>>Live from Barcelona, Spain. It's the Cube covering Cisco Live 2020 right to you by Cisco and its ecosystem partners. >>Welcome back, everyone to the Cube's live coverage Day four of four days of wall to wall action here in Barcelona, Spain, for Cisco Live. 2020. I'm John Furrier with my co host Dave Volante, with a very special guest here to wrap up Cisco Live. The president of Europe, Middle East Africa and Russia. Francisco Wendy Mars Cube Alumni. Great to see you. Thanks for coming on to. I kind of put a book into the show here. Thanks for joining us. >>It's absolutely great to be here. Thank you. >>So what a transformation. As Cisco's business model of continues to evolve, we've been saying brick by brick, we still think big move coming. I think there's more action. I can sense the walls talking to us like Cisco live in the US and more technical announcement. In the next 24 months, you can see you can see where it's going. It's cloud, it's APS. It's policy based program ability. It's really a whole another business model shift for you and your customers. Technology shift in the business model shift. So I want to get your perspective this year. Opening. Keynote. Oh, you let it off Talking about the philosophy of the business model, but also the first presenter was not a networking guy. It was an application person. App dynamics. Yep, this is a shift. What's going on with Cisco? What's happening? What's the story? >>You know, if if you look for all of the work that we're doing is is really driven by what we see from requirements from our customers to change, that's happening in the market and it is all around. You know, if you think digital transformation is the driver organizations now are incredibly interested in, how do they capture that opportunity? How do they use technology to help them? But, you know, if you look at it, really, there's the three items that are so important it's the business model evolution. It's actually the business operations for for organizations. Plus, there people, they're people in the communities within that those three things working together. And if you look at it with, it's so exciting with application dynamics there because if you look for us within Cisco, that linkage off the application layer through into the infrastructure into the network. And bringing that linkage together is the most powerful thing because that's the insights and the value our customers are looking for. >>You know, we've been talking about the the innovation sandwich, you know, you got data in the middle and you've got technology and applications underneath. That's kind of what's going on here, but I'm glad you brought up the part about business model. This is operations and people in communities. During your keynote, you had a slide that laid out three kind of pillars. Yes, people in communities, business model and business operations. There was no 800 series in there. There was no product discussions. This is fundamentally the big shift that business models are changing. I tweeted provocatively, the killer wrap in digital business model. Because you think about it. The applications are the business. What's running under the covers is the technology, but it's all shifting and changing, so every single vertical every single business is impacted by. This is not like a certain secular thing in the industry. This is a real change. Can you describe how those three things are operating with that can >>sure. I think if you look from, you know, so thinking through those three areas. If you look at the actual business model itself, our business models is organizations are fundamentally changing and they're changing towards as consumers. We are all much more specific about what we want. We have incredible choice in the market. We are more informed than ever before. But also we are interested in the values of the organizations that we're getting the capability from us as well as the products and the services that naturally we're looking to gain. So if you look in that business model itself, this is about, you know, organizations making sure they stay ahead from a competitive standpoint about the innovation of portfolio that they're able to bring, but also that they have a strong, strong focus around the experience, that they're customer gains from an application, a touch standpoint that all comes through those different channels, which is at the end of the day, the application. Then if you look as to how do you deliver that capability through the systems, the tools, the processes? As we all evolve, our businesses have to change the dynamic within your organization to cope with that. And then, of course, in driving any transformation, the critical success factor is your people and your culture. You need your teams with you. The way teams operate now is incredibly different. It's no longer command and control. It's agile capability coming together. You need that to deliver on any transformation. Never, never mind. Let it be smooth, you know, in the execution they're all three together. >>But what I like about that model and I have to say, this is, you know, 10 years of doing the Cube, you see that marketing in the vendor community often leads what actually happens. Not surprising as we entered the last decade, there's a lot of talk about Cloud. Well, it kind of was a good predictor. We heard a lot about digital transformation. A lot of people roll their eyes and think it's a buzzword, but we really are. I feel like exiting this cloud era into the digital era. It feels, really, and there are companies that get it and are leaning in. There are others that maybe you're complacent. I'm wondering what you're seeing in Europe just in terms of everybody talks digital, every CEO wants to get it right. But there is complacency. Their financial services said Well, I'm doing pretty well, not on my watch. Others say, Hey, we want to be the disruptors and not get disrupted. What are you seeing in the region? In terms of that sentiment, >>I would say across the region, you know, there will always be verticals and industries that slightly more advanced than others. But I would say that the bulk of conversations that I'm engaged in independence of the industry or the country in which we're having that conversation in there is a acceptance off transfer. Digital transformation is here. It is affecting my business. I if I don't disrupt, I myself will be disrupted and we challenged Help me. So I You know, I'm not disputing the end state and the guidance and support soon drive the transition and risk mitigated manner, and they're looking for help in that there's actually pressure in the board room now around a what are we doing within within organizations within the enterprise service, right of the public sector, any type of style of company. There's that pressure point in the board room of Come on, we need to move it speed. >>Now the other thing about your model is technology plays a role and contribute. It's not the be all end. All that plays a role in each of those the business model of business operations developing and nurturing communities. Can you add more specifics? What role do you see technology in terms of advancing those three years? >>So I think, you know, if you look at it, technology is fundamental to all of those fears in regard. Teoh Theo innovation that differentiation technology could bring the key challenges. One being able to apply it in a manner where you can really see differentiation of value within the business. So and then the customer's organization. Otherwise, it's technology for the sake of technology. So we see very much a movement now to this conversation of talk about the use case, the use cases, the way by which that innovation could be used to deliver value to the organization on also different ways by which a company will work. Look at the collaboration Kate Capability that we announced earlier this week of helping to bring to life that agility. Look at the the APP D discussion of helping the link the layer of the application into the infrastructure of the network to get to root, cause identification quickly and to understand where you may have a problem before you actually arises and causes downtime many, many ways. >>I think the agility message has always been a technical conversation. Agile methodology, technology, softer development, No problem check. That's 10 years ago. But business agility is moving from a buzz word to reality. Exactly. That's what you're kind of getting. >>Their teams have. Teams operate, how they work and being able to be quick, efficient, stand up, stand down and operate in that way. >>You know, we were kind of thinking out loud on the Cube and just riffing with Fabio Gori on your team on Cisco's team about clarification with you, Gene Kim around kind of real time. What was interesting is we're like, Okay, it's been 13 years since the iPhone, and so 13 years of mobile in your territory in Europe, Middle East Africa mobility has been around before the iPhone, so more advanced data privacy much more advanced in your region. So you you you have a region that's pretty much I think, the tell signs for what's going on North American around the world. And so you think about that. You say Okay, how is value created? How the economics changing this is really the conversation about the business model is okay. If the value activities are shifting and being more agile and the economics are changing with SAS, if someone's not on this bandwagon is not an end state discussion, very. It's done Deal. >>Yeah, it's But I think also there were some other conversation which, which are very prevalent here, is in the region so around trust around privacy law, understanding compliance. If you look at data where data resides, portability of that data GDP our came from Europe has pushed out on those conversations will continue as we go over time. And if I also look at, you know, the dialogue that you saw, you know, within World Economic Forum around sustainability that is becoming a key discussion now within government here in Spain, you know, from a climate standpoint and many other areas >>as well. David, I've been riffing around this whole where the innovation is coming from. It's coming from your region, not so much the us US. We've got some great innovations. But look at Blockchain. Us is like, don't touch it pretty progressive outside United States. A little dangerous to, But that's where innovation is coming from, and this is really the key that we're focused on. I want to get your thoughts on. How do you see it going? Next level? The next level. Next. Gen Business model. What's your What's your vision? >>So I think there'll be lots of things if we look at things like it with the introduction. Introduction of artificial intelligence, Robotics capability five g of course, you know, on the horizon we have Mobile World Congress here in Barcelona a few weeks time. And if you talked about with the iPhone, the smartphone, of course, when four g was introduced, no one knew what the use case where that would be. It was the smartphone, which wasn't around at that time. So with five G and the capability there, that will bring again yet more change to the business model for different organizations and capability and what we can bring to market >>the way we think about AI privacy data ownership becomes more important. Some of the things you were talking about before. It's interesting what you're saying. John and Wendy, the GDP are set this standard and and you're seeing in the US they're stovepipes for that standard California is gonna do want every state is gonna have a difference, and that's going to slow things down. It's going to slow down progress. Do you see sort of an extension of GDP, our like framework of being adopted across the region, potentially accelerating some of these sticky issues and public policy issues that can actually move the market forward? >>I think I think that will because I think there'll be more and more if you look at this is terminology of data. Is the new oil What do you do with data? How do you actually get value from that data? Make intelligent business decisions around that? So, yeah, that's critical. But yet if you look for all of ours, we are extremely passionate about where's our data used again? Back to trust and privacy. You need compliance, you need regulation. And I think this is just the beginning off how we will see that >>evolving. You know, when you get your thoughts. David, I've been riffing for 10 years around the death of storage. Long live storage. But data needs to be stored somewhere. Networking is the same kind of conversation just doesn't go away. In fact, there's more pressure now to get the smartphone. That was 13 years ago, before that. Mobility, data and Video. Now super important driver. That's putting more pressure on you guys. And so hey, we did well, networking. So it's kind of like Moore's Law. More networking, more networking. So video and data are now big your thoughts on video and data video. >>But if you look out the Internet of the future, you know what? So if you look for all of us now, we are also demanding as individuals around capability and access of. That's an Internet of the future. The next phase. We want even more so they'll be more more requirement for speed availability, that reliability of service, the way by which we engage in we communicate. There's some fundamentals there, so continuing to grow, which is which is so, so exciting force. >>So you talk about digital transformation that's obviously in the mind of C level executives. I got to believe security is up. There is a topic one other. What's the conversation like in the corner office when you go visit your customers? >>So I think there's a There's a huge excitement around the opportunity, realizing the value of the of the opportunity on. You know, if you look at top of mind conversations around security around, making sure that you can make taint, maintain that fantastic customer experience because if you don't the customer go elsewhere, How do you do that? How do you enrich at all times and also looking at market? Jason sees, you know, as you go in a new tour at senior levels, within, within organizations independent of the industry in which they're in. They're a huge amount of commonalities that we see across those of consistent problems by which organizations are trying to solve. And actually, one of the big questions is what's the pace of change that I should operate us on? When is it too fast? And one is one of my too slow and trying to balance that is exciting but also a challenge for a company. >>So you feel like sentiment. There's still strong, even though we're 10 years into this, this bull market you get Brexit, China tensions with US US elections. But but generally you see sentiment still pretty strong demand. >>So I would say that the the the excitement around technology, the opportunity that is there around technology in its broader sense is greater than ever before. And I think it's on all of us to be able to help organizations to understand how they can consume and see value from us. But it's a fantastic times, >>gets economic indicators way. So >>I know you >>have to be careful, >>but really, the real I think I'm trying to get to is is the mindset of the CEO. The corner office right now is it is that we're gonna we're gonna grow short term by cutting or do we going to be aggressive and go after this incremental opportunity? And it's probably both. You see a lot of automation in cars >>both, and I think if you look fundamentally for organizations, it's it's the three things helped me to make money, how to save money, keep me out of trouble. So those are the pivots they all operate with on, you know, depending on where an organization is in its journey, whether they're start up there in the middle, the more mature and some of the different dynamics and the markets in which they operate in a well, there's all different variables, you know? So it's it's it's mixed. >>Wendy, thanks so much to spend the time to come on. The Cube really appreciate great keynote folks watching. If you haven't seen the keynote opening section, that's good. Second, the business model. I think it's really right on. I think that's gonna be a conversation will continue. So thanks for sharing that before we look. Before we leave, I want to just ask a question around, What? What's going on for you here in Barcelona? As the show winds down, you had all your activities. Take us in the day in the life of what you do. Customer meetings. What were some of those conversations? Take us inside inside. What? What goes on for you here? >>I tell you, it's been an amazing It's been amazing few days, So it's a combination of customer conversations around some of the themes We just talked about conversations with partners. There's investor companies that we invest in a Cisco that I've been spending some time with on also spending time with the teams as well. The definite zone, you know, is amazing. We have this afternoon the closing session where we got a fantastic, um, external guests who's coming in is going to be really exciting as well. And then, of course, the party tonight and will be announcing the next location, which I'm not going to reveal now. Later on today, >>we kind of figured it out because that's our job is to break news, but we're not gonna break it for you to have that. Hey, thank you so much for coming on. Really appreciate. When any market in Europe, Middle East Africa and Russia for Cisco she's got her hand on the pulse and the future is the business model. That's what's going on. Fundamentally radical change across the board in all areas. This is the Cube, bringing you all the action here in Barcelona. Thanks for watching. >>Yeah, yeah,

(techno music) >> Live from Barcelona, Spain it's theCUBE. Covering Cisco Live! Europe. Brought to you by Cisco and it's ecosystem partners. >> Hello everyone, welcome back to theCUBE's live coverage in Barcelona for Cisco Live! 2019. I'm John Furrier co-host of theCUBE with Dave Vellante. Our next guest is Wendy Mars. She is the president of Cisco EMEAR. Europe, Middle East, and Africa and Russia. Welcome to theCUBE. >> Thank you. >> Thanks for joining us. >> Great to be here. >> One of the themes this year certainly is Cloud. Data is starting to come together. The other backdrop is besides security and all the things going on with data, is the global landscape. So Cisco, obviously North America everyone knows what's going on over there at Cisco Live!. What's happening in Europe? Obviously GDPR has been hot in the past year. What's new, what's the scene like here? >> You know I think that certainly the scene is one of huge excitement. You know, from our customers across the whole region of Europe, Middle East, Africa, Russia. It's an incredibly diverse region. But you know if you look at the different countries, the different markets, one thing that absolutely is a constant theme that we hear is the desire and the appetite to gain the benefit from transformation. You know, in the digital transformation and what that value can be. And realizing that. If we look for ours, you know, within Cisco and the positioning around and realizing the secure, intelligent platform is absolutely resonating. Things like Multi-Cloud and realizing that. Reinventing the network. The security challenge in dealing with that. And how you address it with the multi-domain architecture approach. Our customers are really engaged in the conversation, want to learn more. Most importantly, want help with the how. Show me how to do it. >> You guys must be leading the conversation within Cisco. Obviously your team in Europe, Middle East, and Africa and Russia because the complexity around compliance and data has been front and center now for 24 months. >> Yes. >> Now hitting mainstream global landscape. >> Yup. >> This is really impacting the architecture. I mean, look at the, how intent based networking is developing. Policy based fill in the blank. To connecting to multiple clouds. >> Yup. >> So, kind of complex, a whole new architecture, re-imagining networking. How are you guys seeing the trends now? Is it still at the tipping point? Is it still early? What's your assessment of the role of data as it gets more complex, more compliant driven? >> I think that it certainly, if you look for organizations, the power of being able to understand and the importance of your data, where it resides. Being able to demonstrate that. Having the integrity and the quality of that data is extremely important as well. There's a heightened awareness in the market and for organizations. Global organizations who conduct business in EMEAR. You know, of course and we are one of those as well. A knowledge and understanding and appreciation of compliance and regulation. It's only going to become more intense, you know, as we go forward. For organizations to really have robust and rigorous processes around all of that. Technology can be an enabler in the process as well. >> What are the unique aspects, Wendy, in the region? You obviously have visibility on what goes on in North America. What's different in Europe? Especially in the context of Cloud, Multi-Cloud, obviously GDPR, although it's a framework now for everybody. >> Yup. >> Around the world. But what's unique? In the region. >> So I think the uniqueness is, you know, if you look from a Multi-Cloud standpoint for example where organizations are, have been I would say, depending on some of the countries and markets, a little bit more hesitant around a movement to Cloud. Now there is a movement but it's more one of, well what is appropriate for me and how do I ensure I can embrace Multi-Cloud in a way that makes sense for my business? So rather than a full move to public there's been a selected. Based on application and workload environments. Also understanding the security. Back to compliance. And also the regulation. Impacts of some of those movements as well. Of course that depends upon the vertical or the industry in which those organizations are operating. For those who are highly regulated like healthcare, the pharmaceutical sector there's a deep inspect that goes on there as well. I think there's a further requirement for due diligence around some of those topics as well. >> Well, you know, the Snowden backlash had some paranoia for sure with... Everybody said it's going to go to two or three clouds and that's clearly not been the case. >> Yup. >> You have, you know, many dozens and hundreds of service providers that are specialists, obviously, in the region. So, we heard today about, really, an end to end architecture. >> Mmm-hmm. >> Which is a bold and ambitious vision. You have a technical background as well. I wonder if you could just describe sort of how that's all going to to transpire. How do you take the customers on their journey? What are they asking you for help with? Where do you see it going? >> Yeah, so if you look at, you know, from David this morning. David Geckeler and what he talked about. Really for those different domains there are competencies, you know, a few things. There's the data center, there is the edge, there was the security world, the collaboration world. The reality of it is though, that as an enterprise or any organization indeed consumes those things. They want to be able to work across all of those areas. They want the innovation to work in a seamless manner. Because at the end of the day the problem to solve to is simplify for me. I need to automate, reduce complexity. I want to roll out and deploy policy. In a consistent and cohesive way. In order to make that happen you have to have these