>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright music) >> Hey everyone! Welcome back. Good evening from Barcelona, Spain. It's theCUBE, the leader in live tech coverage. As you well know, Lisa Martin and Dave Nicholson. Day two of our coverage of MWC 23. Dave, we've been talking about sexy stuff all day. It's about to get, we're bringing sexy back. >> It's about to get hot. >> It's about to get hot. We've had two guests with us, two senior consultants from the product planning, networking and emerging server solutions group at Dell, Heather Raheel and James Bryan. Welcome guys. >> Thanks for having us. >> Thanks for having us. >> Really appreciate it. >> Lisa: Dude, you're bringing sexy back. >> I know. We are. We are. We wanted to bring it, yes. >> This is like XR8000 >> We've been talking about this all day. It's here... >> Yes. Yes. Talk to us about why this is so innovative. >> So, actually we wanted to bring this, getting a lot of attention here on site. Matter of fact, we even have a lot of our competition taking pictures of it. And why is it so innovative? So one of the things that we've done here is we've taken a lot of insights and feedback from our customers that are looking at 5G deployments and looking at how do they, basically, bring commercial off the shelf to a very proprietary industry. So what we've done is we've built a very flexible and scalable form factor in the XR8000. And so this is actually a product that we've purposely built for the telecommunications space. Specifically can be deployed for serving a virtual DU or DUC at a cell site for distributed ram. Or it can be put in a local data center, but outside a main data center to support centralized ram. We'll get into it, which is where the really excitement gets is it's sled-based in its design. And so because of that, it enables us to provide both functionality for telecommunications. Could be network, could be enterprise edge as well as being designed to be configured to whatever that workload is, and be cost-optimized for whatever that work. >> Ah, you're killing us! Let's see. Show, show it to us. >> Actually this is where I have to hand it off to my colleague Heather. But what I really want to show you here is the flexibility that we have and the scalability. So, right here what I'm going to show you first is a one U sled. So I'll set that out here, and I'll let Heather tell us all about it. >> Yeah. So XR8000. Let's talk about flexibility first. So the chassis is a two U chassis with a hot swap shared power supply on the right. Within it there are two form factors for the sleds. What James brought out here, this is the one U form factor. Each sled features one node or one CPU first sled. So we're calling the one U the highest, highest density sled right? Cause you can have up to four one node one U sleds in the chassis. The other form factor is a two U sled, on the right here. And that's just really building on top of the one U sled that adds two PCIe sleds on top. So this is really our general purpose sled. You could have up to two of these sleds within the chassis. So what's really cool about the flexibility is you can plug and play with these. So you could have two one Us, two two Us, or mix and match of each of those. >> Talk about the catalyst to build this for telco and some of the emerging trends that, that you guys have seen and said this needs to be purpose-built for the telco. There's so much challenge and complexity there, they need this. >> Want me to take this? So actually that, that's a great question by the way. It turns out that the market's growing. It's nascent right now. Different telecommunication providers have different needs. Their workloads are different. So they're looking for a form factor like this that, when we say flexible, they need to be able to configure it for theirs. They don't all configure the same way. And so they're looking for something that they can configure to their needs, but they also don't want to pay for things that they don't need. And so that's what led to the creation of, of this device the way we've created it. >> How is it specific for edge use cases, though? We think of the edge: it's emerging, it's burgeoning. What makes this so (pause) specific to edge use cases? >> Yeah, let's talk about some of the the ruggedized features of the product. So first of all, it is short depth. So only 430 millimeters. And this is designed for extreme temperatures, really for any environment. So the normal temperatures of operating are negative five to 55, but we've also developed an enhanced heat sink to get us even beyond that. >> Dave: That's Celsius? >> Celsius. Thank you. >> Lisa: Right. So this will get us all the way down to negative 20 boot in operating all the way up to 65 C. So this is one of the most extreme temperature edge offerings we've seen on the market so far. >> And so this is all outside the data center, so not your typical data center server. So not only are we getting those capabilities, but half the size when you look at a typical data center server. >> So these can go into a place where there's a rack, maybe, but definitely not, not doesn't have to be raised for... >> Could be a cell side cabinet. >> Yeah. Okay. >> Heather: Yeah. And we also have AC and DC power options that can be changed over time as well. >> So what can you pack into that one one U sled in terms of CPU cores and memory, just as an example? >> Yeah, great. So, each of the sleds will support the fourth generation of Intel Sapphire Rapids up to 32 corp. They'll also be supporting their new vRAN boost SKUs. And the benefit of those is it has an integrated FEC accelerator within the CPU. Traditionally, to get FEC acceleration, you would need a PCIe card that would take up one of the slots here. Now with it integrated, you're freeing up a PCIe slot, and there's also a power savings involved with that as well. >> So talk about the involvement of, of the telco customer here and then design, I know Dell is very tight with its customers. I imagine there was a lot of communications and collaboration with customers to, to deliver this. >> Interesting question. So it turns out that early on, we had had some initial insight, but it was actually through deep engagement with our customers that we actually redesigned the form factor to what you see here today. So we actually spent significant amount of time with various telecommunication customers from around the world, and they had a very strong influence in this form factor. Even to the point, like Lisa mentioned, we ended up redesigning it. >> Do, do you have a sense for how many of these, or in what kinds of configurations would you deploy in like the typical BBU? So if we're thinking about radio access network literally tran- tower transmitter receiver... somewhere down there (pause) in a cabinet, you have one of these, you have multiple units. I know, I know the answer is "it depends". >> You are right. >> But if, but if someone tells you, well you know, we have 20, 20 cellular sites, and we need (pause) we're we're moving to an open model, and we need the horsepower to do what we want to do. I'm trying to, I'm trying to gauge like what, one of these, what does that, what does that mean? Or is it more like four of these? >> So that, so we'll go >> It depends? >> Yeah it depends, you're absolutely right. However, we can go right there. So if you look in the two U >> Yeah. >> we have three PCIe slots, you know, as Heather mentioned. And so let's say you have a typical cell site, right? We could be able to support a cell site that could have it could have three radios in the configuration here, it could have a, multiply by three, right? It could have up to 18 radios, and we could actually support that. We could support multiple form factors or multiple deployments at a particular cell site. It really then to your point, it does depend, and that's one of the reasons that we've designed it the way we have. For example, if a customer says their initial deployment, they only need one compute node because maybe they're only going to have, you know, two or three carriers. So then, there, you've got maybe six or eight or nine radios. Well then, you put in a single node, but then they may want to scale over time. Well then, you actually have a chassis. They just come in, and they put in a new chassis. The other beauty of that is, is that maybe they wait, but then they want to do new technology. They don't even have to buy a whole new server. They can update to >> Heather: Yeah. the newest technology, same chassis put that in, connect to the radios, and keep going. >> But in this chassis, is it fair to say that most people will be shocked by how much traffic can go through something like this? In the sense that, if a tower is servicing 'n' number of conversations and data streams, going through something like this? I mean somehow blow, it blows my mind to think of thousands of people accessing something and having them all wrapped through something like this. >> It, it'll depend on what they're doing with that data. So you've probably talked a lot about a type of radios, right? Are we going to be massive MIMO or what type of radio? Is it going to be a mix of 4G or 5G? So it'll really depend on that type of radio, and then where this is located. Is it in a dense urban environment, or is it in a rural type of environment at that cell site shelter, but out in a suburban area. So will depend, but then, that's the beauty of this is then, (pause) I get the right CPU, I get the right number of adding cards to connect to the right radios. I purchase whatever, what I need. I may scale to that. I may be (pause) in a growing part of the city, like where we're from or where I'm from or in San Diego where Heather's from where she's in a new suburban, and they put out a new tower and the community grows rapidly. Well then, we may, they may put out one and then you may add another one and I can connect to more radios, more carriers. So it really just comes down to the type and what you're trying to put through that. It could edit a stadium where I may have a lot of people. I may have like, video streaming, and other things. Not only could I be a network connectivity, but I could do other functions like me, multi-axis axon point that you've heard about, talked about here. So I could have a GPU processing information on one side. I could do network on the other side. >> I do, I do. >> Go for it >> Yeah, no, no, I'm sorry. I'm sorry. I don't want to, don't want to hog all of the time. What about expansion beyond the chassis? Is there a scenario where you might load this chassis up with four of those nodes, but then because you need some type of external connectivity, you go to another chassis that has maybe some of these sleds? Or are these self-contained and independent of one another? >> They are all independent. >> Okay. >> So, and then we've done that for a reason. So one of the things that was clear from the customers, again and again and again, was cost, right? Total cost of ownership. So not only, how much does this cost when I buy it from you to what is it going to take to power and run it. And so basically we've designed that with that in mind. So we've separated the compute and isolated the compute from the chassis, from the power. So (pause) I can only deal with this. And the other thing is is it's, it's a sophisticated piece of equipment that people that would go out and service it are not used to. So they can just come out, pull it out without even bringing the system down. If they've got multiple nodes, pull it. They don't have to pull out a whole chassis or whole server. Put one in, connect it back up while the system is still running. If a power supply goes out, they can come and pull it out. We've got one, it's designed with a power infrastructure that if I lose one power supply, I'm not losing the whole system. So it's really that serviceability, total cost of ownership at the edge, which led us to do this as a configurable chassis. >> I was just going to ask you about TCO reduction but another thing that I'm curious about is: there seems to be like a sustainability angle here. Is that something that you guys talk with customers about in terms of reducing footprint and being able to pack more in with less reducing TCO, reducing storage, power consumption, that sort of thing? >> Go ahead. >> You want me to take that one as well? So yes, so it comes at me, varies by the customer, but it does come up and matter of fact one- in that vein, similar to this from a chassis perspective is, I don't, especially now with the technology changing so fast and and customers still trying to figure out well is this how we're really going to deploy it? You basically can configure, and so maybe that doesn't work. They reconfigure it, or, as I mentioned earlier, I purchased a single sled today, and I purchased a chassis. Well then the next generation comes. I don't have to purchase a new chassis. I don't have to purchase a new power supply. So we're trying to address those sustainability issues as we go, you know, again, back to the whole TCO. So they, they're kind of related to some extent. >> Right. Right, right. Definitely. We hear a lot from customers in every industry about ESG, and it's, and it's an important initiative. So Dell being able to, to help facilitate that for customers, I'm sure is part of what gives you that competitive advantage, but you talked about, James, that and, and we talked about it in an earlier segment that competitors are coming by, sniffing around your booth. What's going on? Talk about, from both of your lenses, the (pause) competitive advantage that you think this gives Dell in telco. Heather, we'll start with you. >> Heather: Yeah, I think the first one which we've really been hitting home with is the flexibility for scalability, right? This is really designed for any workload, from AI and inferencing on like a factory floor all the way to the cell site. I don't know another server that could say that. All in one box, right? And the second thing is, really, all of the TCO savings that will happen, you know, immediately at the point of sale and also throughout the life cycle of this product that is designed to have an extremely long lifetime compared to a traditional server. >> Yeah, I'll get a little geeky with you on that one. Heather mentioned that we'll be able to take this, eventually, to 65 C operating conditions. So we've even designed some of the thermal solutions enabling us to go there. We'll also help us become more power efficient. So, again, back to the flexibility even on how we cool it so it enables us to do that. >> So do, do you expect, you just mentioned maybe if I, if I heard you correctly, the idea that this might have a longer (pause) user-usable life than the average kind of refresh cycle we see in general IT. What? I mean, how often are they replacing equipment now in, kind of, legacy network environments? >> I believe the traditional life cycle of a of a server is, what? Three? Three to five years? Three to five years traditionally. And with the sled based design, like James said, we'll be designing new sleds, you know, every year two years that can just be plugged in, and swapped out. So the chassis is really designed to live much longer than, than just three to five years. >> James: We're having customers ask anywhere from seven to when it dies. So (pause) substantial increase in the life cycle as we move out because as you can, as you probably know, well, right? The further I get out on the edge, it, the more costly it is. >> Lisa: Yep. >> And, I don't want to change it if I don't have to. And so something has to justify me changing it. And so we're trying to build to support that both that longevity, but then with that longevity, things change. I mean, seven years is a long time in technology. >> Lisa: Yes it is. >> So we need to be there for those customers that are ready for that change, or something changed, and they want to still be able to, to adopt that without having to change a lot of their infrastructure. >> So customers are going to want to get their hands on this, obviously. We know, we, we can tell by your excitement. Is this GA now? Where is it GA, and where can folks go to learn more? >> Yeah, so we are here at Mobile World Congress in our booth. We've got a few featured here, and other booths throughout the venue. But if you're not here at Mobile World Congress, this will be launched live on the market at the end of May for Dell. >> Awesome. And what geographies? >> Worldwide. >> Worldwide. Get your hands on the XR8000. Worldwide in just a couple months. Guys, thank you >> James: Thank you very much. >> for the show and tell, talking to us about really why you're designing this for the telco edge, the importance there, what it's going to enable operators to achieve. We appreciate your time and your insights and your show and tell. >> Thanks! >> Thank you. >> For our guests and for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live, Spain in Mobile MWC 23. Be back with our sho- day two wrap with Dave Valente and some guests in just a minute. (bright music)

(upbeat music) >> Hello, this is Dave Vellante, and we're here to talk about the massive $61 billion planned acquisition of VMware by Broadcom. And I'm here with Phil Brotherton of NetApp to discuss the implications for customers, for the industry, and NetApp's particular point of view. Phil, welcome. Good to see you again. >> It's great to see you, Dave. >> So this topic has garnered a lot of conversation. What's your take on this epic event? What does it mean for the industry generally, and customers specifically? >> You know, I think time will tell a little bit, Dave. We're in the early days. We've, you know, so we heard the original announcements and then it's evolved a little bit, as we're going now. I think overall it'll be good for the ecosystem in the end. There's a lot you can do when you start combining what VMware can do with compute and some of the hardware assets of Broadcom. There's a lot of security things that can be brought, for example, to the infrastructure, that are very high-end and cool, and then integrated, so it's easy to do. So I think there's a lot of upside for it. There's obviously a lot of concern about what it means for vendor consolidation and pricing and things like that. So time will tell. >> You know, when this announcement first came out, I wrote a piece, you know, how "Broadcom will tame the VMware beast," I called it. And, you know, looked at Broadcom's history and said they're going to cut, they're going to raise prices, et cetera, et cetera. But I've seen a different tone, certainly, as Broadcom has got into the details. And I'm sure I and others maybe scared a lot of customers, but I think everybody's kind of calming down now. What are you hearing from customers about this acquisition? How are they thinking about it? >> You know, I think it varies. There's, I'd say generally we have like half our installed base, Dave, runs ESX Server, so the bulk of our customers use VMware, and generally they love VMware. And I'm talking mainly on-prem. We're just extending to the cloud now, really, at scale. And there's a lot of interest in continuing to do that, and that's really strong. The piece that's careful is this vendor, the cost issues that have come up. The things that were in your piece, actually. And what does that mean to me, and how do I balance that out? Those are the questions people are dealing with right now. >> Yeah, so there's obviously a lot of talk about the macro, the macro headwinds. Everybody's being a little cautious. The CIOs are tapping the brakes. We all sort of know that story. But we have some data from our partner ETR that ask, they go out every quarter and they survey, you know, 1500 or so IT practitioners, and they ask the ones that are planning to spend less, that are cutting, "How are you going to approach that? What's your primary methodology in terms of achieving, you know, cost optimization?" The number one, by far, answer was to consolidate redundant vendors. It was like, it's now up to about 40%. The second, distant second, was, "We're going to, you know, optimize cloud costs." You know, still significant, but it was really that consolidating the redundant vendors. Do you see that? How does NetApp fit into that? >> Yeah, that is an interesting, that's a very interesting bit of research, Dave. I think it's very right. One thing I would say is, because I've been in the infrastructure business in Silicon Valley now for 30 years. So these ups and downs are, that's a consistent thing in our industry, and I always think people should think of their infrastructure and cost management. That's always an issue, with infrastructure as cost management. What I've told customers forever is that when you look at cost management, our best customers at cost management are typically service providers. There's another aspect to cost management, is you want to automate as much as possible. And automation goes along with vendor consolidation, because how you automate different products, you don't want to have too many vendors in your layers. And what I mean by the layers of ecosystem, there's a storage layer, the network layer, the compute layer, like, the security layer, database layer, et cetera. When you think like that, everybody should pick their partners very carefully, per layer. And one last thought on this is, it's not like people are dumb, and not trying to do this. It's, when you look at what happens in the real world, acquisitions happen, things change as you go. And in these big customers, that's just normal, that things change. But you always have to have this push towards consolidating and picking your vendors very carefully. >> Also, just to follow up on that, I mean, you know, when you think about multi-cloud, and you mentioned, you know, you've got some big customers, they do a lot of M & A, it's kind of been multi-cloud by accident. "Oh, we got all these other tools and storage platforms and whatever it is." So where does NetApp fit in that whole consolidation equation? I'm thinking about, you know, cross-cloud services, which is a big VMware theme, thinking about a consistent experience, on-prem, hybrid, across the three big clouds, out to the edge. Where do you fit? >> So our view has been, and it was this view, and we extend it to the cloud, is that the data layer, so in our software, is called ONTAP, the data layer is a really important layer that provides a lot of efficiency. It only gets bigger, how you do compliance, how you do backup, DR, blah blah blah. All that data layer services needs to operate on-prem and on the clouds. So when you look at what we've done over the years, we've extended to all the clouds, our data layer. We've put controls, management tools, over the top, so that you can manage the entire data layer, on-prem and cloud, as one layer. And we're continuing to head down that path, 'cause we think that data layer is obviously the path to maximum ability to do compliance, maximum cost advantages, et cetera. So we've really been the company that set our sights on managing the data layer. Now, if you look at VMware, go up into the network layer, the compute layer, VMware is a great partner, and that's why we work with them so closely, is they're so perfect a fit for us, and they've been a great partner for 20 years for us, connecting those infrastructural data layers: compute, network, and storage. >> Well, just to stay on that for a second. I've seen recently, you kind of doubled down on your VMware alliance. You've got stuff at re:Invent I saw, with AWS, you're close to Azure, and I'm really talking about ONTAP, which is sort of an extension of what you were just talking about, Phil, which is, you know, it's kind of NetApp's storage operating system, if you will. It's a world class. But so, maybe talk about that relationship a little bit, and how you see it evolving. >> Well, so what we've been seeing consistently is, customers want to use the advantages of the cloud. So, point one. And when you have to completely refactor apps and all this stuff, it limits, it's friction. It limits what you can do, it raises costs. And what we did with VMware, VMware is this great platform for being able to run basically client-server apps on-prem and cloud, the exact same way. The problem is, when you have large data sets in the VMs, there's some cost issues and things, especially on the cloud. That drove us to work together, and do what we did. We GA-ed, we're the, so NetApp is the only independent storage, independent storage, say this right, independent storage platform certified to run with VMware cloud on Amazon. We GA-ed that last summer. We GA-ed with Azure, the Azure VMware service, a couple months ago. And you'll see news coming with GCP soon. And so the idea was, make it easy for customers to basically run in a hybrid model. And then if you back out and go, "What does that mean for you as a customer?", it's not saying you should go to the cloud, necessarily, or stay on-prem, or whatever. But it's giving you the flexibility to cost-optimize where you want to be. And from a data management point of view, ONTAP gives you the consistent data management, whichever way you decide to go. >> Yeah, so I've been following NetApp for decades, when you were Network Appliance, and I saw you go from kind of the workstation space into the enterprise. I saw you lean into virtualization really early on, and you've been a great VMware partner ever since. And you were early in cloud, so, sort of talking about, you know, that cross-cloud, what we call supercloud. I'm interested in what you're seeing in terms of specific actions that customers are taking. Like, I think about ELAs, and I think it's a two-edged sword. You know, should customers, you know, lean into ELAs right now? You know, what are you seeing there? You talked about, you know, sort of modernizing apps with things like Kubernetes, you know, cloud migration. What are some of the techniques that you're advising customers to take in the context of this acquisition? >> You know, so the basics of this are pretty easy. One is, and I think even Raghu, the CEO of VMware, has talked about this. Extending your ELA is probably a good idea. Like I said, customers love VMware, so having a commitment for a time, consistent cost management for a time is a good strategy. And I think that's why you're hearing ELA extensions being discussed. It's a good idea. The second part, and I think it goes to your surveys, that cost optimization point on the cloud is, moving to the cloud has huge advantages, but if you just kind of lift and shift, oftentimes the costs aren't realized the way you'd want. And the term "modernization," changing your app to use more Kubernetes, more cloud-native services, is often a consideration that goes into that. But that requires time. And you know, most companies have hundreds of apps, or thousands of apps, they have to consider modernizing. So you want to then think through the journey, what apps are going to move, what gets modernized, what gets lifted-shifted, how many data centers are you compressing? There's a lot of data center, the term I've been hearing is "data center evacuations," but data center consolidation. So that there's some even energy savings advantages sometimes with that. But the whole point, I mean, back up to my whole point, the whole point is having the infrastructure that gives you the flexibility to make the journey on your cost advantages and your business requirements. Not being forced to it. Like, it's not really a philosophy, it's more of a business optimization strategy. >> When you think about application modernization and Kubernetes, how does NetApp, you know, fit into that, as a data layer? >> Well, so if you kind of think, you said, like our journey, Dave, was, when we started our life, we were doing basically virtualization of volumes and things for technical customers. And the servers were always bare metal servers that we got involved with back then. This is, like, going back 20 years. Then everyone moved to VMs, and, like, it's probably, today, I mean, getting to your question in a second, but today, loosely, 20% bare metal servers, 80% virtual machines today. And containers is growing, now a big growing piece. So, if you will, sort of another level of virtual machines in containers. And containers were historically stateless, meaning the storage didn't have anything to do. Storage is always the stateful area in the architectures. But as containers are getting used more, stateful containers have become a big deal. So we've put a lot of emphasis into a product line we call Astra that is the world's best data management for containers. And that's both a cloud service and used on-prem in a lot of my customers. It's a big growth area. So that's what, when I say, like, one partner that can do data management, just, that's what we have to do. We have to keep moving with our customers to the type of data they want to store, and how do you store it most efficiently? Hey, one last thought on this is, where I really see this happening, there's a booming business right now in artificial intelligence, and we call it modern data analytics, but people combining big data lakes with AI, and that's where some of this, a lot of the container work comes in. We've extended objects, we have a thing we call file-object duality, to make it easy to bridge the old world of files to the new world of objects. Those all go hand in hand with app modernization. >> Yeah, it's a great thing about this industry. It never sits still. And you're right, it's- >> It's why I'm in it. >> Me too. Yeah, it's so much fun. There's always something. >> It is an abstraction layer. There's always going to be another abstraction layer. Serverless is another example. It's, you know, primarily stateless, that's probably going to, you know, change over time. All right, last question. In thinking about this Broadcom acquisition of VMware, in the macro climate, put a sort of bow on where NetApp fits into this equation. What's the value you bring in this context? >> Oh yeah, well it's like I said earlier, I think it's the data layer of, it's being the data layer that gives you what you guys call the supercloud, that gives you the ability to choose which cloud. Another thing, all customers are running at least two clouds, and you want to be able to pick and choose, and do it your way. So being the data layer, VMware is going to be in our infrastructures for at least as long as I'm in the computer business, Dave. I'm getting a little old. So maybe, you know, but "decades" I think is an easy prediction, and we plan to work with VMware very closely, along with our customers, as they extend from on-prem to hybrid cloud operations. That's where I think this will go. >> Yeah, and I think you're absolutely right. Look at the business case for migrating off of VMware. It just doesn't make sense. It works, it's world class, it recover... They've done so much amazing, you know, they used to be called, Moritz called it the software mainframe, right? And that's kind of what it is. I mean, it means it doesn't go down, right? And it supports virtually any application, you know, around the world, so. >> And I think getting back to your original point about your article, from the very beginning, is, I think Broadcom's really getting a sense of what they've bought, and it's going to be, hopefully, I think it'll be really a fun, another fun era in our business. >> Well, and you can drive EBIT a couple of ways. You can cut, okay, fine. And I'm sure there's some redundancies that they'll find. But there's also, you can drive top-line revenue. And you know, we've seen how, you know, EMC and then Dell used that growth from VMware to throw off free cash flow, and it was just, you know, funded so much, you know, innovation. So innovation is the key. Hock Tan has talked about that a lot. I think there's a perception that Broadcom, you know, doesn't invest in R & D. That's not true. I think they just get very focused with that investment. So, Phil, I really appreciate your time. Thanks so much for joining us. >> Thanks a lot, Dave. It's fun being here. >> Yeah, our pleasure. And thank you for watching theCUBE, your leader in enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Hello, this is Dave Valente with theCUBE, and one of the most gratifying aspects of my role as a host of "theCUBE TV" is I get to cover a wide range of topics. And quite often, we're able to bring to our program a level of expertise that allows us to more deeply explore and unpack some of the topics that we cover throughout the year. And one of our favorite topics, of course, is data. Now, in 2021, after being in isolation for the better part of two years, a group of industry analysts met up at AWS re:Invent and started a collaboration to look at the trends in data and predict what some likely outcomes will be for the coming year. And it resulted in a very popular session that we had last year focused on the future of data management. And I'm very excited and pleased to tell you that the 2023 edition of that predictions episode is back, and with me are five outstanding market analyst, Sanjeev Mohan of SanjMo, Tony Baer of dbInsight, Carl Olofson from IDC, Dave Menninger from Ventana Research, and Doug Henschen, VP and Principal Analyst at Constellation Research. Now, what is it that we're calling you, guys? A data pack like the rat pack? No, no, no, no, that's not it. It's the data crowd, the data crowd, and the crowd includes some of the best minds in the data analyst community. They'll discuss how data management is evolving and what listeners should prepare for in 2023. Guys, welcome back. Great to see you. >> Good to be here. >> Thank you. >> Thanks, Dave. (Tony and Dave faintly speaks) >> All right, before we get into 2023 predictions, we thought it'd be good to do a look back at how we did in 2022 and give a transparent assessment of those predictions. So, let's get right into it. We're going to bring these up here, the predictions from 2022, they're color-coded red, yellow, and green to signify the degree of accuracy. And I'm pleased to report there's no red. Well, maybe some of you will want to debate that grading system. But as always, we want to be open, so you can decide for yourselves. So, we're going to ask each analyst to review their 2022 prediction and explain their rating and what evidence they have that led them to their conclusion. So, Sanjeev, please kick it off. Your prediction was data governance becomes key. I know that's going to knock you guys over, but elaborate, because you had more detail when you double click on that. >> Yeah, absolutely. Thank you so much, Dave, for having us on the show today. And we self-graded ourselves. I could have very easily made my prediction from last year green, but I mentioned why I left it as yellow. I totally fully believe that data governance was in a renaissance in 2022. And why do I say that? You have to look no further than AWS launching its own data catalog called DataZone. Before that, mid-year, we saw Unity Catalog from Databricks went GA. So, overall, I saw there was tremendous movement. When you see these big players launching a new data catalog, you know that they want to be in this space. And this space is highly critical to everything that I feel we will talk about in today's call. Also, if you look at established players, I spoke at Collibra's conference, data.world, work closely with Alation, Informatica, a bunch of other companies, they all added tremendous new capabilities. So, it did become key. The reason I left it as yellow is because I had made a prediction that Collibra would go IPO, and it did not. And I don't think anyone is going IPO right now. The market is really, really down, the funding in VC IPO market. But other than that, data governance had a banner year in 2022. >> Yeah. Well, thank you for that. And of course, you saw data clean rooms being announced at AWS re:Invent, so more evidence. And I like how the fact that you included in your predictions some things that were binary, so you dinged yourself there. So, good job. Okay, Tony Baer, you're up next. Data mesh hits reality check. As you see here, you've given yourself a bright green thumbs up. (Tony laughing) Okay. Let's hear why you feel that was the case. What do you mean by reality check? >> Okay. Thanks, Dave, for having us back again. This is something I just wrote and just tried to get away from, and this just a topic just won't go away. I did speak with a number of folks, early adopters and non-adopters during the year. And I did find that basically that it pretty much validated what I was expecting, which was that there was a lot more, this has now become a front burner issue. And if I had any doubt in my mind, the evidence I would point to is what was originally intended to be a throwaway post on LinkedIn, which I just quickly scribbled down the night before leaving for re:Invent. I was packing at the time, and for some reason, I was doing Google search on data mesh. And I happened to have tripped across this ridiculous article, I will not say where, because it doesn't deserve any publicity, about the eight (Dave laughing) best data mesh software companies of 2022. (Tony laughing) One of my predictions was that you'd see data mesh washing. And I just quickly just hopped on that maybe three sentences and wrote it at about a couple minutes saying this is hogwash, essentially. (laughs) And that just reun... And then, I left for re:Invent. And the next night, when I got into my Vegas hotel room, I clicked on my computer. I saw a 15,000 hits on that post, which was the most hits of any single post I put all year. And the responses were wildly pro and con. So, it pretty much validates my expectation in that data mesh really did hit a lot more scrutiny over this past year. >> Yeah, thank you for that. I remember that article. I remember rolling my eyes when I saw it, and then I recently, (Tony laughing) I talked to Walmart and they actually invoked Martin Fowler and they said that they're working through their data mesh. So, it takes a really lot of thought, and it really, as we've talked about, is really as much an organizational construct. You're not buying data mesh >> Bingo. >> to your point. Okay. Thank you, Tony. Carl Olofson, here we go. You've graded yourself a yellow in the prediction of graph databases. Take off. Please elaborate. >> Yeah, sure. So, I realized in looking at the prediction that it seemed to imply that graph databases could be a major factor in the data world in 2022, which obviously didn't become the case. It was an error on my part in that I should have said it in the right context. It's really a three to five-year time period that graph databases will really become significant, because they still need accepted methodologies that can be applied in a business context as well as proper tools in order for people to be able to use them seriously. But I stand by the idea that it is taking off, because for one thing, Neo4j, which is the leading independent graph database provider, had a very good year. And also, we're seeing interesting developments in terms of things like AWS with Neptune and with Oracle providing graph support in Oracle database this past year. Those things are, as I said, growing gradually. There are other companies like TigerGraph and so forth, that deserve watching as well. But as far as becoming mainstream, it's going to be a few years before we get all the elements together to make that happen. Like any new technology, you have to create an environment in which ordinary people without a whole ton of technical training can actually apply the technology to solve business problems. >> Yeah, thank you for that. These specialized databases, graph databases, time series databases, you see them embedded into mainstream data platforms, but there's a place for these specialized databases, I would suspect we're going to see new types of databases emerge with all this cloud sprawl that we have and maybe to the edge. >> Well, part of it is that it's not as specialized as you might think it. You can apply graphs to great many workloads and use cases. It's just that people have yet to fully explore and discover what those are. >> Yeah. >> And so, it's going to be a process. (laughs) >> All right, Dave Menninger, streaming data permeates the landscape. You gave yourself a yellow. Why? >> Well, I couldn't think of a appropriate combination of yellow and green. Maybe I should have used chartreuse, (Dave laughing) but I was probably a little hard on myself making it yellow. This is another type of specialized data processing like Carl was talking about graph databases is a stream processing, and nearly every data platform offers streaming capabilities now. Often, it's based on Kafka. If you look at Confluent, their revenues have grown at more than 50%, continue to grow at more than 50% a year. They're expected to do more than half a billion dollars in revenue this year. But the thing that hasn't happened yet, and to be honest, they didn't necessarily expect it to happen in one year, is that streaming hasn't become the default way in which we deal with data. It's still a sidecar to data at rest. And I do expect that we'll continue