>> Narrator: From around the globe, it's theCUBE with coverage of SUSECON Digital brought to you by SUSE. >> Welcome back to theCUBE's coverage of SUSECON Digital '20. I'm Stu Miniman and happy to welcome to the program one of SUSE's partners, we have Marc O'Regan, he is the CTO of EMEA for Dell Technologies. Marc, it is great to see you, we all wish, I know when I talked to Melissa Di Donato and the team, everybody was really looking forward to coming to Ireland, but at least we're talking to you in Ireland so thanks so much for joining us. >> Stu, thanks very much for having me. I'm delighted to be here. You know, really looking forward to getting you guys here, unfortunately it wasn't a beaver, once we're all safe and well, great to talk. >> Yeah, absolutely, that's the important thing. Everybody is safe, we've had theCUBE a couple of times in Dublin. I'd actually, you know, circled this one on my calendar 'cause I wanted to get back the Emerald Isle but, Marc, let's talk first, you know, the Dell and SUSE relationship you know, disclaimer, you know, I've got a little bit of background on this. You know, I was the product manager for Linux at a company known as EMC back before Dell bought them, many moons ago, so I know that, you know, Dell and the Dell EMC relationship with SUSE go back a couple of decades, but, you know, bring us into, you know, what your teams are working together and we'll go from there. >> Yeah, sure, Stu, so, quite correct, nearly a two decade long relationship with SUSE and one that we hold very dear to our heart. I think what both organizations have in common is their thirst and will to innovate and we've been doing that with SUSE for 16, 17 years, right back to, you know, SUSE Enterprise Linux sitting on, you know, PowerEdge architecture way, way back in the day into you know, some of the developments and collaborations that we, that we worked through with the SUSE teams. I remember back 2013, 2014 doing a pretty cool program with our then Fluid Cache technology. So, when you look at, you know, OLTP kind of environments, what you want to kind of get away from is the, you know, the read-write, commits and latency that are inherent in those types of environments. So, as you start to build and get more users hitting the, hitting the ecosystem, you need to be able to respond and SUSE has been absolutely, you know, instrumental to helping us build an architecture then with our Fluid Cache technology back in the day, and the SUSE technology sitting around and under that and then of course, in more recent times, really extending that innovation aspiration, I guess, has been absolutely a pleasure to, to watch and to be involved with, see it mature so some of the cool platforms that we're developing with SUSE together it's a, it's pretty neat so I'm, you know, one of those being-- >> So, Marc, yeah, well, you know, bring us up to speed, you know, right in the early days, it was, you know, Linux on the SUSE side, it was, you know, servers and storage from the Dell side, you know, today it's, you know, microservice architectures, cloud native solutions. So, you know, bring us up to speed as to some of the important technologies and obviously, you know, both companies have matured and grown and have a much broader portfolio other than they would have years ago. >> Yeah, for sure, absolutely. So, I mean, what's exciting is when you look at some of the architectures that we are building together, we're building reference architectures. So we're taking this work that we're doing together and we're building edge architectures that are suitable for small, medium, and you know, and large environments. And the common thread that pulls those three architectures together is that they are all enterprise grade architectures. And the architectures are used as frameworks. We don't always expect our customers to use them, you know, by the letter of the law, but they are a framework and, by which they can look to roll out scalable storage solutions. For example, like the Ceph, the SUSE Enterprise Storage solution that we collaborate with and have built such a reference architecture for. So this is, you know, it's built on Ceph architecture under the hood, but, you know, both ourselves and SUSE have brought a level of innovation, you know, into an arena, where you need cost, and you need low latency, and you need those types of things that we spoke about, I guess a moment ago, and into, you know, this new cloud native ecosystem that you just spoke to a few moments ago. So on the cloud native side, we're also heavily collaborating, and near co-engineering with SUSE on their CaaS technologies. So here it's really interesting to look at organizations like SAP and what we're doing with data hub and SAP, it's all part of the intelligent enterprise for SAP. This is where SUSE and Dell Tech together really get, you know, into looking at how we can extract information out of data, different data repositories. You know, you may have Oracle you may have, you know, you may have HDFS, you may have Excel and you're trying to extract data and information from that data, from those different siloed environments and the CaaS technology brings its, you know, its micro, capability to the forum in that regard, our hardware architecture is the perfect fit to, to bring that scalar platform, cloud native platform into the ecosystem. >> So, you know, Marc, you've got the CTO hat on for the European theater there. When we, we've been talking to SUSE, when they talk about their innovation, obviously, the community and open-source is a big piece of what they're doing. You were just walking through some of the cloud native pieces, give us what you're seeing when it comes to, you know, how is Dell helping drive innovation, you know, and how does that connects with what you're doing with partners like SUSE. >> Yeah, well, you know, innovation is massively, massively important. So there's a number of different factors that, you know, make up a very good innovation framework or a good innovation program. And at Dell Tech we happen to have what we believe to be an extraordinarily good innovation framework. And we have a lot of R&D budget assigned to helping innovate and we get the chance to go out and work with SUSE and other partners as well. What SUSE and Dell Tech do really, really well together is bring other partners and other technologies into the mix. And, you know, this allows us to innovate, co-innovate together as part of that framework that I just mentioned. So on the Dell Tech framework, we'll obviously, you know, take technologies, you know, we'll take them, perhaps into the office of the CTO, look at new, you know, emerging tech and look at, you know, more traditional tech, for example, and we will blend those together. And, you know, as part of the process and the innovation process, we generally take a view on some of the partners that we actually want to get involved in that process. And SUSE is very much one of those partners, as a matter of fact, right now, we're doing a couple of things with SUSE, one in the labs in Walldorf in Germany, where we're looking at high availability solution that we're trying to develop and optimize there right now at this point in time. And another good example that I can think of at the moment is looking at how customers are migrating off, you know, older, more traditional platforms, they need to look at the cloud native world, they need look at how they can, platform for success in this cloud native world. And we're looking at how we can get smarter, I guess about migrating them from that, you know, extraordinarily stealthy world that they had been in the past but that needs to get from that stealthy world into an even stealthier scalable world that is, that is cloud native world. >> Yeah, Marc, you talk about customers going through these transformations, I wonder if you can help connect the dots for us as to how these types of solutions fit into customers overall cloud strategies. So, you know, obviously, you know, Dell has broad portfolio, a lot of different pieces that are on the cloud, you know, I know there's a long partnership between Dell and SUSE and like SAP solutions, we've been looking at how those modernize so, you know, where does cloud fit in and we'd love any of kind of the European insights that you can give on that overall cloud discussion. >> Yeah, sure, so, again, ourselves and SUSE go back on, in history, you know, on the cloud platforming side, I mean, we've collaborated on developing a cloud platform in the past as well. So we had an OpenStack platform that we both collaborated on and you know, it was very successful for both of us. Where I'm seeing a lot of the requirement in this multicloud world that we're kind of living in right now, is the ability to be able to build a performant scalable platform that is going to be able to respond in the cloud native ecosystem. And that is going to be able to traverse workloads from on-prem to off-prem and from different cloud platforms with different underlying dependencies there. And that's really the whole aspiration, I guess, of this open cloud ecosystem. How do we get workloads to traverse across, across those types of domain. And the other is bringing the kind of, you know, performance that's expected out of these new workloads that are starting to emerge in the cloud native spaces. And as we start to look to data and extract information from data, we are also looking to do so in an extraordinary, accurate and in an extraordinary performant way and having the right kind of architecture underneath that is absolutely, absolutely essential. So I mentioned, you know, SAP's data hub a little earlier on, that's a really, really good example. As is, a matter of fact, SAP's Leonardo framework so, you know, my background is HPC, right? So, I will always look to how we can possibly architect to get the compute engineering as close to the data sources as possible as we can. And that means having to, in some way get out of these monolithic stacks that we've been used to over the last, you know, for a number of decades into a more horizontally scaled out kind of architecture. That means landing the right architecture into those environments, being able to respond, you know, in a meaningful way that's going to ultimately drive value to users and for the users and for the providers of the services, who are building these type of, these type of ecosystems. Again, you know, as I said, you know, data hub, and some of the work that Dell Tech are doing with the CaaS platform is absolutely, you know, perfectly positioned to address those types of, those types of problems and those types of challenges. On the other side, as I mentioned, the, you know, the story solutions that we're doing with SUSE are really taking off as well. So I was involved in a number of years ago in the Ceph program on the Irish government network and, so these would have been very big. And one of the earliest to be honest, Ceph firm I was involved with probably around five, six years ago, perhaps. And the overlying architecture, funnily enough, was, as you probably have guessed by now was SUSE Enterprise. And here we are today building, you know, entire, entire Ceph scale out storage solutions with SUSE. So yeah, what we're seeing is an open ecosystem, a scalable ecosystem and a performant ecosystem that needs to be able to respond and that's what the partnership with SUSE is actually bringing. >> So, Marc, I guess the last thing I'd like to ask you is, you know, we're all dealing with the, the ripple effects of what are happening with the COVID-19 global pandemic. >> Sure. >> You know, I know I've seen online lots that Dell is doing, I'm wondering what is the impact that, you know, you're seeing and anything specific regarding, you know, how this impact partnerships and how, you know, tech communities come together in these challenging times? >> Yeah, that's a great question to end on, Stu. And I think it's times like we're living through at the moment when we see, you know, the real potential of, I guess of human and machine collaboration when you think of the industry we're in, when you think of some of the problems that we're trying to solve. Here we are, a global pandemic, we have a problem that's distributed by its very nature, and I'm trying to find patterns, I guess, I'm trying to model, you know, for the treatment of, you know, COVID-19 is something that's very, very close to our heart. So we're doing a lot on the technology side where we're looking to, as I said, model for treatment but also use distributed analytical architectures to collaborate with partners in order to be able to, you know, contribute to the effort of finding treatments for COVID-19. On the commercial side of things then Dell Tech are doing a huge amount so, you know, we're, for instance, we're designing a, we're designing a financial model or framework, if you will, where our customers and our partners have, you know, can take our infrastructure and our partners infrastructure and those collaborations that we spoke about today. And they can land them into their ecosystem with pretty much zero percent finance. And so it's kind of a, it's an opportunity where, you know, we're taking the technology and we're taking the capability to land that technology into these ecosystems at a very, very low cost, but also give organizations the breadth and opportunity to consume those technologies without having to worry about, you know, ultimately paying up front they can start to look at the financial model that will suit them and that will, that will, that will, hopefully, accelerate their time, their time to market, trying to solve some of these problem that we've been speaking about. >> Well, Marc, thank you so much for the updates. Definitely good to hear about the technology pieces as well as some of these impacts that will have a more global impact. Thanks so much for joining us. >> Stu, my pleasure. Thank you, take care and stay safe. >> Thanks, same to you. All right, I'm Stu Miniman, back with lots more covered from SUSECON Digital '20. Thank you, for always, for watching theCUBE. 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>> (Narrator) The CUBE's live coverage is made possible by funding by Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Fira Barcelona. It's theCUBE live at MWC23 our third day of coverage of this great, huge event continues. Lisa Martin and Dave Nicholson here. We've got Dell and Dish here, we are going to be talking about what they're doing together. Andy Sheahen joins as global director of Telecom Cloud Core and Next Gen Ops at Dell. And Marc Rouanne, one of our alumni is back, EVP and Chief Network Officer at Dish Wireless. Welcome guys. >> Great to be here. >> (Both) Thank you. >> (Lisa) Great to have you. Mark, talk to us about what's going on at Dish wireless. Give us the update. >> Yeah so we've built a network from scratch in the US, that covered the US, we use a cloud base Cloud native, so from the bottom of the tower all the way to the internet uses cloud distributed cloud, emits it, so there are a lot of things about that. But it's unique, and now it's working, so we're starting to play with it and that's pretty cool. >> What's some of the proof points, proof in the pudding? >> Well, for us, first of all it was to do basic voice and data on a smartphone and for me the success would that you won't see the difference for a smartphone. That's base line. the next step is bringing this to the enterprise for their use case. So we've covered- now we have services for smartphones. We use our brand, Boost brand, and we are distributing that across the US. But as I said, the real good stuff is when you start to making you know the machines and all the data and the applications for the enterprise. >> Andy, how is Dell a facilitator of what Marc just described and the use cases and what their able to deliver? >> We're providing a number of the servers that are being used out in their radio access network. The virtual DU servers, we're also providing some bare metal orchestration capabilities to help automate the process of deploying all these hundreds and thousands of nodes out in the field. Both of these, the servers and the bare metal orchestra product are things that we developed in concert with Dish, working together to understand the way, the best way to automate, based on the tooling their using in other parts of their network, and we've been with you guys since day one, really. >> (Marc) Absolutely, yeah. >> Making each others solutions better the whole way. >> Marc, why Dell? >> So, the way the networks work is you have a cloud, and you have a distributed edge you need someone who understands the diversity of the edge in order to bring the cloud software to the edge, and Dell is the best there, you know, you can, we can ask them to mix and match accelerators, processors memory, it's very diverse distributed edge. We are building twenty thousands sides so you imagine the size and the complexity and Dell was the right partner for that. >> (Andy) Thank you. >> So you mentioned addressing enterprise leads, which is interesting because there's nothing that would prevent you from going after consumer wireless technically, right but it sounds like you have taken a look at the market and said "we're going to go after this segment of the market." >> (Marc) Yeah. >> At least for now. Are there significant differences between what an enterprise expects from a 5G network than, verses a consumer? >> Yeah. >> (Dave) They have higher expectations, maybe, number one I guess is, if my bill is 150 dollars a month I can have certain levels of expectations whereas a large enterprise the may be making a much more significant investment, are their expectations greater? >> (Marc) Yeah. >> Do you have a higher bar to get over? >> So first, I mean first we use our network for consumers, but for us it's an enterprise. That's the consumer segment, an enterprise. So we expose the network like we would to a car manufacturer, or to a distributor of goods of food and beverage. But what you expect when you are an enterprise, you expect, manage your services. You expect to control the goodness of your services, and for this you need to observe what's happening. Are you delivering the right service? What is the feedback from the enterprise users, and that's what we call the observability. We have a data centric network, so our enterprises are saying "Yeah connecting is enough, but show us how it works, and show us how we can learn from the data, improve, improve, and become more competitive." That's the big difference. >> So what you say Marc, are some of the outcomes you achieved working with Dell? TCO, ROI, CapX, OpX, what are some of the outcomes so far, that you've been able to accomplish? >> Yeah, so obviously we don't share our numbers, but we're very competitive. Both on the CapX and the OpX. And the second thing is that we are much faster in terms of innovation, you know one of the things that Telecorp would not do, was to tap into the IT industry. So we access to the silicon and we have access to the software and at a scale that none of the Telecorp could ever do and for us it's like "wow" and it's a very powerful industry and we've been driving the consist- it's a bit technical but all the silicone, the accelerators, the processors, the GPU, the TPUs and it's like wow. It's really a transformation. >> Andy, is there anything anagallis that you've dealt with in the past to the situation where you have this true core edge, environment where you have to instrument the devices that you provide to give that level of observation or observability, whatever the new word is, that we've invented for that. >> Yeah, yeah. >> I mean has there, is there anything- >> Yeah absolutely. >> Is this unprecedented? >> No, no not at all. I mean Dell's been really working at the edge since before the edge was called the edge right, we've been selling, our hardware and infrastructure out to retail shops, branch office locations, you know just smaller form factors outside of data centers for a very long time and so that's sort of the consistency from what we've been doing for 30 years to now the difference is the volume, the different number of permutations as Marc was saying. The different type of accelerator cards, the different SKUS of different server types, the sheer volume of nodes that you have in a nationwide wireless network. So the volumes are much different, the amount of data is much different, but the process is really the same. It's about having the infrastructure in the right place at the right time and being able to understand if it's working well or if it's not and it's not just about a red light or a green light but healthy and unhealthy conditions and predicting when the red lights going to come on. And we've been doing that for a while it's just a different scale, and a different level of complexity when you're trying to piece together all these different components from different vendors. >> So we talk a lot about ecosystem, and sometimes because of the desire to talk about the outcomes and what the end users, customers, really care about sometimes we will stop at the layer where say a Dell lives, and we'll see that as the sum total of the component when really, when you talk about a server that Dish is using that in and of itself is an ecosystem >> Yep, yeah >> (Dave) or there's an ecosystem behind it you just mentioned it, the kinds of components and the choices that you make when you optimize these devices determine how much value Dish, >> (Andy) Absolutely. >> Can get out of that. How deep are you on that hardware? I'm a knuckle dragging hardware guy. >> Deep, very deep, I mean just the number of permutations that were working through with Dish and other operators as well, different accelerator cards that we talked about, different techniques for timing obviously there's different SKUs with the silicon itself, different chip sets, different chips from different providers, all those things have to come together, and we build the basic foundation and then we also started working with our cloud partners Red Hat, Wind River, all these guys, VM Ware, of course and that's the next layer up, so you've got all the different hardware components, you've got the extraction layer, with your virtualization layer and or ubernetise layer and all of that stuff together has to be managed compatibility matrices that get very deep and very big, very quickly and that's really the foundational challenge we think of open ran is thinking all these different pieces are going to fit together and not just work today but work everyday as everything gets updated much more frequently than in the legacy world. >> So you care about those things, so we don't have to. >> That's right. >> That's the beauty of it. >> Yes. >> Well thank you. (laughter) >> You're welcome. >> I want to understand, you know some of the things that we've been talking about, every company is a data company, regardless of whether it's telco, it's a retailer, if it's my bank, it's my grocery store and they have to be able to use data as quickly as possible to make decisions. One of the things they've been talking here is the monetization of data, the monetization of the network. How do you, how does Dell help, like a Dish be able to achieve the monetization of their data. >> Well as Marc was saying before the enterprise use cases are what we are all kind of betting on for 5G, right? And enterprises expect to have access to data and to telemetry to do whatever use cases they want to execute in their particular industry, so you know, if it's a health care provider, if it's a factory, an agricultural provider that's leveraging this network, they need to get the data from the network, from the devices, they need to correlate it, in order to do things like automatically turn on a watering system at a certain time, right, they need to know the weather around make sure it's not too windy and you're going to waste a lot of water. All that has data, it's going to leverage data from the network, it's going to leverage data from devices, it's going to leverage data from applications and that's data that can be monetized. When you have all that data and it's all correlated there's value, inherit to it and you can even go onto a forward looking state where you can intelligently move workloads around, based on the data. Based on the clarity of the traffic of the network, where is the right place to put it, and even based on current pricing for things like on demand insists from cloud providers. So having all that data correlated allows any enterprise to make an intelligent decision about how to move a workload around a network and get the most efficient placing of that workload. >> Marc, Andy mentions things like data and networks and moving data across the networks. You have on your business card, Chief Network Officer, what potentially either keeps you up at night in terror or gets you very excited about the future of your network? What's out there in the frontier and what are those key obstacles that have to be overcome that you work with? >> Yeah, I think we have the network, we have the baseline, but we don't yet have the consumption that is easy by the enterprise, you know an enterprise likes to say "I have 4K camera, I connect it to my software." Click, click, right? And that's where we need to be so we're talking about it APIs that are so simple that they become a click and we engineers we have a tendency to want to explain but we should not, it should become a click. You know, and the phone revolution with the apps became those clicks, we have to do the same for the enterprise, for video, for surveillance, for analytics, it has to be clicks. >> While balancing flexibility, and agility of course because you know the folks who were fans of CLIs come in light interfaces, who hate gooeys it's because they feel they have the ability to go down to another level, so obviously that's a balancing act. >> But that's our job. >> Yeah. >> Our job is to hide the complexity, but of course there is complexity. It's like in the cloud, an emprise scaler, they manage complex things but it's successful if they hide it. >> (Dave) Yeah. >> It's the same. You know we have to be emprise scaler of connectivity but hide it. >> Yeah. >> So that people connect everything, right? >> Well it's Andy's servers, we're all magicians hiding it all. >> Yeah. >> It really is. >> It's like don't worry about it, just know, >> Let us do it. >> Sit down, we will serve you the meal. Don't worry how it's cooked. >> That's right, the enterprises want the outcome. >> (Dave) Yeah. >> They don't want to deal with that bottom layer. But it is tremendously complex and we want to take that on and make it better for the industry. >> That's critical. Marc I'd love to go back to you and just I know that you've been in telco for such a long time and here we are day three of MWC the name changed this year, from Mobile World Congress, reflecting mobilism isn't the only thing, obviously it was the catalyst, but what some of the things that you've heard at the event, maybe seen at the event that give you the confidence that the right players are here to help move Dish wireless forward, for example. >> You know this is the first, I've been here for decades it's the first time, and I'm a Chief Network Officer, first time we don't talk about the network. >> (Andy) Yeah. >> Isn't that surprising? People don't tell me about speed, or latency, they talk about consumption. Apps, you know videos surveillance, or analytics or it's, so I love that, because now we're starting to talk about how we can consume and monetize but that's the first time. We use to talk about gigabytes and this and that, none of that not once. >> What does that signify to you, in terms of the evolution? >> Well you know, we've seen that the demand for the healthcare, for the smart cities, has been here for a decade, proof of concepts for a decade but the consumption has been behind and for me this is the oldest team is waking up to we are going to make it easy, so that the consumption can take off. The demand is there, we have to serve it. And the fact that people are starting to say we hide the complexity that's our problem, but don't even mention it, I love it. >> Yep. Drop the mic. >> (Andy and Marc) Yeah, yeah. >> Andy last question for you, some of the things we know Dell has a big and verging presents in telco, we've had a chance to see the booth, see the cool things you guys are featuring there, Dave did a great tour of it, talk about some of the things you've heard and maybe even from customers at this event that demonstrate to you that Dell is going in the right direction with it's telco strategy. >> Yeah, I mean personally for me this has been an unbelievable event for Dell we've had tons and tons of customer meetings of course and the feedback we're getting is that the things we're bring to market whether it's infrablocks, or purposeful servers that are designed for the telecom network are what our customers need and have always wanted. We get a lot of wows, right? >> (Lisa) That's nice. >> "Wow we didn't know Dell was doing this, we had no idea." And the other part of it is that not everybody was sure that we were going to move as fast as we have so the speed in which we've been able to bring some of these things to market and part of that was working with Dish, you know a pioneer, to make sure we were building the right things and I think a lot of the customers that we talked to really appreciate the fact that we're doing it with the industry, >> (Lisa) Yeah. >> You know, not at the industry and that comes across in the way they are responding and what their talking to us about now. >> And that came across in the interview that you just did. Thank you both for joining Dave and me. >> Thank you >> Talking about what Dell and Dish are doing together the proof is in the pudding, and you did a great job at explaining that, thanks guys, we appreciate it. >> Thank you. >> All right, our pleasure. For our guest and for Dave Nicholson, I'm Lisa Martin, you're watching theCUBE live from MWC 23 day three. We will be back with our next guest, so don't go anywhere. (upbeat music)

(techno intro music) >> Hey everyone, good afternoon from sin city. This is Lisa Martin with Dave Vellante. We are in full swing of theCUBE's four days of coverage of AWS re:invent 2022. North of 50,000 people are here. We're nearing hundreds of thousands online. Dave, this has been, this is a great event. We've had great conversations. We're going to be having more conversations. One of the things we love talking about on theCUBE is AWS and its ecosystem of partners, and we are going to do just that right now. Brian Henderson joins us, Director of Marketing at Dell Technologies. Marc Trimuschat, Director of Worldwide Storage Specialists at AWS is also here. Guys, it's great to have you. >> Great to be here. >> Great to be here, yeah. Feeling the energy of the show. >> Isn't it great? >> Mark: I know, amazing. >> It's amazing. It started out high and it has not dropped since Monday night. Brian, talk a little bit about Dell, what you're doing with customers on their Cloud journeys. Every customer, every industry is on one at different points in their journey, but what's Dell helping out with there? >> What we're here to talk about is the progression that we've seen, right, Cloud has changed a lot over the years and Dell has really put out a strategy to help people with their Cloud journey, kind of wherever they are. So a lot of people have moved full shift. A lot of people see that as another location, and what we're showing at the booth is the idea of taking these enterprise capabilities that people know and trust from Dell, courting them to the Cloud. In some cases not courting, but just delivering that software in the Cloud, as well as taking some of the Kubernetes integrations, EKS Anywhere, bringing that on-prem. So we've got some storage, data protection, and our Kubernetes integration to talk about at the show. >> Awesome, Mark, talk about the role from Amazon's point of view that third party vendors like Dell Technologies plays in AWS's expanding vision of Cloud. >> Great, well, we're really excited to be partnering with Dell. What we see that historically is, you know, AWS is focused on builders, people, and really the developer community who are building those components themselves, putting together really resilient infrastructure and applications. What we're seeing today is a shift also to the type of customers that we're seeing, more traditional enterprise customers, who are demanding really performance, the scalability, also the resiliency of what they had on-premises, and they want that on the Cloud as well. So with Dell, and we've got some great solutions that we're partnering on, including Dell PowerFlex that provides that linear scalability and some of the high performance capabilities that customers are demanding. And also, another big trend that we're seeing is customers being affected by things like unfortunately malware events, right, and data protection. So Dell provides some great solutions in both those areas that allow enterprise customers to really experience that mission critical capability and resiliency that they have on-premises in the Cloud. >> You know, Brian, we've been at this a long time. >> Brian: Oh yeah, great to see you again. >> And I've been hearing my whole career that storage is going to get commoditized. And I guess if you're talking about spinning discs or flash drives, it's probably true, but as Mark was just saying if you want resilient storage and things that are recoverable, that don't go down all the time, they're not commodities. >> Brian: Yeah. >> It's real engineering. And you built the stack up, so talk about how that connection, what value you bring to the Cloud and your customers. >> Yeah, so what we see is people are always looking out for enterprise grade capabilities. So there's going to be a set of offerings, and AWS has a fantastic foundation for building on top of with the marketplace. So what we're able to do is really bring, in some cases, decades worth of investment in software engineering and put these advanced capabilities, whether it be PowerFlex with its linear scale. We'll have a file offering very soon. These products have been built from the ground up to do a very unique purpose. Giving that to people in the Cloud is just another location for us, AWS being the market leader. We're the market leader in storage. So us working together for the benefit of customers is really where it's at. >> Can you double click on that, Brian, what Dell and AWS? Give us all those juicy details. >> Sure, sure, sure, so what we've done right before this show is we put a product called PowerFlex, if you go back to 2018 scale IO, and you're taking this really linear scaling software defined architecture, and you're putting that in the Cloud. What that allows you to do is get that really advanced linear scale performance. You can even span clusters across AWS regions, as well as zones. So it's a really unique capability that allows us to be able to check in and do that. And in the data protection space, it's a whole separate category. We've been at this actually quite a while. We've got about 14 exo bytes of data that's already being protected on the AWS Cloud. So we've been at that for quite a while. And the two levels are really, do you want to back that up? Do you want to take a traditional back up application, maybe it's a lift and shift, and I want to back it up the way I used to, and you can do that in the Cloud now. Or we're seeing cyber resiliency come up a lot more, and we were just talking right before, it's a question of when, not if, and so we have to give our customers the option to not only detect that failure event early, but also to separate that copy with a logical air gap. >> The cyber resiliency is a topic we are talking more and more about. It's absolutely critical. We've seen the threat landscape change dramatically in the last couple of years. To your point, Brian, it's no longer, when we think of ransomware, it's no longer are we going to get hit? It's when, it's how often. What's the damage going to be? I think I saw a stat recently that there's one ransomware attack every 11 seconds. The average cost of reaches is in the millions, so what you're doing together on cyber resiliency for businesses in any industry is table stakes. >> Yeah, we just saw a survey that, it was done earlier this year survey, 66% unfortunately of corporations have experienced a malware attack. And that's an 80% increase from last year. >> Lisa: Wow. >> So again, I think that's an opportunity. It's a threat, but an opportunity, and so the partnership with Dell really helps bridge that and helps our customers, our mutual customers, recover from those incidents. >> A lot of people might say, this is interesting. A storage guy from Amazon, a storage guy from Dell, two leaders. And one might think, why didn't they just throw in a dash three, right, but you guys are both customer driven, customer obsessed. In the field, what are customers saying to you in terms of how they want you to work together? >> Well I think there's a place for everything. When you say throw in to S3, so S3 today, one of the big trends when you're looking here is just the amount of data, you know, we hear that rhetoric, you know, we've been in storage for many years, and the data has all increased up and to the right. But, you know, AWSI, S3 today, we have over 280 trillion objects in our, driving a hundred million transactions per second right now, so that's scale. So there's always a place for those really, we have hundreds of thousands of customers running their data links, so that's always going to be that really, you know, highly reliable, highly durable, high available solution for data links. But customers, there's a lot of different applications out there. So where customers are asking are those enterpise. So we have EBS, for example, which is our great, you know, scalable block search, elastic block store. We introduced some new volume types, like GP2, GP2, and IO2VX, which will have that performance. But there's still single availability zone. So what customers have done historically is they maybe the application layer, they put an application layer replication or resiliency across, but customers on-prem, they've relied on storage layers to do that work for them. So, with PowerFlex, that'll stand either using instant storage or EBS, building on that really strong foundation, but provide that additional layer to make it easy for customers to get that resiliency and that scalability that Brian talked about. >> Yep, yep. >> Anything you can add to that? >> Yeah, I mean to your question, how do we work together is really, it's all customer driven. So we see customers that are shifting workloads in the Cloud for the first time. And it might make sense to take an object, like PowerFlex or another storage technology, maybe you want to compress it a little bit before you send it to the Cloud. Maybe you don't want to lift and shift everything. So we have a team of people that works very closely with AWS to be able to determine how are you going to shift that workload out there? Does this make the right sense for you? So it's a very collaborative relationship. And it's all very customer driven because our customers are saying, I've got assets in the public Cloud, and I want them to be managed in a similar fashion to how I'm doing that on-prem. >> So customer obsession is clearly on both sides there. We know that. >> It's where it starts. >> Exactly, exactly. Going back to PowerFlex for a second, Brian, and I'd love to get an example of a joint customer that really is showing the value of what Dell and AWS are doing together. The question for you on PowerFlex, talk about the value that it offers to the public Cloud. And why should customers start there if they are early in this journey? >> All right, yeah, so the two angles are basically, are you coming from PowerFlex or you're coming from Cloud. If you're Cloud native, the advantage would be things like a really, really advanced block file system that has been built from the ground up to be software defined and pretty much Cloud native. What you're getting is that really linear scale up to about 1,000 nodes. You can span that across regions, across availability zones, so it's highly resilient. So if there's a node failure in one site, you're going to rebuild really fast, depending on the size of that cluster. So it's a very advanced architecture that's been built to run, you know, we didn't have to change a single line of code to run this product in the Cloud because it was Cloud native by default, so. >> Well that's the thing. We also see, and you've seen that with some of the other solutions, but customers really want that. Enterprise customers are, they want us to make sure those mission critical applications are working and stay up. So they also want to use the same environment. So we were talking before, we also see use cases where maybe they're using PowerFlex on-premises today and they want to