environments able to talk to each other. More importantly push that policy in a cohesive manner across these environments. For ours it's a journey. It's not something you can do overnight. You have to work within your engineering teams and your ecosystem in order to bring that to life. Do it in a way where the customer can consume it. >> I think you really nailed what we see in the trend as well. This cross domain component. With API's now, which are open, are pushing data around. >> Yup. >> You're moving data from point A to point B. Sounds like networking to me. Policy is important. >> Yup. >> But the configuration, the deployment which used to be hard is now being automated. So the question I have for you, we're here in the DevNet zone, I mean it's packed, people are learning about programming. What is the impact of all this to developers who are trying to build apps and your ecosystem? Because there's got to be an opportunity there. Some might go the way of the old guard and kind of fade away. Some new kinds of providers might rise up. >> Yeah, you know there's huge opportunity here and I think it's opportunity around the requirement for new skills, new competencies. Also around new capability to bring this to life. Because if you look from a development standpoint, if you look at how you realize value with organizations and where does the money flow between some of these environments is interesting. The ecosystem itself, for Cisco, what I believe makes this even more powerful is bringing to life for them and accelerating with the ecosystem. At the end of the day the customer will buy an ecosystem style environment. For us to be able to work with all of those parties as we have over many years. There will be new players, the ISV community, the developer community that we work with, that will be really powerful for us as we move. >> So you see the ecosystem growing significantly? Ecosystem growing? >> Absolutely, absolutely. >> What are some examples... >> I mean just look at here, look at all the organizations that are here. >> Well I think the development trends clearly intersecting with networking as it's more programmable. Right? >> Yup. >> That's the big takeaway for us. You can program the network, you have infrastructure as code. That's the DevOps promise. >> Yup. >> That's now here. The question we're looking at is, okay, what's going to be the impact to value creation? If I'm a customer, what does it mean to me? As we look at that I tend to think about the Cisco original business model. Enabling technology. How would you answer that question of what's being enabled today? What's the big ah-ha for customers? What are you guys enabling for your partners and your tech? >> Yeah, so I think a big part of it is we see now a lot of the conversation is around what is use case. It's not just a, I've got some cool stuff, show me the cool stuff that works, it's how do I apply that into my environment to derive value? And that value may be around efficiency. It may be around provisioning in a more rapid manner. Automating in a more realized manner. Lots of different instances where organizations are going to see the benefit associated with that but also it allows them to free up time of their people and their teams to move into newer areas as well. As they move their own business models. It's a massive transition that's happening in the industry overall. It's not just, we're not just changing for the sake of change, we're changing because the market is asking us to do that. >> So customers have to make bets on who their Multi-Cloud provider is going to be. >> Yup. >> Obviously Cisco is coming at that from a position of networking strength. Which is a good place to come from. There are other, there are alternatives. >> Sure. >> Cause it's a big market. >> Yup. >> And it's strategic. What gives you confidence that Cisco is the right solution? What are you telling your customers in that regard? >> If I look at the, what gives me confidence is the fact that we have an openness. If you look from an API standpoint, a developer's standpoint, we've always operated in a mode of an openness so that you have an environment where anyone can write to. That's, people want that, it's incredibly important. So not having a proprietary stance is very powerful. I think also being able to work with a ecosystem that's there, where you have a dependency on others and you meet in the channel on certain solutions and innovations as well. So you empower a greater community to start to drive that acceleration with you as well. If I have a look at the, we talk about reinventing the network. It's happening, it's happening now. You see us doing it and just how important the network is. More than ever before in this transition. Around a number of areas with security, with policy. We see it come to life now. >> Well the old saying the network is the computer. Well duh. (laughter) Cisco is the network. >> Yup. >> I got to ask you about Brexit. As somebody who's based in the UK. >> Yup. Thoughts on effects that that has. Obviously Cisco, a global company but your perspectives on Brexit. >> Yeah, so if I look for a, you know, as someone who lives in the UK, you know, clearly we hear about Brexit a lot. As you do in your country as well. I would say for as we are very, Cisco is a global company, we're very familiar with working with these types of instances and situations. The UK remains for us an incredibly important market and will continue to be. We'll continue to invest from a capabilities and a skills standpoint. I think just for us now, working with our teams there and making sure that there's, we minimize any impacts based on scenarios. To our customers and our partners. And think it through. >> Rules change, you'll adapt. >> Yeah. >> I got to ask you about R, the Russia piece. >> Uh-huh. >> Russia's GDP is about the size of Spain if I'm correct. Interesting that you carve that out as distinct opportunity. How's the business going there? Maybe some comments around Russia. >> Sure. I can't talk directly about business performances, we're in quiet period. I guess we call it out specifically because it is not part of Europe, Middle East or Africa. But is a very important part of our region of EMEAR. If I look forwards of, you know, we believe that there's significant opportunity for us. In that market we have a fantastic team that work closely where, there again with our customers and partners. We believe there's absolutely the opportunity there for us at Cisco in that market. >> Do you have a development team there as well or, or? >> We have capability there that works locally with all of our teams and, you know, engineering competence, sales teams, etc. as well. Yeah. >> Some good math teached there in Russia. >> Wendy, how are you guys organized in your territory? How do you guys maintain close to the customer in the countries? Is it a country strategy? How, just for the people who don't know your business? >> Yeah, it is a country strategy. We have about 123 countries within EMEAR. We have teams that live and operate in all of those countries. That stay very close to us from a regional perspective. So we're one team, you know, that really drives that scale. I have a fantastic opportunity to go and visit those teams. And spend a lot of time on the road. I enjoy it and they do too, you know. >> Is there anything that you could talk to your customers that are watching here or anyone interested. As you guys have transformed as a company, certainly if you look at what Cisco's done over the past few years. A complete transformation, building on your base. You've been through it, you've been agile and getting nimble. >> Yup. >> Being more use case driven, etc., etc. What have you learned? What's your learnings? What would you pay it forward in terms of advice? >> Yeah, if I look at it we're not through, we're still, you know, we're still on the journey. I think a big part of it is accepting and acknowledging a need for change is really important. A big part of this change is culture. If I look forwards within Cisco and the culture of our teams, our people. Having an attitude and a style of a desire, a curiosity. And a willingness for change is really, really important. As we talk about the transformation topic, you need both. Technology is incredibly important and powerful but you need a spirit and a culture in your people and your teams to want to drive that change with you. >> You need that culture DNA, it starts at the top. Well thank you for taking the time. >> A pleasure. >> We look forward to following your progress as we take our CUBE global the next couple years. Looking forward to keeping an eye on what you guys are doing. Thanks for joining us. >> Thank you. Great to see you. >> With theCUBE here live in Barcelona for Cisco Live! 2019. We'll be back with more after this short break. (techno music) (silence)

>> Live from Barcelona, Spain. It's the cue covering Sisqo, Live Europe, Brought to you by Cisco and its ecosystem partners. >> All right, welcome back to the Cubes. Live coverage in Barcelona for Sisqo Live twenty nineteen. John for Rico's Cube with David Lantz. Our next guest is Wendy Marches, the President of Cisco, E. M. R. Europe, Middle East in Africa and Russia. Welcome to the Cube. >> Thank you. >> Thanks for joining us. >> Great to be here. >> So one of the things themes this year certainly is cloud data center coming together. But the other backdrop is besides security and all of the things going on with data is the global landscape. So Cisco, see, North American Windows were going on their school live? What's happening in Europe? Actually, GPR has been hot in the past year. What's new? What's the scene like here? >> You know, I think that certainly the scene is one of huge excitement, you know, from our customers across the whole region of Europe, Middle East, Africa, Russia. It's an incredibly diverse region. But you know, if you look at the different countries, the different markets one thing that absolutely is a constant theme that we hear is the desire and the appetite to gain the benefit from transformation. You know, in the digital transformation and what that value can be and realizing that. And if we look for ours, you know within within Cisco and the positioning around realizing the secure intelligent platform is absolutely resonating, you know, so things like multi cloud and realizing that reinventing the network, the security challenge and dealing with that, how you address it with the multi domain architecture approach so our customers are really engaged in the conversation, want to learn more, but most importantly, want help with how. Show me how to do it. >> You guys must be leading the conversation within Cisco as your team in Europe, Miller's nephew in Russia. Because the complexity around compliance and data has been front and center Now for twenty four months now hitting mainstream global landscape, this >> is really >> impacting the architecture. We look at the how intent based NETWORKINGS developing policy based fill in the blank two. Connecting to multiple clouds so kind of complex. A whole new architecture. Reimagining networking. How are you guys seeing them? Trends now is it's still at the tipping point is it's still early. What's your? What's your assessment of the role of data as it gets more complex, more compliant, driven? >> So I think that it's certainly if you look for organizations, the power of being able to understand the importance of your data where it resides, being able to demonstrate that having the integrity and the quality of that data is extremely important as well. So there's a heightened awareness in the market for organizations, global organizations who conduct business in a mere, you know, of course, and we are one of those as well. So a knowledge and understanding and appreciation ofthe compliance regulation. It's only going to become Mohr intense, you know, as we go for. So for organizations to really have robust and rigorous processes around, all of that on technology could be an enabler in the process as well. What >> are the >> unique aspects? Wendy Inn in the region, you obviously have visibility. And on what goes on in North America, what's different in Europe, especially in the context of cloud multi cloud? Obviously GPR, although it's a framework now for for for everybody get on the world. But what's unique in the region? >> So I think the uniqueness is, you know, if you look from a multi cloud standpoint, for example, where you know organizations are, have been, I would say depending on some of the countries and markets a little bit more hesitant around a movement to cloud. And now there is a movement. But it's more one of, well, what is appropriate for me. And how do I ensure I can embrace multi cloud in a way that makes sense for my business. So, rather than a full move to public, there has been a selected, you know, based on application of workload environments and also understanding the security, back to compliance. And also the regulation impacts have some of those movements as well. And of course, that depends upon the vertical or the industry in which those organizations are operating. So for those who are highly regulated, like health care, you're the pharmaceutical sector. There's a deep inspect that goes on there as well, so I think there's a further requirement for due diligence around some of those topics as well. >> Well, in the you know, the Snowden backlash had some paranoia for sure, with everybody saw going to go to two or three clouds. And that's clearly not been the case. Yeah, you have no many dozens and hundreds of service providers that air that air specialists obviously in the region. So we heard today about a million end to end architecture, which is a a bold and ambitious vision. You have a technical background as well. I wonder if you could just describe sort of how that's all going toe transpire. How do you take the customers on their journey? What are they asking you for help with? And where do you see it going? >> Yeah. So if you look at, you know from David this morning, David, get clear on what he talks about. So really, you know, for those different domains, there are competencies, you know, if you think so. There's the data center. There is the edge. There was security world, the collaboration world. So the reality of it is, though, that as a cousin, enterprise or any organization indeed consumes those things. They want to be able to work across all of those areas. And they want the innovation to work in a seamless manner. Is that the end of the day? The problem to solve. To simplify for me, Anita automate reduced complexity. I wanna roll and deploy policy and a consistent in cohesive way. So in order to make that happen, you have to have these environments able to talk to each other, but more importantly, pushed that policy in a cohesive manor across these environments. So for us, it's a journey, eh? So it's not something you could do over Nice. You have to work within your engineering teams and your ecosystem in order to bring that to life and do it in a way where the custom consider could consume it. >> I think you really nailed that. We see in the trend as well. This cross domain component with AP Eyes now but you're open are pushing data around you, moving data from point A to Point B. Sounds like networking. To me, policy is important, but the configuration the deployment, which used to be hard, is now being automated. So the question I have for you here in the definite zone means packed People are learning about programming. >> What is the >> impact of all this to developers were trying to build APS and your ecosystem. There's gotta be an opportunity there some Mike go the way of the old guard fade away and some new kinds of providers might rise up. >> Yeah, you know, this huge opportunity here, and I think it's opportunity around the requirement for new skills, new competencies, but also around you capability to bring this the life. Because if you look from a development standpoint, if you look at how you realize value with organizations and where does the money flow between some of these environments is interesting and the ecosystem itself. You know, Francisco, what What I believe makes us even more powerful is bringing to life on them and accelerating with the ecosystem, because at the end of the day, the customer will buy an ecosystem style environment. So for us to be able to work with all of those parties as we have over many years and there will be new players, the I s. P community, the developer community that we work with that will be really powerful >> forces with system growing significantly, ecosystem grow >> Absolutely, absolutely awesome. Example. Just lookit here because of the organizations that are here. >> I think the development trends clearly intersecting with networking as more programmable right? >> Yeah. >> That's the big takeaway for us. You can program the network. You have infrastructure as code. That's the devil. Promise that now here. Question we're looking at is okay. What's it going to be? The impact of value creation. So from a customer, what does it mean to me? So so, as we look at that, I sent the thing about the Cisco original business model enabling technology. How would you answer that Question of what's being enabled today. What's the big half a customer's? What are you guys enabling for your partners in your >> S o? I think a big part of it is we see now a lot of the conversation there's around What is is the use case. So it's not just a I've got some cool stuff. Show me the cost ofthe that work is how do I apply that into my environment to derive value and that value, maybe around efficiency and maybe a brand provisioning in a more rapid manner, automating in a more realized manner. Lots of different instances where organizations they don't see the benefit associated with that, but also it allows them to free up time of their people. And their teams to move into new areas as well as they move their own business models. Because, you know, it's a massive transition that's happening in the industry. Overall, it's not just were not just changing for the sake of change were changing because the market is asking us to do that >> well. And so customers have to make bets on who they're multi cloud providers, maybe, and obviously Cisco's coming out that from a position of networking strength, which is a good place to come from. But there are other there alternatives because the Bigg market headed strategic. What gives you confidence that Cisco's the right solution? What are you telling your customers in that regard? >> So you know, if I look at the, what gives me confidence is the fact that we have an openness. You know, if you look from A from a P I standpoint of developer standpoint, we've always operated in a mode of an openness so that you have an environment where anyone could write to that's people want that it's incredibly importance or not. Having a proprietary stance is very powerful, but I think also being able to work with a ecosystem that's there where you are a dependency on others, and you meet with the meat in the channel on certain solutions and innovations as well. So you empower a greater community to start to drive that acceleration with you? A swell. You know, I will. Look at the you know, we talk about reinventing the network. It's happening. It's happening now, you see, is doing it. And just how important the network is more than ever before in this transition, you know, ran a number of areas with security with policy, and it's way see it come to life now. >> Well, the old saying the network is the computer will do you no. Cisco's the network. Yeah. I gotta ask you about Brexit is someone who's based in the UK thoughts on effects that that has. I mean, obviously, sir Francisco Global Company. But your perspectives on Brexit >> s So if I look for, you know, as someone who lives in the U. K. You know, clearly we hear about brexit a loss, you know, you do in your country as well. And I would say four words. We over. You know what Cisco is? A global company were very fair. We're very familiar with working with these types of instances and situations. The UK remains for us is an incredibly important market and will continue to be on We'll, you know, we'll continue to invest from a capabilities and a skill standpoint, and I think just force now, you know, working with our teams there. I'm making sure that there's we minimize any impacts based on scenarios, you know, to our customers and apartments. The rules get through. >> Rules change. Adept. I >> could ask >> you about our The Russia piece rushes of GDP is about the size of Spain from correct, interesting that you carve that out of a distinct opportunity. How's the business going there and maybe some comments around >> you're so I can't talk directly about business performances were in quiet period. But I guess we call it out specifically because it is not part of Europe, Middle Eastern Africa, but is a very important part of our region of Vermeer. And if I look for cores of, you know, we believe that there is significant opportunity for us in that market. We have a fantastic team that were closely where there again with our customers and partners. And, you know, we believe there's, you know, absolutely opportunity for Sisko in that market >> development team there as well. Our way >> have we have capability there that works locally with all of our all of our teams and, you know, engineering Competent sale steams etcetera as well. Yeah. >> Good. Good math. >> Wendy, how are you guys organized in your territory? How do you guys maintain close to the customer in the countries? Is the country strategy had just people don't. >> It is a country strategy. So we have, you know, about one hundred twenty three countries within a mere on, we have teams that live and operate in all of those countries. That's Avery close to us from a regional perspective. So want team, you know, that really drives that scale. I'm a fantastic opportunity to go and visit those teams. You know, I spent a lot of time on the road on DH. You know, I enjoy Ascend and they do to, you know, >> is there anything you could talk to your customers that are watching here? Anyone interested, as you guys have transformed as a company, Certainly looking what Cisco is done over the past few years a complete transformation building on your base You've been through You've been agile getting nimble being Mohr use case driven Central, Central. What have you learned? What's your learnings? And what would you pay it forward in terms of advice? >> Yeah, So, you know, if I if I look at it, we're not through, we're still you know we're still on the journey and I think a big part of it is accepting and acknowledging a need for change is really important. But a big part of this change is culture. You're a friend of Ford's within Sisko, and the culture of our teams are people on having an attitude in a style of a desire, a curiosity, Onda willingness for change is really, really important. And as we talk about the transformation topic, you need both. You know, technology's incredibly important and powerful, but you need a spirit and a culture and your people in your teams you want to drive that change with you >> in their culture starts in trouble. Thank you for taking the time. >> Thank you >> for the following your progress as we take our cue. Global next couple of years. Looking forward to keeping an eye on. You guys are doing. Thanks for joining. >> Thank you. Thank you. See you >> here. Live in Barcelona. Francisco live twenty nineteen. We're back with more after this short break.