to see streaming become more and more mainstream. I do expect perhaps in the five-year timeframe that we will first deal with data as streaming and then at rest, but the worlds are starting to merge. And we even see some vendors bringing products to market, such as K2View, Hazelcast, and RisingWave Labs. So, in addition to all those core data platform vendors adding these capabilities, there are new vendors approaching this market as well. >> I like the tough grading system, and it's not trivial. And when you talk to practitioners doing this stuff, there's still some complications in the data pipeline. And so, but I think, you're right, it probably was a yellow plus. Doug Henschen, data lakehouses will emerge as dominant. When you talk to people about lakehouses, practitioners, they all use that term. They certainly use the term data lake, but now, they're using lakehouse more and more. What's your thoughts on here? Why the green? What's your evidence there? >> Well, I think, I was accurate. I spoke about it specifically as something that vendors would be pursuing. And we saw yet more lakehouse advocacy in 2022. Google introduced its BigLake service alongside BigQuery. Salesforce introduced Genie, which is really a lakehouse architecture. And it was a safe prediction to say vendors are going to be pursuing this in that AWS, Cloudera, Databricks, Microsoft, Oracle, SAP, Salesforce now, IBM, all advocate this idea of a single platform for all of your data. Now, the trend was also supported in 2023, in that we saw a big embrace of Apache Iceberg in 2022. That's a structured table format. It's used with these lakehouse platforms. It's open, so it ensures portability and it also ensures performance. And that's a structured table that helps with the warehouse side performance. But among those announcements, Snowflake, Google, Cloud Era, SAP, Salesforce, IBM, all embraced Iceberg. But keep in mind, again, I'm talking about this as something that vendors are pursuing as their approach. So, they're advocating end users. It's very cutting edge. I'd say the top, leading edge, 5% of of companies have really embraced the lakehouse. I think, we're now seeing the fast followers, the next 20 to 25% of firms embracing this idea and embracing a lakehouse architecture. I recall Christian Kleinerman at the big Snowflake event last summer, making the announcement about Iceberg, and he asked for a show of hands for any of you in the audience at the keynote, have you heard of Iceberg? And just a smattering of hands went up. So, the vendors are ahead of the curve. They're pushing this trend, and we're now seeing a little bit more mainstream uptake. >> Good. Doug, I was there. It was you, me, and I think, two other hands were up. That was just humorous. (Doug laughing) All right, well, so I liked the fact that we had some yellow and some green. When you think about these things, there's the prediction itself. Did it come true or not? There are the sub predictions that you guys make, and of course, the degree of difficulty. So, thank you for that open assessment. All right, let's get into the 2023 predictions. Let's bring up the predictions. Sanjeev, you're going first. You've got a prediction around unified metadata. What's the prediction, please? >> So, my prediction is that metadata space is currently a mess. It needs to get unified. There are too many use cases of metadata, which are being addressed by disparate systems. For example, data quality has become really big in the last couple of years, data observability, the whole catalog space is actually, people don't like to use the word data catalog anymore, because data catalog sounds like it's a catalog, a museum, if you may, of metadata that you go and admire. So, what I'm saying is that in 2023, we will see that metadata will become the driving force behind things like data ops, things like orchestration of tasks using metadata, not rules. Not saying that if this fails, then do this, if this succeeds, go do that. But it's like getting to the metadata level, and then making a decision as to what to orchestrate, what to automate, how to do data quality check, data observability. So, this space is starting to gel, and I see there'll be more maturation in the metadata space. Even security privacy, some of these topics, which are handled separately. And I'm just talking about data security and data privacy. I'm not talking about infrastructure security. These also need to merge into a unified metadata management piece with some knowledge graph, semantic layer on top, so you can do analytics on it. So, it's no longer something that sits on the side, it's limited in its scope. It is actually the very engine, the very glue that is going to connect data producers and consumers. >> Great. Thank you for that. Doug. Doug Henschen, any thoughts on what Sanjeev just said? Do you agree? Do you disagree? >> Well, I agree with many aspects of what he says. I think, there's a huge opportunity for consolidation and streamlining of these as aspects of governance. Last year, Sanjeev, you said something like, we'll see more people using catalogs than BI. And I have to disagree. I don't think this is a category that's headed for mainstream adoption. It's a behind the scenes activity for the wonky few, or better yet, companies want machine learning and automation to take care of these messy details. We've seen these waves of management technologies, some of the latest data observability, customer data platform, but they failed to sweep away all the earlier investments in data quality and master data management. So, yes, I hope the latest tech offers, glimmers that there's going to be a better, cleaner way of addressing these things. But to my mind, the business leaders, including the CIO, only want to spend as much time and effort and money and resources on these sorts of things to avoid getting breached, ending up in headlines, getting fired or going to jail. So, vendors bring on the ML and AI smarts and the automation of these sorts of activities. >> So, if I may say something, the reason why we have this dichotomy between data catalog and the BI vendors is because data catalogs are very soon, not going to be standalone products, in my opinion. They're going to get embedded. So, when you use a BI tool, you'll actually use the catalog to find out what is it that you want to do, whether you are looking for data or you're looking for an existing dashboard. So, the catalog becomes embedded into the BI tool. >> Hey, Dave Menninger, sometimes you have some data in your back pocket. Do you have any stats (chuckles) on this topic? >> No, I'm glad you asked, because I'm going to... Now, data catalogs are something that's interesting. Sanjeev made a statement that data catalogs are falling out of favor. I don't care what you call them. They're valuable to organizations. Our research shows that organizations that have adequate data catalog technologies are three times more likely to express satisfaction with their analytics for just the reasons that Sanjeev was talking about. You can find what you want, you know you're getting the right information, you know whether or not it's trusted. So, those are good things. So, we expect to see the capabilities, whether it's embedded or separate. We expect to see those capabilities continue to permeate the market. >> And a lot of those catalogs are driven now by machine learning and things. So, they're learning from those patterns of usage by people when people use the data. (airy laughs) >> All right. Okay. Thank you, guys. All right. Let's move on to the next one. Tony Bear, let's bring up the predictions. You got something in here about the modern data stack. We need to rethink it. Is the modern data stack getting long at the tooth? Is it not so modern anymore? >> I think, in a way, it's got almost too modern. It's gotten too, I don't know if it's being long in the tooth, but it is getting long. The modern data stack, it's traditionally been defined as basically you have the data platform, which would be the operational database and the data warehouse. And in between, you have all the tools that are necessary to essentially get that data from the operational realm or the streaming realm for that matter into basically the data warehouse, or as we might be seeing more and more, the data lakehouse. And I think, what's important here is that, or I think, we have seen a lot of progress, and this would be in the cloud, is with the SaaS services. And especially you see that in the modern data stack, which is like all these players, not just the MongoDBs or the Oracles or the Amazons have their database platforms. You see they have the Informatica's, and all the other players there in Fivetrans have their own SaaS services. And within those SaaS services, you get a certain degree of simplicity, which is it takes all the housekeeping off the shoulders of the customers. That's a good thing. The problem is that what we're getting to unfortunately is what I would call lots of islands of simplicity, which means that it leads it (Dave laughing) to the customer to have to integrate or put all that stuff together. It's a complex tool chain. And so, what we really need to think about here, we have too many pieces. And going back to the discussion of catalogs, it's like we have so many catalogs out there, which one do we use? 'Cause chances are of most organizations do not rely on a single catalog at this point. What I'm calling on all the data providers or all the SaaS service providers, is to literally get it together and essentially make this modern data stack less of a stack, make it more of a blending of an end-to-end solution. And that can come in a number of different ways. Part of it is that we're data platform providers have been adding services that are adjacent. And there's some very good examples of this. We've seen progress over the past year or so. For instance, MongoDB integrating search. It's a very common, I guess, sort of tool that basically, that the applications that are developed on MongoDB use, so MongoDB then built it into the database rather than requiring an extra elastic search or open search stack. Amazon just... AWS just did the zero-ETL, which is a first step towards simplifying the process from going from Aurora to Redshift. You've seen same thing with Google, BigQuery integrating basically streaming pipelines. And you're seeing also a lot of movement in database machine learning. So, there's some good moves in this direction. I expect to see more than this year. Part of it's from basically the SaaS platform is adding some functionality. But I also see more importantly, because you're never going to get... This is like asking your data team and your developers, herding cats to standardizing the same tool. In most organizations, that is not going to happen. So, take a look at the most popular combinations of tools and start to come up with some pre-built integrations and pre-built orchestrations, and offer some promotional pricing, maybe not quite two for, but in other words, get two products for the price of two services or for the price of one and a half. I see a lot of potential for this. And it's to me, if the class was to simplify things, this is the next logical step and I expect to see more of this here. >> Yeah, and you see in Oracle, MySQL heat wave, yet another example of eliminating that ETL. Carl Olofson, today, if you think about the data stack and the application stack, they're largely separate. Do you have any thoughts on how that's going to play out? Does that play into this prediction? What do you think? >> Well, I think, that the... I really like Tony's phrase, islands of simplification. It really says (Tony chuckles) what's going on here, which is that all these different vendors you ask about, about how these stacks work. All these different vendors have their own stack vision. And you can... One application group is going to use one, and another application group is going to use another. And some people will say, let's go to, like you go to a Informatica conference and they say, we should be the center of your universe, but you can't connect everything in your universe to Informatica, so you need to use other things. So, the challenge is how do we make those things work together? As Tony has said, and I totally agree, we're never going to get to the point where people standardize on one organizing system. So, the alternative is to have metadata that can be shared amongst those systems and protocols that allow those systems to coordinate their operations. This is standard stuff. It's not easy. But the motive for the vendors is that they can become more active critical players in the enterprise. And of course, the motive for the customer is that things will run better and more completely. So, I've been looking at this in terms of two kinds of metadata. One is the meaning metadata, which says what data can be put together. The other is the operational metadata, which says basically where did it come from? Who created it? What's its current state? What's the security level? Et cetera, et cetera, et cetera. The good news is the operational stuff can actually be done automatically, whereas the meaning stuff requires some human intervention. And as we've already heard from, was it Doug, I think, people are disinclined to put a lot of definition into meaning metadata. So, that may be the harder one, but coordination is key. This problem has been with us forever, but with the addition of new data sources, with streaming data with data in different formats, the whole thing has, it's been like what a customer of mine used to say, "I understand your product can make my system run faster, but right now I just feel I'm putting my problems on roller skates. (chuckles) I don't need that to accelerate what's already not working." >> Excellent. Okay, Carl, let's stay with you. I remember in the early days of the big data movement, Hadoop movement, NoSQL was the big thing. And I remember Amr Awadallah said to us in theCUBE that SQL is the killer app for big data. So, your prediction here, if we bring that up is SQL is back. Please elaborate. >> Yeah. So, of course, some people would say, well, it never left. Actually, that's probably closer to true, but in the perception of the marketplace, there's been all this noise about alternative ways of storing, retrieving data, whether it's in key value stores or document databases and so forth. We're getting a lot of messaging that for a while had persuaded people that, oh, we're not going to do analytics in SQL anymore. We're going to use Spark for everything, except that only a handful of people know how to use Spark. Oh, well, that's a problem. Well, how about, and for ordinary conventional business analytics, Spark is like an over-engineered solution to the problem. SQL works just great. What's happened in the past couple years, and what's going to continue to happen is that SQL is insinuating itself into everything we're seeing. We're seeing all the major data lake providers offering SQL support, whether it's Databricks or... And of course, Snowflake is loving this, because that is what they do, and their success is certainly points to the success of SQL, even MongoDB. And we were all, I think, at the MongoDB conference where on one day, we hear SQL is dead. They're not teaching SQL in schools anymore, and this kind of thing. And then, a couple days later at the same conference, they announced we're adding a new analytic capability-based on SQL. But didn't you just say SQL is dead? So, the reality is that SQL is better understood than most other methods of certainly of retrieving and finding data in a data collection, no matter whether it happens to be relational or non-relational. And even in systems that are very non-relational, such as graph and document databases, their query languages are being built or extended to resemble SQL, because SQL is something people understand. >> Now, you remember when we were in high school and you had had to take the... Your debating in the class and you were forced to take one side and defend it. So, I was was at a Vertica conference one time up on stage with Curt Monash, and I had to take the NoSQL, the world is changing paradigm shift. And so just to be controversial, I said to him, Curt Monash, I said, who really needs acid compliance anyway? Tony Baer. And so, (chuckles) of course, his head exploded, but what are your thoughts (guests laughing) on all this? >> Well, my first thought is congratulations, Dave, for surviving being up on stage with Curt Monash. >> Amen. (group laughing) >> I definitely would concur with Carl. We actually are definitely seeing a SQL renaissance and if there's any proof of the pudding here, I see lakehouse is being icing on the cake. As Doug had predicted last year, now, (clears throat) for the record, I think, Doug was about a year ahead of time in his predictions that this year is really the year that I see (clears throat) the lakehouse ecosystems really firming up. You saw the first shots last year. But anyway, on this, data lakes will not go away. I've actually, I'm on the home stretch of doing a market, a landscape on the lakehouse. And lakehouse will not replace data lakes in terms of that. There is the need for those, data scientists who do know Python, who knows Spark, to go in there and basically do their thing without all the restrictions or the constraints of a pre-built, pre-designed table structure. I get that. Same thing for developing models. But on the other hand, there is huge need. Basically, (clears throat) maybe MongoDB was saying that we're not teaching SQL anymore. Well, maybe we have an oversupply of SQL developers. Well, I'm being facetious there, but there is a huge skills based in SQL. Analytics have been built on SQL. They came with lakehouse and why this really helps to fuel a SQL revival is that the core need in the data lake, what brought on the lakehouse was not so much SQL, it was a need for acid. And what was the best way to do it? It was through a relational table structure. So, the whole idea of acid in the lakehouse was not to turn it into a transaction database, but to make the data trusted, secure, and more granularly governed, where you could govern down to column and row level, which you really could not do in a data lake or a file system. So, while lakehouse can be queried in a manner, you can go in there with Python or whatever, it's built on a relational table structure. And so, for that end, for those types of data lakes, it becomes the end state. You cannot bypass that table structure as I learned the hard way during my research. So, the bottom line I'd say here is that lakehouse is proof that we're starting to see the revenge of the SQL nerds. (Dave chuckles) >> Excellent. Okay, let's bring up back up the predictions. Dave Menninger, this one's really thought-provoking and interesting. We're hearing things like data as code, new data applications, machines actually generating plans with no human involvement. And your prediction is the definition of data is expanding. What do you mean by that? >> So, I think, for too long, we've thought about data as the, I would say facts that we collect the readings off of devices and things like that, but data on its own is really insufficient. Organizations need to manipulate that data and examine derivatives of the data to really understand what's happening in their organization, why has it happened, and to project what might happen in the future. And my comment is that these data derivatives need to be supported and managed just like the data needs to be managed. We can't treat this as entirely separate. Think about all the governance discussions we've had. Think about the metadata discussions we've had. If you separate these things, now you've got more moving parts. We're talking about simplicity and simplifying the stack. So, if these things are treated separately, it creates much more complexity. I also think it creates a little bit of a myopic view on the part of the IT organizations that are acquiring these technologies. They need to think more broadly. So, for instance, metrics. Metric stores are becoming much more common part of the tooling that's part of a data platform. Similarly, feature stores are gaining traction. So, those are designed to promote the reuse and consistency across the AI and ML initiatives. The elements that are used in developing an AI or ML model. And let me go back to metrics and just clarify what I mean by that. So, any type of formula involving the data points. I'm distinguishing metrics from features that are used in AI and ML models. And the data platforms themselves are increasingly managing the models as an element of data. So, just like figuring out how to calculate a metric. Well, if you're going to have the features associated with an AI and ML model, you probably need to be managing the model that's associated with those features. The other element where I see expansion is around external data. Organizations for decades have been focused on the data that they generate within their own organization. We see more and more of these platforms acquiring and publishing data to external third-party sources, whether they're within some sort of a partner ecosystem or whether it's a commercial distribution of that information. And our research shows that when organizations use external data, they derive even more benefits from the various analyses that they're conducting. And the last great frontier in my opinion on this expanding world of data is the world of driver-based planning. Very few of the major data platform providers provide these capabilities today. These are the types of things you would do in a spreadsheet. And we all know the issues associated with spreadsheets. They're hard to govern, they're error-prone. And so, if we can take that type of analysis, collecting the occupancy of a rental property, the projected rise in rental rates, the fluctuations perhaps in occupancy, the interest rates associated with financing that property, we can project forward. And that's a very common thing to do. What the income might look like from that property income, the expenses, we can plan and purchase things appropriately. So, I think, we need this broader purview and I'm beginning to see some of those things happen. And the evidence today I would say, is more focused around the metric stores and the feature stores starting to see vendors offer those capabilities. And we're starting to see the ML ops elements of managing the AI and ML models find their way closer to the data platforms as well. >> Very interesting. When I hear metrics, I think of KPIs, I think of data apps, orchestrate people and places and things to optimize around a set of KPIs. It sounds like a metadata challenge more... Somebody once predicted they'll have more metadata than data. Carl, what are your thoughts on this prediction? >> Yeah, I think that what Dave is describing as data derivatives is in a way, another word for what I was calling operational metadata, which not about the data itself, but how it's used, where it came from, what the rules are governing it, and that kind of thing. If you have a rich enough set of those things, then not only can you do a model of how well your vacation property rental may do in terms of income, but also how well your application that's measuring that is doing for you. In other words, how many times have I used it, how much data have I used and what is the relationship between the data that I've used and the benefits that I've derived from using it? Well, we don't have ways of doing that. What's interesting to me is that folks in the content world are way ahead of us here, because they have always tracked their content using these kinds of attributes. Where did it come from? When was it created, when was it modified? Who modified it? And so on and so forth. We need to do more of that with the structure data that we have, so that we can track what it's used. And also, it tells us how well we're doing with it. Is it really benefiting us? Are we being efficient? Are there improvements in processes that we need to consider? Because maybe data gets created and then it isn't used or it gets used, but it gets altered in some way that actually misleads people. (laughs) So, we need the mechanisms to be able to do that. So, I would say that that's... And I'd say that it's true that we need that stuff. I think, that starting to expand is probably the right way to put it. It's going to be expanding for some time. I think, we're still a distance from having all that stuff really working together. >> Maybe we should say it's gestating. (Dave and Carl laughing) >> Sorry, if I may- >> Sanjeev, yeah, I was going to say this... Sanjeev, please comment. This sounds to me like it supports Zhamak Dehghani's principles, but please. >> Absolutely. So, whether we call it data mesh or not, I'm not getting into that conversation, (Dave chuckles) but data (audio breaking) (Tony laughing) everything that I'm hearing what Dave is saying, Carl, this is the year when data products will start to take off. I'm not saying they'll become mainstream. They may take a couple of years to become so, but this is data products, all this thing about vacation rentals and how is it doing, that data is coming from different sources. I'm packaging it into our data product. And to Carl's point, there's a whole operational metadata associated with it. The idea is for organizations to see things like developer productivity, how many releases am I doing of this? What data products are most popular? I'm actually in right now in the process of formulating this concept that just like we had data catalogs, we are very soon going to be requiring data products catalog. So, I can discover these data products. I'm not just creating data products left, right, and center. I need to know, do they already exist? What is the usage? If no one is using a data product, maybe I want to retire and save cost. But this is a data product. Now, there's a associated thing that is also getting debated quite a bit called data contracts. And a data contract to me is literally just formalization of all these aspects of a product. How do you use it? What is the SLA on it, what is the quality that I am prescribing? So, data product, in my opinion, shifts the conversation to the consumers or to the business people. Up to this point when, Dave, you're talking about data and all of data discovery curation is a very data producer-centric. So, I think, we'll see a shift more into the consumer space. >> Yeah. Dave, can I just jump in there just very quickly there, which is that what Sanjeev has been saying there, this is really central to what Zhamak has been talking about. It's basically about making, one, data products are about the lifecycle management of data. Metadata is just elemental to that. And essentially, one of the things that she calls for is making data products discoverable. That's exactly what Sanjeev was talking about. >> By the way, did everyone just no notice how Sanjeev just snuck in another prediction there? So, we've got- >> Yeah. (group laughing) >> But you- >> Can we also say that he snuck in, I think, the term that we'll remember today, which is metadata museums. >> Yeah, but- >> Yeah. >> And also comment to, Tony, to your last year's prediction, you're really talking about it's not something that you're going to buy from a vendor. >> No. >> It's very specific >> Mm-hmm. >> to an organization, their own data product. So, touche on that one. Okay, last prediction. Let's bring them up. Doug Henschen, BI analytics is headed to embedding. What does that mean? >> Well, we all know that conventional BI dashboarding reporting is really commoditized from a vendor perspective. It never enjoyed truly mainstream adoption. Always that 25% of employees are really using these things. I'm seeing rising interest in embedding concise analytics at the point of decision or better still, using analytics as triggers for automation and workflows, and not even necessitating human interaction with visualizations, for example, if we have confidence in the analytics. So, leading companies are pushing for next generation applications, part of this low-code, no-code movement we've seen. And they want to build that decision support right into the app. So, the analytic is right there. Leading enterprise apps vendors, Salesforce, SAP, Microsoft, Oracle, they're all building smart apps with the analytics predictions, even recommendations built into these applications. And I think, the progressive BI analytics vendors are supporting this idea of driving insight to action, not necessarily necessitating humans interacting with it if there's confidence. So, we want prediction, we want embedding, we want automation. This low-code, no-code development movement is very important to bringing the analytics to where people are doing their work. We got to move beyond the, what I call swivel chair integration, between where people do their work and going off to separate reports and dashboards, and having to interpret and analyze before you can go back and do take action. >> And Dave Menninger, today, if you want, analytics or you want to absorb what's happening in the business, you typically got to go ask an expert, and then wait. So, what are your thoughts on Doug's prediction? >> I'm in total agreement with Doug. I'm going to say that collectively... So, how did we get here? I'm going to say collectively as an industry, we made a mistake. We made BI and analytics separate from the operational systems. Now, okay, it wasn't really a mistake. We were limited by the technology available at the time. Decades ago, we had to separate these two systems, so that the analytics didn't impact the operations. You don't want the operations preventing you from being able to do a transaction. But we've gone beyond that now. We can bring these two systems and worlds together and organizations recognize that need to change. As Doug said, the majority of the workforce and the majority of organizations doesn't have access to analytics. That's wrong. (chuckles) We've got to change that. And one of the ways that's going to change is with embedded analytics. 2/3 of organizations recognize that embedded analytics are important and it even ranks higher in importance than AI and ML in those organizations. So, it's interesting. This is a really important topic to the organizations that are consuming these technologies. The good news is it works. Organizations that have embraced embedded analytics are more comfortable with self-service than those that have not, as opposed to turning somebody loose, in the wild with the data. They're given a guided path to the data. And the research shows that 65% of organizations that have adopted embedded analytics are comfortable with self-service compared with just 40% of organizations that are turning people loose in an ad hoc way with the data. So, totally behind Doug's predictions. >> Can I just break in with something here, a comment on what Dave said about what Doug said, which (laughs) is that I totally agree with what you said about embedded analytics. And at IDC, we made a prediction in our future intelligence, future of intelligence service three years ago that this was going to happen. And the thing that we're waiting for is for developers to build... You have to write the applications to work that way. It just doesn't happen automagically. Developers have to write applications that reference analytic data and apply it while they're running. And that could involve simple things like complex queries against the live data, which is through something that I've been calling analytic transaction processing. Or it could be through something more sophisticated that involves AI operations as Doug has been suggesting, where the result is enacted pretty much automatically unless the scores are too low and you need to have a human being look at it. So, I think that that is definitely something we've been watching for. I'm not sure how soon it will come, because it seems to take a long time for people to change their thinking. But I think, as Dave was saying, once they do and they apply these principles in their application development, the rewards are great. >> Yeah, this is very much, I would say, very consistent with what we were talking about, I was talking about before, about basically rethinking the modern data stack and going into more of an end-to-end solution solution. I think, that what we're talking about clearly here is operational analytics. There'll still be a need for your data scientists to go offline just in their data lakes to do all that very exploratory and that deep modeling. But clearly, it just makes sense to bring operational analytics into where people work into their workspace and further flatten that modern data stack. >> But with all this metadata and all this intelligence, we're talking about injecting AI into applications, it does seem like we're entering a new era of not only data, but new era of apps. Today, most applications are about filling forms out or codifying processes and require a human input. And it seems like there's enough data now and enough intelligence in the system that the system can actually pull data from, whether it's the transaction system, e-commerce, the supply chain, ERP, and actually do something with that data without human involvement, present it to humans. Do you guys see this as a new frontier? >> I think, that's certainly- >> Very much so, but it's going to take a while, as Carl said. You have to design it, you have to get the prediction into the system, you have to get the analytics at the point of decision has to be relevant to that decision point. >> And I also recall basically a lot of the ERP vendors back like 10 years ago, we're promising that. And the fact that we're still looking at the promises shows just how difficult, how much of a challenge it is to get to what Doug's saying. >> One element that could be applied in this case is (indistinct) architecture. If applications are developed that are event-driven rather than following the script or sequence that some programmer or designer had preconceived, then you'll have much more flexible applications. You can inject decisions at various points using this technology much more easily. It's a completely different way of writing applications. And it actually involves a lot more data, which is why we should all like it. (laughs) But in the end (Tony laughing) it's more stable, it's easier to manage, easier to maintain, and it's actually more efficient, which is the result of an MIT study from about 10 years ago, and still, we are not seeing this come to fruition in most business applications. >> And do you think it's going to require a new type of data platform database? Today, data's all far-flung. We see that's all over the clouds and at the edge. Today, you cache- >> We need a super cloud. >> You cache that data, you're throwing into memory. I mentioned, MySQL heat wave. There are other examples where it's a brute force approach, but maybe we need new ways of laying data out on disk and new database architectures, and just when we thought we had it all figured out. >> Well, without referring to disk, which to my mind, is almost like talking about cave painting. I think, that (Dave laughing) all the things that have been mentioned by all of us today are elements of what I'm talking about. In other words, the whole improvement of the data mesh, the improvement of metadata across the board and improvement of the ability to track data and judge its freshness the way we judge the freshness of a melon or something like that, to determine whether we can still use it. Is it still good? That kind of thing. Bringing together data from multiple sources dynamically and real-time requires all the things we've been talking about. All the predictions that we've talked about today add up to elements that can make this happen. >> Well, guys, it's always tremendous to get these wonderful minds together and get your insights, and I love how it shapes the outcome here of the predictions, and let's see how we did. We're going to leave it there. I want to thank Sanjeev, Tony, Carl, David, and Doug. Really appreciate the collaboration and thought that you guys put into these sessions. Really, thank you. >> Thank you. >> Thanks, Dave. >> Thank you for having us. >> Thanks. >> Thank you. >> All right, this is Dave Valente for theCUBE, signing off for now. Follow these guys on social media. Look for coverage on siliconangle.com, theCUBE.net. Thank you for watching. (upbeat music)