be able to replicate that to PowerFlex that's in the Cloud. So we're seeing those, and the familiarity with that infrastructure really is that easy path, if you will, for those more conservative mission critical customers. >> We've learned a lot over the years from AWS's entry into the marketplace. Two recent teams working backwards. We talk about customer obsession. And also the Cloud experience. It brings me to APEX. >> Oh yeah. >> Dave: How does APEX fit in here? >> Yeah, so APEX is the categorization for all the things that we're doing around a modern Cloud experience for Dell customers. So we're taking them also on a journey, kind of as a service model. There's a do-it-yourself model. And anything that we do that touches Cloud is now being kind of put under that APEX moniker. So everything that we're doing around Project Alpine, enterprise software capabilities in the Cloud. Do you want someone else to manage it for you? Do you want it in a polo? That might be the right fit for you. It's all under that APEX umbrella and journey. So we're kind of still just getting started there, but we're seeing a lot of great traction. People want to pay as they go, you know, it's a very popular model that AWS has pretty much set the foundation for. So pay as you go, utility based pricing, this is all things our customers have been asking for. >> Yeah, so APEX, you basically set a baseline. You can dial it up, dial it down, very much pay by the drink. >> Absolutely. >> And, you know, like you said, it's early days. >> Brian: Yeah. >> But that's, again, AWS has influenced the business in a lot of different ways. >> Again, with the Dell, you know, the trust customers that Dell has built over the years and having those customers come in. We obviously are getting, again, it's an accelerated option for financial services to healthcare and all these customers that have relied on Dell for years, moving to the Cloud, having that trusted name and also that infrastructure that's similar and familiar to them. And then the resilience of the foundation that we have at AWS, I think it works really well together for those customers. >> I think it underscores to the majority of both AWS and in a lot of ways Dell, right. In the early days of Cloud, it was like uh oh, and now it's like oh, actually big market. Customers are demanding this. There's new value that we can create working together. Let's do it. >> Yeah, I mean, it didn't take us that long to get to it, but I'd say we had little fits and starts over the years, and now we've recognized like, this is where the future is. It's going to be Cloud, it's going to be on-prem, it's going to be Edge, it's going to be everything. It's going to be an and world. And so just doing the right thing for customers I think is exactly where we landed. It's a great partnership. >> Do you have a favorite customer story that you think really shines the light on the value of the Dell AWS partnership in terms of the business impact they're making? >> We have several large customers that I can't always like drop the names, but one of them is a very large video game production company. And we do a lot of work together where they're rendering maybe in house, they're sending to a shared location. They're copying data over to S3. They're able to let all their editors access that. They bring it back when it's compressed down a little bit and deliver that. We're also doing a lot of work with, I think I can say this, Amazon Thursday night football games. So what they've done there, it's a partner of ours working with AWS. All the details inside of that roaming truck that they drive around, there's a lot of Dell gear within there, and then everything connects back to AWS for that exact same kind of model. We need to get to the editors on a nightly basis. They're also streaming directly form that truck while they're enabling the editors to access a shared copy of it, so it's really powerful stuff. >> Thursday night prime is pretty cool. You know, some people are complaining cause I can't just switch channels during the commercials. It's like, first of all, you can. Second of all, the stats are unbelievable, right. You can just do your own replay when you want to. There's some cool innovations there. >> Oh yeah, absolutely. >> Very cool innovations. I've got one more question for each of you before we wrap. Marc, a question for you, we're making a fun Instagram reel. So think about a sizzle reel of if you were to summarize the show so far, what is AWS's message to its massive audience this year? >> Well, that's a big question. Because we have such a wide, as we mentioned, such a wide ranging audience. I really see a couple key trends that we're trying to address. One is, again don't forget, I'm a storage guy, so it's going to come from an angle from data, right. So, I think it's just this volume of data and that customers are bringing into the Cloud, either moving in from enterprises today or organically, just growing. You know, a couple years ago, megabytes were a lot, and now, you know, we're talking about petabytes every day. Soon it's going to be exo bytes are going to become the norm. So the big, I'd say, point one is the trend that I see is just the volume of data. And so what we're doing to address that is obviously we talked a little bit about S3 and being able to manage volumes of data, but also things like DataZone that we introduced because customers are looking to make sure that the right governance and controls to be able to access that data. So I think that's one big thing that I see the theme for the show today. The second thing is around, as I said, really these enterprise customers really wanted to move in these mission critical applications into the Cloud, and having that infrastructure to be able to support that easily from what they're doing today and move in quickly. The third area is around data protection, making sure the data protection and malware recovery, that's the theme that we see is really unfortunately that's today. But being able to recover quickly, both having native services and native offerings just built in resiliency into the core platforms, like S3 with object application, et cetera. And also partnering with Dell with cyber recovery and some of the solutions with Dell. >> Excellent, and Brian, last question for you. A bumper sticker that succinctly and powerfully describes why Dell and AWS are such awesome partners for customer issues. >> Best of both worlds, right? >> Lisa: Mic drop. >> Mic drop, done. >> That's awesome. You said that a lot more succinctly. (people laughing) >> Enterprise in Cloud, Cloud comin' to enterprise. >> Yeah, leader meets leader, right? >> Yeah, right. >> Love it, leader meets leader. Guys, it's been a pleasure having you on theCUBE. We appreciate hearing the latest from AWS and Dell from a storage perspective and from a Cloud perspective and how you're helping customers manage the explosion of data that's not going to slow down. We really appreciate you coming by the set. >> Thank you. >> Great, thanks so much, appreciate it. >> My pleasure. For our guests and Dave Vellante, I'm Lisa Martin, you're watching theCUBE, the leader in live enterprise and emerging tech coverage. (techno music)

(upbeat music) >> For those of you who've been following the cloud database space, you know that MySQL HeatWave has been on a technology tear over the last 24 months with Oracle claiming record breaking benchmarks relative to other database platforms. So far, those benchmarks remain industry leading as competitors have chosen not to respond, perhaps because they don't feel the need to, or maybe they don't feel that doing so would serve their interest. Regardless, the HeatWave team at Oracle has been very aggressive about its performance claims, making lots of noise, challenging the competition to respond, publishing their scripts to GitHub. But so far, there are no takers, but customers seem to be picking up on these moves by Oracle and it's likely the performance numbers resonate with them. Now, the other area we want to explore, which we haven't thus far, is the engine behind HeatWave and that is AMD. AMD's epic processors have been the powerhouse on OCI, running MySQL HeatWave since day one. And today we're going to explore how these two technology companies are working together to deliver these performance gains and some compelling TCO metrics. In fact, a recent Wikibon analysis from senior analyst Marc Staimer made some TCO comparisons in OLAP workloads relative to AWS, Snowflake, GCP, and Azure databases, you can find that research on wikibon.com. And with that, let me introduce today's guest, Nipun Agarwal senior vice president of MySQL HeatWave and Kumaran Siva, who's the corporate vice president for strategic business development at AMD. Welcome to theCUBE gentlemen. >> Welcome. Thank you. >> Thank you, Dave. >> Hey Nipun, you and I have talked a lot about this. You've been on theCUBE a number of times talking about MySQL HeatWave. But for viewers who may not have seen those episodes maybe you could give us an overview of HeatWave and how it's different from competitive cloud database offerings. >> Sure. So MySQL HeatWave is a fully managed MySQL database service offering from Oracle. It's a single database, which can be used to run transactional processing, analytics and machine learning workloads. So, in the past, MySQL has been designed and optimized for transaction processing. So customers of MySQL when they had to run, analytics machine learning, would need to extract the data out of MySQL, into some other database or service, to run analytics or machine learning. MySQL HeatWave offers a single database for running all kinds of workloads so customers don't need to extract data into some of the database. In addition to having a single database, MySQL HeatWave is also very performant compared to one up databases and also it is very price competitive. So the advantages are; single database, very performant, and very good price performance. >> Yes. And you've published some pretty impressive price performance numbers against competitors. Maybe you could describe those benchmarks and highlight some of the results, please. >> Sure. So one thing to notice that the performance of any database is going to like vary, the performance advantage is going to vary based on, the size of the data and the specific workloads, so the mileage varies, that's the first thing to know. So what we have done is, we have published multiple benchmarks. So we have benchmarks on PPCH or PPCDS and we have benchmarks on different data sizes because based on the customer's workload, the mileage is going to vary, so we want to give customers a broad range of comparisons so that they can decide for themselves. So in a specific case, where we are running on a 30 terabyte PPCH workload, HeatWave is about 18 times better price performance compared to Redshift. 18 times better compared to Redshift, about 33 times better price performance, compared to Snowflake, and 42 times better price performance compared to Google BigQuery. So, this is on 30 Terabyte PPCH. Now, if the data size is different, or the workload is different, the characteristics may vary slightly but this is just to give a flavor of the kind of performance advantage MySQL HeatWave offers. >> And then my last question before we bring in Kumaran. We've talked about the secret sauce being the tight integration between hardware and software, but would you add anything to that? What is that secret sauce in HeatWave that enables you to achieve these performance results and what does it mean for customers? >> So there are three parts to this. One is HeatWave has been designed with a scale out architecture in mind. So we have invented and implemented new algorithms for skill out query processing for analytics. The second aspect is that HeatWave has been really optimized for cloud, commodity cloud, and that's where AMD comes in. So for instance, many of the partitioning schemes we have for processing HeatWave, we optimize them for the L3 cache of the AMD processor. The thing which is very important to our customers is not just the sheer performance but the price performance, and that's where we have had a very good partnership with AMD because not only does AMD help us provide very good performance, but the price performance, right? And that all these numbers which I was showing, big part of it is because we are running on AMD which provides very good price performance. So that's the second aspect. And the third aspect is, MySQL autopilot, which provides machine learning based automation. So it's really these three things, a combination of new algorithms, design for scale out query processing, optimized for commodity cloud hardware, specifically AMD processors, and third, MySQL auto pilot which gives us this performance advantage. >> Great, thank you. So that's a good segue for AMD and Kumaran. So Kumaran, what is AMD bringing to the table? What are the, like, for instance, relevance specs of the chips that are used in Oracle cloud infrastructure and what makes them unique? >> Yeah, thanks Dave. That's a good question. So, OCI is a great customer of ours. They use what we call the top of stack devices meaning that they have the highest core count and they also are very, very fast cores. So these are currently Zen 3 cores. I think the HeatWave product is right now deployed on Zen 2 but will shortly be also on the Zen 3 core as well. But we provide in the case of OCI 64 cores. So that's the largest devices that we build. What actually happens is, because these large number of CPUs in a single package and therefore increasing the density of the node, you end up with this fantastic TCO equation and the cost per performance, the cost per for deployed services like HeatWave actually ends up being extraordinarily competitive and that's a big part of the contribution that we're bringing in here. >> So Zen 3 is the AMD micro architecture which you introduced, I think in 2017, and it's the basis for EPIC, which is sort of the enterprise grade that you really attacked the enterprise with. Maybe you could elaborate a little bit, double click on how your chips contribute specifically to HeatWave's, price performance results. >> Yeah, absolutely. So in the case of HeatWave, so as Nipun alluded to, we have very large L3 caches, right? So in our very, very top end parts just like the Milan X devices, we can go all the way up to like 768 megabytes of L3 cache. And that gives you just enormous performance and performance gains. And that's part of what we're seeing with HeatWave today and that not that they're currently on the second generation ROM based product, 'cause it's a 7,002 based product line running with the 64 cores. But as time goes on, they'll be adopting the next generation Milan as well. And the other part of it too is, as our chip led architecture has evolved, we know, so from the first generation Naples way back in 2017, we went from having multiple memory domains and a sort of NUMA architecture at the time, today we've really optimized that architecture. We use a common I/O Die that has all of the memory channels attached to it. And what that means is that, these scale out applications like HeatWave, are able to really scale very efficiently as they go from a small domain of CPUs to, for example the entire chip, all 64 cores that scaling, is been a key focus for AMD and being able to design and build architectures that can take advantage of that and then have applications like HeatWave that scale so well on it, has been, a key aim of ours. >> And Gen 3 moving up the Italian countryside. Nipun, you've taken the somewhat unusual step of posting the benchmark parameters, making them public on GitHub. Now, HeatWave is relatively new. So people felt that when Oracle gained ownership of MySQL it would let it wilt on the vine in favor of Oracle database, so you lost some ground and now, you're getting very aggressive with HeatWave. What's the reason for publishing those benchmark parameters on GitHub? >> So, the main reason for us to publish price performance numbers for HeatWave is to communicate to our customers a sense of what are the benefits they're going to get when they use HeatWave. But we want to be very transparent because as I said the performance advantages for the customers may vary, based on the data size, based on the specific workloads. So one of the reasons for us to publish, all these scripts on GitHub is for transparency. So we want customers to take a look at the scripts, know what we have done, and be confident that we stand by the numbers which we are publishing, and they're very welcome, to try these numbers themselves. In fact, we have had customers who have downloaded the scripts from GitHub and run them on our service to kind of validate. The second aspect is in some cases, they may be some deviations from what we are publishing versus what the customer would like to run in the production deployments so it provides an easy way, for customers to take the scripts, modify them in some ways which may suit their real world scenario and run to see what the performance advantages are. So that's the main reason, first, is transparency, so the customers can see what we are doing, because of the comparison, and B, if they want to modify it to suit their needs, and then see what is the performance of HeatWave, they're very welcome to do so. >> So have customers done that? Have they taken the benchmarks? And I mean, if I were a competitor, honestly, I wouldn't get into that food fight because of the impressive performance, but unless I had to, I mean, have customers picked up on that, Nipun? >> Absolutely. In fact, we have had many customers who have benchmarked the performance of MySQL HeatWave, with other services. And the fact that the scripts are available, gives them a very good starting point, and then they've also tweaked those queries in some cases, to see what the Delta would be. And in some cases, customers got back to us saying, hey the performance advantage of HeatWave is actually slightly higher than what was published and what is the reason. And the reason was, when the customers were trying, they were trying on the latest version of the service, and our benchmark results were posted let's say, two months back. So the service had improved in those two to three months and customers actually saw better performance. So yes, absolutely. We have seen customers download the scripts, try them and also modify them to some extent and then do the comparison of HeatWave with other services. >> Interesting. Maybe a question for both of you how is the competition responding to this? They haven't said, "Hey, we're going to come up "with our own benchmarks." Which is very common, you oftentimes see that. Although, for instance, Snowflake hasn't responded to data bricks, so that's not their game, but if the customers are actually, putting a lot of faith in the benchmarks and actually using that for buying decisions, then it's inevitable. But how have you seen the competition respond to the MySQL HeatWave and AMD combo? >> So maybe I can take the first track from the database service standpoint. When customers have more choice, it is invariably advantages for the customer because then the competition is going to react, right? So the way we have seen the reaction is that we do believe, that the other database services are going to take a closer eye to the price performance, right? Because if you're offering such good price performance, the vendors are already looking at it. And, you know, instances where they have offered let's say discount to the customers, to kind of at least like close the gap to some extent. And the second thing would be in terms of the capability. So like one of the things which I should have mentioned even early on, is that not only does MySQL HeatWave on AMD, provide very good price performance, say on like a small cluster, but it's all the way up to a cluster size of 64 nodes, which has about 1000 cores. So the point is, that HeatWave performs very well, both on a small system, as well as a huge scale out. And this is again, one of those things which is a differentiation compared to other services so we expect that even other database services will have to improve their offerings to provide the same good scale factor, which customers are now starting to expectancy, with MySQL HeatWave. >> Kumaran, anything you'd add to that? I mean, you guys are an arms dealer, you love all your OEMs, but at the same time, you've got chip competitors, Silicon competitors. How do you see the competitive-- >> I'd say the broader answer and the big picture for AMD, we're very maniacally focused on our customers, right? And OCI and Oracle are huge and important customers for us, and this particular use cases is extremely interesting both in that it takes advantage, very well of our architecture and it pulls out some of the value that AMD bring. I think from a big picture standpoint, our aim is to execute, to build to bring out generations of CPUs, kind of, you know, do what we say and say, sorry, say what we do and do what we say. And from that point of view, we're hitting, the schedules that we say, and being able to bring out the latest technology and bring it in a TCO value proposition that generationally keeps OCI and HeatWave ahead. That's the crux of our partnership here. >> Yeah, the execution's been obvious for the last several years. Kumaran, staying with you, how would you characterize the collaboration between, the AMD engineers and the HeatWave engineering team? How do you guys work together? >> No, I'd say we're in a very, very deep collaboration. So, there's a few aspects where, we've actually been working together very closely on the code and being able to optimize for both the large L3 cache that AMD has, and so to be able to take advantage of that. And then also, to be able to take advantage of the scaling. So going between, you know, our architecture is chip like based, so we have these, the CPU cores on, we call 'em CCDs and the inter CCD communication, there's opportunities to optimize an application level and that's something we've been engaged with. In the broader engagement, we are going back now for multiple generations with OCI, and there's a lot of input that now, kind of resonates in the product line itself. And so we value this very close collaboration with HeatWave and OCI. >> Yeah, and the cadence, Nip, and you and I have talked about this quite a bit. The cadence has been quite rapid. It's like this constant cycle every couple of months I turn around, is something new on HeatWave. But for question again, for both of you, what new things do you think that organizations, customers, are going to be able to do with MySQL HeatWave if you could look out next 12 to 18 months, is there anything you can share at this time about future collaborations? >> Right, look, 12 to 18 months is a long time. There's going to be a lot of innovation, a lot of new capabilities coming out on in MySQL HeatWave. But even based on what we are currently offering, and the trend we are seeing is that customers are bringing, more classes of workloads. So we started off with OLTP for MySQL, then it went to analytics. Then we increased it to mixed workloads, and now we offer like machine learning as alike. So one is we are seeing, more and more classes of workloads come to MySQL HeatWave. And the second is a scale, that kind of data volumes people are using HeatWave for, to process these mixed workloads, analytics machine learning OLTP, that's increasing. Now, along the way we are making it simpler to use, we are making it more cost effective use. So for instance, last time, when we talked about, we had introduced this real time elasticity and that's something which is a very, very popular feature because customers want the ability to be able to scale out, or scale down very efficiently. That's something we provided. We provided support for compression. So all of these capabilities are making it more efficient for customers to run a larger part of their workloads on MySQL HeatWave, and we will continue to make it richer in the next 12 to 18 months. >> Thank you. Kumaran, anything you'd add to that, we'll give you the last word as we got to wrap it. >> No, absolutely. So, you know, next 12 to 18 months we will have our Zen 4 CPUs out. So this could potentially go into the next generation of the OCI infrastructure. This would be with the Genoa and then Bergamo CPUs taking us to 96 and 128 cores with 12 channels at DDR five. This capability, you know, when applied to an application like HeatWave, you can see that it'll open up another order of magnitude potentially of use cases, right? And we're excited to see what customers can do do with that. It certainly will make, kind of the, this service, and the cloud in general, that this cloud migration, I think even more attractive. So we're pretty excited to see how things evolve in this period of time. >> Yeah, the innovations are coming together. Guys, thanks so much, we got to leave it there really appreciate your time. >> Thank you. >> All right, and thank you for watching this special Cube conversation, this is Dave Vellante, and we'll see you next time. (soft calm music)

[Music] welcome to the great super cloud debate a power panel of three top technology industry analysts maribel lopez is here she's the founder and principal analyst at lopez research keith townsend is ceo and founder of the cto advisor and sanjeev mohan is principal at sanjmo super cloud is a term that we've used to describe the future of cloud architectures the idea is that super clouds are built on top of hyperscaler capex infrastructure and the idea is it goes beyond multi-cloud the premise being that multi-cloud is primarily a symptom of multi-vendor or m a or both and results in more stove we're going to talk about that super cloud's meant to connote a new architecture that leverages the underlying primitives of hyperscale clouds but hides and abstracts that complexity of each of their respective clouds and adds new value on top of that with services and a continuous experience a similar or identical experience across more than one cloud people may say hey that's multi-cloud we're going to talk about that as well so with that as brief background um i'd like to first welcome our painless guys thanks so much for coming on thecube it's great to see you all again great to be here thank you to be here so i'm going to start with maribel you know what i just described what's your reaction to that is it just like what like cloud is supposed to be is that really what multi-cloud is do you agree with the premise that multi-cloud has really been you know what like chuck whitten from dell calls it it's been multi-cloud by default i call it a symptom of multi-vendor what's your take on on what this is oh wow dave another term here we go right more more to define for people but okay the reality is i agree that it's time for something new something evolved right whether we call that super cloud or something else i you know i don't want to really debate the term but we need to move beyond where we are today in multi-cloud and into if we want to call it cloud 5 multi-cloud 2 whatever we want to call it i believe that we're at the next generation that we have to define what that next generation is but if you think about it we went from public to private to hybrid to multi and every time you have a discussion with somebody about cloud you spend 10 minutes defining what you're talking about so this doesn't seem any different to me so let's just go with super cloud for the moment and see where we go and you know if you're interested after everybody else makes their comments i got a few thoughts about what super cloud might mean as well yeah great so i and i agree with you when we like i said in a recent post you could call it cl cloud you know multi-cloud 2.0 but it's something different is happening and sanjeev i know you're not a you're not a big fan of buzz words either but i wonder if you could weigh in on this topic uh you mean by the way sanjeev is at the mit cdo iq conference a great conference uh in boston uh and so he's it's a public place so we're going to have i think you viewed his line when he's not speaking please go ahead yeah so you know i come from a pedigree of uh being an analyst of uh firms that love inventing new terms i am not a big fan of inventing new terms i feel that when we come up with a new term i spend all my time standing on a stage trying to define what it is it takes me away from trying to solve the problem so so i'm you know i find these terms to be uh words of convenience like for example big data you know big data to me may not mean anything but big data connotes some of this modern way of handling vast volumes of data that traditional systems could not handle so from that point of view i'm i'm completely okay with super cloud but just inventing a new term is what i have called in my previous sessions tyranny of jargons where we have just too many jargons and uh and they resonate with i.t people they do not resonate with the business people business people care about the problem they don't care about what we and i t called them yeah and i think this is a really important point that you make and by the way we're not trying to create a new industry category per se yeah we leave that to gartner that's why actually i like super cloud because nobody's going to use that no vendor's going to use the term super cloud it's just too buzzy so so but but but it brings up the point about practitioners and so keith i want to bring you in so the what we've talked about and i'll just sort of share some some thoughts on the problems that we see and and get keith get your practitioner view most clouds most companies use multiple clouds we all kind of agree on that i think and largely these clouds operate in silos and they have their own development environment their own operating environment different apis different primitives and the functionality of a particular cloud doesn't necessarily extend to other clouds so the problem is that increases friction for customers increases cost increases security risk and so there's this promise maribel multi-cloud 2.0 that's going to solve that problem so keith my question to you is is is that an accurate description of the problem that practitioners face today do what did i miss and i wonder if you could elaborate so i think we'll get into some of the detail later on why this is a problem specifically around technologies but if we think about it in the abstract most customers have their hands full dealing with one cloud like we'll you know through m a and such and you zoom in and you look at companies that have multiple clouds or multi-cloud from result of mma mna m a activity you'll see that most of that is in silos so organizationally the customer may have multiple clouds but sub orchid silos they're generally a single silo in a single cloud so as you think about being able to take advantage of of tooling across the multicloud of what dave you guys are calling the super cloud this becomes a serious problem it's just a skill problem it's too much capability uh across too many things that look completely different than another okay so dave can i pick up on that please i'd love i was gonna just go to you maribel please chime in here okay so if we think about what we're talking about with super cloud and what keith just mentioned remember when we went to see tcp ip and the whole idea was like how do we get computers to talk to each other in a more standardized way how do we get data to move in a more standardized way i think that the problem we have with multi-cloud right now is that we don't have that so i think that's sort of a ground level of getting us to your super cloud premise is that and and you know google's tried it with anthony's like everybody every hyperscaler has tried their like right one to run anywhere but that abstraction layer you talk about what whatever we want to call it is super necessary and it's sort of the foundation so if you really think about it we've spent like 15 years or so building out all the various components of cloud and now's the time to take it so that cloud is actually more of an operating model versus a place there's at least a base level of it that is vendor neutral and then to your point the value that's going to be built on top of that you know people been trying to commoditize the basic infrastructure for a while now and i think that's what you're seeing in your super cloud multi-cloud whatever you want to call it the infrastructure is the infrastructure and then what would have been traditionally that past layer and above is where we're going to start to see some real innovation but we still haven't gotten to that point where you can do visibility observability manageability across that really complex cloud stack that we have the reason i the reason i love that tcpip example hm is because it changed the industry and it had an ecosystem effect in sanjiv the the the example that i first example that i used was snowflake a company that you're very familiar with that is sort of hiding all that complexity and right and so we're not there yet but please chime in on this topic uh you gotta you gotta view it again uh after you building upon what maribel said you know to me uh this sounds like a multi-cloud operating system where uh you know you need that kind of a common uh set of primitives and layers because if you go in in the typical multi-cloud process you've got multiple identities and you can't have that you how can you govern if i'm if i have multiple identities i don't have observability i don't know what's going on across my different stacks so to me super cloud is that call it single pane of glass or or one way through which i'm unifying my experience my my technology interfaces my integration and uh and i as an end user don't even care which uh which cloud i'm in it makes no difference to me it makes a difference to the vendor the vendor may say this is coming from aws and this is coming from gcp or azure but to the end user it is a consistent experience with consistent id and and observability and governance so that to me makes it a big difference and so one of floyer's contribution conversation was in order to have a super cloud you got to have a super pass i'm like oh boy people are going to love that but the point being that that allows a consistent developer experience and to maribel's earlier point about tcp it explodes the ecosystem because the ecosystem can now write to that super pass if you will those apis so keith do you do do you buy that number one and number two do you see that industries financial services and healthcare are actually going to be on clouds or what we call super clouds so sanjeev hit on a really key aspect of this is identity let's make this real they you love talk about data collaboration i love senji's point on the business user kind of doesn't care if this is aws versus super cloud versus etc i was collaborating with the client and he wanted to send video file and the video file uh his organization's access control policy didn't allow him to upload or share the file from their preferred platform so he had to go out to another cloud provider and create yet another identity for that data on the cloud same data different identity a proper super cloud will enable me to simply say as a end user here's a set of data or data sets and i want to share a collaboration a collaborator and that requires cross identity across multiple clouds so even before we get to the past layer and the apis we have to solve the most basic problem which is data how do we stop data scientists from shipping snowballs to a location because we can't figure out the identity the we're duplicating the same data within the same cloud because we can't share identity across customer accounts or etc we we have to solve these basic thoughts before we get to supercloud otherwise we get to us a turtles all the way down thing so we'll get into snowflake and what snowflake can do but that's what happens when i want to share my snowflake data across multiple clouds to a different platform yeah you have to go inside the snowflake cloud which leads right so i would say to keith's question sanjeev snowflake i think is solving that problem but then he brings up the other problem which is what if i want to share share data outside the snowflake cloud so that gets to the point of visit open is it closed and so sanji chime in on the sort of snowflake example and in maribel i wonder if there are networking examples because that's that's keith's saying you got to fix the plumbing before you get these higher level abstractions but sanji first yeah so i so i actually want to go and talk a little bit about network but from a data and analytics point of view so i never built upon what what keith said so i i want to give an example let's say i am getting fantastic web logs i and i know who uh uh how much time they're spending on my web pages and which pages they're looking at so i have all of that now all of that is going into cloud a now it turns out that i use google analytics or maybe i use adobe's you know analytics uh suite now that is giving me the business view and i'm trying to do customer journey analytics and guess what i now have two separate identities two separate products two separate clouds if i and i as an id person no problem i can solve any problem by writing tons of code but why would i do that if i can have that super pass or a multi-cloud layout where i've got like a single way of looking at my network traffic my customer metrics and i can do my customer journey analytics it solves a huge problem and then i can share that data with my with my partners so they can see data about their products which is a combination of data from different uh clouds great thank you uh maribel please i think we're having a lord of the rings moment here with the run one room to rule them all concept and i'm not sure that anybody's actually incented to do that right so i think there's two levels of the stack i think in the basic we're talking a lot about we don't have the basic fundamentals of how do you move data authenticate data secure data do data lineage all that stuff across different clouds right we haven't even spoken right now i feel like we're really just talking about the public cloud venue and we haven't even pulled in the fact that people are doing hybrid cloud right so hybrid cloud you know then you're talking about you've got hardware vendors and you've got hyperscaler vendors and there's two or three different ways of doing things so i honestly think that something will emerge like if we think about where we are in technology today it's almost like we need back to that operating system that sanji was talking about like we need a next generation operating system like nobody wants to build the cloud mouse driver of the 21st century over and over again right we need something like that as a foundation layer but then on top of it you know there's obviously a lot of opportunity to build differentiation like when i think back on what happened with cloud amazon remained aws remained very powerful and popular because people invested in building things on amazon right they created a platform and it took a while for anybody else to catch up to that or to have that kind of presence and i still feel that way when i talk to companies but having said that i talked to retail the other day and they were like hey we spent a long time building an abstraction layer on top of the clouds so that our developers could basically write once and run anywhere but they were a massive global presence retailer that's not something that everybody can do so i think that we are still missing a gap i don't know if that exactly answers your question but i i do feel like we're kind of in this chicken and egg thing which comes first and nobody wants to necessarily invest in like oh well you know amazon has built a way to do this so we're all just going to do it the amazon way right it seems like that's not going to work either but i think you bring up a really important point which there is going to be no one ring to rule them all you're going to have you know vmware is going to solve its multi-cloud problem snowflake's going to do a very has a very specific you know purpose-built system for it itself databricks is going to do its thing and it's going to be you know more open source i would companies like aviatrix i would say cisco even is going to go out and solve this problem dell showed at uh at dell tech world a thing called uh project alpine which is basically storage across clouds they're going to be many super clouds we're going to get maybe super cloud stove pipes but but the point is however for a specific problem in a set of use cases they will be addressing those and solving incremental value so keith maybe we won't have that single cloud operating you know system but we'll have multiple ones what are your thoughts on that yeah we're definitely going to have multiple ones uh the there is no um there is no community large enough or influential enough to push a design take maribel's example of the mega retailer they've solved it but they're not going to that's that's competitive that's their competitive advantage they're not going to share that with the rest of us and open source that and force that upon the industry via just agreement from everyone else so we're not going to get uh the level of collaboration either originated by the cloud provider originated from user groups that solves this problem big for us we will get silos in which this problem is solved we'll get groups working together inside of maybe uh industry or subgroups within the industry to say that hey we're going to share or federate identity across our three or four or five or a dozen organizations we'll be able to share data we're going to solve that data problem but in the same individual organizations in another part of the super cloud problem are going to again just be silos i can't uh i can't run machine learning against my web assets for the community group that i run because that's not part of the working group that solved a different data science problem so yes we're going to have these uh bifurcations and forks within the super cloud the question is where is the focus for each individual organization where do i point my smart people and what problems they solve okay i want to throw out a premise and get you guys reaction to it because i think this again i go back to the maribel's tcpip example it changed the industry it opened up an ecosystem and to me this is what digital transformation is all about you've got now industry participants marc andreessen says every company is a software company you've now got industry participants and here's some examples it's not i wouldn't call them true super clouds yet but walmart's doing their hybrid thing with azure you got goldman sachs announced at the last reinvent and it's going to take its tools its software its data and which is on-prem and connect that to the aws cloud and actually deliver a service capital one we saw sanjiv at the snowflake summit is is taking their tooling and doing it now granted just within snowflake and aws but i fully expect them to expand that across other clouds these are industry examples capital one software is the name of the division that are now it's to the re reason why i don't get so worried that we're not solving the lord of the rings problem that maribel mentioned is because it opens up tremendous opportunities for companies we got like just under five minutes left i want to throw that out there and see what you guys think yeah i would just i want to build upon what maribel said i love what she said you're not going to build a mouse driver so if multi-cloud supercloud is a multi-cloud os the mouse driver would be identity or maybe it's data quality and to teach point that data quality is not going to come from a single vendor that is going to come from a different vendor whose job is to to harmonize data because there might be data might be for the same identity but it may be a different granularity level so you cannot just mix and match so you need to have some sort of like resolution and that is is an example of a driver for multi-cloud interesting okay so you know octa might be the identity cloud or z scaler might be the security cloud or calibre has its cloud etc any thoughts on that keith or maribel yeah so let's talk about where the practical challenges run into this we did some really great research that was sponsored by one of the large cloud providers in which we took all we looked at all the vmware cloud solutions when i say vmware cloud vmware has a lot of products across multi-cloud now in the rock broadcloud portfolio but we're talking about the og solution vmware vsphere it would seem like on paper if i put vmware vsphere in each cloud that is therefore a super cloud i think we would all agree to that in principle what we found in our research was that when we put hands on keyboard the differences of the clouds show themselves in the training gap and that skills gap between the clouds show themselves if i needed to expose less our favorite friend a friend a tc pip address to the public internet that is a different process on each one of the clouds that needs to be done on each one of the clouds and not abstracted in vmware vsphere so as we look at the nuance yes we can give the big controls but where the capital ones the uh jp morgan chase just spent two billion dollars on this type of capability where the spin effort is done is taking it from that 80 percent to that 90 95 experience and that's where the effort and money is spent on that last mile maribel we're out of time but please you know bring us home give us your closing thoughts hey i think we're still going to be working on what the multi-cloud thing is for a while and you know super cloud i think is a direction of the future of cloud computing but we got some real problems to solve around authentication uh identity data lineage data security so i think those are going to be sort of the tactical things that we're working on for the next couple years right guys always a pleasure having you on the cube i hope we see you around keith i understand you're you're bringing your airstream to vmworld or vmware explorer putting it on the on the floor i can't wait to see that and uh mrs cto advisor i'm sure we'll be uh by your side so looking forward to that hopefully sanjeev and maribel we'll see you uh on the circuit as well yes hope to see you there right looking forward to hopefully even doing some content with you guys at vmware explorer too awesome looking forward all right keep it right there for more content from super cloud 22 right back [Music] you