(light music) >> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to Spain everyone. Lisa Martin here with theCUBE Dave Vellante, my co-host for the next four days. We're live in Barcelona, covering MWC23. This is only day one, but I'll tell you the theme of this conference this year is velocity. And I don't know about you Dave, but this day is flying by already. This is ecosystem day. We're going to have a great discussion on the ecosystem next. >> Well we're seeing the disaggregation of the hardened telco stack, and that necessitates an ecosystem open- we're going to talk about Open RAN, we've been talking about even leading up to the show. It's a critical technology enabler and it's compulsory to have an ecosystem to support that. >> Absolutely compulsory. We've got two guests here joining us, Gautam Bhagra, Vice President partnerships at Dell, and Scott Walker, Vice President of global Telco ecosystem at Wind River. Guys, welcome to the program. >> Nice to be here. >> Thanks For having us. >> Thanks for having us. >> So you've got some news, this is day one of the conference, there's some news, Gautam, and let's start with you, unpack it. >> Yeah, well there's a lot of news, as you know, on Dell World. One of the things we are very excited to announce today is the launch of the Open Telecom Ecosystems Community. I think Dave, as you mentioned, getting into an Open RAN world is a challenge. And we know some of the challenges that our customers face. To help solve for those challenges, Dell wants to work with like-minded partners and customers to build innovative solutions, and join go-to-market. So we are launching that today. Wind River is one of our flagship partners for that, and I'm excited to be here to talk about that as well. >> Can you guys talk a little bit about the partnership, maybe a little bit about Wind River so the audience gets that context? >> Sure, absolutely, and the theme of the show, Velocity, is what this partnership is all about. We create velocity for operators if they want to adopt Open RAN, right? We simplify it. Wind River as a company has been around for 40 years. We were part of Intel at one point, and now we're independent, owned by a company called Aptiv. And with that we get another round of investment to help continue our acceleration into this market. So, the Dell partnership is about, like I said, velocity, accelerating the adoption. When we talk to operators, they have told us there are many roadblocks that they face, right? Like systems integration, operating at scale. 'Cause when you buy a traditional radio access network solution from a single supplier, it's very easy. It's works, it's been tested. When you break these components apart and disaggregate 'em, as we talked about David, it creates integration points and support issues, right? And what Dell and Wind River have done together is created a cloud infrastructure solution that could host a variety of RAN workloads, and essentially create a two layer cake. What we're, overall, what we're trying to do is create a traditional RAN experience, with the innovation agility and flexibility of Open RAN. And that's really what this partnership does. >> So these work, this workload innovation is interesting to me because you've got now developers, you know, the, you know, what's the telco developer look like, you know, is to be defined, right? I mean it's like this white sheet of paper that can create all this innovation. And to do that, you've got to have, as I said earlier, an ecosystem. But you've got now, I'm interested in your Open RAN agenda and how you see that sort of maturity model taking place. 'Cause today, you got disruptors that are going to lean right in say "Hey, yeah, that's great." The traditional carriers, they have to have a, you know, they have to migrate, they have to have a hybrid world. We know that takes time. So what's that look like in the marketplace today? >> Yeah, so I mean, I can start, right? So from a Dell's perspective, what we see in the market is yes, there is a drive towards, everyone understands the benefits of being open, right? There's the agility piece, the innovation piece. That's a no-brainer. The question is how do we get there? And I think that's where partnerships become critical to get there, right? So we've been working with partners like Wind River to build solutions that make it easier for customers to start adopting some of the foundational elements of an open network. The, one of the purposes in the agenda of building this community is to bring like-minded developers, like you said like we want those guys to come and work with the customers to create new solutions, and come up with something creative, which no one's even thought about, that accelerates your option even quicker, right? So that's exactly what we want to do as well. And that's one of the reasons why we launched the community. >> Yeah, and what we find with a lot of carriers, they are used to buying, like I said, traditional RAN solutions which are provided from a single provider like Erickson or Nokia and others, right? And we break this apart, and you cloudify that network infrastructure, there's usually a skills gap we see at the operator level, right? And so from a developer standpoint, they struggle with having the expertise in order to execute on that. Wind River helps them, working with companies like Dell, simplify that bottom portion of the stack, the infrastructure stack. So, and we lifecycle manage it, we test- we're continually testing it, and integrating it, so that the operator doesn't have to do that. In addition to that, wind River also has a history and legacy of working with different RAN vendors, both disruptors like Mavenir and Parallel Wireless, as well as traditional RAN providers like Samsung, Erickson, and others soon to be announced. So what we're doing on the northbound side is making it easy by integrating that, and on the southbound side with Dell, so that again, instead of four or five solutions that you need to put together, it's simply two. >> And you think about today how we- how you consume telco services are like there's these fixed blocks of services that you can buy, that has to change. It's more like the, the app stores. It's got to be an open marketplace, and that's where the innovation's going to come in, you know, from the developers, you know, top down maybe. I don't know, how do you see that maturity model evolving? People want to know how long it's going to take. So many questions, when will Open RAN be as reliable. Does it even have to be? You know, so many interesting dynamics going on. >> Yeah, and I think that's something we at Dell are also trying to find out, right? So we have been doing a lot of good work here to help our customers move in that direction. The work with Dish is an example of that. But I think we do understand the challenges as well in terms of getting, adopting the technologies, and adopting the innovation that's being driven by Open. So one of the agendas that we have as a company this year is to work with the community to drive this a lot further, right? We want to have customers adopt the technology more broadly with the tier one, tier two telcos globally. And our sales organizations are going to be working together with Wind Rivers to figure out who's the right set of customers to have these conversations with, so we can drop, drive, start driving this agenda a lot quicker than what we've seen historically. >> And where are you having those customer conversations? Is that at the operator level, is it higher, is it both? >> Well, all operators are deploying 5G in preparation for 6G, right? And we're all looking for those killer use cases which will drive top line revenue and not just make it a TCO discussion. And that starts at a very basic level today by doing things like integrating with Juniper, for their cloud router. So instead of at the far edge cell site, having a separate device that's doing the routing function, right? We take that and we cloudify that application, run it on the same server that's hosting the RAN applications, so you eliminate a device and reduce TCO. Now with Aptiv, which is primarily known as an automotive company, we're having lots of conversations, including with Dell and Intel and others about vehicle to vehicle communication, vehicle to anything communication. And although that's a little bit futuristic, there are shorter term use cases that, like, vehicle to vehicle accident avoidance, which are going to be much nearer term than autonomous driving, for example, which will help drive traffic and new revenue streams for operators. >> So, oh, that's, wow. So many other things (Scott laughs) that's just opened up there too. But I want to come back to, sort of, the Open RAN adoption. And I think you're right, there's a lot of questions that that still have to be determined. But my question is this, based on your knowledge so far does it have to be as hardened and reliable, obviously has to be low latency as existing networks, or can flexibility, like the cloud when it first came out, wasn't better than enterprise IT, it was just more flexible and faster, and you could rent it. And, is there a similar dynamic here where it doesn't have to replicate the hardened stack, it can bring in new benefits that drive adoption, what are your thoughts on that? >> Well there's a couple of things on that, because Wind River, as you know, where our legacy and history is in embedded devices like F-15 fighter jets, right? Or the Mars Rover or the James Web telescope, all run Wind River software. So, we know about can't fail ultra reliable systems, and operators are not letting us off the hook whatsoever. It has to be as hardened and locked down, as secure as a traditional RAN environment. Otherwise they will (indistinct). >> That's table stakes. >> That's table stakes that gets us there. And when River, with our legacy and history, and having operator experience running live commercial networks with a disaggregated stack in the tens of thousands of nodes, understand what this is like because they're running live commercial traffic with live customers. So we can't fail, right? And with that, they want their cake and eat it too, right? Which is, I want ultra reliable, I want what I have today, but I want the agility and flexibility to onboard third party apps. Like for example, this JCNR, this Juniper Cloud-Native Router. You cannot do something as simple as that on a traditional RAN Appliance. In an open ecosystem you can take that workload and onboard it because it is an open ecosystem, and that's really one of the true benefits. >> So they want the mainframe, but they want (Scott laughs) the flexibility of the developer cloud, right? >> That's right. >> They want their, have their cake eat it too and not gain weight. (group laughs) >> Yeah I mean David, I come from the public cloud world. >> We all don't want to do that. >> I used to work with a public cloud company, and nine years ago, public cloud was in the same stage, where you would go to a bank, and they would be like, we don't trust the cloud. It's not secure, it's not safe. It was the digital natives that adopted it, and that that drove the industry forward, right? And that's where the enterprises that realized that they're losing business because of all these innovative new companies that came out. That's what I saw over the last nine years in the cloud space. I think in the telco space also, something similar might happen, right? So a lot of this, I mean a lot of the new age telcos are understanding the value, are looking to innovate are adopting the open technologies, but there's still some inertia and hesitancy, for the reasons as Scott mentioned, to go there so quickly. So we just have to work through and balance between both sides. >> Yeah, well with that said, if there's still some inertia, but there's a theme of velocity, how do you help organizations balance that so they trust evolving? >> Yeah, and I think this is where our solution, like infrastructure block, is a foundational pillar to make that happen, right? So if we can take away the concerns that the organizations have in terms of security, reliability from the fundamental elements that build their infrastructure, by working with partners like Wind River, but Dell takes the ownership end-to-end to make sure that service works and we have those telco grade SLAs, then the telcos can start focusing on what's next. The applications and the customer services on the top. >> Customer service customer experience. >> You know, that's an interesting point Gautam brings up, too, because support is an issue too. We all talk about when you break these things apart, it creates integration points that you need to manage, right? But there's also, so the support aspect of it. So imagine if you will, you had one vendor, you have an outage, you call that one vendor, one necktie to choke, right, for accountability for the network. Now you have four or five vendors that you have to work. You get a lot of finger pointing. So at least at the infrastructure layer, right? Dell takes first call support for both the hardware infrastructure and the Wind River cloud infrastructure for both. And we are training and spinning them up to support, but we're always behind them of course as well. >> Can you give us a favorite customer example of- that really articulates the value of the partnership and the technologies that it's delivering to customers? >> Well, Infra Block- >> (indistinct) >> Is quite new, and we do have our first customer which is LG U plus, which was announced yesterday. Out of Korea, small customer, but a very important one. Okay, and I think they saw the value of the integrated system. They don't have the (indistinct) expertise and they're leveraging Dell and Wind River in order to make that happen. But I always also say historically before this new offering was Vodafone, right? Vodafone is a leader in Europe in terms of Open RAN, been very- Yago and Paco have been very vocal about what they're doing in Open RAN, and Dell and Wind River have been there with them every step of the way. And that's what I would say, kind of, led up to where we are today. We learned from engagements like Vodafone and I think KDDI as well. And it got us where we are today and understanding what the operators need and what the impediments are. And this directly addresses that. >> Those are two very different examples. You were talking about TCO before. I mean, so the earlier example is, that's an example to me of a disruptor. They'll take some chances, you know, maybe not as focused on TCO, of course they're concerned about it. Vodafone I would think very concerned about TCO. But I'm inferring from your comments that you're trying to get the industry, you're trying to check the TCO box, get there. And then move on to higher levels of value monetization. The TCO is going to come down to how many humans it takes to run the network, is it not, is that- >> Well a lot of, okay- >> Or is it devices- >> So the big one now, particularly with Vodafone, is energy cost, right? >> Of course, greening the network. >> Two-thirds of the energy consumption in RAN is the the Radio Access Network. Okay, the OPEX, right? So any reductions, even if they're 5% or 10%, can save tens or hundreds of millions of dollars. So we do things creatively with Dell to understand if there's a lot of traffic at the cell site and if it's not, we will change the C state or P state of the server, which basically spins it down, so it's not consuming power. But that's just at the infrastructure layer. Where this gets really powerful is working with the RAN vendors like Samsung and Ericson and others, and taking data from the traffic information there, applying algorithms to that in AI to shut it down and spin it back up as needed. 'Cause the idea is you don't want that thing powered up if there's no traffic on it. >> Well there's a sustainability, ESG, benefit to that, right? >> Yes. >> And, and it's very compute intensive. >> A hundred percent. >> Which is great for Dell. But at the same time, if you're not able to manage that power consumption, the whole thing fails. I mean it's, because there's going to be so much data, and such a intense requirement. So this is a huge issue. Okay, so Scott, you're saying that in the TCO equation, a big chunk is energy consumption? >> On the OPEX piece. Now there's also the CapEx, right? And Open RAN solutions are now, what we've heard from our customers today, are they're roughly at parity. 'Cause you can do things like repurpose servers after the useful life for a lower demand application which helps the TCO, right? Then you have situations like Juniper, where you can take, now software that runs on the same device, eliminating at a whole other device at the cell site. So we're not just taking a server and software point of view, we're taking a whole cell site point of view as it relates to both CapEx and OPEX. >> And then once that infrastructure it really gets adopted, that's when the innovation occurs. The ecosystem comes in. Developers now start to think of new applications that we haven't thought of yet. >> Gautam: Exactly. >> And that's where, that's going to force the traditional carriers to respond. They're responding, but they're doing so very carefully right now, it's understandable why. >> Yeah, and I think you're already seeing some news in the, I mean Nokia's announcement yesterday with the rebranding, et cetera. That's all positive momentum in my opinion, right? >> What'd you think of the logo? >> I love the logo. >> I liked it too. (group laughs) >> It was beautiful. >> I thought it was good. You had the connectivity down below, You need pipes, right? >> Exactly. >> But you had this sort of cool letters, and then the the pink horizon or pinkish, it was like (Scott laughs) endless opportunity. It was good, I thought it was well thought out. >> Exactly. >> Well, you pick up on an interesting point there, and what we're seeing, like advanced carriers like Dish, who has one of the true Open RAN networks, publishing APIs for programmers to build in their 5G network as part of the application. But we're also seeing the network equipment providers also enable carriers do that, 'cause carriers historically have not been advanced in that way. So there is a real recognition that in order for these networks to monetize new use cases, they need to be programmable, and they need to publish standard APIs, so you can access the 5G network capabilities through software. >> Yeah, and the problem from the carriers, there's not enough APIs that the carriers have produced yet. So that's where the ecosystem comes in, is going to >> A hundred percent >> I think there's eight APIs that are published out of the traditional carriers, which is, I mean there's got to be 8,000 for a marketplace. So that's where the open ecosystem really has the advantage. >> That's right. >> That's right. >> That's right. >> Yeah. >> So it all makes sense on paper, now you just, you got a lot of work to do. >> We got to deliver. Yeah, we launched it today. We got to get some like-minded partners and customers to come together. You'll start seeing results coming out of this hopefully soon, and we'll talk more about it over time. >> Dave: Great Awesome, thanks for sharing with us. >> Excellent. Guys, thank you for sharing, stopping by, sharing what's going on with Dell and Wind River, and why the opportunity's in it for customers and the technological evolution. We appreciate it, you'll have to come back, give us an update. >> Our pleasure, thanks for having us. (Group talks over each other) >> All right, thanks guys >> Appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, Live from MWC23 in Barcelona. theCUBE is the leader in live tech coverage. (upbeat music)

(gentle music) >> Hello, everyone. Welcome to this Cube Conversation. I'm John Furrier, host of theCUBE here, in our Palo Alto Studios. We're featuring OctoML. I'm with the CEO, Luis Ceze. Chief Executive Officer, Co-founder of OctoML. I'm John Furrier of theCUBE. Thanks for joining us today. Luis, great to see you. Last time we spoke was at "re:MARS" Amazon's event. Kind of a joint event between (indistinct) and Amazon, kind of put a lot together. Great to see you. >> Great to see you again, John. I really have good memories of that interview. You know, that was definitely a great time. Great to chat with you again. >> The world of ML and AI, machine learning and AI is really hot. Everyone's talking about it. It's really great to see that advance. So I'm looking forward to this conversation but before we get started, introduce who you are in OctoML. >> Sure. I'm Luis Ceze, Co-founder and CEO at OctoML. I'm also professor of Computer Science at University of Washington. You know, OctoML grew out of our efforts on the Apache CVM project, which is a compiler in runtime system that enables folks to run machine learning models in a broad set of harder in the Edge and in the Cloud very efficiently. You know, we grew that project and grew that community, definitely saw there was something to pain point there. And then we built OctoML, OctoML is about three and a half years old now. And the mission, the company is to enable customers to deploy models very efficiently in the Cloud. And make them, you know, run. Do it quickly, run fast, and run at a low cost, which is something that's especially timely right now. >> I like to point out also for the folks 'casue they should know that you're also a professor in the Computer Science department at University of Washington. A great program there. This is a really an inflection point with AI machine learning. The computer science industry has been waiting for decades to advance AI with all this new cloud computing, all the hardware and silicon advancements, GPUs. This is the perfect storm. And you know, this the computer science now we we're seeing an acceleration. Can you share your view, and you're obviously a professor in that department but also, an entrepreneur. This is a great time for computer science. Explain why. >> Absolutely, yeah, no. Just like the confluence of you know, advances in what, you know, computers can do as devices to computer information. Plus, you know, advances in AI that enable applications that you know, we thought it was highly futuristic and now it's just right there today. You know, AI that can generate photo realistic images from descriptions, you know, can write text that's pretty good. Can help augment, you know, human creativity in a really meaningful way. So you see the confluence of capabilities and the creativity of humankind into new applications is just extremely exciting, both from a researcher point of view as well as an entrepreneur point of view, right. >> What should people know about these large language models we're seeing with ChatGPT and how Google has got a lot of work going on that air. There's been a lot of work recently. What's different now about these models, and why are they so popular and effective now? What's the difference between now, and say five years ago, that makes it more- >> Oh, yeah. It's a huge inflection on their capabilities, I always say like emergent behavior, right? So as these models got more complex and our ability to train and deploy them, you know, got to this point... You know, they really crossed a threshold into doing things that are truly surprising, right? In terms of generating, you know, exhalation for things generating tax, summarizing tax, expending tax. And you know, exhibiting what to some may look like reasoning. They're not quite reasoning fundamentally. They're generating tax that looks like they're reasoning, but they do it so