(lively music) >> Good afternoon and welcome back to beautiful Las Vegas, Nevada, where we're here live from the show floor, all four days of AWS re:Invent. I'm Savannah Peterson, joined with my co-host Dave Vellante. Dave, how you doing? >> Good. Beautiful and chilly Las Vegas. Can't wait to get back to New England where it's warm. >> Balmy, New England this time of year in December. Wow, Dave, that's a bold statement. I am super excited about the conversation that we're going to be having next. And, you know, I'm not even going to tee it up. I just want to bring Dilip on. Dilip, thank you so much for being here. How you doing? >> Savannah, Dave, thank you so much. >> Hey, Dilip. >> Excited to be here. >> It's joy to have you. So, you have been working at Amazon for about 20 years. >> Almost. Almost. >> Yes. >> Feels like 20, 19 1/2. >> Which is very exciting. You've had a lot of roles. I'm going to touch on some of them, but you just came over to AWS from the physical retail side. Talk to me about that. >> Yup, so I've been to Amazon for 19 1/2 years. Done pricing, supply chain. I was Jeff Bezos technical advisor for a couple years. >> Casual name drop. >> Casual name drop. >> Savannah: But a couple people here for that name before. >> Humble brag, hashtag. And then I, for the last several years, I was leading our physical retail initiatives. We just walk out Amazon One, bringing convenience to physical spaces. And then in August, with like as those things were getting a lot of traction and we were selling to third parties, we felt that it would be better suited in AWS. And, but along with that, there was also another trend that's been brewing, which is, you know, companies have loved building on AWS. They love the infrastructure services, but increasingly, they're also asking us to build applications that are higher up in the stack. Solving key, turnkey business problems. Just walk out Amazon One or examples of that, Amazon Connect. We just recently announced supply chain, so now there's a bevy interesting services all coming together, higher up in the stack for customers. So it's an exciting time. >> It was interesting that you're able to, you know, transfer from that retail. I mean, normally, in historically, if you're within an industry, retail, manufacturing, automotive whatever. You were kind as locked in a little bit. >> Dilip: Siloed a little bit. Yeah, yeah, yeah. >> Because they had their own, your own value chain. And I guess, data has changed that maybe, that you can traverse now. >> Yeah, if you think about the things that we did, even when we were in retail, the tenants was less about the industries and more about how can we bring convenience to physical spaces? The fact that you don't like to wait in line is no more like likely, you know, five years from now than it is today. So, it's a very durable tenant, but it's equally applicable whether you're in a grocery store, a convenience store, a stadium, an airport. So it actually transcends any, and like supply chain, think of supply chain. Supply chain isn't, you know, targeted to any one particular industry. It has broad applicability. So these things are very, you know, horizontally applicable. >> Anything that makes my life easier, I'm down. >> Savannah: We're all here for the easy button. We've been talking about it a bit this week. I'm in. And the retail store, I mean, I'm in San Francisco. I've had the experience of going through. Very interesting and seamless journey, honestly. It's very exciting. So tell us a little bit more about the applications group at AWS. >> Yup. So as I said, you know, we are, the applications group is a combination of several services. You know, we have communication developer services, which is the ability to add simple email service or video and embed video, voice chat using a chime SDK. In a higher up in the stack, we are taking care of things that IT administrators have to deal with where you can provision an entire desktop with the workspaces or provide a femoral access to it. And then as you go up even higher up in the stack, you have productivity applications like AWS Wicker, which we just did GA, you know, last week in AWS Clean Rooms which we announced as a service in preview. And then you have, you know, Connect, which is our cloud contact center, AWS supply chain. Just walk out Amazon One, it just feels like we're getting started. >> Just a couple things going on. >> So, clean rooms. Part of the governance play, part of data sharing. Can you explain, you know, we were talking offline, but I remember back in the disk drive days. We were in a clean room, they'd show you the clean room, you couldn't go near it unless you had a hazmat suit on. So now you're applying that to data. Explain that concept. >> Yeah, so the companies across, you know, financial services or healthcare, advertising, they all want to be able to combine and pull together data`sets with their partners in order to get these collaborative insights. The problem is either the data's fragmented, it's siloed or you have, you know, data governance issues that's preventing them from sharing. And the key requirement is that they want to be able to share this data without exposing any of the underlying data. Clean rooms are always emerged as a solution to that, but the problem with that is that they're hard to maintain. They're expensive. You have to write complex privacy queries. And if you make a mistake, you risk exposing the same data that you've been, you know, studiously trying to protect. >> Trying to protect. >> You know, take advertising as an industry, as an example. You know, advertisers care about, is my ad effective? But it turns out that if you're an advertiser and let's say you're a Nike or some other advertiser and your pop, you know, you place an ad on the website. Well, you want to stop showing the ad to people who have already purchased the product. However, people who purchased the product,- >> Savannah: It happens all the time. >> that purchasing data is not accessible to them easily. But if you could combine those insights, you know, the publishers benefit, advertisers benefits. So AWS Clean Rooms is that service that allows you very easily to be able to collaborate with a group of folks and then be able to gain these collaborative insights. >> And the consumers benefit. I mean, how many times you bought, you search it. >> It happens all the time. >> They know. And like, I just bought that guys, you know? >> Yeah, no, exactly. >> Four weeks. >> And I'm like, you don't need to serve me that, you know? And we understand the marketing backend. And it's just a waste of money and energy and resources. I mean, we're talking about sustainability as well. I don't think supply chain has ever had a hotter moment than it's had the last two and a half years. Tell me more about the announcement. >> Yup, so super excited about this. As you know, as you said, supply chains have always been very critical and very core for companies. The pandemic exacerbated it. So, ours way of sort of thinking about supply chains is to say that, you know, companies have taken, over the years many, like dozens, like millions and millions of dollars of investment in building their own supply chains. But the problem with supply chains is that the reason that they're not as functional as they could be is because of the lack of visibility. Because they're strung together very many disparate systems, that lack of visibility affects agility. And so, our approach in it was to say that, well, if we could have folks use their existing supply chain what can we do to improve the investment on the ROI of what they're getting? By creating a layer on top of it, that provides them that insights, connects all of these disparate data and then provides them insights to say, well, you know, here's where you overstock, here's where you under stock. You know, this is the, you know, the carbon emission impact of being able to transfer something. So like rather without requiring people to re-platform, what's the way that we can add value in it? And then also build upon Amazon's, you know, years of supply chain experience, to be able to build these predictive analytics for customers. >> So, that's a good, I like that you started with the why. >> Yes. >> Right now, what is it? It's an abstraction layer and then you're connecting into different data points. >> Yes, that's correct. >> Injecting ML. >> Feel like you can pick in, like if you think about supply chain, you can have warehouse management systems, order management systems. It could be in disparate things. We use ML to be able to bring all of this disparate data in and create our unified data lake. Once you have that unified data lake, you can then run an insights layer on top of it to be able to say, so that as the data changes, supply chain is not a static thing. Data's constantly changing. As the data's changing, the data lake now reflects the most up-to-date information. You can have alerts and insights set up on it to say that, what are the kinds of things that you're interested in? And then more importantly, supply chain and agility is about communication. In order to be able to make certain things happen, you need to be able to communicate, you need to make sure that everyone's on the same page. And we allow for a lot of the communication and collaboration tools to be built within this platform so that you're not necessarily leaving to go and toggle from one place to the other to solve your problems. >> And in the pie chart of how people spend their time, they're spending a lot less time communicating and being proactive. >> That's correct. >> And getting ahead of the curve. They're spending more time trying to figure out actually what's going on. >> Yes. >> And that's the problem that you're going to solve. >> Well, and it ensures that the customer at the other end of that supply chain experience is going to have their expectations managed in terms of when their good might get there or whatever's going to happen. >> Exactly. >> I feel like that expectation management has been such a big part of it. Okay, I just have to ask because I'm very curious. What was it like advising Jeff? >> Quite possibly the best job that I've ever had. You know, he's a fascinating individual. >> Did he pay you to say that? >> Nope. But I would've, like, I would've done it for like, it's remarkable seeing how he thinks and his approach to problem solving. It is, you know, you could be really tactical and go very deep. You could be extremely strategic. And to be able to sort of move effortlessly between those two is a unique skill. I learned a lot. >> Yeah, absolutely. So what made you want to evolve your career at Amazon after that? 'Cause I see on your LinkedIn, you say, it was the best job you ever had. With curiosity? >> Yeah, so one of the things, so the role is designed for you to be able to transition to something new. >> Savannah: Oh, cool. >> So after I finished that role, we were just getting into our foray with physical stores. And the idea between physical stores is that, you and I as consumers, we all have a lot of choices for physical stores. You know, there's a lot of options, there's a lot of formats. And so the last thing we wanted to do is come up with another me too offering. So, our approach was that what can we do to improve convenience in physical stores? That's what resulted in just walk out to Amazon Go. That's what resulted in Amazon One, which is another in a fast, convenient, contactless way to pay using the power of your palm. And now, what started in Amazon retail is now expanded to several third parties in, you know, stadiums, convention centers, airports. >> Airport, I just had, was in the Houston airport and got to do a humanless checkout. >> Dilip: Exactly. >> And actually in Honolulu a couple weeks ago as well too. Yeah, so we're going to see more and more of this. >> Yes. >> So what Amazon, I think has over a million employees. A lot of those are warehouse employees. But what advice would you give to somebody who's somewhere inside of Amazon, maybe they're on AWS, maybe they're Amazon. What advice would you give somebody inside that's maybe, you know, hey, I've been at this job for five, six years, three, four years, whatever it is. I want to do something else. And there's so much opportunity inside Amazon, right? What would you advise them? >> My single advice, which is actually transferable and I use it for myself is choose something that makes you a little uncomfortable. >> Dave: Get out of your comfort zone. >> It's like, you got to do that. It's like, it's not the easiest thing to hear, but it's also the most satisfying. Because almost every single time that I've done it for myself, it's resulted in like, you don't really know what the answer is. You don't really know exactly where you're going to end up, but the process and the journey through it, if you experience a little bit of discomfort constantly, it makes you non complacent. It makes you sort of not take the job, sort of in a stride. You have to be on it to do it. So that's the advice that I would give anyone. >> Yeah, that's good. So something that's maybe adjacent and maybe not completely foreign to you, but also something that, you know, you got to go dig a little bit and learn. >> You're planning a career change over here, Dave? >> No, I know a lot of people in Amazon are like, hey, I'm trying to figure out what I want to do next. I mean, I love it here. I live by the LPS, you know, but, and there's so much to choose from. >> It is, you know, when I joined in 2003, there were so many things that we were sort of doing today. None of those existed. It's a fascinating company. And the evolution, you could be in 20 different places and the breadth of the kinds of things that, you know, the Amazon experience provides is timeless. It's fascinating. >> And, you know, you look at a company like Amazon, and, you know, it's so amazing. You look at this ecosystem. I've been around- >> Even a show floor. >> I've been around a lot of time. And the show floor says it all. But I've seen a lot of, you know, waves. And each subsequent wave, you know, we always talk about how many companies were in the Fortune 1000 and aren't anymore. And, but the leaders, you know, survive and they thrive. And I think it's fascinating to try to better understand the culture that enables that. You know, you look at a company like Microsoft that was irrelevant and then came back. You know, even IBM was on death store for a while and they come back and so they. And so, but Amazon just feels, you know, at the moment you feel like, "Oh wow, nothing can stop this machine." 'Cause everybody's trying to disrupt Amazon and then, you know, only the paranoid survive, all that stuff. But it's not like, past is not prologue, all right? So that's why I asked these questions. And you just said that a lot of the services today that although the ideas didn't even exist, I mean, walkout. I mean, that's just amazing. >> I think one of the things that Amazon does really well culturally is that they create the single threaded leadership. They give people focus. If you have to get something done, you have to give people focus. You can't distract them with like seven different things and then say that, oh, by the way, your eighth job is to innovate. It just doesn't work that way. It's like it's hard. Like it can be- >> And where were the energy come from that? >> Exactly. And so giving people that single threaded focus is super important. >> Frank Slootman, the CEO of Snowflake, has a great quote. He wrote on his book. He said, "If you got 14 priorities, you got none." And he asks,- >> Well said. >> he challenges people. If you had to give up everything and do only one thing for the next 365 days, what would that be? It's a really hard question to answer. >> I feel like as we're around New Year's resolution times. I mean when we thinking about that, maybe we can all share our one thing. So, Dilip, you've been with the the applications team for five months. What's coming up next? >> Well, as I said, you know, it feels like it's still day one for applications. If you think about the things, the news that we introduced and the several services that we introduced, it has applicability across a variety of horizontal industries. But then we're also feeling that there's considerable vertical applications that can be built for specific things. Like, it could be in advertising, it could be in financial services, it could be in manufacturing. The opportunities are endless. I think the notion of people wanting applications higher up in the stack and a little more turnkey solutions is also, it's not new for us, but it's also new and creative too. You know, AWS has traditionally been doing. >> So again, this relates to what we were sort of talking about before. And maybe, this came from Jazzy or maybe it came from Bezos. But you hear a lot, it's okay to be misunderstood or if we were misunderstood for a long time. So when people hear up the stack, they think, when you think about apps, you know, in the last 10 years it was taking on-prem and bringing it into the cloud. Okay, you saw that with CREM, email, CRM, service management, you know, data warehouses, et cetera. Amazon is thinking about this in a different way. It's like you're looking at the world saying, okay, how can we improve whatever? Workflows, people's lives, doing something that's not been done before? And that seems to be the kind of applications that you guys are thinking about building. >> Yeah. >> And that's unique. It's not just, okay, we're going to take something on-prem put it in the cloud. Been there, done that. That S-curve is sort of flattening now. But there's a new S-curve which is completely new workflows and innovations and processes that we really haven't thought about yet. Or you're thinking about, I presume. >> Yeah. Having said that, I'd also like to sort of remind folks that when you consider the, you know, the entire spend, the portion of workloads that are running in the cloud is a teeny tiny fraction. It's like less than 5%, like 4% or something like that. So it's a very, there's still plenty of things that can sort of move to the cloud. But you're right that there is another trend of where in the stack and the types of applications that you can provide as well. >> Yeah, new innovation that haven't well thought of yet. >> So, Dilip, we have a new tradition here on theCUBE at re:Invent. Where we're looking for your 30 minute Instagram reel, your hot take, biggest key theme, either for you, your team, or just general vibe from the show. >> General vibe from the show. Well, 19 1/2 years at Amazon, this is actually my first re:Invent, believe it or not. This is my, as a AWS employee now, as re:Invent with like launching services. So that's the first. I've been to re:Invent before, but as an attendee rather than as a person who's, you know, a contributing number of the workforce. >> Working actually? >> If you will. >> Actually doing your job. >> And so I'm just amazed at the energy and the breadth. And the, you know, from the partners to the customers to the diversity of people who are coming here from everywhere. I had meetings from people in New Zealand. Like, you know, the UK, like customers are coming at us from like very many different places. And it's fascinating for me to see. It's new for me as well given, you know, some of my past experience. But this is a, it's been a blast. >> People are pumped. >> People are pumped. >> They can't believe the booth traffic. Not only that quality. >> Right. All of our guests have talked about that. >> Like, yeah, you know, we're going to throw half of these leads away, but they're saying no, I'm having like really substantive conversations with business people. This is, I think, my 10th re:Invent. And the first one was mostly developers. And I'm like, what are you talking about? And, you know, so. Now it's a lot more business people, a lot of developers too. >> Yeah. >> It's just. >> The community really makes it. Dilip, thank you so much for joining us today on theCube. >> Thank you for having me. >> You're fantastic. I could ask you a million questions. Be sure and tell Jeff that we said hi. >> Will do. >> Savannah: Next time you guys are hanging out. And thank all of you. >> You want to go into space? >> Yeah. Yes, yes, absolutely. I'm perhaps the most space obsessed on the show. And with that, we will continue our out of this world coverage shortly from fabulous Las Vegas where we are at AWS re:Invent. It is day four with Dave Vellante. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

>>Hey everybody. Welcome back. Good afternoon. Lisa Martin here with John Feer live in Detroit, Michigan. We are at Coon Cloud Native Con 2020s North America. John Thank is who. This is nearing the end of our second day of coverage and one of the things that has been breaking all day on this show is news. News. We have more news to >>Break next. Yeah, this next segment is a company we've been following. They got some news we're gonna get into. Managing Kubernetes life cycle has been a huge challenge when you've got large organizations, whether you're spinning up and scaling scale is the big story. Kubernetes is the center of the conversation. This next segment's gonna be great. It >>Is. We've got two guests from Specter Cloud here. Please welcome. It's CEO Chenery Fu and co-founder and it's c g a co-founder Sta Mallek. Guys, great to have you on the program. Thank >>You for having us. My pleasure. >>So Timary, what's going on? What's the big news? >>Yeah, so we just announced our Palace three this morning. So we add a bunch, a new functionality. So first of all we have a Nest cluster. So enable enterprise to easily provide Kubernete service even on top of their existing clusters. And secondly, we also support seamlessly migration for their existing cluster. We enable them to be able to migrate their cluster into our CNC for upstream Kubernete distro called Pallet extended Kubernetes, GX K without any downtime. And lastly, we also add a lot of focus on developer experience. Those additional capability enable developer to easily onboard and and deploy the application for. They have test and troubleshooting without, they have to have a steep Kubernetes lending curve. >>So big breaking news this morning, pallet 3.0. So you got the, you got the product. This is a big theme here. Developer productivity, ease of use is the top story here. As developers are gonna increase their code velocity cuz they're under a lot of pressure. This infrastructure's getting smarter. This is a big part of managing it. So the toil is now moving to the ops. Steves are now dev teams. Security, you gotta enable faster deployment of apps and code. This is what you guys solve while you getting this right. Is that, take us through that specific value proposition. What's the, what are the key things on in this news release? Yeah, >>You're exactly right. Right. So we basically provide our solution to platform engineering ship so that they can use our platform to enable Kubernetes service to serve their developers and their application ship. And then in the meantime, the developers will be able to easily use Kubernetes or without, They have to learn a lot of what Kubernetes specific things like. So maybe you can get in some >>Detail. Yeah. And absolutely the detail about it is there's a big separation between what operations team does and the development teams that are using the actual capabilities. The development teams don't necessarily to know the internals of Kubernetes. There's so much complexity when it comes, comes into it. How do I do things like deployment pause manifests just too much. So what our platform does, it makes it really simple for them to say, I have a containerized application, I wanna be able to model it. It's a really simple profile and from there, being able to say, I have a database service. I wanna attach to it. I have a specific service. Go run it behind the scenes. Does it run inside of a Nest cluster? Which we'll talk into a little bit. Does it run into a host cluster? Those are happen transparently for >>The developer. You know what I love about this? What you guys are doing in the news, it really points out what I love about DevOps. Because cloud, let's face a cloud early adopters, we're all the hardcore cloud folks as it goes mainstream. With Kubernetes, you start to see like words like platform engineering. I mean I love that term. That means as a platform, it's been around for a while. For people who are building their own stuff, that means it's gonna scale and enable people to enable value, build on top of it, move faster. This platform engineering is becoming now standard in enterprises. It wasn't like that before. What's your eyes reactions that, How do you see that evolving faster? Or do you believe that or what's your take on >>It? Yeah, so I think it's starting from the DevOps op team, right? That every application team, they all try to deploy and manage their application under their own ING infrastructure. But very soon all these each application team, they start realize they have to repeatedly do the same thing. So these will need to have a platform engineering team to basically bring some of common practice to >>That. >>And some people call them SREs like and that's really platform >>Engineering. It is, it is. I mean, you think about like Esther ability to deploy your applications at scale and monitoring and observability. I think what platform engineering does is codify all those best practices. Everything when it comes about how you monitor the actual applications. How do you do c i CD your backups? Instead of not having every single individual development team figuring how to do it themselves. Platform engineer is saying, why don't we actually build policy that we can provide as a service to different development teams so that they can operate their own applications at scale. >>So launching Pellet 3.0 today, you also had a launch in September, so just a few weeks ago. Talk about what these two announcements mean from Specter Cloud's perspective in terms of proof points, what you're delivering to the end users and the value that they're getting from that. >>Yeah, so our goal is really to help enterprise to deploy and around Kubernetes anywhere, right? Whether it's in cloud data center or even at Edge locations. So in September we also announce our HV two capabilities, which enable very easy deployment of Edge Kubernetes, right at at at any any location, like a retail stores restaurant, so on and so forth. So as you know, at Edge location, there's no cloud endpoint there. It's not easy to directly deploy and manage Kubernetes. And also at Edge location there's not, it's not as secure as as cloud or data center environment. So how to make the end to end system more secure, right? That it's temper proof, that is also very, very important. >>Right. Great, great take there. Thanks for explaining that. I gotta ask cuz I'm curious, what's the secret sauce? Is it nested clusters? What's, what's the core under the hood here on 3.0 that people should know about it's news? It's what's, what's the, what's that post important >>To? To be honest, it's about enabling developer velocity. Now how do you enable developer velocity? It's gonna be able for them to think about deploying applications without worrying about Kubernetes being able to build this application profiles. This NEA cluster that we're talking about enables them, they get access to it in complete cluster within seconds. They're essentially having access to be able to add any operations, any capabilities without having the ability to provision a cluster on inside of infrastructure. Whether it's Amazon, Google, or OnPrem. >>So, and you get the dev engine too, right? That that, that's a self-service provisioning in for environments. Is that, Yeah, >>So the dev engine itself are the capabilities that we offer to developers so that they can build these application profiles. What the application profiles, again they define aspects about, my application is gonna be a container, it's gonna be a database service, it's gonna be a helm chart. They define that entire structure inside of it. From there they can choose to say, I wanna deploy this. The target environment, whether it becomes an actual host cluster or a cluster itself is irrelevant to them. For them it's complete transparent. >>So transparency, enabling developer velocity. What's been some of the feedback so far? >>Oh, all developer love that. And also same for all >>The ops team. If it's easy and goods faster and the steps >>Win-win team. Yeah, Ops team, they need a consistency. They need a governance, they need visibility, but in the meantime, developers, they need the flexibility then theys or without a steep learning curve. So this really, >>So So I hear a lot of people say, I got a lot of sprawl, cluster sprawl. Yeah, let's get outta hand does, let's solve that. How do you guys solve that problem? Yeah, >>So the Neste cluster is a profit answer for that. So before you nest cluster, for a lot of enterprise to serving developers, they have to either create a very large TED cluster and then isolated by namespace, which not ideal for a lot of situation because name stay namespace is not a hard isolation and also a lot of global resource like CID and operator does not work in space. But the other way is you give each developer a separate, a separate ADE cluster, but that very quickly become too costly. Cause not every developer is working for four, seven, and half of the time your, your cluster is is a sit there idol and that costs a lot of money. So you cluster, you'll be able to basically do all these inside the your wholesale cluster, bring the >>Efficiency there. That is huge. Yeah. Saves a lot of time. Reduces the steps it takes. So I take, take a minute, my last question to you to explain what's in it for the developer, if they work with Spec Cloud, what is your value? What's the pitch? Not the sales pitch, but like what's the value pitch that >>You give them? Yeah, yeah. And the value for us is again, develop their number of different services and teams people are using today are so many, there are so many different languages or so many different libraries there so many different capabilities. It's too hard for developers to have to understand not only the internal development tools, but also the Kubernetes, the containers of technologies. There's too much for it. Our value prop is making it really easy for them to get access to all these different integrations and tooling without having to learn it. Right? And then being able to very easily say, I wanna deploy this into a cluster. Again, whether it's a Nest cluster or a host cluster. But the next layer on top of that is how do we also share those abilities with other teams. If I build my application profile, I'm developing an application, I should be able to share it with my team members. But Henry saying, Hey Tanner, why don't you also take a look at my app profile and let's build and collaborate together on that. So it's about collaboration and be able to move >>Really fast. I mean, more develops gotta be more productive. That's number one. Number one hit here. Great job. >>Exactly. Last question before we run out Time. Is this ga now? Can folks get their hands on it where >>Yes. Yeah. It is GA and available both as a, as a SaaS and also the store. >>Awesome guys, thank you so much for joining us. Congratulations on the announcement and the momentum that Specter Cloud is empowering itself with. We appreciate your insights on your time. >>Thank you. Thank you so much. Right, pleasure. >>Thanks for having us. For our guest and John Furrier, Lisa Martin here live in Michigan at Co con Cloud native PON 22. Our next guests join us in just a minute. So stick around.

(upbeat music) >> Hey guys, welcome back to the show floor of KubeCon + CloudNativeCon '22 North America from Detroit, Michigan. Lisa Martin here with John Furrier. This is day one, John at theCUBE's coverage. >> CUBE's coverage. >> theCUBE's coverage of KubeCon. Try saying that five times fast. Day one, we have three wall-to-wall days. We've been talking about Kubernetes, containers, adoption, cloud adoption, app modernization all morning. We can't talk about those things without addressing security. >> Yeah, this segment we're going to hear container and Kubernetes security for modern application 'cause the enterprise are moving there. And this segment with Red Hat's going to be important because they are the leader in the enterprise when it comes to open source in Linux. So this is going to be a very fun segment. >> Very fun segment. Two guests from Red Hat join us. Please welcome Doron Caspin, Senior Principal Product Manager at Red Hat. Michael Foster joins us as well, Principal Product Marketing Manager and StackRox Community Lead at Red Hat. Guys, great to have you on the program. >> Thanks for having us. >> Thank you for having us. >> It's awesome. So Michael StackRox acquisition's been about a year. You got some news? >> Yeah, 18 months. >> Unpack that for us. >> It's been 18 months, yeah. So StackRox in 2017, originally we shifted to be the Kubernetes-native security platform. That was our goal, that was our vision. Red Hat obviously saw a lot of powerful, let's say, mission statement in that, and they bought us in 2021. Pre-acquisition we were looking to create a cloud service. Originally we ran on Kubernetes platforms, we had an operator and things like that. Now we are looking to basically bring customers in into our service preview for ACS as a cloud service. That's very exciting. Security conversation is top notch right now. It's an all time high. You can't go with anywhere without talking about security. And specifically in the code, we were talking before we came on camera, the software supply chain is real. It's not just about verification. Where do you guys see the challenges right now? Containers having, even scanning them is not good enough. First of all, you got to scan them and that may not be good enough. Where's the security challenges and where's the opportunity? >> I think a little bit of it is a new way of thinking. The speed of security is actually does make you secure. We want to keep our images up and fresh and updated and we also want to make sure that we're keeping the open source and the different images that we're bringing in secure. Doron, I know you have some things to say about that too. He's been working tirelessly on the cloud service. >> Yeah, I think that one thing, you need to trust your sources. Even if in the open source world, you don't want to copy paste libraries from the web. And most of our customers using third party vendors and getting images from different location, we need to trust our sources and we have a really good, even if you have really good scanning solution, you not always can trust it. You need to have a good solution for that. >> And you guys are having news, you're announcing the Red Hat Advanced Cluster Security Cloud Service. >> Yes. >> What is that? >> So we took StackRox and we took the opportunity to make it as a cloud services so customer can consume the product as a cloud services as a start offering and customer can buy it through for Amazon Marketplace and in the future Azure Marketplace. So customer can use it for the AKS and EKS and AKS and also of course OpenShift. So we are not specifically for OpenShift. We're not just OpenShift. We also provide support for EKS and AKS. So we provided the capability to secure the whole cloud posture. We know customer are not only OpenShift or not only EKS. We have both. We have free cloud or full cloud. So we have open. >> So it's not just OpenShift, it's Kubernetes, environments, all together. >> Doron: All together, yeah. >> Lisa: Meeting customers where they are. >> Yeah, exactly. And we focus on, we are not trying to boil the ocean or solve the whole cloud security posture. We try to solve the Kubernetes security cluster. It's very unique and very need unique solution for that. It's not just added value in our cloud security solution. We think it's something special for Kubernetes and this is what Red that is aiming to. To solve this issue. >> And the ACS platform really doesn't change at all. It's just how they're consuming it. It's a lot quicker in the cloud. Time to value is right there. As soon as you start up a Kubernetes cluster, you can get started with ACS cloud service and get going really quickly. >> I'm going to ask you guys a very simple question, but I heard it in the bar in the lobby last night. Practitioners talking and they were excited about the Red Hat opportunity. They actually asked a question, where do I go and get some free Red Hat to test some Kubernetes out and run helm or whatever. They want to play around. And do you guys have a program for someone to get start for free? >> Yeah, so the cloud service specifically, we're going to service preview. So if people sign up, they'll be able to test it out and give us feedback. That's what we're looking for. >> John: Is that a Sandbox or is that going to be in the cloud? >> They can run it in their own environment. So they can sign up. >> John: Free. >> Doron: Yeah, free. >> For the service preview. All we're asking for is for customer feedback. And I know it's actually getting busy there. It's starting December. So the quicker people are, the better. >> So my friend at the lobby I was talking to, I told you it was free. I gave you the sandbox, but check out your cloud too. >> And we also have the open source version so you can download it and use it. >> Yeah, people want to know how to get involved. I'm getting a lot more folks coming to Red Hat from the open source side that want to get their feet wet. That's been a lot of people rarely interested. That's a real testament to the product leadership. Congratulations. >> Yeah, thank you. >> So what are the key challenges that you have on your roadmap right now? You got the products out there, what's the current stake? Can you scope the adoption? Can you share where we're at? What people are doing specifically and the real challenges? >> I think one of the biggest challenges is talking with customers with a slightly, I don't want to say outdated, but an older approach to security. You hear things like malware pop up and it's like, well, really what we should be doing is keeping things into low and medium vulnerabilities, looking at the configuration, managing risk accordingly. Having disparate security tools or different teams doing various things, it's really hard to get a security picture of what's going on in the cluster. That's some of the biggest challenges that we talk with customers about. >> And in terms of resolving those challenges, you mentioned malware, we talk about ransomware. It's a household word these days. It's no longer, are we going to get hit? It's when? It's what's the severity? It's how often? How are you guys helping customers to dial down some of the risk that's inherent and only growing these days? >> Yeah, risk, it's a tough word to generalize, but our whole goal is to give you as much security information in a way that's consumable so that you can evaluate your risk, set policies, and then enforce them early on in the cluster or early on in the development pipeline so that your developers get the security information they need, hopefully asynchronously. That's the best way to do it. It's nice and quick, but yeah. I don't know if Doron you want to add to that? >> Yeah, so I think, yeah, we know that ransomware, again, it's a big world for everyone and we understand the area of the boundaries where we want to, what we want to protect. And we think it's about policies and where we enforce it. So, and if you can enforce it on, we know that as we discussed before that you can scan the image, but we never know what is in it until you really run it. So one of the thing that we we provide is runtime scanning. So you can scan and you can have policy in runtime. So enforce things in runtime. But even if one image got in a way and get to your cluster and run on somewhere, we can stop it in runtime. >> Yeah. And even with the runtime enforcement, the biggest thing we have to educate customers on is that's the last-ditch effort. We want to get these security controls as early as possible. That's where the value's going to be. So we don't want to be blocking things from getting to staging six weeks after developers have been working on a project. >> I want to get you guys thoughts on developer productivity. Had Docker CEO on earlier and since then I had a couple people messaging me. Love the vision of Docker, but Docker Hub has some legacy and it might not, has does something kind of adoption that some people think it does. Are people moving 'cause there times they want to have these their own places? No one place or maybe there is, or how do you guys see the movement of say Docker Hub to just using containers? I don't need to be Docker Hub. What's the vis-a-vis competition? >> I mean working with open source with Red Hat, you have to meet the developers where they are. If your tool isn't cutting it for developers, they're going to find a new tool and really they're the engine, the growth engine of a lot of these technologies. So again, if Docker, I don't want to speak about Docker or what they're doing specifically, but I know that they pretty much kicked off the container revolution and got this whole thing started. >> A lot of people are using your environment too. We're hearing a lot of uptake on the Red Hat side too. So, this is open source help, it all sorts stuff out in the end, like you said, but you guys are getting a lot of traction there. Can you share what's happening there? >> I think one of the biggest things from a developer experience that I've seen is the universal base image that people are using. I can speak from a security standpoint, it's awesome that you have a base image where you can make one change or one issue and it can impact a lot of different applications. That's one of the big benefits that I see in adoption. >> What are some of the business, I'm curious what some of the business outcomes are. You talked about faster time to value obviously being able to get security shifted left and from a control perspective. but what are some of the, if I'm a business, if I'm a telco or a healthcare organization or a financial organization, what are some of the top line benefits that this can bubble up to impact? >> I mean for me, with those two providers, compliance is a massive one. And just having an overall look at what's going on in your clusters, in your environments so that when audit time comes, you're prepared. You can get through that extremely quickly. And then as well, when something inevitably does happen, you can get a good image of all of like, let's say a Log4Shell happens, you know exactly what clusters are affected. The triage time is a lot quicker. Developers can get back to developing and then yeah, you can get through it. >> One thing that we see that customers compliance is huge. >> Yes. And we don't want to, the old way was that, okay, I will provision a cluster and I will do scans and find things, but I need to do for PCI DSS for example. Today the customer want to provision in advance a PCI DSS cluster. So you need to do the compliance before you provision the cluster and make all the configuration already baked for PCI DSS or HIPAA compliance or FedRAMP. And this is where we try to use our compliance, we have tools for compliance today on OpenShift and other clusters and other distribution, but you can do this in advance before you even provision the cluster. And we also have tools to enforce it after that, after your provision, but you have to do it again before and after to make it more feasible. >> Advanced cluster management and the compliance operator really help with that. That's why OpenShift Platform Plus as a bundle is so popular. Just being able to know that when a cluster gets provision, it's going to be in compliance with whatever the healthcare provider is using. And then you can automatically have ACS as well pop up so you know exactly what applications are running, you know it's in compliance. I mean that's the speed. >> You mentioned the word operator, I get triggering word now for me because operator role is changing significantly on this next wave coming because of the automation. They're operating, but they're also devs too. They're developing and composing. It's almost like a dashboard, Lego blocks. The operator's not just manually racking and stacking like the old days, I'm oversimplifying it, but the new operators running stuff, they got observability, they got coding, their servicing policy. There's a lot going on. There's a lot of knobs. Is it going to get simpler? How do you guys see the org structures changing to fill the gap on what should be a very simple, turn some knobs, operate at scale? >> Well, when StackRox originally got acquired, one of the first things we did was put ACS into an operator and it actually made the application life cycle so much easier. It was very easy in the console to go and say, Hey yeah, I want ACS my cluster, click it. It would get provisioned. New clusters would get provisioned automatically. So underneath it might get more complicated. But in terms of the application lifecycle, operators make things so much easier. >> And of course I saw, I was lucky enough with Lisa to see Project Wisdom in AnsibleFest. You going to say, Hey, Red Hat, spin up the clusters and just magically will be voice activated. Starting to see AI come in. So again, operations operator is got to dev vibe and an SRE vibe, but it's not that direct. Something's happening there. We're trying to put our finger on. What do you guys think is happening? What's the real? What's the action? What's transforming? >> That's a good question. I think in general, things just move to the developers all the time. I mean, we talk about shift left