(electronic music) (graphics whooshing) (graphics tinkling) >> Telecommunications is well north of a trillion-dollar business globally, that provides critical services on which virtually everyone on the planet relies. Dramatic changes are occurring in the sector, and one of the most important dimensions of this change is the underlying infrastructure that powers global telecommunications networks. Telcos have been thawing out, if you will, they're frozen infrastructure, modernizing. They're opening up, they're disaggregating their infrastructure, separating, for example, the control plane from the data plane, and adopting open standards. Telco infrastructure is becoming software-defined. And leading telcos are adopting cloud native microservices to help make developers more productive, so they can respond more quickly to market changes. They're embracing technology consumption models, and selectively leveraging the cloud where it makes sense. And these changes are being driven by market forces, the root of which stem from customer demand. So from a customer's perspective, they want services, and they want them fast. Meaning, not only at high speeds, but also they want them now. Customers want the latest, the greatest, and they want these services to be reliable and stable with high quality of service levels. And they want them to be highly cost-effective. Hello and welcome to this preview of Mobile World Congress 2023. My name is Dave Vellante, and at this year's event, theCUBE has a major presence at the show made possible by Dell Technologies, and with me to unpack the trends in telco, and look ahead to MWC23 are Dennis Hoffman, he's the Senior Vice President and General Manager of Dell's telecom business, and Aaron Chaisson, who is the Vice President of Telecom and Edge Solutions Marketing at Dell Technologies, gentlemen, welcome, thanks so much for spending some time with me. >> Thank you, Dave. >> Thanks, glad to be here. >> So, Dennis, let's start with you. Telcos in recent history have been slow to deliver and to monetize new services, and a large part because their purpose-built infrastructure could been somewhat of a barrier to responding to all these market forces. In many ways, this is what makes telecoms, really this market so exciting. So from your perspective, where is the action in this space? >> Yeah, the action Dave is kind of all over the place, partly because it's an ecosystem play. I think it's been, as you point out, the disaggregation trend has been going on for a while. The opportunity's been clear, but it has taken a few years to get all of the vendors, and all of the components that make up a solution, as well as the operators themselves, to a point where we can start putting this stuff together, and actually achieving some of the promise. >> So Aaron, for those who might not be as familiar with Dell's a activities in this area, here we are just ahead of Mobile World Congress, it's the largest event for telecoms, what should people know about Dell? And what's the key message to this industry? >> Sure, yeah, I think everybody knows that there's a lot of innovation that's been happening in the industry of late. One of the major trends that we're seeing is that shift from more of a vertically-integrated technology stack, to more of a disaggregated set of solutions, and that trend has actually created a ton of innovation that's happening across the industry, or along technology vendors and providers, the telecoms themselves. And so, one of the things that Dell's really looking to do is, as Dennis talked about, is build out a really strong ecosystem of partners and vendors that we're working closely together to be able to collaborate on new technologies, new capabilities that are solving challenges that the networks are seeing today. Be able to create new solutions built on those in order to be able to bring new value to the industry. And then finally, we want to help both partners, as well as our CSP providers activate those changes, so that they can bring new solutions to market, to be able to serve their customers. And so, the key areas that we're really focusing on with our customers is, technologies to help modernize the network, to be able to capitalize on the value of open architectures, and bring price performance to what they're expecting, and availability that they're expecting today. And then also, partner with the lines of business to be able to take these new capabilities, produce new solutions, and then deliver new value to their customers. >> Great, thank you, Aaron. So Dennis, you and I, known you for a number of years. I've watched you, you're are a trend spotter. You're a strategic thinker. I love now the fact that you're running a business that you had to go out and analyze, and now you got to make it happen. So, how would you describe Dell's strategy in this market? >> Well, it's really two things. And I appreciate the comment, I'm not sure how much of a trend spotter I am, but I certainly enjoy, and I think I'm fascinated by what's going on in this industry right now. Our two main thrusts, Dave, are first round, trying to catalyze that ecosystem, be a force for pulling together a group of folks, vendors that have been flying in fairly loose formation for a couple of years, to deliver the kinds of solutions that move the needle forward, and produce the outcomes that our network operator customers can actually buy and consume, and deploy, and have them be supported. The other thing is, there's a couple of very key technology areas that need to be advanced here. This ends up being a much anticipated year in telecom. Because of the delivery of some open infrastructure solutions that have being developed for years. With the Intel Sapphire Rapids program coming to market, we've of course got some purpose-built solutions on top of that for telecommunications networks. Some expanded partnerships in the area of multi-cloud infrastructure. And so, I would say the second main thrust is, we've got to bring some intellectual property to the party. It's not just about pulling the ecosystem together. But those two things together really form the twin thrusts of our strategy. >> Okay, so as you point out, you obviously not going to go alone in this market, it's way too broad, there's so many routes to market, partnerships, obviously very, very important. So, can you share a little bit more about the ecosystem and partners, maybe give some examples of some of the key partners that you'd be highlighting or working with, maybe at Mobile World Congress, or other activities this year? >> Yeah, absolutely. As Aaron touched on, I'm a visual thinker. The way I think about this thing is a very, very vertical architecture is tipping sideways. It's becoming horizontal. And all of the layers of that horizontal architecture are really where the partnerships are at. So, let's start at the bottom, silicon. The silicon ecosystem is very much focused on this market. And producing very specific products to enable open, high performance telecom networks. That's both in the form of host processors, as well as accelerators. One layer up, of course, is the stuff that we're known for, subsystems, compute storage, the hardware infrastructure that forms the foundation for telco clouds. A layer above that, all of the cloud software layer, the virtualization and containerization software, and all of the usual suspects there, all of whom are very good partners of ours, and we're looking to expand that pretty broadly this year. And then at the top of the layer cake, all of the network functions, all of the VNF's and CNF's that were once kind of the top of proprietary stacks, that are now opening up and being delivered, as well-formed containers that can run on these clouds. So, we're focusing on all of those, if you will, product partnerships, and there is a services wrapper around all of it. The systems integration necessary to make these systems part of a carrier's network, which of course, has been running for a long time, and needs to be integrated with in a very specific way. And so, all of that, together kind of forms the ecosystem, all of those are partners, and we're really excited about being at the heart of it. >> Interesting, it's not like we've never seen this movie before, which is, it's sort of repeating itself in telco. Aaron, you heard my little intro up front about the need to modernize infrastructure, I wonder if I could touch on another major trend, which we're seeing is the cloud, and I'm talkin' about not only public, but private and hybrid cloud. The public cloud is an opportunity, but it's also a threat for telcos. Telcom providers are lookin' to the public cloud for specific use cases, you think about like bursting for an iPhone launch or whatever. But at the same time, these cloud vendors, they're sort of competing with telcos. They're providing local zones, for example, sometimes trying to do an end run on the telco connectivity services, so telecom companies, they have to find the right balance between what they own and what they rent. And I wonder if you could add some color as to what you see in the market and what Dell specifically is doing to support these trends. >> Yeah, and I think the most important thing is what we're seeing, as you said, is these aren't things that we haven't seen before. And I think that telecom is really going through their own set of cloud transformations, and so, one of the hot topics in the industry now is, what is telco cloud? And what does that look like going forward? And it's going to be, as you said, a combination of services that they offer, services that they leverage. But at the end of the day, it's going to help them modernize how they deliver telecommunication services to their customers, and then provide value added services on top of that. From a Dell perspective, we're really providing the technologies to provide the underpinnings to lay a foundation on which that network can be built, whether that's best of breed servers that are built in design for the telecom environments. Recently, we announced our Infer block program, in partnering with virtualization providers, to be able to provide engineered systems that dramatically simplify how our customers can deploy, manage, and lifecycle manage throughout day two operations, an entire cloud environment. And whether they're using Red Hat, whether they're using Wind River, or VMware, or other virtualization layers, they can deploy the right virtualization layer at the right part of their network to support the applications they're looking to drive. And Dell is looking to solve how they simplify and manage all of that, both from a hardware, as well as on management software perspective. So, this is really what Dell's doing to, again, partner with the broader technology community, to help make that telco cloud a reality. >> Aaron, let's stay here for a second, I'm interested in some of the use cases that you're going after with customers. You've got Edge infrastructure, remote work, 5G, where's security fit, what are the focus areas for Dell, and can we double click on that a little bit? >> Yeah, I mean, I think there's two main areas of telecommunication industry that we're talking to. One, we've really been talking about the sort of the network buyer, how do they modernize the core, the network Edge, the RAN capabilities to deliver traditional telecommunication services, and modernize that as they move into 5G and beyond. I think the other side of the business is, telecoms are really looking from a line of business perspective to figure out how do they monetize that network, and be able to deliver value added services to their enterprise customers on top of these new networks. So, you were just touching on a couple of things that are really critical. In the enterprise space, AI and IoT is driving a tremendous amount of innovation out there, and there's a need for being able to support and manage Edge compute at scale, be able to provide connectivity, like private mobility, and 4G and 5G, being able to support things like mobile workforces and client capabilities, to be able to access these devices that are around all of these Edge environments of the enterprises. And telecoms are seeing as that, as an opportunity for them to not only provide connectivity, but how do they extend their cloud out into these enterprise environments with compute, with connectivity, with client and connectivity resources, and even also provide protection for those environments as well. So, these are areas that Dell is historically very strong at. Being able to provide compute, be able to provide connectivity, and being able to provide data protection and client services, we are looking to work closely with lines of businesses to be able to develop solutions that they can bring to market in combination with us, to be able to serve their end user customers and their enterprises. So, those are really the two key areas, not only network buyer, but being able to enable the lines of business to go and capitalize on the services they're developing for their customers. >> I think that line of business aspect is key, I mean, the telcos have had to sit back and provide the plumbing, cost per bit goes down, data consumption going through the roof, all the over at the top guys have had the field day with the data, and the customer relationships, and now it's almost like the revenge (chuckles) of the telcos. Dennis, I wonder if we could talk about the future. What can we expect in the years ahead from Dell, if you break out the binoculars a little bit. >> Yeah, I think you hit it earlier. We've seen the movie before. This has happened in the IT data center. We went from proprietary vertical solutions to horizontal open systems. We went from client server to software-defined open hardware cloud native. And the trend is likely to be exactly that, in the telecom industry because that's what the operators want. They're not naive to what's happened in the IT data center, they all run very large data centers. And they're trying to get some of the scale economies. Some of the agility, the cost of ownership benefits for the reasons Aaron just discussed. It's clear as you point out, this industry's been really defined by the inability to stop investing, and the difficulty to monetize that investment. And I think now, everybody's looking at this 5G, and frankly, 5G plus 6G, and beyond, as the opportunity to really go get a chunk of that revenue, and Enterprise Edge is the target. >> And 5G is touching so many industries, and that kind of brings me, Aaron into Mobile World Congress. I mean, you look at the floor layout, it's amazing. You got Industry 4.0, you've got our traditional industry and telco colliding. There's public policy. So, give us a teaser to Mobile World Congress 23, what's on deck at the show from Dell? >> Yeah, we're really excited about Mobile World Congress. This, as you know, is a massive event for the industry every year. And it's really the event that the whole industry uses to kick off this coming year. So, we're going to be using this obviously to talk to our customers and our partners about what Dell's looking to do, and what we're innovating on right now, and what we're looking to partner with them around. In the front of the house, we're going to be doin', we're going to be highlighting 13 different solutions and demonstrations to be able to show our customers what we're doing today, and show them the use cases, and put into action, so they get to actually look and feel, and touch, and experience what it is that we're working around. Obviously, meetings are important, everybody knows Mobile World Congress is the place to get those meetings and kickoff for the year. So, we're going to have, we're lookin' at several hundred meetings, hundreds of meetings that we're going to be lookin' to have across the industry with our customers and partners in the broader community. And of course, we've also got technology that's going to be in a variety of different partner spaces as well. So, you can come and see us in hall three, but we're also going to have technologies, kind of spread all over the floor. And of course, there's always theCUBE. You're going to be able to see us live all four days, all day, every day. You're going to be hearing our executives, our partners, our customers, talk about what Dell is doing to innovate in the industry, and how we're looking to leverage the broader, open ecosystem to be able to transform the network, and what we're lookin' to do. So, in that space, we're going to be focusing on what we're doing from an ecosystem perspective, our infrastructure focus. We'll be talking about what we're doing to support telco cloud transformation. And then finally, as we talked about earlier, how are we helping the lines of business within our telecoms monetize the opportunity? So, these are all different things we're really excited to be focusing on, and look forward to the event next month. >> Yeah, it's going to be awesome in Barcelona at the FITA, as you say, Dell's big presence in hall three, Orange is in there, Deutsche Telecom, Intel's in hall three. VMware's there, Nokia, Vodafone, you got some great things to see there. Check that out, and of course, theCUBE, we are super excited to be collaborating with you, we got a great setup. We're in the walkway right between halls four and five, right across from the government of Catalonia, who are the host partners for the event, so there's going to be a ton of action there. Guys, can't wait to see you there, really appreciate your time today. >> Great, thanks. >> Alright, Mobile World Congress, theCUBE's coverage starts on February 27th right after the keynotes. So, first thing in the morning, east coast time, we'll be broadcasting is, Aaron said all week, Monday through Thursday in the show floor, check that out at thecube.net. siliconangle.com has all the written coverage, and go to dell.com, see what's happenin' there, have all the action from the event. Don't miss us, this is Dave Vellante, we'll see you there. (electronic music)

(upbeat music) >> Welcome back, everyone, to our Cube special programming on "Securing Compute, Engineered for the Hybrid World." We got Cole Humphreys who's with HPE, global server security product manager, and Mike Ferron-Jones with Intel. He's the product manager for data security technology. Gentlemen, thank you for coming on this special presentation. >> All right, thanks for having us. >> So, securing compute, I mean, compute, everyone wants more compute. You can't have enough compute as far as we're concerned. You know, more bits are flying around the internet. Hardware's mattering more than ever. Performance markets hot right now for next-gen solutions. When you're talking about security, it's at the center of every single conversation. And Gen11 for the HPE has been big-time focus here. So let's get into the story. What's the market for Gen11, Cole, on the security piece? What's going on? How do you see this impacting the marketplace? >> Hey, you know, thanks. I think this is, again, just a moment in time where we're all working towards solving a problem that doesn't stop. You know, because we are looking at data protection. You know, in compute, you're looking out there, there's international impacts, there's federal impacts, there's state-level impacts, and even regulation to protect the data. So, you know, how do we do this stuff in an environment that keeps changing? >> And on the Intel side, you guys are a Tier 1 combination partner, Better Together. HPE has a deep bench on security, Intel, We know what your history is. You guys have a real root of trust with your code, down to the silicon level, continuing to be, and you're on the 4th Gen Xeon here. Mike, take us through the Intel's relationship with HPE. Super important. You guys have been working together for many, many years. Data security, chips, HPE, Gen11. Take us through the relationship. What's the update? >> Yeah, thanks and I mean, HPE and Intel have been partners in delivering technology and delivering security for decades. And when a customer invests in an HPE server, like at one of the new Gen11s, they're getting the benefit of the combined investment that these two great companies are putting into product security. On the Intel side, for example, we invest heavily in the way that we develop our products for security from the ground up, and also continue to support them once they're in the market. You know, launching a product isn't the end of our security investment. You know, our Intel Red Teams continue to hammer on Intel products looking for any kind of security vulnerability for a platform that's in the field. As well as we invest heavily in the external research community through our bug bounty programs to harness the entire creativity of the security community to find those vulnerabilities, because that allows us to patch them and make sure our customers are staying safe throughout that platform's deployed lifecycle. You know, in 2021, between Intel's internal red teams and our investments in external research, we found 93% of our own vulnerabilities. Only a small percentage were found by unaffiliated external entities. >> Cole, HPE has a great track record and long history serving customers around security, actually, with the solutions you guys had. With Gen11, it's more important than ever. Can you share your thoughts on the talent gap out there? People want to move faster, breaches are happening at a higher velocity. They need more protection now than ever before. Can you share your thoughts on why these breaches are happening, and what you guys are doing, and how you guys see this happening from a customer standpoint? What you guys fill in with Gen11 with solution? >> You bet, you know, because when you hear about the relentless pursuit of innovation from our partners, and we in our engineering organizations in India, and Taiwan, and the Americas all collaborating together years in advance, are about delivering solutions that help protect our customer's environments. But what you hear Mike talking about is it's also about keeping 'em safe. Because you look to the market, right? What you see in, at least from our data from 2021, we have that breaches are still happening, and lot of it has to do with the fact that there is just a lack of adequate security staff with the necessary skills to protect the customer's application and ultimately the workloads. And then that's how these breaches are happening. Because ultimately you need to see some sort of control and visibility of what's going on out there. And what we were talking about earlier is you see time. Time to seeing some incident happen, the blast radius can be tremendous in today's technical, advanced world. And so you have to identify it and then correct it quickly, and that's why this continued innovation and partnership is so important, to help work together to keep up. >> You guys have had a great track record with Intel-based platforms with HPE. Gen11's a really big part of the story. Where do you see that impacting customers? Can you explain the benefits of what's going on with Gen11? What's the key story? What's the most important thing we should be paying attention to here? >> I think there's probably three areas as we look into this generation. And again, this is a point in time, we will continue to evolve. But at this particular point it's about, you know, a fundamental approach to our security enablement, right? Partnering as a Tier 1 OEM with one of the best in the industry, right? We can deliver systems that help protect some of the most critical infrastructure on earth, right? I know of some things that are required to have a non-disclosure because it is some of the most important jobs that you would see out there. And working together with Intel to protect those specific compute workloads, that's a serious deal that protects not only state, and local, and federal interests, but, really, a global one. >> This is a really- >> And then there's another one- Oh sorry. >> No, go ahead. Finish your thought. >> And then there's another one that I would call our uncompromising focus. We work in the industry, we lead and partner with those in the, I would say, in the good side. And we want to focus on enablement through a specific capability set, let's call it our global operations, and that ability to protect our supply chain and deliver infrastructure that can be trusted and into an operating environment. You put all those together and you see very significant and meaningful solutions together. >> The operating benefits are significant. I just want to go back to something you just said before about the joint NDAs and kind of the relationship you kind of unpacked, that to me, you know, I heard you guys say from sand to server, I love that phrase, because, you know, silicone into the server. But this is a combination you guys have with HPE and Intel supply-chain security. I mean, it's not just like you're getting chips and sticking them into a machine. This is, like, there's an in-depth relationship on the supply chain that has a very intricate piece to it. Can you guys just double down on that and share that, how that works and why it's important? >> Sure, so why don't I go ahead and start on that one. So, you know, as you mentioned the, you know, the supply chain that ultimately results in an end user pulling, you know, a new Gen11 HPE server out of the box, you know, started, you know, way, way back in it. And we've been, you know, Intel, from our part are, you know, invest heavily in making sure that all of our entire supply chain to deliver all of the Intel components that are inside that HPE platform have been protected and monitored ever since, you know, their inception at one of any of our 14,000, you know, Intel vendors that we monitor as part of our supply-chain assurance program. I mean we, you know, Intel, you know, invests heavily in compliance with guidelines from places like NIST and ISO, as well as, you know, doing best practices under things like the Transported Asset Protection Alliance, TAPA. You know, we have been intensely invested in making sure that when a customer gets an Intel processor, or any other Intel silicone product, that it has not been tampered with or altered during its trip through the supply chain. HPE then is able to pick up that, those components that we deliver, and add onto that their own supply-chain assurance when it comes down to delivering, you know, the final product to the customer. >> Cole, do you want to- >> That's exactly right. Yeah, I feel like that integration point is a really good segue into why we're talking today, right? Because that then comes into a global operations network that is pulling together these servers and able to deploy 'em all over the world. And as part of the Gen11 launch, we have security services that allow 'em to be hardened from our factories to that next stage into that trusted partner ecosystem for system integration, or directly to customers, right? So that ability to have that chain of trust. And it's not only about attestation and knowing what, you know, came from whom, because, obviously, you want to trust and make sure you're get getting the parts from Intel to build your technical solutions. But it's also about some of the provisioning we're doing in our global operations where we're putting cryptographic identities and manifests of the server and its components and moving it through that supply chain. So you talked about this common challenge we have of assuring no tampering of that device through the supply chain, and that's why this partnering is so important. We deliver secure solutions, we move them, you're able to see and control that information to verify they've not been tampered with, and you move on to your next stage of this very complicated and necessary chain of trust to build, you know, what some people are calling zero-trust type ecosystems. >> Yeah, it's interesting. You know, a lot goes on under the covers. That's good though, right? You want to have greater security and platform integrity, if you can abstract the way the complexity, that's key. Now one of the things I like about this conversation is that you mentioned this idea of a hardware-root-of-trust set of technologies. Can you guys just quickly touch on that, because that's one of the major benefits we see from this combination of the partnership, is that it's not just one, each party doing something, it's the combination. But this notion of hardware-root-of-trust technologies, what is that? >> Yeah, well let me, why don't I go ahead and start on that, and then, you know, Cole can take it from there. Because we provide some of the foundational technologies that underlie a root of trust. Now the idea behind a root of trust, of course, is that you want your platform to, you know, from the moment that first electron hits it from the power supply, that it has a chain of trust that all of the software, firmware, BIOS is loading, to bring that platform up into an operational state is trusted. If you have a breach in one of those lower-level code bases, like in the BIOS or in the system firmware, that can be a huge problem. It can undermine every other software-based security protection that you may have implemented up the stack. So, you know, Intel and HPE work together to coordinate our trusted boot and root-of-trust technologies to make sure that when a customer, you know, boots that platform up, it boots up into a known good state so that it is ready for the customer's workload. So on the Intel side, we've got technologies like our trusted execution technology, or Intel Boot Guard, that then feed into the HPE iLO system to help, you know, create that chain of trust that's rooted in silicon to be able to deliver that known good state to the customer so it's ready for workloads. >> All right, Cole, I got to ask you, with Gen11 HPE platforms that has 4th Gen Intel Xeon, what are the customers really getting? >> So, you know, what a great setup. I'm smiling because it's, like, it has a good answer, because one, this, you know, to be clear, this isn't the first time we've worked on this root-of-trust problem. You know, we have a construct that we call the HPE Silicon Root of Trust. You know, there are, it's an industry standard construct, it's not a proprietary solution to HPE, but it does follow some differentiated steps that we like to say make a little difference in how it's best implemented. And where you see that is that tight, you know, Intel Trusted Execution exchange. The Intel Trusted Execution exchange is a very important step to assuring that route of trust in that HPE Silicon Root of Trust construct, right? So they're not different things, right? We just have an umbrella that we pull under our ProLiant, because there's ILO, our BIOS team, CPLDs, firmware, but I'll tell you this, Gen11, you know, while all that, keeping that moving forward would be good enough, we are not holding to that. We are moving forward. Our uncompromising focus, we want to drive more visibility into that Gen11 server, specifically into the PCIE lanes. And now you're going to be able to see, and measure, and make policies to have control and visibility of the PCI devices, like storage controllers, NICs, direct connect, NVME drives, et cetera. You know, if you follow the trends of where the industry would like to go, all the components in a server would be able to be seen and attested for full infrastructure integrity, right? So, but this is a meaningful step forward between not only the greatness we do together, but, I would say, a little uncompromising focus on this problem and doing a little bit more to make Gen11 Intel's server just a little better for the challenges of the future. >> Yeah, the Tier 1 partnership is really kind of highlighted there. Great, great point. I got to ask you, Mike, on the 4th Gen Xeon Scalable capabilities, what does it do for the customer with Gen11 now that they have these breaches? Does it eliminate stuff? What's in it for the customer? What are some of the new things coming out with the Xeon? You're at Gen4, Gen11 for HP, but you guys have new stuff. What does it do for the customer? Does it help eliminate breaches? Are there things that are inherent in the product that HP is jointly working with you on or you were contributing in to the relationship that we should know about? What's new? >> Yeah, well there's so much great new stuff in our new 4th Gen Xeon Scalable processor. This is the one that was codenamed Sapphire Rapids. I mean, you know, more cores, more performance, AI acceleration, crypto acceleration, it's all in there. But one of my favorite security features, and it is one that's called Intel Control-Flow Enforcement Technology, or Intel CET. And why I like CET is because I find the attack that it is designed to mitigate is just evil genius. This type of attack, which is called a return, a jump, or a call-oriented programming attack, is designed to not bring a whole bunch of new identifiable malware into the system, you know, which could be picked up by security software. What it is designed to do is to look for little bits of existing, little bits of existing code already on the server. So if you're running, say, a web server, it's looking for little bits of that web-server code that it can then execute in a particular order to achieve a malicious outcome, something like open a command prompt, or escalate its privileges. Now in order to get those little code bits to execute in an order, it has a control mechanism. And there are different, each of the different types of attacks uses a different control mechanism. But what CET does is it gets in there and it disrupts those control mechanisms, uses hardware to prevent those particular techniques from being able to dig in and take effect. So CET can, you know, disrupt it and make sure that software behaves safely and as the programmer intended, rather than picking off these little arbitrary bits in one of these return, or jump, or call-oriented programming attacks. Now it is a technology that is included in every single one of the new 4th Gen Xeon Scalable processors. And so it's going to be an inherent characteristic the customers can benefit from when they buy a new Gen11 HPE server. >> Cole, more goodness from Intel there impacting Gen11 on the HPE side. What's your reaction to that? >> I mean, I feel like this is exactly why you do business with the big Tier 1 partners, because you can put, you know, trust in from where it comes from, through the global operations, literally, having it hardened from the factory it's finished in, moving into your operating environment, and then now protecting against attacks in your web hosting services, right? I mean, this is great. I mean, you'll always have an attack on data, you know, as you're seeing in the data. But the more contained, the more information, and the more control and trust we can give to our customers, it's going to make their job a little easier in protecting whatever job they're trying to do. >> Yeah, and enterprise customers, as you know, they're always trying to keep up to date on the skills and battle the threats. Having that built in under the covers is a real good way to kind of help them free up their time, and also protect them is really killer. This is a big, big part of the Gen11 story here. Securing the data, securing compute, that's the topic here for this special cube conversation, engineering for a hybrid world. Cole, I'll give you the final word. What should people pay attention to, Gen11 from HPE, bottom line, what's the story? >> You know, it's, you know, it's not the first time, it's not the last time, but it's our fundamental security approach to just helping customers through their digital transformation defend in an uncompromising focus to help protect our infrastructure in these technical solutions. >> Cole Humphreys is the global server security product manager at HPE. He's got his finger on the pulse and keeping everyone secure in the platform integrity there. Mike Ferron-Jones is the Intel product manager for data security technology. Gentlemen, thank you for this great conversation, getting into the weeds a little bit with Gen11, which is great. Love the hardware route-of-trust technologies, Better Together. Congratulations on Gen11 and your 4th Gen Xeon Scalable. Thanks for coming on. >> All right, thanks, John. >> Thank you very much, guys, appreciate it. Okay, you're watching "theCube's" special presentation, "Securing Compute, Engineered for the Hybrid World." I'm John Furrier, your host. Thanks for watching. (upbeat music)