well, that it feels like was done by a human, right. So I would say that the biggest changes that, you know, now, they can actually do things that are extremely useful for business in people's lives today. And that wasn't the case five years ago. So that's in the model capabilities and that is being paired with huge advances in computing that enabled this to be... Enables this to be, you know, actually see line of sites to be deployed at scale, right. And that's where we come in, by the way, but yeah. >> Yeah, I want to get into that. And also, you know, the fusion of data integrating data sets at scales. Another one we're seeing a lot of happening now. It's not just some, you know, siloed, pre-built data modeling. It's a lot of agility and a lot of new integration capabilities of data. How is that impacting the dynamics? >> Yeah, absolutely. So I'll say that the ability to either take the data that has that exists in training a model to do something useful with it, and more interestingly I would say, using baseline foundational models and with a little bit of data, turn them into something that can do a specialized task really, really well. Created this really fast proliferation of really impactful applications, right? >> If every company now is looking at this trend and I'm seeing a lot... And I think every company will rebuild their business with machine learning. If they're not already doing it. And the folks that aren't will probably be dinosaurs will be out of business. This is a real business transformation moment where machine learning and AI, as it goes mainstream. I think it's just the beginning. This is where you guys come in, and you guys are poised for handling this frenzy to change business with machine learning models. How do you guys help customers as they look at this, you know, transition to get, you know, concept to production with machine learning? >> Great. Great questions, yeah, so I would say that it's fair to say there's a bunch of models out there that can do useful things right off the box, right? So and also, the ability to create models improved quite a bit. So the challenge now shifted to customers, you know. Everyone is looking to incorporating AI into their applications. So what we do for them is to, first of all, how do you do that quickly, without needing highly specialized, difficult to find engineering? And very importantly, how do you do that at cost that's accessible, right? So all of these fantastic models that we just talked about, they use an amount of computing that's just astronomical compared to anything else we've done in the past. It means the costs that come with it, are also very, very high. So it's important to enable customers to, you know, incorporate AI into their applications, to their use cases in a way that they can do, with the people that they have, and the costs that they can afford, such that they can have, you know, the maximum impacting possibly have. And finally, you know, helping them deal with hardware availability, as you know, even though we made a lot of progress in making computing cheaper and cheaper. Even to this day, you know, you can never get enough. And getting an allocation, getting the right hardware to run these incredibly hungry models is hard. And we help customers deal with, you know, harder availability as well. >> Yeah, for the folks watching as a... If you search YouTube, there's an interview we did last year at "re:MARS," I mentioned that earlier, just a great interview. You talked about this hardware independence, this traction. I want to get into that, because if you look at all the foundation models that are out there right now, that are getting traction, you're seeing two trends. You're seeing proprietary and open source. And obviously, open source always wins in my opinion, but, you know, there's this iPhone moment and android moment that one of your investors John Torrey from Madrona, talked about was is iPhone versus Android moment, you know, one's proprietary hardware and they're very specialized high performance and then open source. This is an important distinction and you guys are hardware independent. What's the... Explain what all this means. >> Yeah. Great set of questions. First of all, yeah. So, you know, OpenAI, and of course, they create ChatGPT and they offer an API to run these models that does amazing things. But customers have to be able to go and send their data over to OpenAI, right? So, and run the model there and get the outputs. Now, there's open source models that can do amazing things as well, right? So they typically open source models, so they don't lag behind, you know, these proprietary closed models by more than say, you know, six months or so, let's say. And it means that enabling customers to take the models that they want and deploy under their control is something that's very valuable, because one, you don't have to expose your data to externally. Two, you can customize the model even more to the things that you wanted to do. And then three, you can run on an infrastructure that can be much more cost effective than having to, you know, pay somebody else's, you know, cost and markup, right? So, and where we help them is essentially help customers, enable customers to take machine learning models, say an open source model, and automate the process of putting them into production, optimize them to run with the right performance, and more importantly, give them the independence to run where they need to run, where they can run best, right? >> Yeah, and also, you know, I point out all the time that, you know, there's never any stopping the innovation of hardware silicon. You're seeing cloud computing more coming in there. So, you know, being hardware independent has some advantages. And if you look at OpenAI, for instance, you mentioned ChatGPT, I think this is interesting because I think everyone is scratching their head, going, "Okay, I need to move to this new generation." What's your pro tip and advice for folks who want to move to, or businesses that want to say move to machine learning? How do they get started? What are some of the considerations they need to think about to deploy these models into production? >> Yeah, great though. Great set of questions. First of all, I mean, I'm sure they're very aware of the kind of things that you want to do with AI, right? So you could be interacting with customers, you know, automating, interacting with customers. It could be, you know, finding issues in production lines. It could be, you know... Generating, you know, making it easier to produce content and so on. Like, you know, customers, users would have an idea what they want to do. You know, from that it can actually determine, what kind of machine learning models would solve the problem that would, you know, fits that use case. But then, that's when the hard thing begins, right? So when you find a model, identify the model that can do the thing that you wanted to do, you need to turn that into a thing that you can deploy. So how do you go from machine learning model that does a thing that you need to do, to a container with the right executor, the artifact they can actually go and deploy, right? So we've seen customers doing that on their own, right? So, and it's got a bit of work, and that's why we are excited about the automation that we can offer and then turn that into a turnkey problem, right? So a turnkey process. >> Luis, talk about the use cases. If I don't mind going and double down on the previous answer. You got existing services, and then there's new AI applications, AI for applications. What are the use cases with existing stuff, and the new applications that are being built? >> Yeah, I mean, existing itself is, for example, how do you do very smart search and auto completion, you know, when you are editing documents, for example. Very, very smart search of documents, summarization of tax, expanding bullets into pros in a way that, you know, don't have to spend as much human time. Just some of the existing applications, right? So some of the new ones are like truly AI native ways of producing content. Like there's a company that, you know, we share investors and love what they're doing called runwayyML, for example. It's sort of like an AI first way of editing and creating visual content, right? So you could say you have a video, you could say make this video look like, it's night as opposed to dark, or remove that dog in the corner. You can do that in a way that you couldn't do otherwise. So there's like definitely AI native use cases. And yet not only in life sciences, you know, there's quite a bit of advances on AI-based, you know, therapies and diagnostics processes that are designed using automated processes. And this is something that I feel like, we were just scratching the surface there. There's huge opportunities there, right? >> Talk about the inference and AI and production kind of angle here, because cost is a huge concern when you look at... And there's a hardware and that flexibility there. So I can see how that could help, but is there a cost freight train that can get out of control here if you don't deploy properly? Talk about the scale problem around cost in AI. >> Yeah, absolutely. So, you know, very quickly. One thing that people tend to think about is the cost is. You know, training has really high dollar amounts it tends over index on that. But what you have to think about is that for every model that's actually useful, you're going to train it once, and then run it a large number of times in inference. That means that over the lifetime of a model, the vast majority of the compute cycles and the cost are going to go to inference. And that's what we address, right? So, and to give you some idea, if you're talking about using large language model today, you know, you can say it's going to cost a couple of cents per, you know, 2,000 words output. If you have a million users active, you know, a day, you know, if you're lucky and you have that, you can, this cost can actually balloon very quickly to millions of dollars a month, just in inferencing costs. You know, assuming you know, that you actually have access to the infrastructure to run it, right? So means that if you don't pay attention to these inference costs and that's definitely going to be a surprise. And affects the economics of the product where this is embedded in, right? So this is something that, you know, if there's quite a bit of attention being put on right now on how do you do search with large language models and you don't pay attention to the economics, you know, you can have a surprise. You have to change the business model there. >> Yeah. I think that's important to call out, because you don't want it to be a runaway cost structure where you architected it wrong and then next thing you know, you got to unwind that. I mean, it's more than technical debt, it's actually real debt, it's real money. So, talk about some of the dynamics with the customers. How are they architecting this? How do they get ahead of that problem? What do you guys do specifically to solve that? >> Yeah, I mean, well, we help customers. So, it's first of all, be hyper aware, you know, understanding what's going to be the cost for them deploying the models into production and showing them the possibilities of how you can deploy the model with different cost structure, right? So that's where, you know, the ability to have hardware independence is so important because once you have hardware independence, after you optimize models, obviously, you have a new, you know, dimension of freedom to choose, you know, what is the right throughput per dollar for you. And then where, and what are the options? And once you make that decision, you want to automate the process of putting into production. So the way we help customers is showing very clearly in their use case, you know, how they can deploy their models in a much more cost-effective way. You know, when the cases... There's a case study that we put out recently, showing a 4x reduction in deployment costs, right? So this is by doing a mix optimization and choosing the right hardware. >> How do you address the concern that someone might say, Luis said, "Hey, you know, I don't want to degrade performance and latency, and I don't want the user experience to suffer." What's the answer there? >> Two things. So first of all, all of the manipulations that we do in the model is to turn the model to efficient code without changing the behavior of the models. We wouldn't degrade the experience of the user by having the model be wrong more often. And we don't change that at all. The model behaves the way it was validated for. And then the second thing is, you know, user experience with respect to latency, it's all about a maximum... Like, you could say, I want a model to run at 50 milliseconds or less. If it's much faster than 15 seconds, you're not going to notice the difference. But if it's lower, you're going to notice a difference. So the key here is that, how do you find a set of options to deploy, that you are not overshooting performance in a way that's going to lead to costs that has no additional benefits. And this provides a huge, a very significant margin of choices, set of choices that you can optimize for cost without degrading customer experience, right. End user experience. >> Yeah, and I also point out the large language models like the ChatGPTs of the world, they're coming out with Dave Moth and I were talking on this breaking analysis around, this being like, over 10X more computational intensive on capabilities. So this hardware independence is a huge thing. So, and also supply chain, some people can't get servers by the way, so, or hardware these days. >> Or even more interestingly, right? So they do not grow in trees, John. Like GPUs is not kind of stuff that you plant an orchard until you have a bunch and then you can increase it, but no, these things, you know, take a while. So, and you can't increase it overnight. So being able to live with those cycles that are available to you is not just important for all for cost, but also important for people to scale and serve more users at, you know, at whatever pace that they come, right? >> You know, it's really great to talk to you, and congratulations on OctaML. Looking forward to the startup showcase, we'll be featuring you guys there. But I want to get your personal opinion as someone in the industry and also, someone who's been in the computer science area for your career. You know, computer science has always been great, and there's more people enrolling in computer science, more diversity than ever before, but there's also more computer science related fields. How is this opening up computer science and where's AI going with the computers, with the science? Can you share your vision on, you know, the aperture, or the landscape of CompSci, or CS students, and opportunities. >> Yeah, no, absolutely. I think it's fair to say that computer has been embedded in pretty much every aspect of human life these days. Human life these days, right? So for everything. And AI has been a counterpart, it been an integral component of computer science for a while. And this medicines that happened in the last 10, 15 years in AI has shown, you know, new application has I think re-energized how people see what computers can do. And you, you know, there is this picture in our department that shows computer science at the center called the flower picture, and then all the different paddles like life sciences, social sciences, and then, you know, mechanical engineering, all these other things that, and I feel like it can replace that center with computer science. I put AI there as well, you see AI, you know touching all these applications. AI in healthcare, diagnostics. AI in discovery in the sciences, right? So, but then also AI doing things that, you know, the humans wouldn't have to do anymore. They can do better things with their brains, right? So it's permitting every single aspect of human life from intellectual endeavor to day-to-day work, right? >> Yeah. And I think the ChatGPT and OpenAI has really kind of created a mainstream view that everyone sees value in it. Like you could be in the data center, you could be in bio, you could be in healthcare. I mean, every industry sees value. So this brings up what I can call the horizontally scalable use constance. And so this opens up the conversation, what's going to change from this? Because if you go horizontally scalable, which is a cloud concept as you know, that's going to create a lot of opportunities and some shifting of how you think about architecture around data, for instance. What's your opinion on what this will do to change the inflection of the role of architecting platforms and the role of data specifically? >> Yeah, so good question. There is a lot in there, by the way, I should have added the previous question, that you can use AI to do better AI as well, which is what we do, and other folks are doing as well. And so the point I wanted to make here is that it's pretty clear that you have a cloud focus component with a nudge focused counterparts. Like you have AI models, but both in the Cloud and in the Edge, right? So the ability of being able to run your AI model where it runs best also has a data advantage to it from say, from a privacy point of view. That's inherently could say, "Hey, I want to run something, you know, locally, strictly locally, such that I don't expose the data to an infrastructure." And you know that the data never leaves you, right? Never leaves the device. Now you can imagine things that's already starting to happen, like you do some forms of training and model customization in the model architecture itself and the system architecture, such that you do this as close to the user as possible. And there's something called federated learning that has been around for some time now that's finally happening is, how do you get a data from butcher places, you do, you know, some common learning and then you send a model to the Edges, and they get refined for the final use in a way that you get the advantage of aggregating data but you don't get the disadvantage of privacy issues and so on. >> It's super exciting. >> And some of the considerations, yeah. >> It's super exciting area around data infrastructure, data science, computer science. Luis, congratulations on your success at OctaML. You're in the middle of it. And the best thing about its businesses are looking at this and really reinventing themselves and if a business isn't thinking about restructuring their business around AI, they're probably will be out of business. So this is a great time to be in the field. So thank you for sharing your insights here in theCUBE. >> Great. Thank you very much, John. Always a pleasure talking to you. Always have a lot of fun. And we both speak really fast, I can tell, you know, so. (both laughing) >> I know. We'll not the transcript available, we'll integrate it into our CubeGPT model that we have Luis. >> That's right. >> Great. >> Great. >> Great to talk to you, thank you, John. Thanks, man, bye. >> Hey, this is theCUBE. I'm John Furrier, here in Palo Alto, Cube Conversation. Thanks for watching. (gentle music)

>>How do y'all, and welcome back to Supercomputing 2022. We're the Cube, and we are live from Dallas, Texas. I'm joined by my co-host, David Nicholson. David, hello. Hello. We are gonna be talking about data and enterprise AI at scale during this segment. And we have the pleasure of being joined by both Dell and Navidia. Anthony and Bob, welcome to the show. How you both doing? Doing good. >>Great. Great show so far. >>Love that. Enthusiasm, especially in the afternoon on day two. I think we all, what, what's in that cup? Is there something exciting in there that maybe we should all be sharing with you? >>Just say it's just still Yeah, water. >>Yeah. Yeah. I love that. So I wanna make sure that, cause we haven't talked about this at all during the show yet, on the cube, I wanna make sure that everyone's on the same page when we're talking about data unstructured versus structured data. I, it's in your title, Anthony, tell me what, what's the difference? >>Well, look, the world has been based in analytics around rows and columns, spreadsheets, data warehouses, and we've made predictions around the forecast of sales maintenance issues. But when we take computers and we give them eyes, ears, and fingers, cameras, microphones, and temperature and vibration sensors, we now translate that into more human experience. But that kind of data, the sensor data, that video camera is unstructured or semi-structured, that's what that >>Means. We live in a world of unstructured data structure is something we add to later after the fact. But the world that we see and the world that we experience is unstructured data. And one of the promises of AI is to be able to take advantage of everything that's going on around us and augment that, improve that, solve problems based on that. And so if we're gonna do that job effectively, we can't just depend on structured data to get the problem done. We have to be able to incorporate everything that we can see here, taste, smell, touch, and use >>That as, >>As part of the problem >>Solving. We want the chaos, bring it. >>Chaos has been a little bit of a theme of our >>Show. It has been, yeah. And chaos is in the eye of the beholder. You, you think about, you think about the reason for structuring data to a degree. We had limited processing horsepower back when everything was being structured as a way to allow us to be able to, to to reason over it and gain insights. So it made sense to put things into rows and tables. How does, I'm curious, diving right into where Nvidia fits into this, into this puzzle, how does NVIDIA accelerate or enhance our ability to glean insight from or reason over unstructured data in particular? >>Yeah, great question. It's really all about, I would say it's all about ai and Invidia is a leader in the AI space. We've been investing and focusing on AI since at least 2012, if not before, accelerated computing that we do it. Invidia is an important part of it, really. We believe that AI is gonna revolutionize nearly every aspect of computing. Really nearly every aspect of problem solving, even nearly every aspect of programming. And one of the reasons is for what we're talking about now is it's a little impact. Being able to incorporate unstructured data into problem solving is really critical to being able to solve the next generation of problems. AI unlocks, tools and methodologies that we can realistically do that with. It's not realistic to write procedural code that's gonna look at a picture and solve all the problems that we need to solve if we're talking about a complex problem like autonomous driving. But with AI and its ability to naturally absorb unstructured data and make intelligent reason decisions based on it, it's really a breakthrough. And that's what NVIDIA's been focusing on for at least a decade or more. >>And how does NVIDIA fit into Dell's strategy? >>Well, I mean, look, we've been partners for many, many years delivering beautiful experiences on workstations and laptops. But as we see the transition away from taking something that was designed to make something pretty on screen to being useful in solving problems in life sciences, manufacturing in other places, we work together to provide integrated solutions. So take for example, the dgx a 100 platform, brilliant design, revolutionary bus technologies, but the rocket ship can't go to Mars without the fuel. And so you need a tank that can scale in performance at the same rate as you throw