security, everything's always going that way. Developers how they're handing everything. I'm not sure exactly. Doron, do you have any thoughts on that. >> Doron, what's your reaction? You can just, it's okay, say what you want. >> So I spoke with one of our customers yesterday and they say that in the last years, we developed tons of code just to operate their infrastructure. That if developers, so five or six years ago when a developer wanted VM, it will take him a week to get a VM because they need all their approval and someone need to actually provision this VM on VMware. And today they automate all the way end-to-end and it take two minutes to get a VM for developer. So operators are becoming developers as you said, and they develop code and they make the infrastructure as code and infrastructure as operator to make it more easy for the business to run. >> And then also if you add in DataOps, AIOps, DataOps, Security Ops, that's the new IT. It seems to be the new IT is the stuff that's scaling, a lot of data's coming in, you got security. So all that's got to be brought in. How do you guys view that into the equation? >> Oh, I mean you become big generalists. I think there's a reason why those cloud security or cloud professional certificates are becoming so popular. You have to know a lot about all the different applications, be able to code it, automate it, like you said, hopefully everything as code. And then it also makes it easy for security tools to come in and look and examine where the vulnerabilities are when those things are as code. So because you're going and developing all this automation, you do become, let's say a generalist. >> We've been hearing on theCUBE here and we've been hearing the industry, burnout, associated with security professionals and some DataOps because the tsunami of data, tsunami of breaches, a lot of engineers getting called in the middle of the night. So that's not automated. So this got to get solved quickly, scaled up quickly. >> Yes. There's two part question there. I think in terms of the burnout aspect, you better send some love to your security team because they only get called when things get broken and when they're doing a great job you never hear about them. So I think that's one of the things, it's a thankless profession. From the second part, if you have the right tools in place so that when something does hit the fan and does break, then you can make an automated or a specific decision upstream to change that, then things become easy. It's when the tools aren't in place and you have desperate environments so that when a Log4Shell or something like that comes in, you're scrambling trying to figure out what clusters are where and where you're impacted. >> Point of attack, remediate fast. That seems to be the new move. >> Yeah. And you do need to know exactly what's going on in your clusters and how to remediate it quickly, how to get the most impact with one change. >> And that makes sense. The service area is expanding. More things are being pushed. So things will, whether it's a zero day vulnerability or just attack. >> Just mix, yeah. Customer automate their all of things, but it's good and bad. Some customer told us they, I think Spotify lost the whole a full zone because of one mistake of a customer because they automate everything and you make one mistake. >> It scale the failure really. >> Exactly. Scaled the failure really fast. >> That was actually few contact I think four years ago. They talked about it. It was a great learning experience. >> It worked double edge sword there. >> Yeah. So definitely we need to, again, scale automation, test automation way too, you need to hold the drills around data. >> Yeah, you have to know the impact. There's a lot of talk in the security space about what you can and can't automate. And by default when you install ACS, everything is non-enforced. You have to have an admission control. >> How are you guys seeing your customers? Obviously Red Hat's got a great customer base. How are they adopting to the managed service wave that's coming? People are liking the managed services now because they maybe have skills gap issues. So managed service is becoming a big part of the portfolio. What's your guys' take on the managed services piece? >> It's just time to value. You're developing a new application, you need to get it out there quick. If somebody, your competitor gets out there a month before you do, that's a huge market advantage. >> So you care how you got there. >> Exactly. And so we've had so much Kubernetes expertise over the last 10 or so, 10 plus year or well, Kubernetes for seven plus years at Red Hat, that why wouldn't you leverage that knowledge internally so you can get your application. >> Why change your toolchain and your workflows go faster and take advantage of the managed service because it's just about getting from point A to point B. >> Exactly. >> Well, in time to value is, you mentioned that it's not a trivial term, it's not a marketing term. There's a lot of impact that can be made. Organizations that can move faster, that can iterate faster, develop what their customers are looking for so that they have that competitive advantage. It's definitely not something that's trivial. >> Yeah. And working in marketing, whenever you get that new feature out and I can go and chat about it online, it's always awesome. You always get customers interests. >> Pushing new code, being secure. What's next for you guys? What's on the agenda? What's around the corner? We'll see a lot of Red Hat at re:Invent. Obviously your relationship with AWS as strong as a company. Multi-cloud is here. Supercloud as we've been saying. Supercloud is a thing. What's next for you guys? >> So we launch the cloud services and the idea that we will get feedback from customers. We are not going GA. We're not going to sell it for now. We want to get customers, we want to get feedback to make the product as best what we can sell and best we can give for our customers and get feedback. And when we go GA and we start selling this product, we will get the best product in the market. So this is our goal. We want to get the customer in the loop and get as much as feedback as we can. And also we working very closely with our customers, our existing customers to announce the product to add more and more features what the customer needs. It's all about supply chain. I don't like it, but we have to say, it's all about making things more automated and make things more easy for our customer to use to have security in the Kubernetes environment. >> So where can your customers go? Clearly, you've made a big impact on our viewers with your conversation today. Where are they going to be able to go to get their hands on the release? >> So you can find it on online. We have a website to sign up for this program. It's on my blog. We have a blog out there for ACS cloud services. You can just go there, sign up, and we will contact the customer. >> Yeah. And there's another way, if you ever want to get your hands on it and you can do it for free, Open Source StackRox. The product is open source completely. And I would love feedback in Slack channel. It's one of the, we also get a ton of feedback from people who aren't actually paying customers and they contribute upstream. So that's an awesome way to get started. But like you said, you go to, if you search ACS cloud service and service preview. Don't have to be a Red Hat customer. Just if you're running a CNCF compliant Kubernetes version. we'd love to hear from you. >> All open source, all out in the open. >> Yep. >> Getting it available to the customers, the non-customers, they hopefully pending customers. Guys, thank you so much for joining John and me talking about the new release, the evolution of StackRox in the last season of 18 months. Lot of good stuff here. I think you've done a great job of getting the audience excited about what you're releasing. Thank you for your time. >> Thank you. >> Thank you. >> For our guest and for John Furrier, Lisa Martin here in Detroit, KubeCon + CloudNativeCon North America. Coming to you live, we'll be back with our next guest in just a minute. (gentle music)

(gentle music) >> Okay, we're back with the hybrid cloud power panel. I'm Dave Vellante, and with me Eric Lockard who is the Corporate Vice President of Microsoft Azure Specialized. Thomas Cornely is the Senior Vice President of Products at Nutanix and Indu Keri, who's the Senior Vice President of Engineering, NCI and NC2 at Nutanix. Gentlemen, welcome to The Cube. Thanks for coming on. >> It's good to be here. >> Thanks for having us. >> Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I want to just put everything in the public cloud. >> Yeah, well, I mean the public cloud has a bunch of inherent advantages, right? I mean it's, it has effectively infinite capacity the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a trend towards public cloud, but you know not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise but also take advantage of the cloud for bursting, originality or expansion especially coming out of the pandemic. We saw a lot of this from work from home and and video conferencing and so on driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >> Yeah, makes sense. I want to, Thomas, if you could talk a little bit I don't want to inundate people with the acronyms, but the Nutanix Cloud clusters on Azure, what is that? What problems does it solve? Give us some color there, please. >> Yeah, so, you know, cloud clusters on Azure which we actually call NC2 to make it simple. And so NC2 on Azure is really our solutions for hybrid cloud, right? And you think about hybrid cloud highly desirable, customers want it. They, they know this is the right way to do it for them given that they want to have workloads on premises at the edge, any public clouds, but it's complicated. It's hard to do, right? And the first thing that you deal with is just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise. And dealing with different portals, networking get complicated, security gets complicated. And so you heard me say this already, you know hybrid can be complex. And so what we've done we then NC2 Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as-is to any Azure region where NC2 is available. Once it's running there you keep the same operating model, right? And that's, so that actually super valuable to actually go and do this in a simple fashion. Do it faster, and basically do hybrid in a more (indistinct) fashion know for all your applications. And that's what's really special about NC2 today. >> So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly it's an identical experience. Did I get that right? >> This is the key for us, right? When you think you're sitting on premises you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model to workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster, deploy in NC2 Azure, it's going to look like the same cluster that you might be running at the edge or in your own data center, using the same tools, using the same admin constructs to go protect the workloads make them highly available do disaster recovery or secure them. All of that becomes the same. But now you are in Azure, and this is what we've spent a lot of time working with Eric and his teams on is you actually have access now to all of those suites of Azure services (indistinct) from those workloads. So now you get the best of both world, you know and we bridge them together and you to get seamless access of those services between what you get from Nutanix, what you get from Azure. >> Yeah. And as you alluded to this is traditionally been non-trivial and people have been looking forward to this for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this is not just a press release, this is, or a PowerPoint you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >> So let me start with what's unique about this. And I think Thomas and Eric both did a really good job of describing that. The best way to think about what we are delivering jointly with Microsoft is that it speeds up the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC2 allows you to flip that on its head and say that take your application as-is and then lift and shift it to the public cloud at which point you start the refactor journey. And one of the things that you have done really well with the NC2 on Azure is that NC2 is not something that sits by Azure side. It's fully integrated into the Azure fabric especially the software-defined networking, SDN piece. What that means is that, you know you don't have to worry about connecting your NC2 cluster to Azure to some sort of a network pipe. You have direct access to the Azure services from the same application that's now running on an NC2 cluster. And that makes your refactor journey so much easier. Your management claim looks the same, your high performance notes let the NVMe notes they look the same. And really, I mean, other than the fact that you're doing something in the public cloud all the Nutanix goodness that you're used to continue to receive that. There is a lot of secret sauce that we have had to develop as part of this journey. But if we had to pick one that really stands out it is how do we take the complexity, the network complexity offer public cloud, in this case Azure and make it as familiar to Nutanix's customers as the VPC, the virtual private cloud (indistinct) that allows them to really think of their on-prem networking and the public cloud networking in very similar terms. There's a lot more that's done on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I grew up that, you know if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third, do a cloud development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team and we're very grateful for their support. >> I need NC2 for my house. I live in a house that was built and it's 1687 and we connect all the new and it is a bolt on, but the secret sauce, I mean there's, there's a lot there but is it a (indistinct) layer. You didn't just wrap it in a container and shove it into the public cloud. You've done more than that, I'm inferring. >> You know, the, it's actually an infrastructure layer offering on top of (indistinct). You can obviously run various types of platform services. So for example, down the road if you have a containerized application you'll actually be able to take it from on prem and run it on NC2. But the NC2 offer itself, the NC2 offering itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know define Nutanix to begin with the hypervisor that you're used to the network constructs that you're used to light micro segmentation for security purposes, all of them are available to you on NC2 in Azure the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier that makes your management challenge easier that makes it much easier for an application person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they've done that much faster than they would be able to otherwise. >> Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are that are going to emerge for this solution? >> Yeah, I mean we've, you know we've had a solution for a while and you know this is now new on Azure is going to extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us the first one you know, talks about it is a migration. You know, we see customers on that cloud journey. They're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same culture that were around the application and we make them available now in the Azure region. You can do this for any applications. There's no change to the application, no networking change the same IP constraint will work the same whether you're running on premises or in Azure. The app stays exactly the same manage the same way, protected the same way. So that's a big one. And you know, the type of drivers for (indistinct) maybe I want to go do something different or I want to go and shut down the location on premises I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which we're doing on premises IT disaster recovery and something that we refer to as Elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads. But I think that site sitting in Azure as a small site just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment feed over workloads, run them with performance potentially fill them back to on premises, and then shrink back the environment in Azure to again optimize cost and take advantage of the elasticity that you get from public cloud models. Then the last one, building on top of that is just the fact that you cannot get bursting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workloads and now basically get combined desktops running on premises desktops running on NC2 on Azure same desktop images, same management, same services and do that as a burst use case during say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look I want to go to desktop as a service, but right now I don't want to refactor the entire application stack. I just want to be able to get access to resources on demand in the right place at the right time. >> Makes sense. I mean this is really all about supporting customer's, digital transformations. We all talk about how that was accelerated during the pandemic and but the cloud is a fundamental component of the digital transformations generic. You, you guys have obviously made a commitment between Microsoft and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >> Well, the ultimate vision is really twofold, I think. The one is to, you know first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their administrators and or to obviate their investment that they already have and platforms like Nutanix. And so the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and capabilities of Azure. You know, second is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on-premise Nutanix clusters and bringing the capabilities that provides to the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from two directions. One is from kind of traditional on-premise up into the cloud, and then the second is kind of from the cloud leveraging the investment customers have in on-premise HCI. >> Got it. Thank you. Okay, last question. Maybe each of you could just give us one key takeaway for our audience today. Maybe we start with Thomas and then Indu and then Eric you can bring us home. >> Sure. So the key takeaway is, you know, cloud customers on Azure is now GA you know, this is something that we've had tremendous demand from our customers both from the Microsoft side and the Nutanix side going back years literally, right? People have been wanting to go and see this this is now live GA open for business and you know we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >> Great, Indu. >> In our day, in a prior life about seven or eight years ago, I was a part of a team that took a popular text preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million dollars. And if we had NC2 then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >> Okay. Eric, bring us home please. >> Yeah, I'll just point out that, this is not something that's just bought on or something we started yesterday. This is something the teams both companies have been working on together for years really. And it's a way of deeply integrating Nutanix into the Azure Cloud. And with the ultimate goal of again providing cloud capabilities to the Nutanix customer in a way that they can, you know take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for customers who have significant investments in Nutanix clusters on premise. >> Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >> Thank you. >> Thank you. >> Okay. Keep it right there. You're watching accelerate hybrid cloud, that journey with Nutanix and Microsoft technology on The Cube, your leader in enterprise and emerging tech coverage. (gentle music)

>>Hey everyone. Welcome back to the Cube's day one coverage of VMware Explorer, 2022 live from San Francisco. I'm Lisa Martin, and I'm basically sitting with the cloud. I got a power panel here with me. You are not gonna wanna miss the segment, please. Welcome, nor Barage I probably did. I do. Okay on that. Great, thank you. VP and GM of cloud solutions at VMware. Thanks for joining us. Field brother tune is back our alumni VP solutions and alliances at NetApp bill. Great to see you in person. Thank you. And Steve Jones, GM SAP, and VMware cloud at Amazon. Welcome guys. Thank you. Pleasure. So we got VMware, NetApp and Amazon. I was telling Phil before we went live, I was snooping around on the NetApp website the other day. And I saw a tagline that said two is the company three is a cloud, but I get to sit with the cloud. This is fantastic. Nora, talk to us about the big news that came out just about 24 hours ago. These three powerhouse, we >>Were super excited. We are celebrating five years of VMware cloud this week. And with three powerhouses here, we're announcing the general availability of VMware cloud and AWS with NetApp on tap. We have AWS FSX. And so this solution is now generally available across all global regions. We are super excited with all our joint customers and partners to bring this to the market. >>So Steve, give us your perspective as AWS as the biggest hyperscaler. Talk about the importance of the partnership and the longstanding partnerships that you've had with both NetApp and VMware. >>Yeah, you bet. So first all, maybe I'll start with Ryan and VMware. So we've had a very long standing partnership with VMware for over five years now. One thing that we've heard consistently from customers is they, they want help in reducing the heavy lifting or the, the friction that typically comes with cloud adoption. And VMware's been right in the trenches with us and helping with that over the years with the VMware cloud on AWS offering. And, and now that we've got NetApp, right, the FSX on tap solution, a managed storage solution that is, is been known and trusted in the on-premises world. Now available since September on AWS, but now available for use with VMware cloud is just amazing for customers who are looking for that agility, >>Right? Phil talk about NetApp has done a phenomenal job in its own digital transformation journey. Talk about that as an enabler for what you announced yesterday and the, and the capabilities that NetApp is able to bring to its customers with VMware and with AWS. >>Yeah. You know, it started, it's interesting because we NetApp's always been a company that works very closely with our partners. VMware has been a huge partner of ours since gosh, 2005 probably, or sometime like that. I started working with Amazon back in about 20 13, 20 14, when we first took on tap and brought it to the Amazon platform in the marketplace ahead of what's. Now FSX ends like a dream to bring a fully managed ONAP onto the world's biggest cloud. So that work you you're really looking at about. I mean, it depends how you look at it, 15 years of work. And then as Ryan was saying that VMware was working in parallel with us on being a first party service on Amazon, we came together and, or Ryan and I came together and VMware and NetApp came together about probably about two years ago now with this vision of what we're announcing today and to have so to have GA of this combination for meaning global availability, anybody can try it today. It's just an amazing day. It's really a great day. >>Yeah. It's unbelievable how we have sort of partnered together and hard engineering problems to create a very simple outcome for customers and partners. One of the things, you know, VMware cloud is a very successful service offering with a lot of great consumption and different verticals. Things like cloud migration, you know, transforming your entire, you know, data center and moving to the cloud. Things like, you know, modernizing our apps, disaster recovery now ransomware this week. So really, really exciting uptake and innovation in that whole service. One thing customers always told us that they want more options for storage decouple from compute. And so that really helped customers to lower their total cost of ownership and get to, you know, get even more workloads into VMware cloud. And this partnership really creates that opportunity for us to provide customers with those options. >>Let me give you an example, just I was walking over here just before I walked over here. We were with a customer talking about exactly what Orion's talking about. We were modeling using a TCO calculator that we all put together as well on what we call data intensive workloads, which is in this case, it was a 500 gigabytes per VM. So not a huge amount of data per VM. The, the case study modeled out of 38% cost savings or reduction in total cost, which in the case was like 1.2 million per year of total cost down to 700 million. And just, you could do the, just depends on how many VMs you have and how big odes you have, but that's the kind of cost savings we're talking about. So the, this is a really easy value to talk about. You save a lot of money in it's exactly as nor Ryan said, because we can separate the compute and the storage. Yep. >>Yep. I was just gonna say the reason for that is it used to be with VMware cloud on AWS. If you wanted more storage for your workload, you would have to add another node. So with another node, you would get another compute node. You would get the compute, you'd get the memory and the storage, but now we've actually decoupled the ability to expand the storage footprint from the compute, allowing customers to really expand as their needs grow. And so it's, it's just a lot more flexibility. Yep. That customers had. Yeah. >>Flexibility is key. Every customer needs that they need to be agile. There's always a competitor waiting in the rear view mirror behind any business, waiting to take over. If, if they can't innovate fast enough, if they can't partner with the best of the best to deliver the infrastructure that's needed to enable those business outcomes, I wanna get your perspective, Steve, what are some of the outcomes that when you're talking to customers, you talked about fill the TCO. Those are huge numbers, very compelling. What are some of the other outcomes that customers can expect to achieve from this solution? >>That's a great question. I think customers want the flexibility. We talked about customers absolutely wanna be able to move fast. They're also very demanding customers who have had an experience with solutions like NetApp on tap on premises, right? So they've come to expect enterprise features like thin provisioning, snapshoting cloning, rapid cloning, right? And even replication of data given that customers now can leverage this type of functionality as well through the NetApp solution with VMC, they're getting all those enterprise class features from, from the storage in combination with what they already had with vs a and, and VMC. >>Steve earlier mentioned the word we used, we kind of took it from VMware or from Amazon was friction is so many workloads run in VMware VMs today to be able to just simply pick them up as is move them to Amazon makes cloud adoption. Just, I mean, frictionless is an extreme word, but it's really lowers the friction to cloud adoption. And as Steve said, then you've get all these enterprise features wherever you need to run. >>Just brings speed. >>I was just about to say, it's gotta be the speed. It has to be a huge factor here. Yep, >>Yep. Yeah. >>Sure. One of the things that we've seen with VMware cloud is operational consistency as, as a customer value because when customers are thinking about, you know, complex enterprise apps, moving that to the cloud, they need that operational consistency, which drives down their costs. They don't have to relearn new skills. They're used to VMware, they're used to NetApp. And so this partnership really fosters that operational consistency as a big customer value, and they can reuse those skills and really reapply them in this cloud model. The other thing is the cloud model here is super completely managed. If you think about that, right, customers have to do less VMware, AWS and NetApp is doing more for them. That's true in this model. >>So you're able to really deliver a lot of workforce efficiency, workforce productivity across the stack. >>Absolutely. >>And that's definitely true that it just, as it gets more complex, how do you manage it? Just continue, hear everybody talking about this, right. So when a completely managed service by VMware and Amazon is such a savings in com in management complexity, which then gets back to speed. How do I grow my plant faster? >>I mean, and really at the end of the day, customers are actually able to focus on what differentiate differentiates them, obviously versus the management of the underlying infrastructure and storage and all those, those things that are still critical, but exactly, but >>For, for the customer to be able to have to abstract the underlying underlying technology layer and focus on what differentiates them from the competition. That's like I said, right back here, right. That's especially if there's anything we've learned in the last couple of years, it's that it, that is critical for businesses across every industry, no industry exempt from this. >>None. One other thing, just an example of what you're talking about is we all work a lot on modernization techniques like using Kubernetes and container technologies. So with this, if you think about this, you, this solution, you can move an app as is modernize on the cloud. You can modernize, you can modernize and then move. You can, the flexibility that this enables like. So it's sort of like move to the cloud at your rate is a really big benefit. >>And we've seen so many customer examples of migrating modernize is how we like to summarize it, where customers are, you know, migrating, modernizing at their own pace. Yep. And the good, good thing about the platform and the service is that it is the home for all applications, virtual machines containers with Kubernetes backed by local storage, external storage options. The level of flexibility for all applications is really immense. And that drives down your TCO even more. >>What, from a target customer perspective, Noran, talk about that. Who, who is the target? Obviously I imagine VMware customers, it's NetApp customers, it's AWS, but is there, are there any targets kind of within that, that are really prime candidates for this solution? >>Yeah. A great question. First of all, the, the easy sort of overlap between all of us is our shared customer pool. And so VMware and NetApp have been partners for what, 20 years, something like that. And we have thousands of customers using our joint solutions in the data center. And so that's a very clear target for this solution, as they're considering use cases such as, you know, cloud migration, disaster recovery, virtual desktops, application modernization. So that's a very clear target and we see this day in and day out, obviously there are many other customers that would be interested in this solution, as well as they're considering, you know, AWS and we provide a whole range of consumption options for them. Right. And I think that's one of the, sort of the, the good things about our partnership, including with AWS, where customers can purchase this from VMware can purchase this from AWS and all of these different options, including from our partners really makes it very, very compelling. >>Talk a little bit about from each of your perspectives about the what's in it. For me as a partner of these companies, Steve, we'll start with you. >>I mean, what's in it for me is that it's what my customers have been asking for. And we, we have a long history, I think of providing managed services again, to remove that heavy lifting that customers often just don't want to have to do. Having seen the, the adoption of managed storage offerings, including the, the NetApp solution here and now being able to bring that into the VMware space where they're already using it in an on-premises world, and now they're moving those, those workloads being able to satisfy that need that a customer's asking for is awesome. >>We, every time we're at an AWS event, we are always talking about it's absolute customer obsession, and I know NetApp and VMware well, and know that that is a shared obsession across the three companies. >>Hey, Lisa, let me add one more thing. It's interesting, not everybody sees this, but it's really obvious that the NetApp on-prem installed base with VMware, which is tens of thousands of customers. This is an awesome solution. Not quite as obvious is that every on-prem VMware customer gets that TCO benefit. I mentioned that's not limited to the NetApp on-prem installed base. So we're really excited to be able to expose all the market that hasn't used our products on-prem to this cloud solution. And, and it's really clear customers are adopting the cloud, right? So we're, that's one of the reasons we're so excited about this is it opens up a huge new opportunity to work with new customers for us. Talk >>About those customer conversations, Phil, how, where are they happening at? What level are you talking with customers about migration to cloud? Has it changed in the last couple >>Of years? Oh yeah. You know, I've been working on this for years and a lot of the on-prem conversation, it's been a little bifurcated that on-prem is on-prem and cloud developers or cloud developers. And Amazon's done a huge amount to break that down. VMware getting in the game, a lot of it's networking complexities, those have gone down. A lot of people are cross connected and set up today, which that wasn't so true five years ago. So now it's a lot of conversations about, I hear carbon footprint reduction. I hear data all in around data center reduction. The cloud guys are super efficient operators of data center infrastructure. We were talking about different use cases like disaster recovery. It's it's everybody though. It's small companies, it's big companies. They're all sort of moving into this, it call it at least hybrid world. And that's why when I say we're get really excited about this, because it does get rid of a lot of friction for moving loads in those directions, at the rate, the customer wants to do it. >>And that one last really quick thing is I was using NetApp as an example, we have about 300 enterprise workloads. We wanna move to the cloud two, right? And so they're all running VMware, like most, most of the world. And so this solution is, looks really good to us and we're gonna do the exact, I was just out with our CIO. We're going, looking at those 300, which do we just lift and move? Which do we refactor? And how do we do that? In fact, that Ryan was out to dinner with us last night, talking about >>This it's more and more it's being driven top down. So in the early days, and I've been with Amazon for 10 years now. Yep. Early days, it was kind of developer oriented, often initiated projects. Now it's top level CIOs. Exactly. I >>Are two mandates today talking to customers. >>I think of reinvent as an it conference. Now in the way, some of these top down mandates are driven, but listen, I mean, we got great customer interest. We have been in preview for three to six months now, and we've seen a lot of customers were not able to drag their entire data center workloads because of different reasons of PCO data, intensive workloads, et cetera. And we've seen tremendous amounts of interest from them. And we're also seeing a lot of new customers in the pipeline that want to consider VMware cloud now that we have these great storage options. >>So there's a pretty healthy Tam I'm hearing. >>Absolutely. >>I think so. Yeah. It's interesting. Another, just both like WWT and Presidio, channel partners, big, huge channel partners. It takes no selling to explain. We, we just say, Hey, we're doing this. And they start building services. Presidio is here with us talking about a customer win that they got. So this is it. It's easy for people to see why this is a cool, a cool solution. >>The value prop is there >>Definitely >>There's no having appeal the onion to >>Find it. No, the money savings. It's just in what or Ryan said, a lot of people have seen the, the seen an obstacle of cost. Yeah. So the TCO benefit, I mentioned removes that obstacle. And then that opens the door to all the features Steve was talking about of the advanced storage features and things on the platform. >>So is there a customer that's been in beta on this solution that you can talk about in, in terms of what they were looking for, the challenges that you helped them erase and the outcomes they're achieving? >>Yeah, sure. I can. I can provide one example. A large financial customer was looking at this during the preview phase and you know, for, for, for reasons before that were already a customer, but they were not able to attract a lot of their other workloads from other business units. And with this solution, now the service is a much better candidate for those workloads and those business units that had not considered VMware cloud. So we're really excited to see new workloads coming from that particular customer, given this particular solution and the whole TCO math for them was very, very straightforward and simple. And this became a more attractive option for that particular customer. >>Is there a shadow it elimination factor here in this technology and who you're selling to? >>Not real, I, don't not intent. Wouldn't intentionally. I wouldn't say yeah, not intentionally. I, it was funny with the customers I was thinking is yes. The question, the customers that are in the preview are seeing the benefits that we're talking about. The, one of the reasons we started the project on our side a number of years ago was this very large cement company was looking for carbon CO2 reduction. Part of that was moving disaster recovery to the cloud. There was a lot of friction in the solution prior to this, the, the customers have done some of the things we're talking about, but there's a, it takes a lot of skill. And we were looking at working with that customer going, how could we simplify this? And that was from our point of NetApp's point of view, it, it drove us to VMware and to AWS saying, can't we pull some of the friction of this out. And I think that that's what we've seen in the, in the previews. And it's, that's what I meant. It's so exciting to go from having say, I know we have about 20 previews right now, going to the globe today is the, is the exciting news today. >>And is the solution here in booze that it can be demoed and folks can kind of get their hands on it. >>Yeah. Yeah. They can go to the VMware cloud booth at the expo and they can get their hands on their demo and they can take it for a test drive. >>Excellent. >>You can run TCO calculators and do your own math and see what you're gonna all this, the all that's integrated today. We >>Also have pilots where we can help walk customers through a scenario of their own. >>Yep. Excellent. Is there, is there a, a joint website that you guys have, we should drive folks to? >>Yeah, it's >>Actually talk about the press release. It's >>It's yours. So >>It's it's prominently on our website. Okay. VMware cloud. It is onc.vmware.com where we also have the other, you know, our corporate marketing websites that have this vmware.com is a great starting point. Yeah. And we feature the solution. Prominently customers can get started today and they can even participate in the hands on labs here and take the solution for a test drive. >>All right. Last question, nor Ryan, we'll start with you on this. Here we are. I love the theme of this event, the center of the multicloud universe. Does it not sound like a Marvel movie? I feel like there should be some, is there any superheroes running around? Cause I really feel like there should be, how is this solution an enabler of allowing customers to really extract the most of value from their multi-cloud world that they're living in? >>Yeah. I mean, look, I mean, our mission is to build, run, managed, secure applications in any cloud, right. And regu has been talking about this with the keynote this morning as well. You know, at least with NetApp, we share a very good joint vision of enabling customers to, you know, place applications with really good TCO across clouds. And so it's really good story I feel. And I think this is a really good step in that direction where customers have choice and flexibility in terms of where they put their applications in the TCO value that they get. >>Awesome. Guys, you gotta come back next with a customer would love to dig. Maybe at reinvent sounds, we can dig into more and to see a great story of how a customer came together and is really leveraging that the power that is sitting next to me here. Thank you all so much for joining me and having this great conversation. Congratulations on the announcement and it being GA. >>Thank you. Awesome. >>Thank you. Thanks Lisa. All right. Fun conversation. I told you power panel for my guests. I'm Lisa Martin. You're watching the cube, keep it right here for more live coverage of VMware Explorer, 2022 from downtown San Francisco. We'll be right back with our next guest.

