>>Hi everyone. Welcome to the Cube special presentation here in Palo Alto, California. I'm John Foer, host of the Cube. We've got two great guests, one for calling in from Germany, our videoing in from Germany, one from Maryland. We've got VMware and aws. This is the customer successes with VMware cloud on AWS showcase, accelerating business transformation here in the showcase with Samir Candu Worldwide. VMware strategic alliance solution, architect leader with AWS Samir. Great to have you and Daniel Re Myer, principal architect global AWS synergy at VMware. Guys, you guys are, are working together. You're the key players in the re relationship as it rolls out and continues to grow. So welcome to the cube. >>Thank you. Greatly appreciate it. >>Great to have you guys both on, As you know, we've been covering this since 2016 when Pat Geling, then CEO and then then CEO AWS at Andy Chasy did this. It kind of got people by surprise, but it really kind of cleaned out the positioning in the enterprise for the success. OFM workloads in the cloud. VMware's had great success with it since, and you guys have the great partnerships. So this has been like a really strategic, successful partnership. Where are we right now? You know, years later we got this whole inflection point coming. You're starting to see, you know, this idea of higher level services, more performance are coming in at the infrastructure side. More automation, more serverless, I mean, and a, I mean it's just getting better and better every year in the cloud. Kinda a whole nother level. Where are we, Samir? Let's start with you on, on the relationship. >>Yeah, totally. So I mean, there's several things to keep in mind, right? So in 2016, right, that's when the partnership between AWS and VMware was announced, and then less than a year later, that's when we officially launched VMware cloud on aws. Years later, we've been driving innovation, working with our customers, jointly engineering this between AWS and VMware day in, day out. As far as advancing VMware cloud on aws. You know, even if you look at the innovation that takes place with a solution, things have modernized, things have changed, there's been advancements, you know, whether it's security focus, whether it's platform focus, whether it's networking focus, there's been modifications along the way, even storage, right? More recently, one of the things to keep in mind is we're looking to deliver value to our customers together. These are our joint customers. So there's hundreds of VMware and AWS engineers working together on this solution. >>And then factor in even our sales teams, right? We have VMware and AWS sales teams interacting with each other on a constant daily basis. We're working together with our customers at the end of the day too. Then we're looking to even offer and develop jointly engineered solutions specific to VMware cloud on aws, and even with VMware's, other platforms as well. Then the other thing comes down to is where we have dedicated teams around this at both AWS and VMware. So even from solutions architects, even to our sales specialists, even to our account teams, even to specific engineering teams within the organizations, they all come together to drive this innovation forward with VMware cloud on AWS and the jointly engineered solution partnership as well. And then I think one of the key things to keep in mind comes down to we have nearly 600 channel partners that have achieved VMware cloud on AWS service competency. So think about it from the standpoint there's 300 certified or validated technology solutions, they're now available to our customers. So that's even innovation right off the top as well. >>Great stuff. Daniel, I wanna get to you in a second. Upon this principal architect position you have in your title, you're the global a synergy person. Synergy means bringing things together, making it work. Take us through the architecture, because we heard a lot of folks at VMware explore this year, formerly world, talking about how the, the workloads on it has been completely transforming into cloud and hybrid, right? This is where the action is. Where are you? Is your customers taking advantage of that new shift? You got AI ops, you got it. Ops changing a lot, you got a lot more automation edges right around the corner. This is like a complete transformation from where we were just five years ago. What's your thoughts on the >>Relationship? So at at, at first, I would like to emphasize that our collaboration is not just that we have dedicated teams to help our customers get the most and the best benefits out of VMware cloud on aws. We are also enabling US mutually. So AWS learns from us about the VMware technology, where VMware people learn about the AWS technology. We are also enabling our channel partners and we are working together on customer projects. So we have regular assembled globally and also virtually on Slack and the usual suspect tools working together and listening to customers, that's, that's very important. Asking our customers where are their needs? And we are driving the solution into the direction that our customers get the, the best benefits out of VMware cloud on aws. And over the time we, we really have involved the solution. As Samia mentioned, we just added additional storage solutions to VMware cloud on aws. We now have three different instance types that cover a broad range of, of workload. So for example, we just added the I four I host, which is ideally for workloads that require a lot of CPU power, such as you mentioned it, AI workloads. >>Yeah. So I wanna guess just specifically on the customer journey and their transformation. You know, we've been reporting on Silicon angle in the queue in the past couple weeks in a big way that the OPS teams are now the new devs, right? I mean that sounds OP a little bit weird, but operation IT operations is now part of the, a lot more data ops, security writing code composing, you know, with open source, a lot of great things are changing. Can you share specifically what customers are looking for when you say, as you guys come in and assess their needs, what are they doing? What are some of the things that they're doing with VMware on AWS specifically that's a little bit different? Can you share some of and highlights there? >>That, that's a great point because originally VMware and AWS came from very different directions when it comes to speaking people at customers. So for example, aws very developer focused, whereas VMware has a very great footprint in the IT ops area. And usually these are very different, very different teams, groups, different cultures, but it's, it's getting together. However, we always try to address the customers, right? There are customers that want to build up a new application from the scratch and build resiliency, availability, recoverability, scalability into the application. But there are still a lot of customers that say, well we don't have all of the skills to redevelop everything to refactor an application to make it highly available. So we want to have all of that as a service, recoverability as a service, scalability as a service. We want to have this from the infrastructure. That was one of the unique selling points for VMware on premise and now we are bringing this into the cloud. >>Samir, talk about your perspective. I wanna get your thoughts, and not to take a tangent, but we had covered the AWS remar of, actually it was Amazon res machine learning automation, robotics and space. It was really kinda the confluence of industrial IOT software physical. And so when you look at like the IT operations piece becoming more software, you're seeing things about automation, but the skill gap is huge. So you're seeing low code, no code automation, you know, Hey Alexa, deploy a Kubernetes cluster. Yeah, I mean, I mean that's coming, right? So we're seeing this kind of operating automation meets higher level services meets workloads. Can you unpack that and share your opinion on, on what you see there from an Amazon perspective and how it relates to this? >>Yeah, totally. Right. And you know, look at it from the point of view where we said this is a jointly engineered solution, but it's not migrating to one option or the other option, right? It's more or less together. So even with VMware cloud on aws, yes it is utilizing AWS infrastructure, but your environment is connected to that AWS VPC in your AWS account. So if you wanna leverage any of the native AWS services, so any of the 200 plus AWS services, you have that option to do so. So that's gonna give you that power to do certain things, such as, for example, like how you mentioned with iot, even with utilizing Alexa or if there's any other service that you wanna utilize, that's the joining point between both of the offerings. Right off the top though, with digital transformation, right? You, you have to think about where it's not just about the technology, right? There's also where you want to drive growth in the underlying technology. Even in your business leaders are looking to reinvent their business. They're looking to take different steps as far as pursuing a new strategy. Maybe it's a process, maybe it's with the people, the culture, like how you said before, where people are coming in from a different background, right? They may not be used to the cloud, they may not be used to AWS services, but now you have that capability to mesh them together. Okay. Then also, Oh, >>Go ahead, finish >>Your thought. No, no, I was gonna say, what it also comes down to is you need to think about the operating model too, where it is a shift, right? Especially for that VS four admin that's used to their on-premises at environment. Now with VMware cloud on aws, you have that ability to leverage a cloud, but the investment that you made and certain things as far as automation, even with monitoring, even with logging, yeah. You still have that methodology where you can utilize that in VMware cloud on AWS two. >>Danielle, I wanna get your thoughts on this because at at explore and, and, and after the event, now as we prep for Cuban and reinvent coming up the big AWS show, I had a couple conversations with a lot of the VMware customers and operators and it's like hundreds of thousands of, of, of, of users and millions of people talking about and and peaked on VM we're interested in v VMware. The common thread was one's one, one person said, I'm trying to figure out where I'm gonna put my career in the next 10 to 15 years. And they've been very comfortable with VMware in the past, very loyal, and they're kind of talking about, I'm gonna be the next cloud, but there's no like role yet architects, is it Solution architect sre. So you're starting to see the psychology of the operators who now are gonna try to make these career decisions, like how, what am I gonna work on? And it's, and that was kind of fuzzy, but I wanna get your thoughts. How would you talk to that persona about the future of VMware on, say, cloud for instance? What should they be thinking about? What's the opportunity and what's gonna happen? >>So digital transformation definitely is a huge change for many organizations and leaders are perfectly aware of what that means. And that also means in, in to to some extent, concerns with your existing employees. Concerns about do I have to relearn everything? Do I have to acquire new skills? And, and trainings is everything worthless I learned over the last 15 years of my career? And the, the answer is to make digital transformation a success. We need not just to talk about technology, but also about process people and culture. And this is where VMware really can help because if you are applying VMware cloud on a, on AWS to your infrastructure, to your existing on-premise infrastructure, you do not need to change many things. You can use the same tools and skills, you can manage your virtual machines as you did in your on-premise environment. You can use the same managing and monitoring tools. If you have written, and many customers did this, if you have developed hundreds of, of scripts that automate tasks and if you know how to troubleshoot things, then you can use all of that in VMware cloud on aws. And that gives not just leaders, but but also the architects at customers, the operators at customers, the confidence in, in such a complex project, >>The consistency, very key point, gives them the confidence to go and, and then now that once they're confident they can start committing themselves to new things. Samir, you're reacting to this because you know, on your side you've got higher level services, you got more performance at the hardware level. I mean, lot improvement. So, okay, nothing's changed. I can still run my job now I got goodness on the other side. What's the upside? What's in it for the, for the, for the customer there? >>Yeah, so I think what it comes down to is they've already been so used to or entrenched with that VMware admin mentality, right? But now extending that to the cloud, that's where now you have that bridge between VMware cloud on AWS to bridge that VMware knowledge with that AWS knowledge. So I will look at it from the point of view where now one has that capability and that ability to just learn about the cloud, but if they're comfortable with certain aspects, no one's saying you have to change anything. You can still leverage that, right? But now if you wanna utilize any other AWS service in conjunction with that VM that resides maybe on premises or even in VMware cloud on aws, you have that option to do so. So think about it where you have that ability to be someone who's curious and wants to learn. And then if you wanna expand on the skills, you certainly have that capability to do so. >>Great stuff. I love, love that. Now that we're peeking behind the curtain here, I'd love to have you guys explain, cuz people wanna know what's goes on in behind the scenes. How does innovation get happen? How does it happen with the relationship? Can you take us through a day in the life of kind of what goes on to make innovation happen with the joint partnership? You guys just have a zoom meeting, Do you guys fly out, you write go do you ship thing? I mean I'm making it up, but you get the idea, what's the, what's, how does it work? What's going on behind the scenes? >>So we hope to get more frequently together in person, but of course we had some difficulties over the last two to three years. So we are very used to zoom conferences and and Slack meetings. You always have to have the time difference in mind if we are working globally together. But what we try, for example, we have reg regular assembled now also in person geo based. So for emia, for the Americas, for aj. And we are bringing up interesting customer situations, architectural bits and pieces together. We are discussing it always to share and to contribute to our community. >>What's interesting, you know, as, as events are coming back to here, before you get, you weigh in, I'll comment, as the cube's been going back out to events, we are hearing comments like what, what pandemic we were more productive in the pandemic. I mean, developers know how to work remotely and they've been on all the tools there, but then they get in person, they're happy to see people, but there's no one's, no one's really missed the beat. I mean it seems to be very productive, you know, workflow, not a lot of disruption. More if anything, productivity gains. >>Agreed, right? I think one of the key things to keep in mind is, you know, even if you look at AWS's and even Amazon's leadership principles, right? Customer obsession, that's key. VMware is carrying that forward as well. Where we are working with our customers, like how Daniel said met earlier, right? We might have meetings at different time zones, maybe it's in person, maybe it's virtual, but together we're working to listen to our customers. You know, we're taking and capturing that feedback to drive innovation and VMware cloud on AWS as well. But one of the key things to keep in mind is yes, there have been, there has been the pandemic, we might have been disconnected to a certain extent, but together through technology we've been able to still communicate work with our customers. Even with VMware in between, with AWS and whatnot. We had that flexibility to innovate and continue that innovation. So even if you look at it from the point of view, right? VMware cloud on AWS outposts, that was something that customers have been asking for. We've been been able to leverage the feedback and then continue to drive innovation even around VMware cloud on AWS outposts. So even with the on premises environment, if you're looking to handle maybe data sovereignty or compliance needs, maybe you have low latency requirements, that's where certain advancements come into play, right? So the key thing is always to maintain that communication track. >>And our last segment we did here on the, on this showcase, we listed the accomplishments and they were pretty significant. I mean go, you got the global rollouts of the relationship. It's just really been interesting and, and people can reference that. We won't get into it here, but I will ask you guys to comment on, as you guys continue to evolve the relationship, what's in it for the customer? What can they expect next? Cuz again, I think right now we're in at a, an inflection point more than ever. What can people expect from the relationship and what's coming up with reinvent? Can you share a little bit of kind of what's coming down the pike? >>So one of the most important things we have announced this year, and we will continue to evolve into that direction, is independent scale of storage. That absolutely was one of the most important items customer asked us for over the last years. Whenever, whenever you are requiring additional storage to host your virtual machines, you usually in VMware cloud on aws, you have to add additional notes. Now we have three different note types with different ratios of compute, storage and memory. But if you only require additional storage, you always have to get also additional compute and memory and you have to pay. And now with two solutions which offer choice for the customers, like FS six one, NetApp onap, and VMware cloud Flex Storage, you now have two cost effective opportunities to add storage to your virtual machines. And that offers opportunities for other instance types maybe that don't have local storage. We are also very, very keen looking forward to announcements, exciting announcements at the upcoming events. >>Samir, what's your, what's your reaction take on the, on what's coming down on your side? >>Yeah, I think one of the key things to keep in mind is, you know, we're looking to help our customers be agile and even scale with their needs, right? So with VMware cloud on aws, that's one of the key things that comes to mind, right? There are gonna be announcements, innovations and whatnot with outcoming events. But together we're able to leverage that to advance VMware cloud on AWS to Daniel's point storage, for example, even with host offerings. And then even with decoupling storage from compute and memory, right now you have the flexibility where you can do all of that. So to look at it from the standpoint where now with 21 regions where we have VMware cloud on AWS available as well, where customers can utilize that as needed when needed, right? So it comes down to, you know, transformation will be there. Yes, there's gonna be maybe where workloads have to be adapted where they're utilizing certain AWS services, but you have that flexibility and option to do so. And I think with the continuing events that's gonna give us the options to even advance our own services together. >>Well you guys are in the middle of it, you're in the trenches, you're making things happen, you've got a team of people working together. My final question is really more of a kind of a current situation, kind of future evolutionary thing that you haven't seen this before. I wanna get both of your reaction to it. And we've been bringing this up in, in the open conversations on the cube is in the old days it was going back this generation, you had ecosystems, you had VMware had an ecosystem they did best, had an ecosystem. You know, we have a product, you have a product, biz dev deals happen, people sign relationships and they do business together and they, they sell to each other's products or do some stuff. Now it's more about architecture cuz we're now in a distributed large scale environment where the role of ecosystems are intertwining. >>And this, you guys are in the middle of two big ecosystems. You mentioned channel partners, you both have a lot of partners on both sides. They come together. So you have this now almost a three dimensional or multidimensional ecosystem, you know, interplay. What's your thoughts on this? And, and, and because it's about the architecture, integration is a value, not so much. Innovation is only, you gotta do innovation, but when you do innovation, you gotta integrate it, you gotta connect it. So what is, how do you guys see this as a, as an architectural thing, start to see more technical business deals? >>So we are, we are removing dependencies from individual ecosystems and from individual vendors. So a customer no longer has to decide for one vendor and then it is a very expensive and high effort project to move away from that vendor, which ties customers even, even closer to specific vendors. We are removing these obstacles. So with VMware cloud on aws moving to the cloud, firstly it's, it's not a dead end. If you decide at one point in time because of latency requirements or maybe it's some compliance requirements, you need to move back into on-premise. You can do this if you decide you want to stay with some of your services on premise and just run a couple of dedicated services in the cloud, you can do this and you can mana manage it through a single pane of glass. That's quite important. So cloud is no longer a dead and it's no longer a binary decision, whether it's on premise or the cloud. It it is the cloud. And the second thing is you can choose the best of both works, right? If you are migrating virtual machines that have been running in your on-premise environment to VMware cloud on aws, by the way, in a very, very fast cost effective and safe way, then you can enrich later on enrich these virtual machines with services that are offered by aws. More than 200 different services ranging from object based storage, load balancing and so on. So it's an endless, endless possibility. >>We, we call that super cloud in, in a, in a way that we be generically defining it where everyone's innovating, but yet there's some common services. But the differentiation comes from innovation where the lock in is the value, not some spec, right? Samir, this is gonna where cloud is right now, you guys are, are not commodity. Amazon's completely differentiating, but there's some commodity things. Having got storage, you got compute, but then you got now advances in all areas. But partners innovate with you on their terms. Absolutely. And everybody wins. >>Yeah. And a hundred percent agree with you. I think one of the key things, you know, as Daniel mentioned before, is where it it, it's a cross education where there might be someone who's more proficient on the cloud side with aws, maybe more proficient with the viewers technology, but then for partners, right? They bridge that gap as well where they come in and they might have a specific niche or expertise where their background, where they can help our customers go through that transformation. So then that comes down to, hey, maybe I don't know how to connect to the cloud. Maybe I don't know what the networking constructs are. Maybe I can leverage that partner. That's one aspect to go about it. Now maybe you migrated that workload to VMware cloud on aws. Maybe you wanna leverage any of the native AWS services or even just off the top 200 plus AWS services, right? But it comes down to that skill, right? So again, solutions architecture at the back of, back of the day, end of the day, what it comes down to is being able to utilize the best of both worlds. That's what we're giving our customers at the end of the >>Day. I mean, I just think it's, it's a, it's a refactoring and innovation opportunity at all levels. I think now more than ever, you can take advantage of each other's ecosystems and partners and technologies and change how things get done with keeping the consistency. I mean, Daniel, you nailed that, right? I mean, you don't have to do anything. You still run the fear, the way you working on it and now do new things. This is kind of a cultural shift. >>Yeah, absolutely. And if, if you look, not every, not every customer, not every organization has the resources to refactor and re-platform everything. And we gave, we give them a very simple and easy way to move workloads to the cloud. Simply run them and at the same time they can free up resources to develop new innovations and, and grow their business. >>Awesome. Samir, thank you for coming on. Danielle, thank you for coming to Germany, Octoberfest, I know it's evening over there, your weekend's here. And thank you for spending the time. Samir final give you the final word, AWS reinvents coming up. Preparing. We're gonna have an exclusive with Adam, but Fry, we do a curtain raise, a dual preview. What's coming down on your side with the relationship and what can we expect to hear about what you got going on at reinvent this year? The big show? >>Yeah, so I think, you know, Daniel hit upon some of the key points, but what I will say is we do have, for example, specific sessions, both that VMware's driving and then also that AWS is driving. We do have even where we have what I call a chalk talks. So I would say, and then even with workshops, right? So even with the customers, the attendees who are there, whatnot, if they're looking for to sit and listen to a session, yes that's there. But if they wanna be hands on, that is also there too. So personally for me as an IT background, you know, been in CIS admin world and whatnot, being hands on, that's one of the key things that I personally am looking forward. But I think that's one of the key ways just to learn and get familiar with the technology. Yeah, >>Reinvents an amazing show for the in person. You guys nail it every year. We'll have three sets this year at the cube. It's becoming popular. We more and more content. You guys got live streams going on, a lot of content, a lot of media, so thanks, thanks for sharing that. Samir Daniel, thank you for coming on on this part of the showcase episode of really the customer successes with VMware Cloud Ons, really accelerating business transformation withs and VMware. I'm John Fur with the cube, thanks for watching. Hello everyone. Welcome to this cube showcase, accelerating business transformation with VMware cloud on it's a solution innovation conversation with two great guests, Fred and VP of commercial services at aws and NA Ryan Bard, who's the VP and general manager of cloud solutions at VMware. Gentlemen, thanks for joining me on this showcase. >>Great to be here. >>Hey, thanks for having us on. It's a great topic. You know, we, we've been covering this VMware cloud on abus since, since the launch going back and it's been amazing to watch the evolution from people saying, Oh, it's the worst thing I've ever seen. It's what's this mean? And depress work were, we're kind of not really on board with kind of the vision, but as it played out as you guys had announced together, it did work out great for VMware. It did work out great for a D and it continues two years later and I want just get an update from you guys on where you guys see this has been going. I'll see multiple years. Where is the evolution of the solution as we are right now coming off VMware explorer just recently and going in to reinvent, which is only a couple weeks away, feels like tomorrow. But you know, as we prepare a lot going on, where are we with the evolution of the solution? >>I mean, first thing I wanna say is, you know, PBO 2016 was a someon moment and the history of it, right? When Pat Gelsinger and Andy Jessey came together to announce this and I think John, you were there at the time I was there, it was a great, great moment. We launched the solution in 2017, the year after that at VM Word back when we called it Word, I think we have gone from strength to strength. One of the things that has really mattered to us is we have learned froms also in the processes, this notion of working backwards. So we really, really focused on customer feedback as we build a service offering now five years old, pretty remarkable journey. You know, in the first years we tried to get across all the regions, you know, that was a big focus because there was so much demand for it. >>In the second year we started going really on enterprise grade features. We invented this pretty awesome feature called Stretch clusters, where you could stretch a vSphere cluster using VSA and NSX across two AZs in the same region. Pretty phenomenal four nine s availability that applications start started to get with that particular feature. And we kept moving forward all kinds of integration with AWS direct connect transit gateways with our own advanced networking capabilities. You know, along the way, disaster recovery, we punched out two, two new services just focused on that. And then more recently we launched our outposts partnership. We were up on stage at Reinvent, again with Pat Andy announcing AWS outposts and the VMware flavor of that VMware cloud and AWS outposts. I think it's been significant growth in our federal sector as well with our federal and high certification more recently. So all in all, we are super excited. We're five years old. The customer momentum is really, really strong and we are scaling the service massively across all geos and industries. >>That's great, great update. And I think one of the things that you mentioned was how the advantages you guys got from that relationship. And, and this has kind of been the theme for AWS since I can remember from day one. Fred, you guys do the heavy lifting as as, as you always say for the customers here, VMware comes on board, takes advantage of the AWS and kind of just doesn't miss a beat, continues to move their workloads that everyone's using, you know, vSphere and these are, these are big workloads on aws. What's the AWS perspective on this? How do you see it? >>Yeah, it's pretty fascinating to watch how fast customers can actually transform and move when you take the, the skill set that they're familiar with and the advanced capabilities that they've been using on Preem and then overlay it on top of the AWS infrastructure that's, that's evolving quickly and, and building out new hardware and new instances we'll talk about. But that combined experience between both of us on a jointly engineered solution to bring the best security and the best features that really matter for those workloads drive a lot of efficiency and speed for the, for the customer. So it's been well received and the partnership is stronger than ever from an engineering standpoint, from a business standpoint. And obviously it's been very interesting to look at just how we stay day one in terms of looking at new features and work and, and responding to what customers want. So pretty, pretty excited about just seeing the transformation and the speed that which customers can move to bmc. Yeah, >>That's what great value publish. We've been talking about that in context too. Anyone building on top of the cloud, they can have their own supercloud as we call it. If you take advantage of all the CapEx and and investment Amazon's made and AWS has made and, and and continues to make in performance IAS and pass all great stuff. I have to ask you guys both as you guys see this going to the next level, what are some of the differentiations you see around the service compared to other options on the market? What makes it different? What's the combination? You mentioned jointly engineered, what are some of the key differentiators of the service compared to others? >>Yeah, I think one of the key things Fred talked about is this jointly engineered notion right from day one. We were the earlier doctors of AWS Nitro platform, right? The reinvention of E two back five years ago. And so we have been, you know, having a very, very strong engineering partnership at that level. I think from a VMware customer standpoint, you get the full software defined data center or compute storage networking on EC two, bare metal across all regions. You can scale that elastically up and down. It's pretty phenomenal just having that consistency globally, right on aws EC two global regions. Now the other thing that's a real differentiator for us that customers tell us about is this whole notion of a managed service, right? And this was somewhat new to VMware, but we took away the pain of this undifferentiated heavy lifting where customers had to provision rack, stack hardware, configure the software on top, and then upgrade the software and the security batches on top. >>So we took, took away all of that pain as customers transitioned to VMware cloud and aws. In fact, my favorite story from last year when we were all going through the lock for j debacle industry was just going through that, right? Favorite proof point from customers was before they put even race this issue to us, we sent them a notification saying we already patched all of your systems, no action from you. The customers were super thrilled. I mean these are large banks, many other customers around the world, super thrilled they had to take no action, but a pretty incredible industry challenge that we were all facing. >>Nora, that's a great, so that's a great point. You know, the whole managed service piece brings up the security, you kind of teasing at it, but you know, there's always vulnerabilities that emerge when you are doing complex logic. And as you grow your solutions, there's more bits. You know, Fred, we were commenting before we came on camera, there's more bits than ever before and, and at at the physics layer too, as well as the software. So you never know when there's gonna be a zero day vulnerability out there. Just, it happens. We saw one with fornet this week, this came outta the woodwork. But moving fast on those patches, it's huge. This brings up the whole support angle. I wanted to ask you about how you guys are doing that as well, because to me we see the value when we, when we talk to customers on the cube about this, you know, it was a real, real easy understanding of how, what the cloud means to them with VMware now with the aws. But the question that comes up that we wanna get more clarity on is how do you guys handle support together? >>Well, what's interesting about this is that it's, it's done mutually. We have dedicated support teams on both sides that work together pretty seamlessly to make sure that whether there's a issue at any layer, including all the way up into the app layer, as you think about some of the other workloads like sap, we'll go end to end and make sure that we support the customer regardless of where the particular issue might be for them. And on top of that, we look at where, where we're improving reliability in, in as a first order of, of principle between both companies. So from an availability and reliability standpoint, it's, it's top of mind and no matter where the particular item might land, we're gonna go help the customer resolve. That works really well >>On the VMware side. What's been the feedback there? What's the, what are some of the updates? >>Yeah, I think, look, I mean, VMware owns and operates the service, but we have a phenomenal backend relationship with aws. Customers call VMware for the service for any issues and, and then we have a awesome relationship with AWS on the backend for support issues or any hardware issues. The BASKE management that we jointly do, right? All of the hard problems that customers don't have to worry about. I think on the front end, we also have a really good group of solution architects across the companies that help to really explain the solution. Do complex things like cloud migration, which is much, much easier with VMware cloud aws, you know, we are presenting that easy button to the public cloud in many ways. And so we have a whole technical audience across the two companies that are working with customers every single day. >>You know, you had mentioned, I've got a list here, some of the innovations the, you mentioned the stretch clustering, you know, getting the GOs working, Advanced network, disaster recovery, you know, fed, Fed ramp, public sector certifications, outposts, all good. You guys are checking the boxes every year. You got a good, good accomplishments list there on the VMware AWS side here in this relationship. The question that I'm interested in is what's next? What recent innovations are you doing? Are you making investments in what's on the lists this year? What items will be next year? How do you see the, the new things, the list of accomplishments, people wanna know what's next. They don't wanna see stagnant growth here, they wanna see more action, you know, as as cloud kind of continues to scale and modern applications cloud native, you're seeing more and more containers, more and more, you know, more CF C I C D pipe pipelining with with modern apps, put more pressure on the system. What's new, what's the new innovations? >>Absolutely. And I think as a five yearold service offering innovation is top of mind for us every single day. So just to call out a few recent innovations that we announced in San Francisco at VMware Explorer. First of all, our new platform i four I dot metal, it's isolate based, it's pretty awesome. It's the latest and greatest, all the speeds and feeds that we would expect from VMware