(upbeat music) >> Welcome back to Supercloud 2 this is Dave Vellante. We're here exploring the intersection of data and analytics and the future of cloud. And in this segment, we're going to look at the evolution of cloud, and try to test some of the Supercloud concepts and assumptions with Brian Gracely, is the founder and co-host along with Aaron Delp of the popular Cloudcast program. Amazing series, if you're not already familiar with it. The Cloudcast is one of the best ways to keep up with so many things going on in our industry. Enterprise tech, platform engineering, business models, obviously, cloud developer trends, crypto, Web 3.0. Sorry Brian, I know that's a sore spot, but Brian, thanks for coming >> That's okay. >> on the program, really appreciate it. >> Yeah, great to be with you, Dave. Happy New Year, and great to be back with everybody with SiliconANGLE again this year. >> Yeah, we love having you on. We miss working with you day-to-day, but I want to start with Gracely's theorem, which basically says, I'm going to paraphrase. For the most part, nothing new gets introduced in the enterprise tech business, patterns repeat themselves, maybe get applied in new ways. And you know this industry well, when something comes out that's new, if you take virtualization, for example, been around forever with mainframes, but then VMware applied it, solve a real problem in the client service system. And then it's like, "Okay, this is awesome." We get really excited and then after a while we pushed the architecture, we break things, introduce new things to fix the things that are broken and start adding new features. And oftentimes you do that through acquisitions. So, you know, has the cloud become that sort of thing? And is Supercloud sort of same wine, new bottle, following Gracely's theorem? >> Yeah, I think there's some of both of it. I hate to be the sort of, it depends sort of answer but, I think to a certain extent, you know, obviously Cloud in and of itself was, kind of revolutionary in that, you know, it wasn't that you couldn't rent things in the past, it was just being able to do it at scale, being able to do it with such amazing self-service. And then, you know, kind of proliferation of like, look at how many services I can get from, from one cloud, whether it was Amazon or Azure or Google. And then, you know, we, we slip back into the things that we know, we go, "Oh, well, okay, now I can get computing on demand, but, now it's just computing." Or I can get database on demand and it's, you know, it's got some of the same limitations of, of say, of database, right? It's still, you know, I have to think about IOPS and I have to think about caching, and other stuff. So, I think we do go through that and then we, you know, we have these sort of next paradigms that come along. So, you know, serverless was another one of those where it was like, okay, it seems sort of new. I don't have to, again, it was another level of like, I don't have to think about anything. And I was able to do that because, you know, there was either greater bandwidth available to me, or compute got cheaper. And what's been interesting is not the sort of, that specific thing, serverless in and of itself is just another way of doing compute, but the fact that it now gets applied as, sort of a no-ops model to, you know, again, like how do I provision a database? How do I think about, you know, do I have to think about the location of a service? Does that just get taken care of for me? So I think the Supercloud concept, and I did a thing and, and you and I have talked about it, you know, behind the scenes that maybe the, maybe a better name is Super app for something like Snowflake or other, but I think we're, seeing these these sort of evolutions over and over again of what were the big bottlenecks? How do we, how do we solve those bottlenecks? And I think the big thing here is, it's never, it's very rarely that you can take the old paradigm of what the thing was, the concept was, and apply it to the new model. So, I'll just give you an example. So, you know, something like VMware, which we all know, wildly popular, wildly used, but when we apply like a Supercloud concept of VMware, the concept of VMware has always been around a cluster, right? It's some finite number of servers, you sort of manage it as a cluster. And when you apply that to the cloud and you say, okay, there's, you know, for example, VMware in the cloud, it's still the same concept of a cluster of VMware. But yet when you look at some of these other services that would fit more into the, you know, Supercloud kind of paradigm, whether it's a Snowflake or a MongoDB Atlas or maybe what CloudFlare is doing at the edge, those things get rid of some of those old paradigms. And I think that's where stuff, you start to go, "Oh, okay, this is very different than before." Yes, it's still computing or storage, or data access, but there's a whole nother level of something that we didn't carry forward from the previous days. And that really kind of breaks the paradigm. And so that's the way I think I've started to think about, are these things really brand new? Yes and no, but I think it's when you can see that big, that thing that you didn't leave behind isn't there anymore, you start to get some really interesting new innovation come out of it. >> Yeah. And that's why, you know, lift and shift is okay, when you talk to practitioners, they'll say, "You know, I really didn't change my operating model. And so I just kind of moved it into the cloud. there were some benefits, but it was maybe one zero not three zeros that I was looking for." >> Right. >> You know, we always talk about what's great about cloud, the agility, and all the other wonderful stuff that we know, what's not working in cloud, you know, tie it into multi-cloud, you know, in terms of, you hear people talk about multi-cloud by accident, okay, that's true. >> Yep. >> What's not great about cloud. And then I want to get into, you know, is multi-cloud really a problem or is it just sort of vendor hype? But, but what's not working in cloud? I mean, you mentioned serverless and serverless is kind of narrow, right, for a lot of stateless apps, right? But, what's not great about cloud? >> Well, I think there's a few things that if you ask most people they don't love about cloud. I think, we can argue whether or not sort of this consolidation around a few cloud providers has been a good thing or a bad thing. I think, regardless of that, you know, we are seeing, we are hearing more and more people that say, look, you know, the experience I used to have with cloud when I went to, for example, an Amazon and there was, you know, a dozen services, it was easy to figure out what was going on. It was easy to figure out what my billing looked like. You know, now they've become so widespread, the number of services they have, you know, the number of stories you just hear of people who went, "Oh, I started a service over in US West and I can't find it anymore 'cause it's on a different screen. And I, you know, I just got billed for it." Like, so I think the sprawl of some of the clouds has gotten, has created a user experience that a lot of people are frustrated with. I think that's one thing. And we, you know, we see people like Digital Ocean and we see others who are saying, "Hey, we're going to be that simplified version." So, there's always that yin and yang. I think people are super frustrated at network costs, right? So, you know, and that's kind of at a lot of, at the center of maybe why we do or don't see more of these Supercloud services is just, you know, in the data center as an application owner, I didn't have to think about, well where, where does this go to? Where are my users? Yes, somebody took care of it, but when those things become front and center, that's super frustrating. That's the one area that we've seen absolutely no cost savings, cost reduction. So I think that frustrates people a lot. And then I think the third piece is just, you know, we're, we went from super centralized IT organizations, which, you know, for decades was how it worked. It was part of the reason why the cloud expanded and became a thing, right? Sort of shadow IT and I can't get things done. And then, now what we've seen is sort of this proliferation of little pockets of groups that are your IT, for lack of a better thing, whether they're called platform engineering or SRE or DevOps. But we have this, expansion, explosion if you will, of groups that, if I'm an app dev team, I go, "Hey, you helped me make this stuff run, but then the team next to you has another group and they have another group." And so you see this explosion of, you know, we don't have any standards in the company anymore. And, so sort of self-service has created its own nightmare to a certain extent for a lot of larger companies. >> Yeah. Thank you for that. So, you know, I want, I want to explore this multi-cloud, you know, by accident thing and is a real problem. You hear that a lot from vendors and we've been talking about Supercloud as this unifying layer across cloud. You know, but when you talk to customers, a lot of them are saying, "Yes, we have multiple clouds in our organization, but my group, we have mono cloud, we know the security, edicts, we know how to, you know, deal with the primitives, whether it's, you know, S3 or Azure Blob or whatever it is. And we're very comfortable with this." It's, that's how we're simplifying. So, do you think this is really a problem? Does it have merit that we need that unifying layer across clouds, or is it just too early for that? >> I think, yeah, I think what you, what you've laid out is basically how the world has played out. People have picked a cloud for a specific application or a series of applications. Yeah, and I think if you talk to most companies, they would tell you, you know, holistically, yes, we're multi-cloud, not, maybe not necessarily on, I don't necessarily love the phrase where people say like, well it happened by accident. I think it happened on purpose, but we got to multi-cloud, not in the way that maybe that vendors, you know, perceived, you know, kind of laid out a map for. So it was, it was, well you will lay out this sort of Supercloud framework. We didn't call it that back then, we just called it sort of multi-cloud. Maybe it was Kubernetes or maybe it was whatever. And different groups, because central IT kind of got disbanded or got fragmented. It turned into, go pick the best cloud for your application, for what you need to do for the business. And then, you know, multiple years later it was like, "Oh, hold on, I've got 20% in Google and 50% in AWS and I've got 30% in Azure. And, you know, it's, yeah, it's been evolution. I don't know that it's, I don't know if it's a mistake. I think it's now groups trying to figure out like, should I make sense of it? You know, should I try and standardize and I backwards standardize some stuff? I think that's going to be a hard thing for, for companies to do. 'cause I think they feel okay with where the applications are. They just happen to be in multiple clouds. >> I want to run something by you, and you guys, you and Aaron have talked about this. You know, still depending on who, which keynote you listen to, small percentage of the workloads are actually in cloud. And when you were with us at Wikibon, I think we called it true private cloud, and we looked at things like Nutanix and there were a lot of other examples of companies that were trying to replicate the hyperscale experience on Prem. >> Yeah. >> And, we would evaluate that, you know, beyond virtualization, and so we sort of defined that and, but I think what's, maybe what's more interesting than Supercloud across clouds is if you include that, that on Prem estate, because that's where most of the work is being done, that's where a lot of the proprietary tools have been built, a lot of data, a lot of software. So maybe there's this concept of sending that true private cloud to true hybrid cloud. So I actually think hybrid cloud in some cases is the more interesting use case for so-called Supercloud. What are your thoughts on that? >> Yeah, I think there's a couple aspects too. I think, you know, if we were to go back five or six years even, maybe even a little further and look at like what a data center looked like, even if it was just, "Hey we're a data center that runs primarily on VMware. We use some of their automation". Versus what you can, even what you can do in your data center today. The, you know, the games that people have seen through new types of automation through Kubernetes, through get ops, and a number of these things, like they've gotten significantly further along in terms of I can provision stuff really well, I can do multi-tenancy, I can do self-service. Is it, you know, is it still hard? Yeah. Because those things are hard to do, but there's been significant progress there. I don't, you know, I still look for kind of that, that killer application, that sort of, you know, lighthouse use case of, hybrid applications, you know, between data center and between cloud. I think, you know, we see some stuff where, you know, backup is a part of it. So you use the cloud for storage, maybe you use the cloud for certain kinds of resiliency, especially on maybe front end load balancing and stuff. But I think, you know, I think what we get into is, this being hung up on hybrid cloud or multi-cloud as a term and go like, "Look, what are you trying to measure? Are you trying to measure, you know, efficiency of of of IT usage? Are you trying to measure how quickly can I give these business, you know, these application teams that are part of a line of business resources that they need?" I think if we start measuring that way, we would look at, you know, you'd go, "Wow, it used to be weeks and months. Now we got rid of these boards that have to review everything every time I want to do a change management type of thing." We've seen a lot more self-service. I think those are the things we want to measure on. And then to your point of, you know, where does, where do these Supercloud applications fit in? I think there are a bunch of instances where you go, "Look, I have a, you know, global application, I have a thing that has to span multiple regions." That's where the Supercloud concept really comes into play. We used to do it in the data center, right? We'd had all sorts of technologies to help with that, I think you can now start to do it in the cloud. >> You know, one of the other things, trying to understand, your thoughts on this, do you think that you, you again have talked about this, like I'm with you. It's like, how is it that Google's losing, you know, 3 billion dollars a year, whatever. I mean, because when you go back and look at Amazon, when they were at that level of revenue where Google is today, they were making money, you know, and they were actually growing faster, by the way. So it's kind of interesting what's happened with Google. But, the reason I bring that up is, trying to understand if you think the hyperscalers will ever be motivated to create standards across clouds, and that may be a play for Google. I mean, obviously with Kubernetes it was like a Hail Mary and kind of made them relevant. Where would Google be without Kubernetes? But then did it achieve the objectives? We could have that conversation some other time, but do you think the hyperscalers will actually say, "Okay, we're going to lean in and create these standards across clouds." Because customers would love that, I would think, but it would sub-optimize their competitive advantage. What are your thoughts? >> I think, you know, on the surface, I would say they, they probably aren't. I think if you asked 'em the question, they would say, "Well, you know, first and foremost, you know, we do deliver standards, so we deliver a, you know, standard SQL interface or a SQL you know, or a standard Kubernetes API or whatever. So, in that, from that perspective, you know, we're not locking you into, you know, an Amazon specific database, or a Google specific database." You, you can argue about that, but I think to a certain extent, like they've been very good about, "Hey, we're going to adopt the standards that people want." A lot of times the open source standards. I think the problem is, let's say they did come up with a standard for it. I think you still have the problem of the costs of migration and you know, the longer you've, I think their bet is basically the longer you've been in some cloud. And again, the more data you sort of compile there, the data gravity concept, there's just going to be a natural thing that says, okay, the hurdle to get over to say, "Look, we want to move this to another cloud", becomes so cost prohibitive that they don't really have to worry about, you know, oh, I'm going to get into a war of standards. And so far I think they sort of realize like that's the flywheel that the cloud creates. And you know, unless they want to get into a world where they just cut bandwidth costs, like it just kind of won't happen. You know, I think we've even seen, and you know, the one example I'll use, and I forget the name of it off the top of my head, but there's a, there's a Google service. I think it's like BigQuery external or something along those lines, that allows you to say, "Look, you can use BigQuery against like S3 buckets and against other stuff." And so I think the cloud providers have kind of figured out, I'm never going to get the application out of that other guy's cloud or you know, the other cloud. But maybe I'm going to have to figure out some interesting ways to sort of work with it. And, you know, it's a little bit, it's a little janky, but that might be, you know, a moderate step that sort of gets customers where they want to be. >> Yeah. Or you know, it'd be interesting if you ever see AWS for example, running its database in other clouds, you started, even Oracle is doing that with, with with Azure, which is a form of Supercloud. My last question for you is, I want to get you thinking about sort of how the future plays out. You know, think about some of the companies that we've put forth this Supercloud, and by the way, this has been a criticism of the concept. Charles Fitzer, "Everything is Supercloud!" Which if true would defeat the purpose of course. >> Right. >> And so right with the community effort, we really tried to put some guardrails down on the essential characteristics, the deployment models, you know, so for example, running across multiple clouds with a purpose build pass, creating a common experience, metadata intelligence that solves a specific problem. I mean, the example I often use is Snowflake's governed data sharing. But yeah, Snowflake, Databricks, CloudFlare, Cohesity, you know, I just mentioned Oracle and Azure, these and others, they certainly claim to have that common experience across clouds. But my question is, again, I come back to, do customers need this capability? You know, is Mono Cloud the way to solve that problem? What's your, what are your thoughts on how this plays out in the future of, I guess, PAs, apps and cloud? >> Yeah, I think a couple of things. So, from a technology perspective, I think, you know, the companies you name, the services you've named, have sort of proven that the concept is viable and it's viable at a reasonable size, right? These aren't completely niche businesses, right? They're multi-billion dollar businesses. So, I think there's a subset of applications that, you know, maybe a a bigger than a niche set of applications that are going to use these types of things. A lot of what you talked about is very data centric, and that's, that's fine. That's that layer is, figuring that out. I think we'll see messaging types of services, so like Derek Hallison's, Caya Company runs a, sort of a Supercloud for messaging applications. So I think there'll be places where it makes a ton of sense. I think, the thing that I'm not sure about, and because again, we've been now 10 plus years of sort of super low, you know, interest rates in terms of being able to do things, is a lot of these things come out of research that have been done previously. Then they get turned into maybe somewhat of an open source project, and then they can become something. You know, will we see as much investment into the next Snowflake if, you know, the interest rates are three or four times that they used to be, do we, do we see VCs doing it? So that's the part that worries me a little bit, is I think we've seen what's possible. I think, you know, we've seen companies like what those services are. I think I read yesterday Snowflake was saying like, their biggest customers are growing at 30, like 50 or 60%. Like the, value they get out of it is becoming exponential. And it's just a matter of like, will the economics allow the next big thing to happen? Because some of these things are pretty, pretty costly, you know, expensive to get started. So I'm bullish on the idea. I don't know that it becomes, I think it's okay that it's still sort of, you know, niche plus, plus in terms of the size of it. Because, you know, if we think about all of IT it's still, you know, even microservices is a small part of bigger things. But I'm still really bullish on the idea. I like that it's been proven. I'm a little wary, like a lot of people have the economics of, you know, what might slow things down a little bit. But yeah, I, think the future is going to involve Supercloud somewhere, whatever people end up calling it. And you and I discussed that. (laughs) But I don't, I don't think it goes away. I don't think it's, I don't think it's a fad. I think it is something that people see tremendous value and it's just, it's got to be, you know, for what you're trying to do, your application specific thing. >> You're making a great point on the funding of innovation and we're entering a new era of public policy as well. R and D tax credit is now is shifting. >> Yeah. >> You know, you're going to have to capitalize that over five years now. And that's something that goes back to the 1950s and many people would argue that's at least in part what has helped the United States be so, you know, competitive in tech. But Brian, always great to talk to you. Thanks so much for participating in the program. Great to see you. >> Thanks Dave, appreciate it. Good luck with the rest of the show. >> Thank you. All right, this is Dave Vellante for John Furrier, the entire Cube community. Stay tuned for more content from Supercloud2.