>> Announcer: "theCUBE" presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to HPE Discover 2022. You're watching "theCUBE's" coverage. This is Day 2, Dave Vellante with John Furrier. Sheila Rohra is here. She's the Senior Vice President and GM of the Data Infrastructure Business at Hewlett Packard Enterprise, and of course, the storage division. And Omer Asad. Welcome back to "theCUBE", Omer. Senior Vice President and General Manager for Cloud Data Services, Hewlett Packard Enterprise storage. Guys, thanks for coming on. Good to see you. >> Thank you. Always a pleasure, man. >> Thank you. >> So Sheila, I'll start with you. Explain the difference. The Data Infrastructure Business and then Omer's Cloud Data Services. You first. >> Okay. So Data Infrastructure Business. So I'm responsible for the primary secondary storage. Basically, what you physically store, the data in a box, I actually own that. So I'm going to have Omer explain his business because he can explain it better than me. (laughing) Go ahead. >> So 100% right. So first, data infrastructure platforms, primary secondary storage. And then what I do from a cloud perspective is wrap up those things into offerings, block storage offerings, data protection offerings, and then put them on top of the GreenLake platform, which is the platform that Antonio and Fidelma talked about on main Keynote stage yesterday. That includes multi-tenancy, customer subscription management, sign on management, and then on top of that we build services. Services are cloud-like services, storage services or block service, data protection service, disaster recovery services. Those services are then launched on top of the platform. Some services like data protection services are software only. Some services are software plus hardware. And the hardware on the platform comes along from the primary storage business and we run the control plane for that block service on the GreenLake platform and that's the cloud service. >> So, I just want to clarify. So what we maybe used to know as 3PAR and Nimble and StoreOnce. Those are the products that you're responsible for? >> That is the primary storage part, right? And just to kind of show that, he and I, we do indeed work together. Right. So if you think about the 3PAR, the primary... Sorry, the Primera, the Alletras, the Nimble, right? All that, right? That's the technology that, you know, my team builds. And what Omer does with his magic is that he turns it into HPE GreenLake for storage, right? And to deliver as a service, right? And basically to create a self-service agility for the customer and also to get a very Cloud operational experience for them. >> So if I'm a customer, just so I get this right, if I'm a customer and I want Hybrid, that's what you're delivering as a Cloud service? >> Yes. >> And I don't care where the data is on-premises, in storage, or on Cloud. >> 100%. >> Is that right? >> So the way that would work is, as a customer, you would come along with the partner, because we're 100% partner-led. You'll come to the GreenLake Console. On the GreenLake Console, you will pick one of our services. Could be a data protection service, could be the block storage service. All services are hybrid in nature. Public Cloud is 100% participant in the ecosystem. You'll choose a service. Once you choose a service, you like the rate card for that service. That rate card is just like a hyperscaler rate card. IOPS, Commitment, MINCOMMIT's, whatever. Once you procure that at the price that you like with a partner, you buy the subscription. Then you go to console.greenLake.com, activate your subscription. Once the subscription is activated, if it's a service like block storage, which we talked about yesterday, service will be activated, and our supply chain will send you our platform gear, and that will get activated in your site. Two things, network cable, power cable, dial into the cloud, service gets activated, and you have a cloud control plane. The key difference to remember is that it is cloud-consumption model and cloud-operation model built in together. It is not your traditional as a service, which is just like hardware leasing. >> Yeah, yeah, yeah. >> That's a thing of the past. >> But this answers a question that I had, is how do you transfer or transform from a company that is, you know, selling boxes, of course, most of you are engineers are software engineers, I get that, to one that is selling services. And it sounds like the answer is you've organized, I know it's inside baseball here, but you organize so that you still have, you can build best of breed products and then you can package them into services. >> Omer: 100%. 100%. >> It's separate but complementary organization. >> So the simplest way to look at it would be, we have a platform side at the house that builds the persistence layers, the innovation, the file systems, the speeds and feeds, and then building on top of that, really, really resilient storage services. Then how the customer consumes those storage services, we've got tremendous feedback from our customers, is that the cloud-operational model has won. It's just a very, very simple way to operate it, right? So from a customer's perspective, we have completely abstracted away out hardware, which is in the back. It could be at their own data center, it could be at an MSP, or they could be using a public cloud region. But from an operational perspective, the customer gets a single pane of glass through our service console, whether they're operating stuff on-prem, or they're operating stuff in the public cloud. >> So they get storage no matter what? They want it in the cloud, they got it that way, and if they want it as a service, it just gets shipped. >> 100%. >> They plug it in and it auto configures. >> Omer: It's ready to go. >> That's right. And the key thing is simplicity. We want to take the headache away from our customers, we want our customers to focus on their business outcomes, and their projects, and we're simplifying it through analytics and through this unified cloud platform, right? On like how their data is managed, how they're stored, how they're secured, that's all taken care of in this operational model. >> Okay, so I have a question. So just now the edge, like take me through this. Say I'm a customer, okay I got the data saved on-premise action, cloud, love that. Great, sir. That's a value proposition. Come to HPE because we provide this easily. Yeah. But now at the edge, I want to deploy it out to some edge node. Could be a tower with Telecom, 5G or whatever, I want to box this out there, I want storage. What happens there? Just ship it out there and connects up? Does it work the same way? >> 100%. So from our infrastructure team, you'll consume one or two platforms. You'll consume either the Hyperconverged form factor, SimpliVity, or you might convert, the Converged form factor, which is proliant servers powered by Alletras. Alletra 6Ks. Either of those... But it's very different the way you would procure it. What you would procure from us is an edge service. That edge service will come configured with certain amount of compute, certain amount of storage, and a certain amount of data protection. Once you buy that on a dollars per gig per month basis, whichever rate card you prefer, storage rate card or a VMware rate card, that's all you buy. From that point on, the platform team automatically configures the back-end hardware from that attribute-based ordering and that is shipped out to your edge. Dial in the network cable, dial in the power cable, GreenLake cloud discovers it, and then you start running the- >> Self-service, configure it, it just shows up, plug it in, done. >> Omer: Self-service but partner-led. >> Yeah. >> Because we have preferred pricing for our partners. Our partners would come in, they will configure the subscriptions, and then we activate those customers, and then send out the hardware. So it's like a hyperscaler on-prem at-scale kind of a model. >> Yeah, I like it a lot. >> So you guys are in the data business. You run the data portion of Hewlett Packard Enterprise. I used to call it storage, even if we still call it storage but really, it's evolving into data. So what's your vision for the data business and your customer's data vision, if you will? How are you supporting that? >> Well, I want to kick it off, and then I'm going to have my friend, Omer, chime in. But the key thing is that what the first step is is that we have to create a unified platform, and in this case we're creating a unified cloud platform, right? Where there's a single pane of glass to manage all that data, right? And also leveraging lots of analytics and telemetry data that actually comes from our infosite, right? We use all that, we make it easy for the customer, and all they have to say, and they're basically given the answers to the test. "Hey, you know, you may want to increase your capacity. You may want to tweak your performance here." And all the customers are like, "Yes. No. Yes, no." Basically it, right? Accept and not accept, right? That's actually the easiest way. And again, as I said earlier, this frees up the bandwidth for the IT teams so then they actually focus more on the business side of the house, rather than figuring out how to actually manage every single step of the way of the data. >> Got it. >> So it's exactly what Sheila described, right? The way this strategy manifests itself across an operational roadmap for us is the ability to change from a storage vendor to a data services vendor, right? >> Sheila: Right. >> And then once we start monetizing these data services to our customers through the GreenLake platform, which gives us cloud consumption model and a cloud operational model, and then certain data services come with the platform layer, certain data services are software only. But all the services, all the data services that we provide are hybrid in nature, where we say, when you provision storage, you could provision it on-prem, or you can provision it in a hyperscaler environment. The challenge that most of our customers have come back and told us, is like, data center control planes are getting fragmented. On-premises, I mean there's no secrecy about it, right? VMware is the predominant hypervisor, and as a result of that, vCenter is the predominant configuration layer. Then there is the public cloud side, which is through either Ajour, or GCP, or AWS, being one of the largest ones out there. But when the customer is dealing with data assets, the persistence layer could be anywhere, it could be in AWS region, it could be your own data center, or it could be your MSP. But what this does is it creates an immense amount of fragmentation in the context in which the customers understand the data. Essentially, John, the customers are just trying to answer three questions: What is it that I store? How much of it do I store? Should I even be storing it in the first place? And surprisingly, those three questions just haven't been answered. And we've gotten more and more fragmented. So what we are trying to produce for our customers, is a context to ware data view, which allows the customer to understand structured and unstructured data, and the lineage of how it is stored in the organization. And essentially, the vision is around simplification and context to ware data management. One of the key things that makes that possible, is again, the age old infosite capability that we have continued to hone and develop over time, which is now up to the stage of like 12 trillion data points that are coming into the system that are not corroborated to give that back. >> And of course cost-optimizing it as well. We're up against the clock, but take us through the announcements, what's new from when we sort of last talked? I guess it was in September. >> Omer: Right. >> Right. What's new that's being announced here and, or, you know, GA? >> Right. So three major announcements that came out, because to keep on establishing the context when we were with you last time. So last time we announced GreenLake backup and recovery service. >> John: Right. >> That was VMware backup and recovery as a complete cloud, sort of SaaS control plane. No backup target management, no BDS server management, no catalog management, it's completely a SaaS service. Provide your vCenter address, boom, off you go. We do the backups, agentless, 100% dedup enabled. We have extended that into the public cloud domain. So now, we can back up AWS, EC2, and EBS instances within the same constructs. So a single catalog, single backup policy, single protection framework that protects you both in the cloud and on-prem, no fragmentation, no multiple solutions to deploy. And the second one is we've extended our Hyperconverged service to now be what we call the Hybrid Cloud On-Demand. So basically, you go to GreenLake Console control plane, and from there, you basically just start configuring virtual machines. It supports VMware and AWS at the same time. So you can provision a virtual machine on-prem, or you can provision a virtual machine in the public cloud. >> Got it. >> And, it's the same framework, the same catalog, the same inventory management system across the board. And then, lastly, we extended our block storage service to also become hybrid in nature. >> Got it. >> So you can manage on-prem and AWS, EBS assets as well. >> And Sheila, do you still make product announcements, or does Antonio not allow that? (Omer laughing) >> Well, we make product announcements, and you're going to see our product announcements actually done through the HPE GreenLake for block storage. >> Dave: Oh, okay. >> So our announcements will be coming through that, because we do want to make it as a service. Again, we want to take all of that headache of "What configuration should I buy? How do I actually deploy it? How do I...?" We really want to take that headache away. So you're going to see more feature announcements that's going to come through this. >> So feature acceleration through GreenLake will be exposed? >> Absolutely. >> This is some cool stuff going on behind the scenes. >> Oh, there's a lot good stuff. >> Hardware still matters, you know. >> Hardware still matters. >> Does it still matter? Does hardware matter? >> Hardware still matters, but what matters more is the experience, and that's actually what we want to bring to the customer. (laughing) >> John: That's good. >> Good answer. >> Omer: 100%. (laughing) >> Guys, thanks so much- >> John: Hardware matters. >> For coming on "theCUBE". Good to see you again. >> John: We got it. >> Thanks. >> And hope the experience was good for you Sheila. >> I know, I know. Thank you. >> Omer: Pleasure as always. >> All right, keep it right there. Dave Vellante and John Furrier will be back from HPE Discover 2022. You're watching "theCUBE". (soft music)

>>Hey everyone. Welcome back to the cube. Lisa Martin, with Dave ante. We're here in Las Vegas with snowflake at the snowflake summit 22. This is the fourth annual there's close to 10,000 people here. Lots going on. Customers, partners, analysts, cross media, everyone talking about all of this news. We've got a couple of guests joining us. We're gonna unpack snow park. Torston grabs the director of product management at snowflake and Joe. No NTY AI and MDM architect at Allegis group. Guys. Welcome to the program. Thank >>You so much for having >>Us. Isn't it great to be back in person? It is. >>Oh, wonderful. Yes, it >>Is. Indeed. Joe, talk to us a little bit about Allegis group. What do you do? And then tell us a little bit about your role specifically. >>Well, Allegis group is a collection of OPCA operating companies that do staffing. We're one of the biggest staffing companies in north America. We have a presence in AMEA and in the APAC region. So we work to find people jobs, and we help get 'em staffed and we help companies find people and we help individuals find >>People incredibly important these days, excuse me, incredibly important. These days. It is >>Very, it very is right >>There. Tell me a little bit about your role. You are the AI and MDM architect. You wear a lot of hats. >>Okay. So I'm a architect and I support both of those verticals within the company. So I work, I have a set of engineers and data scientists that work with me on the AI side, and we build data science models and solutions that help support what the company wants to do, right? So we build it to make business business processes faster and more streamlined. And we really see snow park and Python helping us to accelerate that and accelerate that delivery. So we're very excited about it. >>Explain snow park for, for people. I mean, I look at it as this, this wonderful sandbox. You can bring your own developer tools in, but, but explain in your words what it >>Is. Yeah. So we got interested in, in snow park because increasingly the feedback was that everybody wants to interact with snowflake through SQL. There are other languages that they would prefer to use, including Java Scala and of course, Python. Right? So then this led down to the, our, our work into snow park where we're building an infrastructure that allows us to host other languages natively on the snowflake compute platform. And now here, what we're, what we just announced is snow park for Python in public preview. So now you have the ability to natively run Python code on snowflake and benefit from the thousands of packages and libraries that the open source community around Python has contributed over the years. And that's a huge benefit for data scientists. It is ML practitioners and data engineers, because those are the, the languages and packages that are popular with them. So yeah, we very much look forward to working with the likes of you and other data scientists and, and data engineers around the Python ecosystem. >>Yeah. And, and snow park helps reduce the architectural footprint and it makes the data pipelines a little easier and less complex. We have a, we had a pipeline and it works on DMV data. And we converted that entire pipeline from Python, running on a VM to directly running down on snowflake. Right. We were able to eliminate code because you don't have to worry about multi threading, right? Because we can just set the warehouse size through a task, no more multi threading, throw that code away. Don't need to do it anymore. Right. We get the same results, but the architecture to run that pipeline gets immensely easier because it's a store procedure that's already there. And implementing that calling to that store procedure is very easy. The architecture that we use today uses six different components just to be able to run that Python code on a VM within our ecosystem to make sure that it runs on time and is scheduled and all of that. Right. But with snowflake, with snowflake and snow park and snowflake Python, it's two components. It's the store procedure and our ETL tool calling it. >>Okay. So you've simplified that, that stack. Yes. And, and eliminated all the other stuff that you had to do that now Snowflake's doing, am I correct? That you're actually taking the application development stack and the analytics stack and bringing them together? Are they merging? >>I don't know. I think in a way I'm not real sure how I would answer that question to be quite honest. I think with stream lit, there's a little bit of application that's gonna be down there. So you could maybe start to say that I'd have to see how that carries out and what we do and what we produce to really give you an answer to that. But yeah, maybe in a >>Little bit. Well, the reason I asked you is because you talk, we always talk about injecting data into apps, injecting machine intelligence and ML and AI into apps, but there are two separate stacks today. Aren't they >>Certainly the two are getting closer >>To Python Python. It gets a little better. Explain that, >>Explain, explain how >>That I just like in the keynote, right? The other day was SRE. When she showed her sample application, you can start to see that cuz you can do some data pipelining and data building and then throw that into a training module within Python, right down inside a snowflake and have it sitting there. Then you can use something like stream lit to, to expose it to your users. Right? We were talking about that the other day, about how do you get an ML and AI, after you have it running in front of people, we have a model right now that is a Mo a predictive and prescriptive model of one of our top KPIs. Right. And right now we can show it to everybody in the company, but it's through a Jupyter notebook. How do I deliver it? How do I get it in the front of people? So they can use it well with what we saw was streamlet, right? It's a perfect match. And then we can compile it. It's right down there on snowflake. And it's completely easier time to delivery to production because since it's already part of snowflake, there's no architectural review, right. As long as the code passes code review, and it's not poorly written code and isn't using a library that's dangerous, right. It's a simple deployment to production. So because it's encapsulated inside of that snowflake environment, we have approval to just use it. However we see fit. >>It's very, so that code delivery, that code review has to occur irrespective of, you know, not always whatever you're running it on. Okay. So I get that. And, and, but you, it's a frictionless environment you're saying, right. What would you have had to do prior to snowflake that you don't have to do now? >>Well, one, it's a longer review process to allow me to push the solution into production, right. Because I have to explain to my InfoSec people, right? My other it's not >>Trusted. >>Well, well don't use that word. No. Right? It got, there are checks and balances in everything that we do, >>It has to be verified. And >>That's all, it's, it's part of the, the, what I like to call the good bureaucracy, right? Those processes are in place to help all of us stay protected. >>It's the checklist. Yeah. That you >>Gotta go to. >>That's all it is. It's like fly on a plane. You, >>But that checklist gets smaller. And sometimes it's just one box now with, with Python through snow park, running down on the snowflake platform. And that's, that's the real advantage because we can do things faster. Right? We can do things easier, right? We're doing some mathematical data science right now and we're doing it through SQL, but Python will open that up much easier and allow us to deliver faster and more accurate results and easier not to mention, we're gonna try to bolt on the hybrid tables to that afterwards. >>Oh, we had talk about that. So can you, and I don't, I don't need an exact metric, but when you say faster talking 10% faster, 20% faster, 50% path >>Faster, it really depends on the solution. >>Well, gimme a range of, of the worst case, best case. >>I, I really don't have that. I don't, I wish I did. I wish I had that for you, but I really don't have >>It. I mean, obviously it's meaningful. I mean, if >>It is meaningful, it >>Has a business impact. It'll >>Be FA I think what it will do is it will speed up our work inside of our iterations. So we can then, you know, look at the code sooner. Right. And evaluate it sooner, measure it sooner, measure it faster. >>So is it fair to say that as a result, you can do more. Yeah. That's to, >>We be able do more well, and it will enable more of our people because they're used to working in Python. >>Can you talk a little bit about, from an enablement perspective, let's go up the stack to the folks at Allegis who are on the front lines, helping people get jobs. What are some of the benefits that having snow park for Python under the hood, how does it facilitate them being able to get access to data, to deliver what they need to, to their clients? >>Well, I think what we would use snowflake for a Python for there is when we're building them tools to let them know whether or not a user or a piece of talent is already within our system. Right. Things like that. Right. That's how we would leverage that. But again, it's also new. We're still figuring out what solutions we would move to Python. We are, we have some targeted, like we're, I have developers that are waiting for this and they're, and they're in private preview. Now they're playing around with it. They're ready to start using it. They're ready to start doing some analytical work on it, to get some of our analytical work out of, out of GCP. Right. Because that's where it is right now. Right. But all the data's in snowflake and it just, but we need to move that down now and take the data outta the data wasn't in snowflake before. So there, so the dashboards are up in GCP, but now that we've moved all of that data down in, down in the snowflake, the team that did that, those analytical dashboards, they want to use Python because that's the way it's written right now. So it's an easier transformation, an easier migration off of GCP and get us into snow, doing everything in snowflake, which is what we want. >>So you're saying you're doing the visualization in GCP. Is that righting? >>It's just some dashboarding. That's all, >>Not even visualization. You won't even give for. You won't even give me that. Okay. Okay. But >>Cause it's not visualization. It's just some D boardings of numbers and percentages and things like that. It's no graphic >>And it doesn't make sense to run that in snowflake, in GCP, you could just move it into AWS or, or >>No, we, what we'll be able to do now is all that data before was in GCP and all that Python code was running in GCP. We've moved all that data outta GCP, and now it's in snowflake and now we're gonna work on taking those Python scripts that we thought we were gonna have to rewrite differently. Right. Because Python, wasn't available now that Python's available, we have an easier way of getting those dashboards back out to our people. >>Okay. But you're taking it outta GCP, putting it to snowflake where anywhere, >>Well, the, so we'll build the, we'll build those, those, those dashboards. And they'll actually be, they'll be displayed through Tableau, which is our enterprise >>Tool for that. Yeah. Sure. Okay. And then when you operationalize it it'll go. >>But the idea is it's an easier pathway for us to migrate our code, our existing code it's in Python, down into snowflake, have it run against snowflake. Right. And because all the data's there >>Because it's not a, not a going out and coming back in, it's all integrated. >>We want, we, we want our people working on the data in snowflake. We want, that's our data platform. That's where we want our analytics done. Right. We don't want, we don't want, 'em done in other places. We when get all that data down and we've, we've over our data cloud journey, we've worked really hard to move all of that data. We use out of existing systems on prem, and now we're attacking our, the data that's in GCP and making sure it's down. And it's not a lot of data. And we, we fixed it with one data. Pipeline exposes all that data down on, down in snowflake now. And we're just migrating our code down to work against the snowflake platform, which is what we want. >>Why are you excited about hybrid tables? What's what, what, what's the >>Potential hybrid tables I'm excited about? Because we, so some of the data science that we do inside of snowflake produces a set of results and there recommendations, well, we have to get those recommendations back to our people back into our, our talent management system. And there's just some delays. There's about an hour delay of delivering that data back to that team. Well, with hybrid tables, I can just write it to the hybrid table. And that hybrid table can be directly accessed from our talent management system, be for the recruiters and for the hiring managers, to be able to see those recommendations and near real time. And that that's the value. >>Yep. We learned that access to real time. Data it in recent years is no longer a nice to have. It's like a huge competitive differentiator for every industry, including yours guys. Thank you for joining David me on the program, talking about snow park for Python. What that announcement means, how Allegis is leveraging the technology. We look forward to hearing what comes when it's GA >>Yeah. We're looking forward to, to it. Nice >>Guys. Great. All right guys. Thank you for our guests and Dave ante. I'm Lisa Martin. You're watching the cubes coverage of snowflake summit 22 stick around. We'll be right back with our next guest.

>> Welcome back to theCube's coverage of PagerDuty Summit 22. Lisa Martin with you here on the ground. I've got one of our alumni back with me. Sean Scott joins me, the Chief Product Officer at PagerDuty. It's great to have you here in person. >> Super great to be here in person. >> Isn't it nice? >> Quite a change, quite a change. >> It is a change. We were talking before we went live about it. That's that readjustment to actually being with another human, but it's a good readjustment to have >> Awesome readjustment. I've been traveling more and more in the past few weeks and just speaking the offices, seeing the people the energy we get is the smiles, it's amazing. So it's so much better than just sitting at your home and. >> Oh, I couldn't agree more. For me it's the energy and the CEO of DocuSign talked about that with Jennifer during her fireside chat this morning, but yes, finally, someone like me who doesn't like working from home but as one of the things that you talked about in your keynote this morning was the ways traditionally that we've been working are no longer working. Talk to me about the future of work. What does it look like from PagerDuty's lens? >> Sure. So there's a few things. If we just take a step back and think about, what your day looks like from all the different slacks, chats, emails, you have your dashboards, you have more slacks coming in, you have more emails coming in, more chat and so just when you start the day off, you think you know what you're doing and then it kind of blows up out of the gate and so what we're all about is really trying to revolutionize operations so how do you help make sense of all the chaos that's happening and how do you make it simpler so you can get back to doing the more meaningful work and leave the tedium to the machines and just automate. >> That would be critical. One of the things that such an interesting dynamic two years that we've had obviously here we are in San Francisco with virtual event this year but there's so many problems out there that customer landscape's dealing with the great resignation. The data deluge, there's just data coming in everywhere and we have this expectation when we're on the consumer side, that we're going to be that a business will know us and have enough context to make us that the next best offer that actually makes sense but now what we're seeing is like the great resignation and the data overload is really creating for many organizations, this operational complexity that's now a problem really amorphously across the organization. It's no longer something that the back office has to deal with or just the front office, it's really across. >> Yeah, that's right. So you think about just the customer's experience, their expectations are higher than ever. I think there's been a lot of great consumer products that have taught the world, what good looks like, and I came from a consumer background and we measured the customer experience in milliseconds and so customers talking about minutes or hours of outages, customers are thinking in milliseconds so that's the disconnect and so, you have to be focused at that level and have everybody in your organization focused, thinking about milliseconds of customer experience, not seconds, minutes, hours, if that's where you're at, then you're losing customers. And then you think about, you mentioned the great resignation. Well, what does that mean for a given team or organization? That means lost institutional knowledge. So if you have the experts and they leave now, who's the experts? And do you have the processes and the tools and the runbooks to make sure that nothing falls on the ground? Probably not. Most of the people that we talk to, they're trying to figure it out as they go and they're getting better but there's a lot of institutional knowledge that goes out the door when people leave. And so part of our solution is also around our runbook automation and our process automation and some of our announcements today really help address that problem to keep the business running, keep the operations running, keep everything kind of moving and the customers happy ultimately and keep your business going where it needs to go. >> That customer experience is critical for organizations in every industry these days because we don't to your point. We'll tolerate milliseconds, but that's about it. Talk to me about you did this great keynote this morning that I had a chance to watch and you talked about how PagerDuty is revolutionizing operations and I thought, I want you to be able to break that down for this audience who may not have heard that. What are those four tenants or revolutionizing operations that PagerDuty is delivering to ORGS? >> Sure, so it starts with the data. So you mentioned the data deluge that's happening to everybody, right? And so we actually do, we integrate with over 650 systems to bring all that data in, so if you have an API or webhook, you can actually integrate with PagerDuty and push this data into PagerDuty and so that's where it starts, all these integrations and it's everything from a develop perspective, your CI/CD pipelines, your code repositories, from IT we have those systems are instrumented as well, even marketing, more tech stacks we can actually instrument and pull data in. The next step is now we have all this data, how do we make sense of it? So, we think we have machine learning algorithms that really help you focus your attention and kind of point you to the really relevant work, part of that is also noise suppression. So, our algorithms can suppress noise about 98% of the noise can just be eliminated and that helps you really focus where you need to spend your time 'cause if you think about human time and attention, it's pretty expensive and it's probably one of your company's most precious resources is that human time and so you want the humans doing the really meaningful work. Next step is automation, which is okay. We want the humans doing the special work, so what's the TDM? What's the toil that we can get rid of and push that to the machines 'cause machines are really good at doing very easy, repetitive task and there's a lot of them that we do day in, day out. The next step is just orchestrating the work and putting, getting everybody in the organization on the same page and that's where this morning I talked about our customer service operations product into the customer service is on the front lines and they're often getting signals from actual customers that nobody else in the organization may not even be aware of it yet So, I was running a system before and all our metrics are good and you get a customer feedback saying, "This isn't working for me," and you go look at the metrics and your dashboards and all looks good and then you go back and talk to the customer some more and they're like, "No, it's still not working," and you go back to your data, you're back to your dashboards, back to your metrics and sure enough, we had an instrumentation issue but the customer was giving us that feedback and so customer service is really on the front lines and they're often the kind of the unsung heroes for your customers but they're actually really helping and make sure that everything, the right signals are coming to the dev team, to the owners that own it and even in the case when you think you have everything instrumented, you may be missing something and that's where they can really help but our customer service operations product really helps bring everybody on the same page and then as the development teams and the IT teams and the SRA has pushed information back to customer service, then they're equipped, empowered to go tell the customer, "Okay, we know about the issue. Thank you." We should have it up in the next 30 minutes or whatever it is, five minutes, hopefully it's faster than longer, but they can inform the customer so to help that customer experience as opposed to the customer saying, "Oh, I'm just going to go shop somewhere else," or "I'm going to go buy somewhere else or do something else." And the last part is really around, how do we really enable our customers with the best practices? So those million users, the 21,000 companies in organizations we're working with, we've learned a lot around what good looks like. And so we've really embedded that back into our product in terms of our service standards which is really helps SRES and developers set quality standards for how services should be implemented at their company and then they can actually monitor and track across all their teams, what's the quality of the services and this team against different teams in their organization and really raise the quality of the overall system. >> So for businesses and like I mentioned, DocuSign was on this morning, I know some great brand customers that you guys have. I've seen on the website, Peloton Slack, a couple that popped out to me. When you're able to work with a customer to help them revolutionize operations, what are some of the business impacts? 'Cause some of the things that jump out to me would be like reduction in churn, retention rate or some of those things that are really overall impactful to the revenue of a business. >> Absolutely. And so there's a couple different parts of it. One is, all the work what PagerDuty is known for is orchestrating the work for a service outage or a website outage and so that's actually easy to measure 'cause you can measure your revenue that's coming in or missed revenue and how much we've shortened that. So that's the, I guess that's our kind of the history and our legacy but now we've moved into a lot of the cost side as well. So, helping customers really understand from an outage perspective where to focus our time as opposed to just orchestrating the work. Well now, we can say, we think we have a new feature we launched last year called Probable Origin. So when you have an outage, we can actually narrow in where we think the outage and just give you a few clues of this looks anomalous, for example. So let's start here. So that still focus on the top line and then from an automation perspective, there's lots and lots of just toil and noise that people are dealing with on a day in, day out basis and then some of it's easy work, some of it's harder work. One of the ones I really like is our automated diagnostics. So, if you have an incident, one of the first things you have to do is you have to go gather telemetry of what's actually happening on the servers, to say, is the CPU look good? Does the memory look good? Does the disc look good? Does the network look good? And that's all perfect work for automation. And so we can run our automated diagnostics and have all that data pumped directly into the incident so when the responder engages, it's all right there waiting for them and they don't have to go do all that basic task of getting data, cutting and pasting into the incident or if you're using one of those old ticketing systems, cutting and pacing into a a tickety system, it's all right there waiting for you. And that's on average 15 minutes during an outage of time that's saved. And the nice thing about that is that can all be kicked off at time zero so you can actually call from our event orchestration product, you can call directly into automation actions right there when that event first comes in. So you think about, there's a warning for a CPU and instantly it kicks off this diagnostics and then within seconds or even minutes, it's in the incident waiting for you to take action. >> One of the things that you also shared this morning that I loved was one of the stats around customer sale point that they had 60 different alerts coming in and PagerDuty was able to reduce that to one alert. So, 60 X reduction in alerts, getting rid of a lot of noise allowing them to focus on really those probably key high escalations that are going to make the biggest impact to their customers and to their business. >> That's right. You think about, you have a high severity incident like they actually had a database failure and so, when you're in the heat of the moment and you start getting these alerts, you're trying to figure out, is that one incident? Is it 10 incidents? Is it a hundred incidents that I'm having to deal with? And you probably have a good feeling like there's, I know it's probably this thing but you're not quite sure and so, with our machine learning we're able to eliminate a lot of the noise and in this case it was, going from 60 alerts down to one, just to let you know, this is the actual incident, but then also to focus your attention on where we think may be the cause and you think about all the different teams that historically have been had to pull in for a large scale incident. We can quickly narrow into the root cause and just get the right people involved. So we don't have these conference bridges of a hundred people on which you hear about. When these large cottages happen that everyone's on a call across the entire company and it's not just the dev teams and IT teams, you have PR, you have legal, you have everybody's involved in these. And so the more that we can workshop their work and get smarter about using machine learning, some of these other technologies then the more efficient it is for our customers and ultimately the better it is for their customers. >> Right and hopefully, PR, HR, legal doesn't have to be some of those incident response leaders that right now we're seeing across the organization. >> Exactly. Exactly. >> So when you're talking with customers and some of the things that you announced, you mentioned automated actions, incident workflows, what are you hearing from the voice of the customer as the chief product officer and what influence did that have in terms of this year's vision for the PagerDuty Summit? >> Sure. We listen to our customers all the time. It's one of our leadership principles and really trying to hear their feedback and it was interesting. I got sent some of the chat threads during the keynote afterwards, and there's a lot of excitement about the products we announced. So the first one is incident workflows, and this is really, it's a no code workflow based on or a recent acquisition of a company called Catalytic and what it does is it's, you can think of as kind of our next generation of response plays so you can actually go in and and build a workflow using no code tooling to say, when this incident happens or this type of incident happens, here's what that process looks like and so back to your original comment around the great resignation that loss institutional knowledge, well now, you're building all this into your processes through your incident response. And so, I think the incident workflows, if you want to create a incident specific slack channel or an incident specific zoom bridge, or even just in status updates, all that is right there for you and you can use our out of the box orchestrations or you can define your own 'cause we have back to the, our customer list, we have some of the biggest companies in the world, as customers and we have a very opinionated product and so if you're new to the whole DevOps and full service ownership, we help you through that. But then, a lot of our companies are evolving along that continuum, the operational maturity model continuum. And at the other end, we have customers that say "This is great, but we want to extend it. We want to like call this person or send this or update this system here." And so that's where the incident workflows is really powerful and it lets our customers just tailor it to their processes and really extend it for them. >> And that's GA later this year? >> Later this year, yes, we'll start ING probably the next few months and then GA later this year. >> Got it. Last question, as we're almost out of time here, what are some of the things that as you talk to customers day in and day out, as you see you saw the chats from this morning's live keynote, the excitement, the trust that PagerDuty is building with its customers, its partners, et cetera, What excites you about the future? >> So it's really why I came to PagerDuty. I've been here about a year and a half now, but revolutionizing operations, that's a big statement and I think we need it. I think Jennifer said in her keynote today, work is broken and I think our data, we surveyed our customers earlier this year and 42% of the respondents were working more hours in 2021 compared to 2020. And I don't think anyone goes home and if I could only work more hours, I think there's some and if I could only do more of this like TDM, the TDM, more toils, if I could only do more of that, I think life would be so good. We don't hear that. We don't hear that a lot. We hear about there's a lot of noise. We have a massive attrition that every company does. That's the type of feedback that we get and so we're really, that's what gets me excited about, the tools that we're building that and especially when I think just seeing the chat even this morning about some of the announcements, it shows we've been listening and it shows the excitement in our customers when they're, lots of I'm going to use this tool, that tool, I can just use PagerDuty which is awesome. >> The momentum is clear and it's palpable and I love being a part of that. Thank you so much Sean for joining me on theCube this afternoon, talking about what's new, what's exciting and how you guys are fixing work that's broken that validated me thinking the work was broken so thank you. >> Happy to be here and thanks for having me. >> My pleasure. For Sean Scott. I'm Lisa Martin, you're watching theCube's coverage of PagerDuty Summit 22 on the ground from the San Francisco. (soft music)

