equinix or some other approach. Now, for example at re:Invent, we saw that AWS has hybrid strategy, we saw that evolving. AWS is trying to bring AWS to the edge and they treat the data center as just another edge note, so outposts and smaller versions of outposts and things like local zones are all part of bringing AWS to the edge. And we saw a few companies Pure, Infinidant, Veeam come to mind that are connecting to outpost. They saw the Qumulo was in there, Clumio, Commvault, WekaIO is also in there and I'm sure I'm missing some so, DM me, email me, yell at me, I'm sorry I forgot you but you get the point. These companies that are selling on-prem are connecting to the cloud, they're forced to connect to the cloud much in the same way as they were forced to join the VMware ecosystem and try to add value, try to keep moving fast. So, that's what's going on here, what's the prognosis for storage in the coming year? Well, where've of all the good times gone? Look, we would never bet against data but the days of selling storage controllers that masks the deficiencies of spinning disc or add embedded hardware functions or easily picking off a legacy install base with flash, well, those days are gone. Repatriation, it ain't happening it's maybe tiny little pockets. CIOs are rationalizing their on-premises portfolios so they can invest in the cloud, AI, machine learning, machine intelligence, automation and they're re-skilling their teams. Low latency high bandwidth workloads with minimal jitter, that's the sweet spot for on-prem it's becoming the mainframe of storage. CIOs are also developing a cloud first strategy yes, the world is hybrid but what does that mean to CIOs? It means you're going to have some work in the cloud and some work on-prem, there's a hybrid We've got both. Everything that can go to the cloud, will go to the cloud, in our opinion and everything that can't or shouldn't won't. Yes, people will make mistakes and they'll "repatriate" but generally that's the trend. And the CIOs they're building an abstraction layer to connect workloads from an observability and manageability standpoint so they can maintain control and manage lock-in risk, they have options. Everything that doesn't go to the cloud will likely have some type of hybridicity to it, the reverse won't likely be the case. For vendors, cloud strategies involve supporting your install basis migration to the cloud, that's where they're going, that's where they want to go, they want your help there's business to be made there so enabling low latency hybrids in accommodating subscription models, well, that's a whole another topic, but that's the trend that we see and you rethink the business that you're in, for instance, data management and developing an edge strategy that recognizes that edge workloads are going to require new architecture and that's more efficient than what we've seen built around general purpose systems, and wow, that's a topic for another day. You're seeing this whole as a service model really reshape the entire cultures in the way in which the on-prem vendors are operating no longer is it selling a box that has dramatically marked up controllers and disc drives, it's really thinking about services that could be invoked in the cloud. Now remember, these episodes are all available as podcasts, wherever you listen, just search Breaking Analysis podcasts and please subscribe, I'd appreciate that checkout etr.plus for all the survey action. We also publish a full report every week on wikibon.com and siliconangle.com. A lot of ways to get in touch. You can email me at david.vellante@siliconangle.com. you could DM me @dvellante on Twitter, comment on our LinkedIn posts, I always appreciate that. This is Dave Vellante for theCUBE Insights Powered by ETR. Thanks for watching everyone stay safe and we'll see you next time. (upbeat music)

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

>> Announcer: From around the globe, it's theCUBE with digital coverage of Dell Technologies world, digital experience, brought to you by Dell Technologies. >> Hi, I'm Stu Miniman and this is theCUBE coverage of Dell Technologies world digital experience. Happy to welcome to the program. First we have a first time guest Akanksha Mehrotra, she's the Vice President of Marketing with Dell Technologies. Joining us one of our CUBE alumni, Caitlin Gordon, she's the Vice President of Product Marketing, also with Dell Technologies. Caitlin, welcome back, Akanksha welcome to the program. >> Thank you Stu, happy to be here. >> Alright, so one of the big models we've been talking about for the last few years is a change in how customers acquire things, big thing we've talked about, for many years, this shift from CAPEX to OPEX. How cloud is impacting everything Jeff Clarke in the keynote was talking about, it's the Dell Technologies on demand, DTOD, I guess is the, four letter acronym we use Akansha help us understand a little bit from your standpoint, what is it? Why is it important to your customers? >> Yeah, so Stu, as soon as you as you heard, as part of the keynote, from from Jeff and others earlier today, we've been working really hard to bring the benefits of on demand IT to our customers, in private cloud, public cloud and edge. And certainly this year, especially, we've seen a lot of interest in this, COVID have catalyzed customer interest in flexible consumption in as a service. As we talk with our customers and partners, we hear this almost daily, it's required a level of agility that candidly traditional CAPEX based models simply haven't been able to provide, I mean, imagine taking your workforce remote over the weekend, and the stress that puts on your infrastructure. And so I think that's kind of forced IT to consider some of these alternatives. Another factor has also been, companies have been wanting to preserve capital, right, and avoid large cash outlays and having this type of flexibility and being able to pay for infrastructure, as you're using it, it gives them a way to do that. So I mean, those are some of the customer drivers that we've seen. Last year at Dell Tech Summit, around the this time last year, actually, in November timeframe, we introduced Dell Technologies on demand as our umbrella program for a flexible consumption and as a service solutions. And really what it what it seeks to do is make it easier for customers to get the simplicity and flexibility of cloud, along with the performance and security of on-premises infrastructure. So it's giving them a range of consumption models that include both payment option as well as services that they can apply on any one of the products in our portfolio from end user devices