GPUs at it. And so that's where the relationship really comes alive. We enable people to curate the data, organize it, and then feed those algorithms that get the answers that Bob's been talking about. >>So, so as a gamer, I must say you're a little shot at making things pretty on a screen. Come on. That was a low blow. That >>Was a low blow >>Sassy. What I, >>I Now what's in your cup? That's what I wanna know, Dave, >>I apparently have the most boring cup of anyone on you today. I don't know what happened. We're gonna have to talk to the production team. I'm looking at all of you. We're gonna have to make that better. One of the themes that's been on this show, and I love that you all embrace the chaos, we're, we're seeing a lot of trend in the experimentation phase or stage rather. And it's, we're in an academic zone of it with ai, companies are excited to adopt, but most companies haven't really rolled out their strategy. What is necessary for us to move from this kind of science experiment, science fiction in our heads to practical application at scale? Well, >>Let me take this, Bob. So I've noticed there's a pattern of three levels of maturity. The first level is just what you described. It's about having an experience, proof of value, getting stakeholders on board, and then just picking out what technology, what algorithm do I need? What's my data source? That's all fun, but it is chaos over time. People start actually making decisions based on it. This moves us into production. And what's important there is normality, predictability, commonality across, but hidden and embedded in that is a center of excellence. The community of data scientists and business intelligence professionals sharing a common platform in the last stage, we get hungry to replicate those results to other use cases, throwing even more information at it to get better accuracy and precision. But to do this in a budget you can afford. And so how do you figure out all the knobs and dials to turn in order to make, take billions of parameters and process that, that's where casual, what's >>That casual decision matrix there with billions of parameters? >>Yeah. Oh, I mean, >>But you're right that >>That's, that's exactly what we're, we're on this continuum, and this is where I think the partnership does really well, is to marry high performant enterprise grade scalability that provides the consistency, the audit trail, all of the things you need to make sure you don't get in trouble, plus all of the horsepower to get to the results. Bob, what would you >>Add there? I think the thing that we've been talking about here is complexity. And there's complexity in the AI problem solving space. There's complexity everywhere you look. And we talked about the idea that NVIDIA can help with some of that complexity from the architecture and the software development side of it. And Dell helps with that in a whole range of ways, not the least of which is the infrastructure and the server design and everything that goes into unlocking the performance of the technology that we have available to us today. So even the center of excellence is an example of how do I take this incredibly complex problem and simplify it down so that the real world can absorb and use this? And that's really what Dell and Vidia are partnering together to do. And that's really what the center of excellence is. It's an idea to help us say, let's take this extremely complex problem and extract some good value out of >>It. So what is Invidia's superpower in this realm? I mean, look, we're we are in, we, we are in the era of Yeah, yeah, yeah. We're, we're in a season of microprocessor manufacturers, one uping, one another with their latest announcements. There's been an ebb and a flow in our industry between doing everything via the CPU versus offloading processes. Invidia comes up and says, Hey, hold on a second, gpu, which again, was focused on graphics processing originally doing something very, very specific. How does that translate today? What's the Nvidia again? What's, what's, what's the superpower? Because people will say, well, hey, I've got a, I've got a cpu, why do I need you? >>I think our superpower is accelerated computing, and that's really a hardware and software thing. I think your question is slanted towards the hardware side, which is, yes, it is very typical and we do make great processors, but the processor, the graphics processor that you talked about from 10 or 20 years ago was designed to solve a very complex task. And it was exquisitely designed to solve that task with the resources that we had available at that time. Time. Now, fast forward 10 or 15 years, we're talking about a new class of problems called ai. And it requires both exquisite, soft, exquisite processor design as well as very complex and exquisite software design sitting on top of it as well. And the systems and infrastructure knowledge, high performance storage and everything that we're talking about in the solution today. So Nvidia superpower is really about that accelerated computing stack at the bottom. You've got hardware above that, you've got systems above that, you have middleware and libraries and above that you have what we call application SDKs that enable the simplification of this really complex problem to this domain or that domain or that domain, while still allowing you to take advantage of that processing horsepower that we put in that exquisitely designed thing called the gpu >>Decreasing complexity and increasing speed to very key themes of the show. Shocking, no one, you all wanna do more faster. Speaking of that, and I'm curious because you both serve a lot of different unique customers, verticals and use cases, is there a specific project that you're allowed to talk about? Or, I mean, you know, you wanna give us the scoop, that's totally cool too. We're here for the scoop on the cube, but is there a specific project or use case that has you personally excited Anthony? We'll start with that. >>Look, I'm, I've always been a big fan of natural language processing. I don't know why, but to derive intent based on the word choices is very interesting to me. I think what compliments that is natural language generation. So now we're having AI programs actually discover and describe what's inside of a package. It wouldn't surprise me that over time we move from doing the typical summary on the economic, the economics of the day or what happened in football. And we start moving that towards more of the creative advertising and marketing arts where you are no longer needed because the AI is gonna spit out the result. I don't think we're gonna get there, but I really love this idea of human language and computational linguistics. >>What a, what a marriage. I agree. Think it's fascinating. What about you, Bob? It's got you >>Pumped. The thing that really excites me is the problem solving, sort of the tip of the spear in problem solving. The stuff that you've never seen before, the stuff that you know, in a geeky way kind of takes your breath away. And I'm gonna jump or pivot off of what Anthony said. Large language models are really one of those areas that are just, I think they're amazing and they're just kind of surprising everyone with what they can do here on the show floor. I was looking at a demonstration from a large language model startup, basically, and they were showing that you could ask a question about some obscure news piece that was reported only in a German newspaper. It was about a little shipwreck that happened in a hardware. And I could type in a query to this system and it would immediately know where to find that information as if it read the article, summarized it for you, and it even could answer questions that you could only only answer by looking pic, looking at pictures in that article. Just amazing stuff that's going on. Just phenomenal >>Stuff. That's a huge accessibility. >>That's right. And I geek out when I see stuff like that. And that's where I feel like all this work that Dell and Invidia and many others are putting into this space is really starting to show potential in ways that we wouldn't have dreamed of really five years ago. Just really amazing. And >>We see this in media and entertainment. So in broadcasting, you have a sudden event, someone leaves this planet where they discover something new where they get a divorce and they're a major quarterback. You wanna go back somewhere in all of your archives to find that footage. That's a very laborist project. But if you can use AI technology to categorize that and provide the metadata tag so you can, it's searchable, then we're off to better productions, more interesting content and a much richer viewer experience >>And a much more dynamic picture of what's really going on. Factoring all of that in, I love that. I mean, David and I are both nerds and I know we've had take our breath away moments, so I appreciate that you just brought that up. Don't worry, you're in good company. In terms of the Geek Squad over >>Here, I think actually maybe this entire show for Yes, exactly. >>I mean, we were talking about how steampunk some of the liquid cooling stuff is, and you know, this is the only place on earth really, or the only show where you would come and see it at this level in scale and, and just, yeah, it's, it's, it's very, it's very exciting. How important for the future of innovation in HPC are partnerships like the one that Navia and Dell have? >>You wanna start? >>Sure, I would, I would just, I mean, I'm gonna be bold and brash and arrogant and say they're essential. Yeah, you don't not, you do not want to try and roll this on your own. This is, even if we just zoomed in to one little beat, little piece of the technology, the software stack that do modern, accelerated deep learning is incredibly complicated. There can be easily 20 or 30 components that all have to be the right version with the right buttons pushed, built the right way, assembled the right way, and we've got lots of technologies to help with that. But you do not want to be trying to pull that off on your own. That's just one little piece of the complexity that we talked about. And we really need, as technology providers in this space, we really need to do as much as we do to try to unlock the potential. We have to do a lot to make it usable and capable as well. >>I got a question for Anthony. All >>Right, >>So in your role, and I, and I'm, I'm sort of, I'm sort of projecting here, but I think, I think, I think your superpower personally is likely in the realm of being able to connect the dots between technology and the value that that technology holds in a variety of contexts. That's right. Whether it's business or, or whatever, say sentences. Okay. Now it's critical to have people like you to connect those dots. Today in the era of pervasive ai, how important will it be to have AI have to explain its answer? In other words, words, should I trust the information the AI is giving me? If I am a decision maker, should I just trust it on face value? Or am I going to want a demand of the AI kind of what you deliver today, which is No, no, no, no, no, no. You need to explain this to me. How did you arrive at that conclusion, right? How important will that be for people to move forward and trust the results? We can all say, oh hey, just trust us. Hey, it's ai, it's great, it's got Invidia, you know, Invidia acceleration and it's Dell. You can trust us, but come on. So many variables in the background. It's >>An interesting one. And explainability is a big function of ai. People want to know how the black box works, right? Because I don't know if you have an AI engine that's looking for potential maladies in an X-ray, but it misses it. Do you sue the hospital, the doctor or the software company, right? And so that accountability element is huge. I think as we progress and we trust it to be part of our everyday decision making, it's as simply as a recommendation engine. It isn't actually doing all of the decisions. It's supporting us. We still have, after decades of advanced technology algorithms that have been proven, we can't predict what the market price of any object is gonna be tomorrow. And you know why? You know why human beings, we are so unpredictable. How we feel in the moment is radically different. And whereas we can extrapolate for a population to an individual choice, we can't do that. So humans and computers will not be separated. It's a, it's a joint partnership. But I wanna get back to your point, and I think this is very fundamental to the philosophy of both companies. Yeah, it's about a community. It's always about the people sharing ideas, getting the best. And anytime you have a center of excellence and algorithm that works for sales forecasting may actually be really interesting for churn analysis to make sure the employees or students don't leave the institution. So it's that community of interest that I think is unparalleled at other conferences. This is the place where a lot of that happens. >>I totally agree with that. We felt that on the show. I think that's a beautiful note to close on. Anthony, Bob, thank you so much for being here. I'm sure everyone feels more educated and perhaps more at peace with the chaos. David, thanks for sitting next to me asking the best questions of any host on the cube. And thank you all for being a part of our community. Speaking of community here on the cube, we're alive from Dallas, Texas. It's super computing all week. My name is Savannah Peterson and I'm grateful you're here. >>So I.

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

(lighthearted music) >> Hey all. Welcome back to theCube's coverage of Kubecon North America '22 CloudNativeCon. We're in Detroit. We've been here all day covering day one of the event from our perspective. Three days of coverage coming at you. Lisa Martin here with John Furrier. John, a lot of buzz today. A lot of talk about the maturation of Kubernetes with different services that vendors are offering. We talked a little bit about security earlier today. One of the things that is a hot topic is national security. >> Yeah, this is a huge segment we got coming up. It really takes that all that nerd talk about Kubernetes and puts it into action. We actually see demonstrable results. This is about advanced artificial intelligence for tactical decision making at the edge to support our military operations because a lot of the deaths are because of bad technology. And this has been talked about. We've been covering Silicon Angle, we wrote a story there now on this topic. This should be a really exciting segment so I'm really looking forward to it. >> Excellent, so am I. Please welcome back one of our alumni, Nick Barcet senior director, customer led open innovation at Red Hat. Great to have you back. Greg Forrest joins us as well from Lockheed Martin Director of AI Foundations. Guys, great to have you on the program. Nick, what's been your perception before we dig into the news and break that open of KubeCon 2022? >> So, KubeCon is always a wonderful event because we can see people working with us in the community developing new stuff, people that we see virtually all year. But it's the time at which we can really establish human contact and that's wonderful. And it's also the moments where we can make big topic move forward and the topics have been plenty at this KubeCon from MicroShift to KCP, to AI, to all domains have been covered. >> Greg, you're the director of AI foundations at Lockheed Martin. Obviously well known, contractors to the military lot of intellectual property, storied history. >> Greg: Sure. >> Talk about this announcement with Red Hat 'cause I think this is really indicative of what's happening at the edge. Data, compute, industrial equipment, and people, in this case lives are in danger or to preserve peace. This is a killer story in terms of understanding what this all means. What's your take on this relationship with Red Hat? What's the secret sauce? >> Yeah, it's really important for us. So part of our 21st century security strategy as a company is to partner with companies like Red Hat and Big Tech and bring the best of the commercial world into the Department of Defense for our soldiers on the ground. And that's exactly what we announced today or Tuesday in our partnership. And so the ability to take commercial products and utilize them in theater is really important for saving lives on the ground. And so we can go through exactly what we did as part of this demonstration, but we took MicroShift at the edge and we were able to run our AI payloads on that. That provided us with the ability to do things like AI based RF sensing, so radio frequency sensing. And we were also able to do computer vision based technologies at the edge. So we went out, we had a small UAV that went out and searched for a target on the ground. It found a target using its radio frequency capabilities, the RF capabilities. Then once we're able to hone in on that target, what Red Hat device edge and MicroShift enables us to do is actually then switch sensing modalities. And then we're able to look at this target via the camera and use computer vision-based technologies to actually more accurately locate the target and then track that target in real time. So that's one of the keys to be able to actually switch modalities in real time on one platform is really important for our joint all domain operations construct. The idea of how do you actually connect all of these assets in the environment, in the battle space. >> Talk about the challenge and how hard it is to do this. The back haul, you'll go back to the central server, bring data back, connecting things. What if there's insecurity around connectivity? I mean there's a lot of things going, can you just scope the magnitude of how hard it's to actually deploy something at a tactical edge? >> It is. There's a lot of data that comes from all of these sensors, whether they're RF sensors or EO or IR. We're working across multiple domains, right? And so we want to take that data back and train on that and then redeploy to the edge. And so with MicroShift, we're able to do that in a way that's robust, that's repeatable, and that's automated. And that really instills trust in us and our customers that when we deploy new software capabilities to the edge over the air, like we did in this demonstration that they're going to run right on the target hardware. And so that's a huge advantage to what we're doing here that when we push software to the edge in real time we know it's going to run. >> And in realtime is absolutely critical. We talk about it in so many different industries. Oh, it's customers expect realtime access whether it's your banking app or whatnot. But here we're talking about literally life and death situations on the battlefield. So that realtime data access is literally life and death. >> It's paramount to what we're doing. In this case, the aircraft started with one role which was to go find a radio frequency admitter and then switch roles to then go get cameras and eyes on that. So where is that coming from? Are there people on the ground? Are there dangerous people on the ground? And it gives the end user on the ground complete situational awareness of what is actually happening. And that is key for enhanced decision making. Enhanced decision making is critical to what we're doing. And so that's really where we're advancing this technology and where we can save lives. >> I read a report from General Mattis when he was in service that a lot of the deaths are due to not having enough information really at the edge. >> Greg: Friendly fire. >> Friendly fire, a lot of stuff that goes on there. So this is really, really important. Nick, you're sitting there saying this is great. My customer's talking about the product. This is your innovation, Red Hat device edge in action. This is real. This is industrial- >> So it's more than real. Actually this type of use case is what convinced us to transform a technology we had been working on which is a small form factor of Kubernetes to transform it into a product. Because sometimes, US engineers have a tendency to invent stuff that are great on paper, but it's a solution trying to find a problem. And we need customers to work with us to make sure that do solution do solve a real problem. And Lockheed was great. Worked with us upstream on that project. Helped us prove out that the concept was actually worth it and we waited until Lockheed had tested the concept in the air. >> Okay, so Red Hat device edge and MicroShift, explain that, how that works real quick for the folks that don't know. So one of the thing we learned is that Kubernetes is great but it's only part of the journey. In order to get those workloads on those aircraft or in order to get those workloads in a factory, you also need to consider the full life cycle of the device itself. And you don't handle a device that is inside of a UAV or inside of a factory the same way you handle a server. You have to deal with those devices in a way that is much more akin to a setup box. So we had to modify how the OS was behaving to deal with devices and we reduced what we had built in real for each edge aspect and combined it with MicroShift and that's what became with that Red Hat device edge. >> We're in a low SWAP environment, space, weight and power, right? Or very limited, We're on a small UAS in this demonstration. So the ability to spool up and spool down containers and to save computing power and to do that on demand and orchestrate that with MicroShift is paramount to what we're doing. We wouldn't be able to do it without that capability. >> John: That's awesome. >> I want to get both of your opinions. Nick, we'll start with you and then Greg we'll go to you. In terms of MicroShift , what is its superpower? What differentiates it from other competing solutions in the market? >> So MicroShift is Kubernetes but reduced to the strict minimum of a runtime version of Kubernetes so that it takes a minimal footprint so that we maximize the space available for the workload in those very constraints environments. On a board where you have eight or 16 gig of RAM, if you use only two gig of that to run the infrastructure component, you leave the rest for the AI workload that you need on the drone. And that's what is really important. >> And these AI payloads, the inference that we're doing at the edge is very compute intensive. So again, the ability to manage that and orchestrate that is paramount to running on these very small board computers. These are small drones that don't have a lot of weight that don't allow a lot of space. >> John: Got to be efficient >> And be efficient with it. >> How were you guys involved? Talk about the relationship. So you guys were tightly involved. Talk about the roles you guys played together. Was it co-development? Was it customer/partner? Talk about the relationship. >> Yeah, so we started actually with satellite. So you can think of small cube sets in a very similar environment to a low powered UAV. And it started there. And then in the last, I would say year or so, Nick we have worked together to develop MicroShift. We work closely on Slack channels together like we're part of the same team. >> John: That's great. >> And hey Red Hat, this is what we need, this is what we're looking for. These are the constraints that we have. And this team has been amazing and just delivered on everything that we've asked for. >> I mean this is really an example of the innovation at the edge, industrial edge specifically. You got an operating system, you got form factor challenges, you got operating parameters. And just to having that flex, you can't just take this and put it over there. >> But it's what really is a community applied to an industrial context. So what happened there is we worked as part of the MicroShift community together with a real time communication channel, the same slack that anybody developing Kubernetes uses we've been using to identify where the problems were, how to solve them, bring new ideas and that's how we tackle these problems. >> Yeah, a true open source model I mean the Red Hat and the Lockheed teams were in it together on a daily basis communicating like we were part of the same company. And and that's really how you move these things forward. >> Yeah, and of course open source is great but also you got to lock down the security. How did you guys handle that? What's going on with the security? 