(soft music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain, everybody. We're here at the Fira in MWC23. Is just an amazing day. This place is packed. They said 80,000 people. I think it might even be a few more walk-ins. I'm Dave Vellante, Lisa Martin is here, David Nicholson. But right now we have the Analyst Hot Takes with three friends of theCUBE. Chris Lewis is back again with me in the co-host seat. Zeus Kerravala, analyst extraordinaire. Great to see you, Z. and Sarbjeet SJ Johal. Good to see you again, theCUBE contributor. And that's my new name for him. He says that is his nickname. Guys, thanks for coming back on. We got the all male panel, sorry, but it is what it is. So Z, is this the first time you've been on it at MWC. Take aways from the show, Hot Takes. What are you seeing? Same wine, new bottle? >> In a lot of ways, yeah. I mean, I was talking to somebody this earlier that if you had come from like MWC five years ago to this year, a lot of the themes are the same. Telco transformation, cloud. I mean, 5G is a little new. Sustainability is certainly a newer theme here. But I think it highlights just the difficulty I think the telcos have in making this transformation. And I think, in some ways, I've been unfair to them in some degree 'cause I've picked on them in the past for not moving fast enough. These are, you know, I think these kind of big transformations almost take like a perfect storm of things that come together to happen, right? And so, in the past, we had technologies that maybe might have lowered opex, but they're hard to deploy. They're vertically integrated. We didn't have the software stacks. But it appears today that between the cloudification of, you know, going to cloud native, the software stacks, the APIs, the ecosystems, I think we're actually in a position to see this industry finally move forward. >> Yeah, and Chris, I mean, you have served this industry for a long time. And you know, when you, when you do that, you get briefed as an analyst, you actually realize, wow, there's a lot of really smart people here, and they're actually, they have challenges, they're working through it. So Zeus was saying he's been tough on the industry. You know, what do you think about how the telcos have evolved in the last five years? >> I think they've changed enormously. I think the problem we have is we're always looking for the great change, the big step change, and there is no big step change in a way. What telcos deliver to us as individuals, businesses, society, the connectivity piece, that's changed. We get better and better and more reliable connectivity. We're shunting a load more capacity through. What I think has really changed is their attitude to their suppliers, their attitude to their partners, and their attitude to the ecosystem in which they play. Understanding that connectivity is not the end game. Connectivity is part of the emerging end game where it will include storage, compute, connect, and analytics and everything else. So I think the realization that they are not playing their own game anymore, it's a much more open game. And some things they will continue to do, some things they'll stop doing. We've seen them withdraw from moving into adjacent markets as much as we used to see. So a lot of them in the past went off to try and do movies, media, and a lot went way way into business IT stuff. They've mainly pulled back from that, and they're focusing on, and let's face it, it's not just a 5G show. The fixed environment is unbelievably important. We saw that during the pandemic. Having that fixed broadband connection using wifi, combining with cellular. We love it. But the problem as an industry is that the users often don't even know the connectivity's there. They only know when it doesn't work, right? >> If it's not media and it's not business services, what is it? >> Well, in my view, it will be enabling third parties to deliver the services that will include media, that will include business services. So embedding the connectivity all the way into the application that gets delivered or embedding it so the quality mechanism deliver the gaming much more accurately or, I'm not a gamer, so I can't comment on that. But no, the video quality if you want to have a high quality video will come through better. >> And those cohorts will pay for that value? >> Somebody will pay somewhere along the line. >> Seems fuzzy to me. >> Me too. >> I do think it's use case dependent. Like you look at all the work Verizon did at the Super Bowl this year, that's a perfect case where they could have upsold. >> Explain that. I'm not familiar with it. >> So Verizon provided all the 5G in the Super Bowl. They provided a lot of, they provided private connectivity for the coaches to talk to the sidelines. And that's a mission critical application, right? In the NFL, if one side can't talk, the other side gets shut down. You can't communicate with the quarterback or the coaches. There's a lot of risk at that. So, but you know, there's a case there, though, I think where they could have even made that fan facing. Right? And if you're paying 2000 bucks to go to a game, would you pay 50 bucks more to have a higher tier of bandwidth so you can post things on social? People that go there, they want people to know they were there. >> Every football game you go to, you can't use your cell. >> Analyst: Yeah, I know, right? >> All right, let's talk about developers because we saw the eight APIs come out. I think ISVs are going to be a big part of this. But it's like Dee Arthur said. Hey, eight's better than zero, I guess. Okay, so, but so the innovation is going to come from ISVs and developers, but what are your hot takes from this show and now day two, we're a day and a half in, almost two days in. >> Yeah, yeah. There's a thing that we have talked, I mentioned many times is skills gravity, right? Skills have gravity, and also, to outcompete, you have to also educate. That's another theme actually of my talks is, or my research is that to puts your technology out there to the practitioners, you have to educate them. And that's the only way to democratize your technology. What telcos have been doing is they have been stuck to the proprietary software and proprietary hardware for too long, from Nokia's of the world and other vendors like that. So now with the open sourcing of some of the components and a few others, right? And they're open source space and antenna, you know? Antennas are becoming software now. So with the invent of these things, which is open source, it helps us democratize that to the other sort of skirts of the practitioners, if you will. And that will bring in more applications first into the IOT space, and then maybe into the core sort of California, if you will. >> So what does a telco developer look like? I mean, all the blockchain developers and crypto developers are moving into generative AI, right? So maybe those worlds come together. >> You'd like to think though that the developers would understand everything's network centric today. So you'd like to think they'd understand that how the network responds, you know, you'd take a simple app like Zoom or something. If it notices the bandwidth changes, it should knock down the resolution. If it goes up it, then you can add different features and things and you can make apps a lot smarter that way. >> Well, G2 was saying today that they did a deal with Mercedes, you know this probably better than I do, where they're going to embed WebEx in the car. And if you're driving, it'll shut off the camera. >> Of course. >> I'm like, okay. >> I'll give you a better example though. >> But that's my point. Like, isn't there more that we can do? >> You noticed down on the SKT stand the little helicopter. That's a vertical lift helicopter. So it's an electric vertical lift helicopter. Just think of that for a second. And then think of the connectivity to control that, to securely control that. And then I was recently at an event with Zeus actually where we saw an air traffic control system where there was no people manning the tower. It was managed by someone remotely with all the cameras around them. So managing all of those different elements, we call it IOT, but actually it's way more than what we thought of as IOT. All those components connecting, communicating securely and safely. 'Cause I don't want that helicopter to come down on my head, do you? (men laugh) >> Especially if you're in there. (men laugh) >> Okay, so you mentioned sustainability. Everybody's talking about power. I don't know if you guys have a lot of experience around TCO, but I'm trying to get to, well, is this just because energy costs are so high, and then when the energy becomes cheap again, nobody's going to pay any attention to it? Or is this the real deal? >> So one of the issues around the, if we want to experience all that connectivity locally or that helicopter wants to have that connectivity, we have to ultimately build denser, more reliable networks. So there's a CapEx, we're going to put more base stations in place. We need more fiber in the ground to support them. Therefore, the energy consumption will go up. So we need to be more efficient in the use of energy. Simple as that. >> How much of the operating expense is energy? Like what percent of it? Is it 10%? Is it 20%? Is it, does anybody know? >> It depends who you ask and it depends on the- >> I can't get an answer to that. I mean, in the enterprise- >> Analyst: The data centers? >> Yeah, the data centers. >> We have the numbers. I think 10 to 15%. >> It's 10 to 12%, something like that. Is it much higher? >> I've got feeling it's 30%. >> Okay, so if it's 30%, that's pretty good. >> I do think we have to get better at understanding how to measure too. You know, like I was talking with John Davidson at Sysco about this that every rev of silicon they come out with uses more power, but it's a lot more dense. So at the surface, you go, well, that's using a lot more power. But you can consolidate 10 switches down to two switches. >> Well, Intel was on early and talking about how they can intelligently control the cores. >> But it's based off workload, right? That's the thing. So what are you running over it? You know, and so, I don't think our industry measures that very well. I think we look at things kind of boxed by box versus look at total consumption. >> Well, somebody else in theCUBE was saying they go full throttle. That the networks just say just full throttle everything. And that obviously has to change from the power consumption standpoint. >> Obviously sustainability and sensory or sensors from IOT side, they go hand in hand. Just simple examples like, you know, lights in the restrooms, like in public areas. Somebody goes in there and just only then turns. The same concept is being applied to servers and compute and storage and every aspects and to networks as well. >> Cell tower. >> Yeah. >> Cut 'em off, right? >> Like the serverless telco? (crosstalk) >> Cell towers. >> Well, no, I'm saying, right, but like serverless, you're not paying for the compute when you're not using it, you know? >> It is serverless from the economics point of view. Yes, it's like that, you know? It goes to the lowest level almost like sleep on our laptops, sleep level when you need more power, more compute. >> I mean, some of that stuff's been in networking equipment for a long time, it just never really got turned on. >> I want to ask you about private networks. You wrote a piece, Athenet was acquired by HPE right after Dell announced a relationship with Athenet, which was kind of, that was kind of funny. And so a good move, good judo move by by HP. I asked Dell about it, and they said, look, we're open. They said the right things. We'll see, but I think it's up to HP. >> Well, and the network inside Dell is. >> Yeah, okay, so. Okay, cool. So, but you said something in that article you wrote on Silicon Angle that a lot of people feel like P5G is going to basically replace wireless or cannibalize wireless. You said you didn't agree with that. Explain why? >> Analyst: Wifi. >> Wifi, sorry, I said wireless. >> No, that's, I mean that's ridiculous. Pat Gelsinger said that in his last VMware, which I thought was completely irresponsible. >> That it was going to cannibalize? >> Cannibalize wifi globally is what he said, right? Now he had Verizon on stage with him, so. >> Analyst: Wifi's too inexpensive and flexible. >> Wifi's cheap- >> Analyst: It's going to embed really well. Embedded in that. >> It's reached near ubiquity. It's unlicensed. So a lot of businesses don't want to manage their own spectrum, right? And it's great for this, right? >> Analyst: It does the job. >> For casual connectivity. >> Not today. >> Well, it does for the most part. Right now- >> For the most part. But never at these events. >> If it's engineered correctly, it will. Right? Where you need private 5G is when reliability is an absolute must. So, Chris, you and I visited the Port of Rotterdam, right? So they're putting 5G, private 5G there, but there's metal containers everywhere, right? And that's going to disrupt it. And so there are certain use cases where it makes sense. >> I've been in your basement, and you got some pretty intense equipment in there. You have private 5G in there. >> But for carpeted offices, it does not make sense to bring private. The economics don't make any sense. And you know, it runs hot. >> So where's it going to be used? Give us some examples of where we should be looking for. >> The early ones are obviously in mining, and you say in ports, in airports. It broadens cities because you've got so many moving parts in there, and always think about it, very expensive moving parts. The cranes in the port are normally expensive piece of kits. You're moving that, all that logistics around. So managing that over a distance where the wifi won't work over the distance. And in mining, we're going to see enormous expensive trucks moving around trying to- >> I think a great new use case though, so the Cleveland Browns actually the first NFL team to use it for facial recognition to enter the stadium. So instead of having to even pull your phone out, it says, hey Dave Vellante. You've got four tickets, can we check you all in? And you just walk through. You could apply that to airports. You could do put that in a hotel. You could walk up and check in. >> Analyst: Retail. >> Yeah, retail. And so I think video, realtime video analytics, I think it's a perfect use case for that. >> But you don't need 5G to do that. You could do that through another mechanism, couldn't you? >> You could do wire depending on how mobile you want to do it. Like in a stadium, you're pulling those things in and out all the time. You're moving 'em around and things, so. >> Yeah, but you're coming in at a static point. >> I'll take the contrary view here. >> See, we can't even agree on that. (men laugh) >> Yeah, I love it. Let's go. >> I believe the reliability of connection is very important, right? And the moving parts. What are the moving parts in wifi? We have the NIC card, you know, the wifi card in these suckers, right? In a machine, you know? They're bigger in size, and the radios for 5G are smaller in size. So neutralization is important part of the whole sort of progress to future, right? >> I think 5G costs as well. Yes, cost as well. But cost, we know that it goes down with time, right? We're already talking about 60, and the 5G stuff will be good. >> Actually, sorry, so one of the big boom areas at the moment is 4G LTE because the component price has come down so much, so it is affordable, you can afford to bring it all together. People don't, because we're still on 5G, if 5G standalone everywhere, you're not going to get a consistent service. So those components are unbelievably important. The skillsets of the people doing integration to bring them all together, unbelievably important. And the business case within the business. So I was talking to one of the heads of one of the big retail outlets in the UK, and I said, when are you going to do 5G in the stores? He said, well, why would I tear out all the wifi? I've got perfectly functioning wifi. >> Yeah, that's true. It's already there. But I think the technology which disappears in front of you, that's the best technology. Like you don't worry about it. You don't think it's there. Wifi, we think we think about that like it's there. >> And I do think wifi 5G switching's got to get easier too. Like for most users, you don't know which is better. You don't even know how to test it. And to your point, it does need to be invisible where the user doesn't need to think about it, right? >> Invisible. See, we came back to invisible. We talked about that yesterday. Telecom should be invisible. >> And it should be, you know? You don't want to be thinking about telecom, but at the same time, telecoms want to be more visible. They want to be visible like Netflix, don't they? I still don't see the path. It's fuzzy to me the path of how they're not going to repeat what happened with the over the top providers if they're invisible. >> Well, if you think about what telcos delivers to consumers, to businesses, then extending that connectivity into your home to help you support secure and extend your connection into Zeus's basement, whatever it is. Obviously that's- >> His awesome setup down there. >> And then in the business environment, there's a big change going on from the old NPLS networks, the old rigid structures of networks to SD1 where the control point is moved outside, which can be under control of the telco, could be under the control of a third party integrator. So there's a lot changing. I think we obsess about the relative role of the telco. The demand is phenomenal for connectivity. So address that, fulfill that. And if they do that, then they'll start to build trust in other areas. >> But don't you think they're going to address that and fulfill that? I mean, they're good at it. That's their wheelhouse. >> And it's a 1.6 trillion market, right? So it's not to be sniffed at. That's fixed on mobile together, obviously. But no, it's a big market. And do we keep changing? As long as the service is good, we don't move away from it. >> So back to the APIs, the eight APIs, right? >> I mean- >> Eight APIs is a joke actually almost. I think they released it too early. The release release on the main stage, you know? Like, what? What is this, right? But of course they will grow into hundreds and thousands of APIs. But they have to spend a lot of time and effort in that sort of context. >> I'd actually like to see the GSMA work with like AWS and Microsoft and VMware and software companies and create some standardization across their APIs. >> Yeah. >> I spoke to them yes- >> We're trying to reinvent them. >> Is that not what they're doing? >> No, they said we are not in the business of a defining standards. And they used a different term, not standard. I mean, seriously. I was like, are you kidding me? >> Let's face it, there aren't just eight APIs out there. There's so many of them. The TM forum's been defining when it's open data architecture. You know, the telcos themselves are defining them. The standards we talked about too earlier with Danielle. There's a lot of APIs out there, but the consistency of APIs, so we can bring them together, to bring all the different services together that will support us in our different lives is really important. I think telcos will do it, it's in their interest to do it. >> All right, guys, we got to wrap. Let's go around the horn here, starting with Chris, Zeus, and then Sarbjeet, just bring us home. Number one hot take from Mobile World Congress MWC23 day two. >> My favorite hot take is the willingness of all the participants who have been traditional telco players who looked inwardly at the industry looking outside for help for partnerships, and to build an ecosystem, a more open ecosystem, which will address our requirements. >> Zeus? >> Yeah, I was going to talk about ecosystem. I think for the first time ever, when I've met with the telcos here, I think they're actually, I don't think they know how to get there yet, but they're at least aware of the fact that they need to understand how to build a big ecosystem around them. So if you think back like 50 years ago, IBM and compute was the center of everything in your company, and then the ecosystem surrounded it. I think today with digital transformation being network centric, the telcos actually have the opportunity to be that center of excellence, and then build an ecosystem around them. I think the SIs are actually in a really interesting place to help them do that 'cause they understand everything top to bottom that I, you know, pre pandemic, I'm not sure the telcos were really understand. I think they understand it today, I'm just not sure they know how to get there. . >> Sarbjeet? >> I've seen the lot of RN demos and testing companies and I'm amazed by it. Everything is turning into software, almost everything. The parts which are not turned into software. I mean every, they will soon. But everybody says that we need the hardware to run something, right? But that hardware, in my view, is getting miniaturized, and it's becoming smaller and smaller. The antennas are becoming smaller. The equipment is getting smaller. That means the cost on the physicality of the assets is going down. But the cost on the software side will go up for telcos in future. And telco is a messy business. Not everybody can do it. So only few will survive, I believe. So that's what- >> Software defined telco. So I'm on a mission. I'm looking for the monetization path. And what I haven't seen yet is, you know, you want to follow the money, follow the data, I say. So next two days, I'm going to be looking for that data play, that potential, the way in which this industry is going to break down the data silos I think there's potential goldmine there, but I haven't figured out yet. >> That's a subject for another day. >> Guys, thanks so much for coming on. You guys are extraordinary partners of theCUBE friends, and great analysts and congratulations and thank you for all you do. Really appreciate it. >> Analyst: Thank you. >> Thanks a lot. >> All right, this is a wrap on day two MWC 23. Go to siliconangle.com for all the news. Where Rob Hope and team are just covering all the news. John Furrier is in the Palo Alto studio. We're rocking all that news, taking all that news and putting it on video. Go to theCUBE.net, you'll see everything on demand. Thanks for watching. This is a wrap on day two. We'll see you tomorrow. (soft music)