>> Welcome everyone to "theCUBE's" coverage of "Compute engineered for your hybrid world," sponsored by HP and Intel. Today we're going to going to discuss how to transform your compute management experience with the new 4th Gen Intel Xeon scalable processors. Hello, I'm John Furrier, host of "theCUBE," and my guests today are Chinmay Ashok, director cloud engineering at Intel, and Koichiro Nakajima, principal product manager, compute at cloud services with HPE. Gentlemen, thanks for coming on this segment, "Transform your compute management experience." >> Thanks for having us. >> Great topic. A lot of people want to see that system management one pane of glass and want to manage everything. This is a really important topic and they started getting into distributed computing and cloud and hybrid. This is a major discussion point. What are some of the major trends you guys see in the system management space? >> Yeah, so system management is trying to help user manage their IT infrastructure effectively and efficiently. So, the system management is evolving along with the IT infrastructures which is trying to accommodate market trends. We have been observing the continuous trends like digital transformation, edge computing, and exponential data growth never stops. AI, machine learning, deep learning, cloud native applications, hybrid cloud, multi-cloud strategies. There's a lot of things going on. Also, COVID-19 pandemic has changed the way we live and work. These are all the things that, given a profound implication to the system design architectures that system management has to consider. Also, security has always been the very important topic, but it has become more important than ever before. Some of the research is saying that the cyber criminals becoming like a $10.5 trillion per year. We all do our efforts on the solution provider size and on the user side, but still cyber criminals are growing 15% year by year. So, with all this kind of thing in the mind, system management really have to evolve in a way to help user efficiently and effectively manage their more and more distributed IT infrastructure. >> Chinmay, what's your thoughts on the major trends in system management space? >> Thanks, John, Yeah, to add to what Koichiro said, I think especially with the view of the system or the service provider, as he was saying, is changing, is evolving over the last few years, especially with the advent of the cloud and the different types of cloud usage models like platform as a service, on-premises, of course, infrastructure is a service, but the traditional software as a service implies that the service provider needs a different view of the system and the context in which we need the CPU vendor, or the platform vendor needs to provide that, is changing. That includes both in-band telemetry being able to monitor what is going on on the system through traditional in-band methods, but also the advent of the out-of-band methods to do this without end user disruption is a key element to the enhancements that our customers are expecting from us as we deploy CPUs and platforms. >> That's great. You know what I love about this discussion is we had multiple generation enhancements, 4th Gen Xeon, 11th Gen ProLiant, iLOs going to come up with got another generation increase on that one. We'll get into that on the next segment, but while we're here, what is iLO? Can you guys define what that is and why it's important? >> Yeah, great question. Real quick, so HPE Integrated Lights-Out is the formal name of the product and we tend to call it as a iLO for short. iLO is HPE'S BMC. If you're familiar with this topic it's a Baseboard Management Controller. If not, this is a small computer on the server mother board and it runs independently from host CPU and the operating system. So, that's why it's named as Lights-Out. Now what can you do with the iLO? iLO really helps a user manage and use and monitor the server remotely, securely, throughout its life from the deployment to the retirement. So, you can really do things like, you know, turning a server power on, off, install operating system, access to IT, firmware update, and when you decide to retire server, you can completely wipe the data off that server so then it's ready to trash. iLO is really a best solution to manage a single server, but when you try to manage hundreds or thousand of servers in a larger scale environment, then managing server one by one by one through the iLO is not practical. So, HPE has two options. One of them is a HPE OneView. OneView is a best solution to manage a very complex, on-prem IT infrastructure that involves a thousand of servers as well as the other IT elements like fiber channel storage through the storage agent network and so on. Another option that we have is HPE for GreenLake Compute Ops Management. This is our latest, greatest product that we recently launched and this is a best solution to manage a distributed IT environment with multiple edge points or multiple clouds. And I recently involved in the customer conversation about the computer office management and with the hotel chain, global hotel chain with 9,000 locations worldwide and each of the location only have like a couple of servers to manage, but combined it's, you know, 27,000 servers and over the 9,000 locations, we didn't really have a great answer for that kind of environment before, but now HPE has GreenLake for computer office management for also deal with, you know, such kind of environment. >> Awesome. We're going to do a big dive on iLO in the next segment, but Chinmay, before we end this segment, what is PMT? >> Sure, so yeah, with the introduction of the 4th Gen Intel Xeon scalable processor, we of course introduce many new technologies like PCI Gen 5, DDR5, et cetera. And these are very key to general system provision, if you will. But with all of these new technologies come new sources of telemetry that the service provider now has to manage, right? So, the PMT is a technology called Platform Monitoring Technology. That is a capability that we introduced with the Intel 4th Gen Xeon scalable processor that allows the service provider to monitor all of these sources of telemetry within the system, within the system on chip, the CPU SOC, in all of these contexts that we talked about, like the hybrid cloud and cloud infrastructure as a service or platform as a service, but both in their in-band traditional telemetry collection models, but also out-of-band collection models such as the ones that Koichiro was talking about through the BMC et cetera. So, this is a key enhancement that we believe that takes the Intel product line closer to what the service providers require for managing their end user experience. >> Awesome, well thanks so much for spending the time in this segment. We're going to take a quick break, we're going to come back and we're going to discuss more what's new with Gen 11 and iLO 6. You're watching "theCUBE," the leader in high tech enterprise coverage. We'll be right back. (light music) Welcome back. We're continuing the coverage of "theCUBE's" coverage of compute engineered for your hybrid world. I'm John Furrier, I'm joined by Chinmay Ashok who's from Intel and Koichiro Nakajima with HPE. We're going to dive deeper into transforming your compute management experience with 4th Gen Intel Xeon scalable processors and HP ProLiant Gen11. Okay, let's get into it. We want to talk about Gen11. What's new with Gen11? What's new with iLO 6? So, NexGen increases in performance capabilities. What's new, what's new at Gen11 and iLO 6 let's go. >> Yeah, iLO 6 accommodates a lot of new features and the latest, greatest technology advancements like a new generation CPUs, DDR5 memories, PCI Gen 5, GPGPUs, SmartNICs. There's a lot of great feature functions. So, it's an iLO, make sure that supports all the use cases that associate with those latest, greatest advancements. For instance, like you know, some of the higher thermal design point CPU SKUs that requires a liquid cooling. We all support those kind of things. And also iLO6 accommodates latest, greatest industry standard system management, standard specifications, for instance, like an DMTF, TLDN, DMTF, RDE, SPDM. And what are these means for the iLO6 and Gen11? iLO6 really offers the greatest manageability and monitoring user experiences as well as the greatest automation through the refresh APIs. >> Chinmay, what's your thoughts on the Gen11 and iLO6? You're at Intel, you're enabling all this innovation. >> Yeah. >> What's the new features? >> Yeah, thanks John. Yeah, so yeah, to add to what Koichiro said, I think with the introduction of Gen11, 4th Gen Intel Xeon scalable processor, we have all of these rich new feature sets, right? With the DDR5, PCI Gen5, liquid cooling, et cetera. And then all of these new accelerators for various specific workloads that customers can use using this processor. So, as we were discussing previously, what this brings is all of these different sources of telemetry, right? So, our sources of data that the system provider or the service provider then needs to utilize to manage the compute experience for their end user. And so, what's new from that perspective is Intel realized that these new different sources of telemetry and the new mechanisms by which the service provider has to extract this telemetry required us to fundamentally think about how we provide the telemetry experience to the service provider. And that meant extending our existing best-in-class, in-band telemetry capabilities that we have today already built into in market Intel processors. But now, extending that with the introduction of the PMT, the Platform Monitoring Technology, that allows us to expand on that in-band telemetry, but also include all of these new sources of telemetry data through all of these new accelerators through the new features like PCI Gen5, DDR5, et cetera, but also bring in that out-of-band telemetry management experience. And so, I think that's a key innovation here, helping prepare for the world that the cloud is enabling. >> It's interesting, you know, Koichiro you had mentioned on the previous segment, COVID-19, we all know the impact of how that changed, how IT at the managed, you know, all of a sudden remote work, right? So, as you have cloud go to hybrid, now we got the edge coming, we're talking about a distributed computing environment, we got telemetry, you got management. This is a huge shift and it's happening super fast. What's the Gen11 iLO6 mean for architects as they start to look at going beyond hybrid and going to the edge, you're going to need all this telemetry. What's the impact? Can you guys just riff and share your thoughts on what this means for that kind of NexGen cloud that we see coming on on which is essentially distributed computing. >> Yeah, that's a great topic to discuss. So, there's a couple of the things. Really, to make sure those remote environment and also the management distributed IT environments, the system management has to reach across the remote location, across the internet connections, and the connectivities. So, the system management protocol, for instance, like traditionally IPMI or SNMP, or those things, got to be modernized into more restful API and those modern integration friendly to the modern tool chains. So, we're investing on those like refresh APIs and also again, the security becomes paramount importance because those are exposed to the bad people to snoop and trying to do some bad thing like men in a middle attacks, things like that. So we really, you know, focus on the security side on the two aspects on the iLO6 and Gen11. One other thing is we continue our industry unique silicon root of trust technology. So, that one is fortunate platform making sure the platform firmware, only the authentic and legitimate image of the firmware can run on HP server. And when you check in, validating the firmware images, the root of the trust reside in the silicon. So, no one can change it. Even the bad people trying to change the root of trust, it's bond in the chips so you cannot really change. And that's why, even bad people trying to compromise, you know, install compromise the firmware image on the HPE servers, you cannot do that. Another thing is we're making a lot of enhancements to make sure security on board our HP server into your network or onto a services like a GreenLake. Give you a couple of example, for instance, like a IDevID, Initial Device ID. That one is conforming to IEEE 802.1AR and it's immutable so no one can change it. And by using the IDevID, you can really identify you are not onboarding a rogue server or unknown server, but the server that you you want to onboard, right? It's absolutely important. Another thing is like platform certificate. Platform certificate really is the measurement of the configuration. So again, this is a great feature that makes sure you receive a server from the factory and no one during the transportation touch the server and alter the configuration. >> Chinmay, what's your reaction to this new distributed NextGen cloud? You got data, security, edge, move the compute to the data, don't move the data around. These are big conversations. >> Yeah, great question, John. I think this is an important thing to consider for the end user, the service provider in all of these contexts, right? I think Koichiro mentioned some of these key elements that go into as we develop and design these new products. But for example, from a security perspective, we introduce the trust domain extensions, TDX feature, for confidential computing in Intel 4th Generation Xeon scalable processors. And that enables the isolation of user workloads in these cloud environments, et cetera. But again, going back to the point Koichiro was making where if you go to the edge, you go to the cloud and then have the edge connect to the cloud you have independent networks for system management, independent networks for user data, et cetera. So, you need the ability to create that isolation. All of this telemetry data that needs to be isolated from the user, but used by the service provider to provide the best experience. All of these are built on the foundations of technologies such as TDX, PMT, iLO6, et cetera. >> Great stuff, gentlemen. Well, we have a lot more to discuss on our next segment. We're going to take a break here before wrapping up. We'll be right back with more. You're watching "theCUBE," the leader in high tech coverage. (light music) Okay, welcome back here, on "theCUBE's" coverage of "Compute engineered for your hybrid world." I'm John Furrier, host of the Cube. We're wrapping up our discussion here on transforming compute management experience with 4th Gen Intel Xeon scalable processors and obviously HPE ProLiant Gen11. Gentlemen, welcome back. Let's get into the takeaways for this discussion. Obviously, systems management has been around for a while, but transforming that experience on the management side is super important as the environment just radically changing for the better. What are some of the key takeaways for the audience watching here that they should put into their kind of tickler file and/or put on their to-do list to keep an eye on? >> Yeah, so Gen11 and iLO6 offers the latest, greatest technologies with new generation CPUs, DDR5, PCI Gen5, and so on and on. There's a lot of things in there and also iLO6 is the most mature version of iLO and it offers the best manageability and security. On top of iLO, HP offers the best of read management options like HP OneView and Compute Ops Management. It's really a lot of the things that help user achieve a lot of the things regardless of the use case like edge computing, or distributed IT, or hybrid strategy and so on and on. And you could also have a great system management that you can unleash all the full potential of latest, greatest technology. >> Chinmay, what's your thoughts on the key takeaways? Obviously as the world's changing, more gen chips are coming out, specialized workloads, performance. I mean, I've never met anyone that says they want to run on slower infrastructure. I mean, come on, performance matters. >> Yes, no, it definitely, I think one of the key things I would say is yes, with Gen11 Intel for gen scalable we're introducing all of these technologies, but I think one of the key things that has grown over the last few years is the view of the system provider, the abstraction that's needed, right? Like the end user today is migrating a lot of what they're traditionally used to from a physical compute perspective to the cloud. Everything goes to the cloud and when that happens there's a lot of just the experience that the end user sees, but everything underneath is abstracted away and then managed by the system provider, right? So we at Intel, and of course, our partners at HP, we have spent a lot of time figuring out what are the best sets of features that provide that best system management experience that allow for that abstraction to work seamlessly without the end user noticing? And I think from that perspective, the 4th Gen Intel Xeon scalable processors is so far the best Intel product that we have introduced that is prepared for that type of abstraction. >> So, I'm going to put my customer hat on for a second. I'll ask you both. What's in it for me? I'm the customer. What's in it for me? What's the benefit to me? What does this all mean to me? What's my win? >> Yeah, I can start there. I think the key thing here is that when we create capabilities that allow you to build the best cloud, at the end of the day that efficiency, that performance, all of that translates to a better experience for the consumer, right? So, as the service provider is able to have all of these myriad capabilities to use and choose from and then manage the system experience, what that implies is that the end user sees a seamless experience as they go from one application to another as they go about their daily lives. >> Koichiro, what's your thoughts on what's in it for me? You guys got a lot of engineering going on in Gen11, every gen increase always is a step function and increase of value. What's in it for me? What do I care? What's in it for me? I'm the customer. >> Alright. Yeah, so I fully agree with Chinmay's point. You know, he lays out the all the good points, right? Again, you know what the Gen11 and iLO6 offer all the latest, greatest features and all the technology and advancements are packed in the Gen11 platform and iLO6 unleash all full potentials for those benefits. And things are really dynamic in today's world and IT system also going to be agile and the system management get really far, to the point like we never imagine what the system management can do in the past. For instance, the managing on-prem devices across multiple locations from a single point, like a single pane of glass on the cloud management system, management on the cloud, that's what really the compute office management that HP offers. It's all new and it's really help customers unleash full potential of the gear and their investment and provide the best TCO and ROIs, right? I'm very excited that all the things that all the teams have worked for the multiple years have finally come to their life and to the public. And I can't really wait to see our customers start putting their hands on and enjoy the benefit of the latest, greatest offerings. >> Yeah, 4th Gen Xeon, Gen11 ProLiant, I mean, all the things coming together, accelerators, more cores. You got data, you got compute, and you got now this idea of security, I mean, you got hitting all the points, data and security big features here, right? Data being computed in a way with Gen4 and Gen11. This is like the big theme, data security, kind of the the big part of the core here in this announcement, in this relationship. >> Absolutely. I believe, I think the key things as these new generations of processors enable is new types of compute which imply is more types of data, more types of and hence, with more types of data, more types of compute. You have more types of system management more differentiation that the service provider has to then deal with, the disaggregation that they have to deal with. So yes, absolutely this is, I think exciting times for end users, but also for new frontiers for service providers to go tackle. And we believe that the features that we're introducing with this CPU and this platform will enable them to do so. >> Well Chinmay thank you so much for sharing your Intel perspective, Koichiro with HPE. Congratulations on all that hard work and engineering coming together. Bearing fruit, as you said, Koichiro, this is an exciting time. And again, keep moving the needle. This is an important inflection point in the industry and now more than ever this compute is needed and this kind of specialization's all awesome. So, congratulations and participating in the "Transforming your compute management experience" segment. >> Thank you very much. >> Okay. I'm John Furrier with "theCUBE." You're watching the "Compute Engineered for your Hybrid World Series" sponsored by HP and Intel. Thanks for watching. (light music)

>> Welcome to "theCUBE's" coverage of "Compute Engineered for Your Hybrid World" sponsored by HPE and Intel. I'm John Furrier, host of "theCUBE" with the new fourth gen Intel Z on scalable process being announced, HPE is releasing four new HPE ProLiant Gen 11 servers and here to talk about the feature of those servers as well as the partnership between HPE and Intel, we have Darren Anthony, director compute server product manager with HPE, and Suzi Jewett, general manager of the Zion products with Intel. Thanks for joining us folks. Appreciate you coming on. >> Thanks for having us. (Suzi's speech drowned out) >> This segment is about NextGen enhanced scale of process. Obviously the Zion fourth gen. This is really cool stuff. What's the most exciting element of the new Intel fourth gen Zion processor? >> Yeah, John, thanks for asking. Of course, I'm very excited about the fourth gen Intel Zion processor. I think the best thing that we'll be delivering is our new ong package accelerators, which you know allows us to service the majority of the server market, which still is buying in that mid core count range and provide workload acceleration that matters for every one of the products that we sell. And that workload acceleration allows us to drive better efficiency and allows us to really dive into improved sustainability and workload optimizations for the data center. >> It's about al the rage about the cores. Now we got the acceleration continued to innovate with Zion. Congratulations. Darren what does the new Intel fourth Gen Zion processes mean for HPE from the ProLiant perspective? You're on Gen 11 servers. What's in it? What's it mean for you guys and for your customers? >> Well, John, first we got to talk about the great partnership. HPE and Intel have been partners delivering innovation for our server products for over 30 years, and we're continuing that partnership with HP ProLiant Gen 11 servers to deliver compelling business outcomes for our customers. Customers are on a digital transformation journey, and they need the right compute to power applications, accelerate analytics, and turn data into value. HP ProLiant Compute is engineered for your hybrid world and delivers optimized performance for your workloads. With HP ProLiant Gen 11 servers and Intel fourth gen Zion processors, you can have the performance to accelerate workloads from the data center to the edge. With Gen 11, we have more. More performance to meet new workload demands. With PCI Gen five which delivers increased bandwidth with room for more data and graphics accelerators for workloads like VDI, our new demands at the edge. DDR5 memory springs greater bandwidth and performance increases for low latency and memory solutions for database and analytics workloads and higher clock speed CPU chipset combinations for processor intensive AI and machine learning applications. >> Got to love the low latency. Got to love the more performance. Got to love the engineered for the hybrid world. You mentioned that. Can you elaborate more on engineered for the hybrid world? What does that mean? Can you elaborate? >> Well, HP ProLiant Compute is based on three pillars. First, an intuitive cloud operating experience with HPE GreenLake compute ops management. Second, trusted security by design with a zero trust approach from silicone to cloud. And third, optimize for performance for your workloads, whether you deploy as a traditional infrastructure or a pay-as-you-go model with HPE GreenLake on-premise at the edge in a colo and in the public cloud. >> Well, thanks Suzi and Darren, we'll be right back. We're going to take a quick break. We're going to come back and do a deep dive and get into the ProLiant Gen 11 servers. We're going to dig into it. You're watching "theCUBE," the leader in high tech enterprise coverage. We'll be right back. (upbeat music) >> Hello everyone. Welcome back continuing coverage of "theCUBE's" "Compute Engineered for Your Hybrid World" with HP and Intel. I'm John Furrier, host of "theCUBE'" joined back by Darren Anthony from HPE and Suzie Jewitt from Intel. as we continue our conversation on the fourth gen Zion scalable processor and HP Gen 11 servers. Suzi, we'll start with you first. Can you give us some use cases around the new fourth gen, Intel Zion scalable processors? >> Yeah, I'd love to. What we're really seeing with an ever-changing market, and you know, adapting to that is we're leading with that workload focus approach. Some examples, you know, that we see are with vRAN. For in vRAN, we estimate the 2021 market size was about 150 million, and we expect a CAG of almost 30% all the way through 2030. So we're really focused on that, on, you know deployed edge use cases, growing about 10% to over 50% in 2026. And HPC use cases, of course, continue to grow at a study CAGR around, you know, about 7%. Then last but not least is cloud. So we're, you know, targeting a growth rate of almost 20% over a five year CAGR. And the fourth G Zion is targeted to all of those workloads, both through our architectural improvements that, you know deliver node level performance as well as our operational improvements that deliver data center performance. And wrapping that all around with the accelerators that I talked about earlier that provide that workload specific improvements that get us to where our customers need to operationalize in their data center. >> I love the focus solutions around seeing compute used that way and the processors. Great stuff. Darren, how do you see the new ProLiant Gen 11 servers being used on your side? I mean obviously, you've got the customers deploying the servers. What are you seeing on those workloads? Those targeted workloads? (John chuckling) >> Well, you know, very much in line with what Suzi was talking about. The generational improvements that we're seeing in performance for Gen 11. They're outstanding for many different use cases. You know, obviously VDI. what we're seeing a lot is around the analytics. You know, with moving to the edge, there's a lot more data. Customers need to convert that data into something tangible. Something that's actionable. And so we're really seeing the strong use cases around analytics in order to mine that data and to make better, faster decisions for the customers. >> You know what I love about this market is people really want to hear about performance. They love speed, they love the power, and low power, by the way on the other side. So, you know, this has really been a big part of the focus now this year. We're seeing a lot more discussion. Suzi, can you tell us more about the key performance improvements on the processors? And Darren, if you don't mind, if you can follow up on the benefits of the new servers relative to the performance. Suzi? >> Sure, so, you know, at a standard expectant rate we're looking at, you know, 60% gen over gen, from our previous third gen Zion, but more importantly as we've been mentioning is the performance improvement we get with the accelerators. As an example, an average accelerator proof point that we have is 2.9 times improvement in performance per wat for accelerated workloads versus non-accelerated workloads. Additionally, we're seeing really great and performance improvement in low jitter so almost 20 to 50 times improvement versus previous gen in jitter on particular workloads which is really important, you know to our cloud service providers. >> Darren, what's your follow up on this? This is obviously translates into the the gen 11 servers. >> Well, you know, this generation. Huge improvements across the board. And what we're seeing is that not only customers are prepared for what they need now you know, workloads are evolving and transitioning. Customers need more. They're doing more. They're doing more analytics. And so not only do you have the performance you need now, but it's actually built for the future. We know that customers are looking to take in that data and do something and work with the data wherever it resides within their infrastructure. We also see customers that are beginning to move servers out of a centralized data center more to the edge, closer to the way that where the data resides. And so this new generation really tremendous for that. Seeing a lot of benefits for the customers from that perspective. >> Okay, Suzi, Darren, I want to get your thoughts on one of the hottest trends happening right now. Obviously machine learning and AI has always been hot, but recently more and more focus has been on AI. As you start to see this kind of next gen kind of AI coming on, and the younger generation of developers, you know, they're all into this. This is really the one of the hottest trends of AI. We've seen the momentum and accelerations kind of going next level. Can you guys comment on how Zion here and Gen 11 are tying into that? What's that mean for AI? >> So, exactly. With the fourth gen Intel Zion, we have one of our key you know, on package accelerators in every core is our AMX. It delivers up to 10 times improvement on inference and training versus previous gens, and, you know throws the competition out of the water. So we are really excited for our AI performance leading with Zion >> And- >> And John, what we're seeing is that this next generation, you know you're absolutely right, you know. Workloads a lot more focused. A lot more taking more advantage of AI machine learning capabilities. And with this generation together with the Intel Zion fourth gen, you know what we're seeing is the opportunity with that increase in IO bandwidth that now we have an opportunity for those applications and those use cases and those workloads to take advantage of this capability. We haven't had that before, but now more than ever, we've actually, you know opened the throttle with the performance and with the capabilities to support those workloads. >> That's great stuff. And you know, the AI stuff also does all lot on differentiated heavy lifting, and it needs processing power. It needs the servers. This is just, (John chuckling) it creates more and more value. This is right in line. Congratulations. Super excited by that call out. Really appreciate it. Thanks Suzi and Darren. Really appreciate. A lot more discuss with you guys as we go a little bit deeper. We're going to talk about security and wrap things up after this short break. I'm John Furrier, "theCUBE," the leader in enterprise tech coverage. (upbeat music) >> Welcome back to "theCUBE's" coverage of "Compute Engineered for Your Hybrid World." I'm John Furrier, host of "theCUBE" joined by Darren Anthony from HPE and Suzi Jewett from Intel as we turn our discussion to security. A lot of great features with the new Zion scalable processor's gen four and the ProLiant gen 11. Let's get into it. Suzi, what are some of the cool features of the fourth gen Intel Zion scalable processors? >> Sure, John, I'd love to talk about it. With fourth gen, Intel offers the most comprehensive confidential computing portfolio to really enhance data security and ingest regulatory compliance and sovereignty concerns. A couple examples of those features and technologies that we've included are a larger baseline enclave with the SGX technology, which is our application isolation technology and our Intel CET substantially reduces the risk of whole class software-based attacks. That wrapped around at a platform level really allows us, you know, to secure workload acceleration software and ensure platform integrity. >> Darren, this is a great enablement for HPE. Can you tell us about the security with the the new HP ProLiant Gen 11 servers? >> Absolutely, John. So HP ProLiant engineered with a fundamental security approach to defend against increasingly complex threats and uncompromising focus on state-of-the-art security innovations that are built right into our DNA, from silicon to software, from the factory to the cloud. It's our goal to protect the customer's infrastructure, workloads, and the data from threats to hardware and risk from third party software and devices. So Gen 11 is just a continuation of the the great technological innovations that we've had around providing zero trust architecture. We're extending our Silicon Root of Trust, and it's just a motion forward for innovating on that Silicon Root of Trust that we've had. So with Silicon Root of Trust, we protect millions of lines of firmware code from malware and ransomware with the digital footprint that's unique to the server. With this Silicon Root of Trust, we're securing over 4 million HPE servers around the world and beyond that Silicon, the authentication of and extending this to our partner ecosystem, the authentication of platform components, such as network interface cards and storage controllers just gives us that protection against additional entry points of security threats that can compromise the entire server infrastructure. With this latest version, we're also doing authentication integrity with those components using the security protocol and data model protocol or SPDM. But we know that trusted and protected infrastructure begins with a secure supply chain, a layer of protection that starts at the manufacturing floor. HP provides you optimized protection for ProLiant servers from trusted suppliers to the factories and into transit to the customer. >> Any final messages Darren you'd like to share with your audience on the hybrid world engineering for the hybrid world security overall the new Gen 11 servers with the Zion fourth generation process scalable processors? >> Well, it's really about choice. Having the right choice for your compute, and we know HPE ProLiant servers, together, ProLiant Gen 11 servers together with the new Zion processors is the right choice. Delivering the capabilities to performance and the efficiency that customers need to run their most complex workloads and their most performance hungry work workloads. We're really excited about this next generation of platforms. >> ProLiant Gen 11. Suzi, great customer for Intel. You got the fourth generation Zion scalable processes. We've been tracking multiple generations for both of you guys for many, many years now, the past decade. A lot of growth, a lot of innovation. I'll give you the last word on the series here on this segment. Can you share the the collaboration between Intel and HP? What does it mean and what's that mean for customers? Can you give your thoughts and share your views on the relationship with with HPE? >> Yeah, we value, obviously HPE as one of our key customers. We partner with them from the beginning of when we are defining the product all the way through the development and validation. HP has been a great partner in making sure that we deliver collaboratively to the needs of their customers and our customers all together to make sure that we get the best product in the market that meets our customer needs allowing for the flexibility, the operational efficiency, the security that our markets demand. >> Darren, Suzi, thank you so much. You know, "Compute for an Engineered Hybrid World" is really important. Compute is... (John stuttering) We need more compute. (John chuckling) Give us more power and less power on the sustainability side. So a lot of great advances. Thank you so much for spending the time and give us an overview on the innovation around the Zion and, and the ProLiant Gen 11. Appreciate your time. Appreciate it. >> You're welcome. Thanks for having us. >> You're watching "theCUBE's" coverage of "Compute Engineered for Your Hybrid World" sponsored by HPE and Intel. I'm John Furrier with "theCUBE." Thanks for watching. (upbeat music)

>> Hello, everyone. Welcome to theCUBE's coverage of "Compute Engineered for your Hybrid World," sponsored by HPE and Intel. Today we're going to discuss the new 4th Gen Intel Xeon Scalable process impact on containers and AI. I'm John Furrier, your host of theCUBE, and I'm joined by three experts to guide us along. We have Jordan Plum, Senior Director of AI and products for Intel, Bradley Sweeney, Big Data and AI Product Manager, Mainstream Compute Workloads at HPE, and Gary Wang, Containers Product Manager, Mainstream Compute Workloads at HPE. Welcome to the program gentlemen. Thanks for coming on. >> Thanks John. >> Thank you for having us. >> This segment is going to be talking about containers to deploy high performance AI applications. This is a really important area right now. We're seeing a lot more AI deployed, kind of next gen AI coming. How is HPE supporting and testing and delivering containers for AI? >> Yeah, so what we're doing from HPE's perspective is we're taking these container platforms, combining with the next generation Intel servers to fully validate the deployment of the containers. So what we're doing is we're publishing the reference architectures. We're creating these automation scripts, and also creating a monitoring and security strategy for these container platforms. So for customers to easily deploy these Kubernete clusters and to easily secure their community environments. >> Gary, give us a quick overview of the new Proliant DL 360 and 380 Gen 11 servers. >> Yeah, the load, for example, for container platforms what we're seeing mostly is the DL 360 and DL 380 for matching really well for container use cases, especially for AI. The DL 360, with the expended now the DDR five memory and the new PCI five slots really, really helps the speeds to deploy these container environments and also to grow the data that's required to store it within these container environments. So for example, like the DL 380 if you want to deploy a data fabric whether it's the Ezmeral data fabric or different vendors data fabric software you can do so with the DL 360 and DL 380 with the new Intel Xeon processors. >> How does HP help customers with Kubernetes deployments? >> Yeah, like I mentioned earlier so we do a full validation to ensure the container deployment is easy and it's fast. So we create these automation scripts and then we publish them on GitHub for customers to use and to reference. So they can take that and then they can adjust as they need to. But following the deployment guide that we provide will make the, deploy the community deployment much easier, much faster. So we also have demo videos that's also published and then for reference architecture document that's published to guide the customer step by step through the process. >> Great stuff. Thanks everyone. We'll be going to take a quick break here and come back. We're going to do a deep dive on the fourth gen Intel Xeon scalable process and the impact on AI and containers. You're watching theCUBE, the leader in tech coverage. We'll be right back. (intense music) Hey, welcome back to theCUBE's continuing coverage of "Compute Engineered for your Hybrid World" series. I'm John Furrier with the Cube, joined by Jordan Plum with Intel, Bradley Sweeney with HPE, and Gary Wang from HPE. We're going to do a drill down and do a deeper dive into the AI containers with the fourth gen Intel Xeon scalable processors we appreciate your time coming in. Jordan, great to see you. I got to ask you right out of the gate, what is the view right now in terms of Intel's approach to containers for AI? It's hot right now. AI is booming. You're seeing kind of next gen use cases. What's your approach to containers relative to AI? >> Thanks John and thanks for the question. With the fourth generation Xeon scalable processor launch we have tested and validated this platform with over 400 deep learning and machine learning models and workloads. These models and workloads are publicly available in the framework repositories and they can be downloaded by anybody. Yet customers are not only looking for model validation they're looking for model performance and performance is usually a combination of a given throughput at a target latency. And to do that in the data center all the way to the factory floor, this is not always delivered from these generic proxy models that are publicly available in the industry. >> You know, performance is critical. We're seeing more and more developers saying, "Hey, I want to go faster on a better platform, faster all the time." No one wants to run slower stuff, that's for sure. Can you talk more about the different container approaches Intel is pursuing? >> Sure. First our approach is to meet the customers where they are and help them build and deploy AI everywhere. Some customers just want to focus on deployment they have more mature use cases, and they just want to download a model that works that's high performing and run. Others are really focused more on development and innovation. They want to build and train models from scratch or at least highly customize them. Therefore we have several container approaches to accelerate the customer's time to solution and help them meet their business SLA along their AI journey. >> So what developers can just download these containers and just go? >> Yeah, so let me talk about the different kinds of containers we have. We start off with pre-trained containers. We'll have about 55 or more of these containers where the model is actually pre-trained, highly performant, some are optimized for low latency, others are optimized for throughput and the customers can just download these from Intel's website or from HPE and they can just go into production right away. >> That's great. A lot of choice. People can just get jump right in. That's awesome. Good, good choice for developers. They want more faster velocity. We know that. What else does Intel provide? Can you share some thoughts there? What you guys else provide developers? >> Yeah, so we talked about how hey some are just focused on deployment and they maybe they have more mature use cases. Other customers really want to do some more customization or optimization. So we have another class of containers called development containers and this includes not just the kind of a model itself but it's integrated with the framework and some other capabilities and techniques like model serving. So now that customers can download just not only the model but an entire AI stack and they can be sort of do some optimizations but they can also be sure that Intel has optimized that specific stack on top of the HPE servers. >> So it sounds simple to just get started using the DL model and containers. Is that it? Where, what else are customers looking for? What can you take a little bit deeper? >> Yeah, not quite. Well, while the customer customer's ability to reproduce performance on their site that HPE and Intel have measured in our own labs is fantastic. That's not actually what the customer is only trying to do. They're actually building very complex end-to-end AI pipelines, okay? And a lot of data scientists are really good at building models, really good at building algorithms but they're less experienced in building end-to-end pipelines especially 'cause the number of use cases end-to-end are kind of infinite. So we are building end-to-end pipeline containers for use cases like media analytics and sentiment analysis, anomaly detection. Therefore a customer can download these end-to-end containers, right? They can either use them as a reference, just like, see how we built them and maybe they have some changes in their own data center where they like to use different tools, but they can just see, "Okay this is what's possible with an end-to-end container on top of an HPE server." And other cases they could actually, if the overlap in the use case is pretty close, they can just take our containers and go directly into production. So this provides developers, all three types of containers that I discussed provide developers an easy starting point to get them up and running quickly and make them productive. And that's a really important point. You talked a lot about performance, John. But really when we talk to data scientists what they really want to be is productive, right? They're under pressure to change the business to transform the business and containers is a great way to get started fast >> People take product productivity, you know, seriously now with developer productivity is the hottest trend obviously they want performance. Totally nailed it. Where can customers get these containers? >> Right. Great, thank you John. Our pre-trained model containers, our developmental containers, and our end-to-end containers are available at intel.com at the developer catalog. But we'd also post these on many third party marketplaces that other people like to pull containers from. And they're frequently updated. >> Love the developer productivity angle. Great stuff. We've still got more to discuss with Jordan, Bradley, and Gary. We're going to take a short break here. You're watching theCUBE, the leader in high tech coverage. We'll be right back. (intense music) Welcome back to theCUBE's coverage of "Compute Engineered for your Hybrid World." I'm John Furrier with theCUBE and we'll be discussing and wrapping up our discussion on containers to deploy high performance AI. This is a great segment on really a lot of demand for AI and the applications involved. And we got the fourth gen Intel Xeon scalable processors with HP Gen 11 servers. Bradley, what is the top AI use case that Gen 11 HP Proliant servers are optimized for? >> Yeah, thanks John. I would have to say intelligent video analytics. It's a use case that's supplied across industries and verticals. For example, a smart hospital solution that we conducted with Nvidia and Artisight in our previous customer success we've seen 5% more hospital procedures, a 16 times return on investment using operating room coordination. With that IVA, so with the Gen 11 DL 380 that we provide using the the Intel four gen Xeon processors it can really support workloads at scale. Whether that is a smart hospital solution whether that's manufacturing at the edge security camera integration, we can do it all with Intel. >> You know what's really great about AI right now you're starting to see people starting to figure out kind of where the value is does a lot of the heavy lifting on setting things up to make humans more productive. This has been clearly now kind of going neck level. You're seeing it all in the media now and all these new tools coming out. How does HPE make it easier for customers to manage their AI workloads? I imagine there's going to be a surge in demand. How are you guys making it easier to manage their AI workloads? >> Well, I would say the biggest way we do this is through GreenLake, which is our IT as a service model. So customers deploying AI workloads can get fully-managed services to optimize not only their operations but also their spending and the cost that they're putting towards it. In addition to that we have our Gen 11 reliance servers equipped with iLO 6 technology. What this does is allows customers to securely manage their server complete environment from anywhere in the world remotely. >> Any last thoughts or message on the overall fourth gen intel Xeon based Proliant Gen 11 servers? How they will improve workload performance? >> You know, with this generation, obviously the performance is only getting ramped up as the needs and requirements for customers grow. We partner with Intel to support that. >> Jordan, gimme the last word on the container's effect on AI applications. Your thoughts as we close out. >> Yeah, great. I think it's important to remember that containers themselves don't deliver performance, right? The AI stack is a very complex set of software that's compiled together and what we're doing together is to make it easier for customers to get access to that software, to make sure it all works well together and that it can be easily installed and run on sort of a cloud native infrastructure that's hosted by HPE Proliant servers. Hence the title of this talk. How to use Containers to Deploy High Performance AI Applications. Thank you. >> Gentlemen. Thank you for your time on the Compute Engineered for your Hybrid World sponsored by HPE and Intel. Again, I love this segment for AI applications Containers to Deploy Higher Performance. This is a great topic. Thanks for your time. >> Thank you. >> Thanks John. >> Okay, I'm John. We'll be back with more coverage. See you soon. (soft music)