'Cause you got to make sure no take over the devices. >> So the funny thing is that even though what we produce is highly inclusive of security concern, our development model is completely open. So it's not security biopurification, it's security because we apply the best practices. >> John: You see everything. >> Absolutely. >> Yes. >> And then you harden it in the joint development, there it is. >> Yeah, but what we support, what we offer as a product is the same for Lockheed or for any other customer because there is no domain where security is not important. When you control the recognition on a drone or where you control the behavior of a robot in a factory, security is paramount because you can't immobilize a country by infecting a robot the same way you could immobilize a military operation- >> Greg: That's right. >> By infecting a UAV. >> Not to change the subject, but I got to go on a tangent here cause it pops in my head. You mentioned cube set, not related to theCUBE of course. Where theCube for the video. Cube sets are very powerful. People can launch space right now very inexpensively. So it's a highly contested and congested environment. Any space activity going on around the corner with you guys? 'Cause remember the world's not around, it's edge is now in space. Mars is the edge. >> That's right. >> Our first prototype for MicroShift was actually a cube set. >> Greg: That's where it started. >> And IBM project, the project called Endurance. That's the first time we actually put MicroShift into use. And that was a very interesting project, very early version of MicroShift . And now we have talks with many other people on reproducing that at more industrial level this was more like a cool high school project. >> But to your point, the scalability across different platforms is there. If we're running on top of MicroShift on this common OS, it just eases the development. Behind the scenes, we have a whole AI factory at Lockheed Martin where we have a common ecosystem for how we actually develop and deploy these algorithms to the edge. And now we've got a common ecosystem at the edge. And so it helps that whole process to be able to do that in automated ways, repeatable ways so we can instill trust in our DRD customer that the validation of verification of this is a really important aspect. >> John: Must be a fun place to work. >> It is, it's exciting. There's endless opportunities. >> You must get a lot of young kids applying for those jobs. They're barely into the whole. I mean, AI's a hot feel and people want to get their hands on real applications. I was serious about space. Is there space activity going on with you guys or is it just now military edge, not yet military space? Or is that classified? >> Yeah, so we're working across multiple fronts, absolutely. >> That's awesome. >> What excite, oh, sorry John. What excites you most, never a dull moment with what you're doing, but just the potential to enable a safer, a more secure world, what excites you most about this partnership and the direction and the we'll say the trajectory it's going on? >> Yeah, I think, for me, the safer insecure world is paramount to what we're doing. We're here for national defense and for our allies and that's really critical to what we're doing. That's what motivates me. That's what gets me up in the morning to know that there is a soldier on the ground who will be using this technology and we will give be giving that person the situational awareness to make the right decisions at the right time. So we can go from small UAVs to larger aircraft or we can do it in a small confined edge device like a stalker UAV. We can scale this up to different products different platforms and they don't even have to be Lockheed Martin >> John: And more devices that are going to be imagined. >> More devices that we haven't even imagined yet. >> Right, that aren't even on the frontier yet. Nick, what's next from your perspective? >> In the domain we are in, next is always plenty of things. Sustainability is a huge domain right now on which we're working. We have lots of things going on in the AI space, stuff going on with Lockheed Martin. We have things going on in the radio network domain. We've been very heavily involved in telecommunication and this is constantly evolving. There is not one domain that, in terms of infrastructure Red Hat is not touching >> Well, this is the first of multiple demonstrations. The scenarios will get more complex with multiple aircraft and in the future, we're also looking at bringing a lot of the 5G work. Lockheed has put a large focus on 5G.mil for military applications and running some of those workloads on top of MicroShift as well is things to come in the future that we are already planning and looking at. >> Yeah, and it's needed in theater to have connectivity. Got to have your own connectivity. >> It's paramount, absolutely. >> Absolutely, it's paramount. It's game-changing. Guys, thank you so much for joining John and me on theCube talking about how Red Hat and Lockheed Martin are working together to leverage AI to really improve decision making and save more lives. It was a wonderful conversation. We're going to have to have you back 'cause we got to follow this. >> Yeah, of course. >> This was great, thank you so much. >> Thank you very much for having us. >> Lisa: Our pleasure, thank you. >> Greg: Really appreciate it. >> Excellent. For our guests and John Furrier, I'm Lisa Martin. You're watching theCUBE Live from KubeCon CloudNativeCon '22 from Detroit. Stick around. Next guest is going to join John and Savannah in just a minute. (lighthearted music)

>>Hey everyone. Welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four, where we continue to talk with the AWS ecosystem partners, this topic, cybersecurity protect and detect against threats. I'm your host, Lisa Martin. I've got a new guest with me. Ryan Ferris joins me the VP of products and engineering at Anisha. Ryan. Welcome to the program. Great to have you. >>Thank you so much for having me. >>So let's dig right in. Why are software vendors turning to Anisha to help them address and access the nearly for over 200 billion market public sector, federal market for cloud services? What is that key event? >>Yeah, it's it. If you know anything about FedRAMP and if you've looked into it, it takes a long time to achieve Fedra. So when customers kind of go into this cold and they're from Mars and they're like, what is bed? They usually find that it's an 18 month journey, maybe a 24 month journey. And so Anisha helps shorten that journey with lower costs and faster time to market. So if you're waiting for our revenue stream from say a government entity, we can get you there faster and get you to a, a state of Fedra certified in a shorter time period. And that's the value problem. >>Faster time to value is critical for organizations. So let's look at this journey as you talked about it, what does the path to compliance look like for specifically for AWS customers with a nation and without help us understand the value add? >>Yeah. So if you're doing it without Angen or if you're just kind of doing it yourself, which some customers choose to do, then they have to go on that journey and kind of learn about three primary things. One thing is how do I just write the entire package? Like there there's a thing called an SSP or a, a system security plan. And that thing is maybe seven or 800 pages long. And you have to offer that all by yourself so you can get help with that or not. That's sort of the academic and, and, and tech writing piece of it. There's another piece of it around what does my environment look like? So as I am ruling out this Fedra solution, what are each piece in my environment that needs to be compliant with Fedra? And it's a voluminous amount of things can be either a dozen or maybe up to a hundred things that you have to tweak and change. So there's a technical deployment store here as well. And then the third thing is keeping you compliant in your AWS environment after you've achieved kind of that readiness state. So the journey does not stop once you achieve Fedra, ATO, it goes on and on and on, and Anisha helps customers kind of maintain and keep them there in that fully compliance state after achieving ATO, >>What's the timeframe for AWS customers in terms of going, alright, we realize we're going on this journey. It's challenging. We need An's help. What's the timeframe to get them actually certified. >>Yeah. We look at the timeframe between the moment you deploy and the moment you start writing about that tech, that Fedra package and when you're audit ready, and in the best case scenario, that could be a few months, right? But you're always, your mileage may vary based on kind of your application readiness and how ready you are to pursue that journey. So the fastest happy path is a few months to audit, audit an audit ready state, but then you have, you kinda have to go through a process whereby you're in the queue for Fedra. And that can kind of take maybe an extra few months, but it really is that that three month accelerated timeframe in the best case scenario, >>Got it. Three months accelerated timeframe. Are there other compliance standards that besides Fedra that you help organizations get compliance with? >>Right. So it's a great question. So FedRAMP in and of itself is just really hard to get to. It's just so many things that you have to do, but if you get to that state, it's based off of a standard called missed 853 specifically rev four, that's kind of a mouthful, but once you achieve that state, there's basically 325 controls that come along with fed moderate. And that buys you a lot of leverage in leeway in mapping and sort of crosswalking to other compliance levels. So if you achieve that state, you buy a lot of, kind of goodness with things that map to either PCI or even HIPAA or SOC two. And, and so you, you kind of get a big benefit and sort of a big bang for your buck by having achieved that, that state for Fedra. >>So from an AWS customer, talk to me about, obviously we talked about the time to value the speed with which you enable organizations to achieve compliance and, and readiness. What what's in it for me in terms of working with a nation as an AWS customer. >>Yeah. For, so for AWS specifically our stack, well, we have kind of two versions of our stack. One is meant for Azure and it's kind of cookie cutter and meant for folks that have an entrenched Azure footprint. The other is it's the majority of our market it's folks that want to in accelerator footprint in AWS. So what's in it for you is that Anan kind of presents something that looks pretty similar to a landing zone, but it's a little bit more peppered with complexity and with tuned configurations. So if you're an AWS customer and let's see you've had an environment for the last 5, 6, 7 years, we help you kind of take that environment and enhance it and become FedRAMP ready in a much faster state. And we are leveraging and utilizing a lot of native AWS core services like ECR, for example, is one we're just starting to lean into AWS inspector for bone scans, those types of things. And then kind of when you get up to that audit, ready state and through ATO, we aggregate a lot of that vulnerability information and vulnerability scanning information into a parable readable, actionable format. And most of those things, those gatherings of data are AWS specific functions that we kind of piggyback on. So we're heavily into cloud trail and, and quite heavy into kind of using the things that are already at our fingertips just by deploying into AWS. >>Yeah. Leveraging what they already are familiar with kind of meeting the customers where they are. I think these days is such an important factor to help organizations make the changes as quickly and dynamically as they need to. >>That's right. Yeah. That's perfect. Yeah. A lot of customers, you know, when, when they start on the journey, they kind of, they, they sort of uncover the, uncover the details around, well, I have an application and this application has existed for six or seven years. How do I get this thing FedRAMP ready? And what does onboarding mean to your stack? We try to make that specific step as easy as possible. So when I'm on the phone with prospects and I'm talking to 'em about embarking on a journey, I kind of get them to a mental model where they treat their application VPC or their application environment as sort of a, and we deploy a separate VPC into their, into their cloud account. And then we peer that information. It's kind of getting into the mechanics a little bit, but we try to make it as easy as possible to start doing the things that we're obliged to do for FedRAMP, for their application, like bone scans and, and operationalization of logging and things like that. And then we pull that information into our AIAN managed BPC. And I think once customers really start to understand and sort of synthesize that mental model, then they kind of have this Baha moment. They're like, oh, okay. Now I, now I really understand how your platform can accelerate this journey into a period that is no more than say two or three months of onboarding >>No more than two or three months. That's, that's a nice kind of guarantee for organizations who are you typically engaging with? Is it the CISO level or are there other folks involved in this conversation? >>Yeah, I, the CISO is probably the best persona to engage with, but it so varies from customer to customer and you never really know who's really gonna, oftentimes it's the CEO or, or sometimes it's a champion that might be the CFO or someone that's incentivized to really start getting market share for federal customers that they don't have access to. That might even be a VP of engineering that we're, that we're conversing with. But most often I think the CISO is central because the CISO of course wants to give in details of what does the staff consist of and exactly how are you helping me with this big burden of continuous monitoring that fed Fedra makes me do. And, and where, where do you fit in that story? So it's usually the CSO, >>Usually the CSO, but some of the other personas that you mentioned sounds like it's definitely a C level or at least a, an executive level conversation. >>It is. Yeah. I'll try to divide that a little bit from my persona. Like I, I run engineering and product. I'm usually dealing with a rather talking to and engaging with the CSO, but the folks that cut the check are either either the CEO or the CFO that really want to widen that kind of revenue stream that they don't have access to. And they're the real decision making personas in this deal. Now, after the decision decision is made, then, you know, they're vetting through VPs of engineering or engineering leaders or the CSO. So like the, the folks that pull the purse strings are usually, you know, the ones that are cutting the check to make this investment that is usually the CSO or rather CEO and the CFO. >>Got it. Okay. So if I'm an AWS customer and I'm on this journey for fed re certification, I've, I've been on it for a while. How do I know it's time to raise my hand or pick up the phone and call Anisha? >>Yeah. You know, some customers that we speak with have already tried to do it and maybe they've failed. Maybe they've been like 12 or 14 months into the journey. And they've said things like, we just don't know how to put the package together, or maybe they've engaged with the third party auditor. And the third party auditor has said, sorry, you guys need to go back to the drawing board or maybe they've missed a good percentage of the technical requirements and they need some consultation and advice or a cookie cutter approach. So it kind of, every journey is different when we are engaging. Sometimes folks are just coming in completely cold or maybe they failed. But the more interesting ones, and I think when we can look a little bit more like heroes are the ones that have tried it, and then a year later they come back, they come back to an, and they want that accelerated goodness. >>Do you have a favorite customer story that you think really articulates the value either from a customer who came in cold or a customer who came in after trying it on their own or with another partner for a year that you think really demonstrates the value that AIAN delivers? >>Yeah. There is a customer story that's sort of top of mind and it's, I think the guy primarily stuck in what tooling I'll anonymize the customer, but this customer kind of chose the wrong level of tooling as they embarked on their journey. And by tooling, I mean, let me get a little bit more specific here. You can't just choose any vulnerability scanner, for instance, if it's a SAS product, or if it's sending data or requests outside of your Fedra boundary, then you're gonna run into trouble. And this reference customer, or this prospect at the time kind of had a lot of friction there. So as they were bumping up against that three Pao deadline, they realized they had a lot of work to do. And we simplified that, that part of the journey substantially for them by essentially selecting and spoon feeding them and, and sort of accelerating that part of the deployment and technical journey for them. And they were very delighted by that part of it. >>When you're talking with customers who are in, in a state of, of change and fluxes, who isn't these days, we've seen the acceleration of digital transformation considerably over the last couple of years. How do you talk with them about a nation as an enabler of their digital transformation overall? >>Yeah. Digital transformation. It's a, it's a broad word. Isn't it like for, for customers that are moving from an on-prem world into the cloud world, you have this great opportunity to kind of start from scratch. And so for Anisha, we are deploying and maybe not start from scratch, but when you're moving from an on-prem environment into the cloud, your footprint, you have this really nice opportunity to embrace more of AWS core services and to kind of rebuild things, kind of make your architecture drastically improved, or like look different to be more supportable and like less operational overhead. And so when an nation presents itself as sort of this platform in a walled garden environment, some customers have this aha moment that like, if you're gonna move either a portion of your environment or a specific application to the cloud, AIAN really helps you establish that security within that boundary and that footprint in a, in a much more accelerated fashion, then if you were selecting each part of your security infrastructure and then trying to implement it by hand, and that's kind of where we shine. >>Got it. We talked about the personas that you're typically engaging with depending on the organization, but how do you help enterprise companies who say Anisha, we wanna improve DevOps efficiency. We wanna get our applications secure that are running on AWS and those that we may wanna move to AWS in the future. >>Yeah. This gets into futures a little bit, but part of our roadmap, a little bit of a, a kind of a look around the corner for our roadmap is that since we know so much about the FedRAMP environment and FedRAMP moderate and the standard called this 853, it's a really powerful security view. And it's also a really powerful compliance view. So, you know, as I was saying before that, if you achieve a lot of depth and excellence in nest 853, it buys you a lot of kind of crosswalk and applicability for SOC two and HIPAA and PCI. So for DevOps organizations and for just engineering organizations that want more pre-pro insight, there's no reason why you can't just deploy our platform and our stack in a pre fraud environment to get that security signaling such that you can catch things early and prevent maybe spillage or leakage or security issues to go into production. So one of the things that we're doing on a roadmap is a, a feature that we call compliance insights, whereby we present a frame of missed 853 RAV4 that you can deploy into any environment. And that particularly helps the DevOps role by saying, well, if I just, for example, exposed an S3 bucket to world, then I can catch that configuration, that compliance product and catch it, trap it and fix before it leaks out to. >>So you talked a little bit about kind of some of the things that are coming up on a, on the product side, what's next for Anisha, as we look at we're rounding out calendar year 22 coming into 2023, there's still so much change in the market. We've got to embrace that. What's next for the company. What can we expect from the VP of products and engineering? >>Yeah, I think in two, two big areas here, we're gonna double down on our Fedra offering offering, and just continuously improve it and improve it. We're pretty tempted to lean in more heavily to CMMC. We hear a lot about CMMC kind of on the periphery, but we just haven't quite felt the market pressure to really go after that. But there's definitely something there. And I would anticipate some offering that maps to that specific compliance that, that compliance framework. And then in the enterprise, we just month after month, we discuss more about how we can create more flexibility in our platform, such that commercial customers can get more of that goodness, and sort of more of that consolidation and time to market, particularly for small and mid-sized customers. So we'll be releasing more of those pieces of functionality in 2023 as well. >>So the commercial folks be on the lookout for that. >>Yes, absolutely. That's a huge untapped market for us. We're super excited about it and we'll be a little cagey on in our plans until we kind of get through this early availability period and then probably make a bigger splash in the first half of 2023. >>That sounds appropriate. Where can the audience go to learn more about what you guys are doing and maybe get ahead on some of those teaser that you just mentioned? >>Yeah. I think our marketing folks will push out more data sheets and marketing material on what's to come. And if you ever wanted to be part of this early availability program that I just discussed, or that I mentioned, you can always go to anan.com and ping us, and we'd be happy to have a conversation with you and we'll lift up the hood and allow you to look under there for, and just carry on the conversation around what's to come. >>All right, getting a peek of what's under the hood. That's always exciting, Ryan, thank you for joining me on this program. AWS startup showcase. We appreciate your time, your insights and a peek into what's going on at Anisha. >>Awesome. It was a pleasure. Thank you so much. >>Likewise. We wanna thank you for watching the AWS startup showcase for Ryan Ferris. I'm Lisa Martin stick right here on the, for great content coming your way. Take care.