>> Hello everyone. Welcome to theCUBEs coverage of Compute Engineered for your Hybrid World sponsored by HPE and Intel. Today we're going to dive into advanced performance of VDI with the fourth gen Intel Zion scalable processors. Hello I'm John Furrier, the host of theCUBE. My guests today are Alan Chu, Director of Data Center Performance and Competition for Intel as well as Denis Kondakov who's the VDI product manager at HPE, and also joining us is Cynthia Sustiva, CAD/CAM product manager at HPE. Thanks for coming on, really appreciate you guys taking the time. >> Thank you. >> So accelerating VDI to the Edge. That's the topic of this topic here today. Let's get into it, Dennis, tell us about the new HPE ProLiant DL321 Gen 11 server. >> Okay, absolutely. Hello everybody. So HP ProLiant DL320 Gen 11 server is the new age center CCO and density optimized compact server, compact form factor server. It enables to modernize and power at the next generation of workloads in the diverse rec environment at the Edge in an industry standard designed with flexible scale for advanced graphics and compute. So it is one unit, one processor rec optimized server that can be deployed in the enterprise data center as well as at the remote office at end age. >> Cynthia HPE has announced another server, the ProLiant ML350. What can you tell us about that? >> Yeah, so the HPE ProLiant ML350 Gen 11 server is a powerful tower solution for a wide range of workloads. It is ideal for remote office compute with NextGen performance and expandability with two processors in tower form factor. This enables the server to be used not only in the data center environment, but also in the open office space as a powerful workstation use case. >> Dennis mentioned both servers are empowered by the fourth gen Intel Zion scale of process. Can you talk about the relationship between Intel HPE to get this done? How do you guys come together, what's behind the scenes? Share as much as you can. >> Yeah, thanks a lot John. So without a doubt it takes a lot to put all this together and I think the partnership that HPE and Intel bring together is a little bit of a critical point for us to be able to deliver to our customers. And I'm really thrilled to say that these leading Edge solutions that Dennis and Cynthia just talked about, they're built on the foundation of our fourth Gen Z on scalable platform that's trying to meet a wide variety of deployments for today and into the future. So I think the key point of it is we're together trying to drive leading performance with built-in acceleration and in order to deliver a lot of the business values to our customers, both HP and Intels, look to scale, drive down costs and deliver new services. >> You got the fourth Gen Z on, you got the Gen 11 and multiple ProLiants, a lot of action going on. Again, I love when these next gens come out. Can each of you guys comment and share what are the use cases for each of the systems? Because I think what we're looking at here is the next level innovation. What are some of the use cases on the systems? >> Yeah, so for the ML350, in the modern world where more and more data are generated at the Edge, we need to deploy computer infrastructure where the data is generated. So smaller form factor service will satisfy the requirements of S&B customers or remote and branch offices to deliver required performance redundancy where we're needed. This type of locations can be lacking dedicated facilities with strict humidity, temperature and noise isolation control. The server, the ML350 Gen 11 can be used as a powerful workstation sitting under a desk in the office or open space as well as the server for visualized workloads. It is a productivity workhorse with the ability to scale and adapt to any environment. One of the use cases can be for hosting digital workplace for manufacturing CAD/CAM engineering or oil and gas customers industry. So this server can be used as a high end bare metal workstation for local end users or it can be virtualized desktop solution environments for local and remote users. And talk about the DL320 Gen 11, I will pass it on to Dennis. >> Okay. >> Sure. So when we are talking about age of location we are talking about very specific requirements. So we need to provide solution building blocks that will empower and performance efficient, secure available for scaling up and down in a smaller increments than compared to the enterprise data center and of course redundant. So DL 320 Gen 11 server is the perfect server to satisfy all of those requirements. So for example, S&B customers can build a video solution, for example starting with just two HP ProLiant TL320 Gen 11 servers that will provide sufficient performance for high density video solution and at the same time be redundant and enable it for scaling up as required. So for VGI use cases it can be used for high density general VDI without GP acceleration or for a high performance VDI with virtual VGPU. So thanks to the modern modular architecture that is used on the server, it can be tailored for GPU or high density storage deployment with software defined compute and storage environment and to provide greater details on your Intel view I'm going to pass to Alan. >> Thanks a lot Dennis and I loved how you're both seeing the importance of how we scale and the applicability of the use cases of both the ML350 and DL320 solutions. So scalability is certainly a key tenant towards how we're delivering Intel's Zion scalable platform. It is called Zion scalable after all. And we know that deployments are happening in all different sorts of environments. And I think Cynthia you talked a little bit about kind of a environmental factors that go into how we're designing and I think a lot of people think of a traditional data center with all the bells and whistles and cooling technology where it sometimes might just be a dusty closet in the Edge. So we're defining fortunes you see on scalable to kind of tackle all those different environments and keep that in mind. Our SKUs range from low to high power, general purpose to segment optimize. We're supporting long life use cases so that all goes into account in delivering value to our customers. A lot of the latency sensitive nature of these Edge deployments also benefit greatly from monolithic architectures. And with our latest CPUs we do maintain quite a bit of that with many of our SKUs and delivering higher frequencies along with those SKUs optimized for those specific workloads in networking. So in the end we're looking to drive scalability. We're looking to drive value in a lot of our end users most important KPIs, whether it's latency throughput or efficiency and 4th Gen Z on scalable is looking to deliver that with 60 cores up to 60 cores, the most builtin accelerators of any CPUs in the market. And really the true technology transitions of the platform with DDR5, PCIE, Gen five and CXL. >> Love the scalability story, love the performance. We're going to take a break. Thanks Cynthia, Dennis. Now we're going to come back on our next segment after a quick break to discuss the performance and the benefits of the fourth Gen Intel Zion Scalable. You're watching theCUBE, the leader in high tech coverage, be right back. Welcome back around. We're continuing theCUBE's coverage of compute engineer for your hybrid world. I'm John Furrier, I'm joined by Alan Chu from Intel and Denis Konikoff and Cynthia Sistia from HPE. Welcome back. Cynthia, let's start with you. Can you tell us the benefits of the fourth Gen Intel Zion scale process for the HP Gen 11 server? >> Yeah, so HP ProLiant Gen 11 servers support DDR five memory which delivers increased bandwidth and lower power consumption. There are 32 DDR five dim slots with up to eight terabyte total on ML350 and 16 DDR five dim slots with up to two terabytes total on DL320. So we deliver more memory at a greater bandwidth. Also PCIE 5.0 delivers an increased bandwidth and greater number of lanes. So when we say increased number of lanes we need to remember that each lane delivers more bandwidth than lanes of the previous generation plus. Also a flexible storage configuration on HPDO 320 Gen 11 makes it an ideal server for establishing software defined compute and storage solution at the Edge. When we consider a server for VDI workloads, we need to keep the right balance between the number of cords and CPU frequency in order to deliver the desire environment density and noncompromised user experience. So the new server generation supports a greater number of single wide and global wide GPU use to deliver more graphic accelerated virtual desktops per server unit than ever before. HPE ProLiant ML 350 Gen 11 server supports up to four double wide GPUs or up to eight single wide GPUs. When the signing GPU accelerated solutions the number of GPUs available in the system and consistently the number of BGPUs that can be provisioned for VMs in the binding factor rather than CPU course or memory. So HPE ProLiant Gen 11 servers with Intel fourth generation science scalable processors enable us to deliver more virtual desktops per server than ever before. And with that I will pass it on to Alan to provide more details on the new Gen CPU performance. >> Thanks Cynthia. So you brought up I think a really great point earlier about the importance of achieving the right balance. So between the both of us, Intel and HPE, I'm sure we've heard countless feedback about how we should be optimizing efficiency for our customers and with four Gen Z and scalable in HP ProLiant Gen 11 servers I think we achieved just that with our built-in accelerator. So built-in acceleration delivers not only the revolutionary performance, but enables significant offload from valuable core execution. That offload unlocks a lot of previously unrealized execution efficiency. So for example, with quick assist technology built in, running engine X, TLS encryption to drive 65,000 connections per second we can offload up to 47% of the course that do other work. Accelerating AI inferences with AMX, that's 10X higher performance and we're now unlocking realtime inferencing. It's becoming an element in every workload from the data center to the Edge. And lastly, so with faster and more efficient database performance with RocksDB, we're executing with Intel in-memory analytics accelerator we're able to deliver 2X the performance per watt than prior gen. So I'll say it's that kind of offload that is really going to enable more and more virtualized desktops or users for any given deployment. >> Thanks everyone. We still got a lot more to discuss with Cynthia, Dennis and Allen, but we're going to take a break. Quick break before wrapping things up. You're watching theCUBE, the leader in tech coverage. We'll be right back. Okay, welcome back everyone to theCUBEs coverage of Compute Engineered for your Hybrid World. I'm John Furrier. We'll be wrapping up our discussion on advanced performance of VDI with the fourth gen Intel Zion scalable processers. Welcome back everyone. Dennis, we'll start with you. Let's continue our conversation and turn our attention to security. Obviously security is baked in from day zero as they say. What are some of the new security features or the key security features for the HP ProLiant Gen 11 server? >> Sure, I would like to start with the balance, right? We were talking about performance, we were talking about density, but Alan mentioned about the balance. So what about the security? The security is really important aspect especially if we're talking about solutions deployed at the H. When the security is not active but other aspects of the environment become non-important. And HP is uniquely positioned to deliver the best in class security solution on the market starting with the trusted supply chain and factories and silicon route of trust implemented from the factory. So the new ISO6 supports added protection leveraging SPDM for component authorization and not only enabled for the embedded server management, but also it is integrated with HP GreenLake compute ops manager that enables environment for secure and optimized configuration deployment and even lifecycle management starting from the single server deployed on the Edge and all the way up to the full scale distributed data center. So it brings uncompromised and trusted solution to customers fully protected at all tiers, hardware, firmware, hypervisor, operational system application and data. And the new intel CPUs play an important role in the securing of the platform. So Alan- >> Yeah, thanks. So Intel, I think our zero trust strategy toward security is a really great and a really strong parallel to all the focus that HPE is also bringing to that segment and market. We have even invested in a lot of hardware enabled security technologies like SGX designed to enhance data protection at rest in motion and in use. SGX'S application isolation is the most deployed, researched and battle tested confidential computing technology for the data center market and with the smallest trust boundary of any solution in market. So as we've talked about a little bit about virtualized use cases a lot of virtualized applications rely also on encryption whether bulk or specific ciphers. And this is again an area where we've seen the opportunity for offload to Intel's quick assist technology to encrypt within a single data flow. I think Intel and HP together, we are really providing security at all facets of execution today. >> I love that Software Guard Extension, SGX, also silicon root of trust. We've heard a lot about great stuff. Congratulations, security's very critical as we see more and more. Got to be embedded, got to be completely zero trust. Final question for you guys. Can you share any messages you'd like to share with the audience each of you, what should they walk away from this? What's in it for them? What does all this mean? >> Yeah, so I'll start. Yes, so to wrap it up, HPR Proliant Gen 11 servers are built on four generation science scalable processors to enable high density and extreme performance with high performance CDR five memory and PCI 5.0 plus HP engine engineered and validated workload solutions provide better ROI in any consumption model and prefer by a customer from Edge to Cloud. >> Dennis? >> And yeah, so you are talking about all of the great features that the new generation servers are bringing to our customers, but at the same time, customer IT organization should be ready to enable, configure, support, and fine tune all of these great features for the new server generation. And this is not an obvious task. It requires investments, skills, knowledge and experience. And HP is ready to step up and help customers at any desired skill with the HP Greenlake H2 cloud platform that enables customers for cloud like experience and convenience and the flexibility with the security of the infrastructure deployed in the private data center or in the Edge. So while consuming all of the HP solutions, customer have flexibility to choose the right level of the service delivered from HP GreenLake, starting from hardwares as a service and scale up or down is required to consume the full stack of the hardwares and software as a service with an option to paper use. >> Awesome. Alan, final word. >> Yeah. What should we walk away with? >> Yeah, thanks. So I'd say that we've talked a lot about the systems here in question with HP ProLiant Gen 11 and they're delivering on a lot of the business outcomes that our customers require in order to optimize for operational efficiency or to optimize for just to, well maybe just to enable what they want to do in, with their customers enabling new features, enabling new capabilities. Underpinning all of that is our fourth Gen Zion scalable platform. Whether it's the technology transitions that we're driving with DDR5 PCIA Gen 5 or the raw performance efficiency and scalability of the platform in CPU, I think we're here for our customers in delivering to it. >> That's great stuff. Alan, Dennis, Cynthia, thank you so much for taking the time to do a deep dive in the advanced performance of VDI with the fourth Gen Intel Zion scalable process. And congratulations on Gen 11 ProLiant. You get some great servers there and again next Gen's here. Thanks for taking the time. >> Thank you so much for having us here. >> Okay, this is theCUBEs keeps coverage of Compute Engineered for your Hybrid World sponsored by HP and Intel. I'm John Furrier for theCUBE. Accelerate VDI at the Edge. Thanks for watching.

>>We are back in the final stretch at Supercomputing 22 here in Dallas. I'm your host Paul Gillum with my co-host Dave Nicholson, and we've been talking to so many smart people this week. It just, it makes, boggles my mind are next guest. J Poso is the HPC and AI technology strategist at Dell. Jay also has a PhD in astronomy from the University of Texas. And I'm guessing you were up watching the Artemis launch the other night? >>I, I wasn't. I really should have been, but, but I wasn't, I was in full super computing conference mode. So that means discussions at, you know, various venues with people into the wee hours. >>How did you make the transition from a PhD in astronomy to an HPC expert? >>It was actually really straightforward. I did theoretical astrophysics and I was modeling what white dwarfs look like when they create matter and then explode as type one A super Novi, which is a class of stars that blow up. And it's a very important class because they blow up almost exactly the same way. So if you know how bright they are physically, not just how bright they appear in the sky, but if you can determine from first principles how bright they're, then you have a standard ruler for the universe when they go off in a galaxy, you know how far the galaxy is about how faint it is. So to model these though, you had to understand equations of physics, including electron degeneracy pressure, as well as normal fluid dynamics kinds of of things. And so you were solving for an explosive burning front, ripping through something. And that required a supercomputer to have anywhere close to the fat fidelity to get a reasonable answer and, and hopefully some understanding. >>So I've always said electrons are degenerate. I've always said it and I, and I mentioned to Paul earlier, I said, finally we're gonna get a guest to consort through this whole dark energy dark matter thing for us. We'll do that after, after, after the segment. >>That's a whole different, >>So, well I guess super computing being a natural tool that you would use. What is, what do you do in your role as a strategist? >>So I'm in the product management team. I spend a lot of time talking to customers about what they want to do next. HPC customers are always trying to be maximally productive of what they've got, but always wanting to know what's coming next. Because if you think about it, we can't simulate the entire human body cell for cell on any supercomputer day. We can simulate parts of it, cell for cell or the whole body with macroscopic physics, but not at the, you know, atomic level, the entire organism. So we're always trying to build more powerful computers to solve larger problems with more fidelity and less approximations in it. And so I help people try to understand which technologies for their next system might give them the best advance in capabilities for their simulation work, their data analytics work, their AI work, et cetera. Another part of it is talking to our great technology partner ecosystem and learning about which technologies they have. Cause it feeds the first thing, right? So understanding what's coming, and Dell has a, we're very proud of our large partner ecosystem. We embrace many different partners in that with different capabilities. So understanding those helps understand what your future systems might be. That those are two of the major roles in it. Strategic customers and strategic technologies. >>So you've had four days to wander the, this massive floor here and lots of startups, lots of established companies doing interesting things. What have you seen this week that really excites you? >>So I'm gonna tell you a dirty little secret here. If you are working for someone who makes super computers, you don't get as much time to wander the floor as you would think because you get lots of meetings with people who really want to understand in an NDA way, not just in the public way that's on the floor, but what's, what are you not telling us on the floor? What's coming next? And so I've been in a large number of customer meetings as well as being on the floor. And while I can't obviously share the everything, that's a non-disclosure topic in those, some things that we're hearing a lot about, people are really concerned with power because they see the TDP on the roadmaps for all the silicon providers going way up. And so people with power comes heat as waste. And so that means cooling. >>So power and cooling has been a big topic here. Obviously accelerators are, are increasing in importance in hpc not just for AI calculations, but now also for simulation calculations. And we are very proud of the three new accelerator platforms we launched here at the show that are coming out in a quarter or so. Those are two of the big topics we've seen. You know, there's, as you walk the floor here, you see lots of interesting storage vendors. HPC community's been do doing storage the same way for roughly 20 years. But now we see a lot of interesting players in that space. We have some great things in storage now and some great things that, you know, are coming in a year or two as well. So it's, it's interesting to see that diversity of that space. And then there's always the fun, exciting topics like quantum computing. We unveiled our first hybrid classical quantum computing system here with I on Q and I can't say what the future holds in this, in this format, but I can say we believe strongly in the future of quantum computing and that this, that future will be integrated with the kind of classical computing infrastructure that we make and that will help make quantum computing more powerful downstream. >>Well, let's go down that rabbit hole because, oh boy, boy, quantum computing has been talked about for a long time. There was a lot of excitement about it four or five years ago, some of the major vendors were announcing quantum computers in the cloud. Excitement has kind of died down. We don't see a lot of activity around, no, not a lot of talk around commercial quantum computers, yet you're deep into this. How close are we to have having a true quantum computer or is it a, is it a hybrid? More >>Likely? So there are probably more than 20 and I think close to 40 companies trying different approaches to make quantum computers. So, you know, Microsoft's pursuing a topol topological approach, do a photonics based approach. I, on Q and i on trap approach. These are all different ways of trying to leverage the quantum properties of nature. We know the properties exist, we use 'em in other technologies. We know the physics, but trying the engineering is very difficult. It's very difficult. I mean, just like it was difficult at one point to split the atom. It's very difficult to build technologies that leverage quantum properties of nature in a consistent and reliable and durable way, right? So I, you know, I wouldn't wanna make a prediction, but I will tell you I'm an optimist. I believe that when a tremendous capability with, with tremendous monetary gain potential lines up with another incentive, national security engineering seems to evolve faster when those things line up, when there's plenty of investment and plenty of incentive things happen. >>So I think a lot of my, my friends in the office of the CTO at Dell Technologies, when they're really leading this effort for us, you know, they would say a few to several years probably I'm an optimist, so I believe that, you know, I, I believe that we will sell some of the solution we announced here in the next year for people that are trying to get their feet wet with quantum. And I believe we'll be selling multiple quantum hybrid classical Dell quantum computing systems multiple a year in a year or two. And then of course you hope it goes to tens and hundreds of, you know, by the end of the decade >>When people talk about, I'm talking about people writ large, super leaders in supercomputing, I would say Dell's name doesn't come up in conversations I have. What would you like them to know that they don't know? >>You know, I, I hope that's not true, but I, I, I guess I understand it. We are so good at making the products from which people make clusters that we're number one in servers, we're number one in enterprise storage. We're number one in so many areas of enterprise technology that I, I think in some ways being number one in those things detracts a little bit from a subset of the market that is a solution subset as opposed to a product subset. But, you know, depending on which analyst you talk to and how they count, we're number one or number two in the world in supercomputing revenue. We don't always do the biggest splashy systems. We do the, the frontier system at t, the HPC five system at ENI in Europe. That's the largest academic supercomputer in the world and the largest industrial super >>That's based the world on Dell. Dell >>On Dell hardware. Yep. But we, I think our vision is really that we want to help more people use HPC to solve more problems than any vendor in the world. And those problems are various scales. So we are really concerned about the more we're democratizing HPC to make it easier for more people to get in at any scale that their budget and workloads require, we're optimizing it to make sure that it's not just some parts they're getting, that they are validated to work together with maximum scalability and performance. And we have a great HPC and AI innovation lab that does this engineering work. Cuz you know, one of the myths is, oh, I can just go buy a bunch of servers from company X and a network from company Y and a storage system from company Z and then it'll all work as an equivalent cluster. Right? Not true. It'll probably work, but it won't be the highest performance, highest scalability, highest reliability. So we spend a lot of time optimizing and then we are doing things to try to advance the state of HPC as well. What our future systems look like in the second half of this decade might be very different than what they look like right. Now. >>You mentioned a great example of a limitation that we're running up against right now. You mentioned an entire human body as a, as a, as an organism >>Or any large system that you try to model at the atomic level, but it's a huge macro system, >>Right? So will we be able to reach milestones where we can get our arms entirely around something like an entire human organism with simply quantitative advances as opposed to qualitative advances? Right now, as an example, let's just, let's go down to the basics from a Dell perspective. You're in a season where microprocessor vendors are coming out with next gen stuff and those next NextGen microprocessors, GPUs and CPUs are gonna be plugged into NextGen motherboards, PCI e