(upbeat music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase. We're in Season two, Episode three, and this is the topic of MarTech and the Emerging Cloud-Scale Customer Experiences, the ongoing coverage of AWS's ecosystem of large scale growth and new companies and growing companies. I'm your host, John Furrier. We're excited to have Tim Barnes, Global Director, General Manager of Advertiser and Marketing at AWS here doing the keynote cloud-scale customer experience. Tim, thanks for coming on. >> Oh, great to be here and thank you for having me. >> You've seen many cycles of innovation, certainly in the ad tech platform space around data, serving consumers and a lot of big, big scale advertisers over the years as the Web 1.0, 2.0, now 3.0 coming, cloud-scale, roll of data, all big conversations changing the game. We see things like cookies going away. What does this all mean? Silos, walled gardens, a lot of new things are impacting the applications and expectations of consumers, which is also impacting the folks trying to reach the consumers. And this is kind of creating a kind of a current situation, which is challenging, but also an opportunity. Can you share your perspective of what this current situation is, as the emerging MarTech landscape emerges? >> Yeah, sure, John, it's funny in this industry, the only constant has changed and it's an ever-changing industry and never more so than right now. I mean, we're seeing with whether it's the rise of privacy legislation or just breach of security of data or changes in how the top tech providers and browser controllers are changing their process for reaching customers. This is an inflection point in the history of both ad tech and MarTech. You hit the nail on the head with cookie deprecation, with Apple removing IDFA, changes to browsers, et cetera, we're at an interesting point. And by the way, we're also seeing an explosion of content sources and ability to reach customers that's unmatched in the history of advertising. So those two things are somewhat at odds. So whether we see the rise of connected television or digital out of home, you mentioned Web 3.0 and the opportunities that may present in metaverse, et cetera, it's an explosion of opportunity, but how do we continue to connect brands with customers and do so in a privacy compliant way? And that's really the big challenge we're facing. One of the things that I see is the rise of modeling or machine learning as a mechanism to help remove some of these barriers. If you think about the idea of one-to-one targeting, well, that's going to be less and less possible as we progress. So how am I still as a brand advertiser or as a targeted advertiser, how am I going to still reach the right audience with the right message in a world where I don't necessarily know who they are. And modeling is a really key way of achieving that goal and we're seeing that across a number of different angles. >> We've always talked about on the ad tech business for years, it's the behemoth of contextual and behavioral, those dynamics. And if you look at the content side of the business, you have now this new, massive source of new sources, blogging has been around for a long time, you got video, you got newsletters, you got all kinds of people, self-publishing, that's been around for a while, right? So you're seeing all these new sources. Trust is a big factor, but everyone wants to control their data. So this walled garden perpetuation of value, I got to control my data, but machine learning works best when you expose data, so this is kind of a paradox. Can you talk about the current challenge here and how to overcome it because you can't fight fashion, as they say, and we see people kind of going down this road as saying, data's a competitive advantage, but I got to figure out a way to keep it, own it, but also share it for the machine learning. What's your take on that? >> Yeah, I think first and foremost, if I may, I would just start with, it's super important to make that connection with the consumer in the first place. So you hit the nail on the head for advertisers and marketers today, the importance of gaining first party access to your customer and with permission and consent is paramount. And so just how you establish that connection point with trust and with very clear directive on how you're going to use the data has never been more important. So I would start there if I was a brand advertiser or a marketer, trying to figure out how I'm going to better connect with my consumers and get more first party data that I could leverage. So that's just building the scale of first party data to enable you to actually perform some of the types of approaches we'll discuss. The second thing I would say is that increasingly, the challenge exists with the exchange of the data itself. So if I'm a data control, if I own a set of first party data that I have consent with consumers to use, and I'm passing that data over to a third party, and that data is leaked, I'm still responsible for that data. Or if somebody wants to opt out of a communication and that opt out signal doesn't flow to the third party, I'm still liable, or at least from the consumer's perspective, I've provided a poor customer experience. And that's where we see the rise of the next generation, I call it of data clean rooms, the approaches that you're seeing, a number of customers take in terms of how they connect data without actually moving the data between two sources. And we're seeing that as certainly a mechanism by which you can preserve accessibility data, we call that federated data exchange or federated data clean rooms and I think you're seeing that from a number of different parties in the industry. >> That's awesome, I want to get into the data interoperability because we have a lot of startups presenting in this episode around that area, but why I got you here, you mentioned data clean room. Could you define for us, what is a federated data clean room, what is that about? >> Yeah, I would simply describe it as zero data movement in a privacy and secure environment. To be a little bit more explicit and detailed, it really is the idea that if I'm a party A and I want to exchange data with party B, how can I run a query for analytics or other purposes without actually moving data anywhere? Can I run a query that has accessibility to both parties, that has the security and the levels of aggregation that both parties agree to and then run the query and get those results sets back in a way that it actually facilitates business between the two parties. And we're seeing that expand with partners like Snowflake and InfoSum, even within Amazon itself, AWS, we have data sharing capabilities within Redshift and some of our other data-led capabilities. And we're just seeing explosion of demand and need for customers to be able to share data, but do it in a way where they still control the data and don't ever hand it over to a third party for execution. >> So if I understand this correctly, this is kind of an evolution to kind of take away the middleman, if you will, between parties that used to be historically the case, is that right? >> Yeah, I'd say this, the middleman still exists in many cases. If you think about joining two parties' data together, you still have the problem of the match key. How do I make sure that I get the broadest set of data to match up with the broadest set of data on the other side? So we have a number of partners that provide these types of services from LiveRamp, TransUnion, Experian, et cetera. So there's still a place for that so-called middleman in terms of helping to facilitate the transaction, but as a clean room itself, I think that term is becoming outdated in terms of a physical third party location, where you push data for analysis, that's controlled by a third party. >> Yeah, great clarification there. I want to get into this data interoperability because the benefits of AWS and cloud scales we've seen over the past decade and looking forward is, it's an API based economy. So APIs and microservices, cloud native stuff is going to be the key to integration. And so connecting people together is kind of what we're seeing as the trend. People are connecting their data, they're sharing code in open source. So there's an opportunity to connect the ecosystem of companies out there with their data. Can you share your view on this interoperability trend, why it's important and what's the impact to customers who want to go down this either automated or programmatic connection oriented way of connecting data. >> Never more important than it has been right now. I mean, if you think about the way we transact it and still too today do to a certain extent through cookie swaps and all sorts of crazy exchanges of data, those are going away at some point in the future; it could be a year from now, it could be later, but they're going away. And I think that that puts a great amount of pressure on the broad ecosystem of customers who transact for marketers, on behalf of marketers, both for advertising and marketing. And so data interoperability to me is how we think about providing that transactional layer between multiple parties so that they can continue to transact in a way that's meaningful and seamless, and frankly at lower cost and at greater scale than we've done in the past with less complexity. And so, we're seeing a number of changes in that regard, whether that's data sharing and data clean rooms or federated clean rooms, as we described earlier, whether that's the rise of next generation identity solutions, for example, the UID 2.0 Consortium, which is an effort to use hashed email addresses and other forms of identifiers to facilitate data exchange for the programmatic ecosystem. These are sort of evolutions based on this notion that the old world is going away, the new world is coming, and part of that is how do we connect data sources in a more seamless and frankly, efficient manner. >> It's almost interesting, it's almost flipped upside down, you had this walled garden mentality, I got to control my data, but now I have data interoperability. So you got to own and collect the data, but also share it. This is going to kind of change the paradigm around my identity platforms, attributions, audience, as audiences move around, and with cookies going away, this is going to require a new abstraction, a new way to do it. So you mentioned some of those standards. Is there a path in this evolution that changes it for the better? What's your view on this? What do you see happening? What's going to come out of this new wave? >> Yeah, my father was always fond of telling me, "The customer, my customers is my customer." And I like to put myself in the shoes of the Marc Pritchards of the world at Procter & Gamble and think, what do they want? And frankly, their requirements for data and for marketing have not changed over the last 20 years. It's, I want to reach the right customer at the right time, with the right message and I want to be able to measure it. In other words, summarizing, I want omnichannel execution with omnichannel measurement, and that's become increasingly difficult as you highlighted with the rise of the walled gardens and increasingly data living in silos. And so I think it's important that we, as an industry start to think about what's in the best interest of the one customer who brings virtually 100% of the dollars to this marketplace, which is the CMO and the CMO office. And how do we think about returning value to them in a way that is meaningful and actually drives its industry forward. And I think that's where the data operability piece becomes really important. How do we think about connecting the omnichannel channels of execution? How do we connect that with partners who run attribution offerings with machine learning or partners who provide augmentation or enrichment data such as third party data providers, or even connecting the buy side with the sell side in a more efficient manner? How do I make that connection between the CMO and the publisher in a more efficient and effective way? And these are all challenges facing us today. And I think at the foundational layer of that is how do we think about first of all, what data does the marketer have, what is the first party data? How do we help them ethically source and collect more of that data with proper consent? And then how do we help them join that data into a variety of data sources in a way that they can gain value from it. And that's where machine learning really comes into play. So whether that's the notion of audience expansion, whether that's looking for some sort of cohort analysis that helps with contextual advertising, whether that's the notion of a more of a modeled approach to attribution versus a one-to-one approach, all of those things I think are in play, as we think about returning value back to that customer of our customer. >> That's interesting, you broke down the customer needs in three areas; CMO office and staff, partners ISV software developers, and then third party services. Kind of all different needs, if you will, kind of tiered, kind of at the center of that's the user, the consumer who have the expectations. So it's interesting, you have the stakeholders, you laid out kind of those three areas as to customers, but the end user, the consumer, they have a preference, they kind of don't want to be locked into one thing. They want to move around, they want to download apps, they want to play on Reddit, they want to be on LinkedIn, they want to be all over the place, they don't want to get locked in. So you have now kind of this high velocity user behavior. How do you see that factoring in, because with cookies going away and kind of the convergence of offline-online, really becoming predominant, how do you know someone's paying attention to what and when attention and reputation. All these things seem complex. How do you make sense of it? >> Yeah, it's a great question. I think that the consumer as you said, finds a creepiness factor with a message that follows them around their various sources of engagement with content. So I think at first and foremost, there's the recognition by the brand that we need to be a little bit more thoughtful about how we interact with our customer and how we build that trust and that relationship with the customer. And that all starts with of course, opt-in process consent management center but it also includes how we communicate with them. What message are we actually putting in front of them? Is it meaningful, is it impactful? Does it drive value for the customer? I think we've seen a lot of studies, I won't recite them that state that most consumers do find value in targeted messaging, but I think they want it done correctly and there in lies the problem. So what does that mean by channel, especially when we lose the ability to look at that consumer interaction across those channels. And I think that's where we have to be a little bit more thoughtful with frankly, kind of going back to the beginning with contextual advertising, with advertising that perhaps has meaning, or has empathy with the consumer, perhaps resonates with the consumer in a different way than just a targeted message. And we're seeing that trend, we're seeing that trend both in television, connected television as those converge, but also as we see about connectivity with gaming and other sort of more nuanced channels. The other thing I would say is, I think there's a movement towards less interruptive advertising as well, which kind of removes a little bit of those barriers for the consumer and the brand to interact. And whether that be dynamic product placement, content optimization, or whether that be sponsorship type opportunities within digital. I think we're seeing an increased movement towards those types of executions, which I think will also provide value to both parties. >> Yeah, I think you nailed it there. I totally agree with you on the contextual targeting, I think that's a huge deal and that's proven over the years of providing benefit. People, they're trying to find what they're looking for, whether it's data to consume or a solution they want to buy. So I think that all kind of ties together. The question is these three stakeholders, the CMO office and staff you mentioned, and the software developers, apps, or walled gardens, and then like ad servers as they come together, have to have standards. And so, I think to me, I'm trying to squint through all the movement and the shifting plates that are going on in the industry and trying to figure out where are the dots connecting? And you've seen many cycles of innovation at the end of the day, it comes down to who can perform best for the end user, as well as the marketers and advertisers, so that balance. What's your view on this shift? It's going to land somewhere, it has to land in the right area, and the market's very efficient. I mean, this ad market's very efficient. >> Yeah, I mean, in some way, so from a standards perspective, I support and we interact extensively with the IB and other industry associations on privacy enhancing technologies and how we think about these next generations of connection points or identifiers to connect with consumers. But I'd say this, with respect to the CMO, and I mentioned the publisher earlier, I think over the last 10 years with the rise of programmatic, certainly we saw the power reside mostly with the CMO who was able to amass a large pool of cookies or purchase a large sort of cohort of customers with cookie based attributes and then execute against that. And so almost a blind fashion to the publisher, the publisher was sort of left to say, "Hey, here's an opportunity, do you want to buy it or not?" With no real reason why the marketer might be buying that customer? And I think that we're seeing a shift backwards towards the publisher and perhaps a healthy balance between the two. And so, I do believe that over time, that we're going to see publishers provide a lot more, what I might almost describe as mini walled gardens. So the ability, great publisher or a set of publishers to create a cohort of customers that can be targeted through programmatic or perhaps through programmatic guaranteed in a way that it's a balance between the two. And frankly thinking about that notion of federated data clean rooms, you can see an approach where publishers are able to share their first party data with a marketer's first party data, without either party feeling like they're giving up something or passing all their value over to the other. And I do believe we're going to see some significant technology changes over the next three to four years. That really rely on that interplay between the marketer and the publisher in a way that it helps both sides achieve their goals, and that is, increasing value back to the publisher in terms of higher CPMs, and of course, better reach and frequency controls for the marketer. >> I think you really brought up a big point there we can maybe follow up on, but I think this idea of publishers getting more control and power and value is an example of the market filling a void and the power log at the long tail, it's kind of a straight line. Then it's got the niche kind of communities, it's growing in the middle there, and I think the middle of the torso of that power law is the publishers because they have all the technology to measure the journeys and the click throughs and all this traffic going on their platform, but they just need to connect to someone else. >> Correct. >> That brings in the interoperability. So, as a publisher ourselves, we see that long tail getting really kind of fat in the middle where new brands are going to emerge, if they have audience. I mean, some podcasts have millions of users and some blogs are attracting massive audience, niche audiences that are growing. >> I would say, just look at the rise of what we might not have considered publishers in the past, but are certainly growing as publishers today. Customers like Instacart or Uber who are creating ad platforms or gaming, which of course has been an ad supported platform for some time, but is growing immensely. Retail as a platform, of course, amazon.com being one of the biggest retail platforms with advertising supported models, but we're seeing that growth across the board for retail customers. And I think that again, there's never been more opportunities to reach customers. We just have to do it the right way, in the way that it's not offensive to customers, not creepy, if you want to call it that, and also maximizes value for both parties and that be both the buy and the sell side. >> Yeah, everyone's a publisher and everyone's a media company. Everyone has their own news network, everyone has their own retail, it's a completely new world. Tim, thanks for coming on and sharing your perspective and insights on this key note, Tim Barnes, Global Director, General Manager of Advertiser and Market at AWS here with the Episode three of Season two of the AWS Startup Showcase. I'm John Furrier, thanks for watching. (upbeat music)

(upbeat music) >> The ascendancy of cloud and SAS has shown new light on how organizations think about, pay for, and value hardware. Once sought after skills for practitioners with expertise in hardware troubleshooting, configuring ports, tuning storage arrays, and maximizing server utilization has been superseded by demand for cloud architects, DevOps pros, developers with expertise in microservices, container, application development, and like. Even a company like Dell, the largest hardware company in enterprise tech touts that it has more software engineers than those working in hardware. Begs the question, is hardware going the way of Coball? Well, not likely. Software has to run on something, but the labor needed to deploy, and troubleshoot, and manage hardware infrastructure is shifting. At the same time, we've seen the value flow also shifting in hardware. Once a world dominated by X86 processors value is flowing to alternatives like Nvidia and arm based designs. Moreover, other componentry like NICs, accelerators, and storage controllers are becoming more advanced, integrated, and increasingly important. The question is, does it matter? And if so, why does it matter and to whom? What does it mean to customers, workloads, OEMs, and the broader society? Hello and welcome to this week's Wikibon theCUBE Insights powered by ETR. In this breaking analysis, we've organized a special power panel of industry analysts and experts to address the question, does hardware still matter? Allow me to introduce the panel. Bob O'Donnell is president and chief analyst at TECHnalysis Research. Zeus Kerravala is the founder and principal analyst at ZK Research. David Nicholson is a CTO and tech expert. Keith Townson is CEO and founder of CTO Advisor. And Marc Staimer is the chief dragon slayer at Dragon Slayer Consulting and oftentimes a Wikibon contributor. Guys, welcome to theCUBE. Thanks so much for spending some time here. >> Good to be here. >> Thanks. >> Thanks for having us. >> Okay before we get into it, I just want to bring up some data from ETR. This is a survey that ETR does every quarter. It's a survey of about 1200 to 1500 CIOs and IT buyers and I'm showing a subset of the taxonomy here. This XY axis and the vertical axis is something called net score. That's a measure of spending momentum. It's essentially the percentage of customers that are spending more on a particular area than those spending less. You subtract the lesses from the mores and you get a net score. Anything the horizontal axis is pervasion in the data set. Sometimes they call it market share. It's not like IDC market share. It's just the percentage of activity in the data set as a percentage of the total. That red 40% line, anything over that is considered highly elevated. And for the past, I don't know, eight to 12 quarters, the big four have been AI and machine learning, containers, RPA and cloud and cloud of course is very impressive because not only is it elevated in the vertical access, but you know it's very highly pervasive on the horizontal. So what I've done is highlighted in red that historical hardware sector. The server, the storage, the networking, and even PCs despite the work from home are depressed in relative terms. And of course, data center collocation services. Okay so you're seeing obviously hardware is not... People don't have the spending momentum today that they used to. They've got other priorities, et cetera, but I want to start and go kind of around the horn with each of you, what is the number one trend that each of you sees in hardware and why does it matter? Bob O'Donnell, can you please start us off? >> Sure Dave, so look, I mean, hardware is incredibly important and one comment first I'll make on that slide is let's not forget that hardware, even though it may not be growing, the amount of money spent on hardware continues to be very, very high. It's just a little bit more stable. It's not as subject to big jumps as we see certainly in other software areas. But look, the important thing that's happening in hardware is the diversification of the types of chip architectures we're seeing and how and where they're being deployed, right? You refer to this in your opening. We've moved from a world of x86 CPUs from Intel and AMD to things like obviously GPUs, DPUs. We've got VPU for, you know, computer vision processing. We've got AI-dedicated accelerators, we've got all kinds of other network acceleration tools and AI-powered tools. There's an incredible diversification of these chip architectures and that's been happening for a while but now we're seeing them more widely deployed and it's being done that way because workloads are evolving. The kinds of workloads that we're seeing in some of these software areas require different types of compute engines than traditionally we've had. The other thing is (coughs), excuse me, the power requirements based on where geographically that compute happens is also evolving. This whole notion of the edge, which I'm sure we'll get into a little bit more detail later is driven by the fact that where the compute actually sits closer to in theory the edge and where edge devices are, depending on your definition, changes the power requirements. It changes the kind of connectivity that connects the applications to those edge devices and those applications. So all of those things are being impacted by this growing diversity in chip architectures. And that's a very long-term trend that I think we're going to continue to see play out through this decade and well into the 2030s as well. >> Excellent, great, great points. Thank you, Bob. Zeus up next, please. >> Yeah, and I think the other thing when you look at this chart to remember too is, you know, through the pandemic and the work from home period a lot of companies did put their office modernization projects on hold and you heard that echoed, you know, from really all the network manufacturers anyways. They always had projects underway to upgrade networks. They put 'em on hold. Now that people are starting to come back to the office, they're looking at that now. So we might see some change there, but Bob's right. The size of those market are quite a bit different. I think the other big trend here is the hardware companies, at least in the areas that I look at networking are understanding now that it's a combination of hardware and software and silicon that works together that creates that optimum type of performance and experience, right? So some things are best done in silicon. Some like data forwarding and things like that. Historically when you look at the way network devices were built, you did everything in hardware. You configured in hardware, they did all the data for you, and did all the management. And that's been decoupled now. So more and more of the control element has been placed in software. A lot of the high-performance things, encryption, and as I mentioned, data forwarding, packet analysis, stuff like that is still done in hardware, but not everything is done in hardware. And so it's a combination of the two. I think, for the people that work with the equipment as well, there's been more shift to understanding how to work with software. And this is a mistake I think the industry made for a while is we had everybody convinced they had to become a programmer. It's really more a software power user. Can you pull things out of software? Can you through API calls and things like that. But I think the big frame here is, David, it's a combination of hardware, software working together that really make a difference. And you know how much you invest in hardware versus software kind of depends on the performance requirements you have. And I'll talk about that later but that's really the big shift that's happened here. It's the vendors that figured out how to optimize performance by leveraging the best of all of those. >> Excellent. You guys both brought up some really good themes that we can tap into Dave Nicholson, please. >> Yeah, so just kind of picking up where Bob started off. Not only are we seeing the rise of a variety of CPU designs, but I think increasingly the connectivity that's involved from a hardware perspective, from a kind of a server or service design perspective has become increasingly important. I think we'll get a chance to look at this in more depth a little bit later but when you look at what happens on the motherboard, you know we're not in so much a CPU-centric world anymore. Various application environments have various demands and you can meet them by using a variety of components. And it's extremely significant when you start looking down at the component level. It's really important that you optimize around those components. So I guess my summary would be, I think we are moving out of the CPU-centric hardware model into more of a connectivity-centric model. We can talk more about that later. >> Yeah, great. And thank you, David, and Keith Townsend I really interested in your perspectives on this. I mean, for years you worked in a data center surrounded by hardware. Now that we have the software defined data center, please chime in here. >> Well, you know, I'm going to dig deeper into that software-defined data center nature of what's happening with hardware. Hardware is meeting software infrastructure as code is a thing. What does that code look like? We're still trying to figure out but servicing up these capabilities that the previous analysts have brought up, how do I ensure that I can get the level of services needed for the applications that I need? Whether they're legacy, traditional data center, workloads, AI ML, workloads, workloads at the edge. How do I codify that and consume that as a service? And hardware vendors are figuring this out. HPE, the big push into GreenLake as a service. Dale now with Apex taking what we need, these bare bone components, moving it forward with DDR five, six CXL, et cetera, and surfacing that as cold or as services. This is a very tough problem. As we transition from consuming a hardware-based configuration to this infrastructure as cold paradigm shift. >> Yeah, programmable infrastructure, really attacking that sort of labor discussion that we were having earlier, okay. Last but not least Marc Staimer, please. >> Thanks, Dave. My peers raised really good points. I agree with most of them, but I'm going to disagree with the title of this session, which is, does hardware matter? It absolutely matters. You can't run software on the air. You can't run it in an ephemeral cloud, although there's the technical cloud and that's a different issue. The cloud is kind of changed everything. And from a market perspective in the 40 plus years I've been in this business, I've seen this perception that hardware has to go down in price every year. And part of that was driven by Moore's law. And we're coming to, let's say a lag or an end, depending on who you talk to Moore's law. So we're not doubling our transistors every 18 to 24 months in a chip and as a result of that, there's been a higher emphasis on software. From a market perception, there's no penalty. They don't put the same pressure on software from the market to reduce the cost every year that they do on hardware, which kind of bass ackwards when you think about it. Hardware costs are fixed. Software costs tend to be very low. It's kind of a weird thing that we do in the market. And what's changing is we're now starting to treat hardware like software from an OPEX versus CapEx perspective. So yes, hardware matters. And we'll talk about that more in length. >> You know, I want to follow up on that. And I wonder if you guys have a thought on this, Bob O'Donnell, you and I have talked about this a little bit. Marc, you just pointed out that Moore's laws could have waning. Pat Gelsinger recently at their investor meeting said that he promised that Moore's law is alive and well. And the point I made in breaking analysis was okay, great. You know, Pat said, doubling transistors every 18 to 24 months, let's say that Intel can do that. Even though we know it's waning somewhat. Look at the M1 Ultra from Apple (chuckles). In about 15 months increased transistor density on their package by 6X. So to your earlier point, Bob, we have this sort of these alternative processors that are really changing things. And to Dave Nicholson's point, there's a whole lot of supporting components as well. Do you have a comment on that, Bob? >> Yeah, I mean, it's a great point, Dave. And one thing to bear in mind as well, not only are we seeing a diversity of these different chip architectures and different types of components as a number of us have raised the other big point and I think it was Keith that mentioned it. CXL and interconnect on the chip itself is dramatically changing it. And a lot of the more interesting advances that are going to continue to drive Moore's law forward in terms of the way we think about performance, if perhaps not number of transistors per se, is the interconnects that become available. You're seeing the development of chiplets or tiles, people use different names, but the idea is you can have different components being put together eventually in sort of a Lego block style. And what that's also going to allow, not only is that going to give interesting performance possibilities 'cause of the faster interconnect. So you can share, have shared memory between things which for big workloads like AI, huge data sets can make a huge difference in terms of how you talk to memory over a network connection, for example, but not only that you're going to see more diversity in the types of solutions that can be built. So we're going to see even more choices in hardware from a silicon perspective because you'll be able to piece together different elements. And oh, by the way, the other benefit of that is we've reached a point in chip architectures where not everything benefits from being smaller. We've been so focused and so obsessed when it comes to Moore's law, to the size of each individual transistor and yes, for certain architecture types, CPUs and GPUs in particular, that's absolutely true, but we've already hit the point where things like RF for 5g and wifi and other wireless technologies and a whole bunch of other things actually don't get any better with a smaller transistor size. They actually get worse. So the beauty of these chiplet architectures is you could actually combine different chip manufacturing