and aws. At this point in our relationship. We announced two different storage options. This notion of working from customer feedback, allowing customers even more price reductions, really take off that storage and park it externally, right? And you know, separate that from compute. So two different storage offerings there. One is with AWS Fsx, with NetApp on tap, which brings in our NetApp partnership as well into the equation and really get that NetApp based, really excited about this offering as well. >>And the second storage offering for VMware cloud Flex Storage, VMware's own managed storage offering. Beyond that, we have done a lot of other innovations as well. I really wanted to talk about VMware cloud Flex Compute, where previously customers could only scale by hosts and a host is 36 to 48 cores, give or take. But with VMware cloud Flex Compute, we are now allowing this notion of a resource defined compute model where customers can just get exactly the V C P memory and storage that maps to the applications, however small they might be. So this notion of granularity is really a big innovation that that we are launching in the market this year. And then last but not least, talk about ransomware. Of course it's a hot topic in industry. We are seeing many, many customers ask for this. We are happy to announce a new ransomware recovery with our VMware cloud DR solution. >>A lot of innovation there and the way we are able to do machine learning and make sure the workloads that are covered from snapshots and backups are actually safe to use. So there's a lot of differentiation on that front as well. A lot of networking innovations with Project Knot star for ability to have layer flow through layer seven, you know, new SaaS services in that area as well. Keep in mind that the service already supports managed Kubernetes for containers. It's built in to the same clusters that have virtual machines. And so this notion of a single service with a great TCO for VMs and containers and sort of at the heart of our office, >>The networking side certainly is a hot area to keep innovating on. Every year it's the same, same conversation, get better, faster networking, more, more options there. The flex computes. Interesting. If you don't mind me getting a quick clarification, could you explain the Drew screen resource defined versus hardware defined? Because this is kind of what we had saw at Explore coming out, that notion of resource defined versus hardware defined. What's the, what does that mean? >>Yeah, I mean I think we have been super successful in this hardware defined notion. We we're scaling by the hardware unit that we present as software defined data centers, right? And so that's been super successful. But we, you know, customers wanted more, especially customers in different parts of the world wanted to start even smaller and grow even more incrementally, right? Lower their costs even more. And so this is the part where resource defined starts to be very, very interesting as a way to think about, you know, here's my bag of resources exactly based on what the customers request for fiber machines, five containers, its size exactly for that. And then as utilization grows, we elastically behind the scenes, we're able to grow it through policies. So that's a whole different dimension. It's a whole different service offering that adds value and customers are comfortable. They can go from one to the other, they can go back to that post based model if they so choose to. And there's a jump off point across these two different economic models. >>It's kind of cloud of flexibility right there. I like the name Fred. Let's get into some of the examples of customers, if you don't mind. Let's get into some of the ex, we have some time. I wanna unpack a little bit of what's going on with the customer deployments. One of the things we've heard again on the cube is from customers is they like the clarity of the relationship, they love the cloud positioning of it. And then what happens is they lift and shift the workloads and it's like, feels great. It's just like we're running VMware on AWS and then they would start consuming higher level services, kind of that adoption next level happens and because it it's in the cloud, so, So can you guys take us through some recent examples of customer wins or deployments where they're using VMware cloud on AWS on getting started, and then how do they progress once they're there? How does it evolve? Can you just walk us through a couple of use cases? >>Sure. There's a, well there's a couple. One, it's pretty interesting that, you know, like you said, as there's more and more bits you need better and better hardware and networking. And we're super excited about the I four and the capabilities there in terms of doubling and or tripling what we're doing around a lower variability on latency and just improving all the speeds. But what customers are doing with it, like the college in New Jersey, they're accelerating their deployment on a, on onboarding over like 7,400 students over a six to eight month period. And they've really realized a ton of savings. But what's interesting is where and how they can actually grow onto additional native services too. So connectivity to any other services is available as they start to move and migrate into this. The, the options there obviously are tied to all the innovation that we have across any services, whether it's containerized and with what they're doing with Tanu or with any other container and or services within aws. >>So there's, there's some pretty interesting scenarios where that data and or the processing, which is moved quickly with full compliance, whether it's in like healthcare or regulatory business is, is allowed to then consume and use things, for example, with tech extract or any other really cool service that has, you know, monthly and quarterly innovations. So there's things that you just can't, could not do before that are coming out and saving customers money and building innovative applications on top of their, their current app base in, in a rapid fashion. So pretty excited about it. There's a lot of examples. I think I probably don't have time to go into too, too many here. Yeah. But that's actually the best part is listening to customers and seeing how many net new services and new applications are they actually building on top of this platform. >>Nora, what's your perspective from the VMware sy? So, you know, you guys have now a lot of headroom to offer customers with Amazon's, you know, higher level services and or whatever's homegrown where's being rolled out? Cuz you now have a lot of hybrid too, so, so what's your, what's your take on what, what's happening in with customers? >>I mean, it's been phenomenal, the, the customer adoption of this and you know, banks and many other highly sensitive verticals are running production grade applications, tier one applications on the service over the last five years. And so, you know, I have a couple of really good examples. S and p Global is one of my favorite examples. Large bank, they merge with IHS market, big sort of conglomeration. Now both customers were using VMware cloud and AWS in different ways. And with the, with the use case, one of their use cases was how do I just respond to these global opportunities without having to invest in physical data centers? And then how do I migrate and consolidate all my data centers across the global, which there were many. And so one specific example for this company was how they migrated thousand 1000 workloads to VMware cloud AWS in just six weeks. Pretty phenomenal. If you think about everything that goes into a cloud migration process, people process technology and the beauty of the technology going from VMware point A to VMware point B, the the lowest cost, lowest risk approach to adopting VMware, VMware cloud, and aws. So that's, you know, one of my favorite examples. There are many other examples across other verticals that we continue to see. The good thing is we are seeing rapid expansion across the globe that constantly entering new markets with the limited number of regions and progressing our roadmap there. >>Yeah, it's great to see, I mean the data center migrations go from months, many, many months to weeks. It's interesting to see some of those success stories. So congratulations. One >>Of other, one of the other interesting fascinating benefits is the sustainability improvement in terms of being green. So the efficiency gains that we have both in current generation and new generation processors and everything that we're doing to make sure that when a customer can be elastic, they're also saving power, which is really critical in a lot of regions worldwide at this point in time. They're, they're seeing those benefits. If you're running really inefficiently in your own data center, that is just a, not a great use of power. So the actual calculators and the benefits to these workloads is, are pretty phenomenal just in being more green, which I like. We just all need to do our part there. And, and this is a big part of it here. >>It's a huge, it's a huge point about the sustainability. Fred, I'm glad you called that out. The other one I would say is supply chain issues. Another one you see that constrains, I can't buy hardware. And the third one is really obvious, but no one really talks about it. It's security, right? I mean, I remember interviewing Stephen Schmidt with that AWS and many years ago, this is like 2013, and you know, at that time people were saying the cloud's not secure. And he's like, listen, it's more secure in the cloud on premise. And if you look at the security breaches, it's all about the on-premise data center vulnerabilities, not so much hardware. So there's a lot you gotta to stay current on, on the isolation there is is hard. So I think, I think the security and supply chain, Fred is, is another one. Do you agree? >>I I absolutely agree. It's, it's hard to manage supply chain nowadays. We put a lot of effort into that and I think we have a great ability to forecast and make sure that we can lean in and, and have the resources that are available and run them, run them more efficiently. Yeah, and then like you said on the security point, security is job one. It is, it is the only P one. And if you think of how we build our infrastructure from Nitro all the way up and how we respond and work with our partners and our customers, there's nothing more important. >>And naron your point earlier about the managed service patching and being on top of things, it's really gonna get better. All right, final question. I really wanna thank you for your time on this showcase. It's really been a great conversation. Fred, you had made a comment earlier. I wanna kind of end with kind of a curve ball and put you eyes on the spot. We're talking about a modern, a new modern shift. It's another, we're seeing another inflection point, we've been documenting it, it's almost like cloud hitting another inflection point with application and open source growth significantly at the app layer. Continue to put a lot of pressure and, and innovation in the infrastructure side. So the question is for you guys each to answer is what's the same and what's different in today's market? So it's kind of like we want more of the same here, but also things have changed radically and better here. What are the, what's, what's changed for the better and where, what's still the same kind of thing hanging around that people are focused on? Can you share your perspective? >>I'll, I'll, I'll, I'll tackle it. You know, businesses are complex and they're often unique that that's the same. What's changed is how fast you can innovate. The ability to combine manage services and new innovative services and build new applications is so much faster today. Leveraging world class hardware that you don't have to worry about that's elastic. You, you could not do that even five, 10 years ago to the degree you can today, especially with innovation. So innovation is accelerating at a, at a rate that most people can't even comprehend and understand the, the set of services that are available to them. It's really fascinating to see what a one pizza team of of engineers can go actually develop in a week. It is phenomenal. So super excited about this space and it's only gonna continue to accelerate that. That's my take. All right. >>You got a lot of platform to compete on with, got a lot to build on then you're Ryan, your side, What's your, what's your answer to that question? >>I think we are seeing a lot of innovation with new applications that customers are constant. I think what we see is this whole notion of how do you go from desktop to production to the secure supply chain and how can we truly, you know, build on the agility that developers desire and build all the security and the pipelines to energize that motor production quickly and efficiently. I think we, we are seeing, you know, we are at the very start of that sort of of journey. Of course we have invested in Kubernetes the means to an end, but there's so much more beyond that's happening in industry. And I think we're at the very, very beginning of this transformations, enterprise transformation that many of our customers are going through and we are inherently part of it. >>Yeah. Well gentlemen, I really appreciate that we're seeing the same thing. It's more the same here on, you know, solving these complexities with distractions. Whether it's, you know, higher level services with large scale infrastructure at, at your fingertips. Infrastructures, code, infrastructure to be provisioned, serverless, all the good stuff happen in Fred with AWS on your side. And we're seeing customers resonate with this idea of being an operator, again, being a cloud operator and developer. So the developer ops is kind of, DevOps is kind of changing too. So all for the better. Thank you for spending the time and we're seeing again, that traction with the VMware customer base and of us getting, getting along great together. So thanks for sharing your perspectives, >>I appreciate it. Thank you so >>Much. Okay, thank you John. Okay, this is the Cube and AWS VMware showcase, accelerating business transformation. VMware cloud on aws, jointly engineered solution, bringing innovation to the VMware customer base, going to the cloud and beyond. I'm John Fur, your host. Thanks for watching. Hello everyone. Welcome to the special cube presentation of accelerating business transformation on vmc on aws. I'm John Furrier, host of the Cube. We have dawan director of global sales and go to market for VMware cloud on adb. This is a great showcase and should be a lot of fun. Ashish, thanks for coming on. >>Hi John. Thank you so much. >>So VMware cloud on AWS has been well documented as this big success for VMware and aws. As customers move their workloads into the cloud, IT operations of VMware customers has signaling a lot of change. This is changing the landscape globally is on cloud migration and beyond. What's your take on this? Can you open this up with the most important story around VMC on aws? >>Yes, John. The most important thing for our customers today is the how they can safely and swiftly move their ID infrastructure and applications through cloud. Now, VMware cloud AWS is a service that allows all vSphere based workloads to move to cloud safely, swiftly and reliably. Banks can move their core, core banking platforms, insurance companies move their core insurance platforms, telcos move their goss, bss, PLA platforms, government organizations are moving their citizen engagement platforms using VMC on aws because this is one platform that allows you to move it, move their VMware based platforms very fast. Migrations can happen in a matter of days instead of months. Extremely securely. It's a VMware manage service. It's very secure and highly reliably. It gets the, the reliability of the underlyings infrastructure along with it. So win-win from our customers perspective. >>You know, we reported on this big news in 2016 with Andy Chas, the, and Pat Geling at the time, a lot of people said it was a bad deal. It turned out to be a great deal because not only could VMware customers actually have a cloud migrate to the cloud, do it safely, which was their number one concern. They didn't want to have disruption to their operations, but also position themselves for what's beyond just shifting to the cloud. So I have to ask you, since you got the finger on the pulse here, what are we seeing in the market when it comes to migrating and modern modernizing in the cloud? Because that's the next step. They go to the cloud, you guys have done that, doing it, then they go, I gotta modernize, which means kind of upgrading or refactoring. What's your take on that? >>Yeah, absolutely. Look, the first step is to help our customers assess their infrastructure and licensing and entire ID operations. Once we've done the assessment, we then create their migration plans. A lot of our customers are at that inflection point. They're, they're looking at their real estate, ex data center, real estate. They're looking at their contracts with colocation vendors. They really want to exit their data centers, right? And VMware cloud and AWS is a perfect solution for customers who wanna exit their data centers, migrate these applications onto the AWS platform using VMC on aws, get rid of additional real estate overheads, power overheads, be socially and environmentally conscious by doing that as well, right? So that's the migration story, but to your point, it doesn't end there, right? Modernization is a critical aspect of the entire customer journey as as well customers, once they've migrated their ID applications and infrastructure on cloud get access to all the modernization services that AWS has. They can correct easily to our data lake services, to our AIML services, to custom databases, right? They can decide which applications they want to keep and which applications they want to refactor. They want to take decisions on containerization, make decisions on service computing once they've come to the cloud. But the most important thing is to take that first step. You know, exit data centers, come to AWS using vmc or aws, and then a whole host of modernization options available to them. >>Yeah, I gotta say, we had this right on this, on this story, because you just pointed out a big thing, which was first order of business is to make sure to leverage the on-prem investments that those customers made and then migrate to the cloud where they can maintain their applications, their data, their infrastructure operations that they're used to, and then be in position to start getting modern. So I have to ask you, how are you guys specifically, or how is VMware cloud on s addressing these needs of the customers? Because what happens next is something that needs to happen faster. And sometimes the skills might not be there because if they're running old school, IT ops now they gotta come in and jump in. They're gonna use a data cloud, they're gonna want to use all kinds of machine learning, and there's a lot of great goodness going on above the stack there. So as you move with the higher level services, you know, it's a no brainer, obviously, but they're not, it's not yesterday's higher level services in the cloud. So how are, how is this being addressed? >>Absolutely. I think you hit up on a very important point, and that is skills, right? When our customers are operating, some of the most critical applications I just mentioned, core banking, core insurance, et cetera, they're most of the core applications that our customers have across industries, like even, even large scale ERP systems, they're actually sitting on VMware's vSphere platform right now. When the customer wants to migrate these to cloud, one of the key bottlenecks they face is skill sets. They have the trained manpower for these core applications, but for these high level services, they may not, right? So the first order of business is to help them ease this migration pain as much as possible by not wanting them to, to upscale immediately. And we VMware cloud and AWS exactly does that. I mean, you don't have to do anything. You don't have to create new skill set for doing this, right? Their existing skill sets suffice, but at the same time, it gives them that, that leeway to build that skills roadmap for their team. DNS is invested in that, right? Yes. We want to help them build those skills in the high level services, be it aml, be it, be it i t be it data lake and analytics. We want to invest in them, and we help our customers through that. So that ultimately the ultimate goal of making them drop data is, is, is a front and center. >>I wanna get into some of the use cases and success stories, but I want to just reiterate, hit back your point on the skill thing. Because if you look at what you guys have done at aws, you've essentially, and Andy Chassey used to talk about this all the time when I would interview him, and now last year Adam was saying the same thing. You guys do all the heavy lifting, but if you're a VMware customer user or operator, you are used to things. You don't have to be relearn to be a cloud architect. Now you're already in the game. So this is like almost like a instant path to cloud skills for the VMware. There's hundreds of thousands of, of VMware architects and operators that now instantly become cloud architects, literally overnight. Can you respond to that? Do you agree with that? And then give an example. >>Yes, absolutely. You know, if you have skills on the VMware platform, you know, know, migrating to AWS using via by cloud and AWS is absolutely possible. You don't have to really change the skills. The operations are exactly the same. The management systems are exactly the same. So you don't really have to change anything but the advantages that you get access to all the other AWS services. So you are instantly able to integrate with other AWS services and you become a cloud architect immediately, right? You are able to solve some of the critical problems that your underlying IT infrastructure has immediately using this. And I think that's a great value proposition for our customers to use this service. >>And just one more point, I want just get into something that's really kind of inside baseball or nuanced VMC or VMware cloud on AWS means something. Could you take a minute to explain what on AWS means? Just because you're like hosting and using Amazon as a, as a work workload? Being on AWS means something specific in your world, being VMC on AWS mean? >>Yes. This is a great question, by the way, You know, on AWS means that, you know, VMware's vse platform is, is a, is an iconic enterprise virtualization software, you know, a disproportionately high market share across industries. So when we wanted to create a cloud product along with them, obviously our aim was for them, for the, for this platform to have the goodness of the AWS underlying infrastructure, right? And, and therefore, when we created this VMware cloud solution, it it literally use the AWS platform under the eighth, right? And that's why it's called a VMs VMware cloud on AWS using, using the, the, the wide portfolio of our regions across the world and the strength of the underlying infrastructure, the reliability and, and, and sustainability that it offers. And therefore this product is called VMC on aws. >>It's a distinction I think is worth noting, and it does reflect engineering and some levels of integration that go well beyond just having a SaaS app and, and basically platform as a service or past services. So I just wanna make sure that now super cloud, we'll talk about that a little bit in another interview, but I gotta get one more question in before we get into the use cases and customer success stories is in, in most of the VM world, VMware world, in that IT world, it used to, when you heard migration, people would go, Oh my God, that's gonna take months. And when I hear about moving stuff around and doing cloud native, the first reaction people might have is complexity. So two questions for you before we move on to the next talk. Track complexity. How are you addressing the complexity issue and how long these migrations take? Is it easy? Is it it hard? I mean, you know, the knee jerk reaction is month, You're very used to that. If they're dealing with Oracle or other old school vendors, like, they're, like the old guard would be like, takes a year to move stuff around. So can you comment on complexity and speed? >>Yeah. So the first, first thing is complexity. And you know, what makes what makes anything complex is if you're, if you're required to acquire new skill sets or you've gotta, if you're required to manage something differently, and as far as VMware cloud and AWS on both these aspects, you don't have to do anything, right? You don't have to acquire new skill sets. Your existing idea operation skill sets on, on VMware's platforms are absolutely fine and you don't have to manage it any differently like, than what you're managing your, your ID infrastructure today. So in both these aspects, it's exactly the same and therefore it is absolutely not complex as far as, as far as, as far as we cloud and AWS is concerned. And the other thing is speed. This is where the huge differentiation is. You have seen that, you know, large banks and large telcos have now moved their workloads, you know, literally in days instead of months. >>Because because of VMware cloud and aws, a lot of time customers come to us with specific deadlines because they want to exit their data centers on a particular date. And what happens, VMware cloud and AWS is called upon to do that migration, right? So speed is absolutely critical. The reason is also exactly the same because you are using the exactly the same platform, the same management systems, people are available to you, you're able to migrate quickly, right? I would just reference recently we got an award from President Zelensky of Ukraine for, you know, migrating their entire ID digital infrastructure and, and that that happened because they were using VMware cloud database and happened very swiftly. >>That's been a great example. I mean, that's one political, but the economic advantage of getting outta the data center could be national security. You mentioned Ukraine, I mean Oscar see bombing and death over there. So clearly that's a critical crown jewel for their running their operations, which is, you know, you know, world mission critical. So great stuff. I love the speed thing. I think that's a huge one. Let's get into some of the use cases. One of them is, the first one I wanted to talk about was we just hit on data, data center migration. It could be financial reasons on a downturn or our, or market growth. People can make money by shifting to the cloud, either saving money or making money. You win on both sides. It's a, it's a, it's almost a recession proof, if you will. Cloud is so use case for number one data center migration. Take us through what that looks like. Give an example of a success. Take us through a day, day in the life of a data center migration in, in a couple minutes. >>Yeah. You know, I can give you an example of a, of a, of a large bank who decided to migrate, you know, their, all their data centers outside their existing infrastructure. And they had, they had a set timeline, right? They had a set timeline to migrate the, the, they were coming up on a renewal and they wanted to make sure that this set timeline is met. We did a, a complete assessment of their infrastructure. We did a complete assessment of their IT applications, more than 80% of their IT applications, underlying v vSphere platform. And we, we thought that the right solution for them in the timeline that they wanted, right, is VMware cloud ands. And obviously it was a large bank, it wanted to do it safely and securely. It wanted to have it completely managed, and therefore VMware cloud and aws, you know, ticked all the boxes as far as that is concerned. >>I'll be happy to report that the large bank has moved to most of their applications on AWS exiting three of their data centers, and they'll be exiting 12 more very soon. So that's a great example of, of, of the large bank exiting data centers. There's another Corolla to that. Not only did they manage to manage to exit their data centers and of course use and be more agile, but they also met their sustainability goals. Their board of directors had given them goals to be carbon neutral by 2025. They found out that 35% of all their carbon foot footprint was in their data centers. And if they moved their, their ID infrastructure to cloud, they would severely reduce the, the carbon footprint, which is 35% down to 17 to 18%. Right? And that meant their, their, their, their sustainability targets and their commitment to the go to being carbon neutral as well. >>And that they, and they shift that to you guys. Would you guys take that burden? A heavy lifting there and you guys have a sustainability story, which is a whole nother showcase in and of itself. We >>Can Exactly. And, and cause of the scale of our, of our operations, we are able to, we are able to work on that really well as >>Well. All right. So love the data migration. I think that's got real proof points. You got, I can save money, I can, I can then move and position my applications into the cloud for that reason and other reasons as a lot of other reasons to do that. But now it gets into what you mentioned earlier was, okay, data migration, clearly a use case and you laid out some successes. I'm sure there's a zillion others. But then the next step comes, now you got cloud architects becoming minted every, and you got managed services and higher level services. What happens next? Can you give us an example of the use case of the modernization around the NextGen workloads, NextGen applications? We're starting to see, you know, things like data clouds, not data warehouses. We're not gonna data clouds, it's gonna be all kinds of clouds. These NextGen apps are pure digital transformation in action. Take us through a use case of how you guys make that happen with a success story. >>Yes, absolutely. And this is, this is an amazing success story and the customer here is s and p global ratings. As you know, s and p global ratings is, is the world leader as far as global ratings, global credit ratings is concerned. And for them, you know, the last couple of years have been tough as far as hardware procurement is concerned, right? The pandemic has really upended the, the supply chain. And it was taking a lot of time to procure hardware, you know, configure it in time, make sure that that's reliable and then, you know, distribute it in the wide variety of, of, of offices and locations that they have. And they came to us. We, we did, again, a, a, a alar, a fairly large comprehensive assessment of their ID infrastructure and their licensing contracts. And we also found out that VMware cloud and AWS is the right solution for them. >>So we worked there, migrated all their applications, and as soon as we migrated all their applications, they got, they got access to, you know, our high level services be our analytics services, our machine learning services, our, our, our, our artificial intelligence services that have been critical for them, for their growth. And, and that really is helping them, you know, get towards their next level of modern applications. Right Now, obviously going forward, they will have, they will have the choice to, you know, really think about which applications they want to, you know, refactor or which applications they want to go ahead with. That is really a choice in front of them. And, but you know, the, we VMware cloud and AWS really gave them the opportunity to first migrate and then, you know, move towards modernization with speed. >>You know, the speed of a startup is always the kind of the Silicon Valley story where you're, you know, people can make massive changes in 18 months, whether that's a pivot or a new product. You see that in startup world. Now, in the enterprise, you can see the same thing. I noticed behind you on your whiteboard, you got a slogan that says, are you thinking big? I know Amazon likes to think big, but also you work back from the customers and, and I think this modern application thing's a big deal because I think the mindset has always been constrained because back before they moved to the cloud, most IT, and, and, and on-premise data center shops, it's slow. You gotta get the hardware, you gotta configure it, you gotta, you gotta stand it up, make sure all the software is validated on it, and loading a database and loading oss, I mean, mean, yeah, it got easier and with scripting and whatnot, but when you move to the cloud, you have more scale, which means more speed, which means it opens up their capability to think differently and build product. What are you seeing there? Can you share your opinion on that epiphany of, wow, things are going fast, I got more time to actually think about maybe doing a cloud native app or transforming this or that. What's your, what's your reaction to that? Can you share your opinion? >>Well, ultimately we, we want our customers to utilize, you know, most of our modern services, you know, applications should be microservices based. When desired, they should use serverless applic. So list technology, they should not have monolithic, you know, relational database contracts. They should use custom databases, they should use containers when needed, right? So ultimately, we want our customers to use these modern technologies to make sure that their IT infrastructure, their licensing, their, their entire IT spend is completely native to cloud technologies. They work with the speed of a startup, but it's important for them to, to, to get to the first step, right? So that's why we create this journey for our customers, where you help them migrate, give them time to build the skills, they'll help them mo modernize, take our partners along with their, along with us to, to make sure that they can address the need for our customers. That's, that's what our customers need today, and that's what we are working backwards from. >>Yeah, and I think that opens up some big ideas. I'll just say that the, you know, we're joking, I was joking the other night with someone here in, in Palo Alto around serverless, and I said, you know, soon you're gonna hear words like architectural list. And that's a criticism on one hand, but you might say, Hey, you know, if you don't really need an architecture, you know, storage lists, I mean, at the end of the day, infrastructure is code means developers can do all the it in the coding cycles and then make the operations cloud based. And I think this is kind of where I see the dots connecting. Final thought here, take us through what you're thinking around how this new world is evolving. I mean, architecturals kind of a joke, but the point is, you know, you have to some sort of architecture, but you don't have to overthink it. >>Totally. No, that's a great thought, by the way. I know it's a joke, but it's a great thought because at the end of the day, you know, what do the customers really want? They want outcomes, right? Why did service technology come? It was because there was an outcome that they needed. They didn't want to get stuck with, you know, the, the, the real estate of, of a, of a server. They wanted to use compute when they needed to, right? Similarly, what you're talking about is, you know, outcome based, you know, desire of our customers and, and, and that's exactly where the word is going to, Right? Cloud really enforces that, right? We are actually, you know, working backwards from a customer's outcome and using, using our area the breadth and depth of our services to, to deliver those outcomes, right? And, and most of our services are in that path, right? When we use VMware cloud and aws, the outcome is a, to migrate then to modernize, but doesn't stop there, use our native services, you know, get the business outcomes using this. So I think that's, that's exactly what we are going through >>Actually, should actually, you're the director of global sales and go to market for VMware cloud on Aus. I wanna thank you for coming on, but I'll give you the final minute. Give a plug, explain what is the VMware cloud on Aus, Why is it great? Why should people engage with you and, and the team, and what ultimately is this path look like for them going forward? >>Yeah. At the end of the day, we want our customers to have the best paths to the cloud, right? The, the best path to the cloud is making sure that they migrate safely, reliably, and securely as well as with speed, right? And then, you know, use that cloud platform to, to utilize AWS's native services to make sure that they modernize their IT infrastructure and applications, right? We want, ultimately that our customers, customers, customer get the best out of, you know, utilizing the, that whole application experience is enhanced tremendously by using our services. And I think that's, that's exactly what we are working towards VMware cloud AWS is, is helping our customers in that journey towards migrating, modernizing, whether they wanna exit a data center or whether they wanna modernize their applications. It's a essential first step that we wanna help our customers with >>One director of global sales and go to market with VMware cloud on neighbors. He's with aws sharing his thoughts on accelerating business transformation on aws. This is a showcase. We're talking about the future path. We're talking about use cases with success stories from customers as she's thank you for spending time today on this showcase. >>Thank you, John. I appreciate it. >>Okay. This is the cube, special coverage, special presentation of the AWS Showcase. I'm John Furrier, thanks for watching.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.