gen five, gen six coming faster memory, bigger memory, faster networking, whether it's NS or InfiniBand storage controllers, all bigger, better, faster, stronger. And I suspect that systems like Frontera, I don't know, but I suspect that a lot of the systems that are out there are not on necessarily what we would think of as current generation technology, but maybe they're n minus one as a practical matter. So, >>But yeah, I mean they have a lifetime, so Exactly. >>The >>Lifetime is longer than the evolution. >>That's the normal technologies. Yeah. So, so what some people miss is this is, this is the reality that when, when we move forward with the latest things that are being talked about here, it's often a two generation move for an individual, for an individual organization. Yep. >>So now some organizations will have multiple systems and they, the system's leapfrog and technology generations, even if one is their real large system, their next one might be newer technology, but smaller, the next one might be a larger one with newer technology and such. Yeah. So the, the biggest super computing sites are, are often running more than one HPC system that have been specifically designed with the latest technologies and, and designed and configured for maybe a different subset of their >>Workloads. Yeah. So, so the, the, to go back to kinda the, the core question, in your opinion, do we need that qualitative leap to something like quantum computing in order to get to the point, or is it simply a question of scale and power at the, at the, at the individual node level to get us to the point where we can in fact gain insight from a digital model of an entire human body, not just looking at a, not, not just looking at an at, at an organ. And to your point, it's not just about human body, any system that we would characterize as being chaotic today, so a weather system, whatever. Do you, are there any milestones that you're thinking of where you're like, wow, you know, I have, I, I understand everything that's going on, and I think we're, we're a year away. We're a, we're, we're a, we're a compute generation away from being able to gain insight out of systems that right now we can't simply because of scale. It's a very, very long question that I just asked you, but I think I, but hopefully, hopefully you're tracking it. What, what are your, what are your thoughts? What are these, what are these inflection points that we, that you've, in your mind? >>So I, I'll I'll start simple. Remember when we used to buy laptops and we worried about what gigahertz the clock speed was Exactly. Everybody knew the gigahertz of it, right? There's some tasks at which we're so good at making the hardware that now the primary issues are how great is the screen? How light is it, what's the battery life like, et cetera. Because for the set of applications on there, we we have enough compute power. We don't, you don't really need your laptop. Most people don't need their laptop to have twice as powerful a processor that actually rather up twice the battery life on it or whatnot, right? We make great laptops. We, we design for all of those, configure those parameters now. And what, you know, we, we see some customers want more of x, somewhat more of y but the, the general point is that the amazing progress in, in microprocessors, it's sufficient for most of the workloads at that level. Now let's go to HPC level or scientific and technical level. And when it needs hpc, if you're trying to model the orbit of the moon around the earth, you don't really need a super computer for that. You can get a highly accurate model on a, on a workstation, on a server, no problem. It won't even really make it break a sweat. >>I had to do it with a slide rule >>That, >>That >>Might make you break a sweat. Yeah. But to do it with a, you know, a single body orbiting with another body, I say orbiting around, but we both know it's really, they're, they're both ordering the center of mass. It's just that if one is much larger, it seems like one's going entirely around the other. So that's, that's not a super computing problem. What about the stars in a galaxy trying to understand how galaxies form spiral arms and how they spur star formation. Right now you're talking a hundred billion stars plus a massive amount of inter stellar medium in there. So can you solve that on that server? Absolutely not. Not even close. Can you solve it on the largest super computer in the world today? Yes and no. You can solve it with approximations on the largest super computer in the world today. But there's a lot of approximations that go into even that. >>The good news is the simulations produce things that we see through our great telescopes. So we know the approximations are sufficient to get good fidelity, but until you really are doing direct numerical simulation of every particle, right? Right. Which is impossible to do. You need a computer as big as the universe to do that. But the approximations and the science in the science as well as the known parts of the science are good enough to give fidelity. So, and answer your question, there's tremendous number of problem scales. There are problems in every field of science and study that exceed the der direct numerical simulation capabilities of systems today. And so we always want more computing power. It's not macho flops, it's real, we need it, we need exo flops and we will need zeta flops beyond that and yada flops beyond that. But an increasing number of problems will be solved as we keep working to solve problems that are farther out there. So in terms of qualitative steps, I do think technologies like quantum computing, to be clear as part of a hybrid classical quantum system, because they're really just accelerators for certain kinds of algorithms, not for general purpose algorithms. I do think advances like that are gonna be necessary to solve some of the very hardest problem. It's easy to actually formulate an optimization problem that is absolutely intractable by the larger systems in the world today, but quantum systems happen to be in theory when they're big and stable enough, great at that kind of problem. >>I, that should be understood. Quantum is not a cure all for absolutely. For the, for the shortage of computing power. It's very good for certain, certain >>Problems. And as you said at this super computing, we see some quantum, but it's a little bit quieter than I probably expected. I think we're in a period now of everybody saying, okay, there's been a lot of buzz. We know it's gonna be real, but let's calm down a little bit and figure out what the right solutions are. And I'm very proud that we offered one of those >>At the show. We, we have barely scratched the surface of what we could talk about as we get into intergalactic space, but unfortunately we only have so many minutes and, and we're out of them. Oh, >>I'm >>J Poso, HPC and AI technology strategist at Dell. Thanks for a fascinating conversation. >>Thanks for having me. Happy to do it anytime. >>We'll be back with our last interview of Supercomputing 22 in Dallas. This is Paul Gillen with Dave Nicholson. Stay with us.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

>>From the Cube Studios in Palo Alto in Boston, bringing you data driven insights from the cube and etr. This is breaking analysis with Dave Ante. >>Have you ever been driving on the highway and traffic suddenly slows way down and then after a little while it picks up again and you're cruising along and you're thinking, Okay, hey, that was weird. But it's clear sailing now. Off we go, only to find out in a bit that the traffic is building up ahead again, forcing you to pump the brakes as the traffic pattern ebbs and flows well. Welcome to the Seesaw economy. The fed induced fire that prompted an unprecedented rally in tech is being purposefully extinguished now by that same fed. And virtually every sector of the tech industry is having to reset its expectations, including the cloud segment. Hello and welcome to this week's Wikibon Cube Insights powered by etr. In this breaking analysis will review the implications of the earnings announcements from the big three cloud players, Amazon, Microsoft, and Google who announced this week. >>And we'll update you on our quarterly IAS forecast and share the latest from ETR with a focus on cloud computing. Now, before we get into the new data, we wanna review something we shared with you on October 14th, just a couple weeks back, this is sort of a, we told you it was coming slide. It's an XY graph that shows ET R'S proprietary net score methodology on the vertical axis. That's a measure of spending momentum, spending velocity, and an overlap or presence in the dataset that's on the X axis. That's really a measure of pervasiveness. In the survey, the table, you see that table insert there that shows Wiki Bond's Q2 estimates of IAS revenue for the big four hyperscalers with their year on year growth rates. Now we told you at the time, this is data from the July TW 22 ETR survey and the ETR hadn't released its October survey results at that time. >>This was just a couple weeks ago. And while we couldn't share the specific data from the October survey, we were able to get a glimpse and we depicted the slowdown that we saw in the October data with those dotted arrows kind of down into the right, we said at the time that we were seeing and across the board slowdown even for the big three cloud vendors. Now, fast forward to this past week and we saw earnings releases from Alphabet, Microsoft, and just last night Amazon. Now you may be thinking, okay, big deal. The ETR survey data didn't really tell us anything we didn't already know. But judging from the negative reaction in the stock market to these earnings announcements, the degree of softness surprised a lot of investors. Now, at the time we didn't update our forecast, it doesn't make sense for us to do that when we're that close to earning season. >>And now that all the big three ha with all the big four with the exception of Alibaba have announced we've, we've updated. And so here's that data. This chart lays out our view of the IS and PAs worldwide revenue. Basically it's cloud infrastructure with an attempt to exclude any SaaS revenue so we can make an apples to apples comparison across all the clouds. Now the reason that actual is in quotes is because Microsoft and Google don't report IAS revenue, but they do give us clues and kind of directional commentary, which we then triangulate with other data that we have from the channel and ETR surveys and just our own intelligence. Now the second column there after the vendor name shows our previous estimates for q3, and then next to that we show our actuals. Same with the growth rates. And then we round out the chart with that lighter blue color highlights, the full year estimates for revenue and growth. >>So the key takeaways are that we shaved about $4 billion in revenue and roughly 300 basis points of growth off of our full year estimates. AWS had a strong July but exited Q3 in the mid 20% growth rate year over year. So we're using that guidance, you know, for our Q4 estimates. Azure came in below our earlier estimates, but Google actually exceeded our expectations. Now the compression in the numbers is in our view of function of the macro demand climate, we've made every attempt to adjust for constant currency. So FX should not be a factor in this data, but it's sure you know that that ma the the, the currency effects are weighing on those companies income statements. And so look, this is the fundamental dynamic of a cloud model where you can dial down consumption when you need to and dial it up when you need to. >>Now you may be thinking that many big cloud customers have a committed level of spending in order to get better discounts. And that's true. But what's happening we think is they'll reallocate that spend toward, let's say for example, lower cost storage tiers or they may take advantage of better price performance processors like Graviton for example. That is a clear trend that we're seeing and smaller companies that were perhaps paying by the drink just on demand, they're moving to reserve instance models to lower their monthly bill. So instead of taking the easy way out and just spending more companies are reallocating their reserve capacity toward lower cost. So those sort of lower cost services, so they're spending time and effort optimizing to get more for, for less whereas, or get more for the same is really how we should, should, should phrase it. Whereas during the pandemic, many companies were, you know, they perhaps were not as focused on doing that because business was booming and they had a response. >>So they just, you know, spend more dial it up. So in general, as they say, customers are are doing more with, with the same. Now let's look at the growth dynamic and spend some time on that. I think this is important. This data shows worldwide quarterly revenue growth rates back to Q1 2019 for the big four. So a couple of interesting things. The data tells us during the pandemic, you saw both AWS and Azure, but the law of large numbers and actually accelerate growth. AWS especially saw progressively increasing growth rates throughout 2021 for each quarter. Now that trend, as you can see is reversed in 2022 for aws. Now we saw Azure come down a bit, but it's still in the low forties in terms of percentage growth. While Google actually saw an uptick in growth this last quarter for GCP by our estimates as GCP is becoming an increasingly large portion of Google's overall cloud business. >>Now, unfortunately Google Cloud continues to lose north of 850 million per quarter, whereas AWS and Azure are profitable cloud businesses even though Alibaba is suffering its woes from China. And we'll see how they come in when they report in mid-November. The overall hyperscale market grew at 32% in Q3 in terms of worldwide revenue. So the slowdown isn't due to the repatriation or competition from on-prem vendors in our view, it's a macro related trend. And cloud will continue to significantly outperform other sectors despite its massive size. You know, on the repatriation point, it just still doesn't show up in the data. The A 16 Z article from Sarah Wong and Martin Martin Kasa claiming that repatriation was inevitable as a means to lower cost of good sold for SaaS companies. You know, while that was thought provoking, it hasn't shown up in the numbers. And if you read the financial statements of both AWS and its partners like Snowflake and you dig into the, to the, to the quarterly reports, you'll see little notes and comments with their ongoing negotiations to lower cloud costs for customers. >>AWS and no doubt execs at Azure and GCP understand that the lifetime value of a customer is worth much more than near term gross margin. And you can expect the cloud vendors to strike a balance between profitability, near term profitability anyway and customer attention. Now, even though Google Cloud platform saw accelerated growth, we need to put that in context for you. So GCP, by our estimate, has now crossed over the $3 billion for quarter market actually did so last quarter, but its growth rate accelerated to 42% this quarter. And so that's a good sign in our view. But let's do a quick little comparison with when AWS and Azure crossed the $3 billion mark and compare their growth rates at the time. So if you go back to to Q2 2016, as we're showing in this chart, that's around the time that AWS hit 3 billion per quarter and at the same time was growing at 58%. >>Azure by our estimates crossed that mark in Q4 2018 and at that time was growing at 67%. Again, compare that to Google's 42%. So one would expect Google's growth rate would be higher than its competitors at this point in the MO in the maturity of its cloud, which it's, you know, it's really not when you compared to to Azure. I mean they're kind of con, you know, comparable now but today, but, but you'll go back, you know, to that $3 billion mark. But more so looking at history, you'd like to see its growth rate at this point of a maturity model at least over 50%, which we don't believe it is. And one other point on this topic, you know, my business friend Matt Baker from Dell often says it's not a zero sum game, meaning there's plenty of opportunity exists to build value on top of hyperscalers. >>And I would totally agree it's not a dollar for dollar swap if you can continue to innovate. But history will show that the first company in makes the most money. Number two can do really well and number three tends to break even. Now maybe cloud is different because you have Microsoft software estate and the power behind that and that's driving its IAS business and Google ads are funding technology buildouts for, for for Google and gcp. So you know, we'll see how that plays out. But right now by this one measurement, Google is four years behind Microsoft in six years behind aws. Now to the point that cloud will continue to outpace other markets, let's, let's break this down a bit in spending terms and see why this claim holds water. This is data from ET r's latest October survey that shows the granularity of its net score or spending velocity metric. >>The lime green is new adoptions, so they're adding the platform, the forest green is spending more 6% or more. The gray bars spending is flat plus or minus, you know, 5%. The pinkish colors represent spending less down 6% or worse. And the bright red shows defections or churn of the platform. You subtract the reds from the greens and you get what's called net score, which is that blue dot that you can see on each of the bars. So what you see in the table insert is that all three have net scores above 40%, which is a highly elevated measure. Microsoft's net scores above 60% AWS well into the fifties and GCP in the mid forties. So all good. Now what's happening with all three is more customers are keep keeping their spending flat. So a higher percentage of customers are saying, our spending is now flat than it was in previous quarters and that's what's accounting for the compression. >>But the churn of all three, even gcp, which we reported, you know, last quarter from last quarter survey was was five x. The other two is actually very low in the single digits. So that might have been an anomaly. So that's a very good sign in our view. You know, again, customers aren't repatriating in droves, it's just not a trend that we would bet on, maybe makes for a FUD or you know, good marketing head, but it's just not a big deal. And you can't help but be impressed with both Microsoft and AWS's performance in the survey. And as we mentioned before, these companies aren't going to give up customers to try and preserve a little bit of gross margin. They'll do what it takes to keep people on their platforms cuz they'll make up for it over time with added services and improved offerings. >>Now, once these companies acquire a customer, they'll be very aggressive about keeping them. So customers take note, you have negotiating leverage, so use it. Okay, let's look at another cut at the cloud market from the ETR data set. Here's the two dimensional view, again, it's back, it's one of our favorites. Net score or spending momentum plotted against presence. And the data set, that's the x axis net score on the, on the vertical axis, this is a view of et r's cloud computing sector sector. You can see we put that magic 40% dotted red line in the table showing and, and then that the table inserts shows how the data are plotted with net score against presence. I e n in the survey, notably only the big three are above the 40% line of the names that we're showing here. The oth there, there are others. >>I mean if you put Snowflake on there, it'd be higher than any of these names, but we'll dig into that name in a later breaking analysis episode. Now this is just another way of quantifying the dominance of AWS and Azure, not only relative to Google, but the other cloud platforms out there. So we've, we've taken the opportunity here to plot IBM and Oracle, which both own a public cloud. Their performance is largely a reflection of them migrating their install bases to their respective public clouds and or hybrid clouds. And you know, that's fine, they're in the game. That's a point that we've made, you know, a number of times they're able to make it through the cloud, not whole and they at least have one, but they simply don't have the business momentum of AWS and Azure, which is actually quite impressive because AWS and Azure are now as large or larger than IBM and Oracle. >>And to show this type of continued growth that that that Azure and AWS show at their size is quite remarkable and customers are starting to recognize the viability of on-prem hi, you know, hybrid clouds like HPE GreenLake and Dell's apex. You know, you may say, well that's not cloud, but if the customer thinks it is and it was reporting in the survey that it is, we're gonna continue to report this view. You know, I don't know what's happening with H P E, They had a big down tick this quarter and I, and I don't read too much into that because their end is still pretty small at 53. So big fluctuations are not uncommon with those types of smaller ends, but it's over 50. So, you know, we did notice a a a negative within a giant public and private sector, which is often a, a bellwether giant public private is big public companies and large private companies like, like a Mars for example. >>So it, you know, it looks like for HPE it could be an outlier. We saw within the Fortune 1000 HPE E'S cloud looked actually really good and it had good spending momentum in that sector. When you di dig into the industry data within ETR dataset, obviously we're not showing that here, but we'll continue to monitor that. Okay, so where's this Leave us. Well look, this is really a tactical story of currency and macro headwinds as you can see. You know, we've laid out some of the points on this slide. The action in the stock market today, which is Friday after some of the soft earnings reports is really robust. You know, we'll see how it ends up in the day. So maybe this is a sign that the worst is over, but we don't think so. The visibility from tech companies is murky right now as most are guiding down, which indicates that their conservative outlook last quarter was still too optimistic. >>But as it relates to cloud, that platform is not going anywhere anytime soon. Sure, there are potential disruptors on the horizon, especially at the edge, but we're still a long ways off from, from the possibility that a new economic model emerges from the edge to disrupt the cloud and the opportunities in the cloud remain strong. I mean, what other path is there? Really private cloud. It was kind of a bandaid until the on-prem guys could get their a as a service models rolled out, which is just now happening. The hybrid thing is real, but it's, you know, defensive for the incumbents until they can get their super cloud investments going. Super cloud implying, capturing value above the hyperscaler CapEx, you know, call it what you want multi what multi-cloud should have been, the metacloud, the Uber cloud, whatever you like. But there are opportunities to play offense and that's clearly happening in the cloud ecosystem with the likes of Snowflake, Mongo, Hashi Corp. >>Hammer Spaces is a startup in this area. Aviatrix, CrowdStrike, Zeke Scaler, Okta, many, many more. And even the projects we see coming out of enterprise players like Dell, like with Project Alpine and what Pure Storage is doing along with a number of other of the backup vendors. So Q4 should be really interesting, but the real story is the investments that that companies are making now to leverage the cloud for digital transformations will be paying off down the road. This is not 1999. We had, you know, May might have had some good ideas and admittedly at a lot of bad ones too, but you didn't have the infrastructure to service customers at a low enough cost like you do today. The cloud is that infrastructure and so far it's been transformative, but it's likely the best is yet to come. Okay, let's call this a rap. >>Many thanks to Alex Morrison who does production and manages the podcast. Also Can Schiffman is our newest edition to the Boston Studio. Kristin Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Ho is our editor in chief over@siliconangle.com, who does some wonderful editing for us. Thank you. Remember, all these episodes are available as podcasts. Wherever you listen, just search breaking analysis podcast. I publish each week on wiki bond.com at silicon angle.com. And you can email me at David dot valante@siliconangle.com or DM me at Dante or comment on my LinkedIn posts. And please do checkout etr.ai. They got the best survey data in the enterprise tech business. This is Dave Valante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.