>> "theCube" presents Dell Technologies World, brought to you by Dell. >> Hey everyone, Welcome back to "theCube's" continuing coverage of Dell Technologies World 2022. Live from the show floor in Las Vegas. We have been here since Monday evening. About seven to 8,000 folks here. It's been a fantastically well-attended event that Dell has done. Lots of talk about announcements, including APEX. Lisa Martin with Dave Vellante are going to unpack more of APEX with our next two Cube alumni who are returning, Akanksha Mehrotra, VP of APEX product marketing joins us, and Chad Dunn, VP of product management APEX. Guys, welcome back. >> Thank you. >> Thank you. >> Thank you for having us. >> It is really great to be back. >> So just in case there's anybody out there that's been under a rock since Monday, APEX has now been what GA for a year, celebrating a momentous year and some big news. Akanksha, walk us through that and then talk about some of the feedback that you've gotten on what you guys announced just two days ago. >> Yeah. So it's been an exciting week like you said. APEX just for sort of background is our portfolio of as-a-service solutions, we introduced it a year ago. We have now 10 plus services in our portfolio. We added our very first full stack managed service for cyber recovery this week. The feedback from customers over the past year and then the conversations we've had, you know, over the course of this week has been phenomenal. If I had to really summarize it, I would say the pain point that we're looking to solve, helping organizations manage data across disparate and fragmented environments across a variety of clouds, you know, on-premises, in a co-lo, on the far edge, at a hyperscale or in the telco edge is resonating. This is a pain point... This is very real pain point for them. And our goal in our vision to create a consistent and a secure experience across all of these different, you know, silos of data, if you will. It's something that they really want more of from us. >> Chad, talk a little bit about the influence of the customer in the last couple of years. Well, in the last year, in terms of releasing the cyber recovery solution on APEX, we have seen the threat landscape massively change. >> It increases every day. >> It increases every day, ransomware is no longer a... Is it going to happen too? It's a matter of when? >> Yes. >> Talk to us about the influence of the customer of this being the first full stack solution on APEX. >> Sure, like I don't think there's a boardroom in the world where this isn't being discussed as just such a high risk environment for cyber techs. It's damaging to lose your data. It's damaging to your reputation, it's financially damaging. So it's incredibly important into our customers. And we're finding that, you know, many of them don't necessarily have all the expertise to be able to defend against it themselves. And so that's where an as-a-service solution, like the one that we're offering really makes sense to them, right? They're much more apt to consume as-a-service when the competency doesn't necessarily already exist in their IT organizations. So we've been doing this for a few years as a solution with managed services. And in fact, we've deployed over 2000 of these, and making that a standardized offering with T-shirt sizing, subscription basis, really seems to be a winner. And every customer I've talked to has been absolutely over the moon with it. >> All right, so we have Chad in product management, Akanksha, you're in product marketing. So you knew going into this, that it was going to be different. So I'm interested in kind of what your learnings were, that internal transformation, which is ongoing now, I understand that, but how did it change how you manage, you know, deploy the life cycle of the product and communicate that. >> I'll get us started and I'm sure Chad will add on. So, you know, to your point, when we started this journey internally before we started it externally, we knew this was going to be a multi-year transformation for us. And a multi-year transformation that affects every part of the company, how we build products, how we market products, how we bring them to market, how we sell them, et cetera. And so we made a very conscious effort to kind of secure that buy-in early on. And it starts Michael on down. This is a strategic priority for him as I'm sure both of you know. And each function has kind of established, you know, areas where they know they need to transform and a north star goal for where they want to get to. So I'll speak for marketing as a place that's, you know, close to my heart. One, we know as we get into this space, we're going to be talking to different types of folks and having conversations with different types of personas within an account than we have had before. Using cyber recovery solution as an example, yes, we want to talk to, you know, IT administrators and CIO who we've been talking to. But as Chad said, this is something that CISOs care about. This is something that security teams care about. That those are a different set of personas for us to market to, to communicate with, whose pain points we need to understand better. So that's an example of a change. Another one is moving from a... I mean, events like this are great, and we certainly love to be back in person, but in as-a-service model, you want to have much more frequent communication with your intended audiences. So we've moved to more of an always on-marketing motion leveraging our blog, leveraging other vehicles. And that's that has also been a transformation for us. >> On the marketing side, I'm curious, sorry, Dave. Chad, you brought up one of the big things that is a huge challenge for any organization and any industry with respect to the cybersecurity in that threat landscape is brand reputation. >> Yeah. >> Are you having more conversations at the CMO level? I'm just curious if they're involved in this. We got to make sure that we don't have... We're not the next one on the news because customers will churn like crazy. Is that at all part of the conversation than persona change? >> It is certainly part of it. But, you know, we don't want to be motivated by fear, right? We want to be motivated by preparation and securing the business and growing the business. So, you know, it is a sea level discussion to, you know, understand how we need to protect our critical data. But it's really from a lens of, you know, how do we grow and we grow more quickly? And you know, if you look at APEX overall, yes, we've made a lot of internal changes to get where we are and we're going to continue to make those. And I'll talk through some examples. But this is also a journey for our customers, right? The change to, you know, consuming by the drip, consuming APEX, consuming as-a-service, you could take two companies with identical size and an identical vertical, and they're going to have different priorities about how they want to consume this infrastructure and these services. So we're on that journey with them just as we have to transform ourselves internally, from the way that we do accounting, from the way that we do sales compensation, from the way that we actually build product. And in fact, we just changed up the model by which we're, you know, developing product in APEX today. So I'm about 90 days into my role in APEX. I came from the HCI business. And I'm here with my engineering leader who was also in the HCI business. So we were able to be fortunate enough to work in an organization that went from zero to 4 billion in pretty quickly. So, Hey, let's see if we can apply some of that learning to this. But it's an incredible partnership inside of Dell with people like Dell Digital and our transformation office. Because we've done things roughly the same way for about 30 years. And this is all very new to us. So it's pretty amazing journey. >> I'm interested in what's different. You weren't first to market. The public cloud guys might say, "Eh, it's not cloud." >> No. >> Okay, so how are you different than public cloud and how are you different from your traditional on-prem competitors? >> Again, I'll get us started and chime in. I would say... I'll take your first example. I want to go back to kind of what our customers... Where they want help from us and what are they're asking us for. As I said, the debate is over. They have told us pretty definitively, and our data and your data shows it, that they will and the data will continue to grow in all these different fragmented silos. What they want is an experience that orchestrated across all of these different environments, by a vendor that they trust, right? And that's what we are committed to delivering to them. That's our north star, that's where we're going. I would argue that any one of the hyperscalers don't have incentives to kind of make that same experience happen across all those different environments. A vendor like Dell, who has been trusted by many years... You know, for many years from our customer, who doesn't have a single dog in the race, but is looking to partner with folks across the entire ecosystem, is looking to innovate with our software, our services, and our infrastructure is best positioned to help them orchestrate across. >> Yeah. Well, you know, if you're wondering what's different, you really have to look at what the value proposition is for public clouds versus keeping data on-prem or keeping it in a place where it's accessible to multiple clouds. You know, I think if you haven't been under a rock here at the show, you know it is all about multi-cloud, and you know that we're, you know, absolutely embracing it from, you know, Project Alpine where we're putting storage endpoints in public cloud, to what we're doing with APEX and our data storage services and the move of our customers into co-locations where the data can be accessible to multiple clouds. I think that getting the commerce capabilities in place that we've done over the course of the last year is a great first step. But look for us to double down on the day two management and operations, using that platform that we've created for APEX. And that's going to allow us to create more velocity and bring more solutions into the fold more quickly, and then provide more day two management optimization operation of the solutions by our customers. >> Okay. Sorry. So definitely agree with the public cloud. And I got to trust them to do my multi-cloud or what I call super-cloud. What about your traditional competitors? Is it the normal sort of what we'd expect for the Dell differentiators portfolio, supply chain, et cetera, or are there APEX specific differentiators? >> Yeah, absolutely. Yeah, so there are absolutely the Dell differentiators of the breadth of our sales force through both our direct sales teams as well as our partners, our secure supply chain, our services team, and the expertise that they've built, which we're obviously bringing to bear with this market and this offer. Those are kind of the Dell wide advantages that we bring to bear with this. But specifically for APEX against the traditional on-prem competitors, I would say the simplicity with which we are bringing our offers to market is a differentiator for us. And it's one that our customers in the past year have retreated back to us. So the commerce experience that Chad was just talking about, we have made very conscious efforts to simplify and abstract the way that complexity from our customers, so that they are picking very easy to understand outcomes that they care about. And then not really worry about the peace parts, whether it's the hardware, the software, or the services that help make that service level outcome happen. I would argue, you know, some of the other competitors, traditional competitors that we have haven't done that. And it's more of a... You know, that complexity is still there. And what we hear from our customers is, I want the simplicity and agility that public cloud provides. That's something that hyperscalers did get right. And we're bringing that experience to our infrastructure. >> Yeah. Like I think the other way that we'll differentiate ourselves is going to be by the breadth of the solutions, right? So we've got a tremendous amount of IP in solutions like cyber recovery, right? This wasn't a new thing for us. This is something we've been doing for a few years as there's tremendous consulting capabilities, services capabilities, the underlying products of course. Well, there's a pipeline of solutions lined up behind that. So as we move into high performance computer as-a-service, MLOps as-a-service, we can draw on those solutions that we've offered, but in a very custom way in the past now at a high velocity manner in the console. >> Well, the high velocity these days is critical. As we've seen the last two years, things have changed so dramatically for customers in every industry that needed to pivot with speed and accelerate their transformation. >> And the transparency. Right? So going back to his example, having that price transparency. You can go to our website and look at the pricing, pick in the two or three very simple options and see it right there and order it through the console. In a matter of minutes versus, you know, wait for two weeks to get the code and then wait for a month to get the hardware, and then wait for the services team to show up. So what we are hearing... I mean, we have truly been able to take deployments that used to take several months to a matter of days. And so that's how the simplicity kind of, you know, pays off not only in that initial deployment, but over the course of the subscription, the day two operations that Chad was just talking about and the innovation and the work that we're doing to simplify their lives in that process, allow them to focus in other areas. >> Oh, absolutely. That time to value, time to market has never been more critical. And the ability, to your point, Akanksha, to allow folks to be able to focus more on the strategic initiatives that will actually help move the business for... Add value, move the business forward and allow it to be competitive and differentiate itself is critical for everybody in every industry. Chad, I wanted to kind of pivot on multi-cloud for a second. You talked about that. And we had Chuck Whit on yesterday. He was talking about, you know, multi-cloud. A lot of organizations, many, many, many in multi-cloud by default. But what Dell wants to do is change that, multi-cloud by design. Is APEX going to be a facilitator of multi-cloud by design? Talk to us about that for customers. >> We absolutely will be. So if you look at what made customers multi-cloud by default, it's them going for the services that exist in the cloud and looking for best of breed services. Whether it's machine learning, speech recognition, database, they're going to those best of breed players. And so the value proposition for us is since you're in those clouds, you want access to your data and you want it centrally, so you can see it, leverage it, use it from any of those clouds, but you may have other reasons for keeping your data or even your compute on-prem or in a co-location. It could be data sovereignty, it could be policy compliance, it could be data gravity. So we want to make the concept of having your workloads or your data anywhere, very seamless for our customers, right? So it's really embracing the concept of multi-cloud and making it easier. >> The cyber recovery solution is really interesting to me. I was talking to one of the partners here and they said, "Dave, this was a really good show for us." And they probably had a quasi competitive solution. I don't really know. But like a lot of customers and, you know, got a lot of leads out of it. So it's the hot topic and that's what they said. This is cyber, everybody wants cyber. So how did that solution come together? Because I know you... You really... You've always been security conscious. But I never really full cracked the security solution. And now here it is in APEX, it's like, boom, out of the box or out of the service. How'd that come about? >> It really started back in 2014, specifically. It's funny when you can point to an event where, you know, something started like this. So there was a fairly high profile ransomware attack in 2014. And that caused us to look at the assets that we had from our data protection portfolio, from a software and storage perspective and say, "Hey, we can put something together that can really address this, right? Through novel use of existing technology." So we built out reference architectures. We built out the consulting service on how you protect your data. We partnered and built software to be able to secure the data in an air gaped imutable vault and offer the services to be able to manage that, monitor that, restore the data when needed. So we did that in a very custom way for years. In fact, as I said, over 2,000 systems deployed this way. So having a vehicle like APEX that has the as-a-service capability built in, the subscription capability built in, the ease and velocity of purchasing and operating was really a natural fit. So you know, we expect this is going to be a very high volume solution for us. >> Great. Awesome. >> Akanksha, can you talk a little bit about the partner ecosystem involved here in APEX? You know, when I think about ransomware in data protection, I think organizations need to be able to protect apps, users, data platforms. But we think of how data is so spread out, customers want that single pane of glass to be able to manage all that and know that that data is protected. Talk to us about how you're working with partners. I know the partner ecosystem at Dell's huge. How are you working with partners and how can they build upon APEX? >> Yeah So our partners are a very important part of our ecosystem. They help expand our reach. They also help complement our capabilities. You know, for example, in specific verticals. They may have services or expertise in a particular area. For the APEX portfolio, we actually offer a wide variety of ways for partners to engage with us. Starting out, they could refer our solutions and refer, you know, some of our services, if they want to take more of an advisory role in some capacity. They could resell our services with additional services included. In this scenario, for example, they would leverage our console, include some of their services in there and then offer it to their end customers. They could host APEX offers in their own data center or in a co-lo data center and build their practice on top of it. A lot of our partners and customers, we've got kind of joint customer partners that for example, have built a healthcare practice on top of an APEX solution, where they've added their services or built their business on top of it. And then finally, there's of course, technology and ISV partners, right? And that is where we might leverage, you know, some of their technology, built it to be part of a service or a solution that we're doing and join the go-to market. So I think the answer is lots of ways for partners to engage with APEX. And we absolutely are engaging with them in a wide variety of ways. And I think cyber recovery is no different. >> Well, there must be not a dull moment with what you guys have going on with APEX. Thank you for taking some time to talk to us about that. Sounds like the momentous year that you've had is going to continue. And it sounds like you've gotten great feedback from the customers and the partner so far. Thank you for joining "theCube" and telling us what's going on. And we can't wait to hear more next year. I'm sure there will be lots more next year. >> Yes indeed. >> Absolutely. Thank you very much. >> For our guests and Dave Vellante, I'm Lisa Martin, and you're watching "theCube's" coverage of Dell Technologies World 2022, live from Las Vegas. Stick around, we'll be right back with our next guest. (upbeat music)

>>The cube presents. Dell technologies world brought to you by Dell. >>Welcome to Las Vegas. Lisa Martin, with Dave Volante. The cube is live at Dell technologies world 2022. Dave, hope you say live, live <laugh>. We are live. We are in person. We are three-D. We are also here on the first day of our coverage with an eight time, right? Eight time cube alum, GA Norris joins us the senior vice president of edge portfolio solutions at Dell technologies. Welcome back our friend. >>Thank you. It's great to be here in this forum with live people, you know, and 3d, >>Isn't it. We're amazing. We're not, we're not via a screen. This is actually real. So Gill a a lot, a lot of buzz, great attendance at this first event, since 20, lot's been going on since then, we're talking a lot about edge. It's not new, but there's a lot changing what's going on there. >>Well, you know, edge has been around for a while. Um, actually since, you know, the beginning of time people were doing, you know, compute and, and applications, they in the, um, in the physical space where data it, but more and more, um, data is based on sensors in cameras and machine vision. And if you wanna make real time decisions, there's a few reasons why you can't just send everything back to a data center or a cloud. Maybe you don't have the right latency, maybe, um, you it's too costly. Maybe you don't have the right end with maybe you have security challenges, maybe have compliance challenges. So the world's moving more and more resources towards where the data is created and to make real time decisions and to generate new business values, things are changing and they're becoming much more, um, um, involved than before, much more. Um, so basically that that's, what's changing. You know, we need to deal with distributed architectures much more than we needed before. >>I think one of the things we've learned in the last very dynamic two years is that access to realtime data is no longer a nice to have it's table stakes for whether we're talking about retail, healthcare, et cetera. So that the, the realtime data access is critical for everybody to these days. >>Right? And it, it could be a real time decision, or it could even be data collection either way. You need to place some device, some comput next to the source. And then, you know, you have a lot of them and you just multiply by multiple use cases and you be, you basically, you have a very complex problem to solve. And if you ask me what's new is that complexity is big coming more and more, um, critical to solve >>Critical. >>Oh, go ahead, please. >>I was just gonna say, talk to me about some of the, from a, from a complexity resolution perspective, what are some of the things that Dell is doing to help organizations as they spread out to the edge more to meet that consumer demand, but reduce that complexity from an infrastructure standpoint. >>So we focus on simplifying. I think that's what people need right now. So there are two things we do. We, we optimize our products, um, whether they need regularization or different temperature envelopes or, uh, management capability, remote management capability, and we create solutions. And so we develop, um, solutions that look at specific, um, outcomes and we size it and we create deployment guides. Um, we do everything we can, um, to simplify the, uh, the edge uses for our customers. >>You know, you guys is talking about, it's not new. I, and I know you do a lot in retail. I think of like the NCR cash register as the, the original edge, you know, but there's other use cases. Uh there's you Gil, you and I have talked about AI inferencing in, in real time, there was a question today in the analyst forum, uh, I think it went to Jeff or nobody wanted to take it. No, maybe it was Michael, but the metaverse, but that there's edge space is the edge industrial I OT. So how do you, I mean, the Tam is enormous. How do you think about the use cases? Are there ones that, that aren't necessarily sort of horizontal for you that you don't go after, like EVs and TA the cars? Or how are you thinking about >>It? Depends. I agree that the, uh, edge business is very verticalized. Um, at the same time, there are very, uh, there is, there are themes that emerge across every industry. Um, so we're trying to solve things horizontally being Dell, we need to solve for, um, repeatability and scale, but we do package, you know, vertical solutions on top of them because that's what people need. Um, so for example, you know, you said, um, NCR being the, uh, the original edge. If I asked you today, name how many applications are, are running in a retail store to enable your experience? You'd say, well, there's self checkout. Maybe there is a, um, fraud detection, >>Let's say a handful >>It's handful. The fact is it's not, it's about 30 different applications, 30 that are running. So you have, you know, digital labels and you have, you know, a curbside delivery and you have inventory management and you have crowd management and you have safety and security. And what happens today is that every one of those solar is purchased separately and deployed separately and connected to the network separately and secured separately. Hence you see the problem, right? And so I know what we do, and we create a solution. For example, we see, okay, infrastructure, what can we consolidate onto an infrastructure that could scale over time? And then we look at it in the context of a solution. So, you know, the solution we're announcing, or we announced last week does just that on the left side, it looks at a consolidated infrastructure based on VxRail and VMware stack. So you can run multiple applications on the right side, it working with a company called deep north for Inso analytics and actually people that, um, and the show they can go and see this in action, um, in our, um, you know, fake retail store, uh, back at the edge booth. Um, but the point is those elements of siloed applications and the need to consolidate their true for every industry. And that's what we're trying to solve for. >>I was just wondering, you said they're true for every industry. Every industry is facing the same challenges there. What, what makes retail so prime for transformation right now? >>That's a great question. So, you know, using my example from before, if you are faced with this set, have a shopper that buys online and they now are coming back to the stores and they need to, they want the same experience. They want the stuff that they search for. They want it available to them. Um, and in fact, we research that 80% of people say, if they have a bad experience will not come back to a retail store. So you've got all of those use cases that you need to put to, you've got this savvy shopping that comes in, you've got heightened labor costs. You've got a supply chain problem in most of those markets, labor >>Shortages as >>Well. It's a perfect storm. And you wanna give an experience, right? So CIOs are looking at this and they go, how do I do all of that? Um, and they, they, as I said before, the key management, the key problem is management of all of those things is why they can innovate faster. And so retail is in this perfect storm where they need to innovate and they want to innovate. And now they're looking for options and we're here to help them. >>You know, a lot of times we talk about the in industrial IOT, we talk about the it and the OT schism. Is there a similar sort of dissonance between it, your peeps, Dell's traditional market, and what's happening, you know, at the near edge, the retail infrastructure sort of different requirements. How are you thinking about that and managing that >>About, um, 50% of edge projects today are, are somehow involving it. Um, usually every project will involve it for networking and security, so they have to manage it either way. And today there's a lot of what we used to call shadow it. When we talked about cloud, this has happens at the edge as well. Now this happened for a good reason because the expertise are the OT people expertise on the, the specific use case. It's true for manufacturing. It's also for true for, for retail. Um, our traditional audience is the it audience and, and we will never be able to merger two worlds unless it was better able to service the OT buyers. And even in the show, I I've had multiple conversations today. We, with people to talk about the divide, how to bring it together, it will come together when it can deliver a better service to the OT, um, constituents. And that's definitely a job for Dell, right? This is what we do. If we enable our it buyer to do a better job in servicing the OT crowd or their business crowd in retail, um, more innovation will happen, you know, across the, those different dimensions. So I'm happy you asked that because that's actually part of the mission we're taking on. >>Where is one of the things I think about when you, you talk about that consumer experience and we're very demanding as consumers. We wanna ha as you described, we wanna have the same experience we expect to have that regardless of where we are. And if that doesn't happen, you, you mentioned that number of 80% of people's survey said, if I have a bad experience with a merchant, I'm out, I'm going somewhere else. Right. So where is the rest of the Csuite in the conversation? I can think of, um, a COO the chief marketing officer from brand value, brand reputation perspective. Are you talking with those folks as well to help make the connective so reality? >>Um, I, I, I don't know that we're having those conversation with those business owners. We we're a, um, a system, an infrastructure company. So, you know, we get involved once they understand, you know, what they want to do. We just look at it in. And so if you solve it one way, it's gonna be one outcome. Maybe there is a better way to look at it. Maybe there's an architecture, maybe there's a more, you know, thoughtful way to think about, you know, the problems before they happen. And, um, but the fact that they're all looking shows you, that their business owners are very, very concerned with, with this reality, their >>Key stakeholders. Can >>We come back to your announcement? Can you, can we unpack that a little bit, uh, for those who might not be familiar with it? What, what, what is it called again? And give us a peel, the onion a little bit Gil. Yeah. >>So, so we call it a Dell technologies validated design. Um, it is essentially reference architecture. Um, we take a use case, we size it. So we, you know, we, um, we save customers, the effort of, of testing and sizing. We document the deployment step by step. We just make it simpler. And as says, before we look for consolidation, so we took a VXL, which is our leading ACI product based on VMware technology with a VMware application management stack with Tansu. Um, and then we, we, we look at that as the infrastructure, and then we test it with a company called deep north and deep north, um, are, um, store analytics. So through machine vision, they can tell you where people are queuing up. If there is somebody in the store that needs help and nobody's approaching, if there is a water spill and somebody might, you know, slip and hurt themselves, if a fridge is open and something may get spot. >>And so all of those things together through machine vision and realtime decisions can have this much better experience. So we put all of this together, we created a design and now it's out there in the market for our partners to use for our customers to use. Um, this is an extension of our manufacturing solutions, where we did the same thing. We partner with a company called PTC. I know of obviously in a company called Litmos, um, to create, um, industrial and the leading solution. So this whole word of solutioning is supposed to look at the infrastructure and a use case and bring them together and document in a way that simplifies things for >>Customers. Do you ever see that becoming a Aku at some point in time or, >>Um, personal, if you ask me? I don't think so. And the reason is there's still a lot of variability in those and skewing, but that's a very formal, you know, internal discussion. Yeah. Um, the point is we are, we want people to buy as much of it as they need to, and, and we really want to help them if Aku could help them, we will get there, but we need to see repeatability before creating skews. >>Can you give us an example of a, of a retail or a manufacturing customer that's using this Dell validated design, this DVD, and that really has reduced or eliminated that complexity that was there before. >>So this solution is new. I mean, it's brand new, we just announced it. So, no, but, um, I don't know what names I can call out, cuz referenceability is probably examples though about generic, but I will tell you that most of the large retailers in the us are based in their stores on Dell technologies. Um, a lot of the trail is in, in those stores and you're talking about thousands of locations with remote management. Um, what we're doing here is we're taking it to the next step by looking at new use cases that they have not been implementing before and saying, look, same infrastructure is valid. You know, scalable is it's scalable. And here are the new use cases with machine vision and other things that here is how you do that. But we're seeing a lot of success in retail in the last few years. >>So what should we expect looking forward, you know, any gaps that customers are asking for trying to fill? What, what two to three years out, what should we expect? >>Um, I think we're gonna stay very true to our simplification message. We want to help people simplify. So if it's simplifying, um, maintenance, if it's simplifying management, if it's simplifying through solutioning, you're gonna see us more and more and more, um, investing in simplification of edge. Um, and that's through our own IP, through our partnerships. Um, there, there is a lot more coming if, if I may say it myself, but, but it's, it's a little too early to, uh, to talk about it. >>So for those folks that are here at the show that get to see it and play with it and touch it and feel it, what would you say some of the biggest impacts are that this technology can deliver tomorrow? >>Well, first of all, it's enabling to do what they want. See, we don't have to go and, and tell people, oh, you probably really need to move things through the edge. They know they need to do it. Our job is to tell them how to do it in a secure way, in a simplified way. So that's, that's a nice thing about this, this market it's happening, whether we want it or not. Um, people in this show can go see some things in action. They can see the solution in action. They can see the manufacturing solution in action and even more so. And I forgot to say part of our announcement was a set of solution centers in Limerick island and in Singapore, that was just open. And soon enough in Austin, Texas saw that, and we will have people come in and have the full experience of IOT OT and edge device devices in action. So AR and VR, I T IEN technology and scanning technology. So they could be, um, thinking about the art of the possible, right? Thinking about this immersive experience that will help them invent with us. And so we're expecting a lot of innovation to come out of those conversations for us and for them. >>So doing a lot of testing before deployment and really gleaning that testing >>Before deployment solution architecture, just ideation, if they're not there yet. So, and I've just been to Singapore in one of those, um, they asked me to, um, pretend I was a, um, retail ski enter in a distribution center and I didn't do so well, but I was still impressed with the technology. So, >>Well, eight time Q alumni. Now you have a career to fall back on if you need to. Exactly. >><laugh> >>GA it's been great to have you. Thank you so much for coming back, talking to us about what's new on day one of Dell technologies world 22. Thank >>You for having me again, >>Our pleasure for Dave Volante. I'm Lisa Martin, coming to you live from the Venetian in Las Vegas at Dell technologies world 2022. This is day one of our coverage stick around Dave and I will be right back with our next guest.