(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase AI/ML Top Startups Building Foundation Model Infrastructure. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem to talk about data and analytics. I'm your host, Lisa Martin and today we're excited to be joined by two guests from Astronomer. Steven Hillion joins us, it's Chief Data Officer and Jeff Fletcher, it's director of ML. They're here to talk about machine learning and data orchestration. Guys, thank you so much for joining us today. >> Thank you. >> It's great to be here. >> Before we get into machine learning let's give the audience an overview of Astronomer. Talk about what that is, Steven. Talk about what you mean by data orchestration. >> Yeah, let's start with Astronomer. We're the Airflow company basically. The commercial developer behind the open-source project, Apache Airflow. I don't know if you've heard of Airflow. It's sort of de-facto standard these days for orchestrating data pipelines, data engineering pipelines, and as we'll talk about later, machine learning pipelines. It's really is the de-facto standard. I think we're up to about 12 million downloads a month. That's actually as a open-source project. I think at this point it's more popular by some measures than Slack. Airflow was created by Airbnb some years ago to manage all of their data pipelines and manage all of their workflows and now it powers the data ecosystem for organizations as diverse as Electronic Arts, Conde Nast is one of our big customers, a big user of Airflow. And also not to mention the biggest banks on Wall Street use Airflow and Astronomer to power the flow of data throughout their organizations. >> Talk about that a little bit more, Steven, in terms of the business impact. You mentioned some great customer names there. What is the business impact or outcomes that a data orchestration strategy enables businesses to achieve? >> Yeah, I mean, at the heart of it is quite simply, scheduling and managing data pipelines. And so if you have some enormous retailer who's managing the flow of information throughout their organization they may literally have thousands or even tens of thousands of data pipelines that need to execute every day to do things as simple as delivering metrics for the executives to consume at the end of the day, to producing on a weekly basis new machine learning models that can be used to drive product recommendations. One of our customers, for example, is a British food delivery service. And you get those recommendations in your application that says, "Well, maybe you want to have samosas with your curry." That sort of thing is powered by machine learning models that they train on a regular basis to reflect changing conditions in the market. And those are produced through Airflow and through the Astronomer platform, which is essentially a managed platform for running airflow. So at its simplest it really is just scheduling and managing those workflows. But that's easier said than done of course. I mean if you have 10 thousands of those things then you need to make sure that they all run that they all have sufficient compute resources. If things fail, how do you track those down across those 10,000 workflows? How easy is it for an average data scientist or data engineer to contribute their code, their Python notebooks or their SQL code into a production environment? And then you've got reproducibility, governance, auditing, like managing data flows across an organization which we think of as orchestrating them is much more than just scheduling. It becomes really complicated pretty quickly. >> I imagine there's a fair amount of complexity there. Jeff, let's bring you into the conversation. Talk a little bit about Astronomer through your lens, data orchestration and how it applies to MLOps. >> So I come from a machine learning background and for me the interesting part is that machine learning requires the expansion into orchestration. A lot of the same things that you're using to go and develop and build pipelines in a standard data orchestration space applies equally well in a machine learning orchestration space. What you're doing is you're moving data between different locations, between different tools, and then tasking different types of tools to act on that data. So extending it made logical sense from a implementation perspective. And a lot of my focus at Astronomer is really to explain how Airflow can be used well in a machine learning context. It is being used well, it is being used a lot by the customers that we have and also by users of the open source version. But it's really being able to explain to people why it's a natural extension for it and how well it fits into that. And a lot of it is also extending some of the infrastructure capabilities that Astronomer provides to those customers for them to be able to run some of the more platform specific requirements that come with doing machine learning pipelines. >> Let's get into some of the things that make Astronomer unique. Jeff, sticking with you, when you're in customer conversations, what are some of the key differentiators that you articulate to customers? >> So a lot of it is that we are not specific to one cloud provider. So we have the ability to operate across all of the big cloud providers. I know, I'm certain we have the best developers that understand how best practices implementations for data orchestration works. So we spend a lot of time talking to not just the business outcomes and the business users of the product, but also also for the technical people, how to help them better implement things that they may have come across on a Stack Overflow article or not necessarily just grown with how the product has migrated. So it's the ability to run it wherever you need to run it and also our ability to help you, the customer, better implement and understand those workflows that I think are two of the primary differentiators that we have. >> Lisa: Got it. >> I'll add another one if you don't mind. >> You can go ahead, Steven. >> Is lineage and dependencies between workflows. One thing we've done is to augment core Airflow with Lineage services. So using the Open Lineage framework, another open source framework for tracking datasets as they move from one workflow to another one, team to another, one data source to another is a really key component of what we do and we bundle that within the service so that as a developer or as a production engineer, you really don't have to worry about lineage, it just happens. Jeff, may show us some of this later that you can actually see as data flows from source through to a data warehouse out through a Python notebook to produce a predictive model or a dashboard. Can you see how those data products relate to each other? And when something goes wrong, figure out what upstream maybe caused the problem, or if you're about to change something, figure out what the impact is going to be on the rest of the organization. So Lineage is a big deal for us. >> Got it. >> And just to add on to that, the other thing to think about is that traditional Airflow is actually a complicated implementation. It required quite a lot of time spent understanding or was almost a bespoke language that you needed to be able to develop in two write these DAGs, which is like fundamental pipelines. So part of what we are focusing on is tooling that makes it more accessible to say a data analyst or a data scientist who doesn't have or really needs to gain the necessary background in how the semantics of Airflow DAGs works to still be able to get the benefit of what Airflow can do. So there is new features and capabilities built into the astronomer cloud platform that effectively obfuscates and removes the need to understand some of the deep work that goes on. But you can still do it, you still have that capability, but we are expanding it to be able to have orchestrated and repeatable processes accessible to more teams within the business. >> In terms of accessibility to more teams in the business. You talked about data scientists, data analysts, developers. Steven, I want to talk to you, as the chief data officer, are you having more and more conversations with that role and how is it emerging and evolving within your customer base? >> Hmm. That's a good question, and it is evolving because I think if you look historically at the way that Airflow has been used it's often from the ground up. You have individual data engineers or maybe single data engineering teams who adopt Airflow 'cause it's very popular. Lots of people know how to use it and they bring it into an organization and say, "Hey, let's use this to run our data pipelines." But then increasingly as you turn from pure workflow management and job scheduling to the larger topic of orchestration you realize it gets pretty complicated, you want to have coordination across teams, and you want to have standardization for the way that you manage your data pipelines. And so having a managed service for Airflow that exists in the cloud is easy to spin up as you expand usage across the organization. And thinking long term about that in the context of orchestration that's where I think the chief data officer or the head of analytics tends to get involved because they really want to think of this as a strategic investment that they're making. Not just per team individual Airflow deployments, but a network of data orchestrators. >> That network is key. Every company these days has to be a data company. We talk about companies being data driven. It's a common word, but it's true. It's whether it is a grocer or a bank or a hospital, they've got to be data companies. So talk to me a little bit about Astronomer's business model. How is this available? How do customers get their hands on it? >> Jeff, go ahead. >> Yeah, yeah. So we have a managed cloud service and we have two modes of operation. One, you can bring your own cloud infrastructure. So you can say here is an account in say, AWS or Azure and we can go and deploy the necessary infrastructure into that, or alternatively we can host everything for you. So it becomes a full SaaS offering. But we then provide a platform that connects at the backend to your internal IDP process. So however you are authenticating users to make sure that the correct people are accessing the services that they need with role-based access control. From there we are deploying through Kubernetes, the different services and capabilities into either your cloud account or into an account that we host. And from there Airflow does what Airflow does, which is its ability to then reach to different data systems and data platforms and to then run the orchestration. We make sure we do it securely, we have all the necessary compliance certifications required for GDPR in Europe and HIPAA based out of the US, and a whole bunch host of others. So it is a secure platform that can run in a place that you need it to run, but it is a managed Airflow that includes a lot of the extra capabilities like the cloud developer environment and the open lineage services to enhance the overall airflow experience. >> Enhance the overall experience. So Steven, going back to you, if I'm a Conde Nast or another organization, what are some of the key business outcomes that I can expect? As one of the things I think we've learned during the pandemic is access to realtime data is no longer a nice to have for organizations. It's really an imperative. It's that demanding consumer that wants to have that personalized, customized, instant access to a product or a service. So if I'm a Conde Nast or I'm one of your customers, what can I expect my business to be able to achieve as a result of data orchestration? >> Yeah, I think in a nutshell it's about providing a reliable, scalable, and easy to use service for developing and running data workflows. And talking of demanding customers, I mean, I'm actually a customer myself, as you mentioned, I'm the head of data for Astronomer. You won't be surprised to hear that we actually use Astronomer and Airflow to run all of our data pipelines. And so I can actually talk about my experience. When I started I was of course familiar with Airflow, but it always seemed a little bit unapproachable to me if I was introducing that to a new team of data scientists. They don't necessarily want to have to think about learning something new. But I think because of the layers that Astronomer has provided with our Astro service around Airflow it was pretty easy for me to get up and running. Of course I've got an incentive for doing that. I work for the Airflow company, but we went from about, at the beginning of last year, about 500 data tasks that we were running on a daily basis to about 15,000 every day. We run something like a million data operations every month within my team. And so as one outcome, just the ability to spin up new production workflows essentially in a single day you go from an idea in the morning to a new dashboard or a new model in the afternoon, that's really the business outcome is just removing that friction to operationalizing your machine learning and data workflows. >> And I imagine too, oh, go ahead, Jeff. >> Yeah, I think to add to that, one of the things that becomes part of the business cycle is a repeatable capabilities for things like reporting, for things like new machine learning models. And the impediment that has existed is that it's difficult to take that from a team that's an analyst team who then provide that or a data science team that then provide that to the data engineering team who have to work the workflow all the way through. What we're trying to unlock is the ability for those teams to directly get access to scheduling and orchestrating capabilities so that a business analyst can have a new report for C-suite execs that needs to be done once a week, but the time to repeatability for that report is much shorter. So it is then immediately in the hands of the person that needs to see it. It doesn't have to go into a long list of to-dos for a data engineering team that's already overworked that they eventually get it to it in a month's time. So that is also a part of it is that the realizing, orchestration I think is fairly well and a lot of people get the benefit of being able to orchestrate things within a business, but it's having more people be able to do it and shorten the time that that repeatability is there is one of the main benefits from good managed orchestration. >> So a lot of workforce productivity improvements in what you're doing to simplify things, giving more people access to data to be able to make those faster decisions, which ultimately helps the end user on the other end to get that product or the service that they're expecting like that. Jeff, I understand you have a demo that you can share so we can kind of dig into this. >> Yeah, let me take you through a quick look of how the whole thing works. So our starting point is our cloud infrastructure. This is the login. You go to the portal. You can see there's a a bunch of workspaces that are available. Workspaces are like individual places for people to operate in. I'm not going to delve into all the deep technical details here, but starting point for a lot of our data science customers is we have what we call our Cloud IDE, which is a web-based development environment for writing and building out DAGs without actually having to know how the underpinnings of Airflow work. This is an internal one, something that we use. You have a notebook-like interface that lets you write python code and SQL code and a bunch of specific bespoke type of blocks if you want. They all get pulled together and create a workflow. So this is a workflow, which gets compiled to something that looks like a complicated set of Python code, which is the DAG. I then have a CICD process pipeline where I commit this through to my GitHub repo. So this comes to a repo here, which is where these DAGs that I created in the previous step exist. I can then go and say, all right, I want to see how those particular DAGs have been running. We then get to the actual Airflow part. So this is the managed Airflow component. So we add the ability for teams to fairly easily bring up an Airflow instance and write code inside our notebook-like environment to get it into that instance. So you can see it's been running. That same process that we built here that graph ends up here inside this, but you don't need to know how the fundamentals of Airflow work in order to get this going. Then we can run one of these, it runs in the background and we can manage how it goes. And from there, every time this runs, it's emitting to a process underneath, which is the open lineage service, which is the lineage integration that allows me to come in here and have a look and see this was that actual, that same graph that we built, but now it's the historic version. So I know where things started, where things are going, and how it ran. And then I can also do a comparison. So if I want to see how this particular run worked compared to one historically, I can grab one from a previous date and it will show me the comparison between the two. So that combination of managed Airflow, getting Airflow up and running very quickly, but the Cloud IDE that lets you write code and know how to get something into a repeatable format get that into Airflow and have that attached to the lineage process adds what is a complete end-to-end orchestration process for any business looking to get the benefit from orchestration. >> Outstanding. Thank you so much Jeff for digging into that. So one of my last questions, Steven is for you. This is exciting. There's a lot that you guys are enabling organizations to achieve here to really become data-driven companies. So where can folks go to get their hands on this? >> Yeah, just go to astronomer.io and we have plenty of resources. If you're new to Airflow, you can read our documentation, our guides to getting started. We have a CLI that you can download that is really I think the easiest way to get started with Airflow. But you can actually sign up for a trial. You can sign up for a guided trial where our teams, we have a team of experts, really the world experts on getting Airflow up and running. And they'll take you through that trial and allow you to actually kick the tires and see how this works with your data. And I think you'll see pretty quickly that it's very easy to get started with Airflow, whether you're doing that from the command line or doing that in our cloud service. And all of that is available on our website >> astronomer.io. Jeff, last question for you. What are you excited about? There's so much going on here. What are some of the things, maybe you can give us a sneak peek coming down the road here that prospects and existing customers should be excited about? >> I think a lot of the development around the data awareness components, so one of the things that's traditionally been complicated with orchestration is you leave your data in the place that you're operating on and we're starting to have more data processing capability being built into Airflow. And from a Astronomer perspective, we are adding more capabilities around working with larger datasets, doing bigger data manipulation with inside the Airflow process itself. And that lends itself to better machine learning implementation. So as we start to grow and as we start to get better in the machine learning context, well, in the data awareness context, it unlocks a lot more capability to do and implement proper machine learning pipelines. >> Awesome guys. Exciting stuff. Thank you so much for talking to me about Astronomer, machine learning, data orchestration, and really the value in it for your customers. Steve and Jeff, we appreciate your time. >> Thank you. >> My pleasure, thanks. >> And we thank you for watching. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem. I'm your host, Lisa Martin. You're watching theCUBE, the leader in live tech coverage. (upbeat music)

(upbeat music) >> Hello everyone. Welcome to theCube's presentation of the "AWS Startup Showcase." The topic this episode is AI and machine learning, top startups building foundational model infrastructure. This is season three, episode one of the ongoing series covering exciting startups from the AWS ecosystem. And this time we're talking about AI and machine learning. I'm your host, John Furrier. I'm excited I'm joined today by Robert Nishihara, who's the co-founder and CEO of a hot startup called Anyscale. He's here to talk about Ray, the open source project, Anyscale's infrastructure for foundation as well. Robert, thank you for joining us today. >> Yeah, thanks so much as well. >> I've been following your company since the founding pre pandemic and you guys really had a great vision scaled up and in a perfect position for this big wave that we all see with ChatGPT and OpenAI that's gone mainstream. Finally, AI has broken out through the ropes and now gone mainstream, so I think you guys are really well positioned. I'm looking forward to to talking with you today. But before we get into it, introduce the core mission for Anyscale. Why do you guys exist? What is the North Star for Anyscale? >> Yeah, like you mentioned, there's a tremendous amount of excitement about AI right now. You know, I think a lot of us believe that AI can transform just every different industry. So one of the things that was clear to us when we started this company was that the amount of compute needed to do AI was just exploding. Like to actually succeed with AI, companies like OpenAI or Google or you know, these companies getting a lot of value from AI, were not just running these machine learning models on their laptops or on a single machine. They were scaling these applications across hundreds or thousands or more machines and GPUs and other resources in the Cloud. And so to actually succeed with AI, and this has been one of the biggest trends in computing, maybe the biggest trend in computing in, you know, in recent history, the amount of compute has been exploding. And so to actually succeed with that AI, to actually build these scalable applications and scale the AI applications, there's a tremendous software engineering lift to build the infrastructure to actually run these scalable applications. And that's very hard to do. So one of the reasons many AI projects and initiatives fail is that, or don't make it to production, is the need for this scale, the infrastructure lift, to actually make it happen. So our goal here with Anyscale and Ray, is to make that easy, is to make scalable computing easy. So that as a developer or as a business, if you want to do AI, if you want to get value out of AI, all you need to know is how to program on your laptop. Like, all you need to know is how to program in Python. And if you can do that, then you're good to go. Then you can do what companies like OpenAI or Google do and get value out of machine learning. >> That programming example of how easy it is with Python reminds me of the early days of Cloud, when infrastructure as code was talked about was, it was just code the infrastructure programmable. That's super important. That's what AI people wanted, first program AI. That's the new trend. And I want to understand, if you don't mind explaining, the relationship that Anyscale has to these foundational models and particular the large language models, also called LLMs, was seen with like OpenAI and ChatGPT. Before you get into the relationship that you have with them, can you explain why the hype around foundational models? Why are people going crazy over foundational models? What is it and why is it so important? >> Yeah, so foundational models and foundation models are incredibly important because they enable businesses and developers to get value out of machine learning, to use machine learning off the shelf with these large models that have been trained on tons of data and that are useful out of the box. And then, of course, you know, as a business or as a developer, you can take those foundational models and repurpose them or fine tune them or adapt them to your specific use case and what you want to achieve. But it's much easier to do that than to train them from scratch. And I think there are three, for people to actually use foundation models, there are three main types of workloads or problems that need to be solved. One is training these foundation models in the first place, like actually creating them. The second is fine tuning them and adapting them to your use case. And the third is serving them and actually deploying them. Okay, so Ray and Anyscale are used for all of these three different workloads. Companies like OpenAI or Cohere that train large language models. Or open source versions like GPTJ are done on top of Ray. There are many startups and other businesses that fine tune, that, you know, don't want to train the large underlying foundation models, but that do want to fine tune them, do want to adapt them to their purposes, and build products around them and serve them, those are also using Ray and Anyscale for that fine tuning and that serving. And so the reason that Ray and Anyscale are important here is that, you know, building and using foundation models requires a huge scale. It requires a lot of data. It requires a lot of compute, GPUs, TPUs, other resources. And to actually take advantage of that and actually build these scalable applications, there's a lot of infrastructure that needs to happen under the hood. And so you can either use Ray and Anyscale to take care of that and manage the infrastructure and solve those infrastructure problems. Or you can build the infrastructure and manage the infrastructure yourself, which you can do, but it's going to slow your team down. It's going to, you know, many of the businesses we work with simply don't want to be in the business of managing infrastructure and building infrastructure. They want to focus on product development and move faster. >> I know you got a keynote presentation we're going to go to in a second, but I think you hit on something I think is the real tipping point, doing it yourself, hard to do. These are things where opportunities are and the Cloud did that with data centers. Turned a data center and made it an API. The heavy lifting went away and went to the Cloud so people could be more creative and build their product. In this case, build their creativity. Is that kind of what's the big deal? Is that kind of a big deal happening that you guys are taking the learnings and making that available so people don't have to do that? >> That's exactly right. So today, if you want to succeed with AI, if you want to use AI in your business, infrastructure work is on the critical path for doing that. To do AI, you have to build infrastructure. You have to figure out how to scale your applications. That's going to change. We're going to get to the point, and you know, with Ray and Anyscale, we're going to remove the infrastructure from the critical path so that as a developer or as a business, all you need to focus on is your application logic, what you want the the program to do, what you want your application to do, how you want the AI to actually interface with the rest of your product. Now the way that will happen is that Ray and Anyscale will still, the infrastructure work will still happen. It'll just be under the hood and taken care of by Ray in Anyscale. And so I think something like this is really necessary for AI to reach its potential, for AI to have the impact and the reach that we think it will, you have to make it easier to do. >> And just for clarification to point out, if you don't mind explaining the relationship of Ray and Anyscale real quick just before we get into the presentation. >> So Ray is an open source project. We created it. We were at Berkeley doing machine learning. We started Ray so that, in order to provide an easy, a simple open source tool for building and running scalable applications. And Anyscale is the managed version of Ray, basically we will run Ray for you in the Cloud, provide a lot of tools around the developer experience and managing the infrastructure and providing more performance and superior infrastructure. >> Awesome. I know you got a presentation on Ray and Anyscale and you guys are positioning as the infrastructure for foundational models. So I'll let you take it away and then when you're done presenting, we'll come back, I'll probably grill you with a few questions and then we'll close it out so take it away. >> Robert: Sounds great. So I'll say a little bit about how companies are using Ray and Anyscale for foundation models. The first thing I want to mention is just why we're doing this in the first place. And the underlying observation, the underlying trend here, and this is a plot from OpenAI, is that the amount of compute needed to do machine learning has been exploding. It's been growing at something like 35 times every 18 months. This is absolutely enormous. And other people have written papers measuring this trend and you get different numbers. But the point is, no matter how you slice and dice it, it' a astronomical rate. Now if you compare that to something we're all familiar with, like Moore's Law, which says that, you know, the processor performance doubles every roughly 18 months, you can see that there's just a tremendous gap between the needs, the compute needs of machine learning applications, and what you can do with a single chip, right. So even if Moore's Law were continuing strong and you know, doing what it used to be doing, even if that were the case, there would still be a tremendous gap between what you can do with the chip and what you need in order to do machine learning. And so given this graph, what we've seen, and what has been clear to us since we started this company, is that doing AI requires scaling. There's no way around it. It's not a nice to have, it's really a requirement. And so that led us to start Ray, which is the open source project that we started to make it easy to build these scalable Python applications and scalable machine learning applications. And since we started the project, it's been adopted by a tremendous number of companies. Companies like OpenAI, which use Ray to train their large models like ChatGPT, companies like Uber, which run all of their deep learning and classical machine learning on top of Ray, companies like Shopify or Spotify or Instacart or Lyft or Netflix, ByteDance, which use Ray for their machine learning infrastructure. Companies like Ant Group, which makes Alipay, you know, they use Ray across the board for fraud detection, for online learning, for detecting money laundering, you know, for graph processing, stream processing. Companies like Amazon, you know, run Ray at a tremendous scale and just petabytes of data every single day. And so the project has seen just enormous adoption since, over the past few years. And one of the most exciting use cases is really providing the infrastructure for building training, fine tuning, and serving foundation models. So I'll say a little bit about, you know, here are some examples of companies using Ray for foundation models. Cohere trains large language models. OpenAI also trains large language models. You can think about the workloads required there are things like supervised pre-training, also reinforcement learning from human feedback. So this is not only the regular supervised learning, but actually more complex reinforcement learning workloads that take human input about what response to a particular question, you know is better than a certain other response. And incorporating that into the learning. There's open source versions as well, like GPTJ also built on top of Ray as well as projects like Alpa coming out of UC Berkeley. So these are some of the examples of exciting projects in organizations, training and creating these large language models and serving them using Ray. Okay, so what actually is Ray? Well, there are two layers to Ray. At the lowest level, there's the core Ray system. This is essentially low level primitives for building scalable Python applications. Things like taking a Python function or a Python class and executing them in the cluster setting. So Ray core is extremely flexible and you can build arbitrary scalable applications on top of Ray. So on top of Ray, on top of the core system, what really gives Ray a lot of its power is this ecosystem of scalable libraries. So on top of the core system you have libraries, scalable libraries for ingesting and pre-processing data, for training your models, for fine tuning those models, for hyper parameter tuning, for doing batch processing and batch inference, for doing model serving and deployment, right. And a lot of the Ray users, the reason they like Ray is that they want to run multiple workloads. They want to train and serve their models, right. They want to load their data and feed that into training. And Ray provides common infrastructure for all of these different workloads. So this is a little overview of what Ray, the different components of Ray. So why do people choose to go with Ray? I think there are three main reasons. The first is the unified nature. The fact that it is common infrastructure for scaling arbitrary workloads, from data ingest to pre-processing to training to inference and serving, right. This also includes the fact that it's future proof. AI is incredibly fast moving. And so many people, many companies that have built their own machine learning infrastructure and standardized on particular workflows for doing machine learning have found that their workflows are too rigid to enable new capabilities. If they want to do reinforcement learning, if they want to use graph neural networks, they don't have a way of doing that with their standard tooling. And so Ray, being future proof and being flexible and general gives them that ability. Another reason people choose Ray in Anyscale is the scalability. This is really our bread and butter. This is the reason, the whole point of Ray, you know, making it easy to go from your laptop to running on thousands of GPUs, making it easy to scale your development workloads and run them in production, making it easy to scale, you know, training to scale data ingest, pre-processing and so on. So scalability and performance, you know, are critical for doing machine learning and that is something that Ray provides out of the box. And lastly, Ray is an open ecosystem. You can run it anywhere. You can run it on any Cloud provider. Google, you know, Google Cloud, AWS, Asure. You can run it on your Kubernetes cluster. You can run it on your laptop. It's extremely portable. And not only that, it's framework agnostic. You can use Ray to scale arbitrary Python workloads. You can use it to scale and it integrates with libraries like TensorFlow or PyTorch or JAX or XG Boost or Hugging Face or PyTorch Lightning, right, or Scikit-learn or just your own arbitrary Python code. It's open source. And in addition to integrating with the rest of the machine learning ecosystem and these machine learning frameworks, you can use Ray along with all of the other tooling in the machine learning ecosystem. That's things like weights and biases or ML flow, right. Or you know, different data platforms like Databricks, you know, Delta Lake or Snowflake or tools for model monitoring for feature stores, all of these integrate with Ray. And that's, you know, Ray provides that kind of flexibility so that you can integrate it into the rest of your workflow. And then Anyscale is the scalable compute platform that's built on top, you know, that provides Ray. So Anyscale is a managed Ray service that runs in the Cloud. And what Anyscale does is it offers the best way to run Ray. And if you think about what you get with Anyscale, there are fundamentally two things. One is about moving faster, accelerating the time to market. And you get that by having the managed service so that as a developer you don't have to worry about managing infrastructure, you don't have to worry about configuring infrastructure. You also, it provides, you know, optimized developer workflows. Things like easily moving from development to production, things like having the observability tooling, the debug ability to actually easily diagnose what's going wrong in a distributed application. So things like the dashboards and the other other kinds of tooling for collaboration, for monitoring and so on. And then on top of that, so that's the first bucket, developer productivity, moving faster, faster experimentation and iteration. The second reason that people choose Anyscale is superior infrastructure. So this is things like, you know, cost deficiency, being able to easily take advantage of spot instances, being able to get higher GPU utilization, things like faster cluster startup times and auto scaling. Things like just overall better performance and faster scheduling. And so these are the kinds of things that Anyscale provides on top of Ray. It's the managed infrastructure. It's fast, it's like the developer productivity and velocity as well as performance. So this is what I wanted to share about Ray in Anyscale. >> John: Awesome. >> Provide that context. But John, I'm curious what you think. >> I love it. I love the, so first of all, it's a platform because that's the platform architecture right there. So just to clarify, this is an Anyscale platform, not- >> That's right. >> Tools. So you got tools in the platform. Okay, that's key. Love that managed service. Just curious, you mentioned Python multiple times, is that because of PyTorch and TensorFlow or Python's the most friendly with machine learning or it's because it's very common amongst all developers? >> That's a great question. Python is the language that people are using to do machine learning. So it's the natural starting point. Now, of course, Ray is actually designed in a language agnostic way and there are companies out there that use Ray to build scalable Java applications. But for the most part right now we're focused on Python and being the best way to build these scalable Python and machine learning applications. But, of course, down the road there always is that potential. >> So if you're slinging Python code out there and you're watching that, you're watching this video, get on Anyscale bus quickly. Also, I just, while you were giving the presentation, I couldn't help, since you mentioned OpenAI, which by the way, congratulations 'cause they've had great scale, I've noticed in their rapid growth 'cause they were the fastest company to the number of users than anyone in the history of the computer industry, so major successor, OpenAI and ChatGPT, huge fan. I'm not a skeptic at all. I think it's just the beginning, so congratulations. But I actually typed into ChatGPT, what are the top three benefits of Anyscale and came up with scalability, flexibility, and ease of use. Obviously, scalability is what you guys are called. >> That's pretty good. >> So that's what they came up with. So they nailed it. Did you have an inside prompt training, buy it there? Only kidding. (Robert laughs) >> Yeah, we hard coded that one. >> But that's the kind of thing that came up really, really quickly if I asked it to write a sales document, it probably will, but this is the future interface. This is why people are getting excited about the foundational models and the large language models because it's allowing the interface with the user, the consumer, to be more human, more natural. And this is clearly will be in every application in the future. >> Absolutely. This is how people are going to interface with software, how they're going to interface with products in the future. It's not just something, you know, not just a chat bot that you talk to. This is going to be how you get things done, right. How you use your web browser or how you use, you know, how you use Photoshop or how you use other products. Like you're not going to spend hours learning all the APIs and how to use them. You're going to talk to it and tell it what you want it to do. And of course, you know, if it doesn't understand it, it's going to ask clarifying questions. You're going to have a conversation and then it'll figure it out. >> This is going to be one of those things, we're going to look back at this time Robert and saying, "Yeah, from that company, that was the beginning of that wave." And just like AWS and Cloud Computing, the folks who got in early really were in position when say the pandemic came. So getting in early is a good thing and that's what everyone's talking about is getting in early and playing around, maybe replatforming or even picking one or few apps to refactor with some staff and managed services. So people are definitely jumping in. So I have to ask you the ROI cost question. You mentioned some of those, Moore's Law versus what's going on in the industry. When you look at that kind of scale, the first thing that jumps out at people is, "Okay, I love it. Let's go play around." But what's it going to cost me? Am I going to be tied to certain GPUs? What's the landscape look like from an operational standpoint, from the customer? Are they locked in and the benefit was flexibility, are you flexible to handle any Cloud? What is the customers, what are they looking at? Basically, that's my question. What's the customer looking at? >> Cost is super important here and many of the companies, I mean, companies are spending a huge amount on their Cloud computing, on AWS, and on doing AI, right. And I think a lot of the advantage of Anyscale, what we can provide here is not only better performance, but cost efficiency. Because if we can run something faster and more efficiently, it can also use less resources and you can lower your Cloud spending, right. We've seen companies go from, you know, 20% GPU utilization with their current setup and the current tools they're using to running on Anyscale and getting more like 95, you know, 100% GPU utilization. That's something like a five x improvement right there. So depending on the kind of application you're running, you know, it's a significant cost savings. We've seen companies that have, you know, processing petabytes of data every single day with Ray going from, you know, getting order of magnitude cost savings by switching from what they were previously doing to running their application on Ray. And when you have applications that are spending, you know, potentially $100 million a year and getting a 10 X cost savings is just absolutely enormous. So these are some of the kinds of- >> Data infrastructure is super important. Again, if the customer, if you're a prospect to this and thinking about going in here, just like the Cloud, you got infrastructure, you got the platform, you got SaaS, same kind of thing's going to go on in AI. So I want to get into that, you know, ROI discussion and some of the impact with your customers that are leveraging the platform. But first I hear you got a demo. >> Robert: Yeah, so let me show you, let me give you a quick run through here. So what I have open here is the Anyscale UI. I've started a little Anyscale Workspace. So Workspaces are the Anyscale concept for interactive developments, right. So here, imagine I'm just, you want to have a familiar experience like you're developing on your laptop. And here I have a terminal. It's not on my laptop. It's actually in the cloud running on Anyscale. And I'm just going to kick this off. This is going to train a large language model, so OPT. And it's doing this on 32 GPUs. We've got a cluster here with a bunch of CPU cores, bunch of memory. And as that's running, and by the way, if I wanted to run this on instead of 32 GPUs, 64, 128, this is just a one line change when I launch the Workspace. And what I can do is I can pull up VS code, right. Remember this is the interactive development experience. I can look at the actual code. Here it's using Ray train to train the torch model. We've got the training loop and we're saying that each worker gets access to one GPU and four CPU