(upbeat music) >> Welcome back everyone to theCUBEs live coverage in San Francisco for VMware Explorer. I'm John Furrier with my host, Dave Vellante. Two sets, three days of wall to wall coverage. This is day two. We got a great guest, Scott Baker, CMO at IBM, VP of Infrastructure at IBM. Great to see you. Thanks for coming on. >> Hey, good to see you guys as well. It's always a pleasure. >> ()Good time last night at your event? >> Great time last night. >> It was really well-attended. IBM always has the best food so that was good and great props, magicians, and it was really a lot of fun, comedians. Good job. >> Yeah, I'm really glad you came on. One of the things we were chatting, before we came on camera was, how much changed. We've been covering IBM storage days, back on the Edge days, and they had the event. Storage is the center of all the conversations, cyber security- >> ()Right? >> ... But it's not just pure cyber. It's still important there. And just data and the role of multi-cloud and hybrid cloud and data and security are the two hottest areas, that I won't say unresolved, but are resolving themselves. And people are talking. It's the most highly discussed topics. >> Right. >> ()Those two areas. And it's just all on storage. >> Yeah, it sure does. And in fact, what I would even go so far as to say is, people are beginning to realize the importance that storage plays, as the data custodian for the organization. Right? Certainly you have humans that are involved in setting strategies, but ultimately whatever those policies are that get applied, have to be applied to a device that must act as a responsible custodian for the data it holds. >> So what's your role at IBM and the infrastructure team? Storage is one only one of the areas. >> ()Right. >> You're here at VMware Explore. What's going on here with IBM? Take us through what you're doing there at IBM, and then here at VMware. What's the conversations? >> Sure thing. I have the distinct pleasure to run both product marketing and strategy for our storage line. That's my primary focus, but I also have responsibility for the mainframe software, so the Z System line, as well as our Power server line, and our technical support organization, or at least the services side of our technical support organization. >> And one of the things that's going on here, lot of noise going on- >> Is that a bird flying around? >> Yeah >> We got fire trucks. What's changed? 'Cause right now with VMware, you're seeing what they're doing. They got the Platform, Under the Hood, Developer focus. It's still an OPS game. What's the relationship with VMware? What are you guys talking about here? What are some of the conversations you're having here in San Francisco? >> Right. Well, IBM has been a partner with VMware for at least the last 20 years. And VMware does, I think, a really good job about trying to create a working space for everyone to be an equal partner with them. It can be challenging too, if you want to sort of throw out your unique value to a customer. So one of the things that we've really been working on is, how do we partner much stronger? When we look at the customers that we support today, what they're looking for isn't just a solid product. They're looking for a solid ecosystem partnership. So we really lean in on that 20 years of partnership experience that we have with IBM. So one of the things that we announced was actually being one of the first VMware partners to bring both a technical innovation delivery mechanism, as well as technical services, alongside VMware technologies. I would say that was one of the first things that we really leaned in on, as we looked out at what customers are expecting from us. >> So I want to zoom out a little bit and talk about the industry. I've been following IBM since the early 1980s. It's trained in the mainframe market, and so we've seen, a lot of things you see come back to the mainframe, but we won't go there. But prior to Arvind coming on, it seemed like, okay, storage, infrastructure, yeah it's good business, and we'll let it throw off some margin. That's fine. But it's all about services and software. Okay, great. With Arvind, and obviously Red Hat, the whole focus shift to hybrid. We were talking, I think yesterday, about okay, where did we first hear hybrid? Obviously we heard that a lot from VMware. I heard it actually first, early on anyway, from IBM, talking hybrid. Some of the storage guys at the time. Okay, so now all of a sudden there's the realization that to make hybrid work, you need software and hardware working together. >> () Right. So it's now a much more fundamental part of the conversation. So when you look out, Scott, at the trends you're seeing in the market, when you talk to customers, what are you seeing and how is that informing your strategy, and how are you bringing together all the pieces? >> That's a really awesome question because it always depends on who, within the organization, you're speaking to. When you're inside the data center, when you're talking to the architects and the administrators, they understand the value in the necessity for a hybrid-cloud architecture. Something that's consistent. On The Edge, On-Prem, in the cloud. Something that allows them to expand the level of control that they have, without having to specialize on equipment and having to redo things as you move from one medium to the next. As you go upstack in that conversation, what I find really interesting is how leaders are beginning to realize that private cloud or on-prem, multi cloud, super cloud, whatever you call it, whatever's in the middle, those are just deployment mechanisms. What they're coming to understand is it's the applications and the data that's hybrid. And so what they're looking for IBM to deliver, and something that we've really invested in on the infrastructure side is, how do we create bidirectional application mobility? Making it easy for organizations, whether they're using containers, virtual machines, just bare metal, how do they move that data back and forth as they need to, and not just back and forth from on-prem to the cloud, but effectively, how do they go from cloud to cloud? >> Yeah. One of the things I noticed is your pin, says I love AI, with the I next to IBM and get all these (indistinct) in there. AI, remember the quote from IBM is, "You can't have AI without IA." Information architect. >> () Right. >> () Rob Thomas. >> Rob Thomas (indistinct) the sound bites. But that brings up the point about machine learning and some of these things that are coming down the like, how is your area devolving the smarts and the brains around leveraging the AI in the systems itself? We're hearing more and more softwares being coded into the hardware. You see Silicon advances. All this is kind of, not changing it, but bringing back the urgency of, hardware matters. >> That's right. >> () At the same time, it's still software too. >> That's right. So let's connect a couple of dots here. We talked a little bit about the importance of cyber resiliency, and let's talk about a little bit on how we use AI in that matter. So, if you look at the direct flash modules that are in the market today, or the SSDs that are in the market today, just standard-capacity drives. If you look at the flash core modules that IBM produces, we actually treat that as a computational storage offering, where you store the data, but it's got intelligence built into the processor, to offload some of the responsibilities of the controller head. The ability to do compression, single (indistinct), deduplication, you name it. But what if you can apply AI at the controller level, so that signals that are being derived by the flash core module itself, that look anomalous, can be handed up to an intelligence to say, "Hey, I'm all of a sudden getting encrypted rights from a host that I've never gotten encrypted rights for. Maybe this could be a problem." And then imagine if you connect that inferencing engine to the rest of the IBM portfolio, "Hey, Qradar. Hey IBM Guardian. What's going on on the network? Can we see some correlation here?" So what you're going to see IBM infrastructure continue to do is invest heavily into entropy and the ability to measure IO characteristics with respect to anomalous behavior and be able to report against that. And the trick here, because the array technically doesn't know if it's under attack or if the host just decided to turn on encryption, the trick here is using the IBM product relationships, and ecosystem relationships, to do correlation of data to determine what's actually happening, to reduce your false positives. >> And have that pattern of data too. It's all access to data too. Big time. >> That's right. >> And that innovation comes out of IBM R&D? Does it come out of the product group? Is it IBM research that then trickles its way in? Is it the storage innovation? Where's that come from? Where's that bubble up? That partnership? >> Well, I got to tell you, it doesn't take very long in this industry before your counterpart, your competitor, has a similar feature. Right? So we're always looking for, what's the next leg? What's the next advancement that we can make? We knew going into this process, that we had plenty of computational power that was untapped on the FPGA, the processor running on the flash core module. Right? So we thought, okay, well, what should we do next? And we thought, "Hey, why not just set this thing up to start watching IO patterns, do calculations, do trending, and report that back?" And what's great about what you brought up too, John, is that it doesn't stay on the box. We push that upstack through the AIOPS architecture. So if you're using Turbonomic, and you want to look applications stack down, to know if you've got threat potential, or your attack surface is open, you can make some changes there. If you want to look at it across your infrastructure landscape with a storage insight, you could do that. But our goal here is to begin to make the machine smarter and aware of impacts on the data, not just on the data they hold onto, but usage, to move it into the appropriate tier, different write activities or read activities or delete activities that could indicate malicious efforts that are underway, and then begin to start making more autonomous, how about managed autonomous responses? I don't want to turn this into a, oh, it's smart, just turn it on and walk away and it's good. I don't know that we'll ever get there just yet, but the important thing here is, what we're looking at is, how do we continually safeguard and protect that data? And how do we drive features in the box that remove more and more of the day to day responsibility from the administrative staff, who are technically hired really, to service and solve for bigger problems in the enterprise, not to be a specialist and have to manage one box at a time. >> Dave mentioned Arvind coming on, the new CEO of IBM, and the Red Hat acquisition and that change, I'd like to get your personal perspective, or industry perspective, so take your IBM-hat off for a second and put the Scott-experience-in-the-industry hat on, the transformation at the customer level right now is more robust, to use that word. I don't want to say chaotic, but it is chaotic. They say chaos in the cloud here at VM, a big part of their messaging, but it's changing the business model, how things are consumed. You're seeing new business models emerge. So IBM has this lot of storage old systems, you're transforming, the company's transforming. Customers are also transforming, so that's going to change how people market products. >> () Right. >> For example, we know that developers and DevOps love self-service. Why? Because they don't want to install it. Let me go faster. And they want to get rid of it, doesn't work. Storage is infrastructure and still software, so how do you see, in your mind's eye, with all your experience, the vision of how to market products that are super important, that are infrastructure products, that have to be put into play, for really new architectures that are going to transform businesses? It's not as easy as saying, "Oh, we're going to go to market and sell something." The old way. >> () Right. >> This shifting happening is, I don't think there's an answer yet, but I want to get your perspective on that. Customers want to hear the storage message, but it might not be speeds and fees. Maybe it is. Maybe it's not. Maybe it's solutions. Maybe it's security. There's multiple touch points now, that you're dealing with at IBM for the customer, without becoming just a storage thing or just- >> () Right. >> ... or just hardware. I mean, hardware does matter, but what's- >> Yeah, no, you're absolutely right, and I think what complicates that too is, if you look at the buying centers around a purchase decision, that's expanded as well, and so as you engage with a customer, you have to be sensitive to the message that you're telling, so that it touches the needs or the desires of the people that are all sitting around the table. Generally what we like to do when we step in and we engage, isn't so much to talk about the product. At some point, maybe later in the engagements, the importance of speeds, feeds, interconnectivity, et cetera, those do come up. Those are a part of the final decision, but early on it's really about outcomes. What outcomes are you delivering? This idea of being able to deliver, if you use the term zero trust or cyber-resilient storage capability as a part of a broader security architecture that you're putting into place, to help that organization, that certainly comes up. We also hear conversations with customers about, or requests from customers about, how do the parts of IBM themselves work together? Right? And I think a lot of that, again, continues to speak to what kind of outcome are you going to give to me? Here's a challenge that I have. How are you helping me overcome it? And that's a combination of IBM hardware, software, and the services side, where we really have an opportunity to stand out. But the thing that I would tell you, that's probably most important is, the engagement that we have up and down the stack in the market perspective, always starts with, what's the outcome that you're going to deliver for me? And then that drags with it the story that would be specific to the gear. >> Okay, so let's say I'm a customer, and I'm buying it to zero trust architecture, but it's going to be somewhat of a long term plan, but I have a tactical need. I'm really nervous about Ransomware, and I don't feel as though I'm prepared, and I want an outcome that protects me. What are you seeing? Are you seeing any patterns? I know it's going to vary, but are you seeing any patterns, in terms of best practice to protect me? >> Man, the first thing that we wanted to do at IBM is divorce ourselves from the company as we thought through this. And what I mean by that is, we wanted to do what's right, on day zero, for the customer. So we set back using the experience that we've been able to amass, going through various recovery operations, and helping customers get through a Ransomware attack. And we realized, "Hey. What we should offer is a free cyber resilience assessment." So we like to, from the storage side, we'd like to look at what we offer to the customer as following the NIST framework. And most vendors will really lean in hard on the response and the recovery side of that, as you should. But that means that there's four other steps that need to be addressed, and that free cyber-resilience assessment, it's a consultative engagement that we offer. What we're really looking at doing is helping you assess how vulnerable you are, how big is that attack surface? And coming out of that, we're going to give you a Vendor Agnostic Report that says here's your situation, here's your grade or your level of risk and vulnerability, and then here's a prioritized roadmap of where we would recommend that you go off and start solving to close up whatever the gaps or the risks are. Now you could say, "Hey, thanks, IBM. I appreciate that. I'm good with my storage vendor today. I'm going to go off and use it." Now, we may not get some kind of commission check. We may not sell the box. But what I do know is that you're going to walk away knowing the risks that you're in, and we're going to give you the recommendations to get started on closing those up. And that helps me sleep at night. >> That's a nice freebie. >> Yeah. >> Yeah, it really is, 'cause you guys got deep expertise in that area. So take advantage of that. >> Scott, great to have you on. Thanks for spending time out of your busy day. Final question, put a plug in for your group. What are you communicating to customers? Share with the audience here. You're here at VMware Explorer, the new rebranded- >> () Right? >> ... multi-cloud, hybrid cloud, steady state. There are three levels of transformation, virtualization, hybrid cloud, DevOps, now- >> Right? >> ... multi-cloud, so they're in chapter three of their journey- >> That's right. >> Really innovative company, like IBM, so put the plugin. What's going on in your world? Take a minute to explain what you want. >> Right on. So here we are at VMware Explorer, really excited to be here. We're showcasing two aspects of the IBM portfolio, all of the releases and announcements that we're making around the IBM cloud. In fact, you should come check out the product demonstration for the IBM Cloud Satellite. And I don't think they've coined it this, but I like to call it the VMware edition, because it has all of the VMware services and tools built into it, to make it easier to move your workloads around. We certainly have the infrastructure side on the storage, talking about how we can help organizations, not only accelerate their deployments in, let's say Tanzu or Containers, but even how we help them transform the application stack that's running on top of their virtualized environment in the most consistent and secure way possible. >> Multiple years of relationships with VMware. IBM, VMware together. Congratulations. >> () That's right. >> () Thanks for coming on. >> Hey, thanks (indistinct). Thank you very much. >> A lot more live coverage here at Moscone west. This is theCUBE. I'm John Furrier with Dave Vellante. Thanks for watching. Two more days of wall-to-wall coverage continuing here. Stay tuned. (soothing music)

>>Welcome back everyone to the cubes live coverage here in San Francisco for VMware Explorer. I'm John farer, Dave LAN two days of Wal three days of Wal Walker. Two sets live events got PERA, had Metabo, senior vice president and general manager of cloud management at VMware. I got it. Right. Thanks for coming on the queue. >>You got it right. Good to >>Be here. We're all smiles. Cause we were talking about your history. You once worked at loud cloud and we were reminiscent about how cloud was before cloud was even cloud. Exactly. And how, how hard it was. >>And >>It's still hard. Complexity is a big deal. And one of the segments we want to talk to you about is the announcement around aria and you see cloud manage a big part of this direction to multi-cloud yes. To tame the complexity. And you know, we were quoting Andy Grove on the cube, let chaos rain, and then rain in the chaos. Exactly. Okay. A very famous quote in tech and the theme here is cloud chaos. Yes. And so we're starting to see signs of raining in that chaos or solving complexity. And every major inflection point has this moment where yes, it gets so hard and then it kicks up to the right and grows and link gets solved. So we feel like we're in that moment. >>I couldn't agree more. And in fact, the way I say is our, our, our tagline is we make the complexity of managing cloud invisible so that you can focus on building your business apps. And you're right about the inflection point. Every time a new technology hits, you have some point of adoption and then it becomes insanely successful. And that's when the complexity hits, then you go and tame the complexity till the next technology hits. Right? That's what happens. It's happened with virtualization. Then it has happened with cloud then with containerization and now the next one will hit. And so with aria, we said, we have to fundamentally change the problem, right? We are constantly running a race of TAing, this complexity. So very excited about this announcement with which we're doing with aria. And we said, imagine if I could have a view of my environment and all the dependencies, I don't need to know everything, just the environment and its dependencies. Then I can now start solving problems and answering questions that I was unable to before. And newer technologies can keep coming and piling on, but I'll always be able to answer that, help >>Our audience understand Ari, a great name and, and what's new. Your Heka what's new from, you know, it's not just V V realize with a new name what's what's new specifically. >>Yeah. Please. No. >>Explain some people. Well, >>There's some commentary on snarky comments, but it's a product it's not a rebrand of something >>Else. It's right. It's not explain that. It's not a, yeah. So what we did is let, let me start off. Why, why we started aria? So we said, okay, native public managing environments, native public cloud environments and cloud native applications is a different ballgame, more Emeral workloads, very large scale, highly fragmented data. So we looked at that problem rounds up and said, we need to have a management solution that solves that problem focused on native public cloud and cloud native apps and the core to solving that problem was you can't just solve it for one cloud or you can't solve it for one discipline. When I say discipline, when you think about management, what do you manage? You're managing to optimize cost. You're managing to optimize performance. You're managing to optimize your security and you're managing to speed up the delivery. That is it. And so we said, we'll have a new look to this management. And what we have done with aria is we have introduced a brand new platform, which we call aria hub powered by aria graph, which allows you to deliver this man on this management challenges, by creating a map of your environment, a near real time map of your environment. And then we are able to, once we know what an application looks like and how it maps to the infrastructure, we can go and query other subsystems to tell you, what is the cost of an application? What is the performance of an application? Creating a common understanding >>This now it's a new architecture. >>I just wanted to get that out there. It's federated >>New graph database. >>Yes. It's a new architecture federated, a platform that not only gives you a map of your environment, but it federates into other sources to pull that data together. Right now, one of the data sources that it federates into is of course also we realize, yeah, yeah. Cloud health, >>You plug and >>Cloud observability. You plug everything into it. Yeah. And as part of the announcement, we didn't just announce a platform. We also announced a set of crosscutting solutions cuz we said, okay, what is the power of the platform? The big thing is it removes the swivel share management. It allows you to answer questions you couldn't answer before. And so >>Swivel share meaning going from one app to another one app logging in exactly >>Credentials in credentials. And you don't have a common understanding of app across those. So now you hire people who do integration buses, right? All kinds of cloud. So the three new end to end solutions we are announcing also in, along with the platform, these are brand new. One is something called aria guardrails. So when I have development environments today, for example, my, I do development on public cloud as well as private cloud. I have thousands of accounts, each one with its own security rules, each one with its own policies. After I initially deploy the account, it becomes a nightmare to manage that. So what aria guardrails allows you to do is set up these multi-cloud environments with the right policies. And not only is it about one time provisioning, but it is maintaining them on >>A run basis. And those credentials are also risk. Cuz you have a password on the dark web, that's exposed on one and you've got to change it. And, and there's so many things going on exactly on security, which brings me up to the point of, you know, we were talking, we're gonna see Tom later on security. We heard earlier, why wasn't security in the keynote? Oh, it's table stakes. That's what Z has said. But we're like, okay, I get that. So let's just say that security is table stakes. There's a big trend towards security as a state of something at a, at a given time. And that CSOs and CSOs are going to defensible. Yes. Meaning being defensible all the time. Yes. As an ongoing thing, which is not just running a pen test once a week. Yes. Like multiple testing, real testing. Not simulation. Yes. To be secure. Yes. So it's not about being secure. It's about having security, but defense ability is the action now not yeah. Yeah. >>Can >>You does that, how does that fit into this? Because this seems to like be in this wheelhouse of management. >>No, I think you're bringing a very important point, which is the security as a post. The fact item is no longer. Right? Right. You want to bake in security. This is a shift left of security that we talk about when you're building an application and you are deploying code in your test, you wanna say, Hey, what is the security? Is it secure? Is it meeting my guardrail? Then when you deploy it from an operations perspective, also it is a security concern. It's not just a security team's concern now. So is my configuration right? Is my configuration secure? Has, is it drifting? It's never a snapshot in time. It's constantly, you have to look at it. Is it drifting? And that is exactly what we are doing also with aria. So >>That's part of the solution you're talking about in the guardrails within being >>Able to maintain the secure configuration right now, as I said, there's always a security discipline. Yeah. Which is you are done by security teams, but you also want operations teams and development teams to enforce security in their respective practices. And that's what Ari allows you to do. >>So the question on multi-cloud comes in, okay. So this is all good. By the way, we love that shift left again, very developer. And I would argue actually we are argue on the cube. That dev ops is the development environment for cloud native. So the it operational once called ops is now in dev just saying he is, and then data ops and security ops are now the new it because that's where the hard problems are. So how do you look at the data side of it as well as security in your view of multi-cloud because you know, hybrid cloud, I can see the steady state between, you know, on premises and cloud, if it's operating cloudlike but now you're starting to look at spanning clouds. Yes. Yes. Not full spanning workloads. That's not there yet, but certainly people have multiple clouds. Yeah. But when you data seems to be the first thing spanning not necessarily the app itself, but how do you guys view that multi-cloud aspect of what you're managing? I mean, how you look at that? >>I think there are different angles to it. Right? You can look at it from the data angle and you look at it on how the, how protected a data is for us. When you look at management discipline, it is all from the perspective of configurations. Okay. If I have configured my environment correctly, then you should not be able to do something that destroys or the data. Right. So getting the configuration right. When you're developing that, getting the configuration right. When you're provisioning the app and then getting the configuration, right. Even when you're doing day two and ongoing operations, that is what we bring to the table. And to some extent, that aria visibility, that I was talking about an Ary graph, a near real time view of the configuration state and its dependencies is very critical. So now I can ask questions. Is there a misconfiguration, by the way, the answer is yes, they, yeah. >>That is a lot by the way, too, right? Yeah. >>Which, which exposes me. And then you can say, Hey, is there user activity associated with that misconfigured? Good object. Now suddenly you have go, go to a red alert. So not only something misconfigured, but there is user activity associated with the misconfigured data. You know, this is something that I have. This >>Is where AI sings beautifully because beautifully, once you have the configuration baseline done, yes. It's like securing the S3 bucket, which is like a knee has to be a like brushing your teeth. It's gotta be a habit. Exactly. It's like, you just don't even think about, you just don't leave an S3 bucket. >>It's gotta be simplified because you're, we're asking the devs now to be security pros, correct. Secure the run time, secure the paths, you know, secure the containers. And so they need help. This is not what they wake up in the morning passionate about. Right. >>But that is where the guardrails comes in. Totally. Yeah. So a a developer, why should they care? They should just say, look, I'm developing for the credit card industry. I need a PCI compliant environment. And then let us take care of defining that environment, deploying that environment, managing that environment on an ongoing basis, they should be building code. Yeah. Right. But there is a change also, which is in the past, these were like two different islands and two different views with aria graft. We also have created this unified API that a developer could query or an ops could query to create a common understanding of the environment. So you're not looking at, you know, the elephant won the trunk and the other one, the tail you're looking at it in a common way. >>Can you talk about the collaboration between tan zoo and aria portfolios? Because obviously the VMware customers are investing in tan zoo. A lot of stuff's coming outta the oven. We heard some Dave heard some stuff from Chris Wolf and he's gonna come on tomorrow. And Raghu was hinting at some other stuff. That's not yet public, but you know, this things happening, >>Things happening, lot of >>Things, you know, you know, announcements happened years ago last year. Now some fruit's coming off the tree, this is a hot product aria. It makes a lot of sense for the customers. Where's the cloud native stuff, kicking, connecting in. What's the give us the overview what's connection >>Is lots and lots of connections. So you have a beautiful Kubernetes environment and a cloud native platform. You have accelerated app development. Now you're building more apps, more microservices based apps, more fragmented data, more information. So think of aria as an envelope around all of this. So wherever you are, whether you are building an application, deploying an application, managing an application, retiring an application through that life cycle, we can bring that management. So what we are doing with Tansu is with the platform, develop and platform. Now we can hook in management with a common perspective earlier in the life cycle. I don't have to wait for it to go to production to start saying, is it secure? Is it configured? How is it performing? What is my cost trade off as a developer, I've decided to, to fix a latency issue, I'm gonna add a new region or I'm gonna scale out a particular tier. Do I know how much it'll cost me? Can I give you that right at your fingertips, potentially even within the development platform and within the ID, that's the power, right? So bringing Ary, >>Not a lot of heavy lifting on the develop. So it's pretty much almost like a query to a database or >>As simple API that they can just query as part of their development process. Yeah. So by bringing aria and Tansu and really aria en developing Tansu right. You're able to bring that power >>Developer. I just always smile because you, I remember we, we have a group called the cloud. AATI the early OG found cloud. >>AATI >>The early days of cloud. When we were talking about infrastructure as code yes. Way back when, and finally it's actually happening. So what you're describing is infrastructure's code because now there's more complexity happening under the hard and top and you know, service are being turned on and off automatically. Yes. And sometimes you might not even know what's going on. Exactly. If you have guard rail, >>But you have to discover the state, know something has turned on, understand the implication and then synthesize, synthesize it down to the insight for the user. >>You know, a lot of people have been complaining about other older companies. Like Splunks the world who have great logging technology for gen one cloud, but now these new logging logging becomes a problem. Can you talk about how you guys are handling that? Give confidence or yeah. Explain that there's everything's gonna be logged properly. Yeah. >>So, so really look, there are three disciplines that we have management. Discipl like, ultimately there are thousands of names, but it boils down to you're managing the cost. You're managing the security, you're managing the performance of your applications. That is it. Right. So what we found is when you think of these disciplines as siloed load solutions, you can't ask a simple question as what is my cost performance trade off. You can't ask a simple question as, Hey, I'm improving performance. How, what is the implication of security? And that's when you start building complex solutions that say, okay, let me collect log from here. Let me collect this from here. Then let me correlate and normalize an application definition and tell you something and then put it in a spreadsheet and put it in a spreadsheet finally for manual work. Exactly. So one of the pillars is about managing performance. >>We have very powerful capabilities today in our portfolio. Tansu observability, which is part of aria portfolio. We realize log, which is part of aria portfolio, networks, insights, and operations. So with the common, when you, when you have a common language, we have a common language. We understand each other. Similarly with Ary graph and aria hub, we have creating this common language. So once we create a common language, all the various observability and log solutions have a meaning. They have relevance. And so we are able to take the noise from all these systems and synthesize it down to what we call business insights. And that's what is one of the big announcement as part of aria, awesome take data, which we have lots of and convert it to information. >>Give us the bumper sticker on why VMware. >>Well, I I'll tell you, when you talk about various public clouds, each public cloud has their native solutions. I've got control tower, I've got cloud wash, cloud trail, different solutions, and some of the hyperscalers are also expanding their solutions to other cloud. I think VMware in a way, from a multi-cloud perspective, we are in a wonderfully neutral position. Not only do we have a wealth of technology and assets that we can bring to the game, but we can also do it evenly across all clouds. So, so look at something like cost. Do you trust one of the hyperscalers to tell you that what is the cost comparison between them and another hyperscaler? That is where the VMware value comes in? >>I think people just try to hear what the cost of one cloud. Exactly, exactly. That is often people make money doing that is a job. No, >>No, definitely. Even a single cloud. What is the cost? >>It's a cloud economist out there and we know who he is. Corey Corey, a friend of the cube. He does it for his living. So help people figure out their bill. Exactly. Just on one cloud. >>Exactly. It's one cloud. So being able, we have the unique position where, and the right sets of technologies and experiences to bring that solution to bear across multicloud. Right. Great. >>What's your vision real quick. One minute left. What's your vision for the group? What are you investing in? What's your goals? What are you trying to do? Ask you the products. New. Gonna roll that out. What's what's the plan. I >>Really, again, the biggest one, the, the, the tagline I talked about, right. I, I, I want to, you know, I'm telling customers, managing stuff is boring. Don't waste your time on it. Let us take care of it. Right? So make the cloud complexity invisible so that you can focus on building your applications and everything that we do in the business unit is targeted towards that one goal. It is not about doing more features, more capabilities. It's are you solving customers questions? And we start from question down, >>Be thank you for spending your valuable time here in the cube, explaining the new news. Appreciate it. All right. Get lunch. After the short breaks, stay more with the cube live here in San Francisco for VMware Explorer, 22. I'm John that's. Dave. >>Thank you.