>>Hello, everyone. Welcome to the AWS startup showcase. This is season two, episode four, the ongoing series covering exciting startups from the AWS ecosystem to talk about cybersecurity. I'm your host, John furrier. And today I'm excited for this keynote presentation and I'm joined by John Ramsey, vice president of AWS security, John, welcome to the cubes coverage of the startup community within AWS. And thanks for this keynote presentation, >>Happy to be here. >>So, John, what do you guys, what do you do at AWS? Take, take minutes to explain your role, cuz it's very comprehensive. We saw at AWS reinforce event recently in Boston, a broad coverage of topics from Steven Schmid CJ, a variety of the executives. What's your role in particular at AWS? >>If you look at AWS, there are, there is a shared security responsibility model and CJ, the C the CSO for AWS is responsible for securing the AWS portion of the shared security responsibility model. Our customers are responsible for securing their part of the shared security responsible, responsible model. For me, I provide services to those customers to help them secure their part of that model. And those services come in different different categories. The first category is threat detection with guard. We that does real time detection and alerting and detective is then used to investigate those alerts to determine if there is an incident vulnerability management, which is inspector, which looks for third party vulnerabilities and security hub, which looks for configuration vulnerabilities and then Macy, which does sensitive data discovery. So I have those sets of services underneath me to help provide, to help customers secure their part of their shared security responsibility model. >>Okay, well, thanks for the call out there. I want to get that out there because I think it's important to note that, you know, everyone talks inside out, outside in customer focus. 80 of us has always been customer focused. We've been covering you guys for a long time, but you do have to secure the core cloud that you provide and you got great infrastructure tools technology down to the, down to the chip level. So that's cool. You're on the customer side. And right now we're seeing from these startups that are serving them. We had interviewed here at the showcase. There's a huge security transformation going on within the security market. It's the plane at 35,000 feet. That's engines being pulled out and rechange, as they say, this is huge. And, and what, what's it take for your, at customers with the enterprises out there that are trying to be more cyber resilient from threats, but also at the same time, protect what they also got. They can't just do a wholesale change overnight. They gotta be, you know, reactive, but proactive. How does it, what, what do they need to do to be resilient? That's the >>Question? Yeah. So, so I, I think it's important to focus on spending your resources. Everyone has constrained security resources and you have to focus those resources in the areas and the ways that reduce the greatest amount of risk. So risk really can be summed up is assets that I have that are most valuable that have a vulnerability that a threat is going to attack in that world. Then you wanna mitigate the threat or mitigate the vulnerability to protect the asset. If you have an asset that's vulnerable, but a threat isn't going to attack, that's less risky, but that changes over time. The threat and vulnerability windows are continuously evolving as threats, developing trade craft as vulnerabilities are being discovered as new software is being released. So it's a continuous picture and it's an adaptive picture where you have to continuously monitor what's happening. You, if you like use the N framework cybersecurity framework, you identify what you have to protect. >>That's the asset parts. Then you have to protect it. That's putting controls in place so that you don't have an incident. Then you from a threat perspective, then you ha to de detect an incident or, or a breach or a, a compromise. And then you respond and then you remediate and you have to continuously do that cycle to be in a position to, to de to have cyber resiliency. And one of the powers of the cloud is if you're building your applications in a cloud native form, you, your ability to respond can be very surgical, which is very important because then you don't introduce risk when you're responding. And by design, the cloud was, is, is architected to be more resilient. So being able to stay cyber resilient in a cloud native architecture is, is important characteristic. >>Yeah. And I think that's, I mean, it sounds so easy. Just identify what's to be protected. You monitor it. You're protected. You remediate sounds easy, but there's a lot of change going on and you got the cloud scale. And so you got security, you got cloud, you guys's a lot of things going on there. How do you think about security and how does the cloud help customers? Because again, there's two things going on. There's a shared responsibility model. And at the end of the day, the customer's responsible on their side. That's right, right. So that's right. Cloud has some tools. How, how do you think about going about security and, and where cloud helps specifically? >>Yeah, so really it's about there, there's a model called observe, orient, decide an actor, the ULO and it was created by John Boyd. He was a fighter pilot in the Korean war. And he knew that if I could observe what the opponent is doing, orient myself to my goals and their goals, make a decision on what the next best action is, and then act, and then follow that UTI loop, or, or also said a sense sense, making, deciding, and acting. If I can do that faster than the, than the enemy, then I can, I will win every fight. So in the cyber world, being in a position where you are observing and that's where cloud can really help you, because you can interrogate the infrastructure, you can look at what's happening, you can build baselines from it. And then you can look at deviations from, from the norm. It's just one way to observe this orient yourself around. Does this represent something that increases risk? If it does, then what's the next best action that I need to take, make that decision and then act. And that's also where the cloud is really powerful, cuz there's this huge con control plane that lets you lets you enable or disable resources or reconfigure resources. And if you're in, in the, in the situation where you can continuously do that very, very rapidly, you can, you can outpace and out maneuver the adversary. >>Yeah. You know, I remember I interviewed Steven Schmidt in 2014 and at that time everybody was poo pooing. Oh man, the cloud is so unsecure. He made a statement to me and we wrote about this. The cloud is more secure and will be more secure because it can be complicated to the hacker, but also easy for the, for provisioning. So he kind of brought up this, this discussion around how cloud would be more secure turns out he's right. He was right now. People are saying, oh, the cloud's more secure than, than standalone. What's different John now than not even going back to 2014, just go back a few years. Cloud is helpful, is more interrogation. You mentioned, this is important. What's, what's changed in the cloud per se in AWS that enables customers and say third parties who are trying to comply and manage risk as well. So you have this shared back and forth. What's different in the cloud now than just a few years ago that that's helping security. >>Yeah. So if you look at the, the parts of the shared responsibility model, AWS is the further up the stack you go from just infrastructure to platforms, say containers up to serverless the, the, we are taking more of the responsibility of that, of that stack. And in the process, we are investing resources and capabilities. For example, guard duty takes an S audit feed for containers to be able to monitor what's happening from a container perspective. And then in server list, really the majority of what, what needs to be defended is, is part of our responsibility model. So that that's an important shift because in that world, we have a very large team in our world. We have a very large team who knows the infrastructure who knows the threat and who knows how to protect customers all the way up to the, to the, to the boundary. And so that, that's a really important consideration. When you think about how you design your design, your applications is you want the developers to focus on the business logic, the business value and let, but still, also the security of the code that they're writing, but let us take over the rest of it so that you don't have to worry about it. >>Great, good, good insight there. I want to get your thoughts too. On another trend here at the showcase, one of the things that's emerging besides the normal threat landscape and the compliance and whatnot is API protection. I mean APIs, that's what made the cloud great. Right? So, you know, and it's not going away, it's only gonna get better cuz we live in an interconnected digital world. So, you know, APIs are gonna be lingual Franko what they say here. Companies just can't sit back and expect third parties complying with cyber regulations and best practices. So how do security and organizations be proactive? Not just on API, it's just a, a signal in my mind of, of, of more connections. So you got shared responsibility, AWS, your customers and your customers, partners and customers of connection points. So we live in an interconnected world. How do security teams and organizations be proactive on the cyber risk management piece? >>Yeah. So when it comes to APIs, the, the thing you look for is the trust boundaries. Where are the trust boundaries in the system between the user and the, in the machine, the machine and another machine on the network, the API is a trust boundary. And it, it is a place where you need to facilitate some kind of some form of control because what you're, what could happen on the trust boundaries, it could be used to, to attack. Like I trust that someone's gonna give me something that is legitimate, but you don't know that that a actually is true. You should assume that the, the one side of the trust boundary is, is malicious and you have to validate it. And by default, make sure that you know, that what you're getting is actually trustworthy and, and valid. So think of an API is just a trust boundary and that whatever you're gonna receive at that boundary is not gonna be legitimate in that you need to validate, validate the contents of, of whatever you receive. >>You know, I was noticing online, I saw my land who runs S3 a us commenting about 10 years anniversary, 10, 10 year birthday of S3, Amazon simple storage service. A lot of the customers are using all their applications with S3 means it's file repository for their application, workflow ingesting literally thousands and trillions of objects from S3 today. You guys have about, I mean, trillions of objects on S3, this is big part of the application workflow. Data security has come up as a big discussion item. You got S3. I mean, forget about the misconfiguration about S3 buckets. That's kind of been reported on beyond that as application workflows, tap into S3 and data becomes the conversation around securing data. How do you talk to customers about that? Because that's also now part of the scaling of these modern cloud native applications, managing data on Preem cross in flight at rest in motion. What's your view on data security, John? >>Yeah. Data security is also a trust boundary. The thing that's going to access the data there, you have to validate it. The challenge with data security is, is customers don't really know where all their data is or even where their sensitive data is. And that continues to be a large problem. That's why we have services like Macy, which are whose job is to find in S3 the data that you need to protect the most because it's because it's sensitive. Getting the least privilege has always been the, the goal when it comes, when it comes to data security. The problem is, is least privilege is really, really hard to, to achieve because there's so many different common nations of roles and accounts and org orgs. And, and so there, there's also another technology called access analyzer that we have that helps customers figure out like this is this the right, if are my intended authorizations, the authorizations I have, are they the ones that are intended for that user? And you have to continuously review that as a, as a means to make sure that you're getting as close to least privilege as you possibly can. >>Well, one of the, the luxuries of having you here on the cube keynote for this showcase is that you also have the internal view at AWS, but also you have the external view with customers. So I have to ask you, as you talk to customers, obviously there's a lot of trends. We're seeing more managed services in areas where there's skill gaps, but teams are also overloaded too. We're hearing stories about security teams, overwhelmed by the solutions that they have to deploy quickly and scale up quickly cost effectively the need for in instrumentation. Sometimes it's intrusive. Sometimes it agentless sensors, OT. I mean, it's getting crazy at re Mars. We saw a bunch of stuff there. This is a reality, the teams aspect of it. Can you share your experiences and observations on how companies are organizing, how they're thinking about team formation, how they're thinking about all these new things coming at them, new environments, new scale choices. What, what do you seeing on, on the customer side relative to security team? Yeah. And their role and relationship to the cloud and, and the technologies. >>Yeah, yeah. A absolutely it. And we have to remember at the end of the day on one end of the wire is a black hat on the other end of the wire is a white hat. And so you need people and, and people are a critical component of being able to defend in the context of security operations alert. Fatigue is absolutely a problem. The, the alerts, the number of alerts, the volume of alerts is, is overwhelming. And so you have to have a means to effectively triage them and get the ones into investigation that, that you think will be the most, the, the most significant going back to the risk equation, you found, you find those alerts and events that are, are the ones that, that could harm you. The most. You'll also one common theme is threat hunting. And the concept behind threat hunting is, is I don't actually wait for an alert I lean in and I'm proactive instead of reactive. >>So I find the system that I at least want the hacker in. I go to that system and I look for any anomalies. I look for anything that might make me think that there is a, that there is a hacker there or a compromise or some unattended consequence. And the reason you do that is because it reduces your dwell time, time between you get compromised to the time detect something, which is you, which might be, you know, months, because there wasn't an alert trigger. So that that's also a very important aspect for, for AWS and our security services. We have a strategy across all of the security services that we call end to end, or how do we move from APIs? Because they're all API driven and security buyers generally not most do not ha have like a development team, like their security operators and they want a solution. And so we're moving more from APIs to outcomes. So how do we stitch all the services together in a way so that the time, the time that an analyst, the SOC analyst spends or someone doing investigation or someone doing incident response is the, is the most important time, most valuable time. And in the process of stitching this all together and helping our customers with alert, fatigue, we'll be doing things that will use sort of inference and machine learning to help prioritize the greatest risk for our customers. >>That's a great, that's a great call out. And that brings up the point of you get the frontline, so to speak and back office, front office kind of approach here. The threats are out there. There's a lot of leaning in, which is a great point. I think that's a good, good comment and insight there. The question I have for you is that everyone's kind of always talks about that, but there's the, the, I won't say boring, the important compliance aspect of things, you know, this has become huge, right? So there's a lot of blocking and tackling that's needed behind the scenes on the compliance side, as well as prevention, right? So can you take us through in your mind how customers are looking at the best strategies for compliance and security, because there's a lot of work you gotta get done and you gotta lay out everything as you mentioned, but compliance specifically to report is also a big thing for >>This. Yeah. Yeah. Compliance is interesting. I suggest taking a security approach to compliance instead of a compliance approach to security. If you're compliant, you may not be secure, but if you're secure, you'll be compliant. And the, the really interesting thing about compliance also is that as soon as something like a, a, a category of control is required in, in some form of compliance, compliance regime, the effectiveness of that control is reduced because the threats go well, I'm gonna presume that they have this control. I'm gonna presume cuz they're compliant. And so now I'm gonna change my tactic to evade the control. So if you only are ever following compliance, you're gonna miss a whole set of tactics that threats have developed because they presume you're compliant and you have those controls in place. So you wanna make sure you have something that's outside of the outside of the realm of compliance, because that's the thing that will trip them up. That's the thing that they're not expecting that threats not expecting and that that's what we'll be able to detect them. >>Yeah. And it almost becomes one of those things where it's his fault, right? So, you know, finger pointing with compliance, you get complacent. I can see that. Can you give an example? Cause I think that's probably something that people are really gonna want to know more about because it's common sense. But can you give an example of security driving compliance? Is there >>Yeah, sure. So there's there they're used just as an example, like multifactor authentication was used everywhere that for, for banks in high risk transactions, in real high risk transactions. And then that like that was a security approach to compliance. Like we said, that's a, that's a high net worth individual. We're gonna give them a token and that's how they're gonna authenticate. And there was no, no, the F F I C didn't say at the time that there needed to be multifactor authentication. And then after a period of time, when account takeover was, was on the rise, the F F I C the federally financial Institute examiner's council, something like that said, we, you need to do multifactor authentication. Multifactor authentication was now on every account. And then the threat went down to, okay, well, we're gonna do man in the browser attacks after the user authenticates, which now is a new tactic in that tactic for those high net worth individuals that had multifactor didn't exist before became commonplace. Yeah. And so that, that, that's a, that's an example of sort of the full life cycle and the important lesson there is that security controls. They have a diminishing halflife of effectiveness. They, they need to be continuous and adaptive or else the value of them is gonna decrease over time. >>Yeah. And I think that's a great call up because agility and speed is a big factor when he's merging threats. It's not a stable, mature hacker market. They're evolving too. All right. Great stuff. I know your time's very valuable, John. I really appreciate you coming on the queue. A couple more questions for you. We have 10 amazing startups here in the, a AWS ecosystem, all private looking grade performance wise, they're all got the kind of the same vibe of they're kind of on something new. They're doing something new and clever and different than what was, what was kind of done 10 years ago. And this is where the cloud advantage is coming in cloud scale. You mentioned that some of those things, data, so you start to see new things emerge. How, how would you talk to CSOs or CXOs that are watching about how to evaluate startups like these they're, they're, they're somewhat, still small relative to some of the bigger players, but they've got unique solutions and they're doing things a little bit differently. How should some, how should CSOs and Steve evaluate them? How can startups work with the CSOs? What's your advice to both the buyer and the startup to, to bring their product to the market. And what's the best way to do that? >>Yeah. So the first thing is when you talk to a CSO, be respected, be respectful of their time like that. Like, they'll appreciate that. I remember when I was very, when I just just started, I went to talk to one of the CISOs as one of the five major banks and he sat me down and he said, and I tried to tell him what I had. And he was like son. And he went through his book and he had, he had 10 of every, one thing that I had. And I realized that, and I, I was grateful for him giving me an explanation. And I said to him, I said, look, I'm sorry. I wasted your time. I will not do that again. I apologize. I, if I can't bring any value, I won't come back. But if I think I can bring you something of value now that I know what I know, please, will you take the meeting? >>He was like, of course. And so be respectful of their time. They know what the problem is. They know what the threat is. You be, be specific about how you're different right now. There is so much confusion in the market about what you do. Like if you're really have something that's differentiated, be very, very specific about it. And don't be afraid of it, like lean into it and explain the value to that. And that, that, that would, would save a, a lot of time and a lot and make the meeting more valuable for the CSO >>And the CISOs. Are they evaluate these startups? How should they look at them? What are some kind of markers that you would say would be good, kind of things to look for size of the team reviews technology, or is it doesn't matter? It's more of a everyone's environment's different. What >>Would your, yeah. And, you know, for me, I, I always look first to the security value. Cause if there isn't security value, nothing else matters. So there's gotta be some security value. Then I tend to look at the management team, quite frankly, what are, what are the, what are their experiences and what, what do they know that that has led them to do something different that is driving security value. And then after that, for me, I tend to look to, is this someone that I can have a long term relationship with? Is this someone that I can, you know, if I have a problem and I call them, are they gonna, you know, do this? Or are they gonna say, yes, we're in, we're in this together, we'll figure it out. And then finally, if, if for AWS, you know, scale is important. So we like to look at, at scale in terms of, is this a solution that I can, that I can, that I can get to, to the scale that I needed at >>Awesome. Awesome. John Ramsey, vice president of security here on the cubes. Keynote. John, thank you for your time. I really appreciate, I know how busy you are with that for the next minute, or so share a little bit of what you're up to. What's on your plate. What are you thinking about as you go out to the marketplace, talk to customers what's on your agenda. What's your talk track, put a plug in for what you're up to. >>Yeah. So for, for the services I have, we, we are, we are absolutely moving. As I mentioned earlier, from APIs to outcomes, we're moving up the stack to be able to defend both containers, as well as, as serverless we're, we're moving out in terms of we wanna get visibility and signal, not just from what we see in AWS, but from other places to inform how do we defend AWS? And then also across, across the N cybersecurity framework in terms of we're doing a lot of, we, we have amazing detection capability and we have this infrastructure that we could respond, do like micro responses to be able to, to interdict the threat. And so me moving across the N cybersecurity framework from detection to respond. >>All right, thanks for your insight and your time sharing in this keynote. We've got great 10 great, amazing startups. Congratulations for all your success at AWS. You guys doing a great job, shared responsibility that the threats are out there. The landscape is changing. The scale's increasing more data tsunamis coming every day, more integration, more interconnected, it's getting more complex. So you guys are doing a lot of great work there. Thanks for your time. Really appreciate >>It. Thank you, John. >>Okay. This is the AWS startup showcase. Season two, episode four of the ongoing series covering the exciting startups coming out of the, a AWS ecosystem. This episode's about cyber security and I'm your host, John furrier. Thanks for watching.