cores. And, of course, as I make the model larger, this is using deep speed, as I make the model larger, I could increase the number of GPUs that each worker gets access to, right. And how that is distributed across the cluster. And if I wanted to run on CPUs instead of GPUs or a different, you know, accelerator type, again, this is just a one line change. And here we're using Ray train to train the models, just taking my vanilla PyTorch model using Hugging Face and then scaling that across a bunch of GPUs. And, of course, if I want to look at the dashboard, I can go to the Ray dashboard. There are a bunch of different visualizations I can look at. I can look at the GPU utilization. I can look at, you know, the CPU utilization here where I think we're currently loading the model and running that actual application to start the training. And some of the things that are really convenient here about Anyscale, both I can get that interactive development experience with VS code. You know, I can look at the dashboards. I can monitor what's going on. It feels, I have a terminal, it feels like my laptop, but it's actually running on a large cluster. And I can, with however many GPUs or other resources that I want. And so it's really trying to combine the best of having the familiar experience of programming on your laptop, but with the benefits, you know, being able to take advantage of all the resources in the Cloud to scale. And it's like when, you know, you're talking about cost efficiency. One of the biggest reasons that people waste money, one of the silly reasons for wasting money is just forgetting to turn off your GPUs. And what you can do here is, of course, things will auto terminate if they're idle. But imagine you go to sleep, I have this big cluster. You can turn it off, shut off the cluster, come back tomorrow, restart the Workspace, and you know, your big cluster is back up and all of your code changes are still there. All of your local file edits. It's like you just closed your laptop and came back and opened it up again. And so this is the kind of experience we want to provide for our users. So that's what I wanted to share with you. >> Well, I think that whole, couple of things, lines of code change, single line of code change, that's game changing. And then the cost thing, I mean human error is a big deal. People pass out at their computer. They've been coding all night or they just forget about it. I mean, and then it's just like leaving the lights on or your water running in your house. It's just, at the scale that it is, the numbers will add up. That's a huge deal. So I think, you know, compute back in the old days, there's no compute. Okay, it's just compute sitting there idle. But you know, data cranking the models is doing, that's a big point. >> Another thing I want to add there about cost efficiency is that we make it really easy to use, if you're running on Anyscale, to use spot instances and these preemptable instances that can just be significantly cheaper than the on-demand instances. And so when we see our customers go from what they're doing before to using Anyscale and they go from not using these spot instances 'cause they don't have the infrastructure around it, the fault tolerance to handle the preemption and things like that, to being able to just check a box and use spot instances and save a bunch of money. >> You know, this was my whole, my feature article at Reinvent last year when I met with Adam Selipsky, this next gen Cloud is here. I mean, it's not auto scale, it's infrastructure scale. It's agility. It's flexibility. I think this is where the world needs to go. Almost what DevOps did for Cloud and what you were showing me that demo had this whole SRE vibe. And remember Google had site reliability engines to manage all those servers. This is kind of like an SRE vibe for data at scale. I mean, a similar kind of order of magnitude. I mean, I might be a little bit off base there, but how would you explain it? >> It's a nice analogy. I mean, what we are trying to do here is get to the point where developers don't think about infrastructure. Where developers only think about their application logic. And where businesses can do AI, can succeed with AI, and build these scalable applications, but they don't have to build, you know, an infrastructure team. They don't have to develop that expertise. They don't have to invest years in building their internal machine learning infrastructure. They can just focus on the Python code, on their application logic, and run the stuff out of the box. >> Awesome. Well, I appreciate the time. Before we wrap up here, give a plug for the company. I know you got a couple websites. Again, go, Ray's got its own website. You got Anyscale. You got an event coming up. Give a plug for the company looking to hire. Put a plug in for the company. >> Yeah, absolutely. Thank you. So first of all, you know, we think AI is really going to transform every industry and the opportunity is there, right. We can be the infrastructure that enables all of that to happen, that makes it easy for companies to succeed with AI, and get value out of AI. Now we have, if you're interested in learning more about Ray, Ray has been emerging as the standard way to build scalable applications. Our adoption has been exploding. I mentioned companies like OpenAI using Ray to train their models. But really across the board companies like Netflix and Cruise and Instacart and Lyft and Uber, you know, just among tech companies. It's across every industry. You know, gaming companies, agriculture, you know, farming, robotics, drug discovery, you know, FinTech, we see it across the board. And all of these companies can get value out of AI, can really use AI to improve their businesses. So if you're interested in learning more about Ray and Anyscale, we have our Ray Summit coming up in September. This is going to highlight a lot of the most impressive use cases and stories across the industry. And if your business, if you want to use LLMs, you want to train these LLMs, these large language models, you want to fine tune them with your data, you want to deploy them, serve them, and build applications and products around them, give us a call, talk to us. You know, we can really take the infrastructure piece, you know, off the critical path and make that easy for you. So that's what I would say. And, you know, like you mentioned, we're hiring across the board, you know, engineering, product, go-to-market, and it's an exciting time. >> Robert Nishihara, co-founder and CEO of Anyscale, congratulations on a great company you've built and continuing to iterate on and you got growth ahead of you, you got a tailwind. I mean, the AI wave is here. I think OpenAI and ChatGPT, a customer of yours, have really opened up the mainstream visibility into this new generation of applications, user interface, roll of data, large scale, how to make that programmable so we're going to need that infrastructure. So thanks for coming on this season three, episode one of the ongoing series of the hot startups. In this case, this episode is the top startups building foundational model infrastructure for AI and ML. I'm John Furrier, your host. Thanks for watching. (upbeat music)

(gentle music) >> Hello, and welcome to theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE. I've got a great guest here, CUBE alumni and very impressive, inspiring, Rachel Mushahwar Skaff, who's a managing director and general manager at AWS. Rachel, great to see you. Thanks for coming on. >> Thank you so much. It's always a pleasure to be here. You all make such a tremendous impact with reporting out what's happening in the tech space, and frankly, investing in topics like this, so thank you. >> It's our pleasure. Your career has been really impressive. You worked at Intel for almost a decade, and that company is very tech, very focused on Moore's law, cadence of technology power in the industry. Now at AWS, powering next-generation cloud. What inspired you to get into tech? How did you get here and how have you approached your career journey, because it's quite a track record? >> Wow, how long do we have? (Rachel and John laugh) >> John: We can go as long as you want. (laughs) It's great. >> You know, all joking aside, I think at the end of the day, it's about this simple statement. If you don't get goosebumps every single morning that you're waking up to do your job, it's not good enough. And that's a bit about how I've made all of the different career transitions that I have. You know, everything from building out data centers around the world, to leading network and engineering teams, to leading applications teams, to going and working for, you know, the largest semiconductor in the world, and now at AWS, every single one of those opportunities gave me goosebumps. And I was really focused on how do I surround myself with humans that are better than I am, smarter than I am, companies that plan in decades, but live in moments, companies that invest in their employees and create like artists? And frankly, for me, being part of a company where people know that life is finite, but they want to make an infinite impact, that's a bit about my career journey in a nutshell. >> Yeah. What's interesting is that, you know, over the years, a lot's changed, and a theme that we're hearing from leaders now that are heading up large teams and running companies, they have, you know, they have 20-plus years of experience under their belt and they look back and they say, "Wow, "things have changed and it's changing faster now, "hopefully faster to get change." But they all talk about confidence and they talk about curiosity and building. When did you know that this was going to be something that you got the goosebumps? And were there blockers in your way and how did you handle that? (Rachel laughs) >> There's always blockers in our way, and I think a lot of people don't actually talk about the blockers. I think they make it sound like, hey, I had this plan from day one, and every decision I've made has been perfect. And for me, I'll tell you, right, there are moments in your life that mark a differentiation and those moments that you realize nothing will be the same. And time is kind of divided into two parts, right, before this moment and after this moment. And that's everything from, before I had kids, that's a pretty big moment in people's lives, to after I had kids, and how do you work through some of those opportunities? Before I got married, before I got divorced. Before I went to this company, after I left this company. And I think the key for all of those is just having an insatiable curiosity around how do you continue to do better, create better and make better? And I'll tell you, those blockers, they exist. Coming back from maternity leave, hard. Coming back from a medical leave, hard. Coming back from caring for a sick parent or a sick friend, hard. But all of those things start to help craft who you are as a human being, not as a leader, but as a human being, and allows you to have some empathy with the people that you surround yourself with, right? And for me, it's, (sighs) you can think about these blockers in one of two ways. You can think about it as, you know, every single time that you're tempted to react in the same way to a blocker, you can be a prisoner of your past, or you can change how you react and be a pioneer of the future. It's not a blocker when you think about it in those terms. >> Mindset matters, and that's really a great point. You brought up something that's interesting, I want to bring this up. Some of the challenges in different stages of our lives. You know, one thing that's come out of this set of interviews, this, of day and in conversations is, that I haven't heard before, is the result of COVID, working at home brought empathy about people's personal lives to the table. That came up in a couple interviews. What's your reaction to that? Because that highlights that we're human, to your point of view. >> It does. It does. And I'm so thankful that you don't ask about balance because that is a pet peeve of mine, because there is no such thing as balance. If you're in perfect balance, you are not moving and you're not changing. But when you think about, you know, the impact of COVID and how the world has changed since that, it has allowed all of us to really think about, you know, what do we want to do versus what do we have to do? And I think so many times, in both our professional lives and our personal lives, we get caught up in doing what we think we have to do to get ahead versus taking a step back and saying, "Hey, what do I want to do? "And how do I become a, you know, "a better human?" And many times, John, I'm asked, "Hey, "how do you define success or achievement?" And, you know, my answer is really, for me, the greatest results that I've achieved, both personally and professionally, is when I eliminate the word success and balance from my vocabulary, and replace them with two words: What's my contribution and what's my impact? Those things make a difference, regardless of gender. And I'll tell you, none of it is easy, ever. I think all of us have been broken, we've been stretched, we've been burnt out. But I also think what we have to talk about as leaders in the industry is how we've also found endurance and resilience. And when we felt unsteady, we've continued to go forward, right? When we can't decide, the best answer is do what's uncomfortable. And all of those things really stemmed from a part of what happened with COVID. >> Yeah, yeah, I love the uncomfortable and the balance highlight. You mentioned being off balance. That means you're growing, you're not standing still. I want to get your thoughts on this because one thing that has come out again this year, and last year as well, is having a team with you when you do it. So if you're off balance and you're going to stretch, if you have a good team with you, that's where people help each other. Not just pick them up, but like maybe get 'em back on track again. So, but if you're solo, you fall, (laughs) you fall harder. So what's your reaction to that? 'Cause this has come up, and this comes up in team building, workforce formation, goal setting, contribution. What's your reaction to that? >> So my reaction to that that is pretty simple. Nobody gets there on their own at all, right? Passion and ambition can only take you so far. You've got to have people and teams that are supporting you. And here's the funny thing about people, and frankly, about being a leader that I think is really important: People don't follow for you. People follow for who you help them become. Think about that for a second. And when you think about all the amazing things that companies and teams are able to do, it's because of those people. And it's because you have leaders that are out there, inspiring them to take what they believe is impossible and turn it into the possible. That's the power of teams. >> Can you give an example of your approach on how you do that? How do you build your teams? How do you grow them? How do you lead them effectively and also make 'em inclusive, diverse and equitable? >> Whew. I'll give you a great example of some work that we're doing at AWS. This year at re:Invent, for the first time in its history, we've launched an initiative with theCUBE called Women of the Cloud. And part of Women of the Cloud is highlighting the business impact that so many of our partners, our customers and our employees have had on the social, on the economic and on the financials of many companies. They just haven't had the opportunity to tell their story. And at Amazon, right, it is absolutely integral to us to highlight those examples and continue to extend that ethos to our partners and our customers. And I think one of the things that I shared with you at re:Invent was, you know, as U2's Bono put it, (John laughs) "We'll build it better than we did before "and we are the people "that we've been waiting for." So if we're not out there, advocating and highlighting all the amazing things that other women are doing in the ecosystem, who will? >> Well, I've got to say, I want to give you props for that program. Not only was it groundbreaking, it's still running strong. And I saw some things on LinkedIn that were really impressive in its network effect. And I met at least half a dozen new people I never would have met before through some of that content interaction and engagement. And this is like the power of the current world. I mean, getting the voices out there creates momentum. And it's good for Amazon. It's not just personal brand building for my next job or whatever, you know, reason. It's sharing and it's attracting others, and it's causing people to connect and meet each other in that world. So it's still going strong. (laughs) And this program we did last year was part of Rachel Thornton, who's now at MessageBird, and Mary Camarata. They were the sponsors for this International Women's Day. They're not there anymore, so we decided we're going to do it again because the impact is so significant. We had the Amazon Education group on. It's amazing and it's free, and we've got to get the word out. I mean, talk about leveling up fast. You get in and you get trained and get certified, and there's a zillion jobs out (laughs) there in cloud, right, and partners. So this kind of leadership is really important. What was the key learnings that you've taken away and how do you extend this opportunity to nurture the talent out there in the field? Because when you throw the content out there from great leaders and practitioners and developers, it attracts other people. >> It does. It does. So look, I think there's two types of people, people that are focused on being and people who are focused on doing. And let me give you an example, right? When we think about labels of, hey, Rachel's a female executive who launched Women of the Cloud, that label really limits me. I'd rather just be a great executive. Or, hey, there's a great entrepreneur. Let's not be a great entrepreneur. Just go build something and sell it. And that's part of this whole Women of the cloud, is I don't want people focused on what their label is. I want people sharing their stories about what they're doing, and that's where the lasting impact happens, right? I think about something that my grandmother used to tell me, and she used to tell me, "Rachel, how successful "you are, doesn't matter. "The lasting impact that you have "is your legacy in this very finite time "that you have on Earth. "Leave a legacy." And that's what Women of the Cloud is about. So that people can start to say, "Oh, geez, "I didn't know that that was possible. "I didn't think about my career in that way." And, you know, all of those different types of stories that you're hearing out there. >> And I want to highlight something you said. We had another Amazonian on the program for this day earlier and she coined a term, 'cause inside Amazon, you have common language. One of them is bar raising. Raise the bar, that's an Amazonian (Rachel laughs) term. It means contribute and improve and raise the bar of capability. She said, "Bar raising is gender neutral. "The bar is a bar." And I'm like, wow, that was amazing. Now, that means your contribution angle there highlights that. What's the biggest challenge to get that mindset set in culture, in these- >> Oh. >> 'Cause it's that simple, contribution is neutral. >> It absolutely is neutral, but it's like I said earlier, I think so many times, people are focused on success and being a great leader versus what's the contribution I'm making and how am I doing as a leader, you know? And when it comes to a lot of the leadership principles that Amazon has, including bar raising, which means insisting on the highest standards, and then those standards continue to raise every single time. And what that is all about is having all of our employees figure out, how do I get better every single day, right? That's what it's about. It's not about being better than the peer next to you. It's about how do I become a better leader, a better human being than I was yesterday? >> Awesome. >> You know, I read this really cute quote and I think it really resonates. "You meditate to upgrade your software "and you work out to upgrade your hardware." And while it's important that we're all ourselves at work, we can't deny that a lot of times, ourselves still need that meditation or that workout. >> Well, I hope I don't have any zero days in my software out there, so, but I'm going to definitely work on that. I love that quote. I'm going to use that. Thank you very much. That was awesome. I got to ask you, I know you're really passionate about, and we've talked about this, around, so you're a great leader but you're also focused on what's behind you in the generation, pipelining women leaders, okay? Seats at the table, mentoring and sponsorship. What can we do to build a strong pipeline of leaders in technology and business? And where do you see the biggest opportunity to nurture the talent in these fields? >> Hmm, you know, that's great, great question. And, you know, I just read a "Forbes" article by another Amazonian, Tanuja Randery, who talked about, you know, some really interesting stats. And one of the stats that she shared was, you know, by 2030, less than 25% of tech specialists will be female, less than 25%. That's only a 6% growth from where we are in 2023, so in seven years. That's alarming. So we've really got to figure out what are the kinds of things that we're going to go do from an Amazon perspective to impact that? And one of the obvious starting points is showcasing tech careers to girls and young women, and talking openly about what a technology career looks like. So specifically at Amazon, we've got an AWS Git IT program that helps schools and educators bring in tech role models to show them what potential careers look like in tech. I think that's one great way that we can help build the pipeline, but once we get the pipeline, we also have to figure out how we don't let that pipeline leak. Meaning how do we keep women and, you know, young women on their tech career? And I think big part of that, John, is really talking about how hard it is, but it's also greater than you can ever imagine. And letting them see executives that are very authentic and will talk about, geez, you know, the challenges of COVID were a time of crisis and accelerated change, and here's what it meant to me personally and here's what we were able to solve professionally. These younger generations are all about social impact, they're about economic impact and they're about financial impact. And if we're not talking about all three of those, both from how AWS is leading from the front, but how its executives are also taking that into their personal lives, they're not going to want to go into tech. >> Yeah, and I think one of the things you mentioned there about getting people that get IT, good call out there, but also, Amazon's going to train 30 million people, put hundreds of millions of dollars into education. And not only are they making it easier to get in to get trained, but once you're in, even savvy folks that are in there still have to accelerate. And there's more ways to level up, more things are happening, but there's a big trend around people changing careers either in their late 20s, early 30s, or even those moments you talk about, where it's before and after, even later in the careers, 40s, 50s. Leaders like, well, good experience, good training, who were in another discipline who re-skilled. So you have, you know, more certifications coming in. So there's still other pivot points in the pipeline. It's not just down here. And that, I find that interesting. Are you seeing that same leadership opportunities coming in where someone can come into tech older? >> Absolutely. You know, we've got some amazing programs, like Amazon Returnity, that really focuses on how do we get other, you know, how do we get women that have taken some time off of work to get back into the workforce? And here's the other thing about switching careers. If I look back on my career, I started out as a civil engineer, heavy highway construction. And now I lead a sales team at the largest cloud company in the world. And there were, you know, twists and turns around there. I've always focused on how do we change and how do we continue to evolve? So it's not just focused on, you know, young women in the pipeline. It's focused on all gender and all diverse types throughout their career, and making sure that we're providing an inclusive environment for them to bring in their unique skillsets. >> Yeah, a building has good steel. It's well structured. Roads have great foundations. You know, you got the builder in you there. >> Yes. >> So I have to ask you, what's on your mind as a tech athlete, as an executive at AWS? You know, you got your huge team, big goals, the economy's got a little bit of a headwind, but still, cloud's transforming, edge is exploding. What's your outlook as you look out in the tech landscape these days and how are you thinking about it? What your plans? Can you share a little bit about what's on your mind? >> Sure. So, geez, there's so many trends that are top of mind right now. Everything from zero trust to artificial intelligence to security. We have more access to data now than ever before. So the opportunities are limitless when we think about how we can apply technology to solve some really difficult customer problems, right? Innovation sometimes feels like it's happening at a rapid pace. And I also say, you know, there are years when nothing happens, and then there's years when centuries happen. And I feel like we're kind of in those years where centuries are happening. Cloud technologies are refining sports as we know them now. There's a surge of innovation in smart energy. Everyone's supply chain is looking to transform. Custom silicon is going mainstream. And frankly, AWS's customers and partners are expecting us to come to them with a point of view on trends and on opportunities. And that's what differentiates us. (John laughs) That's what gives me goosebumps- >> I was just going to ask you that. Does that give you goosebumps? How could you not love technology with that excitement? I mean, AI, throw in AI, too. I just talked to Swami, who heads up the AI and database, and we just talked about the past 24 months, the change. And that is a century moment happening. The large language models, computer vision, more compute. Compute's booming than ever before. Who thought that was going to happen, is still happening? Massive change. So, I mean, if you're in tech, how can you not love tech? >> I know, even if you're not in tech, I think you've got to start to love tech because it gives you access to things you've never had before. And frankly, right, change is the only constant. And if you don't like change, you're going to like being irrelevant even less than you like change. So we've got to be nimble, we've got to adapt. And here's the great thing, once we figure it out, it changes all over again. And it's not something that's easy for any of us to operate. It's hard, right? It's hard learning new technology, it's hard figuring out what do I do next? But here's the secret. I think it's hard because we're doing it right. It's not hard because we're doing it wrong. It's just hard to be human and it's hard to figure out how we apply all this different technology in a way that positively impacts us, you know, economically, financially, environmentally and socially. >> And everyone's different, too. So you got to live those (mumbles). I want to get one more question in before we, my last question, which is about you and your impact. When you talk to your team, your sales, you got a large sales team, North America. And Tanuja, who you mentioned, is in EMEA, we're going to speak with her as well. You guys lead the front lines, helping customers, but also delivering the revenue to the company, which has been fantastic, by the way. So what's your message to the troops and the team out there? When you say, "Take that hill," like what is the motivational pitch, in a few sentences? What's the main North Star message in today's marketplace when you're doing that big team meeting? >> I don't know if it's just limited to a team meeting. I think this is a universal message, and the universal message for me is find your edge, whatever that may be. Whether it is the edge of what you know about artificial intelligence and neural networks or it's the edge of how do we migrate our applications to the cloud more quickly. Or it's the edge of, oh, my gosh, how do I be a better parent and still be great at work, right? Find your edge, and then sharpen it. Go to the brink of what you think is possible, and then force yourself to jump. Get involved. The world is run by the people that show up, professionally and personally. (John laughs) So show up and get started. >> Yeah as Steve Jobs once said, "The future "that everyone looks at was created "by people no smarter than you." And I love that quote. That's really there. Final question for you. I know we're tight on time, but I want to get this in. When you think about your impact on your company, AWS, and the industry, what's something you want people to remember? >> Oh, geez. I think what I want people to remember the most is it's not about what you've said, and this is a Maya Angelou quote. "It's not about what you've said to people "or what you've done, "it's about how you've made them feel." And we can all think back on leaders or we can all think back on personal moments in our lives where we felt like we belonged, where we felt like we did something amazing, where we felt loved. And those are the moments that sit with us for the rest of our lives. I want people to remember how they felt when they were part of something bigger. I want people to belong. It shouldn't be uncommon to talk about feelings at work. So I want people to feel. >> Rachel, thank you for your time. I know you're really busy and we stretched you a little bit there. Thank you so much for contributing to this wonderful day of great leaders sharing their stories. And you're an inspiration. Thanks for everything you do. We appreciate you. >> Thank you. And let's go do some more Women of the Cloud videos. >> We (laughs) got more coming. Bring those stories on. Back up the story truck. We're ready to go. Thanks so much. >> That's good. >> Thank you. >> Okay, this is theCUBE's coverage of International Women's Day. It's not just going to be March 8th. That's the big celebration day. It's going to be every quarter, more stories coming. Stay tuned at siliconangle.com and thecube.net here, with bringing all the stories. I'm John Furrier, your host. Thanks for watching. (gentle music)

(upbeat music) >> Hello, everyone. Welcome to theCUBE's special presentation of International Women's Day. I'm John Furrier, host of theCUBE. Jenni Troutman is here, Director of Products and Services, and Training and Certification at AWS, and Heather Ruden, Director of Education Programs, Training and Certification. Thanks for coming on theCUBE and for the International Women's Day special program. >> Thanks so much for having us. >> So, I'll just get it out of the way. I'm a big fan of what you guys do. I've been shouting at the top of my lungs, "It's free. Get cloud training and you'll have a six figure job." Pretty much. I'm over amplifying. But this is really a big opportunity in the industry, education and the skills gap, and the skill velocities that's changing. New roles are coming on around cloud native, cloud native operators, cybersecurity. There's so much excitement going on around the industry, and all these open positions, and they need new talent. So you can't get a degree for some of these things. So, nope, it doesn't matter what school you went to, everyone's kind of level. This is a really big deal. So, Heather, share with us your thoughts as well on this topic. Jenni, you too. Like, where are you guys at? 'Cause this is a big opportunity for women and anyone to level up in the industry. >> Absolutely. So I'll jump in and then I'll hand it over to Jenni. We're your dream team here. We can talk about both sides of this. So I run a set of programs here at AWS that are really intended to help build the next generation of cloud builders. And we do that with a variety of programs, whether it is targeting young learners from kind of 12 and up. We have AWS GetIT that is designed to get women ambassadors or women mentors in front of girls 12 to 14 and get them curious about a career in STEM. We also have a program that is all digital online. It's available in 11 languages. It's got hundreds of courses. That's called AWS Educate that is designed to do exactly what you just talked about, expose the opportunities and start building cloud skills for learners at age 13 and up. They can go online and register with an email and start learning. We want them to understand not only what the opportunity is for them, but the ways that they can help influence and bring more diversity and more inclusion and into the cloud technology space, and just keep building all those amazing builders that we need here for our customers and partners. And those are the programs that I manage, but Jenni also has an amazing program, a set of programs. And so I'll hand it over to her as you get into the professional side of this things. >> So Jenni, you're on the product side. You've got the keys to the kingdom on all the materials and shaping it. What's your view on this? 'Cause this is a huge opportunity and it's always changing. What's the latest and greatest? >> It is a massive opportunity and to give you a sense, there was a study in '21 where IT executives said that talent availability is the biggest challenge to emerging tech adoption. 64% of IT executives said that up from only 4% the year before. So the challenge is growing really fast, which for everyone that's ready to go out there and learn and try something new is a massive opportunity. And that's really why I'm here. We provide all kinds of learning experiences for people across different cloud technologies to be able to not only gain the knowledge around cloud, but also the confidence to be able to build in the cloud. And so we look across different learner levels, different roles, different opportunities, and we provide those experiences where people can actually get hands-on in a totally risk-free environment and practice building in the cloud so they can go and be ready to get their certifications, their AWS certifications, give them the credentials to be able to show an employer they can do it, and then go out and get these jobs. It's really exciting. And we go kind of end to end from the very beginning. What is cloud? I want to know what it is all the way through to I can prove that I can build in the cloud and I'm ready for a job. >> So Jenni, you nailed that confidence word. I think I want to double click on that. And Heather, you talked about you're the dream team. You guys, you're the go to market, you bring this to the marketplace. Jenni, you get the products. This is the key, but to me the the international women days angle is, is that what I hear over and over again is that, "It's too technical. I'm not qualified." It can be scary. We had a guest on who has two double E degrees in robotics and aerospace and she's hard charging. She almost lost her confidence twice she said in her career. But she was hard charging. It can get scary, but also the ability to level up fast is just as good. So if you can break through that confidence and keep the curiosity and be a builder, talk about that dynamic 'cause you guys are in the middle of it, you're in the industry, how do you handle that? 'Cause I think that's a big thing that comes up over and over again. And confidence is not just women, it's men too. But women can always, that comes up as a theme. >> It is. It is a big challenge. I mean, I've struggled with it personally and I mentor a lot of women and that is the number one challenge that is holding women back from really being able to advance is the confidence to step out there and show what they can do. And what I love about some of the products we've put out recently is we have AWS Skill Builder. You can go online, you can get all kinds of free core training and if you want to go deeper, you can go deeper. And there's a lot of different options on there. But what it does is not only gives you that based knowledge, but you can actually go in. We have something called AWS Labs. You can go in and you can actually practice on the AWS console with the services that people are using in their jobs every day without any risk of doing something that is going to blow up in your face. You're not going to suddenly get this big AWS bill. You're not going to break something that's out there running. You just go in. It's your own little environment that gets wiped when you're done and you can practice. And there's lots of different ways to learn as well. So if you go in there and you're watching a video and to your point you're like, "Oh my gosh, this is too technical. I can't understand it. I don't know what I'm going to go do." You can go another route. There's something called AWS Cloud Quest. It's a game. You go in and it's like you're gaming and it walks you through. You're actually in a virtual world. You're walking through and it's telling you, "Hey, go build this and if you need help, here's hints and here's tips." And it continues to build on itself. So you're learning and you're applying practical skills and it's at your own pace. You don't have to watch somebody else talking that is going at a pace that maybe accelerates beyond what you're ready. You can do it at your own pace, you can redo it, you can try it again until you feel confident that you know it and you're really ready to move on to the next thing. Personally, I find that hugely valuable. I go in and do these myself and I sit there and I have a lot of engineers on my team, very smart people. And I have my own imposter syndrome. I get nervous to go talk to them. Like, are they going to think I'm totally lost? And so I go in and I learn some of this myself by experiment. And then I feel like, okay, now I can go ask them some intelligent questions and they're not going to be like, "Oh gosh, my leader is totally unaware of what we're doing." And so I think that we all struggle with confidence. I think everybody does, but I see it especially in women as I mentor them. And that's what I encourage them to do is go and on your own time, practice a bit, get a little bit of experience and once you feel like you can throw a couple words out there that you know what they mean and suddenly other people look at you like, "Oh, she knows what she's talking about." And you can kind of get past that feeling. >> Well Jenni, you nailed it. Heather, she just mentioned she's in the job and she's going and she's still leveling up. That's the end when you're in, but it's also the barriers to entry are lowering. You guys are doing a good job of getting people in, but also growing fast too. So there's two dynamics at play here. How do people do this? What's the playbook? Because I think that's really key, easy to get in. And then once you're in, you can level up fast at your own pace to ride the wave. And then there's new stuff coming. I mean, every re:Invent there's 5,000 announcements. So it's like zillion new things and AI taught now. >> re:Invent is a perfect example of that ongoing imposter syndrome or confidence check for all of us. I think something that that Jenni said too is we really try and meet learners where they are and make sure that we have the support, whether it's accessibility requirements or we have the content that is built for the age that we're talking to, or we have a workforce development program called re/Start that is for people that have very little tech experience and really want to talk about a career in cloud, but they need a little bit more handholding. They need a combination of instructor-led and digital. But then we have AWS educators, I mentioned. If you want to be more self-directed, all of these tools are intended to work well together and to be complimentary and to take you on a journey as a learner. And the more skills you have, the more you increase your knowledge, the more you can take on more. But meeting folks where they are with a variety of programs, tools, languages, and accessibility really helps ensure that we can do that for learners throughout the world. >> That's awesome. Let's get into it. Let's get into the roadmaps of people and their personas. And you guys can share the programs that you have and where people could fit in. 'Cause this comes up a lot when I talk to folks. There's the young person who's I'm a gamer or whatever, I want to get a job. I'm in high school or an elementary or I want to tinker around or I'm in college or I'm learning, I'm an entry level kind of entry. Then you have the re-skilling. I'm going to change my careers, I'm kind of bored, I want to do something compelling. How do I get into the cloud game? And then the advanced re-skill is I want to get into cyber and AI and then there's other. Could you break down? Did I get that right or did I miss anything? And then what's available for those kind of lanes? So those persona lanes? >> Well, let's see, I could start with maybe the high schooler stuff and then we can bring Jenni in as well. I would say a great place to start for anyone is aws.amazon.com/training. That's going to give them the full suite of options that they could take on. If you're in high school, you can go onto AWS Educate. All you need is an email. And if you're 13 years and older, you can start exploring the types of jobs that are available in the cloud and you could start taking some introductory classes. You can do some of those labs in a safe environment that Jenni mentioned. That's a great place to start. If you are in an environment where you have an educator that is willing to go on this with you, this journey with you, we have this AWS GetIT program that is, again, educator-led. So it's an afterschool or it's an a program where we match mentors and students up with cloud professionals and they do some real-time experimentation. They build an app, they work on things together, and do a presentation at the end. The other thing I would say too is that if you are in a university, I would double check and see if the AWS Academy curriculum is already in your university. And if so, explore some of those classes there. We have instructor-led, educator-ready. course curriculum that we've designed that help people get to those certifications and get closer to those jobs and as well as hopefully then lead people right into skill builder and all the things that Jenni talked about to help them as they start out in a professional environment. >> So is the GetIT, is that an instructor-led that the person has to find someone for? Or is this available for them? >> It is through teachers. It's through educators. We are in, we've reached over 19,000 students. We're available in eight countries. There are ways for educators to lead this, but we want to make sure that we are helping the kids be successful and giving them an educator environment to do that. If they want to do it on their own, then they can absolutely go through AWS Educate or even and to explore where they want to get started. >> So what about someone who's educated in their middle of their career, might want to switch from being a biologist to a cloud cybersecurity guru or a cloud native operator? >> Yeah, so in that case, AWS re/Start is one of the great program for them to explore. We run that program with collaborating organizations in 160 cities in 80 countries throughout the world. That is a multi-week cohort-based program where we do take folks through a very clear path towards certification and job skilling that will help them get into those opportunities. Over 98% of the cohorts, the graduates of those cohorts get an interview and are hopefully on their path to getting a job. So that really has global reach. The partnership with collaborating organizations helps us ensure that we find communities that are often unreached by cloud skills training and we really work to keep a diverse focus on those cohorts and bring those folks into the cloud. >> Okay. Jenni, you've got the Skill Builder action here. What's going on on your side? Because you must have to manage all the change. I mean, AI is hot right now. I'm sure you're cranking away on curriculum and content for SageMaker, large language models, computer vision, cybersecurity. >> We do. There are a lot of options. >> How is your world? Tell us about what people can take out of way from your side. >> Yeah. So a great way to think about it is if they're already out in the workforce or they're entering the workforce, but they are technical, have technical skills is what are the roles that are interesting in the technologies that are interesting. Because the way we put out our training and our certifications is aligned to paths. So if you're look interested in a specific role. If you're interested in architecting a cloud environment or in security as you mentioned, and you want to go deep in security, there are AWS certifications that give you that. If you achieve them, they're very difficult. But if you work to them and achieve them, they give you the credential that you can take to an employer and say, "Look, I can do this job." And they are in very high demand. In fact that's where if you look at some of the publications that have come out, they talk about, what are people making if they have different certifications? What are the most in-demand certifications that are out there? And those are what help people get jobs. And so you identify what is that role or that technology area I want to learn. And then you have multiple options for how you build those skills depending on how you want to learn. And again, that's really our focus, is on providing experiences based on how people learn and making it accessible to them. 