>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

>>Good morning, everyone. Welcome back to the Cube's coverage of snowflake summit live from Caesar's forum in Las Vegas, Lisa Martin, with Dave Valante. Dave, we have had an action packed two days here, talking with loads of folks. There's been about 10,000 attendees here, the momentum, the excitement for snowflake, what they're building, what they're, what they've announced is huge. >>I'll tell you like this is a getaway day and there's still decent amount of buzz going on in the ecosystem here and the exhibit hall. And I was just saying, when you walk around Las Vegas, you'd never know the economy's about the tank with, you know, inflation is on the rise. I mean, Vegas is packed. >>It is packed it a lot of shows going on here. We are excited to welcome Patrick Barch, the senior director of product management at capital one software to the program. Patrick, it's great to have you. >>Thank you. It's great to be here. >>So we all know capital one. I love the commercials. I'm sure you have a, a large say in how fun and creative they are. Talk to us about capital one software. This is a new business software business. It >>Is. And so, you know, from our founding days in 1994, capital one has always recognized the power of data and technology to create differentiated experiences for our customers. But about 10 years ago, we declared that we were gonna reinvent the way that we build and use technology. One of the key steps in that journey was migrating from our owned and operated data centers to the public cloud. But in order to do that, we needed to build a number of products and platforms to help us operate at scale because the market just wasn't quite there yet. And so capital one software, which we announced last week, Woohoo is our first foray into bringing some of those cloud and data management products to market. >>Talk to us about you. Capital one is one of Snowflake's longest running and largest customers. How does snowflake help facilitate that >>A couple different ways? So first snowflake is a, it's a super powerful platform. They've changed the game when it comes to leveraging data. At scale in the cloud, we were an early investor. We were, we were one of their biggest customers. They've been a great partner along the way, helping us adopt the platform. But for us, when we adopted back in 2018 ish, we realized that with all of this power comes a lot of responsibility. And so we needed to make sure that we were putting good governance and good controls around our usage of snowflake from the start. And so, you know, we, we, we needed to build some, some tools to help us optimize our, our usage of snowflake. >>Okay. So you basically said we're going all in the cloud. You guys have made huge investments in, in AWS and obviously snowflake. And then now you're, you're sort of taking what you did internally and exposing it almost like, like Amazon did Amazon retail and then that's how AWS was born. Okay, awesome. What kind of results did you see internally in terms of the primary benefit? If I understand it is cost savings, but also better data management, right? Is that fair? >>So the, the totality of what we've built internally covers both cost savings, data management, data security, adherence to data privacy legislation. The product that we announced here at summit is really focused on cost optimization for snowflake, right? And so with these tools, we've been able to save about 27% on our projected snowflake costs. We've been able to save our teams about 50,000 hours of manual effort by reducing the number of change orders that they have to execute manually through automated infrastructure management. We've reduced our cost per query by about 43%. And so really what these enabled us to do is just get really efficient with how we use the system. You know, one, one of the challenges you might run into with snowflake is, is unexpected costs. And so by leveraging these tools, we've been able to make sure that our costs are predictable and consistent from month to month, which enables us to budget appropriately. >>And, and that's 50,000 hours person hours over what period of time >>Have to get back to you on the exact amounts? I mean, >>Years, months, several years. Weeks. Yeah. Yeah. Okay. So, but we're talking about tens and tens of millions of dollars, right? If you, I mean, just assume a hundred bucks an hour for, for a person just fully loaded. I mean, I'll just do that math. Okay. And 20% percent on snowflake cost. So here's, here's the question? Well, well, first of all, what's the vision, what's the like gimme a five year vision for, for the software group at capital one, >>We wanna bring capital one's data and cloud management expertise to the masses. Okay. We've spoken to a number of companies that are trying to follow in our footsteps. We've, we've heard again and again, that our challenges are their challenges. Our, the path that we walked is the path that they're trying to walk in. So we are super excited about bringing all of our expertise to the market. >>So start with cost savings, but the vision transcends cost savings, absolutely going into security, privacy, data management, >>Absolutely absolutely workflow. And the, the, you know, the industry's in a super interesting place now where it's very fragmented. There is a galaxy of tools out there. You, you look around here, there's hundreds and hundreds of different solutions, but they're point solutions. They're all going after an individual piece of the management puzzle. And what we found was that we needed to create these integrated experiences that were aligned to our team's jobs to be done, not necessarily in terms of, you know, a capability like cataloging or quality or entitlements, you know, in order to efficiently operate at scale, you need to string those things together in a way that lets your team get their job done. >>So my last question on this flow is, I dunno if you're familiar with you guys, maybe familiar with Sarah Wong and Martin CASAA published a piece that got, you know, pretty wide viewing and discussion. They are out out of Andreesen, a 16 Z that the cost of good sold for SaaS companies who are born in the cloud are gonna become so overwhelming that they're gonna repatriate and start managing themselves. And they use Dropbox as an example. Now Dropbox is storage. So it's very specific niche, you know, and I've talked to many, many companies like snowflake about this, and they're like, eh, that ain't happening anytime soon. How do you feel about that? Because if you look at SAS companies that are born in the cloud, their gross margins are, you know, they don't get to 90%, but they're healthy, you know, 75, you know, sometimes 78% even snowflakes, you know, end of decade forecast Scarelli has it. I think it's 78%. And the reason it's not higher is because of the cloud cost. You gotta pay the cloud bills, my belief and I've argued, this is that's okay. I can negotiate cloud bills. I can work with tools like yours over time to keep those down. And the cloud guys are gonna be competing with each other, but, but what do you make of that Patrick >>Cloud costs? Aren't gonna go down. Data is expanding at an exponential rate. The scale of data today is orders of magnitude versus what it was in on-prem systems. And so, you know, I don't think the cloud providers are too worried because data is exploding at such a, a crazy pace. And so it really becomes about using all of those resources as efficiently as possible. And, and in the cloud where compute is fully elastic, it scales infinitely instantly on demand. You know, it's all about getting it's, it's, it's all about making sure that if you're spending more, you're getting more business value. There's not wastage in the system. >>Same question, but different. Do you feel like strategically organizations generally in capital one specifically will, will, will optimize their time on optimizing or spend their, their effort optimizing the cloud costs? Or do you feel like long term you can actually be cheaper to manage yourself? In other words, our, our cloud benefits of not doing all that heavy lifting offset that potential, you know, cost equation. >>I mean, you saved just so much time and effort and headache, not having to manage physical infrastructure. And so like, you know, snowflake, you can write a sequel command to create a database. You can write a sequel command to create a data warehouse. Like the market will not give up that level of simplicity for managing infrastructure. And so I think at the end of the day, you're gonna, you're gonna see a focus on efficiency because what you really want your teams to be focused on your old, your old DBA and data engineering teams is focused on driving customer value, not in the weeds of infrastructure management. >>And that's why I think you guys, this is a great business that you're starting. And I think you, I, frankly, I think you're gonna get a lot of competition, which is a good thing that says you're in a great business and you guys are first >>Talk about the customer experience. You know, we are also as consumers demanding, we wanna be able to transact ASAP. We wanna make sure that, you know, on the swipe fraud detection happens, how does the Slingshot help facilitate and improve the customer experience if I'm transacting or I'm gonna sign up or I'm getting a mortgage. >>So with Slingshot, we enable your company, regardless of what you do at, at capital one, we're, we're a bank to build more personalized experiences for customers in a more cost effective way. And so Enno is our, our intelligent, personal banking assistant with snowflake. We're enable Enno to do way more than we were previously for less than we would've without some of these tools. >>And that's a huge competitive differentiator because we expect as consumers and of whatever it is. We want a personalized experience, right? That's relevant. That's gonna offer us products and services that might build upon what we've already done. >>It's it's kind of table stakes these days. Yes. And so with these tools and with snowflake, we were able to onboard our business teams were able to onboard over 400 new use cases over, over that same time period. And so really what it's enabled us to do is unlock the innovative power of our company and create more of these customer experiences. >>How does the customer visualize those, those cost savings? And, and, and do, do, do you have some tooling, maybe it's in the works to help them predict what kind of cost savings they have based on some modeling that >>You do. And absolutely. So we enable teams to enforce good governance around infrastructure management, up front by building rules and enabling their teams to create warehouses, create databases. And then once that infrastructure is up and running, we give them a whole bunch of dashboards that show transparency and to spend, we enable chargebacks to lines of business in today's consumption, driven business models. It's hard to reconcile at the end of the month, if you spent what you thought you spent and, and data costs have gone from CapEx to OPEX and, but not everybody is an expert. And so we look at usage data, we look at usage history and we come up with recommendations for how you can save money by, you know, tweaking this or tweaking that or better optimizing your, your compute. >>Should we expect you as you expand your opportunity to take your expertise and aim it at AWS more broadly, maybe Redshift more specifically, Google GCP, big query Azure, what, what should we expect there? >>You know, there's, there's a lot of opportunity to help companies optimize costs across other cloud providers as well. This, this concept of elastic compute, isn't just specific to snowflake. That's certainly one path that we could go down. You know, we have a lot of expertise in, in data management as well, and data privacy, data security. And so that's that, that's another path as well that, that we have expertise in. And so, you know, I think it's, it's an exciting time we're in, we're in an exciting place, but it's early days, >>Did you do a working backwards document? Can you share that with us? >>Fortunately >>Not five, five or 10 years down the road, you may decide to do that, right? >>Yeah. Let me, let me check with my PR person to see if I'm allowed to share here. That's >>I mean, I think this is gonna be a huge success and, and I think it it's, it's, it follows a lot of the things that we've learned from AWS. Yeah. And you guys have been all in there and, and, you know, it's funny, right? We laugh about working backwards, customer obsession, two pizza teams. I mean, it really has changed the sort of way that we think about developing software and, and managing infrastructures. I, I think you're gonna have a, a huge business and I, I wish you the best. >>I, I appreciate that. And the, the thing, a lot of that statement is, you know, internal teams are now starting to demand consumer great experiences for the tools that they use. Yeah, for sure. And so one of the things that we did was treat our internal associates. Like they were external customers, we applied design thinking, we applied product management, we built our experience in terms of what are you trying to accomplish? And what's getting in your way, because that's what people have come to expect with all of these consumer experiences, >>Collaboration. That's right. What last question for you? What would you say to peers in your, whatever, same industry, other industries that are really trying to figure out how to get their hands on data to become a data company, what would you advise them? Why should they choose >>Snowflake gives you so many building blocks out of the box to help you create a, a well-managed data ecosystem? You know, the simplicity with which you can create new infrastructure, define policies for that infrastructure onboard new users. I mean, it, it's one of the platforms in internally capital one that has the highest NPS score. And so, you know, if you're looking to adopt a, a data cloud platform, I mean, snowflake is certainly high up on the list of what you should be looking at. >>That's >>Awesome. How do you, do you consider this a SA, is it a consumption or how do you price for this? >>So we, we don't have published pricing at the moment, but it is, it is a SAS product. You know, what we can share is it'll, it'll be a, you know, small fraction of, of your, of your total credit spend with snowflake and, and >>You're thinking a subscription or, or haven't figured that out yet, >>It it'll likely be a, a consumption model based on, you know. Okay. >>So the, so, so say, you know, it's funny SAS, I get it. Software's a service, but it, but because it's consumption, I think it's like modern SAS. If I can say that, you know, it's cloud >>SAS and it, it, you know, it's more important to make sure right now, because we're so early that we're actually providing the right value to customers. We have a pretty generous trial program going on right now where you can try the, the, the software out for free to make sure it, it fits your needs. So, >>Okay. So you're in trial, right. I should have clarified that you're in trial now. And, and so, yeah, of course you haven't figured out exactly how you're gonna price it yet. But >>The, the, the official posture that we're taking is public preview. We've, we've been in private preview for the last six months. We've onboarded a, a couple of customers who are starting to use the product. And so the, the big announcement this week is we're officially in public preview, come on in. >>So you gotta get product market fit. That's right. Before you figure out your pricing and before you, then you, then you're gonna scale. Great. >>What's been the feedback so far >>Overwhelmingly positive. Somebody stopped by the booth and said, oh my God, that's so cool. We've heard a lot of, wow, we need this right now. You know, it's, I had pretty, pretty high expectations coming in, just based on the value that this is created for capital one, but I've, I've been blown away by, by what I've heard from the people who've stopped by our booth. >>Awesome. Patrick, thank you for joining Dave and me on the program, talking about what you're doing with capital one software seems like you're just in early innings, but so much potential to come. We wish you the best of luck with that. And you have to come back and tell us how it's going. Thanks so much. Thanks for having me, our pleasure for Dave ante. I'm Lisa Martin. You're watching the cube our day three coverage of snowflake summit 22 live from Las Vegas continues after a short break.