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

>> We're back at the Big Apple, theCUBE's coverage of MongoDB World 2022. Sahir Azam is here, he's the Chief Product Officer of MongoDB, and Guillermo Rauch who's the CEO of Vercel. Hot off the keynotes from this morning guys, good job. >> Thank you. >> Thank you. >> Thank you for joining us here. Thanks for having us. Guillermo when it comes to modern web development, you know the back-end, the cloud guys got to it kind of sewn up, >> you know- >> Guillermo: Forget about it. >> But all the action's in the front end, and that's where you are. Explain Vercel. >> Yeah so Vercel is the company that pioneers front-end development as serverless infrastructure. So we built Next.js which is the most popular React framework in the world. This is what front-end engineers choose to build innovative UI's, beautiful websites. Companies like Dior and GitHub and TikTok and Twitch, which we mentioned in the keynote, are powering their entire dot-coms or all of their new parts of their dot-coms with Next.js. And Vercel is the serverless platform where you can deploy frameworks like in Next.js and others like Svelte and Vue to create really fast experiences on the web. >> So I hear, so serverless, I hear that's the hot trend. You guys made some announcements today. I mean when you look at the, we have spending data with our friends at ETR right down the street. I mean it's just off the charts, whether it's Amazon, Google, Azure Functions, I mean it's just exploding. >> Sahir: Yeah, it's I think in many ways, it's a natural trend. You know, we talk a lot about, whether it be today's keynote or another industry talks you see around our industry that developers are constantly looking for ways to focus on innovation and the business logic that defines their application and as opposed to managing the plumbing, and management of infrastructure. And we've seen this happen over and over again across every layer of the stack. And so for us, you know MongoDB, we have a bit of, you know sort of a lens of a broad spectrum of the market. We certainly have you know, large enterprises that are modernizing existing kind of core systems, then we have developers all over the world who are building the next big best thing. And that's what led us to partner with Vercel is just the bleeding edge of developers building in a new way, in a much more efficient way. And we wanted to make sure we provide a data platform that fits naturally in the way they want to work. >> So explain to our audience the trade-offs of serverless, and I want to get into sort of how you've resolved that. And then I want to hear from Guillermo, what that means for developers. >> Sahir: Yeah in our case, we don't view it as an either or, there are certain workloads and definitely certain companies that will gravitate towards a more traditional database infrastructure where they're choosing the configuration of their cluster. They want full control over it. And that provides, you know, certain benefits around cost predictability or isolation or perceived benefits at least of those things. And customers will gravitate towards that. Now on the flip side, if you're building a new application or you want the ability to scale seamlessly and not have to worry about any of the plumbing, serverless is clearly the easier model. So over the long term, we certainly expect to see as a mix of things, more and more serverless workloads being built on our platform and just generally in the industry, which is why we leaned in so heavily on investing in Atlas serverless. But the flexibility to not be forced into a particular model, but to get the same database experience across your application and even switch between them is an important characteristic for us as we build going forward. >> And you stressed the cost efficiency, and not having to worry about, you know, starting cold. You've architected around that, and what does that mean for a developer? >> Guillermo: For a developer it means that you kind of get the best of both worlds, right? Like you get the best possible performance. Front-end developers are extremely sensitive to this. That's why us pioneering this concept, serverless front-end, has put us in a very privileged position because we have to deliver that really quick time to first buy, that really quick paint. So any of the old trade-offs of serverless are not accepted by the market. You have to be extremely fast. You have to be instant to deliver that front-end content. So what we talked about today for example, with the Vercel Edge network, we're removing all of the cost of that like first hit. That cold start doesn't really exist. And now we're seeing it all across the board, going into the back-end where Mongo has also gotten rid of it. >> Dave: How do you guys collaborate? What's the focus of integration specifically from, you know, an engineering resource standpoint? >> Yeah the main idea is, idea to global app in seconds, right? You have your idea. We give you the framework. We don't give you infrastructure primitives. We give you all the necessary tools to start your application. In practice this means you host it in a Git repo. You import it onto Vercel. You install the Mongo integration. Now your front-end and your data back-end are connected. And then your application just goes global in seconds. >> So, okay. So you've abstracted away the complexity of those primitives, is that correct? >> Guillermo: Absolutely. >> Do do developers ever say, "That's awesome but I'd like to get to them every now and then." Or do you not allow that? >> Definitely. We expose all the underlying APIs, and the key thing we hear is that, especially with the push for usage-based billing models, observability is of the essence. So at any time you have to be able to query, in real time, every data point that the platform is observing. We give you performance analytics in real time to see how your front-end is performing. We give you statistics about how often you're querying your back-end and so on, and your cache hit ratios. So what I talked about today in the keynote is, it's not just about throwing more compute at the problem, but the ability to use the edge to your advantage to memoize computation and reuse it across different visits. >> When we think of mission critical historically, you know, you think about going to the ATM, right? I mean a financial transaction. But Mongo is positioning for mission critical applications across a variety of industries. Do we need to rethink what mission critical means? >> I think it's all in the eye of the beholder so to speak. If you're a new business starting up, your software and your application is your entire business. So if you have a cold start latency or God forbid something actually goes down, you don't have a business. So it's just as mission critical to that founder of a new business and new technology as it is, you know, an established enterprise that's running sort of a more, you know, day-to-day application that we may all interact with. So we treat all of those scenarios with equal fervor and importance right? And many times, it's a lot of those new experiences that the become the day-to-day experiences for us globally, and are super important. And we power all of those, whether it be an established enterprise all the way to the next big startup. >> I often talk about COVID as the forced march to digital. >> Sahir: Mm-Hmm. >> Which was obviously a little bit rushed, but if you weren't in digital business, you were out of business. And so now you're seeing people step back and say, "All right, let's be more thoughtful about our digital transformation. We've got some time, we've obviously learned some things made some mistakes." It's all about the customer experience though. And that becomes mission critical right? What are you seeing Guillermo, in terms of the patterns in digital transformation now that we're sort of exiting the isolation economy? >> One thing that comes to mind is, we're seeing that it's not always predictable how fast you're going to grow in this digital economy. So we have customers in the ecommerce space, they do a drop and they're piggybacking on serverless to give them that ability to instantly scale. And they couldn't even prepare for some of these events. We see that a lot with the Web3 space and NFT drops, where they're building in such a way that they're not sensitive to this massive fluctuations in traffic. They're taking it for granted. We've put in so much work together behind the scenes to support it. But the digital native creator just, "Oh things are scaling from one second to the next like I'm hitting like 20,000 requests per second, no problem Vercel is handling it." But the amount of infrastructural work that's gone behind the scenes in support has been incredible. >> We see that in gaming all the time, you know it's really hard for a gaming company to necessarily predict where in the globe a game's going to be particularly hot. Games get super popular super fast if they're successful, it's really hard to predict. It's another vertical that's got a similar dynamic. >> So gaming, crypto, so you're saying that you're able to assist your customers in architecting so that the website doesn't crash. >> Guillermo: Absolutely. >> But at the same time, if the the business dynamic changes, they can dial down. >> Yeah. >> Right and in many ways, slow is the new down, right? And if somebody has a slow experience they're going to leave your site just as much as if it's- >> I'm out of here- >> You were down. So you know, it's really maintaining that really fast performance, that amazing customer experience. Because this is all measured, it's scientific. Like anytime there's friction in the process, you're going to lose customers. >> So obviously people are excited about your keynote, but what have they been saying? Any specific comments you can share, or questions that you got that were really interesting or? >> I'm already getting links to the apps that people are deploying. So the whole idea- >> Come on! >> All over the world. Yeah so it's already working I'm excited. >> So they were show they were showing off, "Look what I did" Really? >> Yeah on Twitter. >> That's amazing. >> I think from my standpoint, I got a question earlier, we were with a bunch of financial analysts and investors, and they said they've been talking to a lot of the customers in the halls. And just to see, you know, from the last time we were all in person, the number of our customers that are using multiple capabilities across this idea of a developer data platform, you know, certainly MongoDB's been a popular core database open source for a long time. But the new capabilities around search, analytics, mobile being adopted much more broadly to power these experiences is the most exciting thing from our side. >> So from 2019 to now, you're saying substantial uptick in adoption for these features? >> Yeah. And many of them are new. >> Time series as well, that's pretty new, so yeah. >> Yeah and you know, our philosophy of development at MongoDB is to get capabilities in the hands of customers early. Get that feedback to enrich and drive that product-market fit. And over the last three years especially, we've been transitioning from a single product kind of core, you know, non relational modern database to a data platform, a developer data platform that adds more and more capabilities to power these modern applications. And a lot of those were released during the pandemic. Certainly we talked about them in our virtual conferences and all the zoom meetings we had over the years. But to actually go talk to all these customers, this is the largest conference we've ever put on, and to get a sense of, wow all the amazing things they're doing with them, it's definitely a different feeling when we're all together. >> So that's interesting, when you have such a hot product, product-led growth which is what Mongo has been in, and you add these new features. They're coming from the developers who are saying, "Hey, we need this." >> Yip. >> Okay so you have a pretty high degree of confidence, but how do you know when you have product-market fit? I mean, is it adoption, usage, renewals? What's your metric? >> Yeah I think it's a mix of quantitative measures that you know, around conversion rates, the size of your funnel, the retention rate, NPS which obviously can be measured, but also just qualitative. You know when you're talking to a developer or a technology executive around what their needs are, and then you see how they actually apply it to solve a problem, it's that balance between the qualitative and the quantitative measurement of things. And you can just sort of, frankly you can feel it. You can see it in the numbers sure, but you can kind of feel that excitement, you can see that adoption and what it empowers people to do. And so to me, as a product leader, it's always a blend of those things. If you get too obsessed with purely the metrics, you can always over optimize something for the wrong reason. So you have to bring in that qualitative feedback to balance yourself out. >> Right. >> Guillermo, what's next? What do you not have that you want from Sahir and Mongo? >> So the natural next step for serverless computing is, is the Edge. So we have to auto-scale, we have to tolerate fares. We have to be avail. We have to be easy, but we have to be global. And right now we've been doing this by using a lot of techniques like caching and replication and things like this. But the future's about personalizing even more to each visitor depending on where they are. So if I'm in New York, I want to get the latest offers for New York on demand, just for me, and using AI to continue to personalize that experience. So giving the developer these tools in a way where it feels natural to build an application like this. It doesn't feel like, "Oh I'm going to do this year 10 if I make it, I'm going to do it since the very beginning." >> Dave: Okay interesting. So that says to me that I'm not going to make a round trip to the cloud necessarily for that experience. So I'm going to have some kind, Apple today, at the Worldwide Developer Conference announced the M2, right. I've been looking at the M1 Ultra, and I'm going wow look at that! And so- >> Sahir: You were talking about that new one backstage. >> I mean it's this amazing pace of Silicon development and they're focusing on the NPU and you look at what Tesla's doing. I mean it's just incredible. So you're going to have some new hardware architecture that emerges. Most of the AI that's done today is modeling in the cloud. You're going to have a real time inferencing at the Edge. So that's not going to do the round trip. There's going to be a data store there, I think it has to be. You're going to persist some of the data, maybe not all of it. So it's a whole new architecture- >> Sahir: Absolutely. >> That's developing. That sounds very disruptive. >> Sahir: Yeah. >> How do you think about that, and how does Mongo play there? Guillermo first. >> What I spent a lot of time thinking about is obviously the developer experience, giving the programmer a programming model that is natural, intuitive, and produces its great results. So if they have to think about data that's local because of regulatory reasons for example, how can we let the framework guide them to success? I'm just writing an application I deployed to the cloud and then everything else is figured out. >> Yeah or speed of light is another challenge. (Sahir and Guillermo laugh) >> How can we overcome the speed of light is our next task for sure. >> Well you're working on that aren't you? You've got the best engineers on that one. (Sahir and Guillermo laugh) >> We can solve a lot of problems, I'm not sure of that one. >> So Mongo plays in that scenario or? >> Yeah so I think, absolutely you know, we've been focused heavily on becoming the globally distributed cloud data layer. The back-end data layer that allows you to persist data to align with performance and move data where it needs to be globally or deal with data sovereignty, data nationalism that's starting to rise, but absolutely there is more data being pushed out to the Edge, to your point around processing or inference happening at the Edge. And there's going to be a globally distributed front-end layer as well, whether data and processing takes apart. And so we're focused on one, making sure the data connectivity and the layer is all connected into one unified architecture. We do that in combination with technologies that we have that do with mobility or edge distribution and synchronization of data with realm. And we do it with partnerships. We have edge partnerships with AWS and Verizon. We have partnerships with a lot of CVM players who are building out that Edge platform and making sure that MongoDB is either connected to it or just driving that synchronization back and forth. >> I call that unified experience super cloud, Robbie Belson from Verizon the cloud continuum, but that consistent experience for developers whether you're on Prim, whether you're in you know, Azure, Google, AWS, and ultimately the Edge. That's the big- >> That's where it's going. >> White space right now I'm hearing, Guillermo, right? >> I think it'll define the next generation of how software is built. And we're seeing this almost like a coalition course between some of the ideas that the Web3 developers are excited about, which is like decentralization almost to the extreme. But the Web2 also needs more decentralization, because we're seeing it with like, the data needs to be local to me, I need more privacy. I was looking at the latest encryption features in Mongo, like I think both Web2 need to incorporate more of the ideas of Web3 and vice versa to create the best possible consumer experience. Privacy matters more than ever before. Latency for conversion matters more than ever before. And regulations are changing. >> Sahir: Yeah. >> And you talked about Web3 earlier, talked about new protocols, a new distributed you know, decentralized system emerging, new hardware architectures. I really believe we really think that new economics are going to bleed back into the data center, and yeah every 15 years or so this industry gets disrupted. >> Sahir: Yeah. >> Guillermo: Absolutely. >> You know you ain't see nothing yet guys. >> We all talked about hardware becoming commoditized 10, 15 years ago- >> Yeah of course. >> We get the virtualization, and it's like nope not at all. It's actually a lot of invention happening. >> The lower the price the more the consumption. So guys thanks so much. Great conversation. >> Thank you. >> Really appreciate your time. >> Really appreciate it I enjoyed the conversation. >> All right and thanks for watching. Keep it right there. We'll be back with our next segment right after this short break. Dave Vellante for theCUBE's coverage of MongoDB World 2022. >> Man Offscreen: Clear. (clapping) >> All right wow. Don't get up. >> Sahir: Okay. >> Is that a Moonwatch? >> Sahir: It is a Speedmaster but it's that the-