(upbeat music) >> Let's kick things off. We're here at Mike Capuano the CMO of Pluribus Networks, and Ami Badani VP of Networking, Marketing, and Developer of Ecosystem at NVIDIA. Great to have you welcome folks. >> Thank you. >> Thanks. >> So let's get into the the problem situation with cloud unified networking. What problems are out there? What challenges do cloud operators have Mike? Let's get into it. >> The challenges that we're looking at are for non hyperscalers that's enterprises, governments Tier 2 service providers, cloud service providers. And the first mandate for them is to become as agile as a hyperscaler. So they need to be able to deploy services and security policies in seconds. They need to be able to abstract the complexity of the network and define things in software while it's accelerated in hardware. Really ultimately they need a single operating model everywhere. And then the second thing is they need to distribute networking and security services out to the edge of the host. We're seeing a growth cyber attacks. It's not slowing down. It's only getting worse and solving for this security problem across clouds is absolutely critical. And the way to do it is to move security out to the host. >> With that goal in mind, what's the Pluribus vision how does this tie together? >> So basically what we see is that this demands a new architecture and that new architecture has four tenets. The first tenet is unified and simplified cloud networks. If you look at cloud networks today, there's sort of like discreet bespoke cloud networks per hypervisor, per private cloud, edge cloud, public cloud. Each of the public clouds have different networks, that needs to be unified. If we want these folks to be able to be agile they need to be able to issue a single command or instantiate a security policy across all of those locations with one command and not have to go to each one. The second is, like I mentioned distributed security. Distributed security without compromise, extended out to the host is absolutely critical. So micro segmentation and distributed firewalls. But it doesn't stop there. They also need pervasive visibility. It's sort of like with security you really can't see you can't protect you can't see. So you need visibility everywhere. The problem is visibility to date has been very expensive. Folks have had to basically build a separate overlay network of taps, packet brokers, tap aggregation infrastructure, that really needs to be built in to this unified network I'm talking about. And the last thing is automation. All of this needs to be SDN enabled. So this is related to my comment about abstraction. Abstract the complexity of all these discreet networks whatever's down there in the physical layer. I don't want to see it. I want to abstract it. I want to define things in software but I do want to leverage the power of hardware to accelerate that. So that's the fourth tenet is SDN automation. >> Mike, we've been talking on theCUBE a lot about this architectural shift and customers are looking at this. This is a big part of everyone who's looking at cloud operations, NextGen. How do we get there? How do customer customers get this vision realized? >> That's a great question. And I appreciate the tee up. We're here today for that reason. We're introducing two things today. The first is a unified cloud networking vision. And that is a vision of where Pluribus is headed with our partners like NVIDIA long term. And that is about deploying a common operating model SDN enabled, SDN automated, hardware accelerated across all clouds. And whether that's underlay and overlay switch or server, any hypervisor infrastructure containers, any workload doesn't matter. So that's ultimately where we want to get. And that's what we talked about earlier. The first step in that vision is what we call the unified cloud fabric. And this is the next generation of our adaptive cloud fabric. And what's nice about this is we're not starting from scratch. We have an award-winning adaptive cloud fabric product that is deployed globally. And in particular, we're very proud of the fact that it's deployed in over 100 Tier 1 mobile operators as the network fabric for their 4G and 5G virtualized cores. We know how to build carrier grade networking infrastructure. What we're doing now to realize this next generation unified cloud fabric is we're extending from the switch to this NVIDIA BlueField-2 DPU. We know there's. >> Hold that up real quick. That's a good prop. That's the BlueField NVIDIA card. >> It's the NVIDIA BlueField-2 DPU, data processing unit. What we're doing fundamentally is extending our SDN automated fabric, the unified cloud fabric, out to the host. But it does take processing power. So we knew that we didn't want to do we didn't want to implement that running on the CPUs which is what some other companies do. Because it consumes revenue generating CPUs from the application. So a DPU is a perfect way to implement this. And we knew that NVIDIA was the leader with this BlueField-2. And so that is the first, that's the first step into getting, into realizing this vision. >> NVIDIA has always been powering some great workloads of GPUs, now you got DPUs. Networking and NVIDIA as here. What is the relationship with Pluribus? How did that come together? Tell us the story. >> We've been working with Pluribus for quite some time. I think the last several months was really when it came to fruition. And what Pluribus is trying to build and what NVIDIA has. So we have, this concept of a blue field data processing unit, which, if you think about it, conceptually does really three things, offload, accelerate, and isolate. So offload your workloads from your CPU to your data processing unit, infrastructure workloads that is. Accelerate, so there's a bunch of acceleration engines. You can run infrastructure workloads much faster than you would otherwise. And then isolation, So you have this nice security isolation between the data processing unit and your other CPU environment. And so you can run completely isolated workloads directly on the data processing unit. So we introduced this, a couple years ago. And with Pluribus we've been talking to the Pluribus team for quite some months now. And I think really the combination of what Pluribus is trying to build, and what they've developed around this unified cloud fabric fits really nicely with the DPU and running that on the DPU and extending it really from your physical switch all the way to your host environment, specifically on the data processing unit. So if you think about what's happening as you add data processing units to your environment. So every server we believe over time is going to have data processing units. So now you'll have to manage that complexity from the physical network layer to the host layer. And so what Pluribus is really trying to do is extending the network fabric from the host from the switch to the host and really have that single pane of glass for network operators to be able to configure, provision, manage all of the complexity of the network environment. So that's really how the partnership truly started. And so it started really with extending the network fabric and now we're also working with them on security. If you sort of take that concept of isolation and security isolation, what Pluribus has within their fabric is the concept of micro segmentation. And so now you can take that extend it to the data processing unit and really have isolated micro segmentation workloads whether it's bare metal, cloud native environments, whether it's virtualized environments, whether it's public cloud, private cloud, hybrid cloud. So it really is a magical partnership between the two companies with their unified cloud fabric running on the DPU. >> You know what I love about this conversation is it reminds me of when you have these changing markets. The product gets pulled out of the market and you guys step up and create these new solutions. And I think this is a great example. So I have to ask you how do you guys differentiate what sets this apart for customers? What's in it for the customer? >> So I mentioned three things in terms of the value of what the BlueField brings. There's offloading, accelerating and isolating. And that's sort of the key core tenets of BlueField. So that, if you sort of think about what BlueField what we've done, in terms of the differentiation. We're really a robust platform for innovation. So we introduced BlueField-2 last year. We're introducing BlueField-3 which is our next generation of blue field. It'll have 5X the ARM compute capacity. It will have 400 gig line rate acceleration, 4X better crypto acceleration. So it will be remarkably better than the previous generation. And we'll continue to innovate and add, chips to our portfolio every 18 months to two years. So that's sort of one of the key areas of differentiation. The other is that if you look at NVIDIA, what we're sort of known for is really known for our AI, our artificial intelligence and our artificial intelligence software, as well as our GPU. So you look at artificial intelligence and the combination of artificial intelligence plus data processing. This really creates faster, more efficient secure AI systems from, the core of your data center, all the way out to the edge. And so with NVIDIA we really have these converged accelerators where we've combined the GPU, which does all your AI processing with your data processing with the DPU. So we have this convergence really nice convergence of that area. And I would say the third area is really around our developer environment. One of the key, one of our key motivations at NVIDIA is really to have our partner ecosystem embrace our technology and build solutions around our technology. So if you look at what we've done with the DPU we've created an SDK, which is an open SDK called DOCA. And it's an open SDK for our partners to really build and develop solutions using BlueField and using all these accelerated libraries that we expose through DOCA. And so part of our differentiation is really building this open ecosystem for our partners to take advantage and build solutions around our technology. >> What's exciting is when I hear you talk it's like you realize that there's no one general purpose network anymore. Everyone has their own super environment, super cloud or these new capabilities. They can really craft their own I'd say custom environment at scale with easy tools. And it's all kind of that again this is the new architecture Mike, you were talking about. How does customers run this effectively, cost effectively? And how do people migrate? >> I think that is the key question. So we've got this beautiful architecture. Amazon Nitro is a good example of a SmartNIC architecture that has been successfully deployed but, enterprises and Tier 2 service providers and Tier 1 service providers and governments are not Amazon. So they need to migrate there and they need this architecture to be cost of effective. And that's super key. I mean, the reality is DPU are moving fast but they're not going to be deployed everywhere on day one. Some servers will have have DPUs right away. Some servers will have DPUs in a year or two. And then there are devices that may never have DPUs. IOT gateways, or legacy servers, even mainframes. So that's the beauty of a solution that creates a fabric across both the switch and the DPU. And by leveraging the NVIDIA BlueField DPU what we really like about it is, it's open and that drives cost efficiencies. And then, with this our architectural approach effectively you get a unified solution across switch and DPU, workload independent. It doesn't matter what hypervisor it is. Integrated visibility, integrated security and that can create tremendous cost efficiencies and really extract a lot of the expense from a capital perspective out of the network as well as from an operational perspective because now I have an SDN automated solution where I'm literally issuing a command to deploy a network service, or to deploy a security policy and is deployed everywhere automatically saving the network operations team and the security operations team time. >> So let me rewind that 'cause that's super important. Got the unified cloud architecture. I'm the customer, it's implemented. What's the value again, take me through the value to me. I have a unified environment. What's the value? >> I mean the value is effectively, there's a few pieces of value. The first piece of value is I'm creating this clean demark. I'm taking networking to the host. And like I mentioned, we're not running it on the CPU. So in implementations that run networking on the CPU there's some conflict between the DevOps team who own the server, and the NetOps team who own the network because they're installing software on the CPU stealing cycles from what should be revenue generating CPUs. So now by terminating the networking on the DPU we create this real clean demark. So the DevOps folks are happy because they don't necessarily have the skills to manage network and they don't necessarily want to spend the time managing networking. They've got their network counterparts who are also happy the NetOps team because they want to control the networking. And now we've got this clean demark where the DevOps folks get the services they need and the NetOps folks get the control and agility they need. So that's a huge value. The next piece of value is distributed security. This is essential I mentioned it earlier, pushing out micro segmentation and distributed firewall basically at the application level, where I create these small segments on an application by application basis. So if a bad actor does penetrate the perimeter firewall they're contained once they get inside. 'Cause the worst thing is a bad actor penetrates perimeter firewall and can go wherever they want in wreak havoc. And so that's why this is so essential. And the next benefit obviously is this unified networking operating model. Having an operating model across switch and server, underlay and overlay, workload agnostic, making the life of the NetOps teams much easier so they can focus their time on really strategy instead of spending an afternoon deploying a single VLAN for example. >> Awesome, and I think also for my stand point I mean perimeter security is pretty much, that out there, I guess the firewall still out there exists but pretty much they're being breached all the time the perimeter. You have to have this new security model. And I think the other thing that you mentioned the separation between DevOps is cool because the infrastructure is code is about making the developers be agile and build security in from day one. So this policy aspect is huge new control plan. I think you guys have a new architecture that enables the security to be handled more flexible. That seems to be the killer feature here. >> If you look at the data processing unit, I think one of the great things about sort of this new architecture it's really the foundation for zero trust. So like you talked about the perimeter is getting breached. And so now each and every compute node has to be protected. And I think that's sort of what you see with the partnership between Pluribus and NVIDIA is the DPU is really the foundation of zero trust and Pluribus is really building on that vision with allowing sort of micro-segmentation and being able to protect each and every compute node as well as the underlying network. >> This is super exciting. This is illustration of how the market's evolving architectures are being reshaped and refactored for cloud scale and all this new goodness with data. So I got to ask how you guys go into market together. Michael, start with you. What's the relationship look like in the go to market with NVIDIA? >> We're super excited about the partnership. Obviously we're here together. We think we've got a really good solution for the market so we're jointly marketing it. Obviously we appreciate that NVIDIA's open that's sort of in our DNA, we're about a open networking. They've got other ISVs who are going to run on BlueField-2. We're probably going to run on other DPUs in the future. But right now we feel like we're partnered with the number one provider of DPUs in the world and super excited about making a splash with it. >> Oh man NVIDIA got the hot product. >> So BlueField-2 as I mentioned was GA last year, we're introducing, well we now also have the converged accelerator. So I talked about artificial intelligence our artificial intelligence software with the BlueField DPU, all of that put together on a converged accelerator. The nice thing there is you can either run those workloads, so if you have an artificial intelligence workload and an infrastructure workload, you can work on them separately on the same platform or you can actually use you can actually run artificial intelligence applications on the BlueField itself. So that's what the converged accelerator really brings to the table. So that's available now. Then we have BlueField-3 which will be available late this year. And I talked about sort of, how much better that next generation of BlueField is in comparison to BlueField-2. So we'll see BlueField-3 shipping later on this year. And then our software stack which I talked about, which is called DOCA. We're on our second version, our DOCA 1.2 we're releasing DOCA 1.3 in about two months from now. And so that's really our open ecosystem framework. So allow you to program the BlueField. So we have all of our acceleration libraries, security libraries, that's all packed into this SDK called DOCA. And it really gives that simplicity to our partners to be able to develop on top of BlueField. So as we add new generations of BlueField, next year we'll have another version and so on and so forth. DOCA is really that unified layer that allows BlueField to be both forwards compatible and backwards compatible. So partners only really have to think about writing to that SDK once. And then it automatically works with future generations of BlueField. So that's sort of the nice thing around DOCA. And then in terms of our go to market model we're working with every major OEM. Later on this year you'll see, major server manufacturers releasing BlueField enabled servers, so more to come. >> Awesome, save money, make it easier, more capabilities, more workload power. This is the future of cloud operations. >> And one thing I'll add is we are, we have a number of customers as you'll hear in the next segment that are already signed up and will be working with us for our early field trial starting late April early May. We are accepting registrations. You can go to www.pluribusnetworks.com/eft. If you're interested in signing up for being part of our field trial and providing feedback on the product >> Awesome innovation and networking. Thanks so much for sharing the news. Really appreciate, thanks so much. In a moment we'll be back to look deeper in the product the integration, security, zero trust use cases. You're watching theCUBE, the leader in enterprise tech coverage. (upbeat music)

>>Everyone wants a cloud operating model. Since the introduction of the modern cloud. Last decade, the entire technology landscape has changed. We've learned a lot from the hyperscalers, especially from AWS. Now, one thing is certain in the technology business. It's so competitive. Then if a faster, better, cheaper idea comes along, the industry will move quickly to adopt it. They'll add their unique value and then they'll bring solutions to the market. And that's precisely what's happening throughout the technology industry because of cloud. And one of the best examples is Amazon's nitro. That's AWS has custom built hypervisor that delivers on the promise of more efficiently using resources and expanding things like processor, optionality for customers. It's a secret weapon for Amazon. As, as we, as we wrote last year, every infrastructure company needs something like nitro to compete. Why do we say this? Well, Wiki Bon our research arm estimates that nearly 30% of CPU cores in the data center are wasted. >>They're doing work that they weren't designed to do well, specifically offloading networking, storage, and security tasks. So if you can eliminate that waste, you can recapture dollars that drop right to the bottom line. That's why every company needs a nitro like solution. As a result of these developments, customers are rethinking networks and how they utilize precious compute resources. They can't, or won't put everything into the public cloud for many reasons. That's one of the tailwinds for tier two cloud service providers and why they're growing so fast. They give options to customers that don't want to keep investing in building out their own data centers, and they don't want to migrate all their workloads to the public cloud. So these providers and on-prem customers, they want to be more like hyperscalers, right? They want to be more agile and they do that. They're distributing, networking and security functions and pushing them closer to the applications. >>Now, at the same time, they're unifying their view of the network. So it can be less fragmented, manage more efficiently with more automation and better visibility. How are they doing this? Well, that's what we're going to talk about today. Welcome to changing the game for cloud networking made possible by pluribus networks. My name is Dave Vellante and today on this special cube presentation, John furrier, and I are going to explore these issues in detail. We'll dig into new solutions being created by pluribus and Nvidia to specifically address offloading, wasted resources, accelerating performance, isolating data, and making networks more secure all while unifying the network experience. We're going to start on the west coast and our Palo Alto studios, where John will talk to Mike of pluribus and AMI, but Donnie of Nvidia, then we'll bring on Alessandra Bobby airy of pluribus and Pete Lummus from Nvidia to take a deeper dive into the technology. And then we're gonna bring it back here to our east coast studio and get the independent analyst perspective from Bob Liberte of the enterprise strategy group. We hope you enjoy the program. Okay, let's do this over to John >>Okay. Let's kick things off. We're here at my cafe. One of the TMO and pluribus networks and NAMI by Dani VP of networking, marketing, and developer ecosystem at Nvidia. Great to have you welcome folks. >>Thank you. Thanks. >>So let's get into the, the problem situation with cloud unified network. What problems are out there? What challenges do cloud operators have Mike let's get into it. >>Yeah, it really, you know, the challenges we're looking at are for non hyperscalers that's enterprises, governments, um, tier two service providers, cloud service providers, and the first mandate for them is to become as agile as a hyperscaler. So they need to be able to deploy services and security policies. And second, they need to be able to abstract the complexity of the network and define things in software while it's accelerated in hardware. Um, really ultimately they need a single operating model everywhere. And then the second thing is they need to distribute networking and security services out to the edge of the host. Um, we're seeing a growth in cyber attacks. Um, it's, it's not slowing down. It's only getting worse and, you know, solving for this security problem across clouds is absolutely critical. And the way to do it is to move security out to the host. >>Okay. With that goal in mind, what's the pluribus vision. How does this tie together? >>Yeah. So, um, basically what we see is, uh, that this demands a new architecture and that new architecture has four tenants. The first tenant is unified and simplified cloud networks. If you look at cloud networks today, there's, there's sort of like discreet bespoke cloud networks, you know, per hypervisor, per private cloud edge cloud public cloud. Each of the public clouds have different networks that needs to be unified. You know, if we want these folks to be able to be agile, they need to be able to issue a single command or instantiate a security policy across all those locations with one command and not have to go to each one. The second is like I mentioned, distributed security, um, distributed security without compromise, extended out to the host is absolutely critical. So micro-segmentation and distributed firewalls, but it doesn't stop there. They also need pervasive visibility. >>You know, it's, it's, it's sort of like with security, you really can't see you can't protect what you can't see. So you need visibility everywhere. The problem is visibility to date has been very expensive. Folks have had to basically build a separate overlay network of taps, packet brokers, tap aggregation infrastructure that really needs to be built into this unified network I'm talking about. And the last thing is automation. All of this needs to be SDN enabled. So this is related to my comment about abstraction abstract, the complexity of all of these discreet networks, physic whatever's down there in the physical layer. Yeah. I don't want to see it. I want to abstract it. I wanted to find things in software, but I do want to leverage the power of hardware to accelerate that. So that's the fourth tenant is SDN automation. >>Mike, we've been talking on the cube a lot about this architectural shift and customers are looking at this. This is a big part of everyone who's looking at cloud operations next gen, how do we get there? How do customers get this vision realized? >>That's a great question. And I appreciate the tee up. I mean, we're, we're here today for that reason. We're introducing two things today. Um, the first is a unified cloud networking vision, and that is a vision of where pluribus is headed with our partners like Nvidia longterm. Um, and that is about, uh, deploying a common operating model, SDN enabled SDN, automated hardware, accelerated across all clouds. Um, and whether that's underlying overlay switch or server, um, hype, any hypervisor infrastructure containers, any workload doesn't matter. So that's ultimately where we want to get. And that's what we talked about earlier. Um, the first step in that vision is what we call the unified cloud fabric. And this is the next generation of our adaptive cloud fabric. Um, and what's nice about this is we're not starting from scratch. We have a, a, an award-winning adaptive cloud fabric product that is deployed globally. Um, and in particular, uh, we're very proud of the fact that it's deployed in over a hundred tier one mobile operators as the network fabric for their 4g and 5g virtualized cores. We know how to build carrier grade, uh, networking infrastructure, what we're doing now, um, to realize this next generation unified cloud fabric is we're extending from the switch to this Nvidia Bluefield to DPU. We know there's a, >>Hold that up real quick. That's a good, that's a good prop. That's the blue field and video. >>It's the Nvidia Bluefield two DPU data processing unit. And, um, uh, you know, what we're doing, uh, fundamentally is extending our SDN automated fabric, the unified cloud fabric out to the host, but it does take processing power. So we knew that we didn't want to do, we didn't want to implement that running on the CPU, which is what some other companies do because it consumes revenue generating CPU's from the application. So a DPU is a perfect way to implement this. And we knew that Nvidia was the leader with this blue field too. And so that is the first that's, that's the first step in the getting into realizing this vision. >>I mean, Nvidia has always been powering some great workloads of GPU. Now you've got DPU networking and then video is here. What is the relationship with clothes? How did that come together? Tell us the story. >>Yeah. So, you know, we've been working with pluribus for quite some time. I think the last several months was really when it came to fruition and, uh, what pluribus is trying to build and what Nvidia has. So we have, you know, this concept of a Bluefield data processing unit, which if you think about it, conceptually does really three things, offload, accelerate an isolate. So offload your workloads from your CPU to your data processing unit infrastructure workloads that is, uh, accelerate. So there's a bunch of acceleration engines. So you can run infrastructure workloads much faster than you would otherwise, and then isolation. So you have this nice security isolation between the data processing unit and your other CPU environment. And so you can run completely isolated workloads directly on the data processing unit. So we introduced this, you know, a couple of years ago, and with pluribus, you know, we've been talking to the pluribus team for quite some months now. >>And I think really the combination of what pluribus is trying to build and what they've developed around this unified cloud fabric, uh, is fits really nicely with the DPU and running that on the DPU and extending it really from your physical switch, all the way to your host environment, specifically on the data processing unit. So if you think about what's happening as you add data processing units to your environment. So every server we believe over time is going to have data processing units. So now you'll have to manage that complexity from the physical network layer to the host layer. And so what pluribus is really trying to do is extending the network fabric from the host, from the switch to the host, and really have that single pane of glass for network operators to be able to configure provision, manage all of the complexity of the network environment. >>So that's really how the partnership truly started. And so it started really with extending the network fabric, and now we're also working with them on security. So, you know, if you sort of take that concept of isolation and security isolation, what pluribus has within their fabric is the concept of micro-segmentation. And so now you can take that extended to the data processing unit and really have, um, isolated micro-segmentation workloads, whether it's bare metal cloud native environments, whether it's virtualized environments, whether it's public cloud, private cloud hybrid cloud. So it really is a magical partnership between the two companies with their unified cloud fabric running on, on the DPU. >>You know, what I love about this conversation is it reminds me of when you have these changing markets, the product gets pulled out of the market and, and you guys step up and create these new solutions. And I think this is a great example. So I have to ask you, how do you guys differentiate what sets this apart for customers with what's in it for the customer? >>Yeah. So I mentioned, you know, three things in terms of the value of what the Bluefield brings, right? There's offloading, accelerating, isolating, that's sort of the key core tenants of Bluefield. Um, so that, you know, if you sort of think about what, um, what Bluefields, what we've done, you know, in terms of the differentiation, we're really a robust platform for innovation. So we introduced Bluefield to, uh, last year, we're introducing Bluefield three, which is our next generation of Bluefields, you know, we'll have five X, the arm compute capacity. It will have 400 gig line rate acceleration, four X better crypto acceleration. So it will be remarkably better than the previous generation. And we'll continue to innovate and add, uh, chips to our portfolio every, every 18 months to two years. Um, so that's sort of one of the key areas of differentiation. The other is the, if you look at Nvidia and, and you know, what we're sort of known for is really known for our AI artificial intelligence and our artificial intelligence software, as well as our GPU. >>So you look at artificial intelligence and the combination of artificial intelligence plus data processing. This really creates the, you know, faster, more efficient, secure AI systems from the core of your data center, all the way out to the edge. And so with Nvidia, we really have these converged accelerators where we've combined the GPU, which does all your AI processing with your data processing with the DPU. So we have this convergence really nice convergence of that area. And I would say the third area is really around our developer environment. So, you know, one of the key, one of our key motivations at Nvidia is really to have our partner ecosystem, embrace our technology and build solutions around our technology. So if you look at what we've done with the DPU, with credit and an SDK, which is an open SDK called Doka, and it's an open SDK for our partners to really build and develop solutions using Bluefield and using all these accelerated libraries that we expose through Doka. And so part of our differentiation is really building this open ecosystem for our partners to take advantage and build solutions around our technology. >>You know, what's exciting is when I hear you talk, it's like you realize that there's no one general purpose network anymore. Everyone has their own super environment Supercloud or these new capabilities. They can really craft their own, I'd say, custom environment at scale with easy tools. Right. And it's all kind of, again, this is the new architecture Mike, you were talking about, how does customers run this effectively? Cost-effectively and how do people migrate? >>Yeah, I, I think that is the key question, right? So we've got this beautiful architecture. You, you know, Amazon nitro is a, is a good example of, of a smart NIC architecture that has been successfully deployed, but enterprises and serve tier two service providers and tier one service providers and governments are not Amazon, right? So they need to migrate there and they need this architecture to be cost-effective. And, and that's, that's super key. I mean, the reality is deep user moving fast, but they're not going to be, um, deployed everywhere on day one. Some servers will have DPS right away, some servers will have use and a year or two. And then there are devices that may never have DPS, right. IOT gateways, or legacy servers, even mainframes. Um, so that's the beauty of a solution that creates a fabric across both the switch and the DPU, right. >>Um, and by leveraging the Nvidia Bluefield DPU, what we really like about it is it's open. Um, and that drives, uh, cost efficiencies. And then, um, uh, you know, with this, with this, our architectural approach effectively, you get a unified solution across switch and DPU workload independent doesn't matter what hypervisor it is, integrated visibility, integrated security, and that can, uh, create tremendous cost efficiencies and, and really extract a lot of the expense from, from a capital perspective out of the network, as well as from an operational perspective, because now I have an SDN automated solution where I'm literally issuing a command to deploy a network service or to create or deploy our security policy and is deployed everywhere, automatically saving the oppor, the network operations team and the security operations team time. >>All right. So let me rewind that because that's super important. Get the unified cloud architecture, I'm the customer guy, but it's implemented, what's the value again, take, take me through the value to me. I have a unified environment. What's the value. >>Yeah. So I mean, the value is effectively, um, that, so there's a few pieces of value. The first piece of value is, um, I'm creating this clean D mark. I'm taking networking to the host. And like I mentioned, we're not running it on the CPU. So in implementations that run networking on the CPU, there's some conflict between the dev ops team who owned the server and the NetApps team who own the network because they're installing software on the, on the CPU stealing cycles from what should be revenue generating. Uh CPU's. So now by, by terminating the networking on the DPU, we click create this real clean DMARC. So the dev ops folks are happy because they don't necessarily have the skills to manage network and they don't necessarily want to spend the time managing networking. They've got their network counterparts who are also happy the NetApps team, because they want to control the networking. >>And now we've got this clean DMARC where the DevOps folks get the services they need and the NetApp folks get the control and agility they need. So that's a huge value. Um, the next piece of value is distributed security. This is essential. I mentioned earlier, you know, put pushing out micro-segmentation and distributed firewall, basically at the application level, right, where I create these small, small segments on an by application basis. So if a bad actor does penetrate the perimeter firewall, they're contained once they get inside. Cause the worst thing is a bad actor, penetrates a perimeter firewall and can go wherever they want and wreak havoc. Right? And so that's why this, this is so essential. Um, and the next benefit obviously is this unified networking operating model, right? Having, uh, uh, uh, an operating model across switch and server underlay and overlay, workload agnostic, making the life of the NetApps teams much easier so they can focus their time on really strategy instead of spending an afternoon, deploying a single villain, for example. >>Awesome. And I think also from my standpoint, I mean, perimeter security is pretty much, I mean, they're out there, it gets the firewall still out there exists, but pretty much they're being breached all the time, the perimeter. So you have to have this new security model. And I think the other thing that you mentioned, the separation between dev ops is cool because the infrastructure is code is about making the developers be agile and build security in from day one. So this policy aspect is, is huge. Um, new control points. I think you guys have a new architecture that enables the security to be handled more flexible. >>Right. >>That seems to be the killer feature here, >>Right? Yeah. If you look at the data processing unit, I think one of the great things about sort of this new architecture, it's really the foundation for zero trust it's. So like you talked about the perimeter is getting breached. And so now each and every compute node has to be protected. And I think that's sort of what you see with the partnership between pluribus and Nvidia is the DPU is really the foundation of zero trust. And pluribus is really building on that vision with, uh, allowing sort of micro-segmentation and being able to protect each and every compute node as well as the underlying network. >>This is super exciting. This is an illustration of how the market's evolving architectures are being reshaped and refactored for cloud scale and all this new goodness with data. So I gotta ask how you guys go into market together. Michael, start with you. What's the relationship look like in the go to market with an Nvidia? >>Sure. Um, I mean, we're, you know, we're super excited about the partnership, obviously we're here together. Um, we think we've got a really good solution for the market, so we're jointly marketing it. Um, uh, you know, obviously we appreciate that Nvidia is open. Um, that's, that's sort of in our DNA, we're about open networking. They've got other ISV who are gonna run on Bluefield too. We're probably going to run on other DPS in the, in the future, but right now, um, we're, we feel like we're partnered with the number one, uh, provider of DPS in the world and, uh, super excited about, uh, making a splash with it. >>I'm in get the hot product. >>Yeah. So Bluefield too, as I mentioned was GA last year, we're introducing, uh, well, we now also have the converged accelerator. So I talked about artificial intelligence or artificial intelligence with the Bluefield DPU, all of that put together on a converged accelerator. The nice thing there is you can either run those workloads. So if you have an artificial intelligence workload and an infrastructure workload, you can warn them separately on the same platform or you can actually use, uh, you can actually run artificial intelligence applications on the Bluefield itself. So that's what the converged accelerator really brings to the table. Uh, so that's available now. Then we have Bluefield three, which will be available late this year. And I talked about sort of, you know, uh, how much better that next generation of Bluefield is in comparison to Bluefield two. So we will see Bluefield three shipping later on this year, and then our software stack, which I talked about, which is called Doka we're on our second version are Doka one dot two. >>We're releasing Doka one dot three, uh, in about two months from now. And so that's really our open ecosystem framework. So allow you to program the Bluefields. So we have all of our acceleration libraries, um, security libraries, that's all packed into this STK called Doka. And it really gives that simplicity to our partners to be able to develop on top of Bluefield. So as we add new generations of Bluefield, you know, next, next year, we'll have, you know, another version and so on and so forth Doka is really that unified unified layer that allows, um, Bluefield to be both forwards compatible and backwards compatible. So partners only really have to think about writing to that SDK once, and then it automatically works with future generations of Bluefields. So that's sort of the nice thing around, um, around Doka. And then in terms of our go to market model, we're working with every, every major OEM. So, uh, later on this year, you'll see, you know, major server manufacturers, uh, releasing Bluefield enabled servers. So, um, more to come >>Awesome, save money, make it easier, more capabilities, more workload power. This is the future of, of cloud operations. >>Yeah. And, and, and, uh, one thing I'll add is, um, we are, um, we have a number of customers as you'll hear in the next segment, um, that are already signed up and we'll be working with us for our, uh, early field trial starting late April early may. Um, we are accepting registrations. You can go to www.pluribusnetworks.com/e F T a. If you're interested in signing up for, um, uh, being part of our field trial and providing feedback on the product, >>Awesome innovation and network. Thanks so much for sharing the news. Really appreciate it. Thanks so much. Okay. In a moment, we'll be back to look deeper in the product, the integration security zero trust use cases. You're watching the cube, the leader in enterprise tech coverage, >>Cloud networking is complex and fragmented slowing down your business. How can you simplify and unify your cloud networks to increase agility and business velocity? >>Pluribus unified cloud networking provides a unified simplify and agile network fabric across all clouds. It brings the simplicity of a public cloud operation model to private clouds, dramatically reducing complexity and improving agility, availability, and security. Now enterprises and service providers can increase their business philosophy and delight customers in the distributed multi-cloud era. We achieve this with a new approach to cloud networking, pluribus unified cloud fabric. This open vendor, independent network fabric, unifies, networking, and security across distributed clouds. The first step is extending the fabric to servers equipped with data processing units, unifying the fabric across switches and servers, and it doesn't stop there. The fabric is unified across underlay and overlay networks and across all workloads and virtualization environments. The unified cloud fabric is optimized for seamless migration to this new distributed architecture, leveraging the power of the DPU for application level micro-segmentation distributed fireball and encryption while still supporting those servers and devices that are not equipped with a DPU. Ultimately the unified cloud fabric extends seamlessly across distributed clouds, including central regional at edge private clouds and public clouds. The unified cloud fabric is a comprehensive network solution. That includes everything you need for clouds, networking built in SDN automation, distributed security without compromises, pervasive wire speed, visibility and application insight available on your choice of open networking switches and DP use all at the lowest total cost of ownership. The end result is a dramatically simplified unified cloud networking architecture that unifies your distributed clouds and frees your business to move at cloud speed, >>To learn more, visit www.pluribusnetworks.com. >>Okay. We're back I'm John ferry with the cube, and we're going to go deeper into a deep dive into unified cloud networking solution from Clovis and Nvidia. And we'll examine some of the use cases with Alessandra Burberry, VP of product management and pullovers networks and Pete Bloomberg who's director of technical marketing and video remotely guys. Thanks for coming on. Appreciate it. >>Yeah. >>So deep dive, let's get into the what and how Alexandra we heard earlier about the pluribus Nvidia partnership and the solution you're working together on what is it? >>Yeah. First let's talk about the water. What are we really integrating with the Nvidia Bluefield, the DPO technology, uh, plugable says, um, uh, there's been shipping, uh, in, uh, in volume, uh, in multiple mission critical networks. So this advisor one network operating systems, it runs today on a merchant silicone switches and effectively it's a standard open network operating system for data center. Um, and the novelty about this system that integrates a distributed control plane for, at water made effective in SDN overlay. This automation is a completely open and interoperable and extensible to other type of clouds is not enclosed them. And this is actually what we're now porting to the Nvidia DPO. >>Awesome. So how does it integrate into Nvidia hardware and specifically how has pluribus integrating its software with the Nvidia hardware? >>Yeah, I think, uh, we leverage some of the interesting properties of the Bluefield, the DPO hardware, which allows actually to integrate, uh, um, uh, our software, our network operating system in a manner which is completely isolated and independent from the guest operating system. So the first byproduct of this approach is that whatever we do at the network level on the DPU card that is completely agnostic to the hypervisor layer or OSTP layer running on, uh, on the host even more, um, uh, we can also independently manage this network, know that the switch on a Neek effectively, um, uh, managed completely independently from the host. You don't have to go through the network operating system, running on x86 to control this network node. So you throw yet the experience effectively of a top of rack for virtual machine or a top of rack for, uh, Kubernetes bots, where instead of, uh, um, if you allow me with the analogy instead of connecting a server knee directly to a switchboard, now you're connecting a VM virtual interface to a virtual interface on the switch on an ache. >>And, uh, also as part of this integration, we, uh, put a lot of effort, a lot of emphasis in, uh, accelerating the entire, uh, data plane for networking and security. So we are taking advantage of the DACA, uh, Nvidia DACA API to program the accelerators. And these accomplished two things with that. Number one, uh, you, uh, have much greater performance, much better performance. They're running the same network services on an x86 CPU. And second, this gives you the ability to free up, I would say around 20, 25% of the server capacity to be devoted either to, uh, additional workloads to run your cloud applications, or perhaps you can actually shrink the power footprint and compute footprint of your data center by 20%, if you want to run the same number of compute workloads. So great efficiencies in the overall approach, >>And this is completely independent of the server CPU, right? >>Absolutely. There is zero code from running on the x86, and