>>Okay. We're back with Ari Basu, who is Cisco's resident philosopher, who also holds a master's in computer science. We're gonna have to unpack that a little bit and Najati chair he who's technical lead at Cisco. Welcome guys. Thanks for coming on the cube. >>Happy to be here. Thanks a >>Lot. All right, let's get into it. We want you to explain how Cisco validated the SBRI technology and the proof points that, that you have, that it actually works as advertised. So first Outre tell first, tell us about Cisco tech. What does Cisco tech do? >>So T is otherwise it's an acronym for technical assistance center is Cisco's support arm, the support organization, and, you know, the risk of sounding like I'm spotting a corporate line. The, the easiest way to summarize what tag does is provide world class support to Cisco customers. What that means is we have about 8,000 engineers worldwide, and any of our Cisco customers can either go on our web portal or call us to open a support request. And we get about 2.2 million of these support requests a year. And what these support requests are, are essentially the customer will describe something that they need done some networking goal that they have, that they wanna accomplish. And then it's tax job to make sure that that goal does get accomplished. Now, it could be something like they're having trouble with an existing network solution, and it's not working as expected, or it could be that they're integrating with a new solution. >>They're, you know, upgrading devices, maybe there's a hardware failure, anything really to do with networking support and, you know, the customer's network goals. If they open up a case for request for help, then tax job is to, is to respond and make sure the customer's, you know, questions and requirements are met about 44% of these support requests are usually trivial and, you know, can be solved within a call or within a day. But the rest of tax cases really involve getting into the network device, looking at logs. It's a very technical role. It's a very technical job. You're look you're, you need to be conversing with network solutions, their designs protocols, et cetera. >>Wow. So 56% non-trivial. And so I would imagine you spend a lot of time digging through through logs. Is that, is that true? Can you quantify that like, you know, every month, how much time you spend digging through logs and is that a pain point? >>Yeah, it's interesting. You asked that because when we started this on this journey to augment our support engineers workflow with zebra solution, one of the things that we did was we went out and asked our engineers what their experience was like doing log analysis. And the anecdotal evidence was that on average, an engineer will spend three out of their eight hours reviewing logs, either online or offline. So what that means is either with the customer live on a WebEx, they're going to be going over logs, network, state information, et cetera, or they're gonna do it offline, where the customer sends them the logs, it's attached to a, you know, a service request and they review it and try to figure out what's going on and provide the customer with information. So it's a very large chunk of our day. You know, I said 8,000 plus engineers, and so three hours a day, that's 24,000 man hours a day spent on long analysis. >>Now the struggle with logs or analyzing logs is there by out of necessity. Logs are very contr contr. They try to pack a lot of information in a very little space. And this is for performance reasons, storage reasons, et cetera, BEC, but the side effect of that is they're very esoteric. So they're hard to read if you're not conversant, if you're not the developer who wrote these logs or you or you, aren't doing code deep dives. And you're looking at where this logs getting printed and things like that, it may not be immediately obvious or even after a low while it may not be obvious what that log line means or how it correlates to whatever problem you're troubleshooting. So it requires tenure. It requires, you know, like I was saying before, it requires a lot of knowledge about the protocol what's expected because when you're doing log analysis, what you're really looking for is a needle in a haystack. You're looking for that one anomalous event, that single thing that tells you this shouldn't have happened. And this was a problem right now doing that kind of anomaly detection requires you to know what is normal. It requires, you know, what the baseline is. And that requires a very in-depth understanding of, you know, the state changes for that network solution or product. So it requires time, tenure and expertise to do well. And it takes a lot of time even when you have that kind of expertise. >>Wow. So thank you, archery. And Najati, that's, that's about, that's almost two days a week for, for a technical resource. That's that's not inexpensive. So what was Cisco looking for to sort of help with this and, and how'd you stumble upon zebra? >>Yeah, so, I mean, we have our internal automation system, which has been running more than a decade now. And what happens is when a customer attaches a log bundle or diagnostic bundle into the service request, we take that from the Sr we analyze it and we represent some kind of information. You know, it can be alert or some tables, some graph to the engineer, so they can, you know, troubleshoot this particular issue. This is an incredible system, but it comes with its own challenges around maintenance to keep it up to date and relevant with Cisco's new products or new version of the product, new defects, new issues, and all kind of things. And when I, what I mean with those challenges are, let's say Cisco comes up with a product today. We need to come together with those engineers. We need to figure out how this bundle works, how it's structured out. >>We need to select individual logs, which are relevant and then start modeling these logs and get some values out of those logs, using pars or some rag access to come to a level that we can consume the logs. And then people start writing rules on top of that abstraction. So people can say in this log, I'm seeing this value together with this other value in another log, maybe I'm hitting this particular defect. So that's how it works. And if you look at it, the abstraction, it can fail the next time. And the next release when the development or the engineer decides to change that log line, which you write that rag X, or we can come up with a new version, which we completely change the services or processes, then whatever you have wrote needs to be re written for that new service. And we see that a lot with products, like for instance, WebEx, where you have a very short release cycle that things can change maybe the next week with a new release. >>So whatever you are writing, especially for that abstraction and for those rules are maybe not relevant with that new release. With that being sake, we have a incredible rule creation process and governance process around it, which starts with maybe a defect. And then it takes it to a level where we have an automation in place. But if you look at it, this really ties to human bandwidth. And our engineers are really busy working on, you know, customer facing, working on issues daily and sometimes creating these rules or these pars are not their biggest priorities, so they can be delayed a bit. So we have this delay between a new issue being identified to a level where we have the automation to detect it next time that some customer faces it. So with all these questions and with all challenges in mind, we start looking into ways of actually how we can automate these automations. >>So these things that we are doing manually, how we can move it a bit further and automate. And we had actually a couple of things in mind that we were looking for and this being one of them being, this has to be product agnostic. Like if Cisco comes up with a product tomorrow, I should be able to take it logs without writing, you know, complex regs, pars, whatever, and deploy it into this system. So it can embrace our logs and make sense of it. And we wanted this platform to be unsupervised. So none of the engineers need to create rules, you know, label logs. This is bad. This is good. Or train the system like which requires a lot of computational power. And the other most important thing for us was we wanted this to be not noisy at all, because what happens with noises when your level of false PE positives really high your engineers start ignoring the good things between that noise. >>So they start the next time, you know, thinking that this thing will not be relevant. So we want something with a lot or less noise. And ultimately we wanted this new platform or new framework to be easily adaptable to our existing workflows. So this is where we started. We start looking into the, you know, first of all, internally, if we can build this thing and also start researching it, and we came up to Zeum actually Larry, one of the co co-founders of Zeum. We came upon his presentation where he clearly explained why this is different, how this works, and it immediately clicked in. And we said, okay, this is exactly what we were looking for. We dived deeper. We checked the block posts where SBRI guys really explained everything very clearly there, they are really open about it. And most importantly, there is a button in their system. >>So what happens usually with AI ML vendors is they have this button where you fill in your details and sales guys call you back. And, you know, we explain the system here. They were like, this is our trial system. We believe in the system, you can just sign up and try it yourself. And that's what we did. We took our, one of our Cisco live DNA center, wireless platforms. We start streaming logs out of it. And then we synthetically, you know, introduce errors, like we broke things. And then we realized that zebra was really catching the errors perfectly. And on top of that, it was really quiet unless you are really breaking something. And the other thing we realized was during that first trial is zebra was actually bringing a lot of context on top of the logs. During those failures, we work with couple of technical leaders and they said, okay, if this failure happens, I I'm expecting this individual log to be there. And we found out with zebra, apart from that individual log, there were a lot of other things which gives a bit more context around the root columns, which was great. And that's where we wanted to take it to the next level. Yeah. >>Okay. So, you know, a couple things to unpack there. I mean, you have the dart board behind you, which is kind of interesting, cuz a lot of times it's like throwing darts at the board to try to figure this stuff out. But to your other point, Cisco actually has some pretty rich tools with AppD and doing observability and you've made acquisitions like thousand eyes. And like you said, I'm, I'm presuming you gotta eat your own dog food or drink your own champagne. And so you've gotta be tools agnostic. And when I first heard about Z zebra, I was like, wait a minute. Really? I was kind of skeptical. I've heard this before. You're telling me all I need is plain text and, and a timestamp. And you got my problem solved. So, and I, I understand that you guys said, okay, let's run a POC. Let's see if we can cut that from, let's say two days a week down to one day, a week. In other words, 50%, let's see if we can automate 50% of the root cause analysis. And, and so you funded a POC. How, how did you test it? You, you put, you know, synthetic, you know, errors and problems in there, but how did you test that? It actually works Najati >>Yeah. So we, we wanted to take it to the next level, which is meaning that we wanted to back test is with existing SARS. And we decided, you know, we, we chose four different products from four different verticals, data center, security, collaboration, and enterprise networking. And we find out SARS where the engineer put some kind of log in the resolution summary. So they closed the case. And in the summary of the Sr, they put, I identified these log lines and they led me to the roots and we, we ingested those log bundles. And we, we tried to see if Zeum can surface that exact same log line in their analysis. So we initially did it with archery ourself and after 50 tests or so we were really happy with the results. I mean, almost most of them, we saw the log line that we were looking for, but that was not enough. >>And we brought it of course, to our management and they said, okay, let's, let's try this with real users because the log being there is one thing, but the engineer reaching to that log is another take. So we wanted to make sure that when we put it in front of our users, our engineers, they can actually come to that log themselves because, you know, we, we know this platform so we can, you know, make searches and find whatever we are looking for, but we wanted to do that. So we extended our pilots to some selected engineers and they tested with their own SRSS. Also do some back testing for some SARS, which are closed in the past or recently. And with, with a sample set of, I guess, close to 200 SARS, we find out like majority of the time, almost 95% of the time the engineer could find the log they were looking for in zebra analysis. >>Yeah. Okay. So you were looking for 50%, you got to 95%. And my understanding is you actually did it with four pretty well known Cisco products, WebEx client DNA center, identity services, engine ISE, and then, then UCS. Yes. Unified pursuit. So you use actual real data and, and that was kind of your proof proof point, but Ari. So that's sounds pretty impressive. And, and you've have you put this into production now and what have you found? >>Well, yes, we're, we've launched this with the four products that you mentioned. We're providing our tech engineers with the ability, whenever a, whenever a support bundle for that product gets attached to the support request. We are processing it, using sense and then providing that sense analysis to the tech engineer for their review. >>So are you seeing the results in production? I mean, are you actually able to, to, to reclaim that time that people are spending? I mean, it was literally almost two days a week down to, you know, a part of a day, is that what you're seeing in production and what are you able to do with that extra time and people getting their weekends back? Are you putting 'em on more strategic tasks? How are you handling that? >>Yeah. So, so what we're seeing is, and I can tell you from my own personal experience using this tool, that troubleshooting any one of the cases, I don't take more than 15 to 20 minutes to go through the zebra report. And I know within that time either what the root causes or I know that zebra doesn't have the information that I need to solve this particular case. So we've definitely seen, well, it's been very hard to measure exactly how much time we've saved per engineer, right? What we, again, anecdotally, what we've heard from our users is that out of those three hours that they were spending per day, we're definitely able to reclaim at least one of those hours and, and what, even more importantly, you know, what the kind of feedback that we've gotten in terms of, I think one statement that really summarizes how Zebra's impacted our workflow was from one of our users. >>And they said, well, you know, until you provide us with this tool, log analysis was a very black and white affair, but now it's become really colorful. And I mean, if you think about it, log analysis is indeed black and white. You're looking at it on a terminal screen where the background is black and the text is white, or you're looking at it as a text where the background is white and the text is black, but what's what they're really trying to say. Is there hardly any visual cues that help you navigate these logs, which are so esoteric, so dense, et cetera. But what XRM does is it provides a lot of color and context to the whole process. So now you're able to quickly get to, you know, using their word cloud, using their interactive histogram, using the summaries of every incident. You're very quickly able to summarize what might be happening and what you need to look into. >>Like, what are the important aspects of this particular log bundle that might be relevant to you? So we've definitely seen that a really great use case that kind of encapsulates all of this was very early on in our experiment. There was, there was this support request that had been escalated to the business unit or the development team. And the tech engineer had really, they, they had an intuition about what was going wrong because of their experience because of, you know, the symptoms that they'd seen. They kind of had an idea, but they weren't able to convince the development team because they weren't able to find any evidence to back up what they thought was happening. And we, it was entirely happenstance that I happened to pick up that case and did an analysis using Seebri. And then I sat down with the attack engineer and we were very quickly within 15 minutes, we were able to get down to the exact sequence of events that highlighted what the customer thought was happening, evidence of what the, so not the customer, what the attack engineer thought was the, was a root cause. It was a rude pause. And then we were able to share that evidence with our business unit and, you know, redirect their resources so that we could change down what the problem was. And that really has been, that that really shows you how that color and context helps in log analysis. >>Interesting. You know, we do a fair amount of work in the cube in the RPA space, the robotic process automation and the narrative in the press when our RPA first started taking off was, oh, it's, you know, machines replacing humans, or we're gonna lose jobs. And, and what actually happened was people were just eliminating mundane tasks and, and the, the employee's actually very happy about it. But my question to you is, was there ever a reticence amongst your team? Like, oh, wow, I'm gonna, I'm gonna lose my job if the machine's gonna replace me, or have you found that people were excited about this and what what's been the reaction amongst the team? >>Well, I think, you know, every automation and AI project has that immediate gut reaction of you're automating away our jobs and so forth. And there is initially there's a little bit of reticence, but I mean, it's like you said, once you start using the tool, you realize that it's not your job, that's getting automated away. It's just that your job's becoming a little easier to do, and it's faster and more efficient. And you're able to get more done in less time. That's really what we're trying to accomplish here at the end of the day, rim will identify these incidents. They'll do the correlation, et cetera. But if you don't understand what you're reading, then that information's useless to you. So you need the human, you need the network expert to actually look at these incidents, but what we are able to skin away or get rid of is all of the fat that's involved in our, you know, in our process, like without having to download the bundle, which, you know, when it's many gigabytes in size, and now we're working from home with the pandemic and everything, you're, you know, pulling massive amounts of logs from the corporate network onto your local device that takes time and then opening it up, loading it in a text editor that takes time. >>All of these things are we're trying to get rid of. And instead we're trying to make it easier and quicker for you to find what you're looking for. So it's like you said, you take away the mundane, you take away the, the difficulties and the slog, but you don't really take away the work, the work still needs to be done. >>Yeah. Great guys. Thanks so much. Appreciate you sharing your story. It's quite, quite fascinating. Really. Thank you for coming on. >>Thanks for having us. >>You're very welcome. Okay. In a moment, I'll be back to wrap up with some final thoughts. This is Dave Valante and you're watching the, >>So today we talked about the need, not only to gain end to end visibility, but why there's a need to automate the identification of root cause problems and doing so with modern technology and machine intelligence can dramatically speed up the process and identify the vast majority of issues right out of the box. If you will. And this technology, it can work with log bundles in batches, or with real time data, as long as there's plain text and a timestamp, it seems Zebra's technology will get you the outcome of automating root cause analysis with very high degrees of accuracy. Zebra is available on Preem or in the cloud. Now this is important for some companies on Preem because there's really some sensitive data inside logs that for compliance and governance reasons, companies have to keep inside their four walls. Now SBRI has a free trial. Of course they better, right? So check it out@zebra.com. You can book a live demo and sign up for a free trial. Thanks for watching this special presentation on the cube, the leader in enterprise and emerging tech coverage on Dave Valante and.

(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)

>>Hello, and welcome back to the live cube coverage here in San Francisco, California, the cube live coverage. Two days, day two of a summit 2022, a summit New York city coming up in the summer. We'll be there as well. Events are back. I'm the host, John fur, the cube got great guest here, Johnny Dallas with Ze. Um, here's on the cube. We're gonna talk about his background. Uh, little trivia here. He was the youngest engineer ever worked at Amazon at the age. 17 had to get escorted into reinvent in Vegas cause he was underage <laugh> with security, all good stories. Now the CEO of gonna called Ze know DevOps kind of focus, managed service, a lot of cool stuff, John, welcome to the cube. >>Thanks John. Great. >>So tell a story. You were the youngest engineer at AWS. >>I was, yes. So I used to work at a company called Bebo. I got started very young. I started working when I was about 14, um, kind of as a software engineer. And when I, uh, was about 16, I graduated out of high school early. Um, worked at this company, Bebo running all of the DevOps at that company. Um, I went to reinvent in about 2018 to give a talk about some of the DevOps software I wrote at that company. Um, but you know, as many of those things are probably familiar with reinvent happens in a casino and I was 16, so I was not able to actually go into the casino on my own <laugh> um, so I'd have <inaudible> security as well as C security escort me in to give my talk. >>Did Andy jazzy, was he aware of this? >>Um, you know, that's a great question. I don't know. <laugh> >>I'll ask him great story. So obviously you started a young age. I mean, it's so cool to see you jump right in. I mean, I mean, you never grew up with the old school that I used to grew up in loading package software, loading it onto the server, deploying it, plugging the cables in, I mean you just rocking and rolling with DevOps as you look back now what's the big generational shift because now you got the Z generation coming in, millennials are in the workforce. It's changing. Like no one's putting package software on servers. >>Yeah, no, I mean the tools keep getting better, right? We, we keep creating more abstractions that make it easier and easier. When I, when I started doing DevOps, I could go straight into E two APIs. I had APIs from the get go and you know, my background was, I was a software engineer. I never went through like the CIS admin stack. I, I never had to, like you said, rack servers, myself. I was immediately able to scale to I, I was managing, I think 2,500 concurrent servers across every Ables region through software. It was a fundamental shift. >>Did you know what an SRE was at that time? Uh, you were kind of an SRE on >>Yeah, I was basically our first SRE, um, familiar with the, with the phrasing, but really thought of myself as a software engineer who knows cloud APIs, not a SRE. >>All right. So let's talk about what's what's going on now, as you look at the landscape today, what's the coolest thing that's going on in your mind and cloud? >>Yeah, I think the, I think the coolest thing is, you know, we're seeing the next layer of those abstraction tools exist and that's what we're doing with Ze is we've basically gone and we've, we're building an app platform that deploys onto your cloud. So if you're familiar with something like Carku, um, where you just click a GitHub repo, uh, we actually make it that easy. You click a GI hub repo and it'll deploy on a AWS using Al AWS tools. >>So, right. So this is Z. This is the company. Yes. How old's the company >>About a year and a half old now. >>Right. So explain what it does. >>Yeah. So we make it really easy for any software engineer to deploy on a AWS. Um, that's not SREs. These are the actual application engineers doing the business logic. Mm-hmm <affirmative> they don't really want to think about Yamo. They don't really want to configure everything super deeply. Um, they want to say, run this API on a AWS in the best way possible. We've encoded all the best practices into software and we set it up for you. >>Yeah. So I think the problem you're solving is, is that there's a lot of want to be DevOps engineers. And then they realize, oh shit, I don't wanna do this. Yeah. And the people want to do it. They loved under the hood. Right. People love that infrastructure, but the average developer needs to actually be as agile on scale. So that seems to be the problem you solve. Right? Yeah. >>We, we, we give way more productivity to each individual engineer, you know? >>All right. So let me ask you a question. So let me just say, I'm a developer. Cool. I built this new app. It's a streaming app or whatever. I'm making it up cube here, but let's just say I deploy it. I need your service. But what happens about when my customers say, Hey, what's your SLA? The CDN went down from this it's flaky. Does Amazon have? So how do you handle all that SLA reporting that Amazon provides? Cause they do a good job with sock reports all through the console. But as you start getting into DevOps and sell your app, mm-hmm <affirmative> you have customer issues. You, how do you view that? Yeah, >>Well, I, I think you make a great point of AWS has all this stuff already. AWS has SLAs. AWS has contract. Aw, has a lot of the tools that are expected. Um, so we don't have to reinvent the wheel here. What we do is we help people get to those SLAs more easily. So, Hey, this is a AWS SLA as a default. Um, Hey, we'll configure your services. This is what you can expect here. Um, but we can really leverage AWS reli ability of you don't have to trust us. You have to trust S and trust that the setup is good there. >>Do you handle all the recovery or mitigation between, uh, identification say downtime for instance, oh, the servers not 99% downtime, uh, went down for an hour, say something's going on? And is there a service dashboard? How does it get what's the remedy? Do you have, how does all that work? >>Yeah, so we have some built in remediation. You know, we, we basically say we're gonna do as much as we can to keep your endpoint up 24 7 mm-hmm <affirmative>. If it's something in our control, we'll do it. If it's a disc failure, that's on us. If you push bad code, we won't put out that new version until it's working. Um, so we do a lot to make sure that your endpoint stays up, um, and then alert you if there's a problem that we can't fix. So cool. Hey, S has some downtime, this thing's going on. You need to do this action. Um, we'll let you know. >>All right. So what do you do for fun? >>Yeah, so, uh, for, for fun, um, a lot of side projects. <laugh>, uh, >>What's your side hustle right now. You got going on >>The, uh, it's a lot of schools playing >>With serverless. >>Yeah. Playing with a lot of serverless stuff. Um, I think there's a lot of really cool Lam stuff as well, going on right now. Um, I love tools is, is the truest answer is I love building something that I can give to somebody else. And they're suddenly twice as productive because of it. Um, >>That's a good feeling, isn't it? Oh >>Yeah. There's nothing >>Like that. Tools versus platforms. Mm-hmm, <affirmative>, you know, the expression, too many tools in the tool, she becomes, you know, tools for all. And then ultimately tools become platforms. What's your view on that? Because if a good tool works and starts to get traction, you need to either add more tools or start building a platform platform versus tool. What's your, what's your view on our reaction to that kind of concept debate? >>Yeah, it's a good question. Uh, we we've basically started as like a, a platform. First of we've really focused on these, uh, developers who don't wanna get deep into the DevOps. And so we've done all of the piece of the stacks. We do C I C D management. We do container orchestration, we do monitoring. Um, and now we're, spliting those up into individual tools so they can be used awesome in conjunction more. >>Right. So what are some of the use cases that you see for your service? It's DevOps basically nano service DevOps for people on a DevOps team. Do clients have a DevOps person and then one person, two people what's the requirements to run >>Z? Yeah. So we we've got teams, um, from no DevOps is kind of when they start and then we've had teams grow up to about, uh, five, 10 man DevOps teams. Mm-hmm <affirmative> um, so, you know, as more structured people come in, because we're in your cloud, you're able to go in and configure it on top you're we can't block you. Uh, you wanna use some new AOL service. You're welcome to use that alongside the stack that we deploy for >>You. How many customers do you have now? >>So we've got about 40 companies that are using