sizes. You know you hear about four nanometer and five nanometer along with 14 nanometer on a single chip, each one optimized for its specific application yet together, they can give you the best of all worlds. And so we're just at the very beginning of that era, which I think is going to drive a ton of innovation. Again, gets back to my comment about different types of devices located geographically different places at the edge, in the data center, you know, in a private cloud versus a public cloud. All of those things are going to be impacted and there'll be a lot more options because of this silicon diversity and this interconnect diversity that we're just starting to see. >> Yeah, David. David Nicholson's got a graphic on that. They're going to show later. Before we do that, I want to introduce some data. I actually want to ask Keith to comment on this before we, you know, go on. This next slide is some data from ETR that shows the percent of customers that cited difficulty procuring hardware. And you can see the red is they had significant issues and it's most pronounced in laptops and networking hardware on the far right-hand side, but virtually all categories, firewalls, peripheral servers, storage are having moderately difficult procurement issues. That's the sort of pinkish or significant challenges. So Keith, I mean, what are you seeing with your customers in the hardware supply chains and bottlenecks? And you know we're seeing it with automobiles and appliances but so it goes beyond IT. The semiconductor, you know, challenges. What's been the impact on the buyer community and society and do you have any sense as to when it will subside? >> You know, I was just asked this question yesterday and I'm feeling the pain. People question, kind of a side project within the CTO advisor, we built a hybrid infrastructure, traditional IT data center that we're walking with the traditional customer and modernizing that data center. So it was, you know, kind of a snapshot of time in 2016, 2017, 10 gigabit, ARISTA switches, some older Dell's 730 XD switches, you know, speeds and feeds. And we said we would modern that with the latest Intel stack and connected to the public cloud and then the pandemic hit and we are experiencing a lot of the same challenges. I thought we'd easily migrate from 10 gig networking to 25 gig networking path that customers are going on. The 10 gig network switches that I bought used are now double the price because you can't get legacy 10 gig network switches because all of the manufacturers are focusing on the more profitable 25 gig for capacity, even the 25 gig switches. And we're focused on networking right now. It's hard to procure. We're talking about nine to 12 months or more lead time. So we're seeing customers adjust by adopting cloud. But if you remember early on in the pandemic, Microsoft Azure kind of gated customers that didn't have a capacity agreement. So customers are keeping an eye on that. There's a desire to abstract away from the underlying vendor to be able to control or provision your IT services in a way that we do with VMware VP or some other virtualization technology where it doesn't matter who can get me the hardware, they can just get me the hardware because it's critically impacting projects and timelines. >> So that's a great setup Zeus for you with Keith mentioned the earlier the software-defined data center with software-defined networking and cloud. Do you see a day where networking hardware is monetized and it's all about the software, or are we there already? >> No, we're not there already. And I don't see that really happening any time in the near future. I do think it's changed though. And just to be clear, I mean, when you look at that data, this is saying customers have had problems procuring the equipment, right? And there's not a network vendor out there. I've talked to Norman Rice at Extreme, and I've talked to the folks at Cisco and ARISTA about this. They all said they could have had blowout quarters had they had the inventory to ship. So it's not like customers aren't buying this anymore. Right? I do think though, when it comes to networking network has certainly changed some because there's a lot more controls as I mentioned before that you can do in software. And I think the customers need to start thinking about the types of hardware they buy and you know, where they're going to use it and, you know, what its purpose is. Because I've talked to customers that have tried to run software and commodity hardware and where the performance requirements are very high and it's bogged down, right? It just doesn't have the horsepower to run it. And, you know, even when you do that, you have to start thinking of the components you use. The NICs you buy. And I've talked to customers that have simply just gone through the process replacing a NIC card and a commodity box and had some performance problems and, you know, things like that. So if agility is more important than performance, then by all means try running software on commodity hardware. I think that works in some cases. If performance though is more important, that's when you need that kind of turnkey hardware system. And I've actually seen more and more customers reverting back to that model. In fact, when you talk to even some startups I think today about when they come to market, they're delivering things more on appliances because that's what customers want. And so there's this kind of app pivot this pendulum of agility and performance. And if performance absolutely matters, that's when you do need to buy these kind of turnkey, prebuilt hardware systems. If agility matters more, that's when you can go more to software, but the underlying hardware still does matter. So I think, you know, will we ever have a day where you can just run it on whatever hardware? Maybe but I'll long be retired by that point. So I don't care. >> Well, you bring up a good point Zeus. And I remember the early days of cloud, the narrative was, oh, the cloud vendors. They don't use EMC storage, they just run on commodity storage. And then of course, low and behold, you know, they've trot out James Hamilton to talk about all the custom hardware that they were building. And you saw Google and Microsoft follow suit. >> Well, (indistinct) been falling for this forever. Right? And I mean, all the way back to the turn of the century, we were calling for the commodity of hardware. And it's never really happened because you can still drive. As long as you can drive innovation into it, customers will always lean towards the innovation cycles 'cause they get more features faster and things. And so the vendors have done a good job of keeping that cycle up but it'll be a long time before. >> Yeah, and that's why you see companies like Pure Storage. A storage company has 69% gross margins. All right. I want to go jump ahead. We're going to bring up the slide four. I want to go back to something that Bob O'Donnell was talking about, the sort of supporting act. The diversity of silicon and we've marched to the cadence of Moore's law for decades. You know, we asked, you know, is Moore's law dead? We say it's moderating. Dave Nicholson. You want to talk about those supporting components. And you shared with us a slide that shift. You call it a shift from a processor-centric world to a connect-centric world. What do you mean by that? And let's bring up slide four and you can talk to that. >> Yeah, yeah. So first, I want to echo this sentiment that the question does hardware matter is sort of the answer is of course it matters. Maybe the real question should be, should you care about it? And the answer to that is it depends who you are. If you're an end user using an application on your mobile device, maybe you don't care how the architecture is put together. You just care that the service is delivered but as you back away from that and you get closer and closer to the source, someone needs to care about the hardware and it should matter. Why? Because essentially what hardware is doing is it's consuming electricity and dollars and the more efficiently you can configure hardware, the more bang you're going to get for your buck. So it's not only a quantitative question in terms of how much can you deliver? But it also ends up being a qualitative change as capabilities allow for things we couldn't do before, because we just didn't have the aggregate horsepower to do it. So this chart actually comes out of some performance tests that were done. So it happens to be Dell servers with Broadcom components. And the point here was to peel back, you know, peel off the top of the server and look at what's in that server, starting with, you know, the PCI interconnect. So PCIE gen three, gen four, moving forward. What are the effects on from an interconnect versus on performance application performance, translating into new orders per minute, processed per dollar, et cetera, et cetera? If you look at the advances in CPU architecture mapped against the advances in interconnect and storage subsystem performance, you can see that CPU architecture is sort of lagging behind in a way. And Bob mentioned this idea of tiling and all of the different ways to get around that. When we do performance testing, we can actually peg CPUs, just running the performance tests without any actual database environments working. So right now we're at this sort of imbalance point where you have to make sure you design things properly to get the most bang per kilowatt hour of power per dollar input. So the key thing here what this is highlighting is just as a very specific example, you take a card that's designed as a gen three PCIE device, and you plug it into a gen four slot. Now the card is the bottleneck. You plug a gen four card into a gen four slot. Now the gen four slot is the bottleneck. So we're constantly chasing these bottlenecks. Someone has to be focused on that from an architectural perspective, it's critically important. So there's no question that it matters. But of course, various people in this food chain won't care where it comes from. I guess a good analogy might be, where does our food come from? If I get a steak, it's a pink thing wrapped in plastic, right? Well, there are a lot of inputs that a lot of people have to care about to get that to me. Do I care about all of those things? No. Are they important? They're critically important. >> So, okay. So all I want to get to the, okay. So what does this all mean to customers? And so what I'm hearing from you is to balance a system it's becoming, you know, more complicated. And I kind of been waiting for this day for a long time, because as we all know the bottleneck was always the spinning disc, the last mechanical. So people who wrote software knew that when they were doing it right, the disc had to go and do stuff. And so they were doing other things in the software. And now with all these new interconnects and flash and things like you could do atomic rights. And so that opens up new software possibilities and combine that with alternative processes. But what's the so what on this to the customer and the application impact? Can anybody address that? >> Yeah, let me address that for a moment. I want to leverage some of the things that Bob said, Keith said, Zeus said, and David said, yeah. So I'm a bit of a contrarian in some of this. For example, on the chip side. As the chips get smaller, 14 nanometer, 10 nanometer, five nanometer, soon three nanometer, we talk about more cores, but the biggest problem on the chip is the interconnect from the chip 'cause the wires get smaller. People don't realize in 2004 the latency on those wires in the chips was 80 picoseconds. Today it's 1300 picoseconds. That's on the chip. This is why they're not getting faster. So we maybe getting a little bit slowing down in Moore's law. But even as we kind of conquer that you still have the interconnect problem and the interconnect problem goes beyond the chip. It goes within the system, composable architectures. It goes to the point where Keith made, ultimately you need a hybrid because what we're seeing, what I'm seeing and I'm talking to customers, the biggest issue they have is moving data. Whether it be in a chip, in a system, in a data center, between data centers, moving data is now the biggest gating item in performance. So if you want to move it from, let's say your transactional database to your machine learning, it's the bottleneck, it's moving the data. And so when you look at it from a distributed environment, now you've got to move the compute to the data. The only way to get around these bottlenecks today is to spend less time in trying to move the data and more time in taking the compute, the software, running on hardware closer to the data. Go ahead. >> So is this what you mean when Nicholson was talking about a shift from a processor centric world to a connectivity centric world? You're talking about moving the bits across all the different components, not having the processor you're saying is essentially becoming the bottleneck or the memory, I guess. >> Well, that's one of them and there's a lot of different bottlenecks, but it's the data movement itself. It's moving away from, wait, why do we need to move the data? Can we move the compute, the processing closer to the data? Because if we keep them separate and this has been a trend now where people are moving processing away from it. It's like the edge. I think it was Zeus or David. You were talking about the edge earlier. As you look at the edge, who defines the edge, right? Is the edge a closet or is it a sensor? If it's a sensor, how do you do AI at the edge? When you don't have enough power, you don't have enough computable. People were inventing chips to do that. To do all that at the edge, to do AI within the sensor, instead of moving the data to a data center or a cloud to do the processing. Because the lag in latency is always limited by speed of light. How fast can you move the electrons? And all this interconnecting, all the processing, and all the improvement we're seeing in the PCIE bus from three, to four, to five, to CXL, to a higher bandwidth on the network. And that's all great but none of that deals with the speed of light latency. And that's an-- Go ahead. >> You know Marc, no, I just want to just because what you're referring to could be looked at at a macro level, which I think is what you're describing. You can also look at it at a more micro level from a systems design perspective, right? I'm going to be the resident knuckle dragging hardware guy on the panel today. But it's exactly right. You moving compute closer to data includes concepts like peripheral cards that have built in intelligence, right? So again, in some of this testing that I'm referring to, we saw dramatic improvements when you basically took the horsepower instead of using the CPU horsepower for the like IO. Now you have essentially offload engines in the form of storage controllers, rate controllers, of course, for ethernet NICs, smart NICs. And so when you can have these sort of offload engines and we've gone through these waves over time. People think, well, wait a minute, raid controller and NVMe? You know, flash storage devices. Does that make sense? It turns out it does. Why? Because you're actually at a micro level doing exactly what you're referring to. You're bringing compute closer to the data. Now, closer to the data meaning closer to the data storage subsystem. It doesn't solve the macro issue that you're referring to but it is important. Again, going back to this idea of system design optimization, always chasing the bottleneck, plugging the holes. Someone needs to do that in this value chain in order to get the best value for every kilowatt hour of power and every dollar. >> Yeah. >> Well this whole drive performance has created some really interesting architectural designs, right? Like Nickelson, the rise of the DPU right? Brings more processing power into systems that already had a lot of processing power. There's also been some really interesting, you know, kind of innovation in the area of systems architecture too. If you look at the way Nvidia goes to market, their drive kit is a prebuilt piece of hardware, you know, optimized for self-driving cars, right? They partnered with Pure Storage and ARISTA to build that AI-ready infrastructure. I remember when I talked to Charlie Giancarlo, the CEO of Pure about when the three companies rolled that out. He said, "Look, if you're going to do AI, "you need good store. "You need fast storage, fast processor and fast network." And so for customers to be able to put that together themselves was very, very difficult. There's a lot of software that needs tuning as well. So the three companies partner together to create a fully integrated turnkey hardware system with a bunch of optimized software that runs on it. And so in that case, in some ways the hardware was leading the software innovation. And so, the variety of different architectures we have today around hardware has really exploded. And I think it, part of the what Bob brought up at the beginning about the different chip design. >> Yeah, Bob talked about that earlier. Bob, I mean, most AI today is modeling, you know, and a lot of that's done in the cloud and it looks from my standpoint anyway that the future is going to be a lot of AI inferencing at the edge. And that's a radically different architecture, Bob, isn't it? >> It is, it's a completely different architecture. And just to follow up on a couple points, excellent conversation guys. Dave talked about system architecture and really this that's what this boils down to, right? But it's looking at architecture at every level. I was talking about the individual different components the new interconnect methods. There's this new thing called UCIE universal connection. I forget what it stands answer for, but it's a mechanism for doing chiplet architectures, but then again, you have to take it up to the system level, 'cause it's all fine and good. If you have this SOC that's tuned and optimized, but it has to talk to the rest of the system. And that's where you see other issues. And you've seen things like CXL and other interconnect standards, you know, and nobody likes to talk about interconnect 'cause it's really wonky and really technical and not that sexy, but at the end of the day it's incredibly important exactly. To the other points that were being raised like mark raised, for example, about getting that compute closer to where the data is and that's where again, a diversity of chip architectures help and exactly to your last comment there Dave, putting that ability in an edge device is really at the cutting edge of what we're seeing on a semiconductor design and the ability to, for example, maybe it's an FPGA, maybe it's a dedicated AI chip. It's another kind of chip architecture that's being created to do that inferencing on the edge. Because again, it's that the cost and the challenges of moving lots of data, whether it be from say a smartphone to a cloud-based application or whether it be from a private network to a cloud or any other kinds of permutations we can think of really matters. And the other thing is we're tackling bigger problems. So architecturally, not even just architecturally within a system, but when we think about DPUs and the sort of the east west data center movement conversation that we hear Nvidia and others talk about, it's about combining multiple sets of these systems to function together more efficiently again with even bigger sets of data. So really is about tackling where the processing is needed, having the interconnect and the ability to get where the data you need to the right place at the right time. And because those needs are diversifying, we're just going to continue to see an explosion of different choices and options, which is going to make hardware even more essential I would argue than it is today. And so I think what we're going to see not only does hardware matter, it's going to matter even more in the future than it does now. >> Great, yeah. Great discussion, guys. I want to bring Keith back into the conversation here. Keith, if your main expertise in tech is provisioning LUNs, you probably you want to look for another job. So maybe clearly hardware matters, but with software defined everything, do people with hardware expertise matter outside of for instance, component manufacturers or cloud companies? I mean, VMware certainly changed the dynamic in servers. Dell just spun off its most profitable asset and VMware. So it obviously thinks hardware can stand alone. How does an enterprise architect view the shift to software defined hyperscale cloud and how do you see the shifting demand for skills in enterprise IT? >> So I love the question and I'll take a different view of it. If you're a data analyst and your primary value add is that you do ETL transformation, talk to a CDO, a chief data officer over midsize bank a little bit ago. He said 80% of his data scientists' time is done on ETL. Super not value ad. He wants his data scientists to do data science work. Chances are if your only value is that you do LUN provisioning, then you probably don't have a job now. The technologies have gotten much more intelligent. As infrastructure pros, we want to give infrastructure pros the opportunities to shine and I think the software defined nature and the automation that we're seeing vendors undertake, whether it's Dell, HP, Lenovo take your pick that Pure Storage, NetApp that are doing the automation and the ML needed so that these practitioners don't spend 80% of their time doing LUN provisioning and focusing on their true expertise, which is ensuring that data is stored. Data is retrievable, data's protected, et cetera. I think the shift is to focus on that part of the job that you're ensuring no matter where the data's at, because as my data is spread across the enterprise hybrid different types, you know, Dave, you talk about the super cloud a lot. If my data is in the super cloud, protecting that data and securing that data becomes much more complicated when than when it was me just procuring or provisioning LUNs. So when you say, where should the shift be, or look be, you know, focusing on the real value, which is making sure that customers can access data, can recover data, can get data at performance levels that they need within the price point. They need to get at those datasets and where they need it. We talked a lot about where they need out. One last point about this interconnecting. I have this vision and I think we all do of composable infrastructure. This idea that scaled out does not solve every problem. The cloud can give me infinite scale out. Sometimes I just need a single OS with 64 terabytes of RAM and 204 GPUs or GPU instances that single OS does not exist today. And the opportunity is to create composable infrastructure so that we solve a lot of these problems that just simply don't scale out. >> You know, wow. So many interesting points there. I had just interviewed Zhamak Dehghani, who's the founder of Data Mesh last week. And she made a really interesting point. She said, "Think about, we have separate stacks. "We have an application stack and we have "a data pipeline stack and the transaction systems, "the transaction database, we extract data from that," to your point, "We ETL it in, you know, it takes forever. "And then we have this separate sort of data stack." If we're going to inject more intelligence and data and AI into applications, those two stacks, her contention is they have to come together. And when you think about, you know, super cloud bringing compute to data, that was what Haduck was supposed to be. It ended up all sort of going into a central location, but it's almost a rhetorical question. I mean, it seems that that necessitates new thinking around hardware architectures as it kind of everything's the edge. And the other point is to your point, Keith, it's really hard to secure that. So when you can think about offloads, right, you've heard the stats, you know, Nvidia talks about it. Broadcom talks about it that, you know, that 30%, 25 to 30% of the CPU cycles are wasted on doing things like storage offloads, or networking or security. It seems like maybe Zeus you have a comment on this. It seems like new architectures need to come other to support, you know, all of that stuff that Keith and I just dispute. >> Yeah, and by the way, I do want to Keith, the question you just asked. Keith, it's the point I made at the beginning too about engineers do need to be more software-centric, right? They do need to have better software skills. In fact, I remember talking to Cisco about this last year when they surveyed their engineer base, only about a third of 'em had ever made an API call, which you know that that kind of shows this big skillset change, you know, that has to come. But on the point of architectures, I think the big change here is edge because it brings in distributed compute models. Historically, when you think about compute, even with multi-cloud, we never really had multi-cloud. We'd use multiple centralized clouds, but compute was always centralized, right? It was in a branch office, in a data center, in a cloud. With edge what we creates is the rise of distributed computing where we'll have an application that actually accesses different resources and at different edge locations. And I think Marc, you were talking about this, like the edge could be in your IoT device. It could be your campus edge. It could be cellular edge, it could be your car, right? And so we need to start thinkin' about how our applications interact with all those different parts of that edge ecosystem, you know, to create a single experience. The consumer apps, a lot of consumer apps largely works that way. If you think of like app like Uber, right? It pulls in information from all kinds of different edge application, edge services. And, you know, it creates pretty cool experience. We're just starting to get to that point in the business world now. There's a lot of security implications and things like that, but I do think it drives more architectural decisions to be made about how I deploy what data where and where I do my processing, where I do my AI and things like that. It actually makes the world more complicated. In some ways we can do so much more with it, but I think it does drive us more towards turnkey systems, at least initially in order to, you know, ensure performance and security. >> Right. Marc, I wanted to go to you. You had indicated to me that you wanted to chat about this a little bit. You've written quite a bit about the integration of hardware and software. You know, we've watched Oracle's move from, you know, buying Sun and then basically using that in a highly differentiated approach. Engineered systems. What's your take on all that? I know you also have some thoughts on the shift from CapEx to OPEX chime in on that. >> Sure. When you look at it, there are advantages to having one vendor who has the software and hardware. They can synergistically make them work together that you can't do in a commodity basis. If you own the software and somebody else has the hardware, I'll give you an example would be Oracle. As you talked about with their exit data platform, they literally are leveraging microcode in the Intel chips. And now in AMD chips and all the way down to Optane, they make basically AMD database servers work with Optane memory PMM in their storage systems, not MVME, SSD PMM. I'm talking about the cards itself. So there are advantages you can take advantage of if you own the stack, as you were putting out earlier, Dave, of both the software and the hardware. Okay, that's great. But on the other side of that, that tends to give you better performance, but it tends to cost a little more. On the commodity side it costs less but you get less performance. What Zeus had said earlier, it depends where you're running your application. How much performance do you need? What kind of performance do you need? One of the things about moving to the edge and I'll get to the OPEX CapEx in a second. One of the issues about moving to the edge is what kind of processing do you need? If you're running in a CCTV camera on top of a traffic light, how much power do you have? How much cooling do you have that you can run this? And more importantly, do you have to take the data you're getting and move it somewhere else and get processed and the information is sent back? I mean, there are companies out there like Brain Chip that have developed AI chips that can run on the sensor without a CPU. Without any additional memory. So, I mean, there's innovation going on to deal with this question of data movement. There's companies out there like Tachyon that are combining GPUs, CPUs, and DPUs in a single chip. Think of it as super composable architecture. They're looking at being able to do more in less. On the OPEX and CapEx issue. >> Hold that thought, hold that thought on the OPEX CapEx, 'cause we're running out of time and maybe you can wrap on that. I just wanted to pick up on something you said about the integrated hardware software. I mean, other than the fact that, you know, Michael Dell unlocked whatever $40 billion for himself and Silverlake, I was always a fan of a spin in with VMware basically become the Oracle of hardware. Now I know it would've been a nightmare for the ecosystem and culturally, they probably would've had a VMware brain drain, but what does anybody have any thoughts on that as a sort of a thought exercise? I was always a fan of that on paper. >> I got to eat a little crow. I did not like the Dale VMware acquisition for the industry in general. And I think it hurt the industry in general, HPE, Cisco walked away a little bit from that VMware relationship. But when I talked to customers, they loved it. You know, I got to be honest. They absolutely loved the integration. The VxRail, VxRack solution exploded. Nutanix became kind of a afterthought when it came to competing. So that spin in, when we talk about the ability to innovate and the ability to create solutions that you just simply can't create because you don't have the full stack. Dell was well positioned to do that with a potential span in of VMware. >> Yeah, we're going to be-- Go ahead please. >> Yeah, in fact, I think you're right, Keith, it was terrible for the industry. Great for Dell. And I remember talking to Chad Sakac when he was running, you know, VCE, which became Rack and Rail, their ability to stay in lockstep with what VMware was doing. What was the number one workload running on hyperconverged forever? It was VMware. So their ability to remain in lockstep with VMware gave them a huge competitive advantage. And Dell came out of nowhere in, you know, the hyper-converged market and just started taking share because of that relationship. So, you know, this sort I guess it's, you know, from a Dell perspective I thought it gave them a pretty big advantage that they didn't really exploit across their other properties, right? Networking and service and things like they could have given the dominance that VMware had. From an industry perspective though, I do think it's better to have them be coupled. So. >> I agree. I mean, they could. I think they could have dominated in super cloud and maybe they would become the next Oracle where everybody hates 'em, but they kick ass. But guys. We got to wrap up here. And so what I'm going to ask you is I'm going to go and reverse the order this time, you know, big takeaways from this conversation today, which guys by the way, I can't thank you enough phenomenal insights, but big takeaways, any final thoughts, any research that you're working on that you want highlight or you know, what you look for in the future? Try to keep it brief. We'll go in reverse order. Maybe Marc, you could start us off please. >> Sure, on the research front, I'm working on a total cost of ownership of an integrated database analytics machine learning versus separate services. On the other aspect that I would wanted to chat about real quickly, OPEX versus CapEx, the cloud changed the market perception of hardware in the sense that you can use hardware or buy hardware like you do software. As you use it, pay for what you use in arrears. The good thing about that is you're only paying for what you use, period. You're not for what you don't use. I mean, it's compute time, everything else. The bad side about that is you have no predictability in your bill. It's elastic, but every user I've talked to says every month it's different. And from a budgeting perspective, it's very hard to set up your budget year to year and it's causing a lot of nightmares. So it's just something to be aware of. From a CapEx perspective, you have no more CapEx if you're using that kind of base system but you lose a certain amount of control as well. So ultimately that's some of the issues. But my biggest point, my biggest takeaway from this is the biggest issue right now that everybody I talk to in some shape or form it comes down to data movement whether it be ETLs that you talked about Keith or other aspects moving it between hybrid locations, moving it within a system, moving it within a chip. All those are key issues. >> Great, thank you. Okay, CTO advisor, give us your final thoughts. >> All right. Really, really great commentary. Again, I'm going to point back to us taking the walk that our customers are taking, which is trying to do this conversion of all primary data center to a hybrid of which I have this hard earned philosophy that enterprise IT is additive. When we add a service, we rarely subtract a service. So the landscape and service area what we support has to grow. So our research focuses on taking that walk. We are taking a monolithic application, decomposing that to containers, and putting that in a public cloud, and connecting that back private data center and telling that story and walking that walk with our customers. This has been a super enlightening panel. >> Yeah, thank you. Real, real different world coming. David Nicholson, please. >> You know, it really hearkens back to the beginning of the conversation. You talked about momentum in the direction of cloud. I'm sort of spending my time under the hood, getting grease under my fingernails, focusing on where still the lions share of spend will be in coming years, which is OnPrem. And then of course, obviously data center infrastructure for cloud but really diving under the covers and helping folks understand the ramifications of movement between generations of CPU architecture. I know we all know Sapphire Rapids pushed into the future. When's the next Intel release coming? Who knows? We think, you know, in 2023. There have been a lot of people standing by from a practitioner's standpoint asking, well, what do I do between now and then? Does it make sense to upgrade bits and pieces of hardware or go from a last generation to a current generation when we know the next generation is coming? And so I've been very, very focused on looking at how these connectivity components like rate controllers and NICs. I know it's not as sexy as talking about cloud but just how these opponents completely change the game and actually can justify movement from say a 14th-generation architecture to a 15th-generation architecture today, even though gen 16 is coming, let's say 12 months from now. So that's where I am. Keep my phone number in the Rolodex. I literally reference Rolodex intentionally because like I said, I'm in there under the hood and it's not as sexy. But yeah, so that's what I'm focused on Dave. >> Well, you know, to paraphrase it, maybe derivative paraphrase of, you know, Larry Ellison's rant on what is cloud? It's operating systems and databases, et cetera. Rate controllers and NICs live inside of clouds. All right. You know, one of the reasons I love working with you guys is 'cause have such a wide observation space and Zeus Kerravala you, of all people, you know you have your fingers in a lot of pies. So give us your final thoughts. >> Yeah, I'm not a propeller heady as my chip counterparts here. (all laugh) So, you know, I look at the world a little differently and a lot of my research I'm doing now is the impact that distributed computing has on customer employee experiences, right? You talk to every business and how the experiences they deliver to their customers is really differentiating how they go to market. And so they're looking at these different ways of feeding up data and analytics and things like that in different places. And I think this is going to have a really profound impact on enterprise IT architecture. We're putting more data, more compute in more places all the way down to like little micro edges and retailers and things like that. And so we need the variety. Historically, if you think back to when I was in IT you know, pre-Y2K, we didn't have a lot of choice in things, right? We had a server that was rack mount or standup, right? And there wasn't a whole lot of, you know, differences in choice. But today we can deploy, you know, these really high-performance compute systems on little blades inside servers or inside, you know, autonomous vehicles and things. I think the world from here gets... You know, just the choice of what we have and the way hardware and software works together is really going to, I think, change the world the way we do things. We're already seeing that, like I said, in the consumer world, right? There's so many things you can do from, you know, smart home perspective, you know, natural language processing, stuff like that. And it's starting to hit businesses now. So just wait and watch the next five years. >> Yeah, totally. The computing power at the edge is just going to be mind blowing. >> It's unbelievable what you can do at the edge. >> Yeah, yeah. Hey Z, I just want to say that we know you're not a propeller head and I for one would like to thank you for having your master's thesis hanging on the wall behind you 'cause we know that you studied basket weaving. >> I was actually a physics math major, so. >> Good man. Another math major. All right, Bob O'Donnell, you're going to bring us home. I mean, we've seen the importance of semiconductors and silicon in our everyday lives, but your last thoughts please. >> Sure and just to clarify, by the way I was a great books major and this was actually for my final paper. And so I was like philosophy and all that kind of stuff and literature but I still somehow got into tech. Look, it's been a great conversation and I want to pick up a little bit on a comment Zeus made, which is this it's the combination of the hardware and the software and coming together and the manner with which that needs to happen, I think is critically important. And the other thing is because of the diversity of the chip architectures and all those different pieces and elements, it's going to be how software tools evolve to adapt to that new world. So I look at things like what Intel's trying to do with oneAPI. You know, what Nvidia has done with CUDA. What other platform companies are trying to create tools that allow them to leverage the hardware, but also embrace the variety of hardware that is there. And so as those software development environments and software development tools evolve to take advantage of these new capabilities, that's going to open up a lot of interesting opportunities that can leverage all these new chip architectures. That can leverage all these new interconnects. That can leverage all these new system architectures and figure out ways to make that all happen, I think is going to be critically important. And then finally, I'll mention the research I'm actually currently working on is on private 5g and how companies are thinking about deploying private 5g and the potential for edge applications for that. So I'm doing a survey of several hundred us companies as we speak and really looking forward to getting that done in the next couple of weeks. >> Yeah, look forward to that. Guys, again, thank you so much. Outstanding conversation. Anybody going to be at Dell tech world in a couple of weeks? Bob's going to be there. Dave Nicholson. Well drinks on me and guys I really can't thank you enough for the insights and your participation today. Really appreciate it. Okay, and thank you for watching this special power panel episode of theCube Insights powered by ETR. Remember we publish each week on Siliconangle.com and wikibon.com. All these episodes they're available as podcasts. DM me or any of these guys. I'm at DVellante. You can email me at David.Vellante@siliconangle.com. Check out etr.ai for all the data. This is Dave Vellante. We'll see you next time. (upbeat music)