to core data center infrastructure to hybrid cloud solutions. And we've announced that last year, one of the things that you heard about today, and that we're announcing over this event is that we're continually looking to make it easier and simpler for our customers with various turnkey offerings and simpler offerings for them, given the interest that we've seen. >> Yeah, I want to key off of, you mentioned the impact of COVID-19. And for your customers, it's something we've definitely seen that the promise of cloud always has been to be highly flexible, we can scale up, we can scale down. We know that some services out there aren't always as flexible as we might hope. There's certain SaaS solutions, where you're signing up for a multi year offering and even for the cloud, I might lock in some savings by buying something in bulk. So help us understand, what are the benefits that your customer sees, the savings that they get and is this truly cloud flexible, which means I can burst up and scale as I need. And I can it reached the point, oh, hey, I need half the capacity for the next six months. Can I do that? >> Yeah, absolutely. So, Stu we actually commissioned IBC to talk to a few of our customers. So let me maybe share some of the benefits that they saw in broad terms, and then I can maybe share a specific example of what a particular customer saw. So we had IDC talk to several of the customers using Dell Technologies on demand models, various GIOS, and various sort of sizes. And what they found was that on average, they saw about a 23%, lower cost of storage operations per year, which is great, right? Lower cost of operations is always great. IT is always looking for those efficiencies, especially, in the current environment, but that's not all. I think that's just sort of part of the story. What they also shared with us is that, these types of models were able to help them become much more agile in how they work and change how they work. And what they found was that they saw 54% fewer incidents of downtime and they were 92% faster in their ability to deploy storage capacity, because they had that capacity in their data center available ready for that spike when their business saw it. ` So those are just some of the broad examples of what our customers have seen. Another specific example that I would would share with you is a large multinational institution, financial services company, we've been working with them for years to service their, enterprise scale, private cloud. And then more recently, they had us also, manage their storage as a service managed utility. And they've seen phenomenal results, they've been able to get 50% more compute power at 8%, lower cost, and 90% faster or reduce time and provisioning data. It's all about the yes, it's about the cost savings but really, it's about the agility that the business gets, right. And as you started out, right, with COVID, they really needed that agility and that flexibility and having these models available, ready to spike, ready to go down, right, have been able to provide that. >> Yeah, I think another thing we've seen is, people rush to cloud because it promised that agility, and we've had those conversations before is, there's a reality of what that means, which it might not be the resiliency you're looking for, it also might not actually be as simple as he thought it might be. And we're seeing some of that come back on-prem, whether you need resiliency or performance or security, or you don't want to be really locked into a specific public cloud but you still want to have that agility in the benefits of really running your data center in a service oriented model. And that trend has been picking up over the past couple years. And as we've already said a couple times today, we've seen that accelerate, but also, we starting to see more customers ask for it. It's not just the big and more strategic and the aggressive customers that are looking for this more and more customers are kind of seeing that this is the end game and that's kind of leads into where we're going, which is, how do we make this more accessible to others? >> Well, Caitlin, you're using one of one of my punch lines that I've used for a number of years now if remember, when we thought that cloud was inexpensive and easy to use, it's not. And if we look at what customers are doing, it's a hybrid model. They're deploying in multiple environments, we're seeing the public cloud look more like the enterprise, the enterprise look more like, the public cloud. So these offerings have, OPEX flexibility and the like, make a whole lot of sense. So you've said that, you've seen a lot of growth, especially this year, any metrics you can give us on, adoption, love the one customer example, in the financial space, anything else to kind of paint the picture as to, how prevalent this is becoming. >> Yeah, maybe I'll get started. So, we've seen nearly 50%, year over year growth in the customer base or our most recent quarter, and it's growing, we've seen over 500% increase, year on year in signed contracts, customer demand in these types of models has caused us to expand our offerings to into countries like Brazil, Chile, Colombia, India, and China. I mean, we already offered about 50 plus countries and along with our partner, network and even more, so, I mean, those are just some of the data points around business traction. In the models that we have another proof point that I could point you to is that, in April, we include, we announced a payment flexibility program, which gave our customers a number of promotions and options to extend this flexibility into, across our portfolio and into other parts of our businesses. And just recently, about a month ago, we extended that, and we've seen really good traction in that as well. So I think overall, like you said there's aspects about public cloud that customers really like, and they tell us, hey, I want to be able to pay as I go, I want to be able to extend and contract the infrastructure as I'm using it. I want a simple management experience. But then as Caitlin said, they realize that Oh, but I don't want to, pay for the refactoring and then the egress and the ingress charges and some of my workloads are better off on premises for performance, locality, security, compliance reasons, right. And therein lies the promise of as a service for on-prem infrastructure, 'cause really, I keep looking for the best of both worlds. And this gives you that right you can use the consumption models to grow and shrink as you needed, you can us the payment models to only pay for what you're using and along with our partner network, you can have in the location