us for all of their infrastructure, um, kind of across the board, um, as well as >>What's the pricing model. >>Uh, so our pricing model is we, we charge basically similar to an engineer salary. So we charge, uh, a monthly rate. We have plans at 300 bucks a month, a thousand bucks a month, and then enterprise plan for based >>On the requirement scale. Yeah. You know, so back into the people cost, you must offer her discounts, not a fully loaded thing, is it? >>Yeah. There's a discounts kind of at scale, >>Then you pass through the Amazon bill. >>Yeah. So our customers actually pay for the Amazon bill themselves. Oh. So >>They have their own >>Account. There's no margin on top. You're linking your Aless account in, um, it, which is huge because we can, we are now able to help our customers get better deals with Amazon. Um, got it. We're incentivized on their team to drive your cost down. >>And what's your unit main unit of economics software scale. >>Yeah. Um, yeah, so we, we think of things as projects. How many services do you have to deploy as that scales up? Um, awesome. >>All right. You're 20 years old now you not even can't even drink legally. <laugh> what are you gonna do when you're 30? We're gonna be there. >>Well, we're, uh, we're making it better. And >>The better, the old guy on the cube here. >><laugh> I think, uh, I think we're seeing a big shift of, um, you know, we've got these major clouds. AWS is obviously the biggest cloud. Um, and it's constantly coming out with new services. Yeah. But we're starting to see other clouds have built many of the common services. So Kubernetes is a great example. It exists across all the clouds. Um, and we're starting to see new platforms come up on top that allow you to leverage tools from multiple clouds. At the same time. Many of our customers actually have AWS as their primary cloud and they'll have secondary clouds or they'll pull features from other clouds into AWS, um, through our software. I think that I'm very excited by that. And I, uh, expect to be working on that when I'm 30. Awesome. >>Well, you gonna have a good future. I gotta ask you this question cuz uh, you know, I've always, I was a computer science undergraduate in the, in the eighties and um, computer science back then was hardcore, mostly systems OS stuff, uh, database compiler. Um, now there's so much compi, right? So mm-hmm <affirmative> how do you look at the high school college curriculum experience slash folks who are nerding out on computer science? It's not one or two things much. You've got a lot of, a lot of things. I mean, look at Python, data engineering, merging as a huge skill. What's it? What's it like for college kids now and high school kids? What, what do you think they should be doing if you had to give advice to your 16 year old self back a few years ago now in college? Um, I mean Python's not a great language, but it's super effective for coding and the data's really relevant, but it's you got other language opportunities, you got tools to build. So you got a whole culture of young builders out there. What should, what should people gravitate to in your opinion stay away from yeah. Or >>Stay away from that's a good question. I, I think that first of all, you're very right of the, the amount of developers is increasing so quickly. Um, and so we see more specialization. That's why we also see, you know, these SREs that are different than typical application engineering. You get more specialization in job roles. Um, I think if, what I'd say to my 16 year old self is do projects, um, the, I learned most of my, what I've learned just on the job or online trying things, playing with different technologies, actually getting stuff out into the world, um, way more useful than what you'll learn in kind of a college classroom. I think classrooms great to, uh, get a basis, but you need to go out and experiment actually try things. >>You know? I think that's great advice. In fact, I would just say from my experience of doing all the hard stuff and cloud is so great for just saying, okay, I'm done, I'm abandoning the project. Move on. Yeah. Because you know, it's not gonna work in the old days. You have to build this data center. I bought all this certain, you know, people hang on to the old, you know, project and try to force it out there. >>You can launch a project, >>Can see gratification, it ain't working <laugh> or this is shut it down and then move on to something new. >>Yeah, exactly. Instantly you should be able to do that much more quickly. Right. >>So you're saying get those projects and don't be afraid to shut it down. Mm-hmm <affirmative> that? Do you agree with that? >>Yeah. I think it's ex experiment. Um, you're probably not gonna hit it rich on the first one. It's probably not gonna be that idea is DJing me this idea. So don't be afraid to get rid of things and just try over and over again. It's it's number of reps that a win. >>I was commenting online. Elon Musk was gonna buy Twitter, that whole Twitter thing. And, and, and someone said, Hey, you know, what's the, I go look at the product group at Twitter's been so messed up because they actually did get it right on the first time <laugh> and, and became such a great product. They could never change it because people would freak out and the utility of Twitter. I mean, they gotta add some things, the added button and we all know what they need to add, but the product, it was just like this internal dysfunction, the product team, what are we gonna work on? Don't change the product so that you kind of have there's opportunities out there where you might get the lucky strike, right. Outta the gate. Yeah. Right. You don't know, >>It's almost a curse too. It's you're not gonna Twitter. You're not gonna hit a rich second time too. So yeah. >><laugh> Johnny Dallas. Thanks for coming on the cube. Really appreciate it. Give a plug for your company. Um, take a minute to explain what you're working on, what you're looking for. You're hiring funding. Customers. Just give a plug, uh, last minute and have the last word. >>Yeah. So, um, John Dallas from Ze, if you, uh, need any help with your DevOps, if you're a early startup, you don't have DevOps team, um, or you're trying to deploy across clouds, check us out ze.com. Um, we are actively hiring. So if you are a software engineer excited about tools and cloud, or you're interested in helping getting this message out there, hit me up. Um, find a Z. >>Yeah. LinkedIn Twitter handle GitHub handle. >>Yeah. I'm the only Johnny on a LinkedIn and GitHub and underscore Johnny Dallas underscore on Twitter. Right? Um, >>Johnny Dallas, the youngest engineer working at Amazon. Um, now 20 we're on great new project here. The cube builders are all young. They're growing in to the business. They got cloud at their, at their back it's, uh, tailwind. I wish I was 20. Again, this is a cue. I'm John for your host. Thanks for watching. >>Thanks.

>>Hello, welcome to the special cube conversation. I'm John for your host of the queue here in Palo Alto, California. We're still remoting in getting great guests in events are coming back. Next few weeks, we'll be at a bunch of different events and you'll see the cube everywhere, but this conversation's about network challenges in a distributed hybrid workforce era. We've got a team say he principal, product manager, edge networking solutions, a Dell technologies and Rob McBride channel and partner sales engineer at versa networks. Gentlemen, thanks for coming on this cube conversation, >>John. Thank you, John. >>So first of all, obviously with the pandemic and now we're moving out of the pandemic, even with Omnichron out there, we still see visibility into kind of back to work and events and it's, but it's clearly hybrid environment cloud hybrid work. This has been a huge opening of everyone's eyes around network security provisioning, you know, unexpected disruptions around everyone being worked at home. Nobody really forecasted that. The fact that the whole workforce would be remote coming in. So again, put a lot of pressure on the network challenges over over the past two years. How is it coming out of this different what's your guys' take on this. >>Yeah, to then when we start looking at it, let's kind of focus a little bit on challenges, you know, you know, when this all kind of started off, obviously, as you stated, right, everyone was kind of taken by surprise in a way, right? What do we do? We don't know what to do at this moment. And you know, I go back and I remember a customer giving me a call, you know, when they were at first looking at, you know, your traditional land transformation and one of the changed their branches to do something from an SD perspective. And then the pandemic hit. And their question to me was Rob, what do I do? Or what do I need to start thinking about now, all of a sudden to your point, right? Everyone now is no longer in the office and how do I get them to connect. >>And more importantly, now that I can maybe figure out a way to connect them, how do I actually see what they're doing and be able to control what they're actually now accessing? Because I no longer have that level of control as of them coming into the office. And so a lot of customers, you know, we're, we're beginning to develop kind of homegrown solutions, look at various different things to kind of quick hot patches, if you will, to address the remote workers coming in and things of that nature. And we'll be seeing kind of progression through all this as a, as, as opposed to just solving, getting a user, to connect into the, into an environment that it can provide, you know, continuity for. They started coming up with other challenges to the point of security. They started, you know, I have other customers calling me up and saying, you know, I I've now got a ransomware problem, right? >>So, you know, what do I do about that? And what are the things I need to kind of consider with respect to now I'm much more vulnerable because my, my, my branch has state has basically become much more diversified and solutions and things that they're looking for, regardless, obviously around security connectivity, there they've been challenged with addressing how do they unify their levels of visibility without over encumbering themselves and how they actually manage now this kind of much more kind of distributed kind of network if you will. Right? So things around, you know, looking at, you know, acronyms around from like a Z TNA or, you know, cloud security and all this fun stuff starts coming into play. But what it, what it points to is that the biggest challenge ideas, how does, how do they converge networking and security together and provide equitable and uniform policy architecture to identify their users, to connect and access the applications that are relevant to the business and be able to have that uniformity between whether it's the branch for them being remote. And that's part of what we've kind of seen as this progression to the last two years and kind of solutions that they're looking for to kind of help them address that. It's almost like >>It's a good thing in a way. It actually opens up the kimono and say, Hey, this is the real world we've got to prepare for this next generation a TIF. I want to get your take because, you know, remember the old days we were like, oh yeah, we've got to prepare for these scenarios where maybe 30% will be dialing on the V land or remotely, you know, it's not 30%. It was like 100%. So budgets aren't out of whack and yet they want more resiliency at the edge. Right. So, so one, I didn't budget for it. They didn't predict it and it's gotta be better, faster, cheaper, more skier. >>Yeah. Yeah. So, so, so John, the difference is, is that, you know, Dell, for instance, as already was already working towards this distributed model, right? The pandemic just accelerated that transformation. So, so when customers came to us and said, oh, we've got a problem with our workforce and our users being so geographically suddenly dispersed, you know, we had some insight that we could immediately lean on. We had already started working on solutions and building those platforms that can help them address those, those problems. Right. Because we'd already done studies before this, right. We had done studies and we'd come back on this whole work from home or remote office scenario. And, and the results were pretty unanimous in that customers were, all users were always complaining about, you know, application performance issues and, and, you know, connectivity issues and, and things like that. So we, we, we kinda knew about this. And so we were able to proactively start building solutions. And so, you know, so when a customer comes, there's like Rob was talking about, you know, their infrastructure, wasn't set up for everybody to suddenly move on day one and start accessing all the corporate resources where the majority of the organization is accessing corporate resources from away from campus. Right? So we, we, we have solutions, we've been building solutions and we have guidance to offer these customers as they try to modernize that network and address these problems. >>Well, that's a great segue to the next topic. Talk track is, you know, what is a network? What is network monetization? Right. So let's, let's define that if you don't mind, well, I got you guys here. You're both pros get that sound bite, but then let's get into the benefits of the outcomes from what that enables. So if you guys want to take a stab at defining what is network modernization mean? >>I think there's a lot of definitions, or it kind of depends on your point, your point of view of where you're, where you're responsible for, from a network or within the stack, you know, are from a take obviously is, you know, working, working from a vendor. And with solutions that we provide modernization is really around solutions that begin to look at more software defined architectures and definitions to begin a level of decoupling between, you know, points of control, hardware and software, and other kinds of points of visibility and automation to the point where, where things are let's, let's kind of put an air quotes in a sense of being more digitized. And in the sense, like even how we're looking at things from a consumerization perspective, but looking at things a much more, more cloud aware cloud specific cloud native in built automation, as well as inbuilt kind of analytics where things are much more in a, in a broader SDN, kind of a construct would be a form of a definition from a, from a, from a, from a monetization perspective. >>Now, do the other element of your, kind of a question in regards to, it's kind of the benefits that come as a result of this. So as customers have been in the last 24 months, looking at different solutions to address part of what we've been talking about, part of it is you want, when you're looking at, whether it's like you're using a word like sassy to kind of define, you know, how are enterprises looking for ZTE and they based solutions or cloud security to augment their, their overall needs. The benefits that they're finding are simplicity of management, because they're now looking for more uniform solutions that can address secure access for remote workers, in addition to their own kind of traditional access, as it relates to their offices to better visibility. Because as this uniformity of this kind of architecture, the now able to actually really see the level of context, right? >>I can see you, John, as far as where you're coming in and access and what applications on what devices. And now I have a means to actually apply a policy to that matters to me as the business, from an IP perspective, to protect me as the business, but also to ensure that you're actually authorized and accessing things that I have from an it regular reg regulations perspective. So benefits and the summary are kind of like Mo in bill automation, better, you know, things get done faster, things repair on their own in a different way, as a result of automation, greater visibility. Now they have much more greater insights into what we are doing as users of the overall it infrastructure and better overall control. That's been ultimately simplified as result of consolidation and unification. >>That's awesome. Insight. I T what's your take on the benefits of ma network modernization? >>So I'd like to sort of double down on, on, you know, something Rob said, right? So the visibility, right? So enhanced visibility in layman's terms, that just means more insight, more insight means the ability to implement best practices around application usage, application performance, more insights means control that it departments are, are meeting. They need that to manage and address security threats, right? To be able to identify an abnormal traffic pattern or unauthorized data movement, to be able to push updates and, and patches quickly. So, so it's really about, you know, that, that manageability, that that level of control gives them the ability to offer a resilient and secure underlying networking infrastructure. And then, you know, finally one of the key benefits is cost savings of, you know, everybody is trying to be more efficient. And so from, from our perspective, it's, it's really about building an open platform. >>You know, we've built a platform or an x86 based platform. We've we chose that because we wanted to tap into a mature ecosystem that, you know, customers can leverage as they, as they build their build towards their modernizing modernization goals. And so we're like tech leveraging technologies, like UCPs so universal customer premise equipments. And so that's really just an open hardware platform, but what you get by consolidating your network functions like routing and firewall, and when optimization you, and when you consolidate it all onto a single device, you get hardware savings, cost savings. You, you get operational savings as well, right? So you've it, common hardware infrastructure means a common deployment model means a streamlined operations means fewer truck rolls, right? So, so there's a tremendous amount of, of, of benefit from the cost standpoint as well, because from our perspective, it's really that what customers are looking for, they need enterprise grade solutions that can scale in a cost-effective manner. >>That's awesome. You guys mentioned sassy earlier. I'm like, first of all, software as a service is very sassy, big modern application movements. Always get my hair sassy. I think, you know, a kind of a term around SAS software as a service, but for you guys, it's talking about secure access service edge, which is a huge category growth right now where, you know, per security and networking, it's a huge discussion SD win fits into that somehow, because it used to be campus networking before now. It's everyone's world is the same. Now it's connected. So sassy is huge. How does that fit into SD when it's in the trend of the SAS at the same? What's the difference? Cause wan has been booming for the past decade as well in terms of trends. How are you guys seeing those converging in what's the difference? >>You know, I like to also agree with you, this thing has been booming the last couple of years, right. You know, kind of, kind of bread and butter part of what we've been doing, but, you know, to your question in regards to kind of its linkage relative to sassy, right. You know, as you articulated, right. It's the sassy secure access service edge from a definition of the acronym. So it's authority is first kind of good to kind of define a little bit, maybe for some of those that may not be overly familiar with it. And I like to kind of dumb it down a little bit into the point of sassy is really an architecture that is around, you know, the convergence of networking and security being put together in a uniform platform or service that is delivered from both the cloud, as well as addressing, you know, their, their kind of traditional land requirements. >>Now digging in sassy is broken to two little buckets, right? It's broken into a network layer and the six security layer and by its definition, right, by, by a particular analyst, the network component, a big portion of that is SD wan. And so SD wan providing that value associated to what does, you know, dynamic lanes, steering automation, application attachments, so on and so forth is a core element of the foundation of the network layer associates, associate sassy. And then the other element of zesty is around the security bit. And so they're very much intrinsically linked, whether, you know, for example, like versus just the kind of mentioned this here, the, the, the sassy cloud that we built for our customers to leverage for private access, public access, you know, secure internet CASBY, DLP type of services is built upon SQM. In addition to our customers that are using Guesty Lampard or traditional land are using SD wan to connect to that cloud. >>So it's very, very much linked and they kind of go hand in hand, depending on your approach to the broader architecture. And, you know, another point I'll bring into that. What, what it also highlights is that whether it's around sassy or not, when we, when in pertinent to everything we'd been other kind of been talking about, the other thing that's coming with sun intrinsically and natively is really the concept of security it's around, whether it's security at the branch, or whether it's around some form of, you know, identity management or a point of improving posture for the, for the enterprise to, you know, obviously the spec traffic at the branch where remotely, but what we're seeing at a trend wise, which, you know, part by customer adoption from our own platform, if you will, is basically security and SD Wang coming together, whether for your traditional land transformation, or as a result of sassy services for a hybrid needs of connectivity, right? Remote workers, hybrid workforce, going into the cloud for, for their connectivity needs and optimizations. In addition to obviously the, the enterprises branch transformations, >>I like that native aspect of it. We used to joke and call SD way in St. Cloud because it's, we're all using cloud technologies. Talk about the security impact real quick. If you don't mind, I want to just double click them what you mentioned there, because I think the cloud effication plus the security piece seems to be a key part of this dynamic. Is that true? Or did they get that right? What's what's this all mean with cloud vacation? Yeah, >>And I, I would, I, I, I agree with, I guess kind of where you're leading into that is, you know, review all of us you're right now. Exactly. In talking with you right now, right. John is, as you stated at the beginning, we're all remote. And so from a business perspective, right, we are accessing, or from an engagement we're accessing a cloud service. Now what's critical for us, as you know, obviously enterprise employees is that our means of accessing this cloud service needs to have some level of hardening. We need to protect, right. Not only our own asset that we're using, right. Our laptops or other machinery that you use to connect to the network, but in addition to protect our company, right? So our company also needs to protect them. So how can we do that? Right? How can we do that in a very fast and distributed way? >>Sure. We can put security endpoints at every location with every user and every home. And that's one means of, of a particular solution. So your point about cloud is now take all of that and bring it to the cloud where you'd have a much more distributed means, right? And much more dynamically, scalable approach to actually doing that level of inspection, posture and, and enforcement. And so that's kind of where the rubber meets the road, right, is for us to access those cloud applications. The cloud that we're using as a conduit for security, as well as network also is now even connected and optimized paths to applications like what we're using right now, right. To, to, to do this conversation. So that's kind of where it meets together. And the security element is because we're so diverse, we just need, we, we, we need to ensure, right. We're all much, we're much more vulnerable. Right? My home network is, you know, maybe arguably maybe not as secure as when I go into an office. Right? >>So most people, because you have worked for virtual networks, >>I can make that argument. Yes. Right. But you know, the average, most of us, remote workers, you know, our homes aren't as hard. And so we point a point of risk, right? And so, as we, as we go to cloud apps, we're more connected to the internet. Right. You know, the, the, the point of being able to do this enforcement from a sassy concept helps provide that improved posture for enterprises to secure their traffic and get visibility into that. >>All my network engineer, friends are secure, as you read about. And I always joked to the malware, you missed, missed the wrong network engineer. If I go after them, their house, spear fishing. And you're trying to get into your network. I'd say, if I want to bring this back, because what we're bringing up here is cloud is actually enabling more on premises because you're working at home. That's a premise, right? So you're also edge is a premise edge and cloud. And a cloud kind of eliminates all this notion of what is cloud and edge, but at the end of the day is where you are. Right. So having the performance and the security and the partnership that same with Dell, I know you guys have been on this for a while because I've been covering it, but the notion of edge completely changes now, because what does that even mean? Home's edge is the camp of data centers and edge the, the cars and edge, the telco monopoles and edge. This is a big deal. This is the unit about the unification. This is all about making it all work. What's your, what's your take on this from the Dell perspective. >>Yeah. And I think, I mean, it that's, I mean, you, you kind of summarize it, right. I mean, what does edge mean to you? Right. It's and then, so every time I have a conversation with, with somebody, I always start with, let's define what your edge is. And so, you know, from, from our perspective, from the Dell perspective is, you know, we believe that we want to provide enterprise grade infrastructure. We want to give our customers the right tools. And we're seeing that with this trend of a hybrid workforce, a geographically dispersed user base, we're seeing a tremendous need for, you know, from it departments for tools, for solutions that can give them the control that they can sort of push out into their networks to ensure a safe and secure external access to corporate resources. Right. And so that's what we're committed to is making sure that, that, that management layer by either developing the solutions, in-house bringing the right partners to the table and just ensuring that our customers have the right tools because this sort of trend, or this, this, this new normal is not going away. And so we have to adapt. >>So thanks for coming on, Rob, we'll give you the final word. What's changed the most, in your opinion, with customers, environments, around how they're handling their networks as we come out of the pandemic, which has proven kind of which projects are working, which ones aren't where to double down on what was screwed up. I mean, come on. This is, we're kind of seeing it all play out. What's your, what's your take on as we come through the pandemic and people come out of this, what's the big learning. Okay. >>Well that you need partners. Right. Okay. So it's not even from a vendor perspective. What I mean by partners is what we're finding and what I think a lot of other customers I've engaged with and others is this ain't easy for even as much as we can within the technology vendor market, right. It's to make things easier to do. There's a lot of technology and the enterprise, it is recognized. They need a lot of these building blocks, right. To, to accomplish a lot of different things, whether it's around automation, to, in other tools as, as auto was leading into. And so we're finding that, you know, a lot of our, our base or our interactions are really trying to identify an appropriate partner that can help not only talk to the technology, but help them actually understand all the various different, you know, multi-colored legal blocks, they've got to put together, but also help help them actually put that into a realization. >>Right. And, you know, and then be able to then give the keys to them so they can eventually drive the car. Right. And so the learning that we're seeing here is this is a lot of tech, there's a lot of new tech, new approaches to existing technology of things that they've actually done. And they're, they're, they're looking for help. Right. And so they're looking for kind of, let's call it like trusted advisor kind of status of people that can help explain the technology to them and then help them understand how do they put it together. So they can then ultimately accomplish our overall kind of, you know, other kinds of objectives from an it perspective. And the other learning that I'll just say, and then I'll, then I'll stop. Here is SD wan isn't dead, right? Yes. The man is actually still driving. And it's actually an impetus for a lot of other things that enterprise is actually doing, whether it's around, you know, sassy, oriented services, remote access, private access, and other things of that nature. >>I totally agree. I think the networking, stuff's still going to be so much innovation going on with the edge exploding as well. That the really great, amazing stuff happening. Thanks for coming on this cube conversation, great conversation, taking it to the edge network challenges in the distributed hybrid workforce era is about moving things around the internet, making them secure. I'm John for your host. Thanks for watching.