(upbeat music) >> Once a staid and boring business dominated by IBM, Oracle, and at the time newcomer Microsoft, along with a handful of wannabes, the database business has exploded in the past decade and has become a staple of financial excellence, customer experience, analytic advantage, competitive strategy, growth initiatives, visualizations, not to mention compliance, security, privacy and dozens of other important use cases and initiatives. And on the vendor's side of the house, we've seen the rapid ascendancy of cloud databases. Most notably from Snowflake, whose massive raises leading up to its IPO in late 2020 sparked a spate of interest and VC investment in the separation of compute and storage and all that elastic resource stuff in the cloud. The company joined AWS, Azure and Google to popularize cloud databases, which have become a linchpin of competitive strategies for technology suppliers. And if I get you to put your data in my database and in my cloud, and I keep innovating, I'm going to build a moat and achieve a hugely attractive lifetime customer value in a really amazing marginal economics dynamic that is going to fund my future. And I'll be able to sell other adjacent services, not just compute and storage, but machine learning and inference and training and all kinds of stuff, dozens of lucrative cloud offerings. Meanwhile, the database leader, Oracle has invested massive amounts of money to maintain its lead. It's building on its position as the king of mission critical workloads and making typical Oracle like claims against the competition. Most were recently just yesterday with another announcement around MySQL HeatWave. An extension of MySQL that is compatible with on-premises MySQLs and is setting new standards in price performance. We're seeing a dramatic divergence in strategies across the database spectrum. On the far left, we see Amazon with more than a dozen database offerings each with its own API and primitives. AWS is taking a right tool for the right job approach, often building on open source platforms and creating services that it offers to customers to solve very specific problems for developers. And on the other side of the line, we see Oracle, which is taking the Swiss Army Knife approach, converging database functionality, enabling analytic and transactional workloads to run in the same data store, eliminating the need to ETL, at the same time adding capabilities into its platform like automation and machine learning. Welcome to this database Power Panel. My name is Dave Vellante, and I'm so excited to bring together some of the most respected industry analyst in the community. Today we're going to assess what's happening in the market. We're going to dig into the competitive landscape and explore the future of database and database platforms and decode what it means to customers. Let me take a moment to welcome our guest analyst today. Matt Kimball is a vice president and principal analysts at Moor Insights and Strategy, Matt. He knows products, he knows industry, he's got real world IT expertise, and he's got all the angles 25 plus years of experience in all kinds of great background. Matt, welcome. Thanks very much for coming on theCUBE. Holgar Mueller, friend of theCUBE, vice president and principal analyst at Constellation Research in depth knowledge on applications, application development, knows developers. He's worked at SAP and Oracle. And then Bob Evans is Chief Content Officer and co-founder of the Acceleration Economy, founder and principle of Cloud Wars. Covers all kinds of industry topics and great insights. He's got awesome videos, these three minute hits. If you haven't seen 'em, checking them out, knows cloud companies, his Cloud Wars minutes are fantastic. And then of course, Marc Staimer is the founder of Dragon Slayer Research. A frequent contributor and guest analyst at Wikibon. He's got a wide ranging knowledge across IT products, knows technology really well, can go deep. And then of course, Ron Westfall, Senior Analyst and Director Research Director at Futurum Research, great all around product trends knowledge. Can take, you know, technical dives and really understands competitive angles, knows Redshift, Snowflake, and many others. Gents, thanks so much for taking the time to join us in theCube today. It's great to have you on, good to see you. >> Good to be here, thanks for having us. >> Thanks, Dave. >> All right, let's start with an around the horn and briefly, if each of you would describe, you know, anything I missed in your areas of expertise and then you answer the following question, how would you describe the state of the database, state of platform market today? Matt Kimball, please start. >> Oh, I hate going first, but that it's okay. How would I describe the world today? I would just in one sentence, I would say, I'm glad I'm not in IT anymore, right? So, you know, it is a complex and dangerous world out there. And I don't envy IT folks I'd have to support, you know, these modernization and transformation efforts that are going on within the enterprise. It used to be, you mentioned it, Dave, you would argue about IBM versus Oracle versus this newcomer in the database space called Microsoft. And don't forget Sybase back in the day, but you know, now it's not just, which SQL vendor am I going to go with? It's all of these different, divergent data types that have to be taken, they have to be merged together, synthesized. And somehow I have to do that cleanly and use this to drive strategic decisions for my business. That is not easy. So, you know, you have to look at it from the perspective of the business user. It's great for them because as a DevOps person, or as an analyst, I have so much flexibility and I have this thing called the cloud now where I can go get services immediately. As an IT person or a DBA, I am calling up prevention hotlines 24 hours a day, because I don't know how I'm going to be able to support the business. And as an Oracle or as an Oracle or a Microsoft or some of the cloud providers and cloud databases out there, I'm licking my chops because, you know, my market is expanding and expanding every day. >> Great, thank you for that, Matt. Holgar, how do you see the world these days? You always have a good perspective on things, share with us. >> Well, I think it's the best time to be in IT, I'm not sure what Matt is talking about. (laughing) It's easier than ever, right? The direction is going to cloud. Kubernetes has won, Google has the best AI for now, right? So things are easier than ever before. You made commitments for five plus years on hardware, networking and so on premise, and I got gray hair about worrying it was the wrong decision. No, just kidding. But you kind of both sides, just to be controversial, make it interesting, right. So yeah, no, I think the interesting thing specifically with databases, right? We have this big suite versus best of breed, right? Obviously innovation, like you mentioned with Snowflake and others happening in the cloud, the cloud vendors server, where to save of their databases. And then we have one of the few survivors of the old guard as Evans likes to call them is Oracle who's doing well, both their traditional database. And now, which is really interesting, remarkable from that because Oracle it was always the power of one, have one database, add more to it, make it what I call the universal database. And now this new HeatWave offering is coming and MySQL open source side. So they're getting the second (indistinct) right? So it's interesting that older players, traditional players who still are in the market are diversifying their offerings. Something we don't see so much from the traditional tools from Oracle on the Microsoft side or the IBM side these days. >> Great, thank you Holgar. Bob Evans, you've covered this business for a while. You've worked at, you know, a number of different outlets and companies and you cover the competition, how do you see things? >> Dave, you know, the other angle to look at this from is from the customer side, right? You got now CEOs who are any sort of business across all sorts of industries, and they understand that their future success is going to be dependent on their ability to become a digital company, to understand data, to use it the right way. So as you outline Dave, I think in your intro there, it is a fantastic time to be in the database business. And I think we've got a lot of new buyers and influencers coming in. They don't know all this history about IBM and Microsoft and Oracle and you know, whoever else. So I think they're going to take a long, hard look, Dave, at some of these results and who is able to help these companies not serve up the best technology, but who's going to be able to help their business move into the digital future. So it's a fascinating time now from every perspective. >> Great points, Bob. I mean, digital transformation has gone from buzzword to imperative. Mr. Staimer, how do you see things? >> I see things a little bit differently than my peers here in that I see the database market being segmented. There's all the different kinds of databases that people are looking at for different kinds of data, and then there is databases in the cloud. And so database as cloud service, I view very differently than databases because the traditional way of implementing a database is changing and it's changing rapidly. So one of the premises that you stated earlier on was that you viewed Oracle as a database company. I don't view Oracle as a database company anymore. I view Oracle as a cloud company that happens to have a significant expertise and specialty in databases, and they still sell database software in the traditional way, but ultimately they're a cloud company. So database cloud services from my point of view is a very distinct market from databases. >> Okay, well, you gave us some good meat on the bone to talk about that. Last but not least-- >> Dave did Marc, just say Oracle's a cloud company? >> Yeah. (laughing) Take away the database, it would be interesting to have that discussion, but let's let Ron jump in here. Ron, give us your take. >> That's a great segue. I think it's truly the era of the cloud database, that's something that's rising. And the key trends that come with it include for example, elastic scaling. That is the ability to scale on demand, to right size workloads according to customer requirements. And also I think it's going to increase the prioritization for high availability. That is the player who can provide the highest availability is going to have, I think, a great deal of success in this emerging market. And also I anticipate that there will be more consolidation across platforms in order to enable cost savings for customers, and that's something that's always going to be important. And I think we'll see more of that over the horizon. And then finally security, security will be more important than ever. We've seen a spike (indistinct), we certainly have seen geopolitical originated cybersecurity concerns. And as a result, I see database security becoming all the more important. >> Great, thank you. Okay, let me share some data with you guys. I'm going to throw this at you and see what you think. We have this awesome data partner called Enterprise Technology Research, ETR. They do these quarterly surveys and each period with dozens of industry segments, they track clients spending, customer spending. And this is the database, data warehouse sector okay so it's taxonomy, so it's not perfect, but it's a big kind of chunk. They essentially ask customers within a category and buy a specific vendor, you're spending more or less on the platform? And then they subtract the lesses from the mores and they derive a metric called net score. It's like NPS, it's a measure of spending velocity. It's more complicated and granular than that, but that's the basis and that's the vertical axis. The horizontal axis is what they call market share, it's not like IDC market share, it's just pervasiveness in the data set. And so there are a couple of things that stand out here and that we can use as reference point. The first is the momentum of Snowflake. They've been off the charts for many, many, for over two years now, anything above that dotted red line, that 40%, is considered by ETR to be highly elevated and Snowflake's even way above that. And I think it's probably not sustainable. We're going to see in the next April survey, next month from those guys, when it comes out. And then you see AWS and Microsoft, they're really pervasive on the horizontal axis and highly elevated, Google falls behind them. And then you got a number of well funded players. You got Cockroach Labs, Mongo, Redis, MariaDB, which of course is a fork on MySQL started almost as protest at Oracle when they acquired Sun and they got MySQL and you can see the number of others. Now Oracle who's the leading database player, despite what Marc Staimer says, we know, (laughs) and they're a cloud player (laughing) who happens to be a leading database player. They dominate in the mission critical space, we know that they're the king of that sector, but you can see here that they're kind of legacy, right? They've been around a long time, they get a big install base. So they don't have the spending momentum on the vertical axis. Now remember this is, just really this doesn't capture spending levels, so that understates Oracle but nonetheless. So it's not a complete picture like SAP for instance is not in here, no Hana. I think people are actually buying it, but it doesn't show up here, (laughs) but it does give an indication of momentum and presence. So Bob Evans, I'm going to start with you. You've commented on many of these companies, you know, what does this data tell you? >> Yeah, you know, Dave, I think all these compilations of things like that are interesting, and that folks at ETR do some good work, but I think as you said, it's a snapshot sort of a two-dimensional thing of a rapidly changing, three dimensional world. You know, the incidents at which some of these companies are mentioned versus the volume that happens. I think it's, you know, with Oracle and I'm not going to declare my religious affiliation, either as cloud company or database company, you know, they're all of those things and more, and I think some of our old language of how we classify companies is just not relevant anymore. But I want to ask too something in here, the autonomous database from Oracle, nobody else has done that. So either Oracle is crazy, they've tried out a technology that nobody other than them is interested in, or they're onto something that nobody else can match. So to me, Dave, within Oracle, trying to identify how they're doing there, I would watch autonomous database growth too, because right, it's either going to be a big plan and it breaks through, or it's going to be caught behind. And the Snowflake phenomenon as you mentioned, that is a rare, rare bird who comes up and can grow 100% at a billion dollar revenue level like that. So now they've had a chance to come in, scare the crap out of everybody, rock the market with something totally new, the data cloud. Will the bigger companies be able to catch up and offer a compelling alternative, or is Snowflake going to continue to be this outlier. It's a fascinating time. >> Really, interesting points there. Holgar, I want to ask you, I mean, I've talked to certainly I'm sure you guys have too, the founders of Snowflake that came out of Oracle and they actually, they don't apologize. They say, "Hey, we not going to do all that complicated stuff that Oracle does, we were trying to keep it real simple." But at the same time, you know, they don't do sophisticated workload management. They don't do complex joints. They're kind of relying on the ecosystems. So when you look at the data like this and the various momentums, and we talked about the diverging strategies, what does this say to you? >> Well, it is a great point. And I think Snowflake is an example how the cloud can turbo charge a well understood concept in this case, the data warehouse, right? You move that and you find steroids and you see like for some players who've been big in data warehouse, like Sentara Data, as an example, here in San Diego, what could have been for them right in that part. The interesting thing, the problem though is the cloud hides a lot of complexity too, which you can scale really well as you attract lots of customers to go there. And you don't have to build things like what Bob said, right? One of the fascinating things, right, nobody's answering Oracle on the autonomous database. I don't think is that they cannot, they just have different priorities or the database is not such a priority. I would dare to say that it's for IBM and Microsoft right now at the moment. And the cloud vendors, you just hide that right through scripts and through scale because you support thousands of customers and you can deal with a little more complexity, right? It's not against them. Whereas if you have to run it yourself, very different story, right? You want to have the autonomous parts, you want to have the powerful tools to do things. >> Thank you. And so Matt, I want to go to you, you've set up front, you know, it's just complicated if you're in IT, it's a complicated situation and you've been on the customer side. And if you're a buyer, it's obviously, it's like Holgar said, "Cloud's supposed to make this stuff easier, but the simpler it gets the more complicated gets." So where do you place your bets? Or I guess more importantly, how do you decide where to place your bets? >> Yeah, it's a good question. And to what Bob and Holgar said, you know, the around autonomous database, I think, you know, part of, as I, you know, play kind of armchair psychologist, if you will, corporate psychologists, I look at what Oracle is doing and, you know, databases where they've made their mark and it's kind of, that's their strong position, right? So it makes sense if you're making an entry into this cloud and you really want to kind of build momentum, you go with what you're good at, right? So that's kind of the strength of Oracle. Let's put a lot of focus on that. They do a lot more than database, don't get me wrong, but you know, I'm going to short my strength and then kind of pivot from there. With regards to, you know, what IT looks at and what I would look at you know as an IT director or somebody who is, you know, trying to consume services from these different cloud providers. First and foremost, I go with what I know, right? Let's not forget IT is a conservative group. And when we look at, you know, all the different permutations of database types out there, SQL, NoSQL, all the different types of NoSQL, those are largely being deployed by business users that are looking for agility or businesses that are looking for agility. You know, the reason why MongoDB is so popular is because of DevOps, right? It's a great platform to develop on and that's where it kind of gained its traction. But as an IT person, I want to go with what I know, where my muscle memory is, and that's my first position. And so as I evaluate different cloud service providers and cloud databases, I look for, you know, what I know and what I've invested in and where my muscle memory is. Is there enough there and do I have enough belief that that company or that service is going to be able to take me to, you know, where I see my organization in five years from a data management perspective, from a business perspective, are they going to be there? And if they are, then I'm a little bit more willing to make that investment, but it is, you know, if I'm kind of going in this blind or if I'm cloud native, you know, that's where the Snowflakes of the world become very attractive to me. >> Thank you. So Marc, I asked Andy Jackson in theCube one time, you have all these, you know, data stores and different APIs and primitives and you know, very granular, what's the strategy there? And he said, "Hey, that allows us as the market changes, it allows us to be more flexible. If we start building abstractions layers, it's harder for us." I think also it was not a good time to market advantage, but let me ask you, I described earlier on that spectrum from AWS to Oracle. We just saw yesterday, Oracle announced, I think the third major enhancement in like 15 months to MySQL HeatWave, what do you make of that announcement? How do you think it impacts the competitive landscape, particularly as it relates to, you know, converging transaction and analytics, eliminating ELT, I know you have some thoughts on this. >> So let me back up for a second and defend my cloud statement about Oracle for a moment. (laughing) AWS did a great job in developing the cloud market in general and everything in the cloud market. I mean, I give them lots of kudos on that. And a lot of what they did is they took open source software and they rent it to people who use their cloud. So I give 'em lots of credit, they dominate the market. Oracle was late to the cloud market. In fact, they actually poo-pooed it initially, if you look at some of Larry Ellison's statements, they said, "Oh, it's never going to take off." And then they did 180 turn, and they said, "Oh, we're going to embrace the cloud." And they really have, but when you're late to a market, you've got to be compelling. And this ties into the announcement yesterday, but let's deal with this compelling. To be compelling from a user point of view, you got to be twice as fast, offer twice as much functionality, at half the cost. That's generally what compelling is that you're going to capture market share from the leaders who established the market. It's very difficult to capture market share in a new market for yourself. And you're right. I mean, Bob was correct on this and Holgar and Matt in which you look at Oracle, and they did a great job of leveraging their database to move into this market, give 'em lots of kudos for that too. But yesterday they announced, as you said, the third innovation release and the pace is just amazing of what they're doing on these releases on HeatWave that ties together initially MySQL with an integrated builtin analytics engine, so a data warehouse built in. And then they added automation with autopilot, and now they've added machine learning to it, and it's all in the same service. It's not something you can buy and put on your premise unless you buy their cloud customers stuff. But generally it's a cloud offering, so it's compellingly better as far as the integration. You don't buy multiple services, you buy one and it's lower cost than any of the other services, but more importantly, it's faster, which again, give 'em credit for, they have more integration of a product. They can tie things together in a way that nobody else does. There's no additional services, ETL services like Glue and AWS. So from that perspective, they're getting better performance, fewer services, lower cost. Hmm, they're aiming at the compelling side again. So from a customer point of view it's compelling. Matt, you wanted to say something there. >> Yeah, I want to kind of, on what you just said there Marc, and this is something I've found really interesting, you know. The traditional way that you look at software and, you know, purchasing software and IT is, you look at either best of breed solutions and you have to work on the backend to integrate them all and make them all work well. And generally, you know, the big hit against the, you know, we have one integrated offering is that, you lose capability or you lose depth of features, right. And to what you were saying, you know, that's the thing I found interesting about what Oracle is doing is they're building in depth as they kind of, you know, build that service. It's not like you're losing a lot of capabilities, because you're going to one integrated service versus having to use A versus B versus C, and I love that idea. >> You're right. Yeah, not only you're not losing, but you're gaining functionality that you can't get by integrating a lot of these. I mean, I can take Snowflake and integrate it in with machine learning, but I also have to integrate in with a transactional database. So I've got to have connectors between all of this, which means I'm adding time. And what it comes down to at the end of the day is expertise, effort, time, and cost. And so what I see the difference from the Oracle announcements is they're aiming at reducing all of that by increasing performance as well. Correct me if I'm wrong on that but that's what I saw at the announcement yesterday. >> You know, Marc, one thing though Marc, it's funny you say that because I started out saying, you know, I'm glad I'm not 19 anymore. And the reason is because of exactly what you said, it's almost like there's a pseudo level of witchcraft that's required to support the modern data environment right in the enterprise. And I need simpler faster, better. That's what I need, you know, I am no longer wearing pocket protectors. I have turned from, you know, break, fix kind of person, to you know, business consultant. And I need that point and click simplicity, but I can't sacrifice, you know, a depth of features of functionality on the backend as I play that consultancy role. >> So, Ron, I want to bring in Ron, you know, it's funny. So Matt, you mentioned Mongo, I often and say, if Oracle mentions you, you're on the map. We saw them yesterday Ron, (laughing) they hammered RedShifts auto ML, they took swipes at Snowflake, a little bit of BigQuery. What were your thoughts on that? Do you agree with what these guys are saying in terms of HeatWaves capabilities? >> Yes, Dave, I think that's an excellent question. And fundamentally I do agree. And the question is why, and I think it's important to know that all of the Oracle data is backed by the fact that they're using benchmarks. For example, all of the ML and all of the TPC benchmarks, including all the scripts, all the configs and all the detail are posted on GitHub. So anybody can look at these results and they're fully transparent and replicate themselves. If you don't agree with this data, then by all means challenge it. And we have not really seen that in all of the new updates in HeatWave over the last 15 months. And as a result, when it comes to these, you know, fundamentals in looking at the competitive landscape, which I think gives validity to outcomes such as Oracle being able to deliver 4.8 times better price performance than Redshift. As well as for example, 14.4 better price performance than Snowflake, and also 12.9 better price performance than BigQuery. And so that is, you know, looking at the quantitative side of things. But again, I think, you know, to Marc's point and to Matt's point, there are also qualitative aspects that clearly differentiate the Oracle proposition, from my perspective. For example now the MySQL HeatWave ML capabilities are native, they're built in, and they also support things such as completion criteria. And as a result, that enables them to show that hey, when you're using Redshift ML for example, you're having to also use their SageMaker tool and it's running on a meter. And so, you know, nobody really wants to be running on a meter when, you know, executing these incredibly complex tasks. And likewise, when it comes to Snowflake, they have to use a third party capability. They don't have the built in, it's not native. So the user, to the point that he's having to spend more time and it increases complexity to use auto ML capabilities across the Snowflake platform. And also, I think it also applies to other important features such as data sampling, for example, with the HeatWave ML, it's intelligent sampling that's being implemented. Whereas in contrast, we're seeing Redshift using random sampling. And again, Snowflake, you're having to use a third party library in order to achieve the same capabilities. So I think the differentiation is crystal clear. I think it definitely is refreshing. It's showing that this is where true value can be assigned. And if you don't agree with it, by all means challenge the data. >> Yeah, I want to come to the benchmarks in a minute. By the way, you know, the gentleman who's the Oracle's architect, he did a great job on the call yesterday explaining what you have to do. I thought that was quite impressive. But Bob, I know you follow the financials pretty closely and on the earnings call earlier this month, Ellison said that, "We're going to see HeatWave on AWS." And the skeptic in me said, oh, they must not be getting people to come to OCI. And then they, you remember this chart they showed yesterday that showed the growth of HeatWave on OCI. But of course there was no data on there, it was just sort of, you know, lines up and to the right. So what do you guys think of that? (Marc laughs) Does it signal Bob, desperation by Oracle that they can't get traction on OCI, or is it just really a smart tame expansion move? What do you think? >> Yeah, Dave, that's a great question. You know, along the way there, and you know, just inside of that was something that said Ellison said on earnings call that spoke to a different sort of philosophy or mindset, almost Marc, where he said, "We're going to make this multicloud," right? With a lot of their other cloud stuff, if you wanted to use any of Oracle's cloud software, you had to use Oracle's infrastructure, OCI, there was no other way out of it. But this one, but I thought it was a classic Ellison line. He said, "Well, we're making this available on AWS. We're making this available, you know, on Snowflake because we're going after those users. And once they see what can be done here." So he's looking at it, I guess you could say, it's a concession to customers because they want multi-cloud. The other way to look at it, it's a hunting expedition and it's one of those uniquely I think Oracle ways. He said up front, right, he doesn't say, "Well, there's a big market, there's a lot for everybody, we just want on our slice." Said, "No, we are going after Amazon, we're going after Redshift, we're going after Aurora. We're going after these users of Snowflake and so on." And I think it's really fairly refreshing these days to hear somebody say that, because now if I'm a buyer, I can look at that and say, you know, to Marc's point, "Do they measure up, do they crack that threshold ceiling? Or is this just going to be more pain than a few dollars savings is worth?" But you look at those numbers that Ron pointed out and that we all saw in that chart. I've never seen Dave, anything like that. In a substantive market, a new player coming in here, and being able to establish differences that are four, seven, eight, 10, 12 times better than competition. And as new buyers look at that, they're going to say, "What the hell are we doing paying, you know, five times more to get a poor result? What's going on here?" So I think this is going to rattle people and force a harder, closer look at what these alternatives are. >> I wonder if the guy, thank you. Let's just skip ahead of the benchmarks guys, bring up the next slide, let's skip ahead a little bit here, which talks to the benchmarks and the benchmarking if we can. You know, David Floyer, the sort of semiretired, you know, Wikibon analyst said, "Dave, this is going to force Amazon and others, Snowflake," he said, "To rethink actually how they architect databases." And this is kind of a compilation of some of the data that they shared. They went after Redshift mostly, (laughs) but also, you know, as I say, Snowflake, BigQuery. And, like I said, you can always tell which companies are doing well, 'cause Oracle will come after you, but they're on the radar here. (laughing) Holgar should we take this stuff seriously? I mean, or is it, you know, a grain salt? What are your thoughts here? >> I think you have to take it seriously. I mean, that's a great question, great point on that. Because like Ron said, "If there's a flaw in a benchmark, we know this database traditionally, right?" If anybody came up that, everybody will be, "Oh, you put the wrong benchmark, it wasn't audited right, let us do it again," and so on. We don't see this happening, right? So kudos to Oracle to be aggressive, differentiated, and seem to having impeccable benchmarks. But what we really see, I think in my view is that the classic and we can talk about this in 100 years, right? Is the suite versus best of breed, right? And the key question of the suite, because the suite's always slower, right? No matter at which level of the stack, you have the suite, then the best of breed that will come up with something new, use a cloud, put the data warehouse on steroids and so on. The important thing is that you have to assess as a buyer what is the speed of my suite vendor. And that's what you guys mentioned before as well, right? Marc said that and so on, "Like, this is a third release in one year of the HeatWave team, right?" So everybody in the database open source Marc, and there's so many MySQL spinoffs to certain point is put on shine on the speed of (indistinct) team, putting out fundamental changes. And the beauty of that is right, is so inherent to the Oracle value proposition. Larry's vision of building the IBM of the 21st century, right from the Silicon, from the chip all the way across the seven stacks to the click of the user. And that what makes the database what Rob was saying, "Tied to the OCI infrastructure," because designed for that, it runs uniquely better for that, that's why we see the cross connect to Microsoft. HeatWave so it's different, right? Because HeatWave runs on cheap hardware, right? Which is the breadth and butter 886 scale of any cloud provider, right? So Oracle probably needs it to scale OCI in a different category, not the expensive side, but also allow us to do what we said before, the multicloud capability, which ultimately CIOs really want, because data gravity is real, you want to operate where that is. If you have a fast, innovative offering, which gives you more functionality and the R and D speed is really impressive for the space, puts away bad results, then it's a good bet to look at. >> Yeah, so you're saying, that we versus best of breed. I just want to sort of play back then Marc a comment. That suite versus best of breed, there's always been that trade off. If I understand you Holgar you're saying that somehow Oracle has magically cut through that trade off and they're giving you the best of both. >> It's the developing velocity, right? The provision of important features, which matter to buyers of the suite vendor, eclipses the best of breed vendor, then the best of breed vendor is in the hell of a potential job. >> Yeah, go ahead Marc. >> Yeah and I want to add on what Holgar just said there. I mean the worst job in the data center is data movement, moving the data sucks. I don't care who you are, nobody likes it. You never get any kudos for doing it well, and you always get the ah craps, when things go wrong. So it's in- >> In the data center Marc all the time across data centers, across cloud. That's where the bleeding comes. >> It's right, you get beat up all the time. So nobody likes to move data, ever. So what you're looking at with what they announce with HeatWave and what I love about HeatWave is it doesn't matter when you started with it, you get all the additional features they announce it's part of the service, all the time. But they don't have to move any of the data. You want to analyze the data that's in your transactional, MySQL database, it's there. You want to do machine learning models, it's there, there's no data movement. The data movement is the key thing, and they just eliminate that, in so many ways. And the other thing I wanted to talk about is on the benchmarks. As great as those benchmarks are, they're really conservative 'cause they're underestimating the cost of that data movement. The ETLs, the other services, everything's left out. It's just comparing HeatWave, MySQL cloud service with HeatWave versus Redshift, not Redshift and Aurora and Glue, Redshift and Redshift ML and SageMaker, it's just Redshift. >> Yeah, so what you're saying is what Oracle's doing is saying, "Okay, we're going to run MySQL HeatWave benchmarks on analytics against Redshift, and then we're going to run 'em in transaction against Aurora." >> Right. >> But if you really had to look at what you would have to do with the ETL, you'd have to buy two different data stores and all the infrastructure around that, and that goes away so. >> Due to the nature of the competition, they're running narrow best of breed benchmarks. There is no suite level benchmark (Dave laughs) because they created something new. >> Well that's you're the earlier point they're beating best of breed with a suite. So that's, I guess to Floyer's earlier point, "That's going to shake things up." But I want to come back to Bob Evans, 'cause I want to tap your Cloud Wars mojo before we wrap. And line up the horses, you got AWS, you got Microsoft, Google and Oracle. Now they all own their own cloud. Snowflake, Mongo, Couchbase, Redis, Cockroach by the way they're all doing very well. They run in the cloud as do many others. I think you guys all saw the Andreessen, you know, commentary from Sarah Wang and company, to talk about the cost of goods sold impact of cloud. So owning your own cloud has to be an advantage because other guys like Snowflake have to pay cloud vendors and negotiate down versus having the whole enchilada, Safra Catz's dream. Bob, how do you think this is going to impact the market long term? >> Well, Dave, that's a great question about, you know, how this is all going to play out. If I could mention three things, one, Frank Slootman has done a fantastic job with Snowflake. Really good company before he got there, but since he's been there, the growth mindset, the discipline, the rigor and the phenomenon of what Snowflake has done has forced all these bigger companies to really accelerate what they're doing. And again, it's an example of how this intense competition makes all the different cloud vendors better and it provides enormous value to customers. Second thing I wanted to mention here was look at the Adam Selipsky effect at AWS, took over in the middle of May, and in Q2, Q3, Q4, AWS's growth rate accelerated. And in each of those three quotas, they grew faster than Microsoft's cloud, which has not happened in two or three years, so they're closing the gap on Microsoft. The third thing, Dave, in this, you know, incredibly intense competitive nature here, look at Larry Ellison, right? He's got his, you know, the product that for the last two or three years, he said, "It's going to help determine the future of the company, autonomous database." You would think he's the last person in the world who's going to bring in, you know, in some ways another database to think about there, but he has put, you know, his whole effort and energy behind this. The investments Oracle's made, he's riding this horse really hard. So it's not just a technology achievement, but it's also an investment priority for Oracle going forward. And I think it's going to form a lot of how they position themselves to this new breed of buyer with a new type of need and expectations from IT. So I just think the next two or three years are going to be fantastic for people who are lucky enough to get to do the sorts of things that we do. >> You know, it's a great point you made about AWS. Back in 2018 Q3, they were doing about 7.4 billion a quarter and they were growing in the mid forties. They dropped down to like 29% Q4, 2020, I'm looking at the data now. They popped back up last quarter, last reported quarter to 40%, that is 17.8 billion, so they more doubled and they accelerated their growth rate. (laughs) So maybe that pretends, people are concerned about Snowflake right now decelerating growth. You know, maybe that's going to be different. By the way, I think Snowflake has a different strategy, the whole data cloud thing, data sharing. They're not trying to necessarily take Oracle head on, which is going to make this next 10 years, really interesting. All right, we got to go, last question. 30 seconds or less, what can we expect from the future of data platforms? Matt, please start. >> I have to go first again? You're killing me, Dave. (laughing) In the next few years, I think you're going to see the major players continue to meet customers where they are, right. Every organization, every environment is, you know, kind of, we use these words bespoke in Snowflake, pardon the pun, but Snowflakes, right. But you know, they're all opinionated and unique and what's great as an IT person is, you know, there is a service for me regardless of where I am on my journey, in my data management journey. I think you're going to continue to see with regards specifically to Oracle, I think you're going to see the company continue along this path of being all things to all people, if you will, or all organizations without sacrificing, you know, kind of richness of features and sacrificing who they are, right. Look, they are the data kings, right? I mean, they've been a database leader for an awful long time. I don't see that going away any time soon and I love the innovative spirit they've brought in with HeatWave. >> All right, great thank you. Okay, 30 seconds, Holgar go. >> Yeah, I mean, the interesting thing that we see is really that trend to autonomous as Oracle calls or self-driving software, right? So the database will have to do more things than just store the data and support the DVA. It will have to show it can wide insights, the whole upside, it will be able to show to one machine learning. We haven't really talked about that. How in just exciting what kind of use case we can get of machine learning running real time on data as it changes, right? So, which is part of the E5 announcement, right? So we'll see more of that self-driving nature in the database space. And because you said we can promote it, right. Check out my report about HeatWave latest release where I post in oracle.com. >> Great, thank you for that. And Bob Evans, please. You're great at quick hits, hit us. >> Dave, thanks. I really enjoyed getting to hear everybody's opinion here today and I think what's going to happen too. I think there's a new generation of buyers, a new set of CXO influencers in here. And I think what Oracle's done with this, MySQL HeatWave, those benchmarks that Ron talked about so eloquently here that is going to become something that forces other companies, not just try to get incrementally better. I think we're going to see a massive new wave of innovation to try to play catch up. So I really take my hat off to Oracle's achievement from going to, push everybody to be better. >> Excellent. Marc Staimer, what do you say? >> Sure, I'm going to leverage off of something Matt said earlier, "Those companies that are going to develop faster, cheaper, simpler products that are going to solve customer problems, IT problems are the ones that are going to succeed, or the ones who are going to grow. The one who are just focused on the technology are going to fall by the wayside." So those who can solve more problems, do it more elegantly and do it for less money are going to do great. So Oracle's going down that path today, Snowflake's going down that path. They're trying to do more integration with third party, but as a result, aiming at that simpler, faster, cheaper mentality is where you're going to continue to see this market go. >> Amen brother Marc. >> Thank you, Ron Westfall, we'll give you the last word, bring us home. >> Well, thank you. And I'm loving it. I see a wave of innovation across the entire cloud database ecosystem and Oracle is fueling it. We are seeing it, with the native integration of auto ML capabilities, elastic scaling, lower entry price points, et cetera. And this is just going to be great news for buyers, but also developers and increased use of open APIs. And so I think that is really the key takeaways. Just we're going to see a lot of great innovation on the horizon here. >> Guys, fantastic insights, one of the best power panel as I've ever done. Love to have you back. Thanks so much for coming on today. >> Great job, Dave, thank you. >> All right, and thank you for watching. This is Dave Vellante for theCube and we'll see you next time. (soft music)