this is what we think this enables a very clean demarcation between computer and network. >>So Pete, I gotta get, I gotta get you in here. We heard that, uh, the DPU is enabled cleaner separation of dev ops and net ops. Can you explain why that's important because everyone's talking DevSecOps right now, you've got net ops, net, net sec ops, this separation. Why is this clean separation important? >>Yeah, I think it's a, you know, it's a pragmatic solution in my opinion. Um, you know, we wish the world was all kind of rainbows and unicorns, but it's a little, a little messier than that. And I think a lot of the dev ops stuff and that, uh, mentality and philosophy, there's a natural fit there. Right? You have applications running on servers. So you're talking about developers with those applications integrating with the operators of those servers. Well, the network has always been this other thing and the network operators have always had a very different approach to things than compute operators. And, you know, I think that we, we in the networking industry have gotten closer together, but there's still a gap there's still some distance. And I think in that distance, isn't going to be closed. And so, you know, again, it comes down to pragmatism and I think, you know, one of my favorite phrases is look good fences, make good neighbors. And that's what this is. >>Yeah. That's a great point because dev ops has become kind of the calling card for cloud, right. But dev ops is as simply infrastructure as code and infrastructure is networking, right? So if infrastructure is code, you know, you're talking about, you know, that part of the stack under the covers under the hood, if you will, this is super important distinction. And this is where the innovation is. Can you elaborate on how you see that? Because this is really where the action is right now. >>Yeah, exactly. And I think that's where, um, one from, from the policy, the security that the zero trust aspect of this, right? If you get it wrong on that network side, all of a sudden you, you can totally open up that those capabilities. And so security is part of that. But the other part is thinking about this at scale, right? So we're taking one top of rack switch and adding, you know, up to 48 servers per rack. And so that ability to automate, orchestrate and manage at scale becomes absolutely critical. >>I'll Sandra, this is really the why we're talking about here, and this is scale. And again, getting it right. If you don't get it right, you're going to be really kind of up, you know what you know, so this is a huge deal. Networking matters, security matters, automation matters, dev ops, net ops, all coming together, clean separation, um, help us understand how this joint solution with Nvidia fits into the pluribus unified cloud networking vision, because this is what people are talking about and working on right now. >>Yeah, absolutely. So I think here with this solution, we're attacking two major problems in cloud networking. One is, uh, operation of, uh, cloud networking. And the second is a distributing security services in the cloud infrastructure. First, let me talk about the first water. We really unifying. If we're unifying something, something must be at least fragmented or this jointed and the, what is this joint that is actually the network in the cloud. If you look holistically, how networking is deployed in the cloud, you have your physical fabric infrastructure, right? Your switches and routers, you'll build your IP clause fabric leaf in spine typologies. This is actually a well understood the problem. I, I would say, um, there are multiple vendors, uh, uh, with, uh, um, uh, let's say similar technologies, um, very well standardized, whether you will understood, um, and almost a commodity, I would say building an IP fabric these days, but this is not the place where you deploy most of your services in the cloud, particularly from a security standpoint, two services are actually now moved into the compute layer where you actually were called builders, have to instrument the, a separate, uh, network virtualization layer, where they deploy segmentation and security closer to the workloads. >>And this is where the complication arise. These high value part of the cloud network is where you have a plethora of options that they don't talk to each other. And they are very dependent on the kind of hypervisor or compute solution you choose. Um, for example, the networking API to be between an GSXI environment or an hyper V or a Zen are completely disjointed. You have multiple orchestration layers. And when, and then when you throw in also Kubernetes in this, in this, in this type of architecture, uh, you're introducing yet another level of networking. And when Kubernetes runs on top of VMs, which is a prevalent approach, you actually just stacking up multiple networks on the compute layer that they eventually run on the physical fabric infrastructure. Those are all ships in the nights effectively, right? They operate as completely disjointed. And we're trying to attack this problem first with the notion of a unified fabric, which is independent from any workloads, whether it's this fabric spans on a switch, which can be con connected to a bare metal workload, or can span all the way inside the DPU, uh, where, um, you have, uh, your multi hypervisor compute environment. >>It's one API, one common network control plane, and one common set of segmentation services for the network. That's probably the number one, >>You know, it's interesting you, man, I hear you talking, I hear one network month, different operating models reminds me of the old serverless days. You know, there's still servers, but they call it serverless. Is there going to be a term network list? Because at the end of the day, it should be one network, not multiple operating models. This, this is a problem that you guys are working on. Is that right? I mean, I'm not, I'm just joking server listen network list, but the idea is it should be one thing. >>Yeah, it's effectively. What we're trying to do is we are trying to recompose this fragmentation in terms of network operation, across physical networking and server networking server networking is where the majority of the problems are because of the, uh, as much as you have standardized the ways of building, uh, physical networks and cloud fabrics with IP protocols and internet, you don't have that kind of, uh, uh, sort of, uh, um, um, uh, operational efficiency, uh, at the server layer. And, uh, this is what we're trying to attack first. The, with this technology, the second aspect we're trying to attack is are we distribute the security services throughout the infrastructure, more efficiently, whether it's micro-segmentation is a stateful firewall services, or even encryption. Those are all capabilities enabled by the blue field, uh, uh, the Butte technology and, uh, uh, we can actually integrate those capabilities directly into the nettle Fabrica, uh, limiting dramatically, at least for east-west traffic, the sprawl of, uh, security appliances, whether virtual or physical, that is typically the way the people today, uh, segment and secure the traffic in the cloud. >>Awesome. Pete, all kidding aside about network lists and serverless kind of fun, fun play on words there, the network is one thing it's basically distributed computing, right? So I love to get your thoughts about this distributed security with zero trust as the driver for this architecture you guys are doing. Can you share in more detail the depth of why DPU based approach is better than alternatives? >>Yeah, I think what's, what's beautiful and kind of what the DPU brings. That's new to this model is a completely isolated compute environment inside. So, you know, it's the, uh, yo dog, I heard you like a server, so I put a server inside your server. Uh, and so we provide, uh, you know, armed CPU's memory and network accelerators inside, and that is completely isolated from the host. So the server, the, the actual x86 host just thinks it has a regular Nick in there, but you actually have this full control plane thing. It's just like taking your top of rack switch and shoving it inside of your compute node. And so you have not only the separation, um, within the data plane, but you have this complete control plane separation. So you have this element that the network team can now control and manage, but we're taking all of the functions we used to do at the top of rack switch, and we're just shooting them now. >>And, you know, as time has gone on we've, we've struggled to put more and more and more into that network edge. And the reality is the network edge is the compute layer, not the top of rack switch layer. And so that provides this phenomenal enforcement point for security and policy. And I think outside of today's solutions around virtual firewalls, um, the other option is centralized appliances. And even if you can get one that can scale large enough, the question is, can you afford it? And so what we end up doing is we kind of hope that of aliens good enough, or we hope that if the excellent tunnel is good enough and we can actually apply more advanced techniques there because we can't physically, you know, financially afford that appliance to see all of the traffic. And now that we have a distributed model with this accelerator, we could do it. >>So what's the what's in it for the customer. I real quick, cause I think this is interesting point. You mentioned policy, everyone in networking knows policy is just a great thing and it adds, you hear it being talked about up the stack as well. When you start getting to orchestrating microservices and whatnot, all that good stuff going on there, containers and whatnot and modern applications. What's the benefit to the customers with this approach? Because what I heard was more scale, more edge deployment, flexibility, relative to security policies and application enablement. I mean, is that what what's the customer get out of this architecture? What's the enablement. >>It comes down to, uh, taking again the capabilities that were in that top of rack switch and asserting them down. So that makes simplicity smaller blast radiuses for failure, smaller failure domains, maintenance on the networks, and the systems become easier. Your ability to integrate across workloads becomes infinitely easier. Um, and again, you know, we always want to kind of separate each one of those layers. So just as in say, a VX land network, my leaf and spine don't have to be tightly coupled together. I can now do this at a different layer. And so you can run a DPU with any networking in the core there. And so you get this extreme flexibility. You can start small, you can scale large. Um, you know, to me, the, the possibilities are endless. Yes, >>It's a great security control plan. Really flexibility is key. And, and also being situationally aware of any kind of threats or new vectors or whatever's happening in the network. Alessandra, this is huge upside, right? You've already identified some successes with some customers on your early field trials. What are they doing and why are they attracted to the solution? >>Yeah, I think the response from customers has been, uh, the most, uh, encouraging and, uh, exciting, uh, for, uh, for us to, uh, to sort of continue and work and develop this product. And we have actually learned a lot in the process. Um, we talked to tier two tier three cloud providers. Uh, we talked to, uh, SP um, software Tyco type of networks, uh, as well as a large enterprise customers, um, in, uh, one particular case. Um, uh, one, uh, I think, um, let me, let me call out a couple of examples here, just to give you a flavor. Uh, there is a service provider, a cloud provider, uh, in Asia who is actually managing a cloud, uh, where they are offering services based on multiple hypervisors. They are native services based on Zen, but they also are on ramp into the cloud, uh, workloads based on, uh, ESI and, uh, uh, and KVM, depending on what the customer picks from the piece on the menu. >>And they have the problem of now orchestrating through their orchestrate or integrating with the Zen center with vSphere, uh, with, uh, open stack to coordinate these multiple environments and in the process to provide security, they actually deploy virtual appliances everywhere, which has a lot of costs, complication, and eats up into the server CPU. The problem is that they saw in this technology, they call it actually game changing is actually to remove all this complexity of in a single network and distribute the micro-segmentation service directly into the fabric. And overall, they're hoping to get out of it, uh, uh, tremendous, uh, um, opics, uh, benefit and overall, um, uh, operational simplification for the cloud infrastructure. That's one potent a use case. Uh, another, uh, large enterprise customer global enterprise customer, uh, is running, uh, both ESI and hyper V in that environment. And they don't have a solution to do micro-segmentation consistently across hypervisors. >>So again, micro-segmentation is a huge driver security looks like it's a recurring theme, uh, talking to most of these customers and in the Tyco space, um, uh, we're working with a few types of customers on the CFT program, uh, where the main goal is actually to our Monet's network operation. They typically handle all the VNF search with their own homegrown DPDK stack. This is overly complex. It is frankly also as low and inefficient, and then they have a physical network to manage the, the idea of having again, one network, uh, to coordinate the provision in our cloud services between the, the take of VNF, uh, and, uh, the rest of the infrastructure, uh, is extremely powerful on top of the offloading capability of the, by the bluefin DPOs. Those are just some examples. >>That was a great use case, a lot more potential. I see that with the unified cloud networking, great stuff, feed, shout out to you guys at Nvidia had been following your success for a long time and continuing to innovate as cloud scales and pluribus here with the unified networking, kind of bring it to the next level. Great stuff. Great to have you guys on. And again, software keeps driving the innovation again, networking is just a part of it, and it's the key solution. So I got to ask both of you to wrap this up. How can cloud operators who are interested in, in this, uh, new architecture and solution, uh, learn more because this is an architectural shift. People are working on this problem. They're trying to think about multiple clouds of trying to think about unification around the network and giving more security, more flexibility, uh, to their teams. How can people learn more? >>Yeah, so, uh, all Sandra and I have a talk at the upcoming Nvidia GTC conference. Um, so that's the week of March 21st through 24th. Um, you can go and register for free and video.com/at GTC. Um, you can also watch recorded sessions if you ended up watching us on YouTube a little bit after the fact. Um, and we're going to dive a little bit more into the specifics and the details and what we're providing in the solution. >>Alexandra, how can people learn more? >>Yeah, absolutely. People can go to the pluribus, a website, www boost networks.com/eft, and they can fill up the form and, uh, they will contact durables to either know more or to know more and actually to sign up for the actual early field trial program, which starts at the end of April. >>Okay. Well, we'll leave it there. Thanks. You both for joining. Appreciate it up next. You're going to hear an independent analyst perspective and review some of the research from the enterprise strategy group ESG. I'm John ferry with the >>Cube. Thanks for watching. >>Okay. We've heard from the folks at networks and Nvidia about their effort to transform cloud networking and unify bespoke infrastructure. Now let's get the perspective from an independent analyst and to do so. We welcome in ESG, senior analysts, Bob LA Liberte, Bob. Good to see you. Thanks for coming into our east coast studios. >>Oh, thanks for having me. It's great to be >>Here. Yeah. So this, this idea of unified cloud networking approach, how serious is it? What's what's driving it. >>Yeah, there's certainly a lot of drivers behind it, but probably the first and foremost is the fact that application environments are becoming a lot more distributed, right? So the, it pendulum tends to swing back and forth. And we're definitely on one that's swinging from consolidated to distributed. And so applications are being deployed in multiple private data centers, multiple public cloud locations, edge locations. And as a result of that, what you're seeing is a lot of complexity. So organizations are having to deal with this highly disparate environment. They have to secure it. They have to ensure connectivity to it and all that's driving up complexity. In fact, when we asked in one of our last surveys and last year about network complexity, more than half 54% came out and said, Hey, our network environment is now either more or significantly more complex than it used to be. >>And as a result of that, what you're seeing is it's really impacting agility. So everyone's moving to these modern application environments, distributing them across areas so they can improve agility yet it's creating more complexity. So a little bit counter to the fact and, you know, really counter to their overarching digital transformation initiatives. From what we've seen, you know, nine out of 10 organizations today are either beginning in process or have a mature digital transformation process or initiative, but their top goals, when you look at them, it probably shouldn't be a surprise. The number one goal is driving operational efficiency. So it makes sense. I've distributed my environment to create agility, but I've created a lot of complexity. So now I need these tools that are going to help me drive operational efficiency, drive better experience. >>I mean, I love how you bring in the data yesterday. Does a great job with that. Uh, questions is, is it about just unifying existing networks or is there sort of a need to rethink kind of a do-over network, how networks are built? >>Yeah, that's a, that's a really good point because certainly unifying networks helps right. Driving any kind of operational efficiency helps. But in this particular case, because we've made the transition to new application architectures and the impact that's having as well, it's really about changing and bringing in new frameworks and new network architectures to accommodate those new application architectures. And by that, what I'm talking about is the fact that these new modern application architectures, microservices, containers are driving a lot more east west traffic. So in the old days, it used to be easier in north south coming out of the server, one application per server, things like that. Right now you've got hundreds, if not thousands of microservices communicating with each other users communicating to them. So there's a lot more traffic and a lot of it's taking place within the servers themselves. The other issue that you starting to see as well from that security perspective, when we were all consolidated, we had those perimeter based legacy, you know, castle and moat security architectures, but that doesn't work anymore when the applications aren't in the castle, right. >>When everything's spread out that that no longer happens. So we're absolutely seeing, um, organizations trying to, trying to make a shift. And, and I think much, like if you think about the shift that we're seeing with all the remote workers and the sassy framework to enable a secure framework there, this it's almost the same thing. We're seeing this distributed services framework come up to support the applications better within the data centers, within the cloud data centers, so that you can drive that security closer to those applications and make sure they're, they're fully protected. Uh, and that's really driving a lot of the, you know, the zero trust stuff you hear, right? So never trust, always verify, making sure that everything is, is, is really secure micro-segmentation is another big area. So ensuring that these applications, when they're connected to each other, they're, they're fully segmented out. And that's again, because if someone does get a breach, if they are in your data center, you want to limit the blast radius, you want to limit the amount of damage that's done. So that by doing that, it really makes it a lot harder for them to see everything that's in there. >>You know, you mentioned zero trust. It used to be a buzzword, and now it's like become a mandate. And I love the mode analogy. You know, you build a moat to protect the queen and the castle, the Queens left the castles, it's just distributed. So how should we think about this, this pluribus and Nvidia solution. There's a spectrum, help us understand that you've got appliances, you've got pure software solutions. You've got what pluribus is doing with Nvidia, help us understand that. >>Yeah, absolutely. I think as organizations recognize the need to distribute their services to closer to the applications, they're trying different models. So from a legacy approach, you know, from a security perspective, they've got these centralized firewalls that they're deploying within their data centers. The hard part for that is if you want all this traffic to be secured, you're actually sending it out of the server up through the rack, usually to in different location in the data center and back. So with the need for agility, with the need for performance, right, that adds a lot of latency. Plus when you start needing to scale, that means adding more and more network connections, more and more appliances. So it can get very costly as well as impacting the performance. The other way that organizations are seeking to solve this problem is by taking the software itself and deploying it on the servers. Okay. So that's a, it's a great approach, right? It brings it really close to the applications, but the things you start running into there, there's a couple of things. One is that you start seeing that the DevOps team start taking on that networking and security responsibility, which they >>Don't want to >>Do, they don't want to do right. And the operations teams loses a little bit of visibility into that. Um, plus when you load the software onto the server, you're taking up precious CPU cycles. So if you're really wanting your applications to perform at an optimized state, having additional software on there, isn't going to, isn't going to do it. So, you know, when we think about all those types of things, right, and certainly the other side effects of that is the impact of the performance, but there's also a cost. So if you have to buy more servers because your CPU's are being utilized, right, and you have hundreds or thousands of servers, right, those costs are going to add up. So what, what Nvidia and pluribus have done by working together is to be able to take some of those services and be able to deploy them onto a smart Nick, right? >>To be able to deploy the DPU based smart SMARTNICK into the servers themselves. And then pluribus has come in and said, we're going to unify create that unified fabric across the networking space, into those networking services all the way down to the server. So the benefits of having that are pretty clear in that you're offloading that capability from the server. So your CPU's are optimized. You're saving a lot of money. You're not having to go outside of the server and go to a different rack somewhere else in the data center. So your performance is going to be optimized as well. You're not going to incur any latency hit for every trip round trip to the, to the firewall and back. So I think all those things are really important. Plus the fact that you're going to see from a, an organizational aspect, we talked about the dev ops and net ops teams. The network operations teams now can work with the security teams to establish the security policies and the networking policies. So that they've dev ops teams. Don't have to worry about that. So essentially they just create the guardrails and let the dev op team run. Cause that's what they want. They want that agility and speed. >>Yeah. Your point about CPU cycles is key. I mean, it's estimated that 25 to 30% of CPU cycles in the data center are wasted. The cores are wasted doing storage offload or, or networking or security offload. And, you know, I've said many times everybody needs a nitro like Amazon nugget, but you can't go, you can only buy Amazon nitro if you go into AWS. Right. Everybody needs a nitro. So is that how we should think about this? >>Yeah. That's a great analogy to think about this. Um, and I think I would take it a step further because it's, it's almost the opposite end of the spectrum because pluribus and video are doing this in a very open way. And so pluribus has always been a proponent of open networking. And so what they're trying to do is extend that now to these distributed services. So leverage working with Nvidia, who's also open as well, being able to bring that to bear so that organizations can not only take advantage of these distributed services, but also that unified networking fabric, that unified cloud fabric across that environment from the server across the switches, the other key piece of what pluribus is doing, because they've been doing this for a while now, and they've been doing it with the older application environments and the older server environments, they're able to provide that unified networking experience across a host of different types of servers and platforms. So you can have not only the modern application supported, but also the legacy environments, um, you know, bare metal. You could go any type of virtualization, you can run containers, et cetera. So a wide gambit of different technologies hosting those applications supported by a unified cloud fabric from pluribus. >>So what does that mean for the customer? I don't have to rip and replace my whole infrastructure, right? >>Yeah. Well, think what it does for, again, from that operational efficiency, when you're going from a legacy environment to that modern environment, it helps with the migration helps you accelerate that migration because you're not switching different management systems to accomplish that. You've got the same unified networking fabric that you've been working with to enable you to run your legacy as well as transfer over to those modern applications. Okay. >>So your people are comfortable with the skillsets, et cetera. All right. I'll give you the last word. Give us the bottom line here. >>So yeah, I think obviously with all the modern applications that are coming out, the distributed application environments, it's really posing a lot of risk on these organizations to be able to get not only security, but also visibility into those environments. And so organizations have to find solutions. As I said, at the beginning, they're looking to drive operational efficiency. So getting operational efficiency from a unified cloud networking solution, that it goes from the server across the servers to multiple different environments, right in different cloud environments is certainly going to help organizations drive that operational efficiency. It's going to help them save money for visibility, for security and even open networking. So a great opportunity for organizations, especially large enterprises, cloud providers who are trying to build that hyperscaler like environment. You mentioned the nitro card, right? This is a great way to do it with an open solution. >>Bob, thanks so much for, for coming in and sharing your insights. Appreciate it. >>You're welcome. Thanks. >>Thanks for watching the program today. Remember all these videos are available on demand@thekey.net. You can check out all the news from today@siliconangle.com and of course, pluribus networks.com many thanks diplomas for making this program possible and sponsoring the cube. This is Dave Volante. Thanks for watching. Be well, we'll see you next time.

>>Okay, let's kick things off. We're here at my capital. One of the CMO of pluribus networks and AMI by Dani VP of networking, marketing developer ecosystem at Nvidia. Great to have you welcome folks. Thank you. Thanks. So let's get into the, the problem situation with cloud unified network. What problems are out there? What challenges do cloud operators have Mike let's get into? >>Yeah, really, you know, the challenges we're looking at are for non hyperscalers that's enterprises, governments, tier two service providers, cloud service providers, and the first mandate for them is to become as agile as a hyperscaler. So they need to be able to deploy services and security policies in seconds. They need to be able to abstract the complexity of the network and define things in software while it's accelerated in hardware. Really ultimately they need a single operating model everywhere. And then the second thing is they need to distribute networking and security services out to the edge of the host. We're seeing a growth in cyber attacks. It's it's not slowing down. It's only getting worse and, you know, solving for this security problem across clouds is absolutely critical. And the way to do it is to move security out to the host. >>Okay. With that goal in mind, what's the pluribus vision. How does this tie together? >>Yeah, so basically what we see is that this demands a new architecture and that new architecture has four tenants. The first tenant is unified and simplified cloud networks. If you look at cloud networks today, there's, there's sort of like discrete bespoke cloud networks, you know, per hypervisor, per private cloud edge cloud public cloud. Each of the public clouds have different networks that needs to be unified. You know, if we want these folks to be able to be agile, they need to be able to issue a single command or instantiate a security policy across all of those locations with one command and not have to go to each one. The second is like I mentioned, distributed security, distributed security without compromise, extended out to the host is absolutely critical. So micro-segmentation and distributed firewalls, but it doesn't stop there. They also need pervasive visibility. You know, it's, it's, it's sort of like with security, you really can't see you can't protect what you can't see. >>So you need visibility everywhere. The problem is visibility to date has been very expensive. Folks have had to basically build a separate overlay network of taps, packet brokers, tap aggregation infrastructure that really needs to be built into this unified network I'm talking about. And the last thing is automation. All of this needs to be SDN enabled. So this is related to my comment about abstraction abstract, the complexity of all these discreet networks, physic whatever's down there in the physical layer. Yeah. I don't want to see it. I want abstract it. I wanted to find things in software, but I do want to leverage the power of hardware to accelerate that. So that's the fourth tenant is SDN automation. >>Mike, we've been talking on the cable a lot about this architectural shift and customers are looking at this. This is a big part of everyone who's looking at cloud operations next gen, how do we get there? How do customers get this vision realized? >>That's a great question. And I appreciate the tee up. I mean, we're, we're here today for that reason. We're introducing two things today. The first is a unified cloud networking vision. And that is a vision of where pluribus is headed with our partners like Nvidia longterm. And that is about deploying a common operating model, SDN enabled SDN, automated hardware, accelerated across all clouds and whether that's underlying overlay switch or server hype, any hypervisor infrastructure containers, any workload doesn't matter. So that's ultimately where we want to get. And that's what we talked about earlier. The first step in that vision is what we call the unified cloud fabric. And this is the next generation of our adaptive cloud fabric. And what's nice about this is we're not starting from scratch. We have an award-winning adaptive cloud fabric product that is deployed globally. And in particular we're very proud of the fact that it's deployed in over a hundred tier one mobile operators as the network fabric for their 4g and 5g virtualized cores. We know how to build carrier grade networking infrastructure. What we're doing now to realize this next generation unified cloud fabric is we're extending from the switch to this Nvidia Bluefield to DPU. We, >>No, there's all that up real quick. That's a good, that's a good prop. That's the blue field and video. >>It's the Nvidia Bluefield two DPU data processing unit. And you know, what we're doing fundamentally is extending our SDN automated fabric, the unified cloud fabric out to the host, but it does take processing power. So we knew that we didn't want to do, we didn't want to implement that running on the CPU, which is what some other companies do because it consumes revenue generating CPU's from the application. So a DPU is a perfect way to implement this. And we knew that Nvidia was the leader with this blue field too. And so that is the first that's, that's the first step in the getting into realizing this vision >>And video has always been powering some great workloads of GPU. Now you've got DP networking, and then video is here. What is the relationship with clothes? How did that come together? Tell us the story. >>Yeah. So, you know, we've been working with pluribus for quite some time. I think the last several months was really when it came to fruition and what pluribus is trying build and what Nvidia has. So we have, you know, this concept of a Bluefield data processing unit, which if you think about it, conceptually does really three things, offload, accelerate an isolate. So offload your workloads from your CPU to your data processing unit infrastructure workloads, that is a accelerate. So there's a bunch of acceleration engine. So you can run infrastructure workloads much faster than you would otherwise, and then isolation. So you have this nice security isolation between the data processing unit and your other CPU environment. And so you can run completely isolated workloads directly on the data processing unit. So we introduced this, you know, a couple of years ago, and with pluribus, you know, we've been talking to the pluribus team for quite some months now. >>And I think really the combination of what pluribus is trying to build and what they've developed around this unified cloud fabric is fits really nicely with the DPU and running that on the DPU and extending it really from your physical switch, all the way to your host environment, specifically on the data processing unit. So if you think about what's happening as you add data processing units to your environment. So every server we believe over time is going to have data processing units. So now you'll have to manage that complexity from the physical network layer to the host layer. And so what pluribus is really trying to do is extending the network fabric from the host, from the switch to the host, and really have that single pane of glass for network operators to be able to configure provision, manage all of the complexity of the network environment. >>So that's really how the partnership truly started. And so it started really with extending the network fabric, and now we're also working with them on security. So, you know, if you sort of take that concept of isolation and security isolation, what pluribus has within their fabric is the concept of micro-segmentation. And so now you can take that extended to the data processing unit and really have isolated micro-segmentation workloads, whether it's bare metal cloud native environments, whether it's virtualized environments, whether it's public cloud, private cloud hybrid cloud. So it really is a magical partnership between the two companies with their unified cloud fabric running on, on the DPU. >>I love about this conversation is it reminds me of when you have these changing markets, the product gets pulled out of the market and, and you guys step up and create these new solutions. And I think this is a great example. So I have to ask you, how do you guys differentiate what sets this apart for customers with what's in it for the, >>Yeah. So I mentioned, you know, three things in terms of the value of what the Bluefield brings, right? There's offloading, accelerating, isolating, that's sort of the key core tenants of Bluefield, so that, you know, if you sort of think about what, what Bluefield, what we've done, you know, in terms of the differentiation, we're really a robust platform for innovation. So we introduced Bluefield to last year, we're introducing Bluefield three, which is our next generation of Bluefields, you know, we'll have five X, the arm compute capacity. It will have 400 gig line rate acceleration for X better crypto acceleration. So it will be remarkably better than the previous generation. And we'll continue to innovate and add, you know, chips to our portfolio every, every 18 months to two years. So that's sort of one of the key areas of differentiation. The other is the, if you look at Nvidia and, and you know, what we're sort of known for is really known for our AI artificial intelligence and our artificial intelligence software, as well as our GPU. >>So you look at artificial intelligence and the combination of artificial intelligence plus data processing. This really creates the faster, more efficient, secure AI systems from, you know, the core of your data center all the way out to the edge. And so with Nvidia, we really have these converged accelerators where we've combined the GPU, which does all your AI processing with your data processing with the DPU. So we have this convergence really nice convergence of, of that area. And I would say the third area is really around our developer environment. So, you know, one of the key, one of our key motivations at Nvidia is really to have our partner ecosystem, embrace our technology and build solutions around our technology. So if you look at what we've done with the DPU, with credit and an SDK, which is an open SDK called Doka, and it's an open SDK for our partners to really build and develop solutions using Bluefield and using all these accelerated libraries that we expose through Doka. And so part of our differentiation is really building this open ecosystem for our partners to take advantage and build solutions around our technology. >>You know, it's exciting is when I hear you talk, it's like you realize that there's no one general purpose network anymore. Everyone has their own super environment Supercloud or these new capabilities. They can really craft their own, I'd say custom environment at scale with easy tools. Right. And it's all kind of, again, this is the new architecture Mike, you were talking about, how does customers run this effectively? Cost-effectively and how do people migrate? >>Yeah, I think that is the key question, right? So we've got this beautiful architecture. You, you know, Amazon nitro is a, is a good example of, of a smart NIC architecture that has been successfully deployed, but enterprises and serve tier two service providers and tier one service providers and governments are not Amazon, right? So they need to migrate there and they need this architecture to be cost-effective. And, and that's, that's super key. I mean, the reality is deep user moving fast, but they're not going to be deployed everywhere on day one. Some servers will ha have DPS right away. Some servers will have deep use in a year or two. And then there are devices that may never have DPS, right? IOT gateways, or legacy servers, even mainframes. So that's the beauty of a solution that creates a fabric across both the switch and the DPU, right? >>And by leveraging the Nvidia Bluefield DPU, what we really like about it is it's open and that drives cost efficiencies. And then, you know, with this, with this, our architectural approach effectively, you get a unified solution across switch and DPU workload independent doesn't matter what hypervisor it is, integrated visibility, integrated security, and that can create tremendous cost efficiencies and really extract a lot of the expense from, from a capital perspective out of the network, as well as from an operational perspective, because now I have an SDN automated solution where I'm literally issuing a command to deploy a network service or to create or deploy our security policy and is deployed everywhere, automatically saving the oper, the network operations team and the security operations team time. >>All right. So let me rewind that because that's super important. Get the unified cloud architecture, I'm the customer, but it's implemented, what's the value again, take, take me through the value to me. I have a unified environment. What's the value. >>Yeah. So I mean, the value is effectively. So there's a few pieces of value. The first piece of value is I'm creating this clean D mark. I'm taking networking to the host. And like I mentioned, we're not running it on the CPU. So in implementations that run networking on the CPU, there's some conflict between the dev ops team who owned the server and the NetApps team who own the network because they're installing software on the, on the CPU stealing cycles from what should be revenue generating CPU's. So now by, by terminating the networking on the DPU, we click create this real clean DMARC. So the dev ops folks are happy because they don't necessarily have the skills to manage network and they don't necessarily want to spend the time managing networking. They've got their network counterparts who are also happy the NetApps team, because they want to control the networking. >>And now we've got this clean DMARC where the dev ops folks get the services they need and the NetApp folks get the control and agility they need. So that's a huge value. The next piece of value is distributed security. This is essential. I mentioned earlier, you know, put pushing out micro-segmentation and distributed firewall, basically at the application level, right, where I create these small, small segments on an application by application basis. So if a bad actor does penetrate the perimeter firewall, they're contained once they get inside. Cause the worst thing is a bad actor penetrates at perimeter firewall, and it can go wherever they want and wreak havoc, right? And so that's why this, this is so essential. And the next benefit obviously is this unified networking operating model, right? Having an operating model, switch and server underlay and overlay, workload agnostic, making the life of the NetApps teams much easier so they can focus their time on really strategy instead of spending an afternoon, deploying a single V LAN for example. >>Awesome. And I think also from my standpoint, I mean, perimeter security is pretty much, I mean, they're out there, it gets the firewall still out there exists, but pretty much they're being breached all the time, the perimeter. So you have to have this new security model. And I think the other thing that you mentioned, the separation between dev ops is cool because the infrastructure is code is about making the developers be agile and build security in from day one. So this policy aspect is, is huge new control points. I think you guys have a new architecture that enables the security to be handled more flexible. Right. That seems to be the killer feature, >>Right? Yeah. If you look at the data processing unit, I think one of the great things about sort of this new architecture, it's really the foundation for zero trust it's. So like you talked about the perimeter is getting breached. And so now each and every compute node has to be protected. And I think that's sort of what you see with the partnership between pluribus and Nvidia is the DPU is really the foundation of zero trust. And pluribus is really building on that vision with allowing sort of micro-segmentation and being able to protect each and every compute node as well as the underlying network. >>And this is an illustration of how the market's evolving architectures are being reshaped and refactored for cloud scale and all this new goodness with data. So I got to ask how you guys go into market together. Michael, start with you. What's the relationship look like in the go to market with an Nvidia? >>Sure. I mean, we're, you know, we're super excited about the partnership. Obviously we're here together. We think we've got a really good solution for the market, so we're jointly marketing it. You know, obviously we appreciate that Nvidia is open that's, that's sort of in our DNA, we're about open networking. They've got other ISV who are gonna run on Bluefield too. We're probably going to run on other DPS in the future, but right now we're we feel like we're partnered with the number one provider of DPS in the world and super excited about making a splash with it >>In video, get the hot product. >>Yeah. So Bluefield too, as I mentioned was GA last year, we're introducing well, we now also have the converged accelerator. So I talked about artificial intelligence or artificial intelligence software with the Bluefield DPU, all of that put together on a converged accelerator. The nice thing there is you can either run those workloads. So if you have an artificial intelligence workload and an infrastructure workload, you can warn them separately on the same platform or you can actually use, you can actually run artificial intelligence applications on the Bluefield itself. So that's what the converged accelerator really brings the table. So that's available now. Then we have Bluefield three, which will be available late this year. And I talked about sort of, you know, how much better that next generation of Bluefield is in comparison to Bluefield two. So we will see Bluefield three shipping later on this year, and then our software stack, which I talked about, which is called Doka we're on our second version are DACA one dot two. >>We're releasing Doka one dot three in about two months from now. And so that's really our open ecosystem framework. So allow you to program the Bluefields. So we have all of our acceleration libraries, security libraries, that's all packed into this SDK called Doka. And it really gives that simplicity to our partners to be able to develop on top of Bluefield. So as we add new generations of Bluefield, you know, next, next year, we'll have, you know, another version and so on and so forth. Doka is really that unified unified layer that allows Bluefield to be both forwards compatible and backwards compatible. So partners only really have to think about writing to that SDK once and then it automatically works with future generations of Bluefields. So that's sort of the nice thing around, around Doka. And then in terms of our go to market model, we're working with every, every major OEM. So later on this year, you'll see, you know, major server manufacturers releasing Bluefield enabled servers, so more to come >>Save money, make it easier, more capabilities, more workload power. This is the future of, of cloud operations. Yeah. >>And one thing I'll add is we are, we have a number of customers as you'll hear in the next segment that are already signed up and we'll be working with us for our early field trial starting late April early may. We are accepting registrations. You can go to www.pluribusnetworks.com/e F T if you're interested in signing up for being part of our field trial and, and providing feedback on the product, >>Awesome innovation and network. Thanks so much for sharing the news. Really appreciate it. Thanks so much. Okay. In a moment, we'll be back to the deeper in the product, the integration security zero trust use cases. You're watching the cube, the leader in enterprise tech coverage.