'Cause not everybody wants to learn in the same way. And so there is AWS Skill Builder where people can go learn on their own that is really great particularly for people who maybe are already working and have to learn in the evenings, on the weekends. People who like to learn at their own pace, who just want to be hands-on, but are self-starters. And they can get those whole learning plans through there all the way aligned to the certification and then they can go get their certification. There's also classroom training. So a lot of people maybe want to do continuous learning through an online, but want to go really deep with an expert in the room and maybe have a more focused period of time if they can go for a couple days. And so they can do classroom training. We provide a lot of classroom training. We have partners all over the globe who provide classroom training. And so there's that and what we find to be the most powerful is when you couple the two. If you can really get deep, you have an expert, you can ask questions, but first before you go do that, you get some of that foundational that you've kind of learned on your own. And then after you go back and reinforce, you go back online, you try out things that maybe you learned in the classroom, but you didn't quite, you hadn't used it enough yet to quite know how to do it. Now you can go back and actually use it, experiment and play around. And so we really encourage that kind of, figure out what are some areas you're interested in, go learn it and then go get a job and continue to learn because then once you learn that first area, you start to build confidence in it. Suddenly other areas become interesting. 'Cause as you said, cloud is changing fast. And once you learn a space, first of all you have to keep going back to stay up on it as it changes. But you quickly find that there are other areas that are really interesting too. >> I've observed that the training side, it's just like cloud itself, it's very agile. You can get hands-on quickly, you don't need to take a class, and then get in weeks later. You're in it like it's real time. So you're immersed in gamification and all kinds of ways to funnel into the either advanced tracks and certification. So you guys do a great job and I want to give you props for that and a shout out. The question I have for you guys is can you scope the opportunity for these certifications and opportunities for women in particular? What are some of the top jobs pulling down? Scope out the opportunity because I think when people hear that they really fall out of their chair, they go, "Wow, I didn't know I could make $200,000 doing cybersecurity." Well, yeah or maybe more. I just made the number, I don't actually know, but like I know people do make that much in cyber, but there are huge financial opportunities with certifications and education. Can you scope that order of magnitude? Can you share any data? >> Yeah, so in the US they certainly are. Certifications on average aligned to six digit type jobs. And if you go out and do a search, there are research studies out there that are refreshed every year that say what are the top IT industry certifications and how much money do they make? And the reason I don't put a number out there is because it's constantly changing and in fact it keeps going up, >> It's going up, not going down. >> But I would encourage people to do that quick search. What are the top IT industry certifications. Again, based on the country you're in, it makes a difference. But if you're US, there's a lot of data out there for the US and then there is some for other countries as well around how much on average people make. >> Do you list like the higher level certifications, stack rank them in terms of order? Like say, I'm a type A personnel, I want to climb Mount Everest, I want to get the highest level certification. How do I know that? Is it like laddered up or is like how do you guys present that? >> Yeah, so we have different types of certifications. There is a foundational, which we call the cloud practitioner. That one is more about just showing that you know something about cloud. It's not aligned to a specific job role. But then we have what we call associate level certifications, which are aligned to roles. So there's the solutions architect, cloud developer, so developer operations. And so you can tell by the role and associate is kind of that next level. And then the roles often have a professional level, which is even more advanced. And basically that's saying you're kind of an Uber expert at that point. And then there are technology specialties, which are less about a specific role, although some would argue a security technology specialty might align very well to a security role, but they're more about showing the technology. And so typically, it goes foundational, advanced, professional, and then the specialties are more on the side. They're not aligned, but they're deep. They're deep within that area. >> So you can go dig and pick your deep dive and jump into where you're comfortable. Heather, talk about the commitment in terms of dollars. I know Amazon's flaunted some numbers like 30 million or something, people they want to have trained, hundreds of millions of dollars in investment. This is key, obviously, more people trained on cloud, more operators, more cloud usage, obviously. I see the business connection. What's the women relationship to the numbers? Or what the experience is? How do you guys see that? Obviously International Women's Day, get the confidence, got the curiosity. You're a builder, you're in. It's that easy. >> It doesn't always feel that way, I'm sure to everybody, but we'd like to think that it is. Amazon and AWS do invest hundreds of millions of dollars in free training every year that is accessible to everyone out there. I think that sometimes the hardest obstacles to get overcome are getting started and we try and make it as easy as possible to get started with the tools that we've talked about already today. We run into plenty of cohorts of women as part of our re/Start program that are really grateful for the opportunity to see something, see a new way of thinking, see a new opportunity for them. We don't necessarily break out our funding by women versus men. We want to make sure that we are open and diverse for everybody to come in and get the training that they need to. But we definitely want to make sure that we are accessible and available to women and all genders outside of the US and inside the US. >> Well, I know the number's a lot lower than they should be and that's obviously why we're promoting this heavily. There's a lot more interest I see in tech. So digital transformation is gender neutral. I mean, it's like the world eats software and uses software, uses the cloud. So it has to get 50/50 in my opinion. So you guys do a great job. Now that we're done kind of promoting Amazon, which I wanted to do 'cause I think it's super important. Let's talk about you guys. What got you guys involved in tech? What was the inspiration and share some stories about your experiences and advice for folks watching? >> So I've always been in traditionally male dominated roles. I actually started in aviation and then moved to tech. And what I found was I got a mentor early on, a woman who was senior to me and who was kind of who I saw as the smartest person out there. She was incredibly smart, she was incredibly kind, and she was always lifting women up. And I kind of latched onto her and followed her around and she was such an amazing mentor. She brought me from throughout tech, from company to company, job to job, was always positioning me in front of other people as the go-to person. And I realized, "Wow, I want to be like her." And so that's been my focus as well in tech is you can be deeply technical in tech or you can be not deeply technical and be in tech and you can be successful both ways, but the way you're going to be most successful is if you find other people, build them up and help put them out in front. And so I personally love to mentor women and to put them in places where they can feel comfortable being out in front of people. And that's really been my career. I have tried to model her approach as much as I can. >> That's a really interesting observation. It's the pattern we've been seeing in all these interviews for the past two years of doing the International Women's Day is that networking, mentoring and sponsorship are one thing. So it's all one thing. It's not just mentoring. It's like people think, "Oh, just mentoring. What does that mean? Advice?" No, it's sponsorship, it's lifting people up, creating a keiretsu, creating networks. Really important. Heather, what's your experience? >> Yeah, I'm sort of the example of somebody who never thought they'd be in tech, but I happened to graduate from college in the Silicon Valley in the early nineties and next thing you know, it's more than a couple years later and I'm deeply in tech and I think it when we were having the conversation about confidence and willingness to learn and try that really spoke to me as well. I think I had to get out of my own way sometimes and just be willing to not be the smartest person in the room and just be willing to ask a lot of questions. And with every opportunity to ask questions, I think somebody, I ended up with good mentors, male and female, that saw the willingness to ask questions and the willingness to be humble in my approach to learning. And that really helped. I'm also very aware that nobody's journey is the same and I need to create an environment on my team and I need to be a role model within AWS and Amazon for allowing people to show up in the way that they're going to be most successful. And sometimes that will mean giving them learning opportunities. Sometimes that will be hooking them up with a mentor. Sometimes that will be giving them the freedom to do what they need for their family or their personal life. And modeling that behavior regardless of gender has always been how I choose to show up and what I ask my leaders to do. And the more we can do that, I've seen the team been able to grow and flourish in that way and support our entire team. >> I love that story. You also have a great leader, Maureen Lonergan, who I've met many conversations with, but also it starts at the top. Andy Jassy who can come across, he's kind of technical, he's dirty, he's a builder mentality. He has first principles and you're bringing up this first principles concept and whether that's passing it forward, what you've learned, having first principles helps in an organization. Can you guys talk about what that's like at your company? 'Cause everyone's different. And sometimes whether, and I sometimes I worry about what I say, but I also have my first principles. So talk about how principles matter in how you guys interface with others and letting people be their authentic self. >> Yeah, I'll jump in Jenni and then you can. The Amazon leadership principles are super important to how we interact with each other and it really does provide a set of guidelines for how we work with each other and how we work for our customers and with our partners. But most of all it gives us a common language and a common set of expectations. And I will be honest, they're not always easy. When you come from an environment that tends to be less open to feedback and less open to direct conversations than you find at Amazon, it could take a while to get used to that, but for me at least, it was extremely empowering to have those tools and those principles as guidance for how to operate and to gain the confidence in using them. I've also been able to participate in hundreds and hundreds of interviews in the time that I've been here as part of an interview team of bar raisers. I think that really helps us understand whether or not folks are going to be successful at AWS and at Amazon and helps them understand if they're going to be able to be successful. >> Bar raising is an Amazon term and it's gender neutral, right Jenni? >> It is gender neutral. >> Bar is a bar, it raises. >> That's right. And it's funny, we say that our culture here is peculiar. And when I started, I had been in consulting for several years, so I worked with a lot of different companies in tech and so I thought I'd seen everything and I came here and I went, "Hmm." I see what they mean by peculiar. It is very different environment. >> In the fullness of time, it'll all work out. >> That's right, that's right. Well and it's funny because when you first started, it's a lot to figure out to how to operate in an environment where people do use a 16 leadership principles. I've worked at a lot of companies with three or four core values and nobody can state those. We could state all 16 leadership principles and we use them in our regular everyday dialogue. That is an awkward thing when you first come to have people saying, "Oh, I'm going to use bias for action in this situation and I'm going to go move fast. And they're actually used in everyday conversations. But after a couple years suddenly you realize, "Oh, I'm doing that." And maybe even sometimes at the dinner table I'm doing that, which can get to be a bit much. But it creates an environment where we can all be different. We can all think differently. We can all have different ways of doing things, but we have a common overall approach to what we're trying to achieve. And that's really, it gives us a good framework for that. >> Jenni, it's great insight. Heather, thank you so much for sharing your stories. We're going to do this not once a year. We're going to continue this Women in Tech program every quarter. We'll check in with you guys and find out what's new. And thank you for what you do. We appreciate that getting the word out and really is an opportunity for everyone with education and cloud and it's only going to get more opportunities at the edge in AI and so much more tech. Thank you for coming on the program. >> Thank you for having us. >> Thanks, John. >> Thank you. That's the International Women's Day segment here with leaders from AWS. I'm John Furrier. Thanks for watching. (upbeat musiC)

(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. As you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications and data workloads resilient on the cloud?" Meaning  how is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep. >> Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - There's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(gentle music) >> Narrator: "TheCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hello everybody, welcome back to day four of "theCUBE's" coverage of MWC '23. We're here live at the Fira in Barcelona. Wall-to-wall coverage, John Furrier is in our Palo Alto studio, banging out all the news. Really, the whole week we've been talking about the disaggregation of the telco network, the new opportunities in telco. We're really excited to have AT&T and Snowflake here. Dave Whittington is the AVP, at the Chief Data Office at AT&T. Roddy Tranum is the Assistant Vice President, for Channel Performance Data and Tools at AT&T. And Phil Kippen, the Global Head Of Industry-Telecom at Snowflake, Snowflake's new telecom business. Snowflake just announced earnings last night. Typical Scarpelli, they beat earnings, very conservative guidance, stocks down today, but we like Snowflake long term, they're on that path to 10 billion. Guys, welcome to "theCUBE." Thanks so much >> Phil: Thank you. >> for coming on. >> Dave and Roddy: Thanks Dave. >> Dave, let's start with you. The data culture inside of telco, We've had this, we've been talking all week about this monolithic system. Super reliable. You guys did a great job during the pandemic. Everything shifting to landlines. We didn't even notice, you guys didn't miss a beat. Saved us. But the data culture's changing inside telco. Explain that. >> Well, absolutely. So, first of all IoT and edge processing is bringing forth new and exciting opportunities all the time. So, we're bridging the world between a lot of the OSS stuff that we can do with edge processing. But bringing that back, and now we're talking about working, and I would say traditionally, we talk data warehouse. Data warehouse and big data are now becoming a single mesh, all right? And the use cases and the way you can use those, especially I'm taking that edge data and bringing it back over, now I'm running AI and ML models on it, and I'm pushing back to the edge, and I'm combining that with my relational data. So that mesh there is making all the difference. We're getting new use cases that we can do with that. And it's just, and the volume of data is immense. >> Now, I love ChatGPT, but I'm hoping your data models are more accurate than ChatGPT. I never know. Sometimes it's really good, sometimes it's really bad. But enterprise, you got to be clean with your AI, don't you? >> Not only you have to be clean, you have to monitor it for bias and be ethical about it. We're really good about that. First of all with AT&T, our brand is Platinum. We take care of that. So, we may not be as cutting-edge risk takers as others, but when we go to market with an AI or an ML or a product, it's solid. >> Well hey, as telcos go, you guys are leaning into the Cloud. So I mean, that's a good starting point. Roddy, explain your role. You got an interesting title, Channel Performance Data and Tools, what's that all about? >> So literally anything with our consumer, retail, concenters' channels, all of our channels, from a data perspective and metrics perspective, what it takes to run reps, agents, all the way to leadership levels, scorecards, how you rank in the business, how you're driving the business, from sales, service, customer experience, all that data infrastructure with our great partners on the CDO side, as well as Snowflake, that comes from my team. >> And that's traditionally been done in a, I don't mean the pejorative, but we're talking about legacy, monolithic, sort of data warehouse technologies. >> Absolutely. >> We have a love-hate relationship with them. It's what we had. It's what we used, right? And now that's evolving. And you guys are leaning into the Cloud. >> Dramatic evolution. And what Snowflake's enabled for us is impeccable. We've talked about having, people have dreamed of one data warehouse for the longest time and everything in one system. Really, this is the only way that becomes a reality. The more you get in Snowflake, we can have golden source data, and instead of duplicating that 50 times across AT&T, it's in one place, we just share it, everybody leverages it, and now it's not duplicated, and the process efficiency is just incredible. >> But it really hinges on that separation of storage and compute. And we talk about the monolithic warehouse, and one of the nightmares I've lived with, is having a monolithic warehouse. And let's just go with some of my primary, traditional customers, sales, marketing and finance. They are leveraging BSS OSS data all the time. For me to coordinate a deployment, I have to make sure that each one of these units can take an outage, if it's going to be a long deployment. With the separation of storage, compute, they own their own compute cluster. So I can move faster for these people. 'Cause if finance, I can implement his code without impacting finance or marketing. This brings in CI/CD to more reality. It brings us faster to market with more features. So if he wants to implement a new comp plan for the field reps, or we're reacting to the marketplace, where one of our competitors has done something, we can do that in days, versus waiting weeks or months. >> And we've reported on this a lot. This is the brilliance of Snowflake's founders, that whole separation >> Yep. >> from compute and data. I like Dave, that you're starting with sort of the business flexibility, 'cause there's a cost element of this too. You can dial down, you can turn off compute, and then of course the whole world said, "Hey, that's a good idea." And a VC started throwing money at Amazon, but Redshift said, "Oh, we can do that too, sort of, can't turn off the compute." But I want to ask you Phil, so, >> Sure. >> it looks from my vantage point, like you're taking your Data Cloud message which was originally separate compute from storage simplification, now data sharing, automated governance, security, ultimately the marketplace. >> Phil: Right. >> Taking that same model, break down the silos into telecom, right? It's that same, >> Mm-hmm. >> sorry to use the term playbook, Frank Slootman tells me he doesn't use playbooks, but he's not a pattern matcher, but he's a situational CEO, he says. But the situation in telco calls for that type of strategy. So explain what you guys are doing in telco. >> I think there's, so, what we're launching, we launched last week, and it really was three components, right? So we had our platform as you mentioned, >> Dave: Mm-hmm. >> and that platform is being utilized by a number of different companies today. We also are adding, for telecom very specifically, we're adding capabilities in marketplace, so that service providers can not only use some of the data and apps that are in marketplace, but as well service providers can go and sell applications or sell data that they had built. And then as well, we're adding our ecosystem, it's telecom-specific. So, we're bringing partners in, technology partners, and consulting and services partners, that are very much focused on telecoms and what they do internally, but also helping them monetize new services. >> Okay, so it's not just sort of generic Snowflake into telco? You have specific value there. >> We're purposing the platform specifically for- >> Are you a telco guy? >> I am. You are, okay. >> Total telco guy absolutely. >> So there you go. You see that Snowflake is actually an interesting organizational structure, 'cause you're going after verticals, which is kind of rare for a company of your sort of inventory, I'll say, >> Absolutely. >> I don't mean that as a negative. (Dave laughs) So Dave, take us through the data journey at AT&T. It's a long history. You don't have to go back to the 1800s, but- (Dave laughs) >> Thank you for pointing out, we're a 149-year-old company. So, Jesse James was one of the original customers, (Dave laughs) and we have no longer got his data. So, I'll go back. I've been 17 years singular AT&T, and I've watched it through the whole journey of, where the monolithics were growing, when the consolidation of small, wireless carriers, and we went through that boom. And then we've gone through mergers and acquisitions. But, Hadoop came out, and it was going to solve all world hunger. And we had all the aspects of, we're going to monetize and do AI and ML, and some of the things we learned with Hadoop was, we had this monolithic warehouse, we had this file-based-structured Hadoop, but we really didn't know how to bring this all together. And we were bringing items over to the relational, and we were taking the relational and bringing it over to the warehouse, and trying to, and it was a struggle. Let's just go there. And I don't think we were the only company to struggle with that, but we learned a lot. And so now as tech is finally emerging, with the cloud, companies like Snowflake, and others that can handle that, where we can create, we were discussing earlier, but it becomes more of a conducive mesh that's interoperable. So now we're able to simplify that environment. And the cloud is a big thing on that. 'Cause you could not do this on-prem with on-prem technologies. It would be just too cost prohibitive, and too heavy of lifting, going back and forth, and managing the data. The simplicity the cloud brings with a smaller set of tools, and I'll say in the data space specifically, really allows us, maybe not a single instance of data for all use cases, but a greatly reduced ecosystem. And when you simplify your ecosystem, you simplify speed to market and data management. >> So I'm going to ask you, I know it's kind of internal organizational plumbing, but it'll inform my next question. So, Dave, you're with the Chief Data Office, and Roddy, you're kind of, you all serve in the business, but you're really serving the, you're closer to those guys, they're banging on your door for- >> Absolutely. I try to keep the 130,000 users who may or may not have issues sometimes with our data and metrics, away from Dave. And he just gets a call from me. >> And he only calls when he has a problem. He's never wished me happy birthday. (Dave and Phil laugh) >> So the reason I asked that is because, you describe Dave, some of the Hadoop days, and again love-hate with that, but we had hyper-specialized roles. We still do. You've got data engineers, data scientists, data analysts, and you've got this sort of this pipeline, and it had to be this sequential pipeline. I know Snowflake and others have come to simplify that. My question to you is, how is that those roles, how are those roles changing? How is data getting closer to the business? Everybody talks about democratizing business. Are you doing that? What's a real use example? >> From our perspective, those roles, a lot of those roles on my team for years, because we're all about efficiency, >> Dave: Mm-hmm. >> we cut across those areas, and always have cut across those areas. So now we're into a space where things have been simplified, data processes and copying, we've gone from 40 data processes down to five steps now. We've gone from five steps to one step. We've gone from days, now take hours, hours to minutes, minutes to seconds. Literally we're seeing that time in and time out with Snowflake. So these resources that have spent all their time on data engineering and moving data around, are now freed up more on what they have skills for and always have, the data analytics area of the business, and driving the business forward, and new metrics and new analysis. That's some of the great operational value that we've seen here. As this simplification happens, it frees up brain power. >> So, you're pumping data from the OSS, the BSS, the OKRs everywhere >> Everywhere. >> into Snowflake? >> Scheduling systems, you name it. If you can think of what drives our retail and centers and online, all that data, scheduling system, chat data, call center data, call detail data, all of that enters into this common infrastructure to manage the business on a day in and day out basis. >> How are the roles and the skill sets changing? 'Cause you're doing a lot less ETL, you're doing a lot less moving of data around. There were guys that were probably really good at that. I used to joke in the, when I was in the storage world, like if your job is bandaging lungs, you need to look for a new job, right? So, and they did and people move on. So, are you able to sort of redeploy those assets, and those people, those human resources? >> These folks are highly skilled. And we were talking about earlier, SQL hasn't gone away. Relational databases are not going away. And that's one thing that's made this migration excellent, they're just transitioning their skills. Experts in legacy systems are now rapidly becoming experts on the Snowflake side. And it has not been that hard a transition. There are certainly nuances, things that don't operate as well in the cloud environment that we have to learn and optimize. But we're making that transition. >> Dave: So just, >> Please. >> within the Chief Data Office we have a couple of missions, and Roddy is a great partner and an example of how it works. We try to bring the data for democratization, so that we have one interface, now hopefully know we just have a logical connection back to these Snowflake instances that we connect. But we're providing that governance and cleansing, and if there's a business rule at the enterprise level, we provide it. But the goal at CDO is to make sure that business units like Roddy or marketing or finance, that they can come to a platform that's reliable, robust, and self-service. I don't want to be in his way. So I feel like I'm providing a sub-level of platform, that he can come to and anybody can come to, and utilize, that they're not having to go back and undo what's in Salesforce, or ServiceNow, or in our billers. So, I'm sort of that layer. And then making sure that that ecosystem is robust enough for him to use. >> And that self-service infrastructure is predominantly through the Azure Cloud, correct? >> Dave: Absolutely. >> And you work on other clouds, but it's predominantly through Azure? >> We're predominantly in Azure, yeah. >> Dave: That's the first-party citizen? >> Yeah. >> Okay, I like to think in terms sometimes of data products, and I know you've mentioned upfront, you're Gold standard or Platinum standard, you're very careful about personal information. >> Dave: Yeah. >> So you're not trying to sell, I'm an AT&T customer, you're not trying to sell my data, and make money off of my data. So the value prop and the business case for Snowflake is it's simpler. You do things faster, you're in the cloud, lower cost, et cetera. But I presume you're also in the business, AT&T, of making offers and creating packages for customers. I look at those as data products, 'cause it's not a, I mean, yeah, there's a physical phone, but there's data products behind it. So- >> It ultimately is, but not everybody always sees it that way. Data reporting often can be an afterthought. And we're making it more on the forefront now. >> Yeah, so I like to think in terms of data products, I mean even if the financial services business, it's a data business. So, if we can think about that sort of metaphor, do you see yourselves as data product builders? Do you have that, do you think about building products in that regard? >> Within the Chief Data Office, we have a data product team, >> Mm-hmm. >> and by the way, I wouldn't be disingenuous if I said, oh, we're very mature in this, but no, it's where we're going, and it's somewhat of a journey, but I've got a peer, and their whole job is to go from, especially as we migrate from cloud, if Roddy or some other group was using tables three, four and five and joining them together, it's like, "Well look, this is an offer for data product, so let's combine these and put it up in the cloud, and here's the offer data set product, or here's the opportunity data product," and it's a journey. We're on the way, but we have dedicated staff and time to do this. >> I think one of the hardest parts about that is the organizational aspects of it. Like who owns the data now, right? It used to be owned by the techies, and increasingly the business lines want to have access, you're providing self-service. So there's a discussion about, "Okay, what is a data product? Who's responsible for that data product? Is it in my P&L or your P&L? Somebody's got to sign up for that number." So, it sounds like those discussions are taking place. >> They are. And, we feel like we're more the, and CDO at least, we feel more, we're like the guardians, and the shepherds, but not the owners. I mean, we have a role in it all, but he owns his metrics. >> Yeah, and even from our perspective, we see ourselves as an enabler of making whatever AT&T wants to make happen in terms of the key products and officers' trade-in offers, trade-in programs, all that requires this data infrastructure, and managing reps and agents, and what they do from a channel performance perspective. We still ourselves see ourselves as key enablers of that. And we've got to be flexible, and respond quickly to the business. >> I always had empathy for the data engineer, and he or she had to service all these different lines of business with no business context. >> Yeah. >> Like the business knows good data from bad data, and then they just pound that poor individual, and they're like, "Okay, I'm doing my best. It's just ones and zeros to me." So, it sounds like that's, you're on that path. >> Yeah absolutely, and I think, we do have refined, getting more and more refined owners of, since Snowflake enables these golden source data, everybody sees me and my organization, channel performance data, go to Roddy's team, we have a great team, and we go to Dave in terms of making it all happen from a data infrastructure perspective. So we, do have a lot more refined, "This is where you go for the golden source, this is where it is, this is who owns it. If you want to launch this product and services, and you want to manage reps with it, that's the place you-" >> It's a strong story. So Chief Data Office doesn't own the data per se, but it's your responsibility to provide the self-service infrastructure, and make sure it's governed properly, and in as automated way as possible. >> Well, yeah, absolutely. And let me tell you more, everybody talks about single version of the truth, one instance of the data, but there's context to that, that we are taking, trying to take advantage of that as we do data products is, what's the use case here? So we may have an entity of Roddy as a prospective customer, and we may have a entity of Roddy as a customer, high-value customer over here, which may have a different set of mix of data and all, but as a data product, we can then create those for those specific use cases. Still point to the same data, but build it in different constructs. One for marketing, one for sales, one for finance. By the way, that's where your data engineers are struggling. >> Yeah, yeah, of course. So how do I serve all these folks, and really have the context-common story in telco, >> Absolutely. >> or are these guys ahead of the curve a little bit? Or where would you put them? >> I think they're definitely moving a lot faster than the industry is generally. I think the enabling technologies, like for instance, having that single copy of data that everybody sees, a single pane of glass, right, that's definitely something that everybody wants to get to. Not many people are there. I think, what AT&T's doing, is most definitely a little bit further ahead than the industry generally. And I think the successes that are coming out of that, and the learning experiences are starting to generate momentum within AT&T. So I think, it's not just about the product, and having a product now that gives you a single copy of data. It's about the experiences, right? And now, how the teams are getting trained, domains like network engineering for instance. They typically haven't been a part of data discussions, because they've got a lot of data, but they're focused on the infrastructure. >> Mm. >> So, by going ahead and deploying this platform, for platform's purpose, right, and the business value, that's one thing, but also to start bringing, getting that experience, and bringing new experience in to help other groups that traditionally hadn't been data-centric, that's also a huge step ahead, right? So you need to enable those groups. >> A big complaint of course we hear at MWC from carriers is, "The over-the-top guys are killing us. They're riding on our networks, et cetera, et cetera. They have all the data, they have all the client relationships." Do you see your client relationships changing as a result of sort of your data culture evolving? >> Yes, I'm not sure I can- >> It's a loaded question, I know. >> Yeah, and then I, so, we want to start embedding as much into our network on the proprietary value that we have, so we can start getting into that OTT play, us as any other carrier, we have distinct advantages of what we can do at the edge, and we just need to start exploiting those. But you know, 'cause whether it's location or whatnot, so we got to eat into that. Historically, the network is where we make our money in, and we stack the services on top of it. It used to be *69. >> Dave: Yeah. >> If anybody remembers that. >> Dave: Yeah, of course. (Dave laughs) >> But you know, it was stacked on top of our network. Then we stack another product on top of it. It'll be in the edge where we start providing distinct values to other partners as we- >> I mean, it's a great business that you're in. I mean, if they're really good at connectivity. >> Dave: Yeah. >> And so, it sounds like it's still to be determined >> Dave: Yeah. >> where you can go with this. You have to be super careful with private and for personal information. >> Dave: Yep. >> Yeah, but the opportunities are enormous. >> There's a lot. >> Yeah, particularly at the edge, looking at, private networks are just an amazing opportunity. Factories and name it, hospital, remote hospitals, remote locations. I mean- >> Dave: Connected cars. >> Connected cars are really interesting, right? I mean, if you start communicating car to car, and actually drive that, (Dave laughs) I mean that's, now we're getting to visit Xen Fault Tolerance people. This is it. >> Dave: That's not, let's hold the traffic. >> Doesn't scare me as much as we actually learn. (all laugh) >> So how's the show been for you guys? >> Dave: Awesome. >> What're your big takeaways from- >> Tremendous experience. I mean, someone who doesn't go outside the United States much, I'm a homebody. The whole experience, the whole trip, city, Mobile World Congress, the technologies that are out here, it's been a blast. >> Anything, top two things you learned, advice you'd give to others, your colleagues out in general? >> In general, we talked a lot about technologies today, and we talked a lot about data, but I'm going to tell you what, the accelerator that you cannot change, is the relationship that we have. So when the tech and the business can work together toward a common goal, and it's a partnership, you get things done. So, I don't know how many CDOs or CIOs or CEOs are out there, but this connection is what accelerates and makes it work. >> And that is our audience Dave. I mean, it's all about that alignment. So guys, I really appreciate you coming in and sharing your story in "theCUBE." Great stuff. >> Thank you. >> Thanks a lot. >> All right, thanks everybody. Thank you for watching. I'll be right back with Dave Nicholson. Day four SiliconANGLE's coverage of MWC '23. You're watching "theCUBE." (gentle music)