>> Welcome back to New York City everybody. This is The Cube's coverage of MongoDB World 2022, Dev Ittycheria, here is the president and CEO of MongoDB. Thanks for spending some time with us. >> It's Great to be here Dave, thanks for having me. >> You're very welcome. So your keynotes this morning, I was hearkening back to Steve Ballmer, running around the stage screaming, developers, developers, developers. You weren't jumping around like a madman, but the message was the same. And you've not deviated from that message. I remember when it was 10th Gen, so you've been consistent. >> Yes. >> Why is Mongo DB so alluring to developers? >> Yeah, because I would say the reason we're so popular Dave is that our whole business was founded on the ethos, so making developers incredibly productive. Just getting the infrastructure out of the way so that the developers is really focused on what's important and that's building great applications that transform their business. And the way you do that is you look at where they spend most of the time. and they spend most of the time working with data. How do you present data, the right data, the right time, at the right place, and the right way. And when you remove the friction of working with data, you unleash so much more productivity, which people just say, oh my goodness, I can move so much faster. Product leaders can get products out the door faster than the competitors. Senior level executives can seize new opportunities or respond to new threats. And that was so profound during COVID when everyone had to think about pivoting their business. >> When you came to MongoDB, why did you choose this company? What was it that excited you about it? >> I get that question a lot. I would say conventional wisdom would suggest that MongoDB was not a great choice. There weren't that many companies who were very successful in open source, Red Hat was the only one. No one had really built a deep technology company in New York city. They say, you got to do it in the valley. And database companies need a lot of capital. Now turns out that raising capital of this past decade was a lot easier, but it still takes a lot of time, and a lot of capitals, you have to have a lot of patience. When I did my diligence, I was actually a VC before I joined MongoDB. The whole next generation database segment was really taking off. And actually I looked at some competing investments to MongoDB, and when I did my diligence, it was clear even then. And this is circa 2012, that MongoDB is way ahead in terms of customer attraction, commercials, and even kind of developer mind share. And so I ended up passing those investments. and then lo and behold, I got a call from a very senior executive recruiter who said, Dev, you got to take a meeting with MongoDB, there's something really interesting going on. And they had raised a lot of capital and they had just not been able to kind of really execute in terms of the opportunity. And they realized they needed to make a change. And so one thing led to another. One of the things that really actually convinced me, is when I did my diligence, I realized the customers they had loved MongoDB. They just really weren't executing on all cylinders. And I always believe you never bet against a company whose customers love the product. And said, that's something here. The second thing I would say is open source. Yes, is true that open source was not very successful, but that was open source 1.0. Open source 2.0, the technology is much better than the commercial options. And so that convinced me. And then New York, I lived in New York a big part of my life. I think New York's a fabulous place to build a business. There's so much talent, your customers are right... You walk out the door, there's customers all over the place. And getting to Europe is very easy, Almost like flying to the west coast. So it's a very central place to build a business. >> And it's easier to fix execution, wouldn't you say? And maybe even go to market than it is to fix a product that customers really don't love. >> Correct, it's much easier to fix leadership issues, culture issues, execution issues. Nailing product market fit is very, very hard. And there were signs, there's still some issues, there's still some rough spots, but there a lot of signs that this company was very, very close, and that's why I took the bet. >> And this is before there was that huge influx of capital into the separating compute from storage and the whole cloud thing, which is interesting. Because you take a company like Cloudera, they got caught up in that and got kind of washed over. And I guess you could argue Hortonworks did too, and they could have dead ended both. And then that just didn't work. But it's interesting to see Mongo, the market kind of came to you. And that really does speak to the product. It wasn't a barrier for you. You guys have obviously a lot of work to get into the cloud with Atlas, but it seemed like a natural fit with the product. It wasn't like a complete fork. >> Well, I think the challenge that we had was we had a lot of adoption, but we had tough time commercializing the business. And at some point I had to tell the all employees, it's great that we have all these people who are using MongoDB, but if you don't start generating revenue, our investors are going to get tired of subsidizing this company. So I had to try and change the culture. And as you imagine, the engineers didn't really like the salespeople, the salespeople thought the engineers didn't really want to make any money. And what I said, like, let's all galvanize around customers and let's make them really excited and try and create a lot of value. And so we just put a lot more discipline in terms of how we prosecuted deals. We put a lot more discipline in terms of what are the problems we're trying to solve. And one thing led to another, we started building the business brick by brick. And one of the things that became clear for me was that the old open source model of trying to find that happy medium between what you give away and what you charge for, is always a tough game. Like because finding that where the paywall is, if you give away too much new features, you don't make any money. If you don't give away enough, you don't have any adoption. So you're caught in this catch-22. The best way to monetize open source, is open source as a service. And we saw Amazon do that frankly. We learned a lot from how Amazon did that. And one of the advantages that MongoDB had that I didn't fully appreciate when I joined the company, but I was very grateful. It is that they had a much more restrictive license. Which we ended up actually changing and made it even more restrictive, which allowed us to perfect ourselves from being cannibalized by the cloud providers, so that we could build our own business using our own IP that we had invested in and create a cloud service. >> That was a huge milestone. And of course you have great relationships with all the cloud providers, but it got contentious there for a while, but, you give the cloud providers an inch, they're going to take a mile. That's just the way, they're aggressive like that. But thank you for going through the history with me a little bit, because when you go back to the IPO, IPO was 2017, right? >> Correct. >> I always tell young investors, my kids especially, don't buy a stock at IPO, you're going to have a better chance, but the window from Mongo was very narrow. So, you didn't really get a much better chance a little bit. And then it's been a rocket ship since then. Sure, there's been some volatility, but you look at some of the big IPOs, like Facebook, or Snap, or even Snowflake, there was better opportunities. But you guys have executed really, really well. That's part of your ethos in your management team. And it came across on the earnings call recently. >> Yep. >> It was very optimistic, yet at the same time you set cautious tones and you got, I think high marks. >> Yes. >> For some of that caution but that execution. So talk about where you feel the business is today given the economic uncertainty? >> Well, what I'd say is we feel really good about the long term. We feel like the secular trends are really in our favor. Software's fundamentally transforming every industry. And people want to use modern software to either automate inefficient processes, enable new capabilities, drive better customer experiences. And the level of performance and scale you need for today's modern applications is profoundly different than applications yesterday. So we think we're well positioned for that. What we said on the earnings call was that we started seeing a moderation of growth, slight moderation of growth in our low end of the business in Europe. It was in our self-serve business and in the SMB space for the NQ1, towards the end of Q1. And we saw a little bit of that show up in the self-serve business in may in Q2. And that's why while we raised guidance, we basically quantified the impact, which is roughly about 30 to 35 million for the year, based on what we saw. And in that assumption, we assumed like... We just can't assume it's going to only be at the low in the market, probably some effect at the enterprise market. Maybe not as much, but there'll be some effect. So we need to factor that in. And we wanted to help kind of investors have some sort of framework to think about what the impact is. We don't want to be one of those companies that said absolutely nothing. And we don't want to be one of those companies that just waves the hand, but then it wasn't really that useful for investors. >> Yeah, I thought it was substantive. You talked about those market trends, you cited three things. The developers recognize that there are limits to legacy RDBMS. You talked about the, what I call point solutions creep. And then the document model is the best for developers. >> Great. >> And when the conversation turned to consumption, everybody's concerned about consumption obviously. You said... My take, somewhat insulated from that because you're running mission critical apps. It's not discretionary. My question to you is, should we rethink the definition of mission-critical? You think of Oracle mission critical running a bank. Mission -critical today in this digital world seems to be different, is that fair? >> Gosh, when's the last time you ever saw a website down? Like if you're running like any kind of digital channel, or engaging with the customers, or your partners, or your suppliers, you need to be up all the time. And so you need a very resilient, highly available data platform. It needs to be highly performance as you add more users, you need to be scale. And we saw a lot of that when COVID hit. Like companies had to completely repovit. And we talked about some examples where like a health and beauty retailer who was all kind of basically retail, had to suddenly pivot to e-commerce strategy. We've had streaming and gaming companies suddenly saw this massive influx of data that they scaled their operations very, very quickly. So I would say anytime you're engaging with customers, customers they're so used to the kind of the consumer facing applications. I almost joke like slow is the old down. If you're not performant, it doesn't matter. They're going to abandon you and go somewhere else. So if you're an e-commerce site and you're not performing well and not serving up the right skews, depending on what they're looking for, they're going to go somewhere else. >> So it's a click away. You talk about a hundred billion TAM, maybe that's even undercounted as you start to bring new capabilities in there. But there's no lack of market for you. >> Correct. >> How do you think about the market opportunity? >> Well, we believe... Again, software is transforming so many industries. IDC says that 715 million applications will be built over the next two to three years by 2025. To put that number of perspective, that's more apps that will be built the next three to four years than were built in the last 40. The rate and pace of innovation is as exploding. And people are building custom applications. Yes, Workday, Salesforce, other companies, commercial companies are great companies, but my competitors can use Workday or Salesforce, some of those commercial companies. That doesn't gimme a competitive advantage, what gives me a competitive advantage is building custom software that better engage my customers, that transforms my business in adding new capabilities or drives more efficiency. And the applications are only getting smarter. And so you're seeing that innovation explode and that plays to our strength. People need platforms like MongoDB to build the next generation of applications. >> So Atlas is now roughly 60% of your business, think is growing at 85%. So it's at least the midterm future. But my question to you is, is it the future? 'Cause when we start to think about the edge, it's not necessarily the cloud. You're not going to be able to go that round trip and the latency. And we had Verizon on earlier, talking about what they're doing with 5G, and the Mobile Edge. Is Mongo positioning for that edge? And is our definition of cloud changing? Where it's not just OnPrem and across clouds, but it's also out to the edge, this continuous experience. >> So I'll make two points. One, definitely we believe the applications of the future will be mobile first or purely mobile. Because one with the advent of 5G, the distinction between mobile and web is going to blur, with a hundred times faster networking speeds. But the second point I make is that how that shows up on our revenue on our income table will look like Atlas. Because we don't charge nothing for the end point, it's basically driving consumption of the back end. And so we've introduced a bunch of very, very sophisticated capabilities to synchronized data from the edge to the backend and vice versa with things like flexible sync. So we see so many customers now using that capability, whether you're field service technicians, whether you're a mobile first company, et cetera. So that will drive Atlas revenue. So on an income statement, it'll look like Atlas, but we're obviously addressing those broader set of mobile needs. >> You talk a lot about product market fit former VC, of course, Mark Andreen says, product market fit you kind of know when you see it, your hair's on fire, you can't buy a service. How do you know when you have product market fit? >> Well, one, we have the luxury of lots of customers. So they tell us pretty clearly when they're happy, and we can see that by usage behavior. Now the other benefit of a cloud service, is we can see the level of activity. We can see the level of engagement. We can see how much data they're consuming. We can see all the actions they're taking. So you get the fidelity of feedback you get from Atlas versus someone doing something behind their own firewall. And you kind of call 'em and check in on them is very, very different. So that level of insight gives us visibility in terms of what products and features have been used, gives us a sense how things going well, or is there something awry. Maybe they have misconfigured something or they don't know how to use some capabilities. So the level of engagement that we can have with a customer using a service is so much different. And so we've really invested in our customer success organization. So the byproduct of that is that our retention rates are also very, very strong. Because you have such better information about what's happening in terms of your customers. >> See retention in real time. You've been somewhat... Is just so hard to say this 'cause you're growing at 50% a year. But you're somewhat conservative about the pace of hiring for go to market. And I'm curious as to how you think about scaling, especially when you introduce new products. Atlas is several years ago. But as you extend your capabilities and add new products, how do you decide when to scale? >> So it's a constant process. We've been quite aggressive in scaling organization for a couple reasons. One, we have very low market share, so the market's vastly under penetrated. We still don't have reps in every NFL sitting in the United States, which just kind of crazy. There's other parts of the world that we are just still vastly under penetrated in. But we also look at how those organizations are doing. So if we see a team really killing it, we're going to deploy more resources. Because one, it tells us there's more opportunity there, and there's a strong team there. If we see a team that maybe is struggling a little bit, we'll try and uncover. Rather than just applying more resources in, we'll try and uncover what are the issues and make sure we stabilize the organization and then devote resources. It's all in the measure of like being very disciplined about where we deploy our resources, to get those kind of returns. And on the product side, we obviously go through a very iterative process and kind of do rank order all the projects and what we think the expected returns are. Obviously, we look at the customer feedback, we look at what our strategic priorities are. And that informs what projects we fund and what projects kind of are below the line. And we do that over and over again every quarter. So every quarter we revisit the business, we have a very QBR centric culture. So we're constantly checking in and seeing how the business is operating. And then we make those investment decisions. In general, we've been investing very aggressively in terms of expanding our reach around the world. >> It seems like, well, with Mongo, your product portfolios... From an outside observer standpoint, it seems like you've always had pretty good product market fit. But I was curious, in your VC days, would you ever encourage companies to scale go to market prior to having confidence in product market fit? Or did you always see those as sequential activities? >> Well, I think the challenge is this part it's analysis part is judgment. So you don't necessarily have to have perfect product market fit to start investing. But you also don't want to plow a bunch of resources and realize the product doesn't work and then how you're burning through a lot of cash. So there's a little bit of art to the process. When I joined MongoDB, I could tell that we had a strong engineering team. They knew how to build high quality products, but we just struggled with commercialization. The culture wasn't great across the company. And we had some leadership challenges. So that's when I joined, I kind of focused on those things and tried to bring the organization together. And slowly we started chipping away and making people feel like they were winners. And once you start winning, that becomes contagious. And then the nice thing is when you start winning, you get a lot more customer feedback. That feedback helps you refine your products even more, which then adds... It's like the flywheel effect that starts taking off. >> So it seems the culture's working now. Do you have a favorite product from the announcements today? >> Well, I really like our foray to analytics. And essentially what we're seeing is really two big trends. One you're seeing applications get smarter. What applications are doing is really automating a lot of processes and rather than someone having to press a button. Based on analytics, you can automate a lot of decision making. So that's one theme that we're seeing as applications get smarter. The second theme is that people want more and more insight in terms of what's happening. And the source of that is insights is your operational database. Because that's where you're having transactions, that's where you know what products are selling, that's where you know what customers are buying. So people want more and more real time data versus waiting to take that data, put it somewhere else and then run reports and then get some update at the end of the night or maybe at the week. So that's driving a lot of really interesting use cases. And especially when you marry in things like time series use cases where you're collecting a lot of data people want to see trend analysis what's happening. Which I think it's a very exciting area. We introduced a very cool feature called Queryable Encryption, which basically... The problem with encrypting data, is you can't really query it because my definition's encrypted. >> Yeah, you're right. >> But obviously data security is very important. What we announced, is we're using very sophisticated cryptography. People can query the data, but they don't have really access to the data. So it really protects you from like data breaches or malicious users accessing your data, but you still can kind of make that data usable. So that was a very interesting announcer that we made today. >> Sounds like magic without the performance hit. >> Yes. >> You can do that. Dev, thanks so much for coming in The Cube. Congratulations on all activity, bumper sticker on day one. >> Oh, it's super exciting. The energy was palpable, 3,300 people in the room, lots of customers, lots of users. We had lots of investors here as well for our investor day, have a dinner tonight with a bunch of senior execs, so it's been a busy day. >> Future is bright for MongoBD. Dev, thanks for so much for coming on The Cube. And thanks for watching, this is Dave Vellante and we'll see you next time. (upbeat music)

>>Welcome back to the big apple, everybody. The Cube's continuous coverage here of MongoDB world 2022. We're at the new Javet center. It's it's quite nice. It was built during the pandemic. I believe on top of a former bus terminal. I'm told by our next guest Tony bear, who's the principal at DB insight of data and database expert, longtime analyst, Tony. Good to see you. Thanks for coming >>On. Thanks >>For having us. You face to face >>And welcome to New York. >>Yeah. Right. >>New York is open for business. >>So, yeah. And actually, you know, it's interesting. We've been doing a lot of these events lately and, and especially the ones in Vegas, it's the first time everybody's been out, you know, face to face, not so much here, you know, people have been out and about a lot of masks >>In, >>In New York city, but, but it's good. And, and this new venue is fantastic >>Much nicer than the old Javits. >>Yeah. And I would say maybe 3000 people here. >>Yeah. Probably, but I think like most conferences right now are kind of, they're going through like a slow ramp up. And like for instance, you know, sapphires had maybe about one third, their normal turnout. So I think that you're saying like one third to one half seems to be the norm right now are still figuring out how we're, how and where we're gonna get back together. Yeah. >>I think that's about right. And, and I, but I do think that that in most of the cases that we've seen, it's exceeded people's expectations at tenants, but anyway sure. Let's talk about Mongo, very interesting company. You know, we've been kind of been watching their progression from just sort of document database and all the features and functions they're adding, you just published a piece this morning in venture beat is time for Mongo to get into analytics. Yes. You know? Yes. One of your favorite topics. Well, can they expand analytics? They seem to be doing that. Let's dig into it. Well, >>They're taking, they've been taking slow. They've been taking baby steps and there's good reason for that because first thing is an operational database. The last thing you wanna do is slow it down with very complex analytics. On the other hand, there's huge value to be had if you would, if you could, you know, turn, let's say a smart, if you can turn, let's say an operational database or a transaction database into a smart transaction database. In other words, for instance, you know, let's say if you're, you're, you're doing, you know, an eCommerce site and a customer has made an order, that's basically been out of the norm. Whether it be like, you know, good or bad, it would be nice. Basically, if at that point you could then have a next best action, which is where analytics comes in. But it's a very lightweight form of analytics. It's not gonna, it's actually, I think probably the best metaphor for this is real time credit scoring. It's not that they're doing your scoring you in real time. It's that the model has been computed offline so that when you come on in real time, it can make a smart decision. >>Got it. Okay. So, and I think it was your article where I, I wrote down some examples. Sure. Operational, you know, use cases, patient data. There's certainly retail. We had Forbes on earlier, right? Obviously, so very wide range of, of use cases for operational will, will Mongo, essentially, in your view, is it positioned to replace traditional R D BMS? >>Well, okay. That's a long that's, that's much, it's >>Sort of a loaded question, but >>That's, that's a very loaded question. I think that for certain cases, I think it will replace R D BMS, but I still, I mean, where I, where I depart from Mongo is I do not believe that they're going to replace all R D D BMSs. I think, for instance, like when you're doing financial transactions, you know, the world has been used to table, you know, you know, columns and rows and tables. That's, it's a natural form for something that's very structured like that. On the other hand, when you take a look, let's say OT data, or you're taking a look at home listings that tends to more naturally represent itself as documents. And so there's a, so it's kind of like documents are the way that let's say you normally see the world. Relational is the way that you would structure the world. >>Okay. Well, I like that. So, but I mean, in the early days, obviously, and even to this day, it's like the target for Mongo has been Oracle. Yeah. Right, right. And so, and then, you know, you talk to a lot of Oracle customers as do I sure. And they are running the most mission, critical applications in the world, and it's like banking and financial and so many. And, and, and, you know, they've kind of carved out that space, but are we, should we be rethinking the definition of, of mission critical? Is that changing? >>Well, number one, I think what we've traditionally associated mission critical systems with is our financial transaction systems and to a less, and also let's say systems that schedule operations. But the fact is there are many forms of operations where for instance, let's say you're in a social network, do you need to have that very latest update? Or, you know, basically, can you go off, let's say like, you know, a server that's eventually consistent. In other words, the, do you absolutely have, you know, it's just like when you go on Twitter, do you naturally see all the latest tweets? It's not the system's not gonna crash for that reason. Whereas let's say if you're doing it, you know, let's say an ATM banking ATM system, that system better be current. So I think there's a delineation. The fact is, is that in a social network, arguably that operational system is mission critical, but it's mission critical in a different way from a, you know, from, let's say a banking system. >>So coming back to this idea of, of this hybrid, I think, you know, I think Gartner calls it H tab hybrid, transactional analytics >>Is changed by >>The minute, right. I mean, you mentioned that in, in your article, but basically it's bringing analytics to transactions bringing those, those roles together. Right. Right. And you're saying with Mongo, it's, it's lightweight now take, you use two other examples in your article, my SQL heat wave. Right. I think you had a Google example as well, DB, those are, you're saying much, much heavier analytics, is that correct? Or >>I we'll put it this way. I think they're because they're coming from a relational background. And because they also are coming from companies that already have, you know, analytic database or data warehouses, if you will, that their analytic, you know, capabilities are gonna be much more fully rounded than what Mongo has at this point. It's not a criticism of a Mongo MongoDB per >>Per, is that by design though? Or ne not necessarily. Is that a function of maturity? >>I think it's function of maturity. Oh, okay. I mean, look, to a certain extent, it's also a function of design in terms of that the document model is a little, it's not impossible to basically model it for analytics, but it takes more, you know, transformation to, to decide which, you know, let's say field in that document is gonna be a column. >>Now, the big thing about some of these other, these hybrid systems is, is eliminating the need for two databases, right? Eliminating the need for, you know, complex ETL. Is, is that a value proposition that will emerge with, with Mongo in your view? >>You know, I, I mean, put it this way. I think that if you take a look at how they've, how Mongo is basically has added more function to its operations, someone talking about analytics here, for instance, adding streaming, you know, adding, adding, search, adding time series, that's a matter of like where they've eliminated the need to do, you know, transformation ETL, but that's not for analytics per se for analytics. I think through, you know, I mean through replication, there's still gonna be some transformation in terms of turning, let's say data, that's, that's formed in a document into something that's represented by columns. There is a form of transformation, you know, so that said, and Mongo is already, you know, it has some NA you know, nascent capability there, but it's all, but this is still like at a rev 1.0 level, you know, I expect a lot more >>Of so refin you, how Amazon says in the fullness of time, all workloads will be in the cloud. And we could certainly debate that. What do we mean by cloud? So, but there's a sort of analog for Mongo that I'll ask you in the fullness of time, will Mongo be in a position to replace data warehouses or data lakes? No. Or, or, or, and we know the answer is no. So that's of course, yeah. But are these two worlds on a quasi collision course? I think they >>More on a convergence course or the collision course, because number one is I said, the first principle and operational database is the last thing you wanna do is slow it down. And to do all this complex modeling that let's say that you would do in a data bricks, or very complex analytics that you would do in a snowflake that is going to get, you know, you know, no matter how much you partition the load, you know, in Atlas, and yes, you can have separate nodes. The fact is you really do not wanna burden the operational database with that. And that's not what it's meant for, but what it is meant for is, you know, can I make a smart decision on the spot? In other words, kinda like close the loop on that. And so therefore there's a, a form of lightweight analytic that you can perform in there. And actually that's also the same principle, you know, on which let's say for instance, you know, my SQL heat wave and Allo DBR based on, they're not, they're predicated on, they're not meant to replace, you know, whether it be exit data or big query, the idea there is to do more of the lightweight stuff, you know, and keep the database, you know, keep the operations, you know, >>Operating. And, but from a practitioner's standpoint, I, I, I can and should isolate you're saying that node, right. That's what they'll do. Sure. How does that affect cuz my understanding is that that the Mon Mongo specifically, but I think document databases generally will have a primary node. Right? And then you can set up secondary nodes, which then you have to think about availability, but, but would that analytic node be sort of fenced off? Is that part of the >>Well, that's actually what they're, they've already, I mean, they already laid the groundwork for it last year, by saying that you can set up separate nodes and dedicate them to analytics and what they've >>As, as a primary, >>Right? Yes, yes. For analytics and what they've added, what they're a, what they are adding this year is the fact to say like that separate node does not have to be the same instance class, you know, as, as, as, as the, >>What, what does that mean? Explain >>That in other words, it's a, you know, you could have BA you know, for instance, you could have a node for operations, that's basically very eye ops intensive, whereas you could have a node let's say for analytics that might be more compute intensive or, or more he, or, or more heavily, you know, configured with, with memory per se. And so the idea here is you can tailor in a node to the workload. So that's, you know what they're saying with, you know, and I forget what they're calling it, but the idea that you can have a different type, you can specify a different type of node, a different type of instance for the analytic node, I think is, you know, is a major step forward >>And that, and that that's enabled by the cloud and architecture. >>Of course. Yes. I mean, we're separating, compute from data is, is, is the starter. And so yeah. Then at that point you can then start to, you know, you know, to go less vanilla. I think, you know, the re you know, the, you know, the, I guess the fruition of this is going to be when they say, okay, you can run your, let's say your operational nodes, you know, dedicated, but we'll let you run your analytic nodes serverless. Can't do it yet, but I've gotta believe that's on the roadmap. >>Yeah. So seq brings a lot of overhead. So you get MQL, but now square this circle for me, cuz now you got Mago talking sequel. >>They had to start doing that some time. I mean, and I it's been a court take I've had from them from the, from the get go, which I said, I understand that you're looking at this as an alternative to SQL and that's perfectly valid, but don't deny the validity of SQL or the reason why we, you know, we need it. The fact is that you have, okay, the number, you know, according to Ty index, JavaScript is the seventh, most popular language. Most SQL follows closely behind at the ninth, most popular language you don't want to cl. And the fact is those people exist in the enterprise and they're, and they're disproportionately concentrated in analytics. I mean, you know, it's getting a little less, so now we're seeing like, you know, basically, you know, Python, the programmatic, but still, you know, a lot of sequel expertise there. It does not make, it makes no sense for Mongo to, to, to ignore or to overlook that audience. I think now they're, you know, you know, they're taking baby steps to start, you know, reaching out to them. >>It's interesting. You see it going both ways. See Oracle announces a Mongo, DB, Mongo. I mean, it's just convergence. You called it not, I love collisions, you know, >>I know it's like, because you thrive on drama and I thrive on can't. We all love each other, but you know, act. But the thing is actually, I've been, I wrote about this. I forget when I think it was like 2014 or 2016. It's when we, I was noticed I was noting basically the, you know, the rise of all these specialized databases and probably Amazon, you know, AWS is probably the best exemplar of that. I've got 15 or 16 or however, number of databases and they're all dedicated purpose. Right. But I also was, you know, basically saw that inevitably there was gonna be some overlap. It's not that all databases were gonna become one and the same we're gonna be, we're gonna become back into like the, you know, into a pan G continent or something like that. But that you're gonna have a relational database that can do JSON and, and a, and a document database that can do relational. I mean, you know, it's, to me, that's a no brainer. >>So I asked Andy Ja one time, I'd love to get your take on this, about those, you know, multiple data stores at the time. They probably had a thousand. I think they're probably up to 15 now, right? Different APIs, different S et cetera. And his response. I said, why don't you make it easier for, for customers and maybe build an abstraction or converge these? And he said, well, it's by design. What if you buy this? And, and what your thoughts are, cuz I, you know, he's a pretty straight shooter. Yeah. It's by design because it allows us as the market moves, we can move with it. And if we, if we give developers access to those low level primitives and APIs, then they can move with, with at market speed. Right. And so that again, by design, now we heard certainly Mongo poo pooing that today they didn't mention, they didn't call out Amazon. Yeah. Oracle has no compunction about specifically calling out Amazon. They do it all the time. What do you make of that? Can't Amazon have its cake and eat it too. In other words, extend some of the functionality of those specific databases without going to the Swiss army. >>I I'll put it this way. You, you kind of tapped in you're, you're sort of like, you know, killing me softly with your song there, which is that, you know, I was actually kind of went on a rant about this, actually know in, you know, come, you know, you know, my year ahead sort of out predictions. And I said, look, cloud folks, it's great that you're making individual SAS, you know, products easy to use. But now that I have to mix and match SAS products, you know, the burden of integration is on my shoulders. Start making my life easier. I think a good, you know, a good example of this would be, you know, for instance, you could take something like, you know, let's say like a Google big query. There's no reason why I can't have a piece of that that might, you know, might be paired, say, you know, say with span or something like that. >>The idea being is that if we're all working off a common, you know, common storage, we, you know, it's in cloud native, we can separate the computer engines. It means that we can use the right engine for the right part of the task. And the thing is that maybe, you know, myself as a consumer, I should not have to be choosing between big query and span. But the thing is, I should be able to say, look, I want to, you know, globally distribute database, but I also wanna do some analytics and therefore behind the scenes, you know, new microservices, it could connect the two wouldn't >>Microsoft synapse be an example of doing that. >>It should be an example. I wish I, I would love to hear more from Microsoft about this. They've been radio silent for about the past two or three years in data. You hardly hear about it, but synapse is actually those actually one of the ideas I had in mind now keep in mind that with synapse, you're not talking about, let's say, you know, I mean, it's, it's obviously a sequel data warehouse. It's not pure spark. It's basically their, it was their curated version of spark, but that's fine. But again, I would love to hear Microsoft talk more about that. They've been very quiet. >>Yeah. You, you, the intent is there to >>Simplify >>It exactly. And create an abstraction. Exactly. Yeah. They have been quiet about it. Yeah. Yeah. You would expect that, that maybe they're still trying to figure it out. So what's your prognosis from Mongo? I mean, since this company IP, you know, usually I, I tell and I tell everybody this, especially my kids, like don't buy a stock at IPO. You'll always get a better chance at a cheaper price to buy it. Yeah. And even though that was true with Mongo, you didn't have a big window. No. Like you did, for instance, with, with Facebook, certainly that's been the case with snowflake and sure. Alibaba, I mean, I name a zillion style was almost universal. Yeah. But, but since that, that, that first, you know, few months, period, this, this company has been on a roll. Right. And it, it obviously has been some volatility, but the execution has been outstanding. >>No question about that. I mean, the thing is, look what I, what I, and I'm just gonna talk on the product side on the sales side. Yeah. But on the product side, from the get go, they made a product that was easy for developers. Whereas let's say someone's giving an example, for instance, Cosmo CB, where to do certain operations. They had to go through multiple services in, you know, including Azure portal with Atlas, it's all within Atlas. So they've really, it's been kinda like design thinking from the start initially with, with the core Mongo DB, you know, you, the on premise, both this predates Atlas, I mean, part of it was that they were coming with a language that developers knew was just Javas script. The construct that they knew, which was JS on. So they started with that home core advantage, but they weren't the only ones doing that. But they did it with tooling that was very intuitive to developers that met developers, where they lived and what I give them, you know, then additional credit for is that when they went to the cloud and it wasn't an immediate thing, Atlas was not an overnight success, but they employed that same design thinking to Atlas, they made Atlas a good cloud experience. They didn't just do a lift and shift the cloud. And so that's why today basically like five or six years later, Atlas's most of their business. >>Yeah. It's what, 60% of the business now. Yeah. And then Dave, on the, on the earning scholar, maybe it wasn't Dave and somebody else in response to question said, yeah, ultimately this is the future will be be 90% of the business. I'm not gonna predict when. So my, my question is, okay, so let's call that the midterm midterm ATLA is gonna be 90% of the business with some exceptions that people just won't move to the cloud. What's next is the edge. A new opportunity is Mongo architecturally suited for the, I mean, it's certainly suited for the right, the home Depot store. Sure. You know, at the edge. Yeah. If you, if you consider that edge, which I guess it is form of edge, but how about the far edge EVs cell towers, you know, far side, real time, AI inferencing, what's the requirement there, can Mongo fit there? Any thoughts >>On that? I think the AI and the inferencing stuff is interesting. It's something which really Mongo has not tackled yet. I think we take the same principle, which is the lightweight stuff. In other words, you'll say, do let's say a classification or a prediction or some sort of prescriptive action in other words, where you're not doing some convolution, neural networking and trying to do like, you know, text, text to voice or, or, or vice versa. Well, you're not trying to do all that really fancy stuff. I think that's, you know, if you're keeping it SIM you know, kinda like the kiss principle, I think that's very much within Mongo's future. I think with the realm they have, they basically have the infrastructure to go out to the edge. I think with the fact that they've embraced GraphQL has also made them a lot more extensible. So I think they certainly do have, you know, I, I do see the edge as being, you know, you know, in, in, you know, in their, in their pathway. I do see basically lightweight analytics and lightweight, let's say machine learning definitely in their >>Future. And, but, and they would, would you agree that they're in a better position to tap that opportunity than say a snowflake or an Oracle now maybe M and a can change that. R D can maybe change that, but fundamentally from an architectural standpoint yeah. Are they in a better position? >>Good question. I think that that Mongo snowflake by virtual fact, I mean that they've been all, you know, all cloud start off with, I think makes it more difficult, not impossible to move out to the edge, but it means that, and I, and know, and I, and I said, they're really starting to making some tentative moves in that direction. I'm looking forward to next week to, you know, seeing what, you know, hearing what we're gonna, what they're gonna be saying about that. But I do think, right. You know, you know, to answer your question directly, I'd say like right now, I'd say Mongo probably has a, you know, has a head start there. >>I'm losing track of time. I could go forever with you. Tony bear DB insight with tons of insights. Thanks so much for coming back with. >>It's only one insight insight, Dave. Good to see you again. All >>Right. Good to see you. Thank you. Okay. Keep it right there. Right back at the Java center, Mongo DB world 2022, you're watching the cube.