(upbeat music) >> Welcome, everyone, to theCUBE's presentation of the AWS Startup Showcase. And this episode two of season two is called "Data as Code," the ongoing series covering exciting new startups in the AWS ecosystem. I'm John Furrier, your host of theCUBE. Today, we're excited to be joined by Jon Dahl, who is the co-founder and CEO of MUX, a hot new startup building cloud video for developers, video with data. John, great to see you. We did an interview on theCube Conversation. Went into big detail of the awesomeness of your company and the trend that you're on. Welcome back. >> Thank you, glad to be here. >> So, video is everywhere, and video for pivot to video, you hear all these kind of terms in the industry, but now more than ever, video is everywhere and people are building with it, and it's becoming part of the developer experience in applications. So people have to stand up video into their code fast, and data is code, video is data. So you guys are specializing this. Take us through that dynamic. >> Yeah, so video clearly is a growing part of how people are building applications. We see a lot of trends of categories that did not involve video in the past making a major move towards video. I think what Peloton did five years ago to the world of fitness, that was not really a big category. Now video fitness is a huge thing. Video in education, video in business settings, video in a lot of places. I think Marc Andreessen famously said, "Software is eating the world" as a pretty, pretty good indicator of what the internet is actually doing to the economy. I think there's a lot of ways in which video right now is eating software. So categories that we're not video first are becoming video first. And that's what we help with. >> It's not obvious to like most software developers when they think about video, video industries, it's industry shows around video, NAB, others. People know, the video folks know what's going on in video, but when you start to bring it mainstream, it becomes an expectation in the apps. And it's not that easy, it's almost a provision video is hard for a developer 'cause you got to know the full, I guess, stack of video. That's like low level and then kind of just basic high level, just play something. So, in between, this is a media stack kind of dynamic. Can you talk about how hard it is to build video for developers? How is it going to become easier? >> Yeah, I mean, I've lived this story for too long, maybe 13 years now, when I first build my first video stack. And, you know, I'll sometimes say, I think it's kind of a miracle every time a video plays on the internet because the internet is not a medium designed for video. It's been hijacked by video, video is 70% of internet traffic today in an unreliable, sort of untrusted network space, which is totally different than how television used to work or cable or things like that. So yeah, so video is hard because there's so many problems from top to bottom that need to be solved to make video work. So you have to worry about video compression encoding, which is a complicated topic in itself. You have to worry about delivering video around the world at scale, delivering it at low cost, at low latency, with good performance, you have to worry about devices and how every device, Android, iOS, web, TVs, every device handles video differently and so there's a lot of work there. And at the end of the day, these are kind of unofficial standards that everyone's using. So one of the miracles is like, if you want to watch a video, somehow you have to get like Apple and Google to agree on things, which is not always easy. And so there's just so many layers of complexity that are behind it. I think one way to think about it is, if you want to put an image online, you just put an image online. And if you want to put video online, you build complex software, and that's the exact problem that MUX was started to help solve. >> It's interesting you guys have almost creating a whole new category around video infrastructure. And as you look at, you mentioned stack, video stack. I'm looking at a market where the notion of a media stack is developing, and you're seeing these verticals having similar dynamics with cloud. And if you go back to the early days of cloud computing, what was the developer experience or entrepreneurial experience, you had to actually do a lot of stuff before you even do anything, provision a server. And this has all kind of been covered in great detail in the glory of Agile and whatnot. It was expensive, and you had that actually engineer before you could even stand up any code. Now you got video that same thing's happening. So the developers have two choices, go do a bunch of stuff complex, building their own infrastructure, which is like building a data center, or lean in on MUX and say, "Hey, thank you for doing all that years of experience building out the stacks to take that hard part away," but using APIs that they have. This is a developer focused problem that you guys are solving. >> Yeah, that's right. my last company was a company called Zencoder, that was an API to video encoding. So it was kind of an API to a small part of what MUX does today, just one of those problems. And I think the thing that we got right at Zencoder, that we're doing again here at MUX, was building four developers first. So our number one persona is a software developer. Not necessarily a video expert, just we think any developer should be able to build with video. It shouldn't be like, yeah, got to go be a specialist to use this technology, because it should become just of the internet. Video should just be something that any developer can work with. So yeah, so we build for developers first, which means we spend a lot of time thinking about API design, we spend a lot of time thinking about documentation, transparent pricing, the right features, great support and all those kind of things that tend to be characteristics of good developer companies. >> Tell me about the pipe lining of the products. I'm a developer, I work for a company, my boss is putting pressure on me. We need video, we have all this library, it's all stacking up. We hired some people, they left. Where's the video, we've stored it somewhere. I mean, it's a nightmare, right? So I'm like, okay, I'm cloud native, I got an API. I need to get my product to market fast, 'cause that is what Agile developers want. So how do you describe that acceleration for time to market? You mentioned you guys are API first, video first. How do these customers get their product into the market as fast as possible? >> Yeah, well, I mean the first thing we do is we put what we think is probably on average, three to four months of hard engineering work behind a single API call. So if you want to build a video platform, we tell our customers like, "Hey, you can do that." You probably need a team, you probably need video experts on your team so hire them or train them. And then it takes several months just to kind of to get video flowing. One API call at MUX gives you on-demand video or live video that works at scale, works around the world with good performance, good reliability, a rich feature set. So maybe just a couple specific examples, we worked with Robin Hood a few years ago to bring video into their newsfeed, which was hugely successful for them. And they went from talking to us for the first time to a big launch in, I think it was three months, but the actual code time there was like really short. I want to say they had like a proof of concept up and running in a couple days, and then the full launch in three months. Another customer of ours, Bandcamp, I think switched from a legacy provider to MUX in two weeks in band. So one of the big advantages of going a little bit higher in the abstraction layer than just building it yourself is that time to market. >> Talk about this notion of video pipeline 'cause I know I've heard people I talk about, "Hey, I just want to get my product out there. I don't want to get stuck in the weeds on video pipeline." What does that mean for folks that aren't understanding the nuances of video? >> Yeah, I mean, it's all the steps that it takes to publish video. So from ingesting the video, if it's live video from making sure that you have secure, reliable ingest of that live feed potentially around the world to the transcoding, which is we talked a little bit about, but it is a, you know, on its own is a massively complicated problem. And doing that, well, doing that well is hard. Part of the reason it's hard is you really have to know where you're publishing too. And you might want to transcode video differently for different devices, for different types of content. You know, the pipeline typically would also include all of the workflow items you want to do with the video. You want to thumbnail a video, you want clip, create clips of the video, maybe you want to restream the video to Facebook or Twitter or a social platform. You want to archive the video, you want it to be available for downloads after an event. If it's just a, if it's a VOD upload, if it's not live in the first place. You have all those things and you might want to do simulated live with the video. You might want to actually record something and then play it back as a live stream. So, the pipeline Ty typically refers to everything from the ingest of the video to the time that the bits are delivered to a device. >> You know, I hear a lot of people talking about video these days, whether it's events, training, just want peer to peer experience, video is powerful, but customers want to own their own platform, right? They want to have the infrastructure as a service. They kind of want platform as a service, this is cloud talk now, but they want to have their own capability to build it out. This allows them to get what they want. And so you see this, like, is it SaaS? Is it platform? People want customization? So kind of the general purpose video solution does it really exist or doesn't? I mean, 'cause this is the question. Can I just buy software and work or is it going to be customized always? How do you see that? Because this becomes a huge discussion point. Is it a SaaS product or someone's going to make a SaaS product? >> Yeah, so I think one of the most important elements of designing any software, but especially when you get into infrastructure is choosing an abstraction level. So if you think of computing, you can go all the way down to building a data center, you can go all the way down to getting a colo and racking a server like maybe some of us used to do, who are older than others. And that's one way to run a server. On the other extreme, you have just think of the early days of cloud competing, you had app engine, which was a really fantastic, really incredible product. It was one push deploy of, I think Python code, if I remember correctly, and everything just worked. But right in the middle of those, you had EC2, which was, EC2 is basically an API to a server. And it turns out that that abstraction level, not Colo, not the full app engine kind of platform, but the API to virtual server was the right abstraction level for maybe the last 15 years. Maybe now some of the higher level application platforms are doing really well, maybe the needs will shift. But I think that's a little bit of how we think about video. What developers want is an API to video. They don't want an API to the building blocks of video, an API to transcoding, to video storage, to edge caching. They want an API to video. On the other extreme, they don't want a big application that's a drop in white label video in a box like a Shopify kind of thing. Shopify is great, but developers don't want to build on top of Shopify. In the payments world developers want Stripe. And that abstraction level of the API to the actual thing you're getting tends to be the abstraction level that developers want to build on. And the reason for that is, it's the most productive layer to build on. You get maximum flexibility and also maximum velocity when you have that API directly to a function like video. So, we like to tell our customers like you, you own your video when you build on top of MUX, you have full control over everything, how it's stored, when it's stored, where it goes, how it's published, we handle all of the hard technology and we give our customers all of the flexibility in terms of designing their products. >> I want to get back some use case, but you brought that up I might as well just jump to my next point. I'd like you to come back and circle back on some references 'cause I know you have some. You said building on infrastructure that you own, this is a fundamental cloud concept. You mentioned API to a server for the nerds out there that know that that's cool, but the people who aren't super nerdy, that means you're basically got an interface into a server behind the scenes. You're doing the same for video. So, that is a big thing around building services. So what wide range of services can we expect beyond MUX? If I'm going to have an API to video, what could I do possibly? >> What sort of experience could you build? >> Yes, I got a team of developers saying I'm all in API to video, I don't want to do all that transit got straight there, I want to build experiences, video experiences on my app. >> Yeah, I mean, I think, one way to think about it is that, what's the range of key use cases that people do with video? We tend to think about six at MUX, one is kind of the places where the content is, the prop. So one of the things that use video is you can create great video. Think of online courses or fitness or entertainment or news or things like that. That's kind of the first thing everyone thinks of, when you think video, you think Netflix, and that's great. But we see a lot of really interesting uses of video in the world of social media. So customers of ours like Visco, which is an incredible photo sharing application, really for photographers who really care about the craft. And they were able to bring video in and bring that same kind of Visco experience to video using MUX. We think about B2B tools, videos. When you think about it, all video is, is a high bandwidth way of communicating. And so customers are as like HubSpot use video for the marketing platform, for business collaboration, you'll see a lot of growth of video in terms of helping businesses engage their customers or engage with their employees. We see live events obviously have been a massive category over the last few years. You know, we were all forced into a world where we had to do live events two years ago, but I think now we're reemerging into a world where the online part of a conference will be just as important as the in-person component of a conference. So that's another big use case we see. >> Well, full disclosure, if you're watching this live right now, it's being powered by MUX. So shout out, we use MUX on theCUBE platform that you're experiencing in this. Actually in real time, 'cause this is one application, there's many more. So video as code, is data as code is the theme, that's going to bring up the data ops. Video also is code because (laughs) it's just like you said, it's just communicating, but it gets converted to data. So data ops, video ops could be its own new category. What's your reaction to that? >> Yeah, I mean, I think, I have a couple thoughts on that. The first thought is, video is a way that, because the way that companies interact with customers or users, it's really important to have good monitoring and analytics of your video. And so the first product we ever built was actually a product called MUX video, sorry, MUX data, which is the best way to monitor a video platform at scale. So we work with a lot of the big broadcasters, we work with like CBS and Fox Sports and Discovery. We work with big tech companies like Reddit and Vimeo to help them monitor their video. And you just get a huge amount of insight when you look at robust analytics about video delivery that you can use to optimize performance, to make sure that streaming works well globally, especially in hard to reach places or on every device. That's we actually build a MUX data platform first because when we started MUX, we spent time with some of our friends at companies like YouTube and Netflix, and got to know how they use data to power their video platforms. And they do really sophisticated things with data to ensure that their streams well, and we wanted to build the product that would help everyone else do that. So, that's one use. I think the other obvious use is just really understanding what people are doing with their video, who's watching what, what's engaging, those kind of things. >> Yeah, data is definitely there. You guys mentioned some great brands that are working with you guys, and they're doing it because of the developer experience. And I'd like you to explain, if you don't mind, in your words, why is the MUX developer experience so good? What are some of the results you're seeing from your customers? What are they saying to you? Obviously when you win, you get good feedback. What are some of the things that they're saying and what specific develop experiences do they like the best? >> Yeah, I mean, I think that the most gratifying thing about being a startup founder is when your customers like what you're doing. And so we get a lot of this, but it's always, we always pay attention to what customers say. But yeah, people, the number one thing developers say when they think about MUX is that the developer experience is great. I think when they say that, what they mean is two things, first is it's easy to work with, which helps them move faster, software velocity is so important. Every company in the world is investing and wants to move quickly and to build quickly. And so if you can help a team speed up, that's massively valuable. The second thing I think when people like our developer experience is, you know, in a lot of ways that think that we get out of the way and we let them do what they want to do. So well, designed APIs are a key part of that, coming back to abstraction, making sure that you're not forcing customers into decisions that they actually want to make themselves. Like, if our video player only had one design, that that would not be, that would not work for most developers, 'cause developers want to bring their own design and style and workflow and feel to their video. And so, yeah, so I think the way we do that is just think comprehensively about how APIs are designed, think about the workflows that users are trying to accomplish with video, and make sure that we have the right APIs, make sure they're the right information, we have the right webhooks, we have the right SDKs, all of those things in place so that they can build what they want. >> We were just having a conversation on theCUBE, Dave Vellante and I, and our team, and I'd love to get you a reaction to this. And it's more and more, a riff real quick. We're seeing a trend where video as code, data as code, media stack, where you're starting to see the emergence of the media developer, where the application of media looks a lot like kind of software developer, where the app, media as an app. It could be a chat, it could be a peer to peer video, it could be part of an event platform, but with all the recent advances, in UX designers, coders, the front end looks like an emergence of these creators that are essentially media developers for all intent and purpose, they're coding media. What's your reaction to that? How do you see that evolving? >> I think the. >> Or do you agree with it? >> It's okay. >> Yeah, yeah. >> Well, I think a couple things. I think one thing, I think this goes along through saying, but maybe it's disagreement, is that we don't think you should have to be an expert at video or at media to create and produce or create and publish good video, good audio, good images, those kind of things. And so, you know, I think if you look at software overall, I think of 10 years ago, the kind of DevOps movement, where there was kind of a movement away from specialization in software where the same software developer could build and deploy the same software developer maybe could do front end and back end. And we want to bring that to video as well. So you don't have to be a specialist to do it. On the other hand, I do think that investments and tooling, all the way from video creation, which is not our world, but there's a lot of amazing companies out there that are making it easier to produce video, to shoot video, to edit, a lot of interesting innovations there all the way to what we do, which is helping people stream and publish video and video experiences. You know, I think another way about it is, that tool set and companies doing that let anyone be a media developer, which I think is important. >> It's like DevOps turning into low-code, no-code, eventually it's just composability almost like just, you know, "Hey Siri, give me some video." That kind of thing. Final question for you why I got you here, at the end of the day, the decision between a lot of people's build versus buy, "I got to get a developer. Why not just roll my own?" You mentioned data center, "I want to build a data center." So why MUX versus do it yourself? >> Yeah, I mean, part of the reason we started this company is we have a pretty, pretty strong opinion on this. When you think about it, when we started MUX five years ago, six years ago, if you were a developer and you wanted to accept credit cards, if you wanted to bring payment processing into your application, you didn't go build a payment gateway. You just probably used Stripe. And if you wanted to send text messages, you didn't build your own SMS gateway, you probably used Twilio. But if you were a developer and you wanted to stream video, you built your own video gateway, you built your own video application, which was really complex. Like we talked about, you know, probably three, four months of work to get something basic up and running, probably not live video that's probably only on demand video at that point. And you get no benefit by doing it yourself. You're no better than anyone else because you rolled your own video stack. What you get is risk that you might not do a good job, maybe you do worse than your competitors, and you also get distraction where you've just taken, you take 10 engineers and 10 sprints and you apply it to a problem that doesn't actually really give you differentiated value to your users. So we started MUX so that people would not have to do that. It's fine if you want to build your own video platform, once you get to a certain scale, if you can afford a dozen engineers for a VOD platform and you have some really massively differentiated use case, you know, maybe, live is, I don't know, I don't have the rule of thumb, live videos maybe five times harder than on demand video to work with. But you know, in general, like there's such a shortage of software engineers today and software engineers have, frankly, are in such high demand. Like you see what happens in the marketplace and the hiring markets, how competitive it is. You need to use your software team where they're maximally effective, and where they're maximally effective is building differentiation into your products for your customers. And video is just not that, like very few companies actually differentiate on their video technology. So we want to be that team for everyone else. We're 200 people building the absolute best video infrastructure as APIs for developers and making that available to everyone else. >> John, great to have you on with the showcase, love the company, love what you guys do. Video as code, data as code, great stuff. Final plug for the company, for the developers out there and prospects watching for MUX, why should they go to MUX? What are you guys up to? What's the big benefit? >> I mean, first, just check us out. Try try our APIs, read our docs, talk to our support team. We put a lot of work into making our platform the best, you know, as you dig deeper, I think you'd be looking at the performance around, the global performance of what we do, looking at our analytics stack and the insight you get into video streaming. We have an emerging open source video player that's really exciting, and I think is going to be the direction that open source players go for the next decade. And then, you know, we're a quickly growing team. We're 60 people at the beginning of last year. You know, we're one 50 at the beginning of this year, and we're going to a add, we're going to grow really quickly again this year. And this whole team is dedicated to building the best video structure for developers. >> Great job, Jon. Thank you so much for spending the time sharing the story of MUX here on the show, Amazon Startup Showcase season two, episode two, thanks so much. >> Thank you, John. >> Okay, I'm John Furrier, your host of theCUBE. This is season two, episode two, the ongoing series cover the most exciting startups from the AWS Cloud Ecosystem. Talking data analytics here, video cloud, video as a service, video infrastructure, video APIs, hottest thing going on right now, and you're watching it live here on theCUBE. Thanks for watching. (upbeat music)

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

>>Mhm. Hey, everyone, welcome back to the cubes. Continuous coverage of AWS Re Invent 2021. Live from Las Vegas. Lisa Martin with John Ferrier We have to live sets to remote studios over 100 guests on the Cube at this year's show and we're really excited to get to the next decade in cloud innovation and welcome from the keynote stage. Mark Ruin the Chief Network Officer Andy VPs Dish Network Mark, Welcome to the Cube. >>Thank you. >>Enjoyed your keynote this morning. So big news coming from AWS and dish you guys announced in the spring telecom industry First dish in AWS have formed a strategic collaboration to reinvent, reinvent five G connectivity and innovation. Let's let's really kind of dig into the AWS dish partnership. >>Yeah, you know, we're putting our network in the cloud, which allows us to have a different speed of innovation and a much more corroborative way of bringing new technology. And then we have access to all the developer ecosystem of AWS. So that's but as you say, it's a world first to put the telco in the cloud. >>And so the first time the five g network is going to be in the cloud, and it was also announced I'm curious, uh, that Las Vegas is going to be the first city live here. We are sitting in Las Vegas. What's the any status you can give us on >>that? So we're building across the US and Las Vegas is a place that we've built and we better testing. So that's where we have all run and we're testing all sorts of traffic and capability with our people and partners live here at the same time that we have the reinvent and, uh, Bianco around. We're also starting to test new capabilities like orchestration, slicing things that we've never seen any industry. So that's pretty exciting, I >>have to ask you. In the telecom industry, there has been an inflexion point around cloud and cloud Impact Ran is opening up new opportunities. What is the telecom industry getting and missing at the same time? Because it seems to be two schools of thought cloud pro cloud ran and then hold onto the old way. >>I think everybody would like to go to Iran and the cloud, but it's not as easy if you have a big installed base. So for us. You know, we all knew it. It's easy so we can adopt the best technology and the newest. But of course, if you have a big instal base, there is going to be a transformation, if you wish. So you know, people are starting trying to set the expectation of how much time it will take. But for us, you know we are. We're moving ahead because we're building a completely new network. >>It's a lot easier than well, it's a relative term. It's >>really much more fun. And we can We don't have to make compromises, right? So but it's still a lot of work, you know, we're discovering we're learning a lot of things. We're partners. >>What if you have a clean sheet of paper or Greenfield? What's the playbook to roll this out across the campus for a large geographic area? >>Yeah, so pretty much You have the same capability in terms of coverage and capabilities than anybody else, but we can do it in an automated manner. We can do it with much thinner and efficient hardware, pretty much hardware with a few accelerators, so a bit of jargon. But, you know, we just have access to a larger ecosystem and much more silicon and all the good things that are coming with the cloud >>talk to us about some of the unique challenges of five G that make running it in the cloud so much more helpful. And then also, why did you decide to partner with AWS? Clearly you have choice, but I'd love to know the backstory on that. >>Yeah, I've been in the telco industry forever, and I've always seen that our speed of innovation was to slow. The telco is very good at reliability. You know, your phone always works. Um, it's very reliable. You can have massive traffic, but the speed of innovation is not fast enough. And the the applications that are coming on the clouds are much faster. So what we wanted to marry is the reliability of the telco and and all the knowledge that exists with the speed of the cloud. And that's what we're doing with bringing their ecosystem into our ecosystem to get the best of two worlds. >>Lots of transformation in the vertical industries. We heard from Adam today on stage vertical with ai machine learning. How does that apply in the telco world because it's an edge you got. See, sports stadiums, for instance. You're seeing all kinds of home impact. How is vertical specialisation? >>Yeah. So what is unique about the cloud is that you can observe a lot of things, you know, in the cloud you have access to data, so you see what's happening, and then you use a lot of algorithms. We call it Machine Learning Analytics to make decisions. Now, for us, it means if you're a stadium, you're going to have a much better visibility of what's happening. Where is the traffic? You know, people moving in and moving out? Are they going to buy some food awards? So you see the traffic and you can adapt the way you steal the traffic the way you distribute video, the way you distribute entertainment to how people are moving because you can observe what is happening in the network, which you can't do in a classic or legacy five g network. So once you observe, you can have plenty of ideas, right? And you can start innovation again, mix a lot of things and offer new services. >>In this last 22 months, when we saw this rapid pivot to work from home. And now it's work from anywhere, right? We talk about hybrid cloud hybrid events here, but this hybrid work environment talk to me about the impact that that decision A W s are going to have on all of those companies and people who are going to be remote and working from the edge for maybe permanently. >>Yes, you say, You know what is important is that people want to have access to the to the cloud to the services, the enterprise from wherever they are. So as a software architect, I need to make sure that we can follow them and offer that service from wherever they are in a similar manner today. If you're making a phone call, you don't have to think if you're connecting to the Web, you know, through WiFi through this and that, you have to think we want to make it as simple as making a phone call. In the past, where you always connected, you always secured. You always have access to your data. So that's really the ambition we have. And, of course, with the new remote abbots, the video conferencing that's the perfect time to come with a new offer. >>And the Strand also is moving towards policy based. You mentioned understanding video and patterns. Having that differentiated services capability in real time is a big deal. >>Yeah, that's a big deal. Actually, what enterprise want? They want to manage their policy, so they want to decide what traffic gets, a premium access and what traffic can be put in the background. You want to update your computers? Maybe that's not a premium price for that. You can do it at any time, but you want to have real time, customer service and support. You want premium? And who am I to decide for an enterprise? Enterprises want to decide. So what we offer them is the tools to create their policy, and their policy will be a competitive advantage for them when they can different change. >>And this brings up another point. I want to ask you. You brought this up earlier about this. The ideas, the creativity that enables with cloud you mentioned ideas will come out. These are this is where the developers now can really encode. This is the whole theme of this Pathfinders keynote. You were up on stage. This is a real opportunity to add value. Doing all the heavy lifting in the top of the stack and enabling new use cases, new applications, new expectations. >>You know what I tell to my engineers? My dream as an engineer is to be, uh, developer friendly. I want people to come to us because it's fun to work in our environment and try things. And a lot of the ideas that developers will have won't work. But if they can spin it off very fast, they will move to that killer application of killer service very fast. So my job is to bring that to them so that it's very easy to consume and and trying to live And, you know, just like bringing >>candy to a baby here. >>Yeah, cause right And have fun and, uh, and discover it for yourself and decide for yourself. >>I gotta ask your questions in the Telecom for a while. We've been seeing on the Cube earlier in our intro keynote analysis that we're now living in an era with SAS applications. No more shelf where now, with purpose built applications that you're seeing now and horizontally scalable, vertically integrated machine learning. You can't hide the ball anymore around what's working. You can't put a project out there and say no, you can't justify. You can't put you can put lipstick on that. You can't know you're seeing on >>that bad cake. Yeah, it's all the point of beta testing and market adoption. You try, you put it there. It works. You say the brake doesn't work. You try again, right? That's the way it works. And and in Telco, you're right. We were cooking for a year or two years, Three years and saying, Oh, you know what? That's what you need. It doesn't work like this faster now. Yeah, Yeah. And people want to be able to influence and they want to say, I like it. I don't like it. And the market is deciding. >>Speaking of influence, one of the things we know we talk a lot about with A W S and their guests is their customer. First customer obsession focused. You know, the whole reason we're here is that is to serve the customer, talk to me about how customers and joint customers are influencing some of the design choices that you guys are making as you're bringing five due to the cloud. >>So what is important for us? We have to dreams, right? The first one is for consumers. We want consumers to have access to the network so that they feel that they are VIP and often I know you and I, sometimes when we're connected to the network with tropical, we don't get the feeling where a V i p So that's something that's a journey for us to make people feel like they get the service and the network is following them and caring about them for the enterprises. You want to let them decide what they want. You were talking about policy building. They want to come with their own rating engine. They want to come with their own geographical maps. Like here. I have traffic here. I don't need coverage. So we want to open up so that the enterprise decide how they invest, how they spend the money on the network >>giving control back to the end user. Whether that's a consumer or enterprise, >>absolutely giving control to the end user and the enterprises. And we're there to support and accelerate the service for them. >>Mark, I want to ask you about leadership. You mentioned all these new things. Are there your dreams? And it's happening Giving engineers the canvas to paint their own future. It's gonna be fun is fun as you're affecting that change. What can people do as leaders to create that momentum to bring the whole organisation along is their tricks of the trade. Is their best practises >>Absolutely their best practises? Um, we were very much following develops where, you know, as a leader, you don't know, you're just learning and you're exposing and you're sharing. Uh, we're also creating an open world where we're asking all our partners to be open. Sometimes, you know, they feel like a bit challenge. Like, do I want to show what I'm doing? And I would say, Yeah, sure, because you're benefiting between each other. Um, And then you want to give tools to your engineers and your marketers to be fast speed, speed, speed, speed so that they can just play and learn. And at the end of the day, you said it. It's all about fun. You know, if it's fun, it's easy to do >>that. We're having fun here. >>That is true. We always have fun here. Last question for you is talk about some of the things that AWS announced this morning. Lots of stuff going on in Adam's keynote. What excites you about this continued partnership between AWS and Dish? >>Yeah, we were. We were surprised and so happy about AWS answer to when we came in with the first one to come big time in the telco and the Cloud was not ready. To be honest, it was Enterprise and Data Club and AWS. When is going all the way, we've asked to transform their cloud to make it a telco frantic, loud. So we have a lot of discussions about networking, routing, service level agreements and a lot of things that are very technical. And there are a true partner innovating with us. We have a road map with ideas and that's pretty unique. So, great partner, >>I was going to say it sounds like a really true >>trust and partnership. We're sharing ideas and challenging each other all the time, so that's really great. >>Awesome and users benefit consumers Benefit enterprises benefit Mark Thank you for joining Joining me on the programme today. Georgia Keynote enjoyed hearing more about dish and AWS. And what are you doing to power? The future. We appreciate your time. >>Thank you. Thank you >>for John Ferrier. I'm Lisa Martin. You're watching the Cube? The global leader in tech coverage, So mhm. Yeah.