>>Here you are new. Welcome back to the cubes. Continuing coverage of AWS reinvent 2021 live from Las Vegas. Lisa Martin, with John farrier, John, we have two live sets. There's a dueling set right across from us two remote studios over 100 guests on the cube at AWS reinvent 2021. Been great. We've had great conversations. We're talking about the next generation of cloud innovation and we're pleased to welcome one of our alumni back to the program. Lisa Bernays here, the CEO and co-founder of D L Z P group. Lisa. Welcome. >>Hi, thank you. I appreciate the opportunity to be here with you and John. It's a great opportunity >>And John's lucky he gets to lease us for the price of London. One second. Talk to me about da DLDP. This is a woman and minority owned company. Congratulations. That's awesome. But talk to us about your organization and then we'll kind of dig into your partnership with AWS. >>Sure. So DLC P group, we found it in 2012. Um, and for us, we were at the time we were just looking for a way to offer a value added service to our customers. We wanted to always make sure that we were giving them the best quality, but what I also wanted to do is I wanted to create an environment for my employees, where they felt valued, and we kind of built these core values back then about respect, flat hierarchy, um, team, team learning, mentorship, and we incorporated, so everybody can do this remotely from around the world. So we've always made sure that our employees and customers are getting the best value. >>Well, what kind of customers, what target market, what kind of customers do you guys work with? >>Well, we've actually made sure that we're diverse. We make sure that we have 50% in public sector and 50% in private sector, but it's been very, very interesting journey for us because once we started one sec, like we started with cities and then a number of cities started contacting us to do more business. So it's always been this hurdle to make sure we're diverse enough to make sure we offer the best solutions. >>And you jumped in with AWS back in 2012 when most folks were still to your point. I saw your interview earlier this summer, thinking about Amazon as a bookstore, why a debit? What did you see as the opportunity back in 2012 with them? >>Well, when we first heard about AWS, my first thought is, well, it's amazon.com. What is AWS? And then once we started talking to them, we saw the capabilities and the potential there. We saw what it could do. So we partnered with them to actually have the first working PeopleSoft customer on AWS. So that's a large ERP application and that helped build the foundation to prove what could actually run on the cloud. And since then, we've been able to prove so much more about the technology and what AWS is accomplishing. >>Was it a hard sell back in the day? >>It was a little bit hard, but it was interesting because we were speaking with one of our customers they're on premise and they're like, well, you know, we're going to have to re do a whole data center. We're talking about millions of dollars. We don't really have the budget to redo this. And that's when we're like, well, we have this great partnership with Amazon. We think this would be the perfect opportunity to let you try the cloud and see how successful it was. >>At least I want to point out you got your, one of the Pathfinders that Adams Leschi pointed out because back in 2012, getting PeopleSoft onto the cloud, which is really big effort, but that's what everyone's doing now. I just saw the news here. SAP is running their application on graviton too, right? So you start to see and public sector during the pandemic, we saw a ton of connect. So you were really on this whole ERP. ERP is our big applications. It's not small, but now it's, everyone's kind of going that way. What's the current, uh, you feel how you feel about that one? And what's the current update relative to the kind of projects you got going on? >>Well, we've, we've evolved quite a bit. I mean, PeopleSoft is always going to be in our DNA. A lot of my employees are ex or Oracle employees. They have developed a lot of the foundations for PeopleSoft, but since then, like we've worked with serverless technology when that was released a number of years ago, we, we asked our team, okay, AWS just talked about Lambda, serverless technology, go figure out what is the best solution. We ended up running ours, our website serverless. We were one of the first. And from that, we brought our website costs down from hundreds of dollars to pennies a month. So it's a huge savings. And then we started, um, about two years ago, we spoke with our utility company. Um, there were saying how with machine learning, they were only going to be able to get a 75% accuracy for their wind turbines. And we said, well, let us take a shot at it. We have some great solutions on AWS that we think might work. We were able to redo their algorithm using AWS cloud native tools, open source data to get a 97 to 99% accuracy on a daily basis. And that saves them millions of dollars each day. >>Don's right. And as Adam was saying with some of the folks, customers, he was highlighting on main stage the other day, you are a Pathfinder. How did you get the confidence? Especially as a female minority owned business. I'd love to just get maybe for some of those younger viewers out there. How did you get the confidence to, you know what? I think we can do this. >>I think for me, I, I, I don't like to take no for an answer. There's always a solution. So we're always looking at technology, seeing how we can use it to get a better answer. >>What do you think about reinvent this year? A lot of goodies here every year, there's always new creative juices flowing because it's a learning conference, but it's also feels like a futuristic kind of conference. What's your take this year? >>I don't know if you happen to attend midnight madness when they were talking about robotics and the future with that. I mean, we've been talking about that for a number of years of what could be created with robotics. Like even my son back in middle school was talking about creating a robot Butler. He just, everybody knows what the future is. And it's so great that we finally have the foundation in technology to be able to create these >>Well, if you're someone that doesn't like to say, no, does your son actually have a robot Butler these >>Days? He's still working on it. >>That's a good answer to say, Hey, sorry, your mom's not going to be there to get the robot. The latency thing. This is the robot. First of all, we'd love the robotics, I think is huge. We just had George on who's the fraught PM for ECE to edge and late, the wavelength stuff looks really promising for the robotics stuff. Super exciting. >>Yes. We can't wait to start playing with it more. I mean, it's something that our team has been dabbling. We spent probably about 30% of our time on R and D. So we're looking at the future and what we can invent next because >>You guys can affect such dramatic changes for customers. You talked about that wind turbine customer going from 75% accuracy to 97, 90 8%. Where are your customer conversations? Cause that's, is, are they at the C level with showing organizations that dramatic reduction in costs and workforce productivity increased that they can get? >>We talk with everyone it's it could be the solution architect. It could be an intern. It could, and we're just sharing our ideas with them. And we also talk with the C level. Um, it's just, it's everybody is interested in and they have different, different ideas that they want to share. So with the solution architect, we can share with them the code and how we're going to architect it. While the C level, we just pointed out black and white, this is your cost. Now this is what your cost is going to be. And everybody is happy. They, they jump on board with it. >>Lisa, you mentioned 30% R and D by the way, it's awesome. By the way, that's well above most averages, what are you working on? Because I totally think companies should have a big R and D play around budget, get a sandbox, going get some tinkering. Cause you never know where the real discoveries we had. David Brown who runs NC to nitro, came out of a card on the network. So you'd never know where the next innovation comes from. What's the, what are you guys doing for R and D? What's the fun projects are what endeavors. >>So there's two of them. One is actually a product, which is a little bit out of our comfort zone, but we're, we're, we're looking to develop something that will be able to help, um, NASA. So that's the goal where, you know, we've been working on it since they released their ma their mission to Mars projection. So it's something that we're very passionate about, but then we're also building a software. Uh, we've been working on it for about three years now and we actually have two customers prototyping it. So we're hoping to be able to launch it to the public within the next year. >>You mentioned NASA and I just about jumped out of my chair. That was my first job out of grad school was really the space program. Can you tell us a little bit more about what you're helping them do? I love how forward-thinking that they are, obviously they always have been, but tell me a little bit more about that. >>So I can't share too much because it's one of those things is a common sense thing. Once you think about a little bit more, it's kind of like why didn't anybody never think about this? So we're using new technology and old technology together to combine the solution. >>Ooh, I can't wait to learn more. Talk to us about these. Think big for small business TB SB program at AWS. How long have you guys been a part of that and what is it enabling? What is it going to enable you to do in 2022? So >>The think big for small business program was the brainchild is Sandy Carter. And I am always, always going to be grateful to her. Um, I met with her in 2019. I shared her journey, our journey with her about how we started out being a premier partner and then over time, because there's so many other partners, we were downgraded. And because just because we're a small business, and even if I had every employee, even my admin staff certified, we would never have enough employees to be to the next level, even though we had the customers, the references. So she listened to us and other small businesses and created the program. And it's been a great opportunity for us because we're, we're gaining access to capital, you know, funding for opportunities. We're getting resources for training. So it, for us, it's been a huge advantage. >>It sounds like a part of that AWS flywheel that we always talk about. John Sandy Carter being one of our famous Cuba alumni. She was just on yesterday with you. Okay. >>And there's so many opportunities for all businesses because you can, you can tackle these problems. You don't have to be a large partner. You can have specialty in AI works really well in these specialized environments. And even technically single-threaded multithreaded applications, which is a technical CS term is actually better to have a single threaded. If you have too many cores, it's actually bad technically. So the world's changing like big time on how technology. So I'm a huge fan of the program. And I think like it's just one of those things where people can get it from cloud and be successful. >>Yes. And that's the goal. I mean, there is so much opportunity in the cloud and we bring interns on all the time, just so they can learn. And what, what resonated with me the most was we brought a high school senior in, he goes, I was with you guys for three months. I learned more in three months, I did four years of high school. And he's like, you set me up for the future. >>Oh my gosh. If there's not validation for you doing in that statement alone. My goodness. Well, you know, some of the things that, that are so many exciting announcements that have come out of this reinvent, so great to be back in person one. Um, but also, you know, being able to help AWS customers become data companies. Because as we were been talking about the last couple of days, every company has to be a data company. You gotta figure it out. If you're, if you haven't by now, there's a competitor right back here, who's ready to take your spot. Talk to us about what excites you about enabling companies to become data companies as we head into 2020. >>Well, for us, everybody has so much data nowadays. You know, I mean even think about cell phones, how much data is stored in that. So each device has so much information, but what do you do with it? So it's great because a lot of these companies are trying to figure out what, how can we use this data to prove that improve the experience for our customers? So that's where we've been coming in and showing them, okay, well, you can take that data. You look at Lisa and John cell phone. You see that they, they love to look up where they're going to go on their next vacation. You can start creating algorithms to make sure that they get the best experience one for the next vacation to make sure it's not a won't Rob the bank. >>Awesome. And going on vacation tomorrow. So I'll be, I'll be expecting some help from you on that. It's been great to have you on the program. Yeah. Congratulations on the success, the partnership, and where can folks go if if young or old years are watching and are interested in working with you, it's the website where they, where can they go to learn more >>Information? So they can go to D L Z P group.com >>DLZ P group.com. Awesome. Lisa, thanks so much for coming back on the program. Great >>To see you. Thank you so much. All >>Right. For John furrier, I'm Lisa Martin and you're watching the cube, the global leader in live tech coverage.

(bright music) >> Okay, welcome back everyone. to theCUBE's coverage of AWS re:Invent 2021, we're in person for a real event. I'm John Furrier, your host. We have two sets here on the floor, also a hybrid event online as well for Amazon, also on theCUBE Zone, go to cubereinvent.com and check out all theCUBE footage there. Maureen Lonergan, VP of Training and Certification AWS CUBE alumni, Maureen, great to see you, thanks for coming on. >> Nice to see you. >> So I remember, years ago, at re:Invent when you came on first time on theCUBE, this was when cloud was just getting going, I don't want to say just getting going, it was going, but it was just like training was going, now you're swimming in needs. You got the big milestone for, what's that? 27 million people, what's that number? >> 29 million training free, yeah. >> 29 million is the target for training, we hear the certifications are up, the pandemic has got everyone geared up for training. Give us the update, what's happening? >> Yeah, so we're doing a lot of interesting things. Obviously, the pandemic changed the world for everyone, but it's been a really good opportunity for us to pivot the business and move things to virtual and digital. And, in 2020, we did make that commitment to train 29 million people for free by 2025. And, you know, we've trained 6 million so far, so we're making great progress on that goal. We've largely done that through a couple of different programs. So we just a month ago launched our Skill Builder platform that provides 500 free training courses in 16 languages, across 200 countries. We also launched the AWS Skill Center in Seattle, which is learner acquisition and bringing in people from the community to learn about cloud. And, we also launched a course on Amazon Books. So, we were really excited about-- >> So you guys, again, this is free training. >> All free training. >> Free training. >> Everything I just mentioned is free. >> What's the most important things, skills are people learning right now? >> I think it's still this, you know, it's the same thing, it's solution architecture, security for sure, DevOps, developer, but we're also seeing a huge interest in business, the business roles, really understanding what cloud is and how it can, you know, help them with their business. >> How about organizations? 'Cause they have skill issues too, I know you guys are going all in on training, which is great, and by the way, congratulations on the mission. I know you're getting close to the numbers. I think there was an announcement, we're getting an update as you guys, have you hit the numbers yet? 29 million? >> The 29 million, yeah. So 6 million we've done so far, yeah. >> So you're on your way. What about organizations? How do they get involved? Because they're trying the same thing. Are you partnering with people? >> Yeah, so we partner with, well, for customers, they're looking for the same thing that we are. We also have a program for underserved and unemployed communities where we go in and do a kind of non-tech to tech training. And we're offering that program in 90 locations this year and really trying to address the early pipeline. >> What are some of the most important things that you're working on for AWS, for training and certification right now? >> The biggest thing that we're doing is just trying to make everything as free and accessible as we can and moving as much as we can to digital, making it where we've really focused this year on experiential learning, so labs and getting engaged with the customer and keeping them because obviously, we release services every day, you know? And it's important that we just work with organizations to have a learning, curious culture. >> Is there any way people can get involved, or you guys have any open programs? What can we do to help on theCUBE? Do you guys have new, cool digital ways to get the word out? What's going on? >> Yes, so, I mean, it depends on what you mean, we always are partnering with collaborating organizations, especially for programs like re/Start, so organizations within communities that are trying to get their community skilled up. So we work with a bunch of different partnerships. And I think, for me, it's really just about, we really think we're very, very focused on building diverse builders. And so, we want to make sure that we're getting the message out that cloud's accessible to anybody. And, by providing free training, we hope that that will attract a new set of learners and start to close the gap on their training pipeline. >> So, have you guys got the Gen Z nailed down yet? 'Cause they're hungry for content, they're on the Discord servers, they're on Twitch. >> Yeah, we actually were training to Twitch this year, because you have to meet the learner where they are, right? And I think, you know, traditional instructor-led training just doesn't work for some people. And so, we have content out on Twitch, we're working on some really cool interactive gaming stuff. And so, we really have pivoted. >> So there's a Discord server called "Ace of Diamonds" that's turning out to be quite the business vibe for the young kids. A lot of young kids from 13 to 17 years old in that kind of learning mode and they want to talk about cloud. Like to them, they're geeking out on NVIDIA GPUs, they want to hear about the graviton, they're nerds. >> Yeah, we actually have a very cool program called "Get IT", and it's very focused on girls in tech and we go into schools and run competitions and do hackathons and they present, and it's a really great way to get, you know, girls interested in tech in a big way. >> Cal Poly hosted a robotics competition, that was pretty interesting, the women's division was phenomenal. There's divisions now, I mean, robotics is like a varsity sport now. >> Yeah, exactly, exactly. >> I mean, this just shows you where the interest level is. Okay, so obviously, there's a young demographic and you've got the re-skilling on the higher end of the demographic of age wise that maybe have come from IT. So you've got the IT folks and/or people that had some business training or whatever, and then you have the young, what's the programs that are working the best that you see to getting those folks, the older folks, in retraining? >> For the younger ones, or? >> John: Older ones, not younger ones, older ones. >> I think what we're trying to do is work with organizations to make training accessible and comfortable. We always say it, you know, we want companies to build an environment where they can experiment and learn. So we're working with large organizations to try and transform them and make them cloud fluent and move people from traditional skills onto cloud skills. And, we're having great success with customers in doing that. But I think providing a really comfortable environment and a place and space for them to learn and building communities within that organization is important. >> What did you learn during the pandemic in your evolution? 'Cause you guys were doing like mid-flight of training, I know you've been rolling, you've been working really hard over the years, I know that for a fact. Pandemic hits, it's now virtual, digital is now a priority. What are some of the new things that have been spawned onto you from digital that are working? >> Yeah, I mean, we learned how to, you know, we're building out labs and we learned to cut content into smaller pieces so people could consume them. I think the biggest thing that we learned is that we just need to, that people were hungry to learn. Everyone was at home and we actually saw a tremendous increase in people taking training, especially digital training. And then, we also pivoted all of our certifications to virtual very rapidly so that people could then validate their skills. I think in light of the pandemic, you know, the great resignation is real, right? And people are assessing where they are. And so, we'd like to acquire people that are interested in that. >> And those jobs that are available with certification are very high paying jobs. >> Yes they are, yeah. >> So you walk through a certification, you're looking at some pretty good salary levels and you could be living anywhere. >> I met a guy last night at an event and he was in finance and he moved from a job making 30,000 to six figures and he did all through self-learning and he came to an event, was super excited about that. >> That's the top story right there, we've got to leave it at that. I know you got to go, I know you've got a hard deadline. Thank you for spending the time to come on theCUBE and sharing this important information around the certification, your goal for free training, it's free. >> Maureen: Free. >> If you want to get a raise, get cloud certification, pro tip. >> Please. >> That's a pro tip right there. Thanks for coming on, Maureen, great to see you. >> Appreciate it. Maureen Lonergan, great work she's doing in Amazon getting free content, you don't have to pay for it, it's free. Just like theCUBE content here, bringing you free insights. I'm John Furrier, worldwide leader in tech coverage at theCUBE, here in person in Las Vegas. Thanks for watching. (bright music)