>>Yeah, yeah, yeah. We're back at the center of the coverage of the world 20 twenty-two, the first live event in three years. Pretty amazing. And I'm really excited to have Tony Coleman. Here is the c e o of those who changing the finance and banking industry. And this is the global head of industry solutions. That would be welcome. Back to the cube. Welcome. First time. Um, so thanks for coming on. Thank you. >>Thanks for having us, >>Tony. Tell us about what are you guys up to? Disrupting the finance world. >>So tomorrow is everyone's banking platform. So we are a software company. We have over 3000 financial institutions around the world. Marketing tell me that that works out is over 1.2 billion people rely on terminal software for their banking and financial needs. 41 of the top 50 banks in the world run software and we are very proud to be powering all of those entities on their innovation journeys and bringing you know, that digital transformation that we've seen so much all over the past few years and enabling a lot of the world's unbanked through digital banking become, you know, members of the >>community. So basically you're bringing the software platform to enable that to somebody you don't have to build it themselves because they never get there. Absolutely. And and so that's why I don't know if you consider that disruptive. I guess I do to the industry to a certain extent. But when you think of disruption in the business, you think of Blockchain and crypto, and 50 is that is completely separate world and you guys participate in that as well. Well, I >>would say it's related right? I mean, I was doing a podcast recently and they had this idea of, um, buzzword jail where you could choose words to go into jail and I said 50 not because I think they're intrinsically bad, but I think just at the moment they are a rife for scam area. I think it's one of those one of these technologies and investment area that people don't understand it, and there's a lot of a lot of mistakes that can be made in that, >>Yeah, >>I mean, it's a fascinating piece that it could be truly transformative if we get it right, but it's very emerging, so we'll see so don't play a huge part in the Blockchain industry directly. We work with partners in that space, but in terms of digital assets and that sort of thing. Yeah, absolutely. >>So, Boris, you have industry solutions in your title. What does that entail? So >>basically, I'm responsible for all the verticals, and that includes great partners like Tony. And we're doing a lot of verticals by now. When you listen. Today in all these various talks, we have so much stuff ranging from banking, go retail, healthcare, insurance, you name it, we have it by now. And that's obviously the clients moving from the edge solution. Like touching a little toe in the water, but longer to going all in building biggest solutions you saw on stage the lady from this morning. These are not second Great. Yeah, we do something small now. We're part of the transformation journey. And this is where Tony and I can regularly together how we transform things and how we built a new way of banking is done with Michael services and technology surrounding it. Yeah, >>but what about performance in this world? Can you tell me about that? >>Yeah. This is an interesting thing because people always challenging what is performance and document databases. And Tony challenged us actually, six weeks before his own show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story because if I get too excited, I follow. >>Yeah, sure, that performance and efficiency topics close close to my heart. I have been for for years. And so, yeah, we every two or three years, we run a high water. We've got a high water benchmark, and this year we sort of double down literally double down on everything we did previously. So this was 200 million accounts, 100 million customers, and we were thrashing through 102,800 seventy-five transactions a second, which is a phenomenal number. And, uh, >>can I do that on the Blockchain? >>Wow. Yeah, exactly. Right. So this is you know, I get asked why we do such high numbers and the reason is very straightforward. If somebody wants 10,000 transactions a second, we're seeing banks now that need that sort of thing. If I can give them a benchmark report, this is 100,000. I don't need to keep doing benchmarks. 10. >>Yeah. Tell me more about the Anytime you get into benchmarks, you want to understand the configuration. The workload. Tell me more about that. So we have >>a pretty well path of a standard transaction mix. We call it a retail transaction mix. And so it's the tries to the workload. Is that because it's a simulation right around what you would do in your daily basis? So you're going to make payments you're going to check? Your balance is you're going to see what he's moved on your account. So we do all of that and we run it through a proper production, good environment. And this is really important. This is something we do in the lab you couldn't go live on. This is all all of the horrible, non functional requirements around high availability, >>security, security passes, private wings, all these things. And one thing is, they're doing this for a long time. So this is not like let's define something new for the world. Now, this is something Tony's doing for literally 10, 15 years now, right? >>It was only 15 years, but this >>is your benchmark >>top >>developed Okay, >>so we run it through and, um yeah, some fantastic numbers. And not just on the share sort of top-level numbers 100,000 transactions. A second response time out of it was fantastic. One-millisecond, which is just brilliant. So it means you get these really efficient numbers what that helped us do with, you know, some of the other partners that are involved in the benchmark as well. It meant that our throughput court, which is a really good measure of efficiency, is up to four times better than we ran it three years ago. So in terms of a sustainability piece, which is so important that that's really a huge improvement, that's down to application changes, architect changes as well as using appropriate technology in the right place. >>How important? With things like the number, of course, the memory size is the block sizes. All that stuff. >>We are very tiny. So this is the part. When I talk to people, we have what we call a system in the back of people. Look at me. Um, how many transactions on that one? So, to be fair, three-quarters, we're going to be one quarter or something else because we're still putting some components of and start procedures for disclosure. But when I think Seventy-five 1000 transactions on a single single 80 system, which is thirty-two cause you're saying correctly, something like that. This is a tiny machine in the world of banking. So before this was the main friends and now it's wonderful instance on a W s. And this is really amazing. Costed and environmental footprint is so, so important >>and there's a heavy right heavy environment. >>So the the way we the way we architect the solution is it follows something called a command query responsibility, segregated segregation. So what we do, we do all the commands inappropriate database for that piece, and that was running at about Twenty-five 1000 transactions a second and then we're streaming the data out of that directly into So actually I was doing more than the Seventy-five 1000 queries. A second, which is the part of it was also investing Twenty-five 1000 transactions the second at the same time >>and okay, and the workload had a high locality medium locality. It was just give us a picture of what that's like. Sorry. So, >>yeah, >>we don't have that. Yeah, >>so explain that That's not That's not the mindset for a document. Exactly. >>Exactly. In the document database, you don't have the hot spotting the one single field off the table, which is suddenly hot spotting. And now you have literally and recovery comes up and we say, What goes, goes together, get together belongs together, comes out together. So the number of, for example, it's much, much smaller and the document system, then historically, relationship. >>So it is not a good good indicator, necessarily >>anymore. That's what this is so much reduced. The number of access patterns are smaller, and I mean it is highly optimized, for example, internally as well. The internal structures, so that was very close to a >>traditional benchmark, would have a cash in front of a high cash rate. So 100 and 99% right, That's a high locality reference. But that's that's irrelevant. >>It's gone. There's no cashing in the middle anymore. It goes straight against the database. All these things are out, and that's what makes it so exciting and all the things in a real environment. I think we really need to stress it. It's not a test that at home. It's a real life environment out into the wild with the benchmark driving and driving. >>How did your customers respond? You did this for your recent event? >>Yeah, we did it for our use. A conference, our community for, um, which was a few weeks ago in London. Um, and the You know, the reaction was Certainly it was a great reception, of course, but the main thing that people are fascinated about, how much more efficient the whole platform it's explaining. So you know when we can run and it's a great number that we've got the team pulled out, which is so having doubled throughput on the platform from what we did three years ago, we're actually using 20% less infrastructure to give double the performance. Uh, macro-level, that's a phenomenal achievement. And that means that these changes that we make everything that we're doing benefits all of our customers. So all of the banks, when they take the latest release, is they get these benefits. Everything is that much more efficient. So everybody benefits from every investment, >>and this was running in the cloud. Is that correct? You're running out of this. >>So this was list, Um, 80 on a W s with a W s cases and processes. And so it was a really reality driven environment, >>pure pure cloud-native or using mana services on a W s. And then at least for the peace. It's >>awesome. I mean, uh, So now how convenient for the timing from, uh, the world. How are you socializing with your community? >>We're having this afternoon session as well, where we talk a little bit more detail about that, and he has a session as well tomorrow. So we see a lot of good feedback as well when we bring it up with clients. Obviously some clients get very specific because this reduction footprint is so huge when you think a client has 89 environments from early development systems to production to emergency standby, maybe a different cloud. All these things what day talks about the different Atlas features multi cloud environmentally. All this stuff comes to play. And this is why I'm so excited to work with them. We should bring up as well the other things which are available to ready already with your front and solutions with Infinity services because that's the other part of the modernization, the Michael Services, which Tony so politely not mentioning. So there's a lot of cool technology into that one, which fits to how it works in micros services. Happy I first all these what they called factors. Micro service a p. I cloud-native headless. I think that was the right order now. So all these things are reflected as well. But with their leadership chief now, I think a lot of companies have to play Catch-up now to what Tony and his team are delivering on the bank. This >>gets the modernization. We really haven't explicitly talks about that. Everything you've just said talks to modernization. So you typically in financial services find a lot of relation. Database twenty-year-old, hardened, etcetera, high availability. Give them credit for that. But a lot of times you'll see them just shift that into the cloud. You guys chose not to do that. What was the modernization journey look like? >>So it's a bit of, um yeah, a firm believer in pragmatism and using. I think you touched on earlier the appropriate technology. So >>horses for courses >>exactly right out of my mouth. And I was talking to one of the uh, the investor analysts earlier. And you know, the exact same question comes up, right? So if you've got a relation database or you've got a big legacy system and you're not gonna mainframe or whatever it is and you wanna pull that over when you it's not just a case of moving the data model from one paradigm to another. You need to look at it holistically, and you need to be ambitious. I think the industry has got, you know, quite nervous about some of these transformation projects, but in some ways it might be counter intuitive. I think being ambitious and being in bold is a better way. Better way through, you know, take take of you, look at it holistically. Layout of plan. It is hard. It is hard to do these sorts of transformations, but that's what makes it the challenge. That's what makes it fun. Take take those bold steps. Look at it holistically. Look at the end state and then work out a practical way. You can deliver value to the business and your customers as you deliver on the road. So >>did you migrate from a traditional R D B. M s to go. >>So So, Yeah, this is a conversation. So, uh, in the late nineties, the kind of the phrase document model hasn't really been coined yet. And for some of our work at the time, we refer to as a hierarchical model. Um, And at that point in time, really, if you wanted to sell to a bank, you needed to be running Oracle. So we took this data model and we got it running an article and then other relational databases as well, but actually under the colors there it is, sort of as well. So there is a project that we're looking at to say Well, okay, taking that model, which is in a relational database. And of course, you build over time, you do rely on some of the features of relations databases moving that over to something like, isn't it? You know, it's not quite as simple as just changing the data model. Um, so there's a few bits and pieces that we need to work through, but there is a concept that we are running, which is looking really promising and spurred on by the amazing results from the benchmark. That could be something That's really >>yeah, I think you know, 20 years ago you probably wouldn't even thought about it. It's just too risky. But today, with the modern tools and the cloud and you're talking about micro services and containers, it becomes potentially more feasible. >>But the other side of it is, you know, it's only relatively recently the Mongo who's had transaction support across multiple document multi collection transactions and in banking. As we all know, you know, it's highly regulated. That is, all of your worst possible non functional requirement. Security transaction reality. Thomas City You know, the whole the whole shebang. Your worst possible nightmare is Monday morning for >>us. So and I think one part which is exciting about this Tony is a very good practical example about this large scale modernization and cutting out by cutting off that layer and going back to the hierarchical internal structures. We're simply find a lot of the backing components of our because obviously translation which was done before, it's not need it anymore. And that is as well for me, an exciting example to see how long it takes what it is. So Tony space in my life experiments so to speak >>well, you're right because it used to be those migrations. Where how many line of code? How long do I have to freeze it? And that a lot of times lead people to say, Well, forget it, because the business is going to shut down. >>But now we do that. We do that. So I'm working, obviously, besides the work with a lot of financial clients, and but now it's my job is normally shift and left a pain in the game because the result of the work is when they move everything to the cloud and it was bad before. It will not be better in the cloud only because it's in somebody else's data center. So these modernization and innovation factor is absolutely critical. And it's only said that people get it by now. This shift and left over it is how can I innovate? How can accelerate innovation, and that leads very quickly to the document model discussion. >>Yeah, I think the world practitioners will tell you, if you really want to affect the operational model, have a meaningful impact on your business. You have to really modernized. You can't just lift shift that they're absolutely. You know, what's the difference between hundreds of millions or billions in some cases, versus, you know, some nice little hits here or there. >>So we see as well a lot of clients asking for solutions like the terminal solutions. And like others where there is not anymore discussion about how to move to the The question is how fast how can accelerate. We see the services request the first one. It's amazing. After the event, what we had in London, 100 clients calling us. So it's not our sales people calling upon the clients, the clients coming in. I saw it. How do we get started? And that is for me, from the vendor perspective, so to speak. Amazing moment >>yourself. You go, guys, we're gonna go. Thanks so much for that. You have to have you back and see how that goes. That. Yeah, that's a big story of if you're a great All right, keep it right there. Everybody will be right back. This is David for the Cube. You're watching our live coverage of mongo D B World 20 twenty-two from New York City. >>Yeah, >>Yeah, yeah, yeah, yeah

>>Welcome back to NYC the Cube's coverage of Mongo DB 2022, a few thousand people here at least bigger than many people, perhaps expected, and a lot of buzz going on and we're gonna talk devs. I'm really excited to welcome back. Robbie Bellson who's the developer relations lead at Verizon and Ian Massingham. Who's the vice president of developer relations at Mongo DB Jens. Good to see you. Great >>To be here. >>Thanks having you. So Robbie, we just met a few weeks ago at the, the red hat summit in Boston and was blown away by what Verizon is doing in, in developer land. And of course, Ian, you know, Mongo it's rayon Detra is, is developers start there? Why is Mongo so developer friendly from your perspective? >>Well, it's been the ethos of MongoDB since day one. You know, back when we launched the first version of MongoDB back in 2009, we've always been about making developers lives easier. And then in 2016, we announced and released MongoDB Atlas, which is our cloud managed service for MongoDB, you know, starting with a small number of regions built on top of AWS and about 2,500 adoption events per week for MongoDB Atlas. After the first year today, MongoDB Atlas provides a managed service for MongoDB developers around the world. We're present in almost a hundred cloud regions across S DCP and Azure. And that adoption number is now running at about 25,000 developers a week. So, you know, the proof are in proof is really in the metrics. MongoDB is an incredibly popular platform for developers that wanna build data-centric applications. You just can't argue with the metrics really, >>You know, Ravi, sometimes there's an analyst who come up with these theories and one of the theories I've been spouting for a long time is that developers are gonna win the edge. And now to, to see you at Verizon building out this developer community was really exciting to me. So explain how you got this started with this journey. >>Absolutely. As you think about Verizon 5g edge or mobile edge computing portfolio, we knew from the start that developers would play a central role and not only consuming the service, but shaping the roadmap for what it means to build a 5g future. And so we started this journey back in late 20, 19 and fast forward to about a year ago with Mongo, we realized, well, wait a minute, you look at the core service offerings available at the edge. We didn't know really what to do with data. We wanted to figure it out. We wanted the vote of confidence from developers. So there I was in an apartment in Colorado racing, your open source Mongo against that in the region edge versus region, what would you see? And we saw tremendous performance improvements. It was so much faster. It's more than 40% faster for thousands and thousands of rights. And we said, well, wait a minute. There's something here. So what often starts is an organic developer, led intuition or hypothesis can really expand to a much broader go to market motion that really brings in the enterprise. And that's been our strategy from day one. Well, >>It's interesting. You talk about the performance. I, I just got off of a session talking about benchmarks in the financial services industry, you know, amazing numbers. And that's one of the hallmarks of, of Mongo is it can play in a lot of different places. So you guys both have developer relations in your title. Is that how you met some formal developer relations? >>We were a >>Program. >>Yeah, I would say that Verizon is one of the few customers that we also collaborate with on a developer relations effort. You know, it's in our mutual best interest to try to drive MongoDB consumption amongst developers using Verizon's 5g edge network and their platform. So of course we work together to help, to increase awareness of MongoDB amongst mobile developers that want to use that kind of technology. >>But so what's your story on this? >>I mean, as I, as I mentioned, everything starts with an organic developer discovery. It all started. I just cold messaged a developer advocate on Twitter and here we are at MongoDB world. It's amazing how things turn out. But one of the things that's really resonated with me as I was speaking with one of, one of your leads within your organization, they were mentioning that as Mongo DVIA developed over the years, the mantra really became, we wanna make software development easy. Yep. And that really stuck with me because from a network perspective, we wanna make networking easy. Developers are not gonna care about the internals of 5g network. In fact, they want us to abstract away those complexities so that they can focus on building their apps. So what better co-innovation opportunity than taking MongoDB, making software easy, and we make the network easy. >>So how do you think about the edge? How does you know variety? I mean, to me, you know, there's a lot of edge use cases, you know, think about the home Depot or lows. Okay, great. I can put like a little mini data center in there. That's cool. That's that's edge. Like, but when I think of Verizon, I mean, you got cell towers, you've got the far edge. How do you think about edge Robbie? >>Well, the edge is a, I believe a very ambiguous term by design. The edge is the device, the mobile device, an IOT device, right? It could be the radio towers that you mentioned. It could be in the Metro edge. The CDN, no one edge is better than the other. They're all just serving different use cases. So when we talk about the edge, we're focused on the mobile edge, which we believe is most conducive to B2B applications, a fleet of IOT devices that you can control a manufacturing plant, a fleet of ground and aerial robotics. And in doing so you can create a powerful compute mesh where you could have a private network and private mobile edge computing by way of say an AWS outpost and then public mobile edge computing by way of AWS wavelength. And why keep them separate. You could have a single compute mesh even with MongoDB. And this is something that we've been exploring. You can extend Atlas, take a cluster, leave it in the region and then use realm the mobile portfolio and spread it all across the edge. So you're creating that unified compute and data mesh together. >>So you're describing what we've been expecting is a new architecture emerging, and that's gonna probably bring new economics of new use cases, right? Where are we today in that first of all, is that a reasonable premise that this is a sort of a new architecture that's being built out and where are we in that build out? How, how do you think about the, the future of >>That? Absolutely. It's definitely early days. I think we're still trying to figure it out, but the architecture is definitely changing the idea to rip out a mobile device that was initially built and envisioned for the device and only for the device and say, well, wait a minute. Why can't it live at the edge? And ultimately become multi-tenant if that's the data volume that may be produced to each of those edge zones with hypothesis that was validated by developers that we continue to build out, but we recognize that we can't, we can't get that static. We gotta keep evolving. So one of our newest ideas as we think about, well, wait a minute, how can Mongo play in the 5g future? We started to get really clever with our 5g network APIs. And I, I think we talked about this briefly last time, 5g, programmability and network APIs have been talked about for a while, but developers haven't had a chance to really use them and our edge discovery service answering the question in this case of which database is the closest database, doesn't have to be invoked by the device anymore. You can take a thin client model and invoke it from the cloud using Atlas functions. So we're constantly permuting across the entire portfolio edge or otherwise for what it means to build at the edge. We've seen such tremendous results. >>So how does Mongo think about the edge and, and, and playing, you know, we've been wondering, okay, which database is actually gonna be positioned best for the edge? >>Well, I think if you've got an ultra low latency access network using data technology, that adds latency is probably not a great idea. So MongoDB since the very formative years of the company and product has been built with performance and scalability in mind, including things like in memory storage for the storage engine that we run as well. So really trying to match the performance characteristics of the data infrastructure with the evolution in the mobile network, I think is really fundamentally important. And that first principles build of MongoDB with performance and scalability in mind is actually really important here. >>So was that a lighter weight instance of, of Mongo or not >>Necessarily? No, not necessarily. No, no, not necessarily. We do have edge cashing with realm, the mobile databases Robbie's already mentioned, but the core database is designed from day one with those performance and scalability characteristics in mind, >>I've been playing around with this. This is kind of a, I get a lot of heat for this term, but super cloud. So super cloud, you might have data on Preem. You might have data in various clouds. You're gonna have data out at the edge. And, and you've got an abstraction that allows a developer to, to, to tap services without necessarily if, if he or she wants to go deep into the S great, but then there's a higher level of services that they can actually build for their customers. So is that a technical reality from a developer standpoint, in your view, >>We support that with the Mongo DB multi-cloud deployment model. So you can place Mongo DB, Atlas nodes in any one of the three hyperscalers that we mentioned, AWS, GCP or Azure, and you can distribute your data across nodes within a cluster that is spread across different cloud providers. So that kinds of an kind of answers the question about how you do data placement inside the MongoDB clustered environment that you run across the different providers. And then for the abstraction layer. When you say that I hear, you know, drivers ODMs the other intermediary software components that we provide to make developers more productive in manipulating data in MongoDB. This is one of the most interesting things about the technology. We're not forcing developers to learn a different dialect or language in order to interact with MongoDB. We meet them where they are by providing idiomatic interfaces to MongoDB in JavaScript in C sharp, in Python, in rust, in that in fact in 12 different pro programming languages that we support as a first party plus additional community contributed programming languages that the community have created drivers for ODMs for. So there's really that model that you've described in hypothesis exist in reality, using >>Those different Compli. It's not just a series of siloed instances in, >>In different it's the, it's the fabric essentially. Yeah. >>What, what does the Verizon developer look like? Where does that individual come from? We talked about this a little bit a few weeks ago, but I wonder if you could describe it. >>Absolutely. My view is that the Verizon or just mobile edge ecosystem in general for developers are present at this very conference. They're everywhere. They're building apps. And as Ian mentioned, those idiomatic interfaces, we need to take our network APIs, take the infrastructure that's being exposed and make sure that it's leveraging languages, frameworks, automation, tools, the likes of Terraform and beyond. We wanna meet developers where they are and build tools that are easy for them to use. And so you had talked about the super cloud. I often call it the cloud continuum. So we, we took it P abstraction by abstraction. We started with, will it work in one edge? Will it work in multiple edges, public and private? Will it work in all of the edges for a given region, public or private, will it work in multiple regions? Could it work in multi clouds? We've taken it piece by piece by piece and in doing so abstracting way, the complexity of the network, meaning developers, where they are providing those idiomatic interfaces to interact with our API. So think the edge discovery, but not in a silo within Atlas functions. So the way that we're able to converge portfolios, using tools that dev developers already use know and love just makes it that much easier. Do, >>Do you feel like I like the cloud continuum cause that's really what it is. The super cloud does the security model, how does the security model evolve with that? >>At least in the context of the mobile edge, the attack surface is a lot smaller because it's only for mobile traffic not to say that there couldn't be various configuration and human error that could be entertained by a given application experience, but it is a much more secure and also reliable environment from a failure domain perspective, there's more edge zones. So it's less conducive to a regionwide failure because there's so many more availability zones. And that goes hand in hand with security. Mm. >>Thoughts on security from your perspective, I mean, you added, you've made some announcements this week, the, the, the encryption component that you guys announced. >>Yeah. We, we issued a press release this morning about a capability called queryable encryption, which actually as we record this Mark Porter, our CTO is talking about in his keynote, and this is really the next generation of security for data stored within databases. So the trade off within field level encryption within databases has always been very hard, very, very rigid. Either you have keys stored within your database, which means that your memory, so your data is decrypted while it's resident in memory on your database engine. This allow, of course, allows you to perform query operations on that data. Or you have keys that are managed and stored in the client, which means the data is permanently OBS from the engine. And therefore you can't offload query capabilities to your data platform. You've gotta do everything in the client. So if you want 10 records, but you've got a million encrypted records, you have to pull a million encrypted records to the client, decrypt them all and see performance hit in there. Big performance hit what we've got with queryable encryption, which we announced today is the ability to keep data encrypted in memory in the engine, in the database, in the data platform, issue queries from the client, but use a technology called structural encryption to allow the database engine, to make decisions, operate queries, and find data without ever being able to see it without it ever being decrypted in the memory of the engine. So it's groundbreaking technology based on research in the field of structured encryption with a first commercial database provided to bring this to market. >>So how does the mobile edge developer think about that? I mean, you hear a lot about shifting left and not bolting on security. I mean, is this, is this an example of that? >>It certainly could be, but I think the mobile edge developer still stuck with how does this stuff even work? And I think we need to, we need to be mindful of that as we build out learning journeys. So one of my favorite moments with Mongo was an immersion day. We had hosted earlier last year where we, our, from an enterprise perspective, we're focused on BW BS, but there's nothing stopping us. You're building a B2C app based on the theme of the winner Olympics. At the time, you could take a picture of Sean White or of Nathan Chen and see that it was in fact that athlete and then overlaid on that web app was the number of medals they accrued with the little trumpeteer congratulating you for selecting that athlete. So I think it's important to build trust and drive education with developers with a more simple experience and then rapidly evolve overlaying the features that Ian just mentioned over time. >>I think one of the keys with cryptography is back to the familiar messaging for the cloud offloading heavy lifting. You actually need to make it difficult to impossible for developers to get this wrong, and you wanna make it as easy as possible for developers to deal with cryptography. And that of course is what we're trying to do with our driver technology combined with structure encryption, with query encryption. >>But Robbie, your point is lots of opportunity for education. I mean, I have to say the developers that I work with, it's, I'm, I'm in awe of how they solve problems and I, and the way they solve problems, if they don't know the answer, they figure out how to go get it. So how, how are your two communities and other communities, you know, how are they coming together to, to solve such problems and share whether it's best practices or how do I do this? >>Well, I'm not gonna lie in person. Events are a bunch of fun. And one of the easiest domain knowledge exchange opportunities, when you're all in person, you can ideate, you can whiteboard, you can brainstorm. And often those conversations are what leads to that infrastructure module that an immersion day features. And it's just amazing what in person events can do, but community groups of interest, whether it's a Twitch stream, whether it's a particular code sample, we rely heavily on digital means today to upscale the developer community, but also build on by, by means of a simple port request, introduce new features that maybe you weren't even thinking of before. >>Yeah. You know, that's a really important point because when you meet people face to face, you build a connection. And so if you ask a question, you're more likely perhaps to get an answer, or if one doesn't exist in a, in a search, you know, you, oh, Hey, we met at the, at the conference and let's collaborate on this guys. Congratulations on, on this brave new world. You're in a really interesting spot. You know, developers, developers, developers, as Steve bomber says screamed. And I was glad to see Dave was not screaming and jumping up and down on the stage like that, but, but the message still resonates. So thank you, definitely appreciate. All right, keep it right there. This is Dave ante for the cubes coverage of Mago DB world 2022 from New York city. We'll be right back.