>> theCUBE's live coverage is made possible by funding from Dell Technologies: "Creating technologies that drive human progress." >> Good late afternoon from Barcelona, Spain at the Theater of Barcelona. It's Lisa Martin and Dave Nicholson of "theCUBE" covering MWC23. This is our third day of continuous wall-to-wall coverage on theCUBE. And you know we're going to be here tomorrow as well. We've been having some amazing conversations about the ecosystem. And we're going to continue those conversations next. Honore Labourdette is here, the VP global partner, Ecosystem Success Team, Telco Media and Entertainment at Red Hat. And Tony Jeffries joins us as well, a Senior Director of Product Management, Telecom Systems Business at Dell. Welcome to the theCUBE. >> Thank you. >> Thank you. >> Great to have both of you here. So we're going to be talking about the evolution of the telecom stack. We've been talking a lot about disaggregation the last couple of days. Honore, starting with you, talk about the evolution of the telecom stock. You were saying before we went live this is your 15th at least MWC. So you've seen a lot of evolution, but what are some of the things you're seeing right now? >> Well, I think the interesting thing about disaggregation, which is a key topic, right? 'Cause it's so relative to 5G and the 5G core and the benefits and the features of 5G core around disaggregation. But one thing we have to remember, when you disaggregate, you separate things. You have to bring those things back together again in a different way. And that's predominantly what we're doing in our partnership with Dell, is we're bringing those disaggregated components back together in a cohesive way that takes advantage of the new technology, at the same time taking out the complexity and making it easier for our Telco customers to deploy and to scale and to get much more, accelerate the time to revenue. So the trend now is, what we're seeing is two things I would say. One is how do we solve for the complexity with the disaggregation? And how do we leverage the ecosystem as a partner in order to help solve for some of those challenges? >> Tony, jump on in, talk about what you guys announced last week, Dell and Red Hat, and how it's addressing the complexities that Honore was saying, "Hey, they're there." >> Yeah. You know, our customers, our operators are saying, "Hey, I want disaggregation." "I want competition in the market." But at the same time who's going to support all this disaggregation, right? And so at the end of the day, there's going to be an operator that's going to have to figure this out. They're going to have an SLA that they're going to have to meet. And so they're going to want to go with a best-in-class partner with Red Hat and Dell, in terms of our infrastructure and their software together as one combined engineered system. And that's what we call a Dell Telecom infrastructure block for Red Hat. And so at the end of the day, things may go wrong, and if they do, who are they going to call for that support? And that's also really a key element of an engineered system, is this experience that they get both with Red Hat and with Dell together supporting the customer as one. Which is really important to solve this disaggregated problem that can arise from a disaggregated open network situation, yeah. >> So what is the market, the go to market motion look like? People have loyalties in the IT space to technologies that they've embraced and been successful with for years and years. So you have folks in the marketplace who are diehard, you know, dyed red, Red Hat folks. Is it primarily a pull from them? How does that work? How do you approach that to your, what are your end user joint customers? What does that look like from your perspective? >> Sure, well, interestingly enough both Red Hat and Dell have been in the marketplace for a very long time, right? So we do have the brand with those Telco customers for these solutions. What we're seeing with this solution is, it's an emerging market. It's an emerging market for a new technology. So there's an opportunity for both Red Hat and Dell together to leverage our brands with those customers with no friction in the marketplace as we go to market together. So our field sales teams will be motivated to, you know, take advantage of the solution for their customers, as will the Dell team. And I'll let Tony speak to the Dell, go to market. >> Yeah. You know, so we really co-sell together, right? We're the key partners. Dell will end up fulfilling that order, right? We send these engineered systems through our factories and we send that out either directly to a customer or to a OTEL lab, like an intermediate lab where we can further refine and customize that offer for that particular customer. And so we got a lot of options there, but we're essentially co-selling. And Dell is fulfilling that from an infrastructure perspective, putting Red Hat software on top and the licensing for that support. So it's a really good mix. >> And I think, if I may, one of the key differentiators is the actual capabilities that we're bringing together inside of this pre-integrated solution. So it includes the Red Hat OpenShift which is the container software, but we also add our advanced cluster management as well as our Ansible automation. And then Dell adds their orchestration capability along with the features and functionalities of the platform. And we put that together and we offer capability, remote automation orchestration and management capabilities that again reduces the operating expense, reduces the complexity, allows for easy scale. So it's, you know, certainly it's all about the partnership but it's also the capabilities of the combined technology. >> I was just going to ask about some of the numbers, and you mentioned some of them. Reduction of TCO I imagine is also a big capability that this solution enables besides reducing OpEx. Talk about the TCO reduction. 'Cause I know there's some numbers there that Dell and Red Hat have already delivered to the market. >> Yeah. You know, so these infrastructure blocks are designed specifically for Core, or for RAN, or for the Edge. We're starting out initially in the Core, but we've done some market research with a company called ACG. And ACG has looked at day zero, day one and day two TCO, FTE hours saved. And we're looking at over 40 to 50% TCO savings over you know, five year period, which is quite significant in terms of cost savings at a TCO level. But also we have a lot of numbers around power consumption and savings around power consumption. But also just that experience for our operator that says, hey, I'm going to go to one company to get the best in class from Red Hat and Dell together. That saves a lot of time in procurement and that entire ordering process as well. So you get a lot of savings that aren't exactly seen in the FTE hours around TCO, but just in that overall experience by talking to one company to get the best of both from both Red Hat and Dell together. >> I think the comic book character Charlie Brown once said, "The most discouraging thing in the world is having a lot of potential." (laughing) >> Right. >> And so when we talk about disaggregating and then reaggregating or reintegrating, that means choice. >> Tony: Yeah. >> How does an operator approach making that choice? Because, yeah, it sounds great. We have this integration lab and you have all these choices. Well, how do I decide, how does a person decide? This is a question for Honore from a Red Hat perspective, what's the secret sauce that you believe differentiates the Red Hat-infused stack versus some other assemblage of gear? >> Well, there's a couple of key characteristics, and the one that I think is most prevalent is that we're open, right? So "open" is in Red Hat's DNA because we're an open source technology company, and with that open source technology and that open platform, our customers can now add workloads. They have options to choose the workloads that they want to run on that open source platform. As they choose those workloads, they can be confident that those workloads have been certified and validated on our platform because we have a very robust ecosystem of ISVs that have already completed that process with open source, with Red Hat OpenShift. So then we take the Red Hat OpenShift and we put it on the Dell platform, which is market leader platform, right? Combine those two things, the customers can be confident that they can put those workloads on the combined platform that we're offering and that those workloads would run. So again, it goes back to making it simpler, making it easy to procure, easy to run workloads, easy to deploy, easy to operate. And all of that of course equates to saving time always equates to saving money. >> Yeah. Absolutely. >> Oh, I thought you wanted to continue. >> No, I think Honore sort of, she nailed it. You know, Red Hat is so dominant in 5G, and what they're doing in the market, especially in the Core and where we're going into the RAN, you know, next steps are to validate those workloads, those workload vendors on top of a stack. And the Red Hat leader in the Core is key, right? It's instant credibility in the core market. And so that's one of the reasons why we, Dell, want to partner with with Red Hat for the core market and beyond. We're going to be looking at not only Core but moving into RAN very soon. But then we do, we take that validated workload on top of that to optimize that workload and then be able to instantiate that in the core and the RAN. It's just a really streamlined, good experience for our operators. At the end of the day, we want happy customers in between our mutual customer base. And that's what you get whenever you do that combined stack together. >> Were operators, any operators, and you don't have to mention them by name, involved in the evolution of the infra blocks? I'm just curious how involved they were in helping to co-develop this. I imagine they were to some degree. >> Yeah, I could take that one. So, in doing so, yeah, we can't be myopic and just assume that we nailed it the first time, right? So yeah, we do work with partners all the way up and down the stack. A lot of our engineering work with Red Hat also brings in customer experience that is key to ensure that you're building and designing the right architecture for the Core. I would like to use the names, I don't know if I should, but a lot of those names are big names that are leaders in our industry. But yeah, their footprints, their fingerprints are all over those design best practices, those architectural designs that we build together. And then we further that by doing those validated workloads on top of that. So just to really prove the point that it's optimized for the Core, RAN, Edge kind of workload. >> And it's a huge added value for Red Hat to have a partner like Dell who can take all of those components, take the workload, take the Red Hat software, put it on the platform, and deliver that out to the customers. That's really, you know, a key part of the partnership and the value of the partnership because nobody really does that better than Dell. That center of excellence around delivery and support. >> Can you share any feedback from any of those nameless operators in terms of... I'm even kind of wondering what the catalyst was for the infra block. Was it operators saying, "Ah, we have these challenges here"? Was it the evolution of the Telco stack and Dell said, "We can come in with Red Hat and solve this problem"? And what's been some of their feedback? >> Yeah, it really comes down to what Honore said about, okay, you know, when we are looking at day zero, which is primarily your design, how much time savings can we do by creating that stack for them, right? We have industry experts designing that Core stack that's optimized for different levels of spectrum. When we do that we save a lot of time in terms of FTE hours for our architects, our operators, and then it goes into day one, right? Which is the deployment aspect for saving tons of hours for our operators by being able to deploy this. Speed to market is key. That ultimately ends up in, you know, faster time to revenue for our customers, right? So it's, when they see that we've already done the pre-work that they don't have to, that's what really resonates for them in terms of that, yeah. >> Honore, Lisa and I happen to be veterans of the Cloud native space, and what we heard from a lot of the folks in that ecosystem is that there is a massive hunger for developers to be able to deploy and manage and orchestrate environments that consist of Cloud native application infrastructure, microservices. >> Right. >> What we've heard here is that 5G equals Cloud native application stacks. Is that a fair assessment of the environment? And what are you seeing from a supply and demand for that kind of labor perspective? Is there still a hunger for those folks who develop in that space? >> Well, there is, because the very nature of an open source, Kubernetes-based container platform, which is what OpenShift is, the very nature of it is to open up that code so that developers can have access to the code to develop the workloads to the platform, right? And so, again, the combination of bringing together the Dell infrastructure with the Red Hat software, it doesn't change anything. The developer, the development community still has access to that same container platform to develop to, you know, Cloud native types of application. And you know, OpenShift is Red Hat's hybrid Cloud platform. So it runs on-prem, it runs in the public Cloud, it runs at the edge, it runs at the far edge. So any of the development community that's trying to develop Cloud native applications can develop it on this platform as they would if they were developing on an OpenShift platform in the public Cloud. >> So in "The Graduate", the advice to the graduate was, "Plastics." Plastics. As someone who has more children than I can remember, I forget how many kids I have. >> Four. >> That's right, I have four. That's right. (laughing) Three in college and grad school already at this point. Cloud native, I don't know. Kubernetes definitely a field that's going to, it's got some legs? >> Yes. >> Okay. So I can get 'em off my payroll quickly. >> Honore: Yes, yes. (laughing) >> Okay, good to know. Good to know. Any thoughts on that open Cloud native world? >> You know, there's so many changes that's going to happen in Kubernetes and services that you got to be able to update quickly. CICD, obviously the topic is huge. How quickly can we keep these systems up to date with new releases, changes? That's a great thing about an engineered system is that we do provide that lifecycle management for three to five years through this engagement with our customers. So we're constantly keeping them up with the latest and the greatest. >> David: Well do those customers have that expertise in-house, though? Do they have that now? Or is this a seismic cultural shift in those environments? >> Well, you know, they do have a lot of that experience, but it takes a lot of that time, and we're taking that off of their plate and putting that within us on our system, within our engineered system, and doing that automatically for them. And so they don't have to check in and try to understand what the release certification matrix is. Every quarter we're providing that to them. We're communicating out to the operator, telling them what's coming up latest and greatest, not only in terms of the software but the hardware and how to optimize it all together. That's the beauty of these systems. These are five year relationships with our operators that we're providing that lifecycle management end to end, for years to come. >> Lisa: So last question. You talked about joint GTM availability. When can operators get their hands on this? >> Yes. Yes. It's currently slated for early September release. >> Lisa: Awesome. So sometime this year? >> Yes. >> Well guys, thank you so much for talking with us today about Dell, Red Hat, what you're doing to really help evolve the telecom stack. We appreciate it. Next time come back with a customer, we can dig into it. That'd be fun. >> We sure will, absolutely. That may happen today actually, a little bit later. Not to let the cat out the bag, but good news. >> All right, well, geez, you're going to want to stick around. Thank you so much for your time. For our guests and for Dave Nicholson. This is Lisa Martin of theCUBE at MWC23 from Barcelona, Spain. We'll be back after a short break. (calm music)

>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (light airy music) >> Hi, everybody, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with my co-host Dave Nicholson. Lisa Martin is in the house. John Furrier is pounding the news from our Palo Alto studio. We are super excited to be talking about cloud at the edge, what that means. Charles Tsai is here. He's the Senior Director of product management at Dell Technologies and Peter Fetterolf is the Chief Technology Officer at ACG Business Analytics, a firm that goes deep into the TCO and the telco space, among other things. Gents, welcome to theCUBE. Thanks for coming on. Thank you. >> Good to be here. >> Yeah, good to be here. >> So I've been in search all week of the elusive next wave of monetization for the telcos. We know they make great money on connectivity, they're really good at that. But they're all talking about how they can't let this happen again. Meaning we can't let the over the top vendors yet again, basically steal our cookies. So we're going to not mess it up this time. We're going to win in the monetization. Charles, where are those monetization opportunities? Obviously at the edge, the telco cloud at the edge. What is that all about and where's the money? >> Well, Dave, I think from a Dell's perspective, what we want to be able to enable operators is a solution that enable them to roll out services much quicker, right? We know there's a lot of innovation around IoT, MEG and so on and so forth, but they continue to rely on traditional technology and way of operations is going to take them years to enable new services. So what Dell is doing is now, creating the entire vertical stack from the hardware through CAST and automation that enable them, not only to push out services very quickly, but operating them using cloud principles. >> So it's when you say the entire vertical stack, it's the integrated hardware components with like, for example, Red Hat on top- >> Right. >> Or a Wind River? >> That's correct. >> Okay, and then open API, so the developers can create workloads, I presume data companies. We just had a data conversation 'cause that was part of the original stack- >> That's correct. >> So through an open ecosystem, you can actually sort of recreate that value, correct? >> That's correct. >> Okay. >> So one thing Dell is doing, is we are offering an infrastructure block where we are taking over the overhead of certifying every release coming from the Red Hat or the Wind River of the world, right? We want telcos to spend their resources on what is going to generate them revenue. Not the overhead of creating this cloud stack. >> Dave, I remember when we went through this in the enterprise and you had companies like, you know, IBM with the AS400 and the mainframe saying it's easier to manage, which it was, but it's still, you know, it was subsumed by the open systems trend. >> Yeah, yeah. And I think that's an important thing to probe on, is this idea of what is, what exactly does it mean to be cloud at the edge in the telecom space? Because it's a much used term. >> Yeah. >> When we talk about cloud and edge, in sort of generalized IT, but what specifically does it mean? >> Yeah, so when we talk about telco cloud, first of all it's kind of different from what you're thinking about public cloud today. And there's a couple differences. One, if you look at the big hyperscaler public cloud today, they tend to be centralized in huge data centers. Okay, telco cloud, there are big data centers, but then there's also regional data centers. There are edge data centers, which are your typical like access central offices that have turned data centers, and then now even cell sites are becoming mini data centers. So it's distributed. I mean like you could have like, even in a country like say Germany, you'd have 30,000 soul sites, each one of them being a data center. So it's a very different model. Now the other thing I want to go back to the question of monetization, okay? So how do you do monetization? The only way to do that, is to be able to offer new services, like Charles said. How do you offer new services? You have to have an open ecosystem that's going to be very, very flexible. And if we look at where telcos are coming from today, they tend to be very inflexible 'cause they're all kind of single vendor solutions. And even as we've moved to virtualization, you know, if you look at packet core for instance, a lot of them are these vertical stacks of say a Nokia or Ericson or Huawei where you know, you can't really put any other vendors or any other solutions into that. So basically the idea is this kind of horizontal architecture, right? Where now across, not just my central data centers, but across my edge data centers, which would be traditionally my access COs, as well as my cell sites. I have an open environment. And we're kind of starting with, you know, packet core obviously with, and UPFs being distributed, but now open ran or virtual ran, where I can have CUs and DUs and I can split CUs, they could be at the soul site, they could be in edge data centers. But then moving forward, we're going to have like MEG, which are, you know, which are new kinds of services, you know, could be, you know, remote cars it could be gaming, it could be the Metaverse. And these are going to be a multi-vendor environment. So one of the things you need to do is you need to have you know, this cloud layer, and that's what Charles was talking about with the infrastructure blocks is helping the service providers do that, but they still own their infrastructure. >> Yeah, so it's still not clear to me how the service providers win that game but we can maybe come back to that because I want to dig into TCO a little bit. >> Sure. >> Because I have a lot of friends at Dell. I don't have a lot of friends at HPE. I've always been critical when they take an X86 server put a name on it that implies edge and they throw it over the fence to the edge, that's not going to work, okay? We're now seeing, you know we were just at the Dell booth yesterday, you did the booth crawl, which was awesome. Purpose-built servers for this environment. >> Charles: That's right. >> So there's two factors here that I want to explore in TCO. One is, how those next gen servers compare to the previous gen, especially in terms of power consumption but other factors and then how these sort of open ran, open ecosystem stacks compared to proprietary stacks. Peter, can you help us understand those? >> Yeah, sure. And Charles can comment on this as well. But I mean there, there's a couple areas. One is just moving the next generation. So especially on the Intel side, moving from Ice Lake to the Sapphire Rapids is a big deal, especially when it comes to the DU. And you know, with the radios, right? There's the radio unit, the RU, and then there's the DU the distributed unit, and the CU. The DU is really like part of the radio, but it's virtualized. When we moved from Ice lake to Sapphire Rapids, which is third generation intel to fourth generation intel, we're literally almost doubling the performance in the DU. And that's really important 'cause it means like almost half the number of servers and we're talking like 30, 40, 50,000 servers in some cases. So, you know, being able to divide that by two, that's really big, right? In terms of not only the the cost but all the TCO and the OpEx. Now another area that's really important, when I was talking moving from these vertical silos to the horizontal, the issue with the vertical silos is, you can't place any other workloads into those silos. So it's kind of inefficient, right? Whereas when we have the horizontal architecture, now you can place workloads wherever you want, which basically also means less servers but also more flexibility, more service agility. And then, you know, I think Charles can comment more, specifically on the XR8000, some things Dell's doing, 'cause it's really exciting relative to- >> Sure. >> What's happening in there. >> So, you know, when we start looking at putting compute at the edge, right? We recognize the first thing we have to do is understand the environment we are going into. So we spend with a lot of time with telcos going to the south side, going to the edge data center, looking at operation, how do the engineer today deal with maintenance replacement at those locations? Then based on understanding the operation constraints at those sites, we create innovation and take a traditional server, remodel it to make sure that we minimize the disruption to the operations, right? Just because we are helping them going from appliances to open compute, we do not want to disrupt what is have been a very efficient operation on the remote sites. So we created a lot of new ideas and develop them on general compute, where we believe we can save a lot of headache and disruptions and still provide the same level of availability, resiliency, and redundancy on an open compute platform. >> So when we talk about open, we don't mean generic? Fair? See what I mean? >> Open is more from the software workload perspective, right? A Dell server can run any type of workload that customer intend. >> But it's engineered for this? >> Environment. >> Environment. >> That's correct. >> And so what are some of the environmental issues that are dealt with in the telecom space that are different than the average data center? >> The most basic one, is in most of the traditional cell tower, they are deployed within cabinets instead of racks. So they are depth constraints that you just have no access to the rear of the chassis. So that means on a server, is everything you need to access, need to be in the front, nothing should be in the back. Then you need to consider how labor union come into play, right? There's a lot of constraint on who can go to a cell tower and touch power, who can go there and touch compute, right? So we minimize all that disruption through a modular design and make it very efficient. >> So when we took a look at XR8000, literally right here, sitting on the desk. >> Uh-huh. >> Took it apart, don't panic, just pulled out some sleds and things. >> Right, right. >> One of the interesting demonstrations was how it compared to the size of a shoe. Now apparently you hired someone at Dell specifically because they wear a size 14 shoe, (Charles laughs) so it was even more dramatic. >> That's right. >> But when you see it, and I would suggest that viewers go back and take a look at that segment, specifically on the hardware. You can see exactly what you just referenced. This idea that everything is accessible from the front. Yeah. >> So I want to dig in a couple things. So I want to push back a little bit on what you were saying about the horizontal 'cause there's the benefit, if you've got the horizontal infrastructure, you can run a lot more workloads. But I compare it to the enterprise 'cause I, that was the argument, I've made that argument with converged infrastructure versus say an Oracle vertical stack, but it turned out that actually Oracle ran Oracle better, okay? Is there an analog in telco or is this new open architecture going to be able to not only service the wide range of emerging apps but also be as resilient as the proprietary infrastructure? >> Yeah and you know, before I answer that, I also want to say that we've been writing a number of white papers. So we have actually three white papers we've just done with Dell looking at infrastructure blocks and looking at vertical versus horizontal and also looking at moving from the previous generation hardware to the next generation hardware. So all those details, you can find the white papers, and you can find them either in the Dell website or at the ACG research website >> ACGresearch.com? >> ACG research. Yeah, if you just search ACG research, you'll find- >> Yeah. >> Lots of white papers on TCO. So you know, what I want to say, relative to the vertical versus horizontal. Yeah, obviously in the vertical side, some of those things will run well, I mean it won't have issues. However, that being said, as we move to cloud native, you know, it's very high performance, okay? In terms of the stack, whether it be a Red Hat or a VMware or other cloud layers, that's really become much more mature. It now it's all CNF base, which is really containerized, very high performance. And so I don't think really performance is an issue. However, my feeling is that, if you want to offer new services and generate new revenue, you're not going to do it in vertical stacks, period. You're going to be able to do a packet core, you'll be able to do a ran over here. But now what if I want to offer a gaming service? What if I want to do metaverse? What if I want to do, you have to have an environment that's a multi-vendor environment that supports an ecosystem. Even in the RAN, when we look at the RIC, and the xApps and the rApps, these are multi-vendor environments that's going to create a lot of flexibility and you can't do that if you're restricted to, I can only have one vendor running on this hardware. >> Yeah, we're seeing these vendors work together and create RICs. That's obviously a key point, but what I'm hearing is that there may be trade offs, but the incremental value is going to overwhelm that. Second question I have, Peter is, TCO, I've been hearing a lot about 30%, you know, where's that 30% come from? Is it Op, is it from an OpEx standpoint? Is it labor, is it power? Is it, you mentioned, you know, cutting the number of servers in half. If I can unpack the granularity of that TCO, where's the benefit coming from? >> Yeah, the answer is yes. (Peter and Charles laugh) >> Okay, we'll do. >> Yeah, so- >> One side that, in terms of, where is the big bang for the bucks? >> So I mean, so you really need to look at the white paper to see details, but definitely power, definitely labor, definitely reducing the number of servers, you know, reducing the CapEx. The other thing is, is as you move to this really next generation horizontal telco cloud, there's the whole automation and orchestration, that is a key component as well. And it's enabled by what Dell is doing. It's enabled by the, because the thing is you're not going to have end-to-end automation if you have all this legacy stuff there or if you have these vertical stacks where you can't integrate. I mean you can automate that part and then you have separate automation here, you separate. you need to have integrated automation and orchestration across the whole thing. >> One other point I would add also, right, on the hardware perspective, right? With the customized hardware, what we allow operator to do is, take out the existing appliance and push a edge optimized server without reworking the entire infrastructure. There is a significant saving where you don't have to rethink about what is my power infrastructure, right? What is my security infrastructure? The server is designed to leverage the existing, what is already there. >> How should telco, Charles, plan for this transformation? Are there specific best practices that you would recommend in terms of the operational model? >> Great question. I think first thing is do an inventory of what you have. Understand what your constraints are and then come to Dell, we will love to consult with you, based on our experience on the best practices. We know how to minimize additional changes. We know how to help your support engineer, understand how to shift appliance based operation to a cloud-based operation. >> Is that a service you offer? Is that a pre-sales freebie? What is maybe both? >> It's both. >> Yeah. >> It's both. >> Yeah. >> Guys- >> Just really quickly. >> We're going to wrap. >> The, yeah. Dave loves the TCO discussion. I'm always thinking in terms of, well how do you measure TCO when you're comparing something where you can't do something to an environment where you're going to be able to do something new? And I know that that's always the challenge in any kind of emerging market where things are changing, any? >> Well, I mean we also look at, not only TCO, but we look at overall business case. So there's basically service at GLD and revenue and then there's faster time to revenues. Well, and actually ACG, we actually have a platform called the BAE or Business Analytics Engine that's a very sophisticated simulation cloud-based platform, where we can actually look at revenue month by month. And we look at what's the impact of accelerating revenue by three months. By four months. >> So you're looking into- >> By six months- >> So you're forward looking. You're just not consistently- >> So we're not just looking at TCO, we're looking at the overall business case benefit. >> Yeah, exactly right. There's the TCO, which is the hard dollars. >> Right. >> CFO wants to see that, he or she needs to see that. But you got to, you can convince that individual, that there's a business case around it. >> Peter: Yeah. >> And then you're going to sign up for that number. >> Peter: Yeah. >> And they're going to be held to it. That's the story the world wants. >> At the end of the day, telcos have to be offered new services 'cause look at all the money that's been spent. >> Dave: Yeah, that's right. >> On investment on 5G and everything else. >> 0.5 trillion over the next seven years. All right, guys, we got to go. Sorry to cut you off. >> Okay, thank you very much. >> But we're wall to wall here. All right, thanks so much for coming on. >> Dave: Fantastic. >> All right, Dave Vellante, for Dave Nicholson. Lisa Martin's in the house. John Furrier in Palo Alto Studios. Keep it right there. MWC 23 live from the Fira in Barcelona. (light airy music)

(upbeat music) >> Hello, everyone; I'm John Furrier with SiliconANGLE NEWS and host of theCUBE, and welcome to our SiliconANGLE NEWS MWC NEWS UPDATE in Barcelona where MWC is the premier event for the cloud telecommunication industry, and in the news here is Red Hat, Red Hat announcing a collaboration with NVIDIA, Samsung and Arm on Efficient Open Networks. Red Hat announced updates across various fields including advanced 5G telecommunications cloud, industrial edge, artificial intelligence, and radio access networks, RAN, and Efficiency. Red Hat's enterprise Kubernetes platform, OpenShift, has added support for NVIDIA's converged accelerators and aerial SDK facilitating RAND deployments on industry standard service across hybrid and multicloud platforms. This composable infrastructure enables telecom firms to support heavier compute demands for edge computing, AI, private 5G, and more, and just also helps network operators adopt open architectures, allowing them to choose non-proprietary components from multiple suppliers. In addition to the NVIDIA collaboration, Red Hat is working with Samsung to offer a new vRAN solution for service providers to better manage their open RAN networks. They're also working with UK chip designer, Arm, to create new networking solutions for energy efficient Red Hat Open Source Kubernetes-based Efficient Power Level Exporter project, or Kepler, has been donated to the open Cloud Native Compute Foundation, allowing enterprise to better understand their cloud native workloads and power consumptions. Kepler can also help in the development of sustainable software by creating less power hungry applications. Again, Red Hat continuing to provide OpenSource, OpenRAN, and contributing an open source project to the CNCF, continuing to create innovation for developers, and, of course, Red Hat knows what, a lot about operating systems and the telco could be the next frontier. That's SiliconANGLE NEWS. I'm John Furrier; thanks for watching. (monotone music)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hi everybody. Welcome back to Barcelona. We're here at the Fira Live, theCUBE's ongoing coverage of day two of MWC 23. Back in 2021 was my first Mobile World Congress. And you know what? It was actually quite an experience because there was nobody there. I talked to my friend, who's now my co-host, Chris Lewis about what to expect. He said, Dave, I don't think a lot of people are going to be there, but Danielle Royston is here and she's the CEO of Totoge. And that year when Erickson tapped out of its space she took out 60,000 square feet and built out Cloud City. If it weren't for Cloud City, there would've been no Mobile World Congress in June and July of 2021. DR is back. Great to see you. Thanks for coming on. >> It's great to see you. >> Chris. Awesome to see you. >> Yeah, Chris. Yep. >> Good to be back. Yep. >> You guys remember the narrative back then. There was this lady running around this crazy lady that I met at at Google Cloud next saying >> Yeah. Yeah. >> the cloud's going to take over Telco. And everybody's like, well, this lady's nuts. The cloud's been leaning in, you know? >> Yeah. >> So what do you think, I mean, what's changed since since you first caused all those ripples? >> I mean, I have to say that I think that I caused a lot of change in the industry. I was talking to leaders over at AWS yesterday and they were like, we've never seen someone push like you have and change so much in a short period of time. And Telco moves slow. It's known for that. And they're like, you are pushing buttons and you're getting people to change and thank you and keep going. And so it's been great. It's awesome. >> Yeah. I mean, it was interesting, Chris, we heard on the keynotes we had Microsoft, Satya came in, Thomas Curian came in. There was no AWS. And now I asked CMO of GSMA about that. She goes, hey, we got a great relationship with it, AWS. >> Danielle: Yeah. >> But why do you think they weren't here? >> Well, they, I mean, they are here. >> Mean, not here. Why do you think they weren't profiled? >> They weren't on the keynote stage. >> But, you know, at AWS, a lot of the times they want to be the main thing. They want to be the main part of the show. They don't like sharing the limelight. I think they just didn't want be on the stage with the Google CLoud guys and the these other guys, what they're doing they're building out, they're doing so much stuff. As Danielle said, with Telcos change in the ecosystem which is what's happening with cloud. Cloud's making the Telcos think about what the next move is, how they fit in with the way other people do business. Right? So Telcos never used to have to listen to anybody. They only listened to themselves and they dictated the way things were done. They're very successful and made a lot of money but they're now having to open up they're having to leverage the cloud they're having to leverage the services that (indistinct words) and people out provide and they're changing the way they work. >> So, okay in 2021, we talked a lot about the cloud as a potential disruptor, and your whole premise was, look you got to lean into the cloud, or you're screwed. >> Danielle: Yeah. >> But the flip side of that is, if they lean into the cloud too much, they might be screwed. >> Danielle: Yeah. >> So what's that equilibrium? Have they been able to find it? Are you working with just the disruptors or how's that? >> No I think they're finding it right. So my talk at MWC 21 was all about the cloud is a double-edged sword, right? There's two sides to it, and you definitely need to proceed through it with caution, but also I don't know that you have a choice, right? I mean, the multicloud, you know is there another industry that spends more on CapEx than Telco? >> No. >> Right. The hyperscalers are doing it right. They spend, you know, easily approaching over a $100 billion in CapEx that rivals this industry. And so when you have a player like that an industry driving, you know and investing so much Telco, you're always complaining how everyone's riding your coattails. This is the opportunity to write someone else's coattails. So jump on, right? I think you don't have a choice especially if other Telco competitors are using hyperscalers and you don't, they're going to be left behind. >> So you advise these companies all the time, but >> I mean, the issue is they're all they're all using all the hyperscalers, right? So they're the multi, the multiple relationships. And as Danielle said, the multi-layer of relationship they're using the hyperscalers to change their own internal operational environments to become more IT-centric to move to that software centric Telco. And they're also then with the hyperscalers going to market in different ways sometimes with them, sometimes competing with them. What what it means from an analyst point of view is you're suddenly changing the dynamic of a market where we used to have nicely well defined markets previously. Now they're, everyone's in it together, you know, it's great. And, and it's making people change the way they think about services. What I, what I really hope it changes more than anything else is the way the customers at the end of the, at the end of the supply, the value chain think this is what we can get hold of this stuff. Now we can go into the network through the cloud and we can get those APIs. We can draw on the mechanisms we need to to run our personal lives, to run our business lives. And frankly, society as a whole. It's really exciting. >> Then your premise is basically you were saying they should ride on the top over the top of the cloud vendor. >> Yeah. Right? >> No. Okay. But don't they lose the, all the data if they do that? >> I don't know. I mean, I think the hyperscalers are not going to take their data, right? I mean, that would be a really really bad business move if Google Cloud and Azure and and AWS start to take over that, that data. >> But they can't take it. >> They can't. >> From regulate, from sovereignty and regulation. >> They can't because of regulation, but also just like business, right? If they started taking their data and like no enterprises would use them. So I think, I think the data is safe. I think you, obviously every country is different. You got to understand the different rules and regulations for data privacy and, and how you keep it. But I think as we look at the long term, right and we always talk about 10 and 20 years there's going to be a hyperscaler region in every country right? And there will be a way for every Telco to use it. I think their data will be safe. And I think it just, you're going to be able to stand on on the shoulders of someone else for once and use the building blocks of software that these guys provide to make better experiences for subscribers. >> You guys got to explain this to me because when I say data I'm not talking about, you know, personal information. I'm talking about all the telemetry, you know, all the all the, you know the plumbing. >> Danielle: Yeah. >> Data, which is- >> It will increasingly be shared because you need to share it in order to deliver the services in the streamline efficient way that needs to be deliver. >> Did I hear the CEO of Ericsson Wright where basically he said, we're going to charge developers for access to that data through APIs. >> What the Ericsson have done, obviously with the Vage acquisition is they want to get into APIs. So the idea is you're exposing features, quality policy on demand type features for example, or even pulling we still use that a lot of SMS, right? So pulling those out using those APIs. So it will be charged in some way. Whether- >> Man: Like Twitter's charging me for APIs, now I API calls, you >> Know what it is? I think it's Twilio. >> Man: Oh, okay. >> Right. >> Man: No, no, that's sure. >> There's no reason why telcos couldn't provide a Twilio like service itself. >> It's a horizontal play though right? >> Danielle: Correct because developers need to be charged by the API. >> But doesn't there need to be an industry standard to do that as- >> Well. I think that's what they just announced. >> Industry standard. >> Danielle: I think they just announced that. Yeah. Right now I haven't looked at that API set, right? >> There's like eight of them. >> There's eight of them. Twilio has, it's a start you got to start somewhere Dave. (crosstalk) >> And there's all, the TM forum is all the other standard >> Right? Eight is better than zero- >> Right? >> Haven't got plenty. >> I mean for an industry that didn't really understand APIs as a feature, as a product as a service, right? For Mats Granryd, the deputy general of GSMA to stand on the keynote stage and say we partnered and we're unveiling, right. Pay by the use APIs. I was for it. I was like, that is insane. >> I liked his keynote actually, because I thought he was going to talk about how many attendees and how much economic benefiting >> Danielle: We're super diverse. >> He said, I would usually talk about that and you know greening in the network by what you did talk about a little bit. But, but that's, that surprised me. >> Yeah. >> But I've seen in the enterprise this is not my space as, you know, you guys don't live this but I've seen Oracle try to get developers. IBM had to pay $35 billion trying to get for Red Hat to get developers, right? EMC used to have a thing called EMC code, failed. >> I mean they got to do something, right? So 4G they didn't really make the business case the ROI on the investment in the network. Here we are with 5G, same discussion is having where's the use case? How are we going to monetize and make the ROI on this massive investment? And now they're starting to talk about 6G. Same fricking problem is going to happen again. And so I think they need to start experimenting with new ideas. I don't know if it's going to work. I don't know if this new a API network gateway theme that Mats talked about yesterday will work. But they need to start unbundling that unlimited plan. They need to start charging people who are using the network more, more money. Those who are using it less, less. They need to figure this out. This is a crisis for them. >> Yeah our own CEO, I mean she basically said, Hey, I'm for net neutrality, but I want to be able to charge the people that are using it more and more >> To make a return on, on a capital. >> I mean it costs billions of dollars to build these networks, right? And they're valuable. We use them and we talked about this in Cloud City 21, right? The ability to start building better metaverses. And I know that's a buzzword and everyone hates it, but it's true. Like we're working from home. We need- there's got to be a better experience in Zoom in 2D, right? And you need a great network for that metaverse to be awesome. >> You do. But Danielle, you don't need cellular for doing that, do you? So the fixed network is as important. >> Sure. >> And we're at mobile worlds. But actually what we beginning to hear and Crystal Bren did say this exactly, it's about the comp the access is sort of irrelevant. Fixed is better because it's more the cost the return on investment is better from fiber. Mobile we're going to change every so many years because we're a new generation. But we need to get the mechanism in place to deliver that. I actually don't agree that we should everyone should pay differently for what they use. It's a universal service. We need it as individuals. We need to make it sustainable for every user. Let's just not go for the biggest user. It's not, it's not the way to build it. It won't work if you do that you'll crash the system if you do that. And, and the other thing which I disagree on it's not about standing on the shoulders and benefiting from what- It's about cooperating across all levels. The hyperscalers want to work with the telcos as much as the telcos want to work with the hyperscalers. There's a lot of synergy there. There's a lot of ways they can work together. It's not one or the other. >> But I think you're saying let the cloud guys do the heavy lifting and I'm - >> Yeah. >> Not at all. >> And so you don't think so because I feel like the telcos are really good at pipes. They've always been good at pipes. They're engineers. >> Danielle: Yeah. >> Are they hanging on to the to the connectivity or should they let that go and well and go toward the developer. >> I mean AWS had two announcements on the 21st a week before MWC. And one was that telco network builder. This is literally being able to deploy a network capability at AWS with keystrokes. >> As a managed service. >> Danielle: Correct. >> Yeah. >> And so I don't know how the telco world I felt the shock waves, right? I was like, whoa, that seems really big. Because they're taking something that previously was like bread and butter. This is what differentiates each telco and now they've standardized it and made it super easy so anyone can do it. Now do I think the five nines of super crazy hardcore network criteria will be built on AWS this way? Probably not, but no >> It's not, it's not end twin. So you can't, no. >> Right. But private networks could be built with this pretty easily, right? And so telcos that don't have as much funding, right. Smaller, more experiments. I think it's going to change the way we think about building networks in telcos >> And those smaller telcos I think are going to be more developer friendly. >> Danielle: Yeah. >> They're going to have business models that invite those developers in. And that's, it's the disruption's going to come from the ISVs and the workloads that are on top of that. >> Well certainly what Dish is trying to do, right? Dish is trying to build a- they launched it reinvent a developer experience. >> Dave: Yeah. >> Right. Built around their network and you know, again I don't know, they were not part of this group that designed these eight APIs but I'm sure they're looking with great intent on what does this mean for them. They'll probably adopt them because they want people to consume the network as APIs. That's their whole thing that Mark Roanne is trying to do. >> Okay, and then they're doing open ran. But is it- they're not really cons- They're not as concerned as Rakuten with the reliability and is that the right play? >> In this discussion? Open RAN is not an issue. It really is irrelevant. It's relevant for the longer term future of the industry by dis aggregating and being able to share, especially ran sharing, for example, in the short term in rural environments. But we'll see some of that happening and it will change, but it will also influence the way the other, the existing ran providers build their services and offer their value. Look you got to remember in the relationship between the equipment providers and the telcos are very dramatically. Whether it's Ericson, NOKIA, Samsung, Huawei, whoever. So those relations really, and the managed services element to that depends on what skills people have in-house within the telco and what service they're trying to deliver. So there's never one size fits all in this industry. >> You're very balanced in your analysis and I appreciate that. >> I try to be. >> But I am not. (chuckles) >> So when Dr went off, this is my question. When Dr went off a couple years ago on the cloud's going to take over the world, you were skeptical. You gave a approach. Have you? >> I still am. >> Have you moderated your thoughts on that or- >> I believe the telecom industry is is a very strong industry. It's my industry of course I love it. But the relationship it is developing much different relationships with the ecosystem players around it. You mentioned developers, you mentioned the cloud players the equipment guys are changing there's so many moving parts to build the telco of the future that every country needs a very strong telco environment to be able to support the site as a whole. People individuals so- >> Well I think two years ago we were talking about should they or shouldn't they, and now it's an inevitability. >> I don't think we were Danielle. >> All using the hyperscalers. >> We were always going to need to transform the telcos from the conservative environments in which they developed. And they've had control of everything in order to reduce if they get no extra revenue at all, reducing the cost they've got to go on a cloud migration path to do that. >> Amenable. >> Has it been harder than you thought? >> It's been easier than I thought. >> You think it's gone faster than >> It's gone way faster than I thought. I mean pushing on this flywheel I thought for sure it would take five to 10 years it is moving. I mean the maths comp thing the AWS announcements last week they're putting in hyperscalers in Saudi Arabia which is probably one of the most sort of data private places in the world. It's happening really fast. >> What Azure's doing? >> I feel like I can't even go to sleep. Because I got to keep up with it. It's crazy. >> Guys. >> This is awesome. >> So awesome having you back on. >> Yeah. >> Chris, thanks for co-hosting. Appreciate you stay here. >> Yep. >> Danielle, amazing. We'll see you. >> See you soon. >> A lot of action here. We're going to come out >> Great. >> Check out your venue. >> Yeah the Togi buses that are outside. >> The big buses. You got a great setup there. We're going to see you on Wednesday. Thanks again. >> Awesome. Thanks. >> All right. Keep it right there. We'll be back to wrap up day two from MWC 23 on theCUBE. (upbeat music)

>> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (ambient music) >> Lisa: Hey everyone, welcome back to Barcelona, Spain. It's theCUBE Live at MWC 23. Lisa Martin with Dave Vellante. This is day two of four days of cube coverage but you know that, because you've already been watching yesterday and today. We're going to have a great conversation next with EnterpriseWeb and Red Hat. We've had great conversations the last day and a half about the Telco industry, the challenges, the opportunities. We're going to unpack that from this lens. Please welcome Dave Duggal, founder and CEO of EnterpriseWeb and Azhar Sayeed is here, Senior Director Solution Architecture at Red Hat. >> Guys, it's great to have you on the program. >> Yes. >> Thank you Lisa, >> Great being here with you. >> Dave let's go ahead and start with you. Give the audience an overview of EnterpriseWeb. What kind of business is it? What's the business model? What do you guys do? >> Okay so, EnterpriseWeb is reinventing middleware, right? So the historic middleware was to build vertically integrated stacks, right? And those stacks are now such becoming the rate limiters for interoperability for so the end-to-end solutions that everybody's looking for, right? Red Hat's talking about the unified platform. You guys are talking about Supercloud, EnterpriseWeb addresses that we've built middleware based on serverless architecture, so lightweight, low latency, high performance middleware. And we're working with the world's biggest, we sell through channels and we work through partners like Red Hat Intel, Fortnet, Keysight, Tech Mahindra. So working with some of the biggest players that have recognized the value of our innovation, to deliver transformation to the Telecom industry. >> So what are you guys doing together? Is this, is this an OpenShift play? >> Is it? >> Yeah. >> Yeah, so we've got two projects right her on the floor at MWC throughout the various partners, where EnterpriseWeb is actually providing an application layer, sorry application middleware over Red Hat's, OpenShift and we're essentially generating operators so Red Hat operators, so that all our vendors, and, sorry vendors that we onboard into our catalog can be deployed easily through the OpenShift platform. And we allow those, those vendors to be flexibly composed into network services. So the real challenge for operators historically is that they, they have challenges onboarding the vendors. It takes a long time. Each one of them is a snowflake. They, you know, even though there's standards they don't all observe or follow the same standards. So we make it easier using models, right? For, in a model driven process to on boards or streamline that onboarding process, compose functions into services deploy those services seamlessly through Red Hat's OpenShift, and then manage the, the lifecycle, like the quality of service and the SLAs for those services. >> So Red Hat obviously has pretty prominent Telco business has for a while. Red Hat OpenStack actually is is pretty popular within the Telco business. People thought, "Oh, OpenStack, that's dead." Actually, no, it's actually doing quite well. We see it all over the place where for whatever reason people want to build their own cloud. And, and so, so what's happening in the industry because you have the traditional Telcos we heard in the keynotes that kind of typical narrative about, you know, we can't let the over the top vendors do this again. We're, we're going to be Apifi everything, we're going to monetize this time around, not just with connectivity but the, but the fact is they really don't have a developer community. >> Yes. >> Yet anyway. >> Then you have these disruptors over here that are saying "Yeah, we're going to enable ISVs." How do you see it? What's the landscape look like? Help us understand, you know, what the horses on the track are doing. >> Sure. I think what has happened, Dave, is that the conversation has moved a little bit from where they were just looking at IS infrastructure service with virtual machines and OpenStack, as you mentioned, to how do we move up the value chain and look at different applications. And therein comes the rub, right? You have applications with different requirements, IT network that have various different requirements that are there. So as you start to build those cloud platform, as you start to modernize those set of applications, you then start to look at microservices and how you build them. You need the ability to orchestrate them. So some of those problem statements have moved from not just refactoring those applications, but actually now to how do you reliably deploy, manage in a multicloud multi cluster way. So this conversation around Supercloud or this conversation around multicloud is very >> You could say Supercloud. That's okay >> (Dave Duggal and Azhar laughs) >> It's absolutely very real though. The reason why it's very real is, if you look at transformations around Telco, there are two things that are happening. One, Telco IT, they're looking at partnerships with hybrid cloud, I mean with public cloud players to build a hybrid environment. They're also building their own Telco Cloud environment for their network functions. Now, in both of those spaces, they end up operating two to three different environments themselves. Now how do you create a level of abstraction across those? How do you manage that particular infrastructure? And then how do you orchestrate all of those different workloads? Those are the type of problems that they're actually beginning to solve. So they've moved on from really just putting that virtualizing their application, putting it on OpenStack to now really seriously looking at "How do I build a service?" "How do I leverage the catalog that's available both in my private and public and build an overall service process?" >> And by the way what you just described as hybrid cloud and multicloud is, you know Supercloud is what multicloud should have been. And what, what it originally became is "I run on this cloud and I run on this cloud" and "I run on this cloud and I have a hybrid." And, and Supercloud is meant to create a common experience across those clouds. >> Dave Duggal: Right? >> Thanks to, you know, Supercloud middleware. >> Yeah. >> Right? And, and so that's what you guys do. >> Yeah, exactly. Exactly. Dave, I mean, even the name EnterpriseWeb, you know we started from looking from the application layer down. If you look at it, the last 10 years we've looked from the infrastructure up, right? And now everybody's looking northbound saying "You know what, actually, if I look from the infrastructure up the only thing I'll ever build is silos, right?" And those silos get in the way of the interoperability and the agility the businesses want. So we take the perspective as high level abstractions, common tools, so that if I'm a CXO, I can look down on my environments, right? When I'm really not, I honestly, if I'm an, if I'm a CEO I don't really care or CXO, I don't really care so much about my infrastructure to be honest. I care about my applications and their behavior. I care about my SLAs and my quality of service, right? Those are the things I care about. So I really want an EnterpriseWeb, right? Something that helps me connect all my distributed applications all across all of the environments. So I can have one place a consistency layer that speaks a common language. We know that there's a lot of heterogeneity down all those layers and a lot of complexity down those layers. But the business doesn't care. They don't want to care, right? They want to actually take their applications deploy them where they're the most performant where they're getting the best cost, right? The lowest and maybe sustainability concerns, all those. They want to address those problems, meet their SLAs meet their quality service. And you know what, if it's running on Amazon, great. If it's running on Google Cloud platform, great. If it, you know, we're doing one project right here that we're demonstrating here is with with Amazon Tech Mahindra and OpenShift, where we took a disaggregated 5G core, right? So this is like sort of latest telecom, you know net networking software, right? We're deploying pulling elements of that network across core, across Amazon EKS, OpenShift on Red Hat ROSA, as well as just OpenShift for cloud. And we, through a single pane of deployment and management, we deployed the elements of the 5G core across them and then connected them in an end-to-end process. That's Telco Supercloud. >> Dave Vellante: So that's an O-RAN deployment. >> Yeah that's >> So, the big advantage of that, pardon me, Dave but the big advantage of that is the customer really doesn't care where the components are being served from for them. It's a 5G capability. It happens to sit in different locations. And that's, it's, it's about how do you abstract and how do you manage all those different workloads in a cohesive way? And that's exactly what EnterpriseWeb is bringing to the table. And what we do is we abstract the underlying infrastructure which is the cloud layer. So if, because AWS operating environment is different then private cloud operating environment then Azure environment, you have the networking is set up is different in each one of them. If there is a way you can abstract all of that and present it in a common operating model it becomes a lot easier than for anybody to be able to consume. >> And what a lot of customers tell me is the way they deal with multicloud complexity is they go with mono cloud, right? And so they'll lose out on some of the best services >> Absolutely >> If best of, so that's not >> that's not ideal, but at the end of the day, agree, developers don't want to muck with all the plumbing >> Dave Duggal: Yep. >> They want to write code. >> Azhar: Correct. >> So like I come back to are the traditional Telcos leaning in on a way that they're going to enable ISVs and developers to write on top of those platforms? Or are there sort of new entrance and disruptors? And I know, I know the answer is both >> Dave Duggal: Yep. >> but I feel as though the Telcos still haven't, traditional Telcos haven't tuned in to that developer affinity, but you guys sell to them. >> What, what are you seeing? >> Yeah, so >> What we have seen is there are Telcos fall into several categories there. If you look at the most mature ones, you know they are very eager to move up the value chain. There are some smaller very nimble ones that have actually doing, they're actually doing something really interesting. For example, they've provided sandbox environments to developers to say "Go develop your applications to the sandbox environment." We'll use that to build an net service with you. I can give you some interesting examples across the globe that, where that is happening, right? In AsiaPac, particularly in Australia, ANZ region. There are a couple of providers who have who have done this, but in, in, in a very interesting way. But the challenges to them, why it's not completely open or public yet is primarily because they haven't figured out how to exactly monetize that. And, and that's the reason why. So in the absence of that, what will happen is they they have to rely on the ISV ecosystem to be able to build those capabilities which they can then bring it on as part of the catalog. But in Latin America, I was talking to one of the providers and they said, "Well look we have a public cloud, we have our own public cloud, right?" What we want do is use that to offer localized services not just bring everything in from the top >> But, but we heard from Ericson's CEO they're basically going to monetize it by what I call "gouge", the developers >> (Azhar laughs) >> access to the network telemetry as opposed to saying, "Hey, here's an open platform development on top of it and it will maybe create something like an app store and we'll take a piece of the action." >> So ours, >> to be is a better model. >> Yeah. So that's perfect. Our second project that we're showing here is with Intel, right? So Intel came to us cause they are a reputation for doing advanced automation solutions. They gave us carte blanche in their labs. So this is Intel Network Builders they said pick your partners. And we went with the Red Hat, Fort Net, Keysite this company KX doing AIML. But to address your DevX, here's Intel explicitly wants to get closer to the developers by exposing their APIs, open APIs over their infrastructure. Just like Red Hat has APIs, right? And so they can expose them northbound to developers so developers can leverage and tune their applications, right? But the challenge there is what Intel is doing at the low level network infrastructure, right? Is fundamentally complex, right? What you want is an abstraction layer where develop and this gets to, to your point Dave where you just said like "The developers just want to get their job done." or really they want to focus on the business logic and accelerate that service delivery, right? So the idea here is an EnterpriseWeb they can literally declaratively compose their services, express their intent. "I want this to run optimized for low latency. I want this to run optimized for energy consumption." Right? And that's all they say, right? That's a very high level statement. And then the run time translates it between all the elements that are participating in that service to realize the developer's intent, right? No hands, right? Zero touch, right? So that's now a movement in telecom. So you're right, it's taking a while because these are pretty fundamental shifts, right? But it's intent based networking, right? So it's almost two parts, right? One is you have to have the open APIs, right? So that the infrastructure has to expose its capabilities. Then you need abstractions over the top that make it simple for developers to take, you know, make use of them. >> See, one of the demonstrations we are doing is around AIOps. And I've had literally here on this floor, two conversations around what I call as network as a platform. Although it sounds like a cliche term, that's exactly what Dave was describing in terms of exposing APIs from the infrastructure and utilizing them. So once you get that data, then now you can do analytics and do machine learning to be able to build models and figure out how you can orchestrate better how you can monetize better, how can how you can utilize better, right? So all of those things become important. It's just not about internal optimization but it's also about how do you expose it to third party ecosystem to translate that into better delivery mechanisms or IOT capability and so on. >> But if they're going to charge me for every API call in the network I'm going to go broke (team laughs) >> And I'm going to get really pissed. I mean, I feel like, I'm just running down, Oracle. IBM tried it. Oracle, okay, they got Java, but they don't they don't have developer jobs. VMware, okay? They got Aria. EMC used to have a thing called code. IBM had to buy Red Hat to get to the developer community. (Lisa laughs) >> So I feel like the telcos don't today have those developer shops. So, so they have to partner. [Azhar] Yes. >> With guys like you and then be more open and and let a zillion flowers bloom or else they're going to get disrupted in a big way and they're going to it's going to be a repeat of the over, over the top in, in in a different model that I can't predict. >> Yeah. >> Absolutely true. I mean, look, they cannot be in the connectivity business. Telcos cannot be just in the connectivity business. It's, I think so, you know, >> Dave Vellante: You had a fry a frozen hand (Dave Daggul laughs) >> off that, you know. >> Well, you know, think about they almost have to go become over the top on themselves, right? That's what the cloud guys are doing, right? >> Yeah. >> They're riding over their backbone that by taking a creating a high level abstraction, they in turn abstract away the infrastructure underneath them, right? And that's really the end game >> Right? >> Dave Vellante: Yeah. >> Is because now, >> they're over the top it's their network, it's their infrastructure, right? They don't want to become bid pipes. >> Yep. >> Now you, they can take OpenShift, run that in any cloud. >> Yep. >> Right? >> You can run that in hybrid cloud, enterprise web can do the application layer configuration and management. And together we're running, you know, OSI layers one through seven, east to west, north to south. We're running across the the RAN, the core and the transport. And that is telco super cloud, my friend. >> Yeah. Well, >> (Dave Duggal laughs) >> I'm dominating the conversation cause I love talking super cloud. >> I knew you would. >> So speaking of super superpowers, when you're in customer or prospective customer conversations with providers and they've got, obviously they're they're in this transformative state right now. How, what do you describe as the superpower between Red Hat and EnterpriseWeb in terms of really helping these Telcos transforms. But at the end of the day, the connectivity's there the end user gets what they want, which is I want this to work wherever I am. >> Yeah, yeah. That's a great question, Lisa. So I think the way you could look at it is most software has, has been evolved to be specialized, right? So in Telcos' no different, right? We have this in the enterprise, right? All these specialized stacks, all these components that they wire together in the, in you think of Telco as a sort of a super set of enterprise problems, right? They have all those problems like magnified manyfold, right? And so you have specialized, let's say orchestrators and other tools for every Telco domain for every Telco layer. Now you have a zoo of orchestrators, right? None of them were designed to work together, right? They all speak a specific language, let's say quote unquote for doing a specific purpose. But everything that's interesting in the 21st century is across layers and across domains, right? If a siloed static application, those are dead, right? Nobody's doing those anymore. Even developers don't do those developers are doing composition today. They're not doing, nobody wants to hear about a 6 million lines of code, right? They want to hear, "How did you take these five things and bring 'em together for productive use?" >> Lisa: Right. How did you deliver faster for my enterprise? How did you save me money? How did you create business value? And that's what we're doing together. >> I mean, just to add on to Dave, I was talking to one of the providers, they have more than 30,000 nodes in their infrastructure. When I say no to your servers running, you know, Kubernetes,running open stack, running different components. If try managing that in one single entity, if you will. Not possible. You got to fragment, you got to segment in some way. Now the question is, if you are not exposing that particular infrastructure and the appropriate KPIs and appropriate things, you will not be able to efficiently utilize that across the board. So you need almost a construct that creates like a manager of managers, a hierarchical structure, which would allow you to be more intelligent in terms of how you place those, how you manage that. And so when you ask the question about what's the secret sauce between the two, well this is exactly where EnterpriseWeb brings in that capability to analyze information, be more intelligent about it. And what we do is provide an abstraction of the cloud layer so that they can, you know, then do the right job in terms of making sure that it's appropriate and it's consistent. >> Consistency is key. Guys, thank you so much. It's been a pleasure really digging through EnterpriseWeb. >> Thank you. >> What you're doing >> with Red Hat. How you're helping the organization transform and Supercloud, we can't forget Supercloud. (Dave Vellante laughs) >> Fight Supercloud. Guys, thank you so much for your time. >> Thank you so much Lisa. >> Thank you. >> Thank you guys. >> Very nice. >> Lisa: We really appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage coming to you live from MWC 23. We'll be back after a short break.

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Welcome back to the Fira in Barcelona. This is Dave Vellante with David Nicholson. Lisa Martin is also here. This is day two of our coverage of MWC 23 on theCUBE. We're super excited. We're in between hall four and five. Stop by if you're here. Dennis Hoffman is here. He's the senior vice president and general manager of the Telecom systems business at Dell Technologies, and he's joined by Yousef Khalidi, who's the corporate vice president of Azure for Operators from Microsoft. Gents, Welcome. >> Thanks, Dave. >> Thank you. >> So we saw Satya in the keynote. He wired in. We saw T.K. came in. No AWS. I don't know. They're maybe not part of the show, but maybe next year they'll figure it out. >> Indeed, indeed. >> Lots of stuff happened in the Telecom, but the Azure operator distributed service is the big news, you guys got here. What's that all about? >> Oh, first of all, we changed the name. >> Oh, you did? >> You did? >> Oh, yeah. We have a real name now. It's called the Azure Operator Nexus. >> Oh, I like Nexus better than that. >> David: That's much better, much better. >> Dave: The engineers named it first time around. >> I wish, long story, but thank you for our marketing team. But seriously, not only did we rename the platform, we expanded the platform. >> Dave: Yeah. >> So it now covers the whole spectrum from the far-edge to the public cloud as well, including the near-edge as well. So essentially, it's a hybrid platform that can also run network functions. So all these operators around you, they now have a platform which combines cloud technologies with the choice where they want to run, optimized for the network. >> Okay and so, you know, we've talked about the disaggregation of the network and how you're bringing kind of engineered systems to the table. We've seen this movie before, but Dennis, there are differences, right? I mean, you didn't really have engineered systems in the 90s. You didn't have those integration points. You really didn't have the public cloud, you didn't have AI. >> Right. >> So you have all those new powers that you can tap, so give us the update from your perspective, having now spent a day and a half here. What's the vibe, what's the buzz, and what's your take on everything? >> Yeah, I think to build on what Yousef said, there's a lot going on with people still trying to figure out exactly how to architect the Telecom network of the future. They know it's got to have a lot to do with cloud. It does have some pretty significant differences, one of those being, there's definitely got to be a hybrid component because there are pieces of the Telecom network that even when modernized will not end up centralized, right? They're going to be highly distributed. I would say though, you know, we took away two things, yesterday, from all the meetings. One, people are done, I think the network operators are done, questioning technology readiness. They're now beginning to wrestle with operationalization of it all, right? So it's like, okay, it's here. I can in fact build a modern network in a very cloud native way, but I've got to figure out how to do that all. And another big part of it is the ecosystem and certainly the partnership long standing between Dell and Microsoft which we're extending into this space is part of that, making it easier on people to actually acquire, deploy, and importantly, support these new technologies. >> So a lot of the traditional carriers, like you said, they're sort of beyond the technology readiness. Jose Maria Alvarez in the keynote said there are three pillars to the future Telecom network. He said low latency, programmable networks, and then cloud and edge, kind of threw that in. You agree with that, Yousef? (Dave and Yousef speaking altogether) >> I mean, we've been for years talking about the cloud and edge. >> Yeah. >> Satya for years had the same graphic. We still have it. Today, we have expanded the graphic a bit to include the network as one, because you can have a cloud without connectivity as well but this is very, very, very, very much true. >> And so the question then, Dennis, is okay, you've got disruptors, we had Dish on yesterday. >> Oh, did you? Good. >> Yeah, yeah, and they're talking about what they're doing with, you know, ORAN and all the applications, really taking account of it. What I see is a developer friendly, you know, environment. You got the carriers talking about how they're going to charge developers for APIs. I think they've published eight APIs which is nowhere near enough. So you've got that sort of, you know, inertia and yet, you have the disruptors that are going to potentially be a catalyst to, you know, cross the chasm, if you will. So, you know, put on your strategy hat. >> Yeah. >> Dave: How do you see that playing out? >> Well, they're trying to tap into three things, the disruptors. You know, I think the thesis is, "If I get to a truly cloud native, communications network first, I ought to have greater agility so that I can launch more services and create more revenue streams. I ought to be lower cost in terms of both acquisition cost and operating cost, right, and I ought to be able to create scale between my IT organization, everything I know how to do there and my Telecom network." You know, classic, right? Better, faster, cheaper if I embrace cloud early on. And people like Dish, you know, they have a clean sheet of paper with which to do that. So innovation and rate of innovation is huge for them. >> So what would you do? We put your Clay Christensen hat on, now. What if you were at a traditional Telco who's like, complaining about- >> You're going to get me in trouble. >> Dave: Come on, come on. >> Don't do it. >> Dave: Help him out. Help him out, help him out. So if, you know, they're complaining about CapEx, they're highly regulated, right, they want net neutrality but they want to be able to sort of dial up the cost of those using the network. So what would you do? Would you try to disrupt yourself? Would you create a skunkworks? Would you kind of spin off a disruptor? That's a real dilemma for those guys. >> Well for mobile network operators, the beauty of 5G is it's the first cloud native cellular standard. So I don't know if anybody's throwing these terms around, but 5G SA is standalone, right? >> Dave: Yeah, yeah. >> So a lot of 'em, it's not a skunkworks. They're just literally saying, "I've got to have a 5G network." And some of 'em are deciding, "I'm going to stand it up all by itself." Now, that's duplicative expense in a lot of ways, but it creates isolation from the two networks. Others are saying, "No, it's got to be NSA. I've got to be able to combine 4G and 5G." And then you're into the brownfield thing. >> That's the hybrid. >> Not hybrid as in cloud, but hybrid as in, you know. >> Yeah, yeah. >> It's a converge network. >> Dave: Yeah, yeah. >> So, you know, I would say for a lot of them, they're adopting, probably rightly so, a wait and see attitude. One thing we haven't talked about and you got to get on the table, their high order bit is resilience. >> Dave: Yeah, totally. >> David: Yeah. >> Right? Can't go down. It's national, secure infrastructure, first responder. >> Indeed. >> Anytime you ask them to embrace any new technology, the first thing that they have to work through in their minds is, you know, "Is the juice worth the squeeze? Like, can I handle the risk?" >> But you're saying they're not questioning the technology. Aren't they questioning ORAN in terms of the quality of service, or are they beyond that? >> Dennis: They're questioning the timing, not the inevitability. >> Okay, so they agree that ORAN is going to be open over time. >> At some point, RAN will be cloud native, whether it's ORAN the spec, open RAN the concept, (Yousef speaking indistinctly) >> Yeah. >> Virtual RAN. But yeah, I mean I think it seems pretty evident at this point that the mainframe will give way to open systems once again. >> Dave: Yeah, yeah, yeah. >> ERAN, ecosystem RAN. >> Any RAN. (Dave laughing) >> You don't have to start with the ORAN where they're inside the house. So as you probably know, our partner AT&T started with the core. >> Dennis: They almost all have. >> And they've been on the virtualization path since 2014 and 15. And what we are working with them on is the hybrid cloud model to expand all the way, if you will, as I mentioned to the far-edge or the public cloud. So there's a way to be in the brownfield environment, yet jump on the new bandwagon of technology without necessarily taking too much risk, because you're quite right. I mean, resiliency, security, service assurance, I mean, for example, AT&T runs the first responder network for the US on their network, on our platform, and I'm personally very familiar of how high the bar is. So it's doable, but you need to go in stages, of course. >> And they've got to do that integration. >> Yes. >> They do. >> And Yousef made a great point. Like, out of the top 30 largest Telcos by CapEx outside of China, three quarters of them have virtualized their core. So the cloudification, if you will, software definition run on industry standard hardware, embraced cloud native principles, containerized apps, that's happened in the core. It's well accepted. Now it's just a ripple-down through the network which will happen as and when things are faster, better, cheaper. >> Right. >> So as implemented, what does this look like? Is it essentially what we used to loosely refer to as Azure stacked software, running with Dell optimized Telecom infrastructure together, sometimes within a BBU, out in a hybrid cloud model communicating back to Azure locations in some cases? Is that what we're looking at? >> Approximately. So you start with the near-edge, okay? So the near-edge lives in the operator's data centers, edges, whatever the case may be, built out of off the shelf hardware. Dell is our great partner there but in principle, it could be different mix and match. So once you have that true near-edge, then you can think of, "Okay, how can I make sure this environment is as uniform, same APIs, same everything, regardless what the physical location is?" And this is key, key for the network function providers and the NEPs because they need to be able to port once, run everywhere, and it's key for the operator to reduce their costs. You want to teach your workforce, your operations folks, if you will, how to manage this system one time, to automation and so forth. So, and that is actually an expansion of the Azure capabilities that people are familiar with in a public cloud, projected into different locations. And we have technology called Arc which basically models everything. >> Yeah, yeah. >> So if you have trained your IT side, you are halfway there, how to manage your new network. Even though of course the network is carrier graded, there's different gear. So yes, what you said, a lot of it is true but the actual components, whatever they might be running, are carrier grade, highly optimized, the next images and our solution is not a DIY solution, okay? I know you cater to a wide spectrum here but for us, we don't believe in the TCO. The proper TCO can be achieved by just putting stuff by yourself. We just published a report with Analysys Mason that shows that our approach will save 36 percent of the cost compared to a DIY approach. >> Dave: What percent? >> 36 percent. >> Dave: Of the cost? >> Of, compared to DIY, which is already cheaper than classical models. >> And there's a long history of fairly failed DIY, right, >> Yeah. >> That preceded this. As in the early days of public cloud, the network operators wrestled with, "Do I have to become one to survive?" >> Dave: Yeah. Right. >> So they all ended up having cloud projects and by and large, they've all dematerialized in favor of this. >> Yeah, and it's hard for them to really invest at scale. Let me give you an example. So, your biggest tier one operator, without naming anybody, okay, how many developers do they have that can build and maintain an OS image, or can keep track of container technology, or build monitoring at scale? In our company, we have literally thousands of developers doing it already for the cloud and all we're doing for the operator segment is customizing it and focusing it at the carrier grade aspects of it. But so, I don't have half a dozen exterior experts. I literally have a building of developers who can do that and I'm being literal, here. So it's a scale thing. Once you have a product that you can give to multiple people, everybody benefits. >> Dave: Yeah, and the carriers are largely, they're equipment engineers in a large setting. >> Oh, they have a tough job. I always have total respect what they do. >> Oh totally, and a lot of the work happens, you know, kind of underground and here they are. >> They are network operators. >> They don't touch. >> It's their business. >> Right, absolutely, and they're good at it. They're really good at it. That's right. You know, you think about it, we love to, you know, poke fun at the big carriers, but think about what happened during the pandemic. When they had us shift everything to remote work, >> Dennis: Yes. >> Landline traffic went through the roof. You didn't even notice. >> Yep. That's very true. >> I mean, that's the example. >> That's very true. >> However, in the future where there's innovation and it's going to be driven by developers, right, that's where the open ecosystem comes in. >> Yousef: Indeed. >> And that's the hard transition for a lot of these folks because the developers are going to win that with new workloads, new applications that we can't even think of. >> Dennis: Right. And a lot of it is because if you look at it, there's the fundamental back strategy hat back on, fundamental dynamics of the industry, forced investment, flat revenues. >> Dave: Yeah. Right. >> Very true. >> Right? Every few years, a new G comes out. "Man, I got to retool this massive thing and where I can't do towers, I'm dropping fiber or vice a versa." And meanwhile, most diversification efforts into media have failed. They've had to unwind them and resell them. There's a lot of debt in the industry. >> Yousef: Yeah. >> Dennis: And so, they're looking for that next big, adjacent revenue stream and increasingly deciding, "If I don't modernize my network, I can't get it." >> Can't do it. >> Right, and again, what I heard from some of the carriers in the keynote was, "We're going to charge for API access 'cause we have data in the network." Okay, but I feel like there's a lot more innovation beyond that that's going to come from the disruptors. >> Dennis: Oh yeah. >> Yousef: Yes. >> You know, that's going to blow that away, right? And then that may not be the right model. We'll see, you know? I mean, what would Microsoft do? They would say, "Here, here's a platform. Go develop." >> No, I'll tell you. We are actually working with CAMARA and GSMA on the whole API layer. We actually announced a service as well as (indistinct). >> Dave: Yeah, yeah, right. >> And the key there, frankly, in my opinion, are not the disruptors as in operators. It's the ISV community. You want to get developers that can write to a global set of APIs, not per Telco APIs, such that they can do the innovation. I mean, this is what we've seen in other industries, >> Absolutely. >> That I critically can think of. >> This is the way they get a slice of that pie, right? The recent history of this industry is one where 4G LTE begot the smartphone and app store era, a bevy of consumer services, and almost every single profit stream went somewhere other than the operator, right? >> Yousef: Someone else. So they're looking at this saying, "Okay, 5G is the enterprise G and there's going to be a bevy of applications that are business service related, based on 5G capability and I can't let the OTT, over the top, thing happen again." >> Right. >> They'll say that. "We cannot let this happen." >> "We can't let this happen again." >> Okay, but how do they, >> Yeah, how do they make that not happen? >> Not let it happen again? >> Eight APIs, Dave. The answer is eight APIs. No, I mean, it's this approach. They need to make it easy to work with people like Yousef and more importantly, the developer community that people like Yousef and his company have found a way to harness. And by the way, they need to be part of that developer community themselves. >> And they're not, today. They're not speaking that developer language. >> Right. >> It's hard. You know, hey. >> Dennis: Hey, what's the fastest way to sell an enterprise, a business service? Resell Azure, Teams, something, right? But that's a resale. >> Yeah, that's a resale thing. >> See, >> That's not their service. >> They also need to free their resources from all the plumbing they do and leave it to us. We are plumbers, okay? >> Dennis: We are proud plumbers. >> We are proud plumbers. I'm a plumber. I keep telling people this thing. We had the same discussion with banks and enterprises 10 years ago, by the way. Don't do the plumbing. Go add value on the top. Retool your workforce to do applications and work with ISVs to the verticals, as opposed to either reselling, which many do, or do the plumbing. You'd be surprised. Traditionally, many operators do around, "I want to plumb this thing to get this small interrupt per second." Like, who cares? >> Well, 'cause they made money on connectivity. >> Yes. >> And we've seen this before. >> And in a world without telephone poles and your cables- >> Hey, if what you have is a hammer, everything's a nail, right? And we sell connectivity services and that's what we know how to do, and that both build and sell. And if that's no longer driving a revenue stream sufficient to cover this forced investment march, not to mention Huawei rip and government initiatives to pull infrastructure out and accelerate investment, they got to find new ways. >> I mean, the regulations have been tough, right? They don't go forward and ask for permission. They really can't, right? They have to be much more careful. >> Dennis: It is tough. >> So, we don't mean to sound like it's easy for these guys. >> Dennis: No, it's not. >> But it does require a new mindset, new skillsets, and I think some of 'em are going to figure it out and then pff, the wave, and you guys are going to be riding that wave. >> We're going to try. >> Definitely. Definitely. >> As a veteran of working with both Dell and Microsoft, specifically Azure on things, I am struck by how you're very well positioned in this with Microsoft in particular. Because of Azure's history, coming out of the on-premises world that Microsoft knows so well, there's a natural affinity to the hybrid nature of Telecom. We talk about edge, we talk about hybrid, this is it, absolutely the center of it. So it seems like a- >> Yousef: Indeed. Actually, if you look at the history of Azure, from day one, and I was there from day one, we always spoke of the hybrid model. >> Yeah. >> The third point, we came from the on-premises world. >> David: Right. >> And don't get me wrong, I want people to use the public cloud, but I also know due to physics, regulation, geopolitical boundaries, there's something called on-prem, something called an edge here. I want to add something else. Remember our deal on how we are partner-centric? We're applying the same playbook, here. So, you know, for every dollar we make, so many of it's been done by the ecosystem. Same applies here. So we have announced partnerships with Ericson, Nokia, (indistinct), all the names, and of course with Dell and many others. The ecosystem has to come together and customers must retain their optionality to drum up whatever they are on. So it's the same playbook, with this. >> And enterprise technology companies are, actually, really good at, you know, decoding the customer, figuring out specific requirements, making some mistakes the first time through and then eventually getting it right. And as these trends unfold, you know, you're in a good position, I think, as are others and it's an exciting time for enterprise tech in this industry, you know? >> It really is. >> Indeed. >> Dave: Guys, thanks so much for coming on. >> Thank you. >> Dave: It's great to see you. Have a great rest of the show. >> Thank you. >> Thanks, Dave. Thank you, Dave. >> All right, keep it right there. John Furrier is live in our studio. He's breaking down all the news. Go to siliconangle.com to go to theCUBE.net. Dave Vellante, David Nicholson and Lisa Martin, we'll be right back from the theater in Barcelona, MWC 23 right after this short break. (relaxing music)