that you want so you can sort of have your cake and eat it too. >> Yeah, and I would just add on to that is that more and more of the conversation is both about how can I consume that more as a service and pay for just what I'm using? But also, how can I spend less time maybe zero time and energy actually managing that infrastructure? And how can I then allocate the time energy resources into running my business and investing in more strategic things? So becomes both an important financial conversation but even more so a conversation about how IT can empower the business, which really just changes what we're able to do for customers. So it's an exciting kind of transition to see this really evolve into really not talking about products anymore, and helping our customers have all their business. >> Well, Caitlin, that's a really interesting point, I want you to talk to us a little bit about the Dell Tech storage as a service, how does that fit, we were just talking about don't want to talk about products, we want to talk about really moving to that full OPEX model so help connect the dots for us. >> Yeah, so we're really excited about this, this will be coming in the first half of next year, as you probably heard earlier today. And what we're doing here is we've really taken what we already have had in market. And we've really upped that to the next level, we've accelerated the simplicity of what we offer here. And think of the experience is all starting in a single console, where you just pick up four things, what's the type of storage you want, what's the performance you want, how much and for how long, that's it. And then now we're counting the time from then to when it's in your data center in days, not months, not weeks, but in days and we're able to get you up and going. And it's your data center of your choice, whether that's on-prem in your own data center, or at a colo facility, we bring that equipment in, we get that deployed, we manage it for you, you operate it, and you simply pay for what you use. So you're really in a quick time to value you're in a very simple model and you're not really responsible for managing infrastructure that's really on us. And that moves you into being in a true OPEX model and it also enables you to accelerate what you're able to leverage that whether it's Blob Storage, file storage, you can get up and running quickly and let us worry about how to manage the infrastructure and we give you the ability to operate what you need to. >> Caitlin, maybe if you could give us a little bit of color as to what happens behind the scenes to make that work. As it sounds wonderful, you've had the program around for a year, these aren't trivial things that you're talking about all the logistics, the management the the gear, and making sure that the physical and the power and everything is all set. So help us understand the engineering, the development, and what this means from kind of a services and go to market that make a solution like this work. >> Yeah, and a lot of ways we're having to change our entire business to help our customers change there's, it goes from top to bottom, and you'll get to hear a lot more about it when we're actually available next year. But when you think about it, we have a lot of the DNA, we have a lot of the experience, we have the technology, but we almost have to completely flip the script on ourselves of how we deliver it, who our customer is, what our then end user customer needs from us, and what the role of things like our global services organization is what the role of our global sales organization is and how do we accelerate providing outcomes to our customers and get the rest out of their way. And the fact that I haven't mentioned a product name, but by the way, we actually have industry leading products and pretty much every category. So of course, on the back end, all of this is going to be powered by our industry leading storage solutions, like power store will be in your data center but at the same time, we will actually have worked to really masked that you don't even need to know that nor do you need to really operate much beyond what you need to really run your business. And that's really it's been an interesting work for us to just flip how we think about everything and you'll hear a whole lot more about it next year as we really bring this out into market but it's been really fun and a big learning for everyone. >> Excellent well yeah, something something power is underneath there well Caitlin. All right why don't you both give us the final takeaway for the Dell Tech on demand account. Start with you in just give us the final takeaway. >> Yeah, so I think look, I back to kind of what we were talking about, we've actually been offering these types of solutions to our customers for a really long time. Through Dell financial services, we've been offering payment flexibility for over 23 years, over 15 years and manage utility. So the customer example that I gave you is a customer who's running storage as a service and has been for many years, I think, building on that experience, listening to our customers feedback over that time period and over, of course, this past year, we're looking to apply all of that, to make it even more simpler for them to consume our infrastructure in the near future. And so, storage as a service is going to be a really exciting proof point of that, the momentum stats and some of the other things that I shared with you today and that you're going to hear about over the next couple of days or another proof point of it. But we're excited about this, and looking forward to continuing the dialogue with our customers with our partners and (mumbles) >> Then I would I'll kind of play off of one of your words there which is is all about simplicity for us is how do we take what we've been able to do for a lot of our customers accelerate that and simplify it to a point where we can offer that for all of our customers. And we're really looking to accelerate this first with storage and then get all of our offerings really into this model, because it's really about getting our customers out of managing infrastructure and give them the time, energy, resources to manage their business and simplicity is paramount to making sure that happens. >> Caitlin and Akanksha, thank you so much for giving us the updates. Congratulations to all the progress and definitely looking forward to hearing more beginning of next year. Thanks for joining. >> Thank you Stu. >> Thank you Stu >> All right, I'm Stu Miniman this is Dell Technology world digital experience. I'm Stu Miniman. And thank you as always for watching theCUBE (upbeat music)