(upbeat music) >> Welcome back to the Javits in the big apple, New York City. This is theCUBE's coverage of MongoDB World 2022. We're here for a full day of coverage. We're talking to customers, partners, executives and analysts as well. Peder Ulander is here. He's the Chief Marketing Officer of MongoDB and he's joined by Radhika Krishnan, who's the Chief Product Officer at Hitachi Ventara. Folks, welcome back to theCUBE. Great to see you both again. >> Good to see you. >> Thank you David, it's good to be back again. >> Peder, first time since 2019, we've been doing a lot of these conferences and many of them, it's the first time people have been out in a physical event in three years. Amazing. >> I mean, after three years to come back here in our hometown of New York and get together with a few thousand of our favorite customers, partners, analysts, and such, to have real good discussions around where we're taking the world with regards to our developer data platform. It's been great. >> I think a big part of that story of course, is ecosystem and partnerships and Radhika, I remember I was at an event when Hitachi announced its strategy and it's name change, and really tried to understand why and the what's behind that. And of course, Hitachi's a company that looks out over the long term, and of course it has to perform tactically, but it thinks about the future. So give us the update on what's new at Hitachi Ventara, especially as it relates to data. >> Sure thing, Dave. As many, many folks might be aware, there's a very strong heritage that Hitachi has had in the data space, right. By virtue of our products and our presence in the data storage market, which dates back to many decades, right? And then on the industrial side, the parent company Hitachi has been heavily focused on the OT sector. And as you know, there is a pretty significant digital transformation underway in the OT arena, which is all being led by data. So if you look at our mission statement, for instance, it's actually engineering the data driven because we do believe that data is the fundamental platform that's going to drive that digital transformation, irrespective of what industry you're in. >> So one of the themes that you guys both talk about is modernization. I mean, you can take a cloud, I remember Alan Nance, who was at the time, he was a CIO at Philips, he said, look, you could take a cloud workload, or on-prem workload, stick it into the cloud and lift it and shift it. And in your case, you could just put it on, run it on an RDBMS, but you're not going to affect the operational models. >> Peder Ulander: It's just your mess for less, man. >> If you do that. >> It's your mess, for less. >> And so, he goes, you'll get a few, you know, you'll get a couple of zeros out of that. But if you want to have, in his case, billion dollar impact to the business, you have to modernize. So what does modernize mean to each of you? >> Maybe Peder, you can start. >> Yeah, no, I'm happy to start. I think it comes down to what's going on in the industry. I mean, we are truly moving from a world of data centers to centers of data, and these centers of data are happening further and further out along the network, all the way down to the edges. And if you look at the transformation of infrastructure or software that has enabled us to get there, we've seen apps go from monoliths to microservices. We've seen compute go from physical to serverless. We've seen networking go from old wireline copper to high powered 5G networks. They've all transformed. What's the one layer that hasn't completely transformed yet, data, right? So if we do see this world where things are getting further and further out, you've got to rethink your data architecture and how you basically support this move to modernization. And we feel that MongoDB with our partners, especially with Hitachi, we're best suited to really kind of help with this transition for our customers as they move from data centers to centers of data. >> So architecture. And at the failure, I will say this and you tell me if you agree or not. A lot of the failures of sort of the big data architectures of today are there's, everything's in this monolithic database, you've got to go through a series of hyper-specialized professionals to get to the data. If you're a business individual, you're so frustrated because the market's changing faster than you can get answers. So you guys, I know, use this concept of data fabric, people talk about data mesh. So how do you think, Radhika, about modernization in the future of data, which by its very nature is distributed? >> Yeah. So Dave, everybody talks about the hybrid cloud, right? And so the reality is, every one of our customers is having to deal with data that's straddled across on-prem as well as the public cloud and many other places as well. And so it becomes incredibly important that you have a fairly seamless framework, that's relatively low friction, that allows you to go from the capture of the data, which could be happening at the edge, could be happening at the core, any number of places, all the way to publish, right. Which is ultimately what you want to do with data because data exists to deliver insights, right? And therefore you dramatically want to minimize the friction in the process. And that is exactly what we're attempting to do with our data fabric construct, right. We're essentially saying, customers don't have to worry about, like you mentioned, they may have federated data structures, architectures, data lakes, fitting in multiple locations. How do you ensure that you're not having to double up custom code in order to drive the pipelines, in order to drive the data movement from one location to the other and so forth. And so essentially what we're providing is a mechanism whereby they can be confident about the quality of the data at the end of the day. And this is so paramount. Every customer that I talk to is most worried about ensuring that they have data that is trustworthy. >> So this is a really important point because I've always felt like, from a data quality standpoint, you know you get the data engineers who might not have any business context, trying to figure out the quality problem. If you can put the data responsibility in the hands of the business owner, who, he or she, has context, that maybe starts to solve this problem. There's some buts though. So infrastructure becomes an operational detail. Let's hide that. Don't worry about it. Figure it out, okay, so the business can run, but you need self-service infrastructure and you have to figure out how to have federated governance so that the right people can have access. So how do you guys think about that problem in the future? 'Cause it's almost like this vision creates those two challenges. Oh, by the way, you got to get your organization behind it. Right, 'cause there's an organizational construct as well. But those are, to me, wonderful opportunities but they create technology challenges. So how are you guys thinking about that and how are you working on it? >> Yeah, no, that's exactly right, Dave. As we talk to data practitioners, the recurring theme that we keep hearing is, there is just a lot of use cases that require you to have deep understanding of data and require you to have that background in data sciences and so on, such as data governance and vary for their use cases. But ultimately, the reason that data exists is to be able to drive those insights for the end customer, for the domain expert, for the end user. And therefore it becomes incredibly important that we be able to bridge that chasm that exists today between the data universe and the end customer. And that is what we essentially are focused on by virtue of leaning into capabilities like publishing, right? Like self, ad hoc reporting and things that allow citizen data scientists to be able to take advantage of the plethora of data that exists. >> Peder, I'm interested in this notion of IT and OT. Of course, Hitachi is a partner, established in both. Talk about Mongo's position in thinking. 'Cause you've got on-prem customers, you're running now across all clouds. I call it super cloud connecting all these things. But part of that is the edge. Is Mongo running there? Can Mongo run there, sort of a lightweight version? How do you see that evolve? Give us some details there. >> So I think first and foremost, we were born on-prem, obviously with the origins of MongoDB, a little over five years ago, we introduced Atlas and today we run across a hundred different availability zones around the globe, so we're pretty well covered there. The third bit that I think people miss is we also picked up a product called Realm. Realm is an embedded database for mobile devices. So if you think about car companies, Toyota, for example, building connected cars, they'll have Realm in the car for the telemetry, connects back into an Atlas system for the bigger operational side of things. So there's this seamless kind of, or consistency that runs between data center to cloud to edge to device, that MongoDB plays across all the way through. And then taking that to the next level. We talked about this before we sat down, we're also building in the security elements of that because obviously you not only have that data in rest and data in motion, but what happens when you have that data in use? And announced, I think today? We purchased a little company, Aroki, experts in encryption, some of the smartest security minds on the planet. And today we introduce query-able encryption, which basically enables developers, without any security background, to be able to build searchable capabilities into their applications to access data and do it in a way where the security rules and the privacy all remain constant, regardless of whether that developer or the end user actually knows how that works. >> This is a great example of people talk about shift left, designing security in, for the developer, right from the start, not as a bolt-on. It's a great example. >> And I'm actually going to ground that with a real life customer example, if that's okay, Dave. We actually have a utility company in North Carolina that's responsible for energy and water. And so you can imagine, I mean, you alluded to the IO to use case, the industrial use case and this particular customer has to contend with millions of sensors that are constantly streaming data back, right. And now think about the challenge that they were encountering. They had all this data streaming in and in large quantities and they were actually resident on numerous databases, right. And so they had this very real challenge of getting to that quality data that I, data quality that I talked about earlier, as well, they had this challenge of being able to consolidate all of it and make sense of it. And so that's where our partnership with MongoDB really paid off where we were able to leverage Pentaho to integrate all of the data, have that be resident on MongoDB. And now they're leveraging some of the data capabilities, the data fabric capabilities that we bring to the table to actually deliver meaningful insights to their customers. Now their customers are actually able to save on their electricity and water bills. So great success story right there. >> So I love the business impact there, and also you mentioned Pentaho, I remember that acquisition was transformative for Hitachi because it was the beginning of sort of your new vector, which became Hitachi Ventara. What is Lumada? That's, I presume the evolution of Pentaho? You brought in organic, and added capabilities on top of that, bringing in your knowledge of IOT and OT? Explain what Lumada is. >> Yeah, no, that's a great question, Dave. And I'll say this, I mentioned this early on, we fundamentally believe that data is the backbone for all digital transformation. And so to that end, Hitachi has actually been making a series of acquisitions as well as investing organically to build up these data capabilities. And so Pentaho, as you know, gives us some of that front-end capability in terms of integrations and so forth. And the Lumada platform, the umbrella brand name is really connoting everything that we do in the data space that allow customers to go through that, to derive those meaningful insights. Lumada literally stands for illuminating data. And so that's exactly what we do. Irrespective of what vertical, what use case we're talking about. As you know very well, Hitachi is very prominent in just about every vertical. We're in like 90% of the Fortune 500 customers across banking and financial, retail, telecom. And as you know very well, very, very strong in the industrial space as well. >> You know, it's interesting, Peder, you and Radhika were both talking about this sort of edge model. And so if I understand it correctly, and maybe you could bring in sort of the IOT requirements as well. You think about AI, most of the AI that's done today is modeling in the cloud. But in the future and as we're seeing this, it's real-time inferencing at the edge and it's massive amounts of data. But you're probably not, you're going to persist some, I'm hearing, probably not going to persist all of it, some of it's going to be throwaway. And then you're going to send some back to the cloud. I think of EVs or, a deer runs in front of the vehicle and they capture that, okay, send that back. The amounts of data is just massive. Is that the right way to think about this new model? Is that going to require new architectures and hearing that Mongo fits in. >> Yeah. >> Beautifully with that. >> So this is a little bit what we talked about earlier, where historically there have been three silos of data. Whether it's classic system of record, system of engagement or system of intelligence and they've each operated independently. But as applications are pushing in further and further to the edge and real time becomes more and more important, you need to be able to take all three types of workloads or models, data models and actually incorporate it into a single platform. That's the vision we have behind our developer data platform. And it enables us to handle those transactional, operational and analytical workloads in real time, right. One of the things that we announced here this week was our columnar indexing, which enables some of that step into the analytics so that we can actually do in-app analytics for those things that are not going back into the data warehouse or not going back into the cloud, real time happening with the application itself. >> As you add, this is interesting, as basically Mongo's becoming this all-in-one database, as you add those capabilities, are you able to preserve, it sounds like you've still focused on simplicity, developer product productivity. Are there trade off, as you add, does it detract from those things or are you able to architecturally preserve those? >> I think it comes down to how we're thinking through the use case and what's going to be important for the developers. So if you look at the model today, the legacy model was, let's put it all in one big monolith. We recognize that that doesn't work for everyone but the counter to that was this explosion of niche databases, right? You go to certain cloud providers, you get to choose between 15 different databases for whatever workload you want. Time series here, graph here, in-memory here. It becomes a big mess that is pushed back on the company to glue back together and figure out how to work within those systems. We're focused on really kind of embracing the document model. We obviously believe that's a great general purpose model for all types of workloads. And then focusing in on not taking a full search platform that's doing everything from log management all the way through in-app, we're optimizing for in-app experiences. We're optimizing analytics for in-app experiences. We're optimizing all of the different things we're doing for what the developer is trying to go accomplish. That helps us maintain consistency on the architectural design. It helps us maintain consistency in the model by which we're engaging with our customers. And I think it helps us innovate as quickly as we've been been able to innovate. >> Great, thank you. Radhika, we'll give you the last word. We're seeing this convergence of function in the data based, data models, but at the same time, we're seeing the distribution of data. We're not, you're clearly not fighting that, you're embracing that. What does the future look like from Hitachi Ventara's standpoint over the next half decade or even further out? >> So, we're trying to lean into what customers are trying to solve for, Dave. And so that fundamentally comes down to use cases and the approaches just may look dramatically different with every customer and every use case, right? And that's perfectly fine. We're leaning into those models, whether that is data refining on the edge or the core or the cloud. We're leaning into it. And our intent really is to ensure that we're providing that frictionless experience from end to end, right. And I'll give a couple of examples. We had this very large bank, one of the top 10 banks here in the US, that essentially had multiple data catalogs that they were using to essentially sort through their metadata and make sense of all of this data that was coming into their systems. And we were able to essentially, dramatically simplify it. Cut down on the amount of time that it takes to deliver insights to them, right. And it was like, the metric shared was 600% improvement. And so this is the kind of thing that we're manically focused on is, how do we deliver that quantifiable end-customer improvement, right? Whether it's in terms of shortening the amount to drive the insights, whether it's in terms of the number of data practitioners that they have to throw at a problem, the level of manual intervention that is required, so we're automating everything. We're trying to build in a lot of security as Peder talked about, that is a common goal for both sides. We're trying to address it through a combination of security solutions at varying ends of the spectrum. And then finally, as well, delivering that resiliency and scale that is required. Because again, the one thing we know for sure that we can take for granted is data is exploding, right? And so you need that scale, you need that resiliency. You need for customers to feel like there is high quality, it's not dirty, it's not dark and it's something that they can rely upon. >> Yeah, if it's not trusted, they're not going to use it. The interesting thing about the partnership, especially with Hitachi, is you're in so many different examples and use cases. You've got IT. You've got OT. You've got industrial and so many different examples. And if Mongo can truly fit into all those, it's just, the rocket ship's going to continue. Peder, Radhika, thank you so much for coming back in theCUBE, it's great to see you both. >> Thank you, appreciate it. >> Thank you, my pleasure. >> All right. Keep it right there. This is Dave Vellante from the Javits Center in New York City at MongoDB World 2022. We'll be right back. (upbeat music)

(upbeat music) >> Welcome back to New York City everybody. You're watching theCUBE's coverage of MongoDB World 2022. My name is Dave Vellante. Pretty good attendance here. I'd say over 3000 people, great buzz, a lot of really technical sessions. There's an executive session going on. There's a financial analyst session. So a lot of diversity in this attendee base. Vadim Supitskiy is here. He's the CTO of Forbes and Abdul Razack is the vice president of Solution Engineering at Google. Gents, thanks for coming on theCUBE. >> Thanks Dave. >> Happy to be here. >> So, Forbes, very interesting business. I'm interested in what occurred during the pandemic for you guys. Right? Everybody went digital. Obviously you guys have a tremendous brand. We all, in the business world reaped from it, but what happened during the isolation era? What happened to your business? >> Yeah, so we've been innovating and going through digital transformation for years, since we launched our website probably 25 years ago. >> But during the pandemic, because of our coverage, our foresight to create a breaking news team, our audiences and readership really skyrocketed. >> Really? >> Yeah, and at that point, we were very happy and really lucky to be in Google Cloud and MongoDB Atlas. So when the audiences went up, we didn't feel any impact, right? Our environments auto-scaled and our users didn't experience any issues at all. So we were able to focus on innovation, our users loyalty and really building cool products. So we were very lucky and happy to be in Google Cloud and MongoDB Atlas. >> So Abdul, the solution and the title you provided, obviously worked. How did you guys end up getting together? What was that like? >> Yeah, I mean, like Vadim said, maybe there's a little bit of the right place at the right time in this case, but you can see the need for digital transformation and the pandemic really accelerated that. And like Vadim said, primarily Forbes wanted to focus on innovation and customer loyalty and the way that comes to bear, is that you have a technology platform that can serve those needs. Right? Whether it is through unique applications that can be delivered, the ability for developers to build those applications quickly and seamlessly and then remove the intangibles of scalability, performance, latency, and things of that nature. So, you can see this all coming together in this scenario. >> So as consumers, we see the website, we read online, maybe sometimes in the laptop, mostly on mobile. What is it that we don't see? I mean, the apps that Abdul talked about, community. What else is there? Paint a picture of that for us. >> Yeah. There is a lot going on behind the scene. Right? So focusing on audience, building communities, but also what it allowed us to do while everything was working well, we were scaling up. Right? We were able to focus on a lot of innovation. And one of those was first-party data platform that we built. We call it Forbes One. And that's in the center of everything that we do at Forbes right now. Right? So it allows us, one, to connect our partners, advertising partners with the audiences that they're looking to engage and to connect with. And then we are growing our consumer business as well and what that allows us to do is target the right products at the right time, to the right people, on the web website and our domain. So, that's just one of the examples that we've built our full first-party data platform on these technologies and we now know our customers so well that we are able to provide them with what they want. >> So the first-party data platform is what? A self-serve for advertiser, so they can identify? >> Not just advertisers. So it's in the center of everything. So advertiser comes in, we provide the segments and users that they want to reach. Now, we are creating products as well, building cool, innovative products and offering our journalism and everything there to our readers and we are able to connect them to the right audiences at the right time, as well as personalization. Right? You come onto the website, you want to read what you want to read. So we able to create that as well, using machine learning and AI. >> So a product, it might be a data product or it might be a content product? >> It could be a data product. It could be like just personalization or something like that. It could be newsletter. Right? It could be a stand-alone product, like investing product. So, there is a lot going on there, but we want to offer the right ones at the right time, to the right audiences and building that platform has allowed us to do that. >> Okay. Now Google's got great tech. What's the tech behind all this? >> Yeah. So when Vadim talked about segmenting to personalize something that is relevant to you and providing recommendations to you. Right? And all that is based on machine learning, AI technology. The fact that Vadim has all the data curated in a in a first-party data platform gives the ability to create a seamless profile. Right? You could be interested in a couple of products. Right? And then the underlying technology can tailor that to bring what is it that you're looking for at the right place at the right time. Right? So those are recommendations, things of that nature that's all powered by AI and machine learning technology. >> So it's running on Mongo, and then you're bringing in Google AI and machine intelligence tools? Can you double click on that? >> Yeah. It's basically a combination of both, using both platform to the deploy it and we embrace Cloud. Right? So we using all the Cloud native technologies. Right? We didn't want to just lift and shift. We wanted to make sure we do it right. And we focused on automation, even if we had to take a step back, we knew that automating things was a key for us. So yes, it's been really successful, but also really informative for us to use the right tools for the job. >> And you had prior experience with Mongo, or? >> We did. >> What's your journey been like there? >> Yeah, we actually were one of the first clients of Mongo. I think we were number 11 at that time. >> 10gen. >> Yes. It was. >> We remember. >> Many years ago it was MongoDB one, right? >> Yeah. >> And at that time we we introduced contributor network for us and our audiences were scaling as well. And we used Out-of-the-Box WordPress as our publishing platform, which couldn't scale. So we had to rethink and figure out, "Alright, so what do we do?" We compared couple of no SQL databases and Mongo was a winner because they checked all the boxes and developers loved it right away. Right? They're like, "All right, this is so much faster to develop on. It's just a great tool for the job going from SQL to, to no SQL". And we scaled and we never looked back. And then obviously Atlas came, so there are kind of two inflection points here. One switch into no SQL and two going away from managing databases. Like we don't want to be in that business. Right? Updates, patches, all of that, that we had to do manually, over-provision in our environments and kind of wasteful. So being on Atlas, that was a second kind of inflection point for us, which opened it up for us to do even more innovation and move faster. >> Okay. And you're happy about this partnership, despite, I mean, you partner with Mongo obviously, Google has its own databases, that's just the nature of the world we live in, isn't it? >> No and fundamentally like that, we always believe that customer choice is the primary notion. Right? I mean, and Google Cloud platform is more of a platform and the ecosystem is critical to that. Right? It's imperative. So, like Vadim said, the combination of Google and Mongo provides a truly Cloud native platform that can serve the needs for years to come, rather than from looking at it from a legacy perspective. And that's the way we look at it. Right? I mean, there is choices all the time and sometimes it's competition. >> Yeah. Yeah. And you're still selling a lot of compute and storage and machine intelligence, so machine learning. This morning in the keynotes, we heard a lot about a lot of different capabilities. We've certainly watched Mongo evolve its platform over the last half a decade or more really. But you've mentioned the developers loved it. Right? As Mongo evolves its platform, is there trade off from a developer simplicity standpoint? Are they able to preserve that from your perspective? >> I think with Atlas, it actually makes it easier now. So when they need to create an environment, they can do it on the fly. When they need to test something, also things available to them right away. So it actually, in general, as the platform becomes more mature and more stable, which is very important, but at the same time, the flexibility remains for development and for creation of environments and things like that. So we've been pretty happy with how it transitioned, to being a more mature platform. >> Did the move to Google Cloud and Atlas change the way that you're able to deliver high availability versus what you were doing when you were self-managing? Can you talk about that a little bit? >> Yeah, absolutely. We were in a data center, so kind of one location and moving to MongoDB Atlas and Google Cloud, now we're multi region. Right? So we have a full DR strategy and we feel a lot more secure and we feel very confident that anything that happens, we can scale, we can fail over. So absolutely, this helps us a lot. And the feature that was introduced probably a few years ago to auto scale MongoDB environments as well, that has been really key for us, so we can sleep well. >> Meaning you can scale while you sleep. >> Right, exactly. Exactly. >> Yeah. Plus the other part is you don't size for peak. right? You size as you grow, and then you, you have that elasticity built in. Right? That it is the nature. And then Mongo is available on multiple Google Cloud regions. So as you expand, you don't worry about all the plumbing that you need to do and things of that nature. >> They asked us serverless this morning. >> Yeah. >> How does that affect what you guys are doing together and what are your thoughts from Google's perspective and then of course, from Forbes? >> And that's the trend that we see constantly. Right? Serverless really decouples the tie to the VMs. Right? And so it makes it much more easier to provide the elasticity and have function calls across. Right? Function as a service and things of that nature. Right? So we see a lot of promise in that. Right? We do that even within our own products and we see that giving the ability to decompose and recompose applications and would love to hear how you're leveraging that. Right? >> Yeah. We fully embrace serverless. So we use all the tools you provide, I think. If you look at our architectural diagrams, it's like all these pops-up, cloud functions, composer, app engine. So we use the full suite and we love it. >> Yeah, Yeah. Okay. And then you talked this morning about the eliminating, the trade-offs with serverless of having to either when you dial it down You have to restart, but you've solved that problem, or I guess Mongo's helped you solve that problem. Can you explain that a little bit from a technical standpoint? >> Yeah. From a technical standpoint, if you look at, like as a developer, right? If you're building an intelligent app, it has multiple components within it. Right? There is pops-up for messaging, there is cloud functions and things of that nature. So you don't worry about, when it's encompassed in a serverless architecture, you don't worry about a lot of the complexities that go on behind it and so that makes the abstraction much more easier. And it eliminates the friction that a developer goes through. I think they've talked about removing friction and that's the primary source of productivity loss, which is the friction. We used to come from a world where developers were more worried. 80% of the time they would spend on plumbing this thing and then only 20% writing code. Right? And then now this whole paradigm should flip that. Right? That's where we see the promise of it. >> Do you still do stuff on Prem or are you pretty much all in the Cloud? >> Fully in the Cloud. >> How long did that take? What was that like? >> It actually was really fast. We had a real aggressive timeline. It took us six months. >> Really? >> Yeah. Yeah. And it was aggressive, but I was happy that we did it in a short period of time. >> And what was the business impact that you saw moving to the Google Cloud? >> Yeah, so obviously after we moved to the Cloud, we wanted to measure, especially the first year, how it affected us and what were the positives out of it. And yeah, we've seen tremendous results. 58% increase in speed to market. We were releasing four times more often than when we were on Prem. We saw 73% increase in initiatives delivered and while our velocity was scaling up, we also saw 30% decreased in hot fixes and rollbacks. So it became more stable while we scaled up the velocity and obviously very happy with those results. >> Wow. Do you golf? >> I don't actually. >> Do you golf? >> No. I watch golf. >> I used to watch. Okay. Do you know what a mulligan is? >> Yeah. >> Okay. mulligan is like a do-over right. If you had a mulligan, would you do anything differently? >> You know, we learned a lot and one of the keys for me was definitely automate everything, make sure that you automate as much as possible, even if it slows you down because in the future that will help you so much and use the platform and the tools that available to you. So, serverless. Right? Use Cloud the way it's supposed to be, as much as possible and I think that's the advice I would give. >> Are there any cautions with regard to automation, either of you that you see? I mean because sometimes automation brings unintended consequences and "Oops" happens really fast. >> Yeah. It's a little bit of a process. Right? If you take a step back, right, and typically what people tend to do is, there is a standardization process and once it's standardized, the next step is you gain efficiencies by automation. Right? In this whole thing, what is underestimated is change management. And we see a lot of room for improvement around educating on change management, getting ahead of that so that you can see what is coming. So that the organization moves across that. I don't know if you saw that in your case, but we see this predominantly in other other cases. >> Yeah. I mean, for us, we wanted to make sure that all the testing was in place and things like that. So not just automation of deploying or anything like that, but make sure that there is something there to catch if something goes wrong and roll back and things like that. So you want to make sure that you protected in many areas. >> So square this circle for me, because especially with COVID, so many unknowns and one of the benefits of document database is you're not tied into a schema. You got a flexible schema. Okay. So you're changing, you can change things much more easily. So when you talk about standardization, you're talking about standardizing, what at the infrastructure layer, or where does that standardization occur? Where should it occur. >> I mean, you could have it at the business process level. >> Okay. >> You could have it at the infrastructure level. You could also have it on the administration aspect of it. So there are three areas where you could apply automation to. >> So is there an analog to flexible schema at the business process level? Is that kind of how to think about it, whereas I'm not locked into a business process schema? I have to build flexibility into that as I change my? >> No, I mean, you can apply it any which way. I mean, I don't think the schema matters so much. Right? Like, for example, if you take the Forbes US case. Right? There is content curation, for example. Right? >> Yeah, okay. >> You could take content curation. Content curation in the previous world, like in the WordPress world, was not very flexible. Right? Like that it wouldn't scale. And now you are in a world where you have a very flexible schema, but the process of curating the content can be standardized. Right? And then the next step of that is to automate that. Right? And so you could apply it in any manner if you will. >> So have you built a custom CMS? Is that what you've done there? >> Yeah. We built our own custom CMS. It's AI powered. We want to make our journalist lives easier. So we're constantly trying to figure out what can we give them to make their day-to-day job much easier. >> So the machines can curate and find the best content. >> We do recommend things. Yes, absolutely. We curate, we tell them what would be the best headline, for example, what would >> Prior to them publishing? >> Yeah. Yeah. What would be the better keywords to include and things like that, what images. Just recommendations. >> And you can automate the insertion of those WordPress to go every time they do, even though they're writing about the same topic. >> It's a recommendation process obviously, but >> There is a human intelligence to that at the end. Right? I mean, but you can create a much more informed view by curating and recommending content rather than a myopic view. >> And you're eliminating that mundane keystroke task. Wow. Amazing story guys. Thanks so much for sharing. >> Absolutely. >> All right. Keep it right there. We're live from MongoDB World 2022 in New York city. Be right back. (upbeat music)