>> Announcer: From the Bellagio Hotel in Las Vegas, it's theCUBE, covering UiPath FORWARD IV brought to you by UiPath. >> Live from Las Vegas, it's theCUBE. We are wrapping up day two of our coverage of UiPath FORWARD IV. Lisa Martin here with Dave Vellante. We've had an amazing event talking with customers, partners, and users, and UiPath folks themselves. And who better to wrap up the show with than Daniel Dines the founder and CEO of UiPath. Welcome, Daniel, great to have you back on theCUBE. >> Oh, thank you so much for having me. I'm becoming a regular at theCUBE. >> Yeah, it's good to see you again. >> You are, this is your fifth... >> Fifth time on theCUBE. >> Fifth time, yes. >> Fifth time, but as you said before we went live, first time since the IPO. Congratulations. >> Thank you. >> UiPath has been a rocket ship for a very long time. I'm sure a tremendous amount of acceleration has occurred since the IPO. We can all see the numbers. You're a public company now, ARR of 726 million. You've got over 9,000 customers. We got the chance to speak with a few of them here today. We know how important the voice of the customer is to UiPath and how very symbiotic it is. But I want to talk about the culture of the company. How is that going? How is it being maintained especially since the big splashy IPO just about six months ago? >> Well, I always believe that in order to build a durable company, culture is maybe the most important thing. I think long lasting companies have very foundational culture. So we've built it, and we invested a lot in the last 5-6 years because in the beginning when it's just a bunch of people, they don't have a culture. It's maybe like a vibe of a group of friends. But then when you go and try to dial in your culture, I think it's important that you look at your roots and who are you? What defines you? So we ended up of this really core values, which is to be humble. To me, it's one of quintessential value of every human being. And all of us want to work with humble people much more inclined to listen, to change their mind. And then we say, you have to be humble, but you have to be bold in the same time. This rocket ship need a bold crew onboard. So you need to be fast because the fastest company will always win. And you need to be immersed because my theory with life and jobs is in whatever you do, you have to be immersed. I don't believe necessarily in life-work balance. I believe in life-work cycles, in life-work immersion. So when you are with family, you are immersed. When you work, you are immersed. That will bring the best of you and the best of productivity. So we try so much to keep our culture alive, to hire people that add to the culture, that nicely fit into the culture. And recently we took a veteran of UiPath and we appointed her as Chief Culture Officer. So I'm very happy of this move. So I think we are one of the few companies that really have a Chief Culture Officer reporting directly to the CEO. So we're really serious of building our culture along the way. And as I said yesterday in my keynote, I think our values are universal values. I think they have the value of the new way of working. All of us would like to work in a company, in an environment that fosters these values. >> I certainly think the events of the last 18 months have forced many more people to be humble and embrace humility. Because everybody on video conferencing, your dog walks in, your kids walk in, you're exposed. They have to be more humble because that's just how they were getting work done. I've seen and heard a lot of humility from your folks and a lot of bold statements from customers as well. We had the CIO of Coca-Cola on talking about how UiPath is fundamental in their transformation. I think that the fact that you are doing an event here in person, whereas as Dave was saying earlier this week, your competitors are on webcams is a great example of the boldness of this company and its culture. >> Well, thank you. I think that we've made a really good decision to do this event in person. Maybe on Zoom over the last 18 months, we kind of lost a bit how important is to connect with people. It's not only about the message, it's about the trust. And I think we are deeply embedded into the critical systems of our customers. They need to trust us. They need to work with the company that they look in their eyes and say, "Yes, we are here for you." And you cannot do it over Zoom. Even I really like Zoom and Eric Yuan is a friend of mine, but a combination I think, and going into this hybrid world, I think it's actually extremely beneficial for all of us. Meeting in person a few times a year, then continuing the relationship over Zoom in time, I think it's awesome. >> Yeah, and the fact that you were able to get so many customers here, I think that's, Lisa, why a lot of companies don't have physical events 'cause they can't get their customers here. You got 2000 customers here, customers and partners, but a lot of customers. I've spoken to dozens and they're easy to find. So I think that's one point I want the audience to know. You've always been on the culture train. And enduring companies, CEOs of great enduring companies, always come back to culture. So that's important. And of course, product. You said today, you're a product guy. That's when you get excited. You've changed the industry. And I think, I've never bought into the narrative about replacing jobs. I'd never been a fan of protecting the past from the future. It's inevitable, but I think the way you've changed the market, I wonder if you could comment is... You had legacy RPA tools that were expensive and cumbersome. And so people had to get the ROI and it took a long time. So that was an obvious way to get it is to reduce headcount. You came in and said, short money you can actually try it even a free version. You compressed that ROI and the light bulb went off, and so people then said, "Oh, wow, this isn't about replacing jobs, but making my life better." And you've always said that. And that's I think one way in which you've changed the market quite dramatically, and now you have a lot of people following that path. >> That was always kind of our biggest competitive advantage. We showed our customers and our partners, this is a technology that gives you the faster time to value and actually faster time to value translate into much higher return on investment. In a typical automation project, the license cost is maybe 5% of the project cost. So the moment you shrink the development time, the implementation time, you increase exponentially the return on investment. So this is why speaking about our roadmap, and we always start with this high level, how can we reduce the development time? So how can we reduce the friction? How can we expand the use cases? Because these are essential themes for us, always thinking customer first, customer value and that serves us pretty well really. We win a lot in all the contests where we go side by side with other competitors. It was a very simple strategy for us. Asking customers, "Just go and test it side-by-side and see," and they see. We implement the same process in halftime, half of resources involved. It's an easy math multiplied by a thousand processes and it's done. >> When theCUBE started Daniel in 2010. It was our first year. And so it coincided with big data movement. And we said at the time that the companies who can figure out how to apply big data are going to make a lot of money, more than the big data vendors. And I think in a way now the problem with big data was too complicated, right? There were only a few big internet giants who could figure out Hadoop and all that stuff. Automation, I think is even bigger in a way, 'cause it involves data. It involves AI, it's transformative. And so we're saying the same thing here. The companies that are applying automation, and we've seen a lot of them here, Coca-Cola, Merck, Applied Materials, on and on and on, are actually the ones that are going to not only survive but thrive, incumbents that don't have to invent AI necessarily or invent their own automation. But coming back to you 'cause I think your company can make a lot of money. You've set the TAM at 60 billion. I think it actually could be well over 100 billion, but we don't have to have that conversation here. It's just convergence of all these markets that guys like IDC and Gartner, they count in stove pipes. So anyway, big, no shortage of opportunity. My question to you is feels like you have the potential to build a next great software company and with the founder as the CEO, and there aren't a lot of them left. Michael Dell is not a software company, but his name is still, Larry Ellison is still there, Marc Benioff. How do you think about the endurance, the enduring UiPath? Are you envisioning building the next great software company, may take 20 years? >> People were asking me for a long time. Did you envision that you'd get here from the beginning? And I always tell them, no. Otherwise I would have been considered mad. (Lisa and Dave laughing) So you build the vision over time. I don't believe in people that start a small SaaS company and they say, "We are going to change the world." This is not how the world works. Really, you build and you understand the customer and you build more. But at some point I realized we change so much how people work, we get the best out of them. It's something major here. And if you look in history, we are in this trap that started with agriculture. This is the trap of manual, repetitive, low value tasks that we have to do. And it took the humanity of us. And I talked to Tom Montag about with this book "Sapiens". It's interesting and that book comes with the theory that our biggest quality is our ability to collaborate. Well, our technology gives people the ability to collaborate more. So, in this way, I think it's truly transformative. And yes, I believe now that we can build the next generation of software company. >> How do you like... That's the wrong question. How are you doing with the 90-day shot clock as Michael Dell calls it? It's a new world for you, right? You've never been a CEO of a public company, the street's getting to know you like, "Who is this guy?" I'll give you another cute story. There were three companies in the early CUBE days, Tableau, Splunk, and ServiceNow that had the kind of customer passion that you have. I think ServiceNow could be one of the next great software companies. Tableau now part of Salesforce. I think Splunk was under capitalized, but we see the same kind of passion here. So now you're the CEO of a public company, except the street's getting to know you a little bit. They're like, "Hmm, how do we read the guy?" All that stuff. That'll sort itself out. But so what's life like on the public markets? >> Well, I don't think anyone prepares you for the life of a public company. (Dave laughing) I thought it's going to be easier, but it's not, because we were used to deal with private investors and it's much easier because I think private investors have access to a lot more data. They look into your books. So they understand your business model. With public investors, they have access only to like a spreadsheet of numbers. So they need to figure out a business model, the trajectory from just a split. It's way more difficult. I've come to appreciate their job. It's much more difficult. So they have to get all the cues from how I dress, how do I say this word? They watch the FED announcements. What do they mean to say by this? And I and the shim we are first time in a job as a public company CEO, public company CFO. So of course it's a lot of learning for us and like in any learning environment, initial learning curve is tough, but you progress quite a lot. So I believe that over the next few quarters, we will be in the position to build trust with the street and they will understand better our business model, and they see that we are building everything for creating durable growth. >> It's a marathon, it's not a sprint. I know it's a cliche, but it really does apply here. >> You've certainly built a tremendous amount of trust within your 9,000 strong customer base. I think I was reading that your 70% of your revenue comes from existing customers. I think this is a great use case for how to do land and expand really well. So, the DNA I think is there at UiPath to be able to build that trust with the street. >> Yeah, absolutely. Our 9,000 plus customers, it's our wealth. This is our IP in a way. It's even better than in our pro. It's our customers. We have one of the best net retention rate in the industry of 144%. So that speaks volume. >> Lisa: It does. >> Automation for good. I know you've read some of the stuff I've written. I've covered you guys pretty extensively over the years. And that theme sounds like a lot of motherhood and apple pie, but one of the things that I wrote is that you look at the productivity decline and particularly in Western countries over the last two decades. Now I know with the pandemic and especially in 2021, productivity is going up for reasons that I think are understood, but the trend is clear. So when you think about big problems, climate change, diversity, income inequality, health of populations, overpopulation, on and on and on and on. You're not going to solve those problems by throwing labor at them. It has to be automation. So that to me is the tie to automation for good. And a lot of people might roll their eyes at it. But does that resonate with you? >> It totally resonates with me. Look at US. US population is not growing at the rates that we were used to. It's going to plateau at some point. It's just obvious. Like it plateaued in Japan, in Japan it's decreasing. US will see a decrease at some point. How do you increase the GDP? If your population is declining, productivity is declining. How do you increase GDP? Because the moment we stop increasing GDP, everything will collapse. The modern world is built on the idea of continuous economical growth. The moment growth stops, the world stops. We'll go back to our case and restart the engine. So, automation is hugely important in continuous GDP growth, which is the engine of our life. >> Which by the way is important because the chasm between the haves and the have-nots, that's how growth allows the people at the bottom to rise up to the middle and the middle to the top. So that's how you deal with that problem. You asked Tom Montag about crypto. So I have to ask you about crypto. What are your thoughts? Are you a fan? Are you not a fan? Do you have any wisdom? >> I have to admit, I never really understood the use cases of crypto. Technology behind crypto, blockchain is fascinating technology, but crypto in itself, I was never a fan. Tom Montag today gave me one of the best explanation of the very same. Look, Daniel, from Americans perspective we have the dollars, and this is the global currency. Crypto doesn't have so much sense, but think about a country like Columbia or Venezuela, countries where there people don't have so much trust in their currency, and where different political system can seize your assets from you. You need to be able to be capable of putting them into something else that is outside government context. I believe this is a good use case but I still don't believe that crypto is that type of asset that you know will survive the test of time. I think it's really too much... To me the difference between gold and Bitcoin is that it's too... You cannot replicate gold whatever you... It's impossible, unless you are God you cannot create gold two, right? It's impossible, but you can create Bitcoin 2. And at some point the fashion will move from Bitcoin 2 to Bitcoin 3. So I don't think the value that you can build in one particular crypto currency right now will stay over time. But it's just me. I was the wrong so many times in my life. >> You've been busy. You haven't had time to study crypto. >> I agree, totally agree. (Lisa and Dave laughing) >> What's been some of the feedback from the customers that are here. We saw yesterday a standing room only keynote. I'm sure it was great for you to be on stage again actually interacting with your customers and your partners. What's been some of the feedback as we've seen really this shift from an RPA point solution to an enterprise automation platform? >> Well, first of all, it was really great to be on stage. I don't know, I'm not a good presenter, really. But going there in front of people felt me with energy. Suddenly I felt a lot of comfort. So, I was capable of being myself with the people, which is really awesome. And the transition to a platform, from a product to a platform was really very well received by our customers because even in our competitive situations, when we are capable of explaining to them, what is the value of having an independent automation platform that is not tied to any big silos that application providers creates, we win and we win by default somehow. You've seen them now. So I think even the next evolution of semantic automation, this one is very well with our customers. >> Well, Daniel, it's been fantastic having you on. We have a good cadence here, and I hope we can continue it. On theCUBE, we love to identify early stage companies. Although as I wrote, you had a long, strange path to IPO because you took a long, long time and I think did it the right way to get product market fit. >> Absolutely. >> And that's not necessarily the way Silicon Valley works, double, double, triple, triple, and that you got product market fit, you got loyal customer base, and I think that's a key part of your success and you can see it and so congratulations, but many more years to come and we're really watching. >> Thank you so much. I'm looking forward to meeting you guys again. Thank you, that was awesome really. Great discussion. >> Exactly, good. Great to have you here in person and thanks for having us here in person as well. We look forward to FORWARD V. >> You will be invited forever. Thank you, guys, really. >> Forever, did you hear that? All right, for Daniel Dines and Dave Vellante, I'm Lisa Martin. This is theCUBE's coverage of UiPath FORWARD IV day two. Thanks for watching. (upbeat music)

(upbeat music) >> Welcome back to theCUBE's continuous coverage of AWS storage day. My name is Dave Vellante and we're here from Seattle. And we're going to look at the really hard workloads, those business and mission critical workloads, the most sensitive data. They're harder to move to the cloud. They're hardened. They have a lot of technical debt. And the blocker in some cases has been storage. Ashish Palekar is here. He's the general manager of EBS snapshots, and he's joined by Cami Tavares who's a senior manager of product management for Amazon EBS. Folks, good to see you. >> Ashish: Good to see you again Dave. >> Dave: Okay, nice to see you again Ashish So first of all, let's start with EBS. People might not be familiar. Everybody knows about S3 is famous, but how are customers using EBS? What do we need to know? >> Yeah, it's super important to get the basics, right? Right, yeah. We have a pretty broad storage portfolio. You talked about S3 and S3 glacier, which are an object and object and archival storage. We have EFS and FSX that cover the file site, and then you have a whole host of data transfer services. Now, when we think about block, we think of a really four things. We think about EBS, which is the system storage for EC2 volumes. When we think about snapshots, which is backups for EBS volumes. Then we think about instant storage, which is really a storage that's directly attached to an instance and manages and then its life cycle is similar to that of an instance. Last but not the least, data services. So things like our elastic volumes capability of fast snapshot restore. So the answer to your question really is EBS is persistent storage for EC2 volumes. So if you've used EC2 instances, you'll likely use EBS volumes. They service boot volumes and they service data volumes, and really cover a wide gamut of workloads from relational databases, no SQL databases, file streaming, media and coding. It really covers the gamut of workloads. >> Dave: So when I heard SAN in the cloud, I laughed out loud. I said, oh, because I could think about a box, a bunch of switches and this complicated network, and then you're turning it into an API. I was like, okay. So you've made some announcements that support SAN in the cloud. What, what can you tell us about? >> Ashish: Yeah, So SANs and for customers and storage, those are storage area networks, really our external arrays that customers buy and connect their performance critical and mission critical workloads. With block storage and with EBS, we got a bunch of customers that came to us and said, I'm thinking about moving those kinds of workloads to the cloud. What do you have? And really what they're looking for and what they were looking for is performance availability and durability characteristics that they would get from their traditional SANs on premises. And so that's what the team embarked on and what we launched at reinvent and then at GEd in July is IO2 block express. And what IO2 block express does is it's a complete ground app, really the invention of our storage product offering and gives customers the same availability, durability, and performance characteristics that can, we'll go into little later about that they're used to in their on premises. The other thing that we realized is that it's not just enough to have a volume. You need an instance that can drive that kind of throughput and IOPS. And so coupled with our trends in EC2 we launched our R5b that now triples the amount of IOPS and throughput that you can get from a single instance to EBS storage. So when you couple the sub millisecond latency, the capacity and the performance that you get from IO2 block express with R5b, what we hear from customers is that gives them enough of the performance availability characteristics and durability characteristics to move their workloads from on premises, into the cloud, for the mission critical and business critical apps. >> Dave: Thank you for that. So Cami when I, if I think about how the prevailing way in which storage works, I drop off a box at the loading dock and then I really don't know what happens. There may be a service organization that's maybe more intimate with the customer, but I don't really see the innovations and the use cases that are applied clouds, different. You know, you live it every day. So you guys always talk about customer inspired innovation. So what are you seeing in terms of how people are using this capability and what innovations they're driving? >> Cami: Yeah, so I think when we look at the EBS portfolio and this, the evolution over the years, you can really see that it was driven by customer need and we have different volume types and they have very specific performance characteristics, and they're built to meet these unique needs of customer workloads. So I'll tell you a little bit about some of our specific volume types to kind of illustrate this evolution over the years. So starting with our general purpose volumes, we have many customers that are using these volumes today. They really are looking for high performance at a low cost, and you have all kinds of transactional workloads and low-latency interactive applications and boot volumes, as Ashish mentioned. And they tell us, the customer is using these general purpose volumes, they tell us that they really like this balanced cost and performance. And customers also told us, listen, I have these more demanding applications that need higher performance. I need more IOPS, more throughput. And so looking at that customer need, we were really talking about these IO intensive applications like SAP HANA and Oracle and databases that require just higher durability. And so we looked at that customer feedback and we launched our provisioned IOPS IO2 volume. And with that volume, you get five nines of durability and four times the IOPS that you would get with general purpose volumes. So it's a really compelling offering. Again, customers came to us and said, this is great. I need more performance, I need more IOPS, more throughput, more storage than I can get with a single IO2 volume. And so these were talking about, you mentioned mission critical applications, SAP HANA, Oracle, and what we saw customers doing often is they were striping together multiple IO2 volumes to get the maximum performance, but very quickly with the most demanding applications, it got to a point where we have more IO2 volumes that you want to manage. And so we took that feedback to heart and we completely reinvented the underlying EBS hardware and the software and networking stacks. And we'll launched block express. With block express, you can get four times the IOPS throughput and storage that you would get with a single io2 volume. So it's a really compelling offering for customers. >> Dave: If I had to go back and ask you, what was the catalyst, what was the sort of business climate that really drove the decision here. Was that people were just sort of fed up with you know, I'll use the phrase, the undifferentiated, heavy lifting around SAN, what was it, was it COVID driven? What was the climate? >> You know, it's important to recognize when we are talking about business climate today, every business is a data business and block storage is really a foundational part of that. And so with SAN in the cloud specifically, we have seen enterprises for several years, buying these traditional hardware arrays for on premises SANs. And it's a very expensive investment. Just this year alone, they're spending over $22 billion on SANs. And with this old model on premises SANs, you would probably spend a lot of time doing this upfront capacity planning, trying to figure out how much storage you might need. And in the end, you'd probably end up overbuying for peak demand because you really don't want to get stuck, not having what you need to scale your business. And so now with block express, you don't have to do that anymore. You pay for what you need today, and then you can increase your storage as your business needs change. So that's cost and cost is a very important factor. But really when we're talking to customers and enterprises that are looking for SAN in the cloud, the number one reason that they want to move to the cloud with their SANs and these mission, critical workloads is agility and speed. And it's really transformational for businesses to be able to change the customer experience for their customers and innovate at a much faster pace. And so with the block express product, you get to do that much faster. You can go from an idea to an implementation orders of magnitude faster. Whereas before if you had these workloads on premises, it would take you several weeks just to get the hardware. And then you have to build all this surrounding infrastructure to get it up and running. Now, you don't have to do that anymore. You get your storage in minutes, and if you change your mind, if your business needs change, if your workloads change, you can modify your EBS volume types without interrupting your workload. >> Dave: Thank you for that. So Cami kind of addressed some of this, but I know store admins say, don't touch my SAN, I'm not moving it. This is a big decision for a lot of people. So kind of a two-part question, you know, why now, what do people need to know? And give us the north star close it out with, with where you see the future. >> Ashish: Yeah, so let's, I'll kick things off and then Cami, do jump in. So first of the volume is one part of the story, right? And with IO2 block express, I think we've given customers an extremely compelling offering to go build their mission critical and business critical applications on. We talked about the instance type R5b in terms of giving that instance level performance, but all this is on the foundation of AWS in terms of availability zones and regions. So you think about the constructs and we talk them in terms of building blocks, but our building blocks are really availability zones and regions. And that gives you that core availability infrastructure that you need to build your mission critical and business critical applications. You then take layer on top of that our regional footprint, right. And now you can spin up those workloads globally, if you need to. And then last but not the least, once you're in AWS, you have access to other services. Be it AI, be it ML, be it our relational database services that you can start to think about undifferentiated, heavy lifting. So really you get the smorgasbord really from the availability footprint to global footprint and all the way up to sort of our service stack that you get access to. >> Dave: So that's really thinking out of the box. We're out of time. Cami we'll give you the last word. >> Cami: I just want to say, if you want to learn more about EBS, there's a deep dive session with our principal engineer, Marc Olson later today. So definitely join that. >> Dave: Folks, thanks so much for coming to theCUBE. (in chorus )Thank you. >> Thank you for watching. Keep it right there for more great content from AWS storage day from Seattle.