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (bright upbeat music plays) >> Welcome back to Barcelona, everybody. You're watching theCUBE's coverage of MWC '23, my name is Dave Vellante. Just left a meeting with the CEO of Cisco, Chuck Robbins, to meet with Jeetu Patel, who's our Executive Vice President and General Manager of security and collaboration at Cisco. Good to see you. >> You never leave a meeting with Chuck Robbins to meet with Jeetu Patel. >> Well, I did. >> That's a bad idea. >> Walked right out. I said, hey, I got an interview to do, right? So, and I'm excited about this. Thanks so much for coming on. >> Thank you for having me. It's a pleasure. >> So, I mean you run such an important part of the business. I mean, obviously the collaboration business but also security. So many changes going on in the security market. Maybe we could start there. I mean, there hasn't been a ton of security talk here Jeetu, because I think it's almost assumed. It was 45 minutes into the keynote yesterday before anybody even mentioned security. >> Huh. >> Right? And so, but it's the most important topic in the enterprise IT world. And obviously is important here. So why is it you think that it's not the first topic that people mention. >> You know, it's a complicated subject area and it's intimidating. And actually that's one of the things that the industry screwed up on. Where we need to simplify security so it actually gets to be relatable for every person on the planet. But, if you think about what's happening in security, it's not just important for business it's critical infrastructure that if you had a breach, you know lives are cost now. Because hospitals could go down, your water supply could go down, your electricity could go down. And so it's one of these things that we have to take pretty seriously. And, it's 51% of all breaches happen because of negligence, not because of malicious intent. >> It's that low. Interesting. I always- >> Someone else told me the same thing, that they though it'd be higher, yeah. >> I always say bad user behavior is going to trump good security every time. >> Every single time. >> You can't beat it. But, you know, it's funny- >> Jeetu: Every single time. >> Back, the earlier part of last decade, you could see that security was becoming a board level issue. It became, it was on the agenda every quarter. And, I remember doing some research at the time, and I asked, I was interviewing Robert Gates, former Defense Secretary, and I asked him, yeah, but we're getting attacked but don't we have the best offense? Can't we have the best technology? He said, yeah but we have so much critical infrastructure the risks to United States are higher. So we have to be careful about how we use security as an offensive weapon, you know? And now you're seeing the future of war involves security and what's going on in Ukraine. It's a whole different ballgame. >> It is, and the scales always tip towards the adversary, not towards the defender, because you have to be right every single time. They have to be right once. >> Yeah. And, to the other point, about bad user behavior. It's going now beyond the board level, to it's everybody's responsibility. >> That's right. >> And everybody's sort of aware of it, everybody's been hacked. And, that's where it being such a complicated topic is problematic. >> It is, and it's actually, what got us this far will not get us to where we need to get to if we don't simplify security radically. You know? The experience has to be almost invisible. And what used to be the case was sophistication had to get to a certain level, for efficacy to go up. But now, that sophistication has turned to complexity. And there's an inverse relationship between complexity and efficacy. So the simpler you make security, the more effective it gets. And so I'll give you an example. We have this great kind of innovation we've done around passwordless, right? Everyone hates passwords. You shouldn't have passwords in 2023. But, when you get to passwordless security, not only do you reduce a whole lot of friction for the user, you actually make the system safer. And that's what you need to do, is you have to make it simpler while making it more effective. And, I think that's what the future is going to hold. >> Yeah, and CISOs tell me that they're, you know zero trust before the pandemic was like, yeah, yeah zero trust. And now it's like a mandate. >> Yeah. >> Every CISO you talk to says, yes we're implementing a zero trust architecture. And a big part of that is that, if they can confirm zero trust, they can get to market a lot faster with revenue generating or critical projects. And many projects as we know are being pushed back, >> Yeah. >> you know? 'Cause of the macro. But, projects that drive revenue and value they want to accelerate, and a zero trust confirmation allows people to rubber stamp it and go faster. >> And the whole concept of zero trust is least privileged access, right? But what we want to make sure that we get to is continuous assessment of least privileged access, not just a one time at login. >> Dave: 'Cause things change so frequently. >> So, for example, if you happen to be someone that's logged into the system and now you start doing some anomalous behavior that doesn't sound like Dave, we want to be able to intercept, not just do it at the time that you're authenticating Dave to come in. >> So you guys got a good business. I mentioned the macro before. >> Yeah. >> The big theme is consolidating redundant vendors. So a company with a portfolio like Cisco's obviously has an advantage there. You know, you guys had great earnings. Palo Alto is another company that can consolidate. Tom Gillis, great pickup. Guy's amazing, you know? >> Love Tom. >> Great respect. Just had a little webinar session with him, where he was geeking out with the analyst and so- >> Yeah, yeah. >> Learned a lot there. Now you guys have some news, at the event event with Mercedes? >> We do. >> Take us through that, and I want to get your take on hybrid work and what's happening there. But what's going on with Mercedes? >> Yeah so look, it all actually stems from the hybrid work story, which is the future is going to be hybrid, people are going to work in mixed mode. Sometimes you'll be in the office, sometimes at home, sometimes somewhere in the middle. One of the places that people are working more and more from is their cars. And connected cars are getting to be a reality. And in fact, cars sometimes become an extension of your home office. And many a times I have found myself in a parking lot, because I didn't have enough time to get home and I was in a parking lot taking a conference call. And so we've made that section easier, because we have now partnered with Mercedes. And they aren't the first partner, but they're a very important partner where we are going to have Webex available, through the connected car, natively in Mercedes. >> Ah, okay. So I could take a call, I can do it all the time. I find good service, pull over, got to take the meeting. >> Yeah. >> I don't want to be driving. I got to concentrate. >> That's right. >> You know, or sometimes, I'll have the picture on and it's not good. >> That's right. >> Okay, so it'll be through the console, and all through the internet? >> It'll be through the console. And many people ask me like, how's safety going to work over that? Because you don't want to do video calls while you're driving. Exactly right. So when you're driving, the video automatically turns off. And you'll have audio going on, just like a conference call. But the moment you stop and put it in park, you can have video turned on. >> Now, of course the whole hybrid work trend, we, seems like a long time ago but it doesn't, you know? And it's really changed the security dynamic as well, didn't it? >> It has, it has. >> I mean, immediately you had to go protect new endpoints. And those changes, I felt at the time, were permanent. And I think it's still the case, but there's an equilibrium now happening. People as they come back to the office, you see a number of companies are mandating back to work. Maybe the central offices, or the headquarters, were underfunded. So what's going on out there in terms of that balance? >> Well firstly, there's no unanimous consensus on the way that the future is going to be, except that it's going to be hybrid. And the reason I say that is some companies mandate two days a week, some companies mandate five days a week, some companies don't mandate at all. Some companies are completely remote. But whatever way you go, you want to make sure that regardless of where you're working from, people can have an inclusive experience. You know? And, when they have that experience, you want to be able to work from a managed device or an unmanaged device, from a corporate network or from a Starbucks, from on the road or stationary. And whenever you do any of those things, we want to make sure that security is always handled, and you don't have to worry about that. And so the way that we say it is the company that created the VPN, which is Cisco, is the one that's going to kill it. Because what we'll do is we'll make it simple enough so that you don't, you as a user, never have to worry about what connection you're going to use to dial in to what app. You will have one, seamless way to dial into any application, public application, private application, or directly to the internet. >> Yeah, I got a love, hate with my VPN. I mean, it's protecting me, but it's in the way a lot. >> It's going to be simple as ever. >> Do you have kids? >> I do, I have a 12 year old daughter. >> Okay, so not quite high school age yet. She will be shortly. >> No, but she's already, I'm not looking forward to high school days, because she has a very, very strong sense of debate and she wins 90% of the arguments. >> So when my kids were that age, I've got four kids, but the local high school banned Wikipedia, they can't use Wikipedia for research. Many colleges, I presume high schools as well, they're banning Chat GPT, can't use it. Now at the same time, I saw recently on Medium a Wharton school professor said he's mandating Chat GPT to teach his students how to prompt in progressively more sophisticated prompts, because the future is interacting with machines. You know, they say in five years we're all going to be interacting in some way, shape, or form with AI. Maybe we already are. What's the intersection between AI and security? >> So a couple very, very consequential things. So firstly on Chat GPT, the next generation skill is going to be to learn how to go out and have the right questions to ask, which is the prompt revolution that we see going on right now. But if you think about what's happening in security, and there's a few areas which are, firstly 3,500 hundred vendors in this space. On average, most companies have 50 to 70 vendors in security. Not a single vendor owns more than 10% of the market. You take out a couple vendors, no one owns more than 5%. Highly fractured market. That's a problem. Because it's untenable for companies to go out and manage 70 policy engines. And going out and making sure that there's no contention. So as you move forward, one of the things that Chat GPT will be really good for is it's fundamentally going to change user experiences, for how software gets built. Because rather than it being point and click, it's going to be I'm going to provide an instruction and it's going to tell me what to do in natural language. Imagine Dave, when you joined a company if someone said, hey give Dave all the permissions that he needs as a direct report to Chuck. And instantly you would get all of the permissions. And it would actually show up in a screen that says, do you approve? And if you hit approve, you're done. The interfaces of the future will get more natural language kind of dominated. The other area that you'll see is the sophistication of attacks and the surface area of attacks is increasing quite exponentially. And we no longer can handle this with human scale. You have to handle it in machine scale. So detecting breaches, making sure that you can effectively and quickly respond in real time to the breaches, and remediate those breaches, is all going to happen through AI and machine learning. >> So, I agree. I mean, just like Amazon turned the data center into an API, I think we're now going to be interfacing with technology through human language. >> That's right. >> I mean I think it's a really interesting point you're making. Now, from a security standpoint as well, I mean, the state of the art today in my email is be careful, this person's outside your organization. I'm like, yeah I know. So it's a good warning sign, but it's really not automated in any way. So two part question. One is, can AI help? You know, with the phishing, obviously it can, but the bad guys have AI too. >> Yeah. >> And they're probably going to be smarter than I am about using it. >> Yeah, and by the way, Talos is our kind of threat detection and response >> Yes. >> kind of engine. And, they had a great kind of piece that came out recently where they talked about this, where Chat GPT, there is going to be more sophistication of the folks that are the bad actors, the adversaries in using Chat GPT to have more sophisticated phishing attacks. But today it's not something that is fundamentally something that we can't handle just yet. But you still need to do the basic hygiene. That's more important. Over time, what you will see is attacks will get more bespoke. And in order, they'll get more sophisticated. And, you will need to have better mechanisms to know that this was actually not a human being writing that to you, but it was actually a machine pretending to be a human being writing something to you. And that you'll have to be more clever about it. >> Oh interesting. >> And so, you will see attacks get more bespoke and we'll have to get smarter and smarter about it. >> The other thing I wanted to ask you before we close is you're right on. I mean you take the top security vendors and they got a single digit market share. And it's like it's untenable for organizations, just far too many tools. We have a partner at ETR, they do quarterly survey research and one of the things they do is survey emerging technology companies. And when we look at in the security sector just the number of emerging technology companies that are focused on cybersecurity is as many as there are out there already. And so, there's got to be consolidation. Maybe that's through M & A. I mean, what do you think happens? Are company's going to go out of business? There's going to be a lot of M & A? You've seen a lot of companies go private. You know, the big PE companies are sucking up all these security companies and may be ready to spit 'em out and go back public. How do you see the landscape? You guys are obviously an inquisitive company. What are your thoughts on that? >> I think there will be a little bit of everything. But the biggest change that you'll see is a shift that's going to happen with an integrated platform, rather than point solution vendors. So what's going to happen is the market's going to consolidate towards very few, less than a half a dozen, integrated platforms. We believe Cisco is going to be one. Microsoft will be one. There'll be others over there. But these, this platform will essentially be able to provide a unified kind of policy engine across a multitude of different services to protect multiple different entities within the organization. And, what we found is that platform will also be something that'll provide, through APIs, the ability for third parties to be able to get their technology incorporated in, and their telemetry ingested. So we certainly intend to do that. We don't believe, we are not arrogant enough to think that every single new innovation will be built by us. When there's someone else who has built that, we want to make sure that we can ingest that telemetry as well, because the real enemy is not the competitor. The real enemy is the adversary. And we all have to get together, so that we can keep humanity safe. >> Do you think there's been enough collaboration in the industry? I mean- >> Jeetu: Not nearly enough. >> We've seen companies, security companies try to monetize private data before, instead of maybe sharing it with competitors. And so I think the industry can do better there. >> Well I think the industry can do better. And we have this concept called the security poverty line. And the security poverty line is the companies that fall below the security poverty line don't have either the influence or the resources or the know how to keep themselves safe. And when they go unsafe, everyone else that communicates with them also gets that exposure. So it is in our collective interest for all of us to make sure that we come together. And, even if Palo Alto might be a competitor of ours, we want to make sure that we invite them to say, let's make sure that we can actually exchange telemetry between our companies. And we'll continue to do that with as many companies that are out there, because actually that's better for the market, that's better for the world. >> The enemy of the enemy is my friend, kind of thing. >> That's right. >> Now, as it relates to, because you're right. I mean I, I see companies coming up, oh, we do IOT security. I'm like, okay, but what about cloud security? Do you that too? Oh no, that's somebody else. But, so that's another stove pipe. >> That's a huge, huge advantage of coming with someone like Cisco. Because we actually have the entire spectrum, and the broadest portfolio in the industry of anyone else. From the user, to the device, to the network, to the applications, we provide the entire end-to-end story for security, which then has the least amount of cracks that you can actually go out and penetrate through. The biggest challenges that happen in security is you've got way too many policy engines with way too much contention between the policies from these different systems. And eventually there's a collision course. Whereas with us, you've actually got a broad portfolio that operates as one platform. >> We were talking about the cloud guys earlier. You mentioned Microsoft. They're obviously a big competitor in the security space. >> Jeetu: But also a great partner. >> So that's right. To my opinion, the cloud has been awesome as a first line of defense if you will. But the shared responsibility model it's different for each cloud, right? So, do you feel that those guys are working together or will work together to actually improve? 'Cause I don't see that yet. >> Yeah so if you think about, this is where we feel like we have a structural advantage in this, because what does a company like Cisco become in the future? I think as the world goes multicloud and hybrid cloud, what'll end up happening is there needs to be a way, today all the CSPs provide everything from storage to computer network, to security, in their own stack. If we can abstract networking and security above them, so that we can acquire and steer any and all traffic with our service providers and steer it to any of those CSPs, and make sure that the security policy transcends those clouds, you would actually be able to have the public cloud economics without the public cloud lock-in. >> That's what we call super cloud Jeetu. It's securing the super cloud. >> Yeah. >> Hey, thanks so much for coming to theCUBE. >> Thank you for having me. >> Really appreciate you coming on our editorial program. >> Such a pleasure. >> All right, great to see you again. >> Cheers. >> All right, keep it right there. Dave Vellante with David Nicholson and Lisa Martin. We'll be back, right after this short break from MWC '23 live, in the Fira, in Barcelona. (bright music resumes) (music fades out)

(intense music) >> Hello, I'm John Furrier with "SiliconANGLE News" and the host of theCUBE here in Palo Alto, with coverage of MWC 2023. theCUBE is onsite in Barcelona, four days of wall to wall coverage. Here is a news update from MWC and in the news here is Google. Google Cloud targets cloud native network transformation for all the carriers or cloud service providers, and the communication service providers. They announced three new products to help communications service providers, also known as CSPs, build, deploy and operate hybrid cloud native networks, as well as collect and manage network data. The new products, when combined with Unified Cloud, enables the CSPs to improve customer experience, artificial intelligence, and data analytics. This is a big move, because 70% of communication service providers are expected to adopt cloud native network functions by the end of this year, making it a big, big wave. One of the key features of Google's products is the telecom network automation. This cloud service accelerates CSPs network and edge deployments through the use of Kubernetes based cloud native automation tools. It's managed by a cloud version of open source Nephio, project that Google founded in 2022. Of course, other key product announcements with Google, the Telecom Data Fabric, a tool that helps CSPs generate insights. That's the data driven piece, to target and optimize their network performance and reliability, works by simplifying the collection, normalization, correlation through an adaptive framework. This is kind of where AI shines. Finally, Google has telecom subscriber insights, a powerful AI tool that enables CSPs to extract insights from existing data sources in a privacy safe environment. Let's see if this is better than Bing search, we'll see. But CSPs are moving to the cloud across all channels. This is a really important trend, as cloud native scale, AI, data, configuration, automation all come to the edge of the network. That's an update from "SiliconANGLE News". Check out the coverage on siliconangle.com. Of course, thecube.net, four days, Dave Vellante and Lisa Martin are there. I'm here in Palo Alto. Thanks for watching. (slow music) (upbeat music)

(gentle music) >> Announcer: "theCube's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo whooshing) >> Hey, everyone, welcome back to "theCube's" coverage of day one, MWC23 live from Barcelona, Lisa Martin here with Dave Vellante. Dave, we've got some great conversations so far This is the biggest, most packed show I've been to in years. About 80,000 people here so far. >> Yeah, down from its peak of 108, but still pretty good. You know, a lot of folks from China come to this show, but with the COVID situation in China, that's impacted the attendance, but still quite amazing. >> Amazing for sure. We're going to be talking about trends and mobility, and all sorts of great things. We have a couple of guests joining us for the first time on "theCUBE." Please welcome Dr. Srinivas Mukkamala or Sri, chief product officer at Ivanti. And Dave Shepherd, VP Ivanti. Guys, welcome to "theCUBE." Great to have you here. >> Thank you. >> So, day one of the conference, Sri, we'll go to you first. Talk about some of the trends that you're seeing in mobility. Obviously, the conference renamed from Mobile World Congress to MWC mobility being part of it, but what are some of the big trends? >> It's interesting, right? I mean, I was catching up with Dave. The first thing is from the keynotes, it took 45 minutes to talk about security. I mean, it's quite interesting when you look at the shore floor. We're talking about Edge, we're talking about 5G, the whole evolution. And there's also the concept of are we going into the Cloud? Are we coming back from the Cloud, back to the Edge? They're really two different things. Edge is all decentralized while you recompute. And one thing I observed here is they're talking about near real-time reality. When you look at automobiles, when you look at medical, when you look at robotics, you can't have things processed in the Cloud. It'll be too late. Because you got to make millisecond-based stations. That's a big trend for me. When I look at staff... Okay, the compute it takes to process in the Cloud versus what needs to happen on-prem, on device, is going to revolutionize the way we think about mobility. >> Revolutionize. David, what are some of the things that you're saying? Do you concur? >> Yeah, 100%. I mean, look, just reading some of the press recently, they're predicting 22 billion IoT devices by 2024. Everything Sri just talked about there. It's growing exponentially. You know, problems we have today are a snapshot. We're probably in the slowest place we are today. Everything's just going to get faster and faster and faster. So it's a, yeah, 100% concur with that. >> You know, Sri, on your point, so Jose Maria Alvarez, the CEO of Telefonica, said there are three pillars of the future of telco, low latency, programmable networks, and Cloud and Edge. So, as to your point, Cloud and low latency haven't gone hand in hand. But the Cloud guys are saying, "All right, we're going to bring the Cloud to the Edge." That's sort of an interesting dynamic. We're going to bypass them. We heard somebody, another speaker say, "You know, Cloud can't do it alone." You know? (chuckles) And so, it's like these worlds need each other in a way, don't they? >> Definitely right. So that's a fantastic way to look at it. The Cloud guys can say, "We're going to come closer to where the computer is." And if you really take a look at it with data localization, where are we going to put the Cloud in, right? I mean, so the data sovereignty becomes a very interesting thing. The localization becomes a very interesting thing. And when it comes to security, it gets completely different. I mean, we talked about moving everything to a centralized compute, really have massive processing, and give you the addition back wherever you are. Whereas when you're localized, I have to process everything within the local environment. So there's already a conflict right there. How are we going to address that? >> Yeah. So another statement, I think, it was the CEO of Ericsson, he was kind of talking about how the OTT guys have heard, "We can't let that happen again. And we're going to find new ways to charge for the network." Basically, he's talking about monetizing the API access. But I'm interested in what you're hearing from customers, right? 'Cause our mindset is, what value you're going to give to customers that they're going to pay for, versus, "I got this data I'm going to charge developers for." But what are you hearing from customers? >> It's amazing, Dave, the way you're looking at it, right? So if we take a look at what we were used to perpetual, and we said we're going to move to a subscription, right? I mean, everybody talks about subscription economy. Telcos on the other hand, had subscription economy for a long time, right? They were always based on usage, right? It's a usage economy. But today, we are basically realizing on compute. We haven't even started charging for compute. If you go to AWS, go to Azure, go to GCP, they still don't quite charge you for actual compute, right? It's kind of, they're still leaning on it. So think about API-based, we're going to break the bank. What people don't realize is, we do millions of API calls for any high transaction environment. A consumer can't afford that. What people don't realize is... I don't know how you're going to monetize. Even if you charge a cent a call, that is still going to be hundreds and thousands of dollars a day. And that's where, if you look at what you call low-code no-code motion? You see a plethora of companies being built on that. They're saying, "Hey, you don't have to write code. I'll give you authentication as a service. What that means is, Every single time you call my API to authenticate a user, I'm going to charge you." So just imagine how many times we authenticate on a single day. You're talking a few dozen times. And if I have to pay every single time I authenticate... >> Real friction in the marketplace, David. >> Yeah, and I tell you what. It's a big topic, right? And it's a topic that we haven't had to deal with at the Edge before, and we hear it probably daily really, complexity. The complexity's growing all the time. That means that we need to start to get insight, visibility. You know? I think a part of... Something that came out of the EU actually this week, stated, you know, there's a cyber attack every 11 seconds. That's fast, right? 2016, that was 40 seconds. So actually that speed I talked about earlier, everything Sri says that's coming down to the Edge, we want to embrace the Edge and that is the way we're going to move. But customers are mindful of the complexity that's involved in that. And that, you know, lens thought to how are we going to deal with those complexities. >> I was just going to ask you, how are you planning to deal with those complexities? You mentioned one ransomware attack every 11 seconds. That's down considerably from just a few years ago. Ransomware is a household word. It's no longer, "Are we going to get attacked?" It's when, it's to what extent, it's how much. So how is Ivanti helping customers deal with some of the complexities, and the changes in the security landscape? >> Yeah. Shall I start on that one first? Yeah, look, we want to give all our customers and perspective customers full visibility of their environment. You know, devices that are attached to the environment. Where are they? What are they doing? How often are we going to look for those devices? Not only when we find those devices. What applications are they running? Are those applications secure? How are we going to manage those applications moving forward? And overall, wrapping it round, what kind of service are we going to do? What processes are we going to put in place? To Sri's point, the low-code no-code angle. How do we build processes that protect our organization? But probably a point where I'll pass to Sri in a moment is how do we add a level of automation to that? How do we add a level of intelligence that doesn't always require a human to be fixing or remediating a problem? >> To Sri, you mentioned... You're right, the keynote, it took 45 minutes before it even mentioned security. And I suppose it's because they've historically, had this hardened stack. Everything's controlled and it's a safe environment. And now that's changing. So what would you add? >> You know, great point, right? If you look at telcos, they're used to a perimeter-based network. >> Yep. >> I mean, that's what we are. Boxed, we knew our perimeter. Today, our perimeter is extended to our home, everywhere work, right? >> Yeah- >> We don't have a definition of a perimeter. Your browser is the new perimeter. And a good example, segueing to that, what we have seen is horizontal-based security. What we haven't seen is verticalization, especially in mobile. We haven't seen vertical mobile security solutions, right? Yes, you hear a little bit about automobile, you hear a little bit about healthcare, but what we haven't seen is, what about food sector? What about the frontline in food? What about supply chain? What security are we really doing? And I'll give you a simple example. You brought up ransomware. Last night, Dole was attacked with ransomware. We have seen the beef producer colonial pipeline. Now, if we have seen agritech being hit, what does it mean? We are starting to hit humanity. If you can't really put food on the table, you're starting to really disrupt the supply chain, right? In a massive way. So you got to start thinking about that. Why is Dole related to mobility? Think about that. They don't carry service and computers. What they carry is mobile devices. that's where the supply chain works. And then that's where you have to start thinking about it. And the evolution of ransomware, rather than a single-trick pony, you see them using multiple vulnerabilities. And Pegasus was the best example. Spyware across all politicians, right? And CEOs. It is six or seven vulnerabilities put together that actually was constructed to do an attack. >> Yeah. How does AI kind of change this? Where does it fit in? The attackers are going to have AI, but we could use AI to defend. But attackers are always ahead, right? (chuckles) So what's your... Do you have a point of view on that? 'Cause everybody's crazy about ChatGPT, right? The banks have all banned it. Certain universities in the United States have banned it. Another one's forcing his students to learn how to use ChatGPT to prompt it. It's all over the place. You have a point of view on this? >> So definitely, Dave, it's a great point. First, we all have to have our own generative AI. I mean, I look at it as your digital assistant, right? So when you had calculators, you can't function without a calculator today. It's not harmful. It's not going to take you away from doing multiplication, right? So we'll still teach arithmetic in school. You'll still use your calculator. So to me, AI will become an integral part. That's one beautiful thing I've seen on the short floor. Every little thing there is a AI-based solution I've seen, right? So ChatGPT is well played from multiple perspective. I would rather up level it and say, generated AI is the way to go. So there are three things. There is human intense triaging, where humans keep doing easy work, minimal work. You can use ML and AI to do that. There is human designing that you need to do. That's when you need to use AI. >> But, I would say this, in the Enterprise, that the quality of the AI has to be better than what we've seen so far out of ChatGPT, even though I love ChatGPT, it's amazing. But what we've seen from being... It's got to be... Is it true that... Don't you think it has to be cleaner, more accurate? It can't make up stuff. If I'm going to be automating my network with AI. >> I'll answer that question. It comes down to three fundamentals. The reason ChatGPT is giving addresses, it's not trained on the latest data. So for any AI and ML method, you got to look at three things. It's your data, it's your domain expertise, who is training it, and your data model. In ChatGPT, it's older data, it's biased to the people that trained it, right? >> Mm-hmm. >> And then, the data model is it's going to spit out what it's trained on. That's a precursor of any GPT, right? It's pre-trained transformation. >> So if we narrow that, right? Train it better for the specific use case, that AI has huge potential. >> You flip that to what the Enterprise customers talk about to us is, insight is invaluable. >> Right. >> But then too much insight too quickly all the time means we go remediation crazy. So we haven't got enough humans to be fixing all the problems. Sri's point with the ChatGPT data, some of that data we are looking at there could be old. So we're trying to triage something that may still be an issue, but it might have been superseded by something else as well. So that's my overriding when I'm talking to customers and we talk ChatGPT, it's in the news all the time. It's very topical. >> It's fun. >> It is. I even said to my 13-year-old son yesterday, your homework's out a date. 'Cause I knew he was doing some summary stuff on ChatGPT. So a little wind up that's out of date just to make that emphasis around the model. And that's where we, with our Neurons platform Ivanti, that's what we want to give the customers all the time, which is the real-time snapshot. So they can make a priority or a decision based on what that information is telling them. >> And we've kind of learned, I think, over the last couple of years, that access to real-time data, real-time AI, is no longer nice to have. It's a massive competitive advantage for organizations, but it's going to enable the on-demand, everything that we expect in our consumer lives, in our business lives. This is going to be table stakes for organizations, I think, in every industry going forward. >> Yeah. >> But assumes 5G, right? Is going to actually happen and somebody's going to- >> Going to absolutely. >> Somebody's going to make some money off it at some point. When are they going to make money off of 5G, do you think? (all laughing) >> No. And then you asked a very good question, Dave. I want to answer that question. Will bad guys use AI? >> Yeah. Yeah. >> Offensive AI is a very big thing. We have to pay attention to it. It's got to create an asymmetric war. If you look at the president of the United States, he said, "If somebody's going to attack us on cyber, we are going to retaliate." For the first time, US is willing to launch a cyber war. What that really means is, we're going to use AI for offensive reasons as well. And we as citizens have to pay attention to that. And that's where I'm worried about, right? AI bias, whether it's data, or domain expertise, or algorithmic bias, is going to be a big thing. And offensive AI is something everybody have to pay attention to. >> To your point, Sri, earlier about critical infrastructure getting hacked, I had this conversation with Dr. Robert Gates several years ago, and I said, "Yeah, but don't we have the best offensive, you know, technology in cyber?" And he said, "Yeah, but we got the most to lose too." >> Yeah, 100%. >> We're the wealthiest nation of the United States. The wealthiest is. So you got to be careful. But to your point, the president of the United States saying, "We'll retaliate," right? Not necessarily start the war, but who started it? >> But that's the thing, right? Attribution is the hardest part. And then you talked about a very interesting thing, rich nations, right? There's emerging nations. There are nations left behind. One thing I've seen on the show floor today is, digital inequality. Digital poverty is a big thing. While we have this amazing technology, 90% of the world doesn't have access to this. >> Right. >> What we have done is we have created an inequality across, and especially in mobility and cyber, if this technology doesn't reach to the last mile, which is emerging nations, I think we are creating a crater back again and putting societies a few miles back. >> And at much greater risk. >> 100%, right? >> Yeah. >> Because those are the guys. In cyber, all you need is a laptop and a brain to attack. >> Yeah. Yeah. >> If I don't have it, that's where the civil war is going to start again. >> Yeah. What are some of the things in our last minute or so, guys, David, we'll start with you and then Sri go to you, that you're looking forward to at this MWC? The theme is velocity. We're talking about so much transformation and evolution in the telecom industry. What are you excited to hear and learn in the next couple of days? >> Just getting a complete picture. One is actually being out after the last couple of years, so you learn a lot. But just walking around and seeing, from my perspective, some vendor names that I haven't seen before, but seeing what they're doing and bringing to the market. But I think goes back to the point made earlier around APIs and integration. Everybody's talking about how can we kind of do this together in a way. So integrations, those smart things is what I'm kind of looking for as well, and how we plug into that as well. >> Excellent, and Sri? >> So for us, there is a lot to offer, right? So while I'm enjoying what I'm seeing here, I'm seeing at an opportunity. We have an amazing portfolio of what we can do. We are into mobile device management. We are the last (indistinct) company. When people find problems, somebody has to go remediators. We are the world's largest patch management company. And what I'm finding is, yes, all these people are embedding software, pumping it like nobody's business. As you find one ability, somebody has to go fix them, and we want to be the (indistinct) company. We had the last smile. And I find an amazing opportunity, not only we can do device management, but do mobile threat defense and give them a risk prioritization on what needs to be remediated, and manage all that in our ITSM. So I look at this as an amazing, amazing opportunity. >> Right. >> Which is exponential than what I've seen before. >> So last question then. Speaking of opportunities, Sri, for you, what are some of the things that customers can go to? Obviously, you guys talk to customers all the time. In terms of learning what Ivanti is going to enable them to do, to take advantage of these opportunities. Any webinars, any events coming up that we want people to know about? >> Absolutely, ivanti.com is the best place to go because we keep everything there. Of course, "theCUBE" interview. >> Of course. >> You should definitely watch that. (all laughing) No. So we have quite a few industry events we do. And especially there's a lot of learning. And we just raised the ransomware report that actually talks about ransomware from a global index perspective. So one thing what we have done is, rather than just looking at vulnerabilities, we showed them the weaknesses that led to the vulnerabilities, and how attackers are using them. And we even talked about DHS, how behind they are in disseminating the information and how it's actually being used by nation states. >> Wow. >> And we did cover mobility as a part of that as well. So there's a quite a bit we did in our report and it actually came out very well. >> I have to check that out. Ransomware is such a fascinating topic. Guys, thank you so much for joining Dave and me on the program today, sharing what's going on at Ivanti, the changes that you're seeing in mobile, and the opportunities that are there for your customers. We appreciate your time. >> Thank you >> Thank you. >> Yes. Thanks, guys. >> Thanks, guys. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching "theCUBE" live from MWC23 in Barcelona. As you know, "theCUBE" is the leader in live tech coverage. Dave and I will be right back with our next guest. (gentle upbeat music)