>>Mhm. Mhm. Yeah. Hello, everybody. Welcome to the Cubes. Coverage of Mongo db World 2022. This is the first Mongo live mongo DB World. Since 2019, the Cube has covered a number of of mongo shows actually going back to when the company was called Engine. Some of you may recall Margo since then has done an i p o p o in 2017, it's It's been a rocket ship company. It's up. It'll probably do 1.2 billion in revenue this year. It's got a billion dollars in cash on the balance sheet. Uh, despite the tech clash, it's still got a 19 or $20 million valuation growing above 50% a year. Uh, company just had a really strong quarter, and and there seems to be hitting on all cylinders. My name is Dave Volonte. And here to kick it off with me as Sanjeev Mohan, who was the principal at Sanremo. So great to see you. You become a wonderful cube contributor, Former Gartner analyst. Really sharp? No, the database space in the data space generally really well, so thanks for coming back on >>you. You know, it's just amazing how exciting. The entire data space is like they used to say. Companies are All companies are software companies. All companies are data >>companies, >>so data has become the the foundation. >>They say software is eating the world. Data is eating software and a little little quips here. But this is a good size show. Four or 5000 people? I don't really know exactly. You know the numbers, but it's exciting. And of course, a lot of financial services were here at the Javits Centre. Um, let's let's lay down the basics for people of Mongo, DB is a is a document database, but they've been advancing. That's a document database as an alternative to R D. B M s. Explain that, but explain also how Mongo has broadened its capabilities and serving a lot more use cases. >>So that's my forte is like databases technology. But before even I talk about that, I have to say I am blown away by this mongo db world because mongo db uh, in beckons to all of us during the pandemic has really come of age, and it's a billion dollar company. Now we are in this brand new Javits Centre That's been built during the pandemic. And and now the company is holding this event the high 1000 people last year. So I think this company has really grown. And why has it drawn is because its offerings have grown to more developers than just a document database document databases. Revolution revolutionised the whole DBM s space where no sequel came up. Because for a change, you don't need a structured schema. You could start bringing data in this document model scheme, uh, like varying schema. But since then, they've added, uh, things like such. So they have you seen such? They added a geospatial. They had a time series last year, and this year they keep adding more and more so like, for example, they are going to add some column store indexes. So from being a purely transactional, they are now starting to address analytical. And they're starting to address more use cases, like, you know, uh, like what? What was announced this morning at keynote was faceted search. So they're expanding the going deeper and deeper into these other data >>structures. Taking Lucy made a search of first class citizens, but I want to ask you some basic questions about document database. So it's no fixed schemes. You put anything in there? Actually, so more data friendly. They're trying to simplify the use of data. Okay, that's that's pretty clear. >>What are the >>trade offs of a document database? >>So it's not like, you know, one technology has solved every problem. Every technology comes with its own tradeoffs. So in a document, you basically get rid of joining tables with primary foreign keys because you can have a flexible schemer and so and wouldn't sing single document. So it's very easy to write and and search. But when you have a lot of repeated elements and you start getting more and more complex, your document size can start expanding quite a bit because you're trying to club everything into a single space. So So that is where the complexity goes >>up. So what does that mean for for practitioner, it means they have to think about what? How they how they are ultimately gonna structure, how they're going to query so they can get the best performances that right. So they're gonna put some time in up front in order to make it pay back at the tail end, but clearly it's it's working. But is that the correct way of thinking about >>100% in, uh, the sequel world? You didn't care about the sequel. Analytical queries You just cared about how your data model was structured and then sequel would would basically such any model. But in the new sequel world, you have to know your patterns before you. You invest into the database so it's changed that equation where you come in knowing what you are signing up. >>So a couple of questions, if I can kind of Colombo questions so to Margo talks about how it's really supporting mission critical applications and at the same time, my understanding is the architecture of mongo specifically, or a document database in general. But specifically, you've got a a primary, uh, database, and you and that is the sort of the master, if you will, right and then you can create secondaries. But so help me square the circle between mission critical and really maybe a more of a focus on, say, consistency versus availability. Do customers have to sort of think about and design in that availability? How do they do that? How a Mongol customers handling that. >>So I have to say, uh, my experience of mongo db was was that the whole company, the whole ethos was developed a friendly. So, to be honest, I don't think Mongo DB was as much focused on high availability, disaster, recovery, even security. To some extent, they were more focused on developer productivity. >>And you've experienced >>simplicity. Make it simple, make the developers productive as fast as you can. What has really, uh, was an inflexion point for Mongo DB was the launch of Atlas because the atlas they were able to introduce all of these management features and hide it abstracted from the end users. So now they've got, you know, like 2014 is when Atlas came out and it was in four regions. But today they're in 100 regions, so they keep expanding, then every hyper scale cloud provider, and they've abstracted that whole managed. >>So Atlas, of course, is the managed database as a service in the cloud. And so it's those clouds, cloud infrastructure and cloud tooling that has allowed them to go after those high available application. My other question is when you talk about adding search, geospatial time series There are a lot of specialised databases that take time series persons. You have time series specialists that go deep into time series can accompany like Mongo with an all in one strategy. Uh, how close can they get to that functionality? Do they have to be? You know, it's kind of a classic Microsoft, you know, maybe not perfect, but good enough. I mean, can they compete with those other areas? Uh, with those other specialists? And what happens to those specialists if the answer is yes. What's your take on that? If that question >>makes sense So David, this is not a mongo db only issue This is this is an issue with, you know, anytime serious database, any graph database Should I put a graph database or should I put a multifunctional database multidimensional database? And and I really think there is no right or wrong answer. It just really comes down to your use case. If you have an extremely let's, uh, complex graph, you know, then maybe you should go with best of breed purpose built database. But more and more, we're starting to see that organisations are looking to simplify their environment by going in for maybe a unified database that has multiple data structures. Yeah, well, >>it's certainly it's interesting when you hear Mongo speak. They don't They don't call out Oracle specifically, but when they talk about legacy r d m r d B m s that don't scale and are complex and are expensive, they're talking about Oracle first. And of course, there are others. Um, And then when they talk about, uh, bespoke databases the horses for courses, databases that they show a picture of that that's like the poster child for Amazon. Of course, they don't call out Amazon. They're a great partner of Amazon's. But those are really the sort of two areas that mangoes going after, Um, now Oracle. Of course, we'll talk about their converged strategy, and they're taking a similar approach. But so help us understand the difference. There is just because they're sort of or close traditional r d B M s, and they have all the drawbacks associated with that. But by the way, there are some benefits as well. So how do you see that all playing >>out? So you know it. Really, uh, it's coming down to the the origins of these databases. Uh, I think they're converging to a point where they are offering similar services. And if you look at some of the benchmark numbers or you talk to users, I from a business point of view, I I don't think there's too much of a difference. Uh, technology writes. The difference is that Mongo DB started in the document space. They were more interested in availability rather than consistency. Oracle started in the relation database with focus on financial services, so asset compliance is what they're based on. And since then they've been adding other pieces, so so they differ from where they started. Oracle has been in the industry for some since 19 seventies, so they have that maturity. But then they have that legacy, >>you know, I love. Recently, Oracle announced the mongo db uh, kpi. So basically saying why? Why leave Oracle when you can just, you know, do the market? So that, to me, is a sign that Mongo DB is doing well because the Oracle calls you out, whether your workday or snowflake or mongo. You know, whoever that's a sign to me that you've got momentum and you're stealing share in that marketplace, and clearly Mongo is they're growing at 50 plus percent per year. So thinking about the early I mentioned 10 gen Early on, I remember that one of the first conferences I went to mongo conferences. It was just It was all developers. A lot of developers here as well. But they have really, since 2014, expanded the capabilities you talk about, Atlas, you talked about all these other you know, types of databases that they've added. If it seems like Mongo is becoming a platform company, uh, what are your thoughts on that in terms of them sort of up levelling the message there now, a billion dollar plus company. What's the next? You know, wave for Mongo. >>So, uh, Oracle announced mongo db a p i s a W s has document d. B has cost most db so they all have a p. I compatible a p. I s not the source code because, you know, mongo DB has its own SPL licence, so they have written their own layer on top. But at the end of the day, you know, if you if you these companies have to keep innovating to catch up with Mongo DB because we can announce a brand new capability, then all these other players have to catch up. So other cloud providers have 80% or so of capabilities, but they'll never have 100% of what Mongo DB has. So people who are diehard Mongo DB fans they prefer to stay on mongo db. They are now able to write more applications like you know, mongo DB bought realm, which is their front end. Uh, like, you know, like, if you're on social media kind of thing, you can build your applications and sink it with Atlas. So So mongo DB is now at a point where they are adding more capabilities that more like developers like, You know, five G is coming. Autonomous cars are coming, so now they can address Iot kind of use cases. So that's why it's becoming such a juggle, not because it's becoming a platform rather than a single document database. >>So atlases, the near the midterm future. Today it's about 60% of revenues, but they have what we call self serve, which is really the traditional on premise stuff. They're connecting those worlds. You're bringing up the point that. Of course, they go across clouds. You also bring up the point that they've got edge plays. We're gonna talk to Verizon later on today. And they're they've got, uh, edge edge activity going on with developers. I I call it Super Cloud. Right, This layer that floats above. Now, of course, a lot of the super Cloud concert says we're gonna hide the underlying complexity. But for developers, they wanna they might want to tap those primitives, so presumably will let them do that. But But that hybrid that what we call Super Cloud that is a new wave of innovation, is it not? And do you? Do you agree with that? And do you see that as a real opportunity from Mongo in terms of penetrating a new tan? >>Yes. So I see this is a new opportunity. In fact, one of the reasons mongo DB has grown so quickly is because they are addressing more markets than they had three pandemic. Um, Also, there are all gradations of users. Some users want full control. They want an eye as kind of, uh, someone passed. And some businesses are like, you know, we don't care. We don't want to deal with the database. So today we heard, uh, mongo db. Several went gear. So now they have surveillance capability, their past. But if you if you're more into communities, they have communities. Operator. So they're addressing the full stack of different types of developers different workloads, different geographical regions. So that that's why the market is expected. >>We're seeing abstraction layers, you know, throughout the started a physical virtual containers surveillance and eventually SuperClubs Sanjeev. Great analysis. Thanks so much for taking your time to come with the cube. Alright, Keep it right there. But right back, right after this short break. This is Dave Volonte from the Javits Centre. Mongo db World 2022. Thank you. >>Mm.

>> theCube presents Dell Technologies World, brought to you by Dell. >> Hi everyone, welcome back to Dell Technologies World 2022. You're watching theCube's coverage of this, three-day coverage wall to wall. My name is David Vellante John Furrier's here, Lisa Martin, David Nicholson. Talk of the town here is data. And one of the big announcements at the show is Snowflake and Dell partnering up, building ecosystems. Snowflake reaching into on-prem, allowing customers to actually access the Snowflake Data Cloud without moving the data or if they want to move the data they can. This is really one of the hotter announcements of the show. Martin Glynn is here, he's the Senior Director of Storage Product Management at Dell Technologies. And Clark Patterson, he's the Head of Product Marketing for Snowflake. Guys, welcome. >> Thanks for having us. >> So a lot of buzz around this and, you know, Clark, you and I have talked about the need to really extend your data vision. And this really is the first step ever you've taken on-prem. Explain the motivation for this from your customer's perspective. >> Yeah. I mean, if you step back and think about Snowflake's vision and our mission of mobilizing the world's data, it's all around trying to break down silos for however customers define what a silo is, right? So we've had a lot of success breaking down silos from a workload perspective where we've expanded the platform to be data warehousing, and data engineering, and machine learning, and data science, and all the kind of compute intensive ways that people work with us. We've also had a lot of success in our sharing capabilities and how we're breaking down silos of organizations, right? So I can share data more seamlessly within my team, I can do it across totally disparate organizations, and break down silos that way. So this partnership is really like the next leg of the stool, so to speak, where we're breaking down the silos of the the data and where the data lives ultimately, right? So up until this point, Cloud, all focus there, and now we have this opportunity with Dell to expand that and into on-premises world and people can bring all those data sets together. >> And the data target for this Martin, is Dell ECS, right? Your object store, and it's got S3 compatibility. Explain that. >> Yeah, we've actually got sort of two flavors. We'll start with ECS, which is our turnkey object storage solution. Object storage offers sort of the ultimate in flexibility, you know, potential performance, ease of use, right? Which is why it fits so well with Snowflake's mission for sort of unlocking, you know, the data within the data center. So we'll offer it to begin with ECS, and then we also recently announced our software defined object scale solution. So add even more flexibility there. >> Okay. And the clock, the way it works is I can now access non-native Snowflake data using what? Materialized views, external tables, how does that work? >> Some combination of all the above. So we've had in Snowflake a capability called external tables which we refer to, it goes hand in hand with this notion of external stages. Basically through the combination of those two capabilities, it's a metadata layer on data wherever it resides. So customers have actually used this in Snowflake for data lake data outside of Snowflake in the Cloud up until this point. So it's effectively an extension of that functionality into the Dell on-premises world, so that we can tap into those things. So we use the external stages to expose all the metadata about what's in the Dell environment. And then we build external tables in Snowflake so that data looks like it is in Snowflake. And then the experience for the analyst or whomever it is, is exactly as though that data lives in the Snowflake world. >> Okay. So for a while you've allowed non-native Snowflake data but it had to be in the Cloud. >> Correct. >> It was the first time it's on-prem, >> that's correct >> that's the innovation here. Okay. And if I want to bring it into the Cloud, can I? >> Yeah, the connection here will help in a migration sense as well, right? So that's the good thing is, it's really giving the user the choice. So we are integrating together as partners to make connection as seamless as possible. And then the end user will say like, look I've got data that needs to live on-premises, for whatever reasons, data sovereignty whatever they decide. And they can keep it there and still do the analytics in another place. But if there's a need and a desire to use this as an opportunity to migrate some of that data to Cloud, that connection between our two platforms will make that easier. >> Well, Michael always says, "Hey, it's customer choice, we're flexible." So you're cool with that? That's been the mission since we kind of came together, right? Is if our customers needed to stay in their data center, if that makes more sense from a cost perspective or, you know, a data gravity perspective, then they can do that. But we also want to help them unlock the value of that data. So if they need to copy it up to the public Cloud and take advantage of it, we're going to integrate directly with Snowflake to make that really easy to do. >> So there are engineering integrations here, obviously that's required. Can you describe what that looks like? Give us the details on when it's available. >> Sure. So it's going to be sort of second half this year that you'll see, we're demoing it this week, but the availability we second half this year. And fundamentally, it's the way Clark described it, that Snowflake will reach into our S3 interface using the standard S3 interface. We're qualifying between the way they expect that S3 interface to present the data and the way our platform works, just to ensure that there's smooth interaction between the two. So that's sort of the first simplest use case. And then the second example we gave where the customer can copy some of that data up to the public Cloud. We're basically copying between two S3 buckets and making sure that Snowflake's Snowpipe is aware that data's being made available and can easily ingest it. >> And then that just goes into a virtual warehouse- >> Exactly. >> and customer does to know or care. >> Yep Exactly. >> Yeah. >> The compute happens in Snowflake the way it does in any other manner. >> And I know you got to crawl, walk, run second half of this year, but I would imagine, okay, you're going to start with AWS, correct? And then eventually you go to other Clouds. I mean, that's going to take other technical integrations, I mean, obviously. So should we assume there's a roadmap here or is this a one and done? >> I would assume that, I mean, based on our multi-Cloud approach, that's kind of our approach at least, yeah. >> Kind of makes sense, right? I mean, that would seem to be a natural progression. My other thought was, okay, I've got operational systems. They might be transaction systems running on a on a PowerMax. >> Yeah. >> Is there a way to get the data into an object store and make that available, now that opens up even more workloads. I know you're not committing to doing that, but it just, conceptually, it seems like something a customer might want to do. >> Yeah. I, a hundred percent, agree. I mean, I think when we brought our team together we started with a blank slate. It was what's the best solution we can build. We landed on this sort of first step, but we got lots of feedback from a lot of our big joint customers about you know, this system over there, this potential integration over here, and whether it's, you know, PowerMax type systems or other file workloads with native Snowflake data types. You know, I think this is just the beginning, right? We have lots of potential here. >> And I don't think you've announced pricing, right? It's premature for that. But have you thought about, and how are you thinking about the pricing model? I mean, you're a consumption based pricing, is that kind of how this is going to work? Or is it a sort of a new pricing model or haven't you figured that out yet? >> I don't know if you've got any details on that, but from a Snowflake perspective, I would assume it's consistent with how our customers engage with us today. >> Yeah. >> And we'll offer both possibilities, right? So you can either continue with the standard, you know, sort of CapEx motion, maybe that's the most optimal for you from a cost perspective, or you can take advantage through our OpEx option, right? So you can do consumption on-prem also. >> Okay. So it could be a dual model, right? Depending on what the customer wants. If they're a Snowflake customer, obviously it's going to be consumption based, however, you guys price. What's happening, Clark, in in the market? Explain why Snowflake has so much momentum and, you know, traction in the marketplace. >> So like I spent a lot of time doing analysis on why we win and lose, core part of my role. And, you know, there's a couple of, there's really three things that come up consistently as to why people people are really excited about Snowflake platform. One is the most simplest thing of all. It feels like is just ease of use and it just works, right? And I think the way that this platform was built for the Cloud from the ground up all the way back 10 years ago, really a lot allows us to deliver that seamless experience of just like instant compute when you want it, it goes away, you know, only pay for what you use. Very few knobs to turn and things like that. And so people absolutely love that factor. The other is multi-Cloud. So, you know, there's definitely a lot of organizations out there that have a multi-Cloud strategy, and, you know, what that means to them can be highly variable, but regardless, they want to be able to interact across Clouds in some capacity. And of course we are a single platform, like literally one single interface, consistent across all the three Cloud providers that we work upon. And it gives them that flexibility to mix and match Cloud infrastructure under any Snowflake however they see fit. The last piece of it is sharing. And, you know, I think it's that ability as I kind of alluded to around like breaking down organizational silos, and allow people to be able to actually connect with each other in ways that you couldn't do before. Like, if you think about how you and I would've shared data before, I'd be like, "Hey, Dave, I'm going to unload this table into a spreadsheet and I'm going to send it over in email." And there's the whole host of issues that get introduced in that and world, now it's like instantly available. I have a lot of control over it, it's governed it's all these other things. And I can create kind of walled gardens, so to speak, of how far out I want that to go. It could be in a controlled environment of organizations that I want to collaborate with, or I can put it on our marketplace and expose it to the whole world, because I think there's a value in that. And if I choose I can monetize it, right? So those, you know, the ease of use aspect of it, absolutely, it's just a fantastic platform. The multi-Cloud aspect of it and our unique differentiation around sharing in our marketplace and monetization. >> Yeah, on the sharing front. I mean, it's now discoverable. Like if you send me an email, like what'd you call that? When did you send that email? And then the same time I can forward that to somebody else's not governed. >> Yeah. >> All right. So that just be creates a nightmare for the compliance. >> Right. Yeah. You think about how you revoke access in that situation. You just don't, right? Now I can just turn it off and you go in to run your query. >> Don't get access on that data anymore. Yeah. Okay. And then the other thing I wanted to ask you, Clark is Snowflake started really as analytics platform, simplifying data warehousing, you're moving into that world of data science, you know, the whole data lake movement, bringing those two worlds together. You know, I was talking to Ben Ward about this, maybe there's a semantic layer that helps us kind of talk between those two worlds, but you don't care, right? If it's in an object store, it can play in both of those worlds, right? >> That's right. >> Yeah, it's up to you to figure it out and the customer- >> Yeah. >> from a storage standpoint. Here it is, serve it up. >> And that's the thrust of this announcement, right? Is bringing together two great companies, the Dell platform, the Snowflake platform, and allowing organizations to bring that together. And they decide like it, as we all know, customers decide how they're going to build their architecture. And so this is just another way that we're helping them leverage the capabilities of our two great platforms. >> Does this push or pull or little bit of both? I mean, where'd this come from? Or customers saying, "Hey, it would be kind of cool if we could have this." Or is it more, "Hey, what do you guys think?" You know, where are you at with that? >> It was definitely both, right? I mean, so we certainly started with, you know, a high level idea that, you know, the technologies are complimentary, right? I mean, as Clark just described, and at the same time we had customers coming to us saying, "Hey, wait a minute, I'm doing this over here, and this over here, how can I make this easier?" So that was like I said, we started with a blank sheet and lots of long customer conversations and this is what resulted. So >> So what are the sequence of events to kind of roll this out? You said it's second half, you know, when do you start getting customers involved? Do you have your already, you know, to poke at this and what's that look like? >> Yeah, sure. I can weigh in there. So, absolutely. We've had a few of our big customers that have been involved sort of in the design already who understand how they want to use it. So I think our expectation is that now that the sort of demonstrations have been in place, we have some pre functionality, we're going to see some initial testing and usage, some beta type situations with our customers. And then second half, we'll ramp from there. >> It's got to be a huge overlap between Dell customers and Snowflake customers. I mean, it's hundred billion. You can't not bump into Dell somewhere. >> Exactly. Yeah, you know. >> So where do you guys want to see this relationship go, kind of how should we measure success? Maybe you could each give your perspectives of that. >> I mean, for us, I think it's really showing the value of the Snowflake platform in this new world where there's a whole new ecosystem of data that is accessible to us, right? So seeing those organizations that are saying like, "Look, I'm doing new things with on-premises data that I didn't think that I could do before", or, "I'm driving efficiency in how I do analytics, and data engineering, and data science, in ways that I couldn't do before," 'cause they were locked out of using a Snowflake-like technology, right? So I think for me, that's going to be that real excitement. I'm really curious to see how the collaboration and the sharing component comes into this, you know, where you can think of having an on-premises data strategy and a need, right? But you can really connect to Cloud native customers and partners and suppliers that live in the Snowflake ecosystem, and that wasn't possible before. And so that is very conceivable and very possible through this relationship. So seeing how those edges get created in in our world and how people start to collaborate across data, both in the Cloud and on-prem is going to be really exciting. >> I remember I asked Frank, it was kind of early in the pandemic. I asked him, come on, tell me about how you're managing things. And he was awesome. And I asked him to at the time, you know, "You're ever going to do, you know, bring this platform on-prem?" He's like unequivocal, "No way, that's never going to happen. We're not going to do it halfway house ware Cloud only." And I kept thinking, but there's got to be a way to expand that team. There's so much data out there, and so boom, now we see the answer . Martin, from your standpoint, what does success look like? >> I think it starts with our partnership, right? So I've been doing this a long time. Probably the first time I've worked so closely with a partner like Snowflake. Joint customer conversations, joint solutioning, making sure what we're building is going to be really, truly as useful as possible to them. And I think we're going to let them guide us as we go forward here, right? You mentioned, you know, systems or record or other potential platforms. We're going to let them tell us where exactly the most value will come from the integration between the two companies. >> Yeah. Follow data. I mean, remember in the old days a hardware company like Dell would go to an ISP like Snowflake and say, "Hey, we ran some benchmarks. Your software runs really fast on our hardware, can we work together?" And you go, "Yeah, of course. Yeah, no problem." But wow! What a different dynamic it is today. >> Yeah. Yeah, absolutely. >> All right guys. Hey, thanks so much for coming to theCube. It's great to see you. We'll see you at the Snowflake Summit in June. >> Snowflake Summit in a month and a half. >> Looking forward to that. All right. Thank you again. >> Thank you Dave. >> All right. Keep it right there everybody. This is Dave Vellante, wall to wall coverage of Dell Tech World 2022. We'll be right back. (gentle music)