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is breaking analysis with Dave Vellante. >> ServiceNow is a company that investors love to love, but there's caution in the investor community right now is confusion about transitory inflation and higher interest rates looms. ServiceNow also suffers from a perfection syndrome of sorts. The company has seen that the slightest misstep can cause many freak outs from the investor community. So what it's done is it's architected a financial and communications model that allows it to beat expectations and raise its outlook on a consistent basis. Regardless, ServiceNow appears to be on track to vie for what its CEO Bill McDermott refers to as the next great enterprise software company. Wait, I thought Marc Benioff had his hands on that steering wheel. Hello everyone, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we'll dig into one of the companies we began following almost 10 years ago and provide some thoughts on ServiceNow's March to 15 billion by 2026, which we think is a highly probable achievement. In 2020, despite the contraction in IT spending, SeviceNow outperformed both the S&P 500 and the NASDAQ, but here's a view of 2021. And you can see while the stock has done well since it saw a softness in May and again in early June, and it bounced off that double bottom, it's performance is well below those other benchmarks. This is not a big surprise given the fact that this is a high growth stock and we all know that those names with high multiples get hurt in an inflationary environment, but still the gaps are notable. This is especially true given the performance of the company. It's not often that you see a company with four to $5 billion in revenue growing at a 30% clip, throwing off billions of dollars in free cash flow and increasing operating margins at 100 basis points a year and promising to do that over the next several years. In fact, I don't think we've ever seen that before. I remember years ago, when the trade press was criticizing SeviceNow for its lofty valuation, despite the fact that it was losing money, then CEO, Frank Slootman said to me, "Dave, we can be highly profitable tomorrow if we want it to be, but this is a marathon and we're planning to go big." So essentially Slootman was telling me that this company was going to be an ATM machine that prints money. And that seems to be how it's shaping up. I happened to be at SeviceNow headquarters in 2017, literally the first day on the job for John Donahoe, the CEO replaced Slootman, and I remember while I was there thinking Donahoe was certainly capable, but why the heck I said, would the board let Frank Slootman get away? You know what? It turned great for Slootman, he's at snowflake. Donahoe, I always felt was a consumer guy anyway, and not long for SeviceNow. And now you have this guy, new CEO, Bill McDermott at the helm. He's not a more qualified CEO for the company in my view. About two months ago, McDermott led a virtual investor day. We've had McDermott on theCUBE a couple of times back when he was CEO of SAP and this individual is very compelling. He's got JFK like looks and charisma, but more than that, he's passionate and convincing. And he obviously knows enterprise software. And with conviction, he laid the groundwork for how SeviceNow will get to $10 billion in revenue by 2024 on its way to 15 billion two years thereafter. And one of the big things McDermott's stressed was they're going to get there without any big M&A moves. And that's important because previously the door was left open for that possibility. And now the company is assuring investors that it can get there organically, even with slower growth. So this chart implies no big M&A, and you can see Slootman handed over the reigns at that year one tick on the horizontal axis. This was not a turnaround story. It was a rocket ship at the time. And look at the logos on this chart. This is a revenue view and SeviceNow is aiming to be the fastest to get to 10 billion in software industry history. SeviceNow is valuation just to sort of shift gears here for a minute blew by workdays years ago. Its sites are now set on SAP which is currently valued at 170 billion. And then there's Oracle and Salesforce. They're at around 250 billion and 225 billion in valuation respectively. And these lines back to revenue show the trajectory that these companies took to get to 10 billion. And you can see how SeviceNow plans to get there with those dotted lines. And this is why I call this a collision course with Salesforce, because I think Marc Benioff might say, "Hey, we are ready." Are the next great enterprise software company. We have no plans to give up that post, that mantle anytime soon. I want to share a clip from four years ago. something we've been saying for a long, long time. Roll the clip. >> As they say their goal now is to be four billion by 2020. It feels like, you know, when we first covered SeviceNow knowledge, we said, wow, this company reminds us a lot of the early days of Salesforce. They've got this platform you can develop on this platform, you know, call it paths or, you know, whatever you want to call it, but we at the time said, they're on a collision course with Salesforce. Now there's plenty of room for both of those companies in the marketplace. Salesforce obviously focused predominantly on Salesforce automation, SeviceNow really on workflow automation, but you can see those sort of two markets coming together. >> Now you may be thinking isn't Salesforce's revenue like 5X that of SeviceNow? And yes it is. But I would say a couple of things. One is that Salesforce has gotten to where it is with a lot of M&A, more than 60 acquisitions. At some high profile wants to like slack and Tableau as well as MuleSoft and Heroku back in the day and many others. So we'll see how far McDermott can get before he reverts to his inquisitive self that we saw at SAP. But the second thing I'll say is serviceNow positions itself as the platform of platforms. And the thing is it runs its own cloud. And when it does acquisitions, it replatforms the acquiree into the now platform so that it can drive integrations more seamlessly. That's fundamentally part of its value proposition, a big part of its value proposition. And that means it's somewhat limited on the acquisitions it can make, it has to be pretty selective. Otherwise it's got to do a heavy lift to get it the now platform. It's the power of the models, especially if customers can get to a single CMDB, that configuration database management system, which by the way, a lot of customers never get to that kind of skirt that, but remember SeviceNow is like the ERP for IT. So the more you can get to a single data model, the more effective you're going to be, especially in this data era where you got to put data at the core of your organization, something we've talked about a lot. And the third thing I'll mention the SeviceNow wants to use this platform to attack what it sees as a very large TAM as shown here. Now, a couple of things I want to point out. One is when SeviceNow IPO in 2012, a lot of the analysts said that they were way overvalued because they were in a market. It was help desk and writing tickets was a $2 billion business that was in decline and BMC remedy. Wasn't really that big of a base to attack. In 2013, the Wikibon team took a stab at sizing the TAM. I dug back into the old Wiki. We had well over 30 billion at the time and we expected the company to move deeper into IT and then beyond IT into lines of business and line of business management. Yeah, we felt we were being conservative. We thought the number could be as big as 100 billion, but we felt like putting that number out there, was too aggressive but, you know, it turns out from SeviceNow standpoint, it sees these new software opportunities coming together. And SeviceNow in a way they can double dip both in and beyond their current markets. What I mean by that is it can partner with, for instance, HCM vendors and then at the same time offer employee workflows. They can partner or even purchase RPA tools from specialists like UI path or automation anywhere. And it can go acquire a company which it did like Intel a bot and integrate what I would consider lighter-weight RPA into its platform. So it can manage workflows for best of breed and pick off functionality throughout the software stack. Now what's interesting in this chart is first, the size of the TAM that SeviceNow sees 175 billion, but also how it's now reorganizing its business around workflows, which you see in the left-hand side. This was done of course, to simplify the many, many, many things that you can buy from SeviceNow. But there's also speculation that SeviceNow is leveraging its orchestration and service catalog capabilities, which are meaningful from a revenue standpoint and using them to power these workflows because the way it was organized was both confusing and not as effective as it could be. Now, it's well known that SeviceNow has ITSM this comprises the biggest piece of its revenue pie, probably a couple billion. And it's adding to that with ITSM pro and ITSM enterprise going deeper, deeper into the ITSM space. And it's ITAM business is also doing well against the likes of Datadog and Elastic and Splunk and others and its acquisition of LightStep. It's going to push it further into this space, which is both crowded is morphing into observability as we've been reporting. What's unclear though is how well, for instance, HR and the CSM businesses are doing as sort of standalone businesses, you might remember they used to be standalone businesses with standalone GMs. They've sort of changed that up a little bit. So this is potentially not only a way to simplify, but also shuffle the deck chairs a bit and maybe prop up the non IT workflows, which then allows SeviceNow to show this chart, which essentially says to the street, see, we have this huge TAM and our TAM expansion strategy is working as the overall business is growing nicely yet the mix is shifting toward customer, employee and creator workflows. See how awesome our business is and see how smart we are. So this is possibly a way to hide some of the warts and accentuate the growth. Look, there's not a lot to criticize SeviceNow about, but they've been pretty good at featuring what some perceive as weaknesses. Like for instance, the way it marketed it's a multi-instance and turned that into an advantage as a better model. Even though the whole cloud world was going multitenant and within a ServiceNow you got to really plan new releases, which they drop every six months, although CJ decide. So he's SeviceNows head of products. He did say at the investor meeting, that event that they held last May, that they do certain releases now bi-monthly and even some bi-weekly. So, yeah, maybe a little bit of nitpicking here, but I always liked to question when such changes are made to the reporting structures to the street. And if workflows are the new black, so to speak, I wonder will SeviceNow start pricing by workflows versus what really has been a legacy of, you know, what's your ticket volume and how many agents need access to the model and we'll charge you accordingly? Now, I'm not a service pricing expert and they don't make it easy to figure out that pricing. So let's dig a little bit more on that and keep an eye on it. Now I want to turn to the customers survey data from ETR on ServiceNow. First, here's the latest update on IT spending from ETR, something that we've been tracking for quite some time. We've been consistently saying to expect this year a seven to 8% growth for 2021 IT spend off of last year's contraction. And the latest ETR survey data puts it right at 8%. So we really liked that number. You know, could even be higher push 10% this year. Now, let's look at the spending profile within the ETR dataset. Of the 1100 plus respondents to this quarter, there were 377 SeviceNow customers, and this chart shows the breakdown of net score or spending velocity among those respondents. Remember, net score is a measure of that spending momentum. What it does is it takes the lime green bar, which is adopting new, that says 11% of that 377 customers are adopting ServiceNow for the first time. It takes that lime green and it adds the forest green bar that's growth in spending of 6% or more this half relative to the first half. That's 43% of the customers that have been surveyed here. And then it subtracts out the reds, which is that pinkish is spending less, that's 3%, small number of spending less. And then the bright red is we're leaving the platform. That's a minuscule 1% of the respondents. And you can see the rest in that gray area is flat spending, which is ignored. And so what this does is it calculates out, you'd take the greens minus the reds. It calculates out to a net score 50% for SeviceNow, which is well above that magic 40% elevated mark that we'd like to see. It's rare for a company of this size, except for the hyperscalers. You see AWS and Microsoft and Google are up that high and oh, there's another great enterprise software company at the 45% net score level. Guess who that is, salesforce.com. But anyway, it's rare to see that large of a company have that much spending momentum in the ETR surveys. Now let's take a look at the time series data for ServiceNow. This chart shows the net score granularity over time. So you see the bars, that time series, the blue line is net score. And you can see that it was dragged down during last year's lockdown. As, even though SeviceNow did pretty well last year and it's now spiking back to pre-COVID levels, which is a very positive sign for the company. That red call-out that ETR makes it shows market share. That's an indicator of pervasiveness in the dataset. I'm not overlyconcern there that downturn. I don't think it's a meaningful indicator because ServiceNow revenue is skewed towards a big spender accounts and this is an account unit indicator, if you will not spending level metric. And okay, and here's another reason and why I'm not concerned about SeviceNow is a so-called market share number in the ETR dataset as ETR defines it. This is an X, Y Z view chart that we'd like to show here. We've got net score on the vertical axis and market share in the horizontal plane. This is focusing on enterprise software. So remember that 40% red line is the magic level, anything above that is really indicative of momentum. Oh look, there's Salesforce and ServiceNow on that little collision course that I talked about. Now, CEO McDermott, I would say as by the way, would his predecessors, look, we're a platform of platforms and we partner with other companies, we'll meet at the customer level and sure we'll integrate functions where we think it can add value to customers. But we also understand we have to work with the vendors that our customers are using. So it's all good, plenty of room for growth for all of us, which by the way is true. But I would say this, anyone who's ever been in the enterprise software industry knows that enterprise software execs and their salespeople believe that every dollar spent on software should go to them. And if it's a good market with momentum and growth, they believe they can either organically write software to deliver customer function and value, or they can acquire to fill gaps. So, well, what McDermott would say is true. The likes of Oracle, Microsoft, SAP, Salesforce, Infor, et cetera, they all want as big of a budget piece as possible in the enterprise software space. That's just the way it is. Now, we're going to close with some anecdotal comments from ETR insights, formerly called VENN, which is a round table discussion with CXOs. You can read the summaries when we post on Wikibon and SiliconANGLE but let me summarize. This first comment comes from an assistant VP in retail who says SeviceNow is a key part of their digital transformation. They moved off of BMC remedy two years ago for the global ticketing system. And this person is saying that while the platform is extremely powerful, you got to buy into specific modules to just get one feature that you want. You may not need a lot of the other features, so it starts to get expensive. The other thing this individual is saying is initially, it's a very services heavy project. And so I'll tell you, when you look at the SeviceNow ecosystem the big SIs, the big names, they have big appetites. They love to eat at the trough as I sometimes say, and they want big clients with big budgets. So if you're not one of those top 500 or 700 customers, the big name SIs, you know, they might not be for you. They're not going to pay attention to you. They're going after the big prizes. So what I would suggest is you call up someone like Jason Wojahn of third era, he's the CEO over there and he's got a lot of experience in this space or some more specialized SeviceNow consultancy like them because you're going to get better value for the money. And you're going to get short-term ROI faster with a long-term sustainable ROI as a measurable objective. And I think this last comment sums it up nice, let me to skip over the second one and go just jump to the third one. This basically says the platform is integrated. It's like a mesh. It's not a bunch of stovepipes and cul-de-sacs. Yes it's expensive, but people love it. And like the iPhone, it just works. And their feature pace is accelerating. So pretty strong testimonials, but I want to keep an eye on price transparency any possible backlash there and how the ecosystem evolves. It's something that we called out early on. It's an indicator and SeviceNow needs to continue to invest in that partner network is especially as it builds out its vertical industry practices and expands internationally. Okay, we'll leave it there for now. Remember I publish each week on wikibon.com and siliconangle.com. These episodes they're all available as podcasts. All you got to do is search for breaking analysis podcast. You can always connect with me on Twitter @DVellante or email me @david.vellantesiliconangle.com. Appreciate the comments on LinkedIn. And don't forget to check out etr.plus for all the survey data. This is Dave Vellante for theCUBE insights powered by ETR. Be well, and we'll see you next time. (upbeat music)

(upbeat music) >> Narrator: From around the globe, it's theCUBE, with digital coverage of Postgres Vision 2021, brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE, and continuing our CUBE conversation as part of Postgres Vision 2021, sponsored by EDB, with EDB Chief Technology Officer, Mr. Mark Linster. Mark, good morning to you. How are you doing today? >> I'm doing very fine, very good, sir. >> Excellent. Excellent. Glad you could join us. And we appreciate the time, chance, to look at what's going on in this world of data, which, as you know, continues to evolve quite rapidly. So let's just take that 30,000-foot perspective here to begin with here, and let's talk about data, and management, and what Postgres is doing in terms of accelerating all these innovative techniques, and solutions, and services that we're seeing these days. >> Yeah, so I think it's really... It's a fantastic confluence of factors that we've seen in Postgres, or are seeing in Postgres today, where Postgres has really, really matured over the last couple of years, where things like high availability, parallel processing, use of very high core counts, et cetera, have come together with the drive towards digital transformation, the enormous amounts of data that businesses are dealing with today, so, and then the third factor's really the embracing of open source, right? I mean, Linux has shown the way, and has shown that this is really, really possible. And now we're seeing Postgres as, I think, the next big open source innovation, after Linux, achieving the same type of transformation. So it's really, it's a maturing, it's an acceptance, and the big drive towards dealing with a lot more data as part of digital transformation. >> You know, part of that acceptance that you talk about is about kind of accepting the fact that you have a legacy system that maybe, if you're not going to completely overhaul, you still have to integrate, right? You've got to compliment and start this kind of migration. So in your perspective, or from your perspective, what kind of progress is Postgres allowing in the mindset of CTOs among your client base, or whatever, that their legacy systems can function in this new environment, that all is not lost, and while there is some, perhaps, catching up to do, or some patching you have to do here and there, that it's not as arduous, or not as complex, as might appear to be on the face. >> Well, I think there's, the maturing of Postgres that has really really opened this up, right? Where we're seeing that Postgres can handle these workloads, right? And at the same time, there's a growing number of success cases where companies across all industries, financial services, insurance, manufacturing, retail are using Postgres. So, so you're no longer, you're no longer the first leader who's taken a higher risk, right? Like, five or 10 years ago, Postgres knowledge was not readily available. So if you want Postgres, it was really hard to find somebody who could support you, right? Or find an employee that you could hire who would be the Postgres expert. That's no longer the case. There's plenty of books about Postgres. There's lots of conferences about Postgres. It's a big meetup topic. So, getting know how and getting acceptance amongst your team to use Postgres has become a lot easier, right? At the same time, over 90% of all enterprises today use open source in one way or the other. Which basically means they have open source policies. They have ways to bring open source into the development stream. So that makes it possible, right? Whereas before it was really hard, you had to have an individual who would be evangelized to go, get open source, et cetera, now open source is something that almost everybody is using. You know, from government to financing services, open sources use all over the place, right? So, so now you have something that really matured, right? There's a lot of references out there and then you have the policies that make it possible, right? You have the success stories and now all the pieces have come together to deal with this onslaught of data, right? And then maybe the last thing that that really plays a big role is the cloud. Postgres runs everywhere, right? I mean, it runs from an Arduino to Amazon. Everywhere. And so, which basically means if you want to drive agile business transformation, you call Postgres because you don't have to decide today where it's going to run. You're not locking into a vendor. You're not locking into a limited support system. You can run this thing anywhere. It'll run on your laptop. It'll run on every cloud in the world. You can have it managed, you can have it hosted. You can add have every flavor you want and there's lots of good Postgres support companies out there. So all of these factors together is really what makes us so interesting, right? >> Kubernetes and this marriage, this complimentary, you know relationship right now with Kubernetes, what has that done? You think in terms of providing additional services or at least providing perhaps a new approach or new philosophies, new concepts in terms of database management? >> Well, it's maybe the most the most surprising thing or surprising from the outside. Probably not from the inside, but you think that that Postgres this now 25 year old, database twenty-five year old open source project would be kind of like completely, you know, incompatible with Kubernetes, with containers. But what really happens is Postgres in containers today is the number one database, after Engine X. It is the number two software that is being deployed in containers. So it's really become the workhorse of the whole microservices transformation, right? A 25 year old software, well, it has a very small footprint. It has a lot of interesting features like GIS, document processing, now graph capabilities, common table expressions all those things that are really like cool for developers. And that's probably what leads it to be the number one database in containers. So it's absolutely compatible with Kubernetes. And the whole transformation towards microservices is is like, you know, there's nothing better out there. It runs everywhere and has the most innovative technologies in it. And that's what we're seeing. Also, you go to the annual stack overflow survey of developers, right? It's been consistently number one or number two most loved and most used database, right? So, so what's amazing is that it's this relatively old technology that is, you know, beating everybody else in this digital transformation and then the adoption by developers. >> Just like old dog new tricks, right? It's still winning, right? >> Yeah, yeah, and, and, you know, the elephant is the symbol and this elephant does dance. >> Still dancing that's right. You know, and this is kind of a loaded question but there are a lot of databases out there, a lot of options, obviously from your perspective, you know, Postgres is winning, right? And, and, and from the size of the marketplace it is certainly leading RA leader. In your opinion, you know, what, what is this confluence of factors that have influenced this, this market position if you will, of Postgres or market acceptance of Postgres? >> It's, I mean, it's the, it's a maturing of the core. As I said before, that the transaction rates et cetera, Postgres can handle, are growing every year and are growing dramatic, right? So that's one thing. And then you have it, that Postgres is really, I think, the most reliable and relational database out there as what is my opinion, I'm biased, I guess. And, and it's, it's super quality code but then you add to that the innovation drive. I mean, it was the first one out there with good JSONB support, right? And now it's brought in JSON Path as as part of the new SQL standard. So now you can address JSON data inside your database and the same way you do it inside your browser. And that's pretty cool for developers. Then you combine that with PostGIS, right, which is, I think the most advanced GIS system out there in database. Now, now you got relations, asset compliant, GIS and document. You may say what's so cool about that. Well, what's cool about it is I can do absolutely reliable asset compliant transactions. I can have a fantastic personalization engine through JSONB, and then all my applications need to know where is the transaction? Where is the next store? How far away I'm a form of the parking spot? Right? So now I got a really really nice recipe to put the applications of the future together. You add onto that movements toward supporting graph and supporting other capabilities inside the database. So now you got, you got capability, you've got reliability and you got fantastic innovation. I mean, there's nothing better out there. >> Let's hit the security angle here, 'cause you talked about the asset test, and certainly, you know, those, that criteria is being met. No question about that, whether it's isolation, durability, consistency, whatever, but, but security, I don't have to tell you what a growing concern this is. It's already paramount, but we're seeing every day write stories about, about intrusions and and invasions, if you will. So in terms of providing that layer of security that everybody's looking for right now, you know, this this ultra impenetrable force, if you will, what in your mind, what's Postgres allowing for, in that respect in terms of security, peace of mind, and maybe a little additional comfort that everybody in your space is looking for these? >> So, so look at, look at security with a database like, like multiple layers, right? There's not just, you don't do security only one place. It's like when you go into a bank branch, right? I mean, they do lock the door, they have a camera, there is a gate in front of the safe, there's a safe door. And inside the safe, there is still, again safety deposit boxes with individual locks. The same applies to Postgres, right? Where let's say we start at the heart of it where we can secure and protect tables and data. We're using access control lists and groups and usernames, et cetera. Right? So that's, that's at the heart of it. But then outside of that, we can encrypt the data when on disk or when it's in transit on disk. Most people use the Linux disc encryption systems but there's also good partners out there, like like more metric or others that we work with, that that provide security on disk. And then you go out from there and then you have the securing of the database itself again through the log-ins and the groups. You go out from there and now you have the securing of the hosts that the database is sitting on. Then you'll look at securing the data on the networks through SSL and certificates, et cetera. So that basically there's a multi-layer security model layer that positions Postgres extremely well. And then maybe the last thing is to say it certainly integrates very well with ELDAP, active directory, Kerberos, all the usual suspects that you would use to secure technology inside the enterprise or in an open network, like where people work from home, et cetera. >> You talked about the history about this 25 year old technology, you know, founded back at Cal Berkeley, you know, probably almost some 30 years ago and certainly has evolved. And, and as you have pointed out now as a very mature technology, what do you see though in terms of growth from here? Like, where does it go from here in the next 18 months, 24 months, what what do you think is that next barrier, that challenge that that you think the technology and this open source community wants to take on? >> Well, I think there's there's the continuous effort of making it faster, right? That always happens, right? Every database wants to be faster do more transactions per second, et cetera. And there's a lot of work that has been done there. I mean, just in the last couple of years, Postgres performance has increased by over 50%. Right? So, so transactions per second and that kind of scalability that is going to continue to be, to be a focus, right? And then the other one is leading the implementation of the SQL standards, right? So there'd be the most advanced database, the most innovative database, because, remember for many years now, Postgres has come up with a new release on an annual basis. Other database vendors are now catching up to that, but Postgres has done that for years. So innovation has always been at the heart of it. So we started with JSONB, Key value pair came even before that, PostGis has been around for a long time, graph extensions are going to be the next thing, ingestion of time series data is going to, is going to happen. So there's going to be an ongoing stream of innovations happening. But one thing that I can say is because Postgres is a pure open source project. There's not a hard roadmap, like where it's going to go but where it's going to go is always driven by what people want to have, right? There is no product management department. There's no, there's no great visionary that says, "Oh, this is where we're going to go." No, no. What's going to happen is what people want to have, right? If companies or contributors want to have a certain feature because they need it, well, that's how it's going to happen. And that's really been at the heart of this since Mike Stonebraker, who's an advisor to EDB today, invented it. And then, you know, the open source project got created. This has always been the movement to only focus on things that people actually want to have because if nobody wants to have it, we're just not going to build it because nobody wants it. Right? So when you asked me for the roadmap I believe it's going to be, you know, faster, obviously, always faster, right? Everybody wants faster. And then there's going to be innovation features like making the document stored even better, graph ingestion of large time series, et cetera. That's really what I believe is going to drive it forward. >> Wow. Yeah, the market has spoken and as you point out the market will continue to speak and, and drive that bus. So Mark, thank you for the time today. We certainly appreciate that. And wish EDB continued success at Postgres vision 2021. And thanks for the time. >> Thanks John, it was a pleasure. >> You bet. Mark Linster, joining us, the CTO at EDB. I'm John Walls, you've been watching theCUBE. (upbeat music)

(upbeat pop music) >> Well, hi everyone, John Walls here on "theCUBE" as we continue our CUBE conversations as part of the "AWS Startup Showcase". And we welcome in today Krishna Gade who is the founder and the CEO of Fiddler AI. and Krishna, good to see you today. Thanks for joining us here on the "theCUBE". >> Hey John, thanks so much for inviting us and I'm glad to be here, and looking forward to our conversation. >> Yeah me two, and first off, I want to say congratulations as I look at your company's, this tremendous roster, this list of awards that just keep coming your way. Most recently recognized by "Forbes" as one of the Top 50 AI Companies To Watch here in 2021. I know Gartner called you one of their Cool Companies not too long ago. World Economic Forum also giving you a shout out. So whatever it is you're doing, you're doing it very well, but it's got to feel good I would think, some validation to get all this kind of recognition. >> Absolutely, I know we've been very fortunate to get all the recognition. You know, part of it is also because of the space we are playing in, right? A lot of companies are, you know, operationalizing AI and therefore, you know, this whole point of, you know, explainability monitoring and governance of AI is like forefront and it's in the news for various different reasons. So there's a lot of, you know, good sort of talk that is going on in the press around how one should bear responsible AI. And we are very fortunate to be, you know, in the space and pioneering, you know, some of the technologies here. >> Right. And talking about machine learning monitoring, obviously, in the AI space, and you mentioned explainability. So let's just talk about that concept broadly first off and explain to our viewers what you mean by explainability in this particular context. >> Yeah, that's a good question. So if you think about an AI system, one of the main differences between it and a traditional software system is that it's a black box in the sense that you cannot open it up and read it's code like a traditional software system. The reason is, you know, the AI systems that are built using data and training models which are represented in this non-human readable format. And you cannot really understand how a model is actually making a prediction at any given point of time. So therefore what happens is when you are deploying these AI systems at scale for a variety of use cases, let's say credit underwriting or, you know, screening resumes, or clinical diagnosis which are extremely, you know, important for general human beings. There is a need to understand how the AI system is working. You know, why did it approve a positive person's loan or reject someone's loan? Or why did it reject someone's, you know, resume from, you know, a job screening pipeline? How is it working overall? Right? And so this is where explainability becomes important because you need to understand the AI system, you need a way to probe it, to interrogate it, to understand how the system is making predictions, how is it being influenced by various inputs you're supplying to the system. And so this gamut of technologies or the algorithms that have come across in the last, you know, few years have really matured to a point where, you know, products like Fiddler are developing them and productizing them for the general enterprise to you know, put it in their machine learning and AI workflows. >> So you're talking about context basically, right? I mean, trying to give everybody an idea. This is, you know, kind of where this inputs coming, this is where the problem is, this is where the bottleneck might be, whatever it is, and and doing that in real time. Very efficient operation here. Well, let's talk about the ML world right now and in terms of how it relates to artificial intelligence and this interaction you know, that we're seeing and the, I guess, the problem that you are trying to fix, if you will, in terms of machine learning monitoring. So let's just deal with that first off. When you look at somebody's architecture and somebody set up, what do you see? What are you looking for? And what kind of problems are you trying to solve for your clients? >> Yeah. So just following up what I said. The two main problems with operationalizing AI is one is the black box nature of AI, which I already talked about. The other problem is that the AI system is fundamentally a stochastic system or a probabilistic system. By that, I mean that its performance, you know, its predictions can change over time based on the data it is receiving. So it's not a deterministic system like traditional software systems where you expect the same output all the time, right? So when you have a system that is stochastic in nature where its performance can vary based on the data it is receiving, then you are in a situation where you have uncertainty, right? You know, you let's say you have an AI system that is deployed for serving a credit underwriting model or a fraud, you know, detection use case. And you see that, okay, sometimes accuracy is up, sometimes accuracy is down. You know, when do you want, when do you trust your predictions, when you're not. How do you know if the model is actually performing in the same manner that you trained it? All of these issues open up the need for continuous monitoring of these AI systems, because without which you may have AI systems making bad predictions for your users, hurting your business metrics, potentially making biased decisions that can put your company into a compliance or a brand reputation risk scenario. To avoid all of these things you can actually monitor these AI systems continuously so that you know exactly if they're performing the way you expect them to be. Do you to retrain them right now, right? Or do you need to shut them down because they are actually not predicting the way that you expect them to be? So this is actually very important. And so that's what Fiddler tries to solve for our customers by helping them operationalize AI with full visibility and explainability, right? So you can essentially install Fiddler in your workflow to continuously monitor your AI systems and analyze and explain them when you have questions about how they're working. >> I mean, you talked about governance earlier a little bit, you know, compliance, obviously a great critical issue, big concern, fraud detection. Security, just in general here, as we know, I mean, we keep almost every day it seems like we're hearing about some kinds of security intrusion. So, in terms of identifying vulnerabilities or in terms of identifying anomalies, whatever it might be, what kind of work are you doing in that space to give your client base the kind of comfort and the peace of mind that everybody's searching for these days? >> Right, I mean, if you step back a little bit, John, we are truly living in the age of algorithms, right? So everything that we interact with on a day-to-day basis, the movies we watch, or when we request an Uber driver, or when we go to a financial institution and request for a loan application or a mortgage, there are algorithms behind the scenes that are processing our requests and delivering the experiences that we have. Now, increasingly these algorithms are becoming AI based algorithms. And when you have these AI based algorithms, they're trained on this data that's available, that an institution may collect from their users, or they may buy from other third parties. And when you develop these AI systems based on this data, if this data is not equally distributed amongst all different ethnicity backgrounds, people coming from different cultures, different religions, different races, different genders, you may actually build systems that can make very different decisions for different individuals based on like this bias that could creep into them. And so this actually needs, this means that at the end of the day, you can actually create a dystopian world where, you know, some people get like really great decisions from your systems, where some people are left out, right? So therefore, you know, this aspect of governing your AI systems so that you're validating what you're building upfront. You're validating the data that you're using to train the systems. You're continuously monitoring the systems there so that they're actually producing the right outcomes for your users. And then you can actually explain if some customer asks you or some regulator or a third party asks you how your system is working. It's very very important. This is an emerging area in industry, certain sectors already have this, for example, financial services. It's in companies like banks, where it is mandated to have model governance, so that every model that they are deploying needs to be validated and needs to be monitored. And we are seeing the emergence of generally AI governance creeping into other sectors as well. And so this is like a broader topic that covers explainability, covers monitoring, covers detecting bias in your AI systems and ensuring that you're building safe and responsible AI for your customers and your organization. >> Yeah, I find the bias point really interesting, actually, because I hadn't really thought about these prejudices or subjectivities, you know, it might bring to our work with us in terms of what we look at, what we ignore, what we process, how we don't. But it's a really interesting point you just raised. So thank you for that. And then there's also the kind of issue with data drift too a little bit, right? It's like, where did it go (laughing)? >> Right. >> What are we doing here? What happened to it? So maybe if you could talk about that a little bit in terms of all this data that's coming in and corralling it, right? Making sure that it stays organized and stays in a way that you can analyze and process it, and then glean insight from. >> Yeah, data drift is one of the main reasons why AI systems deteriorate in performance. So for example, let's say I'm trying to build a recommendation system that predicts the items that you want to buy when you go to an E-commerce website. Now, if I have used data pre-COVID, then the user behavior was very different, right? That kind of items people were probably buying before you know, February, 2020 was like probably much different than the kind of items that people were buying after it. So what happens is when you train your AI systems on datasets that are older but then that data has changed ever since because of an event like COVID-19 has happened, or some other seasonality has kicked in, then your AI systems are seeing different distribution data. For example, you may see that suddenly, you know, people who were shopping, let's say, in March or April last year, people were shopping for all kinds of, you know, toilet paper and all kinds of things to stock up, you know, to be ready for lockdown, right? And maybe they were not buying similar amounts in there previously. So therefore, if you have an inventory management system based on AI or an E-commerce recommendation system based on AI, you know, they would see data drift, because the buying patterns are different. The amount of stuff that people are buying in terms of toilet paper has completely shifted. And so their model is actually, may not be predicting as accurately as it would, right? So therefore identifying this data drift and alerting your AI engineer so that they can be prepared for this is very important. Otherwise, what you would see is if you're an E-commerce company, this has actually happened, you know? Instacart, a grocery delivery company and another company www.etsy.com, they blogged about it where they have seen their models go down in accuracy from 90% to 65% when this data shift happened, you know, especially during COVID-19. And so you need the ability to continuously monitor for drift so that when you can catch these things earlier, and then, you know, save your business from losing, you know, in terms of business metrics like such as number of sales that you may be making, number of bad recommendations that your systems are making to your users. >> So we've talked a lot about these various components of monitoring of which, you know, all of which you do extremely well. And I was reading earlier, just a little bit about the company, and we talked about accountability. We've already talked about that. We talked about fraud detection, we talked about reliability. There was also a point about ethical considerations, you know, and so I was interested in that, hearing from you about that in terms of why that's a pillar of your service or what exactly that was pointed toward in terms of monitoring, and what you can do. >> Right. So, I guess I'll just go back to like a famous quote from Marc Andreessen. He mentioned, you know, a few years ago that software is eating the world, right? Now, what's happening is AI is eating software. All the software that we are consuming is becoming AI based software, because basically at the end of the day some intelligence is being baked into the software to make it, you know, predict more interesting things for you to make those decisions. Instead of rule-based decisions, make it more AI based decisions. And so therefore it is very important that when we are building the software, we need to use ethical practices. You know, we need to know how, where you're collecting the data from. It can be very dangerous if you don't do it and you can land into trouble. And we have seen these incidents many times, right? For example, in 2019, when Apple and Goldman Sachs came up with a credit card, a lot of customers complained about gender bias with respect to the credit card limits that the algorithm was setting. You know, in the same household, the husband and wife were getting 10 times in terms of a difference between the credit limit between a male and a female, right? Even though they probably had similar salary ranges, similar FICO scores, right? So if you do not actually make sure that, you know, you're collecting data from the right sources that your datasets are not outbalanced. If your models, if your algorithms are tested for bias you know, before hand, before you deploy them and then you're continuously monitoring them, these are all ethical practices. These are all the responsible ways of building your AI. You can actually, you know, land into trouble. Your customers will complain about it. You know, you would lose your brand reputation. And at the end of the day you'll be essentially, and instead of actually adding value to the customers, you may be actually hurting them, right? And so this is actually why it's so important, and it's become more important when the more stakes, the higher the stakes are, right? You know, for example, when it's being used for criminal justice scenarios or when it's being used for clinical diagnosis scenarios. Being able to ensure that the system is making unbiased decisions is very, very important. >> Well, before I let you go, too, I like you to touch base on your AWS relationship about, you know, what was the Genesis of that. And currently what it is that you're working on together to provide this great value to your customers. >> Absolutely. So the follow-up to this ethical AI is like Amazon as a company is interested in pursuing, you know, the responsible AI but, you know, they have a lot of AI products. So they are looking for, you know, fostering a community and ecosystem of AI technologies. And in that hypothesis they actually invested in Fiddler last year in terms of enabling us to develop this explainable AI and ethical AI technology. And so we are working with Alexa Fund and also like AWS ecosystem in terms of partnering with how effectively Fiddler can be delivered to other AWS customers through, like, through their marketplace and other sort of areas that we can distribute the software. So it's a great partnership. We are very, very excited about the opportunity to work with Alexa Fund as well as the AWS ecosystem. It increases another opportunity for us to enable a lot more customers than we than we can otherwise. So this is a great win-win situation for both Amazon and Fiddler. >> Well, it sure is. And congratulations on that and developing that partnership. I know it's working well for your clients and it's working well for Fiddler AI obviously by the number of recognitions that have been coming your way. So Krishna, we wish you continued success and thanks for the time here today on "theCUBE". >> Yep. Thank you so much, John. It was a pleasure talking to you today. >> I enjoyed it. Thank you. John Walls here wrapping up our conversation with Fiddler AI's Krishna Gade, talking today about machine learning monitoring on the "AWS Startup Showcase". (upbeat pop music)