>>In 2011, early Facebook employee and Cloudera co-founder Jeff Ocker famously said the best minds of my generation are thinking about how to get people to click on ads. And that sucks. Let's face it more than a decade later organizations continue to be frustrated with how difficult it is to get value from data and build a truly agile data driven enterprise. What does that even mean? You ask? Well, it means that everyone in the organization has the data they need when they need it. In a context that's relevant to advance the mission of an organization. Now that could mean cutting costs could mean increasing profits, driving productivity, saving lives, accelerating drug discovery, making better diagnoses, solving, supply chain problems, predicting weather disasters, simplifying processes, and thousands of other examples where data can completely transform people's lives beyond manipulating internet users to behave a certain way. We've heard the prognostications about the possibilities of data before and in fairness we've made progress, but the hard truth is the original promises of master data management, enterprise data, warehouses, data, Mars, data hubs, and yes, even data lakes were broken and left us wanting for more welcome to the data doesn't lie, or does it a series of conversations produced by the cube and made possible by Starburst data. >>I'm your host, Dave Lanta and joining me today are three industry experts. Justin Borgman is this co-founder and CEO of Starburst. Richard Jarvis is the CTO at EMI health and Theresa tongue is cloud first technologist at Accenture. Today we're gonna have a candid discussion that will expose the unfulfilled and yes, broken promises of a data past we'll expose data lies, big lies, little lies, white lies, and hidden truths. And we'll challenge, age old data conventions and bust some data myths. We're debating questions like is the demise of a single source of truth. Inevitable will the data warehouse ever have feature parody with the data lake or vice versa is the so-called modern data stack simply centralization in the cloud, AKA the old guards model in new cloud close. How can organizations rethink their data architectures and regimes to realize the true promises of data can and will and open ecosystem deliver on these promises in our lifetimes, we're spanning much of the Western world today. Richard is in the UK. Teresa is on the west coast and Justin is in Massachusetts with me. I'm in the cube studios about 30 miles outside of Boston folks. Welcome to the program. Thanks for coming on. Thanks for having us. Let's get right into it. You're very welcome. Now here's the first lie. The most effective data architecture is one that is centralized with a team of data specialists serving various lines of business. What do you think Justin? >>Yeah, definitely a lie. My first startup was a company called hit adapt, which was an early SQL engine for IDU that was acquired by Teradata. And when I got to Teradata, of course, Terada is the pioneer of that central enterprise data warehouse model. One of the things that I found fascinating was that not one of their customers had actually lived up to that vision of centralizing all of their data into one place. They all had data silos. They all had data in different systems. They had data on-prem data in the cloud. You know, those companies were acquiring other companies and inheriting their data architecture. So, you know, despite being the industry leader for 40 years, not one of their customers truly had everything in one place. So I think definitely history has proven that to be a lie. >>So Richard, from a practitioner's point of view, you know, what, what are your thoughts? I mean, there, there's a lot of pressure to cut cost, keep things centralized, you know, serve the business as best as possible from that standpoint. What, what is your experience, Joe? >>Yeah, I mean, I think I would echo Justin's experience really that we, as a business have grown up through acquisition, through storing data in different places sometimes to do information governance in different ways to store data in, in a platform that's close to data experts, people who really understand healthcare data from pharmacies or from, from doctors. And so, although if you were starting from a Greenfield site and you were building something brand new, you might be able to centralize all the data and all of the tooling and teams in one place. The reality is that that businesses just don't grow up like that. And, and it's just really impossible to get that academic perfection of, of storing everything in one place. >>Y you know, Theresa, I feel like Sarbanes Oxley kinda saved the data warehouse, you know? Right. But you actually did have to have a single version of the truth for certain financial data, but really for those, some of those other use cases, I, I mentioned, I, I do feel like the industry has kinda let us down. What's your take on this? Where does it make sense to have that sort of centralized approach versus where does it make sense to maybe decentralized? >>I, I think you gotta have centralized governance, right? So from the central team, for things like swans Oxley, for things like security, for certain very core data sets, having a centralized set of roles, responsibilities to really QA, right. To serve as a design authority for your entire data estate, just like you might with security, but how it's implemented has to be distributed. Otherwise you're not gonna be able to scale. Right? So being able to have different parts of the business really make the right data investments for their needs. And then ultimately you're gonna collaborate with your partners. So partners that are not within the company, right. External partners, we're gonna see a lot more data sharing and model creation. And so you're definitely going to be decentralized. >>So, you know, Justin, you guys last, geez, I think it was about a year ago, had a session on, on data mesh. It was a great program. You invited JAK, Dani, of course, she's the creator of the data mesh. And her one of our fundamental premises is that you've got this hyper specialized team that you've gotta go through. And if you want anything, but at the same time, these, these individuals actually become a bottleneck, even though they're some of the most talented people in the organization. So I guess question for you, Richard, how do you deal with that? Do you, do you organize so that there are a few sort of rock stars that, that, you know, build cubes and, and the like, and, and, and, or have you had any success in sort of decentralizing with, you know, your, your constituencies, that data model? >>Yeah. So, so we absolutely have got rockstar, data scientists and data guardians. If you like people who understand what it means to use this data, particularly as the data that we use at emos is very private it's healthcare information. And some of the, the rules and regulations around using the data are very complex and, and strict. So we have to have people who understand the usage of the data, then people who understand how to build models, how to process the data effectively. And you can think of them like consultants to the wider business, because a pharmacist might not understand how to structure a SQL query, but they do understand how they want to process medication information to improve patient lives. And so that becomes a, a consulting type experience from a, a set of rock stars to help a, a more decentralized business who needs to, to understand the data and to generate some valuable output. >>Justin, what do you say to a, to a customer or prospect that says, look, Justin, I'm gonna, I got a centralized team and that's the most cost effective way to serve the business. Otherwise I got, I got duplication. What do you say to that? >>Well, I, I would argue it's probably not the most cost effective and, and the reason being really twofold. I think, first of all, when you are deploying a enterprise data warehouse model, the, the data warehouse itself is very expensive, generally speaking. And so you're putting all of your most valuable data in the hands of one vendor who now has tremendous leverage over you, you know, for many, many years to come, I think that's the story of Oracle or Terra data or other proprietary database systems. But the other aspect I think is that the reality is those central data warehouse teams is as much as they are experts in the technology. They don't necessarily understand the data itself. And this is one of the core tenets of data mash that that jam writes about is this idea of the domain owners actually know the data the best. >>And so by, you know, not only acknowledging that data is generally decentralized and to your earlier point about, so Oxley, maybe saving the data warehouse, I would argue maybe GDPR and data sovereignty will destroy it because data has to be decentralized for, for those laws to be compliant. But I think the reality is, you know, the data mesh model basically says, data's decentralized, and we're gonna turn that into an asset rather than a liability. And we're gonna turn that into an asset by empowering the people that know the data, the best to participate in the process of, you know, curating and creating data products for, for consumption. So I think when you think about it, that way, you're going to get higher quality data and faster time to insight, which is ultimately going to drive more revenue for your business and reduce costs. So I think that that's the way I see the two, the two models comparing and con contrasting. >>So do you think the demise of the data warehouse is inevitable? I mean, I mean, you know, there Theresa you work with a lot of clients, they're not just gonna rip and replace their existing infrastructure. Maybe they're gonna build on top of it, but the, what does that mean? Does that mean the ed w just becomes, you know, less and less valuable over time, or it's maybe just isolated to specific use cases. What's your take on that? >>Listen, I still would love all my data within a data warehouse would love it. Mastered would love it owned by essential team. Right? I think that's still what I would love to have. That's just not the reality, right? The investment to actually migrate and keep that up to date. I would say it's a losing battle. Like we've been trying to do it for a long time. Nobody has the budgets and then data changes, right? There's gonna be a new technology. That's gonna emerge that we're gonna wanna tap into. There's gonna be not enough investment to bring all the legacy, but still very useful systems into that centralized view. So you keep the data warehouse. I think it's a very, very valuable, very high performance tool for what it's there for, but you could have this, you know, new mesh layer that still takes advantage of the things. I mentioned, the data products in the systems that are meaningful today and the data products that actually might span a number of systems. Maybe either those that either source systems, the domains that know it best, or the consumer based systems and products that need to be packaged in a way that be really meaningful for that end user, right? Each of those are useful for a different part of the business and making sure that the mesh actually allows you to lose all of them. >>So, Richard, let me ask you, you take, take Gemma's principles back to those. You got, you know, the domain ownership and, and, and data as product. Okay, great. Sounds good. But it creates what I would argue or two, you know, challenges self-serve infrastructure let's park that for a second. And then in your industry, one of the high, most regulated, most sensitive computational governance, how do you automate and ensure federated governance in that mesh model that Theresa was just talking about? >>Well, it absolutely depends on some of the tooling and processes that you put in place around those tools to be, to centralize the security and the governance of the data. And, and I think, although a data warehouse makes that very simple, cause it's a single tool, it's not impossible with some of the data mesh technologies that are available. And so what we've done at EMI is we have a single security layer that sits on top of our data mesh, which means that no matter which user is accessing, which data source, we go through a well audited well understood security layer. That means that we know exactly who's got access to which data field, which data tables. And then everything that they do is, is audited in a very kind of standard way, regardless of the underlying data storage technology. So for me, although storing the data in one place might not be possible understanding where your source of truth is and securing that in a common way is still a valuable approach and you can do it without having to bring all that data into a single bucket so that it's all in one place. >>And, and so having done that and investing quite heavily in making that possible has paid dividends in terms of giving wider access to the platform and ensuring that only data that's available under GDPR and other regulations is being used by, by the data users. >>Yeah. So Justin mean Democrat, we always talk about data democratization and you know, up until recently, they really haven't been line of sight as to how to get there. But do you have anything to add to this because you're essentially taking, you know, doing analytic queries and with data, that's all dispersed all over the, how are you seeing your customers handle this, this challenge? >>Yeah, I mean, I think data products is a really interesting aspect of the answer to that. It allows you to, again, leverage the data domain owners, people know the data, the best to, to create, you know, data as a product ultimately to be consumed. And we try to represent that in our product as effectively, almost eCommerce, like experience where you go and discover and look for the data products that have been created in your organization. And then you can start to consume them as, as you'd like. And so really trying to build on that notion of, you know, data democratization and self-service, and making it very easy to discover and, and start to use with whatever BI tool you, you may like, or even just running, you know, SQL queries yourself. >>Okay. G guys grab a sip of water. After the short break, we'll be back to debate whether proprietary or open platforms are the best path to the future of data excellence. Keep it right there.

>>Okay, welcome back everyone. Cube's coverage here in Boston, Massachusetts, AWS reinforced 22, the security conference. It's ADOS big security conference. Of course, the cubes here, all the reinvent res re Mars reinforce. We cover 'em all now and the summits. I'm John. Very my host, Dave ante have IDC weighing in here with their analysis. We've got some great guests here, Jay Brisbane, research VP at IDC and Philip who research managed for cloud security. Gentlemen, thanks for coming on. Thank you. Appreciate it. Great >>To, to be here. I appreciate the got the full >>Circle, right? Just, security's more interesting >>Than storage. Isn't it? >>Dave, Dave and Jay worked together. This is a, a great segment. I'm psyched that you guys are here. We had Crawford and Matt Eastwood on at HPE discover a while back and really the, the, the data you guys are getting and the insights are fantastic. So congratulations to IDC. You guys doing great work. We appreciate your time. I wanna get your reaction to the event and the keynotes. AWS has got some posture and they're very aggressive on some tones. Some things that they didn't, we didn't hear. What's your reaction to the keynote, share your, your assessment. >>So, you know, I managed two different research services at IDC right now. They are both cloud security and identity and, and digital security. Right. And what was really interesting is the intersection between the two this morning, because every one of those speakers that came on had something to say about identity or least privileged access, or, you know, enable MFA, or make sure that you, you know, control who gets access to what and deny explicitly. Right? And it's always been a challenge a little bit in the identity world because a lot of people don't use MFA. And in RSA, that was another big theme at the RSA conference, right? MFA everywhere. Why don't they use it because it introduces friction and all of a sudden people can't get their jobs done. Right. And the whole point of a network is letting people on to get that data they want to get to. So that was kind of interesting, but, you know, as we have in the industry, this shared responsibility model for cloud computing, we've got shared responsibility for between Philip and I, I have done in the ke past more security of the cloud and Philip is more security in the cloud, >>So yeah. And it's, and now with cloud operation, super cloud, as we call it, you have on premises, private cloud coming back, or hasn't really gone anywhere, all that on premises, cloud operations, public cloud, and now edge exploding with new requirements. Yeah. It's really an ops challenge right now. Not so much dev. So the sick and op side is hot right now. >>Yeah. Well, we've made this move from monolithic to microservices based applications. And so during the keynote this morning, the announcement around the guard duty malware protection component, and that being built into the pricing of current guard duty, I thought was, was really key. And there was also a lot of talk about partnering in security certifications. Yeah. Which is also so very important. So we're seeing this move towards filling in that talent gap, which I think we're all aware of in the security industry. >>So Jake square, the circle for me. So Kirk, Coel talked about Amazon AWS identity, where does AWS leave off and, and companies like Okta or ping identity or crock pickup, how are they working together? Does it just create more confusion and more tools for customers? We, we have, we know the over word overused word of seamless. Yeah. Yeah. It's never seamless. So how should we think about that? >>So, you know, identity has been around for 35 years or something like that started with the mainframes and all that. And if you understand the history of it, you make more sense to the current market. You have to know where people came from and the baggage they're carrying, cuz they're still carrying a lot of that baggage. Now, when it comes to the cloud service providers, they're more an accommodation from the identity standpoint, let's make it easy inside of AWS to let you single sign on to anything in the cloud that they have. Right. Let's also introduce an additional MFA capability to keep people safer whenever we can and, you know, provide people the tools to, to get into those applications somewhat easily, right. While leveraging identities that may live somewhere else. So, you know, there's a whole lot of the world that is still active directory centric, right? There's another portion of companies that were born in the cloud that were able to jump on things like Okta and some of the other providers of these universal identities in the cloud. So, you know, like I said, you, if you understand where people came from in the beginning, you start to, to say, yeah, this makes sense. >>It's, it's interesting. You talk about mainframe. I, I always think about rack F you know, and I say, okay, who did what, when, where, yeah. And you hear about a lot of those themes. What, so what's the best practice for MFA? That's, that's non SMS based. Is it, you gotta wear something around your neck, is it to have sort of a third party authenticator? What are people doing that is that, that, that you guys would recommend? >>Yeah. One quick comment about adoption of MFA. You know, if you ask different suppliers, what percent of your base that does SSO also does MFA one of the biggest suppliers out there Microsoft will tell you it's under 25%. That's pretty shocking. Right? All the messaging that's come out about it. So another big player in the market was called duo. Cisco bought them. Yep. Right. And because they provide networks, a lot of people buy their MFA. They have probably the most prevalent type of MFA it's called push. Right. And push can be, you know, a red X and a green check mark to your phone. It can be a QR code, you know, somewhere, it can be an email push as well. So that is the next easiest thing to adopt after SMS. And as you know, SMS has been denigrated by N and others saying, you know, it's susceptible to man and middle attacks. >>It's built on a telephony protocol called SS seven. Yep. You know, predates anything. There's no certification, either side. The other real dynamic and identity is the whole adoption of PKI infrastructure. As you know, certificates are used for all kinds of things, network sessions, data encryption, well identity increasingly, and a lot of the, you know, consumers and especially the work from anywhere, people these days have access through smart devices. Right. And what you can do there is you can have an agent on that smart device, generate your private key and then push out a public key. And so the private key never leaves your device. That's one of the most secure ways to, so if your >>SIM card gets hacked, you're not gonna be as at vulnerable >>Or as vulnerable. Well, the SIM card is another, you know, challenge associated with the, the older waste. But yeah. Yeah. >>So what do you guys think about the open source connection and, and they, they mentioned it up top don't bolt on security implying shift left, which is embedding it in like sneak companies, like sneak do that, right. Container oriented, a lot of Kubernetes kind of cloud native services. So I wanna get your reaction to that. And then also this reasoning angle, they brought up kind of a higher level AI reasoning decisions. So open source and this notion of AI reasoning >>Automation. Yeah. And, and you see more open source discussion happening, right. So you, you know, you have your building maintaining and vetting of the upstream open source code, which is critical. And so I think AWS talking about that today, they're certainly hitting on a nerve as, you know, open source continues to proliferate around the automated reasoning. I think that makes sense. You know, you want to provide guiderails and you want to provide roadmaps and you wanna have sort of that guidance as to okay. What's the, you know, a correlation analysis of different tools and products. And so I think that's gonna go over really well. >>Yeah. One of the other, you know, key points of what open source is, everybody's in a multi-cloud world, right? Yeah. And so they're worried about vendor lockin, they want an open source code base so that they don't experience that. >>Yeah. And they can move the code around and make sure it works well on each system. Dave and I were just talking about some of the dynamics around data control planes. So yeah. They mentioned encrypt everything, which is great. And I message, by the way, I love that one, but oh. And he mentioned data at rest. I'm like, what about data in flight? Didn't hear that one. So one of the things we're seeing with super cloud, and now multi-cloud kind of, as destinations of that, is that in digital transformation, customers are leaning into owning their data flows. >>Yeah. >>Independent of say the control plane aspects of what could come in. This is huge implications for security, where sharing data is huge. Even Schmidt on Steve said we have billions and billions of things happening that we see things that no one else else sees. So that implies, they're >>Sharing quad trillion, >>Trillion, 15 zeros trillion. Yeah. 15 >>Zeros, 15 zeros. Yeah. >>So that implies, they're sharing that or using that, pushing that into something. So sharing's huge with cyber security. So that implies open data, data flows. What do, how do you guys see this evolving? I know it's kind of emerging, but it's becoming a, a nuanced point that's critical to the architecture. >>Well, I, yeah, I think another way to look at that is the sharing of intelligence and some of the recent directives, you know, from the executive branch, making it easier for private companies to share data and intelligence, which I think strengthens the cyber community overall, >>Depending upon the supplier. Right? Yeah. It's either an aggregate level of intelligence that has been, you know, anonymized or it's specific intelligence for your environment that, you know, everybody's got a threat feed, maybe two or three, right. Yeah. But back to the encryption point, I mean, I was working for an encryption startup for a little while. Right after I left IBM. And the thing is that people are scared of it. Right. They're scared of key management and rotation. And so when you provide, >>Because they might lose the key. >>Exactly. Yeah. It's like shooting yourself in the foot. Right. So that's when you have things like, you know, KMS services from Amazon and stuff, they really help out a lot and help people understand, okay, I'm not alone in this. >>Yeah. Crypto >>Owners, they call that hybrid, the hybrid key, they call the, what they call the, today. They call it the hybrid. >>What was that? The management service. Yeah. The hybrid. So hybrid HSM, correct. >>Yeah. What is that? What is that? I didn't, I didn't get that. I didn't understand what he meant by the hybrid post hybrid, post quantum key agreement. Right. That still notes >>Hybrid, post quantum key exchange, >>You know, AWS never made a product name that didn't have four words in it, >>But he did, but he did reference the, the new N algos. And I think I inferred that they were quantum proof or the claim it be. Yeah. And AWS was testing those. Correct. >>Yeah. >>So that was kind of interesting, but I wanna come back to identity for a second. Okay. So, so this idea of bringing traditional IAM and, and privilege access management together, is that a pipe dream, is that something that is actually gonna happen? What's the timeframe, what's your take on that? >>So, you know, there are aspects of privilege in every sort of identity back when, you know, it was only the back office that used computers for calculations, right? Then you were able to control how many people had access. There were two types of users, admins, and users, right? These days, everybody has some aspect of, >>It's a real spectrum, really >>Granular. You got the, you know, the C suite, the finance people, the DevOps, people, you know, even partners and whatever, they all need some sort of privileged access. And the, the term you hear so much is least privileged access. Right? Shut it down, control it. So, you know, in some of my research, I've been saying that vendors who are in the Pam space privilege access management space will probably be growing their suites, playing a bigger role, building out a stack because they have, you know, the, the expertise and the, and the perspective that says we should control this better. How do we do that? Right. And we've been seeing that recently, >>Is that a combination of old kind of antiquated systems meets for proprietary hyperscale or kind of like build your own? Cause I mean, Amazon, these guys, they Facebook, they all build their own stuff. >>Yes. They >>Do enterprises buy services from general purpose identity management systems. >>So as we were talking about, you know, knowing the past and whatever privileged access management used to be about compliance reporting. Yeah. Right. Just making sure that I knew who accessed what and could prove it. So I didn't fail in art. It wasn't >>A critical infrastructure item. >>No. And now these days, what it's transitioning into is much more risk management. Okay. I know what our risk is. I'm ahead of it. And the other thing in the Pam space was really session monitor. Right. Everybody wanted to watch every keystroke, every screen's scrape, all that kind of stuff. A lot of the new privilege access Mon management doesn't really require that it's nice to have feature. You kind of need it on the list, but is anybody really gonna implement it? That's the question. Right. And then, you know, if, if you do all that session monitor, does anybody ever go back and look at it? There's only so many hours in the day. >>How about passwordless access? You know? Right. I've heard people talk about that. Yeah. I mean, that's as a user, I can't wait, but >>It's somewhere we want to all go. Yeah. Right. We all want identity security to just disappear and be recognized when we log in. So the, the thing with password list is there's always a password somewhere and it's usually part of a registration, you know, action. I'm gonna register my device with a username password. And then beyond that, I can use my biometrics. Right. I wanna register my device and get a private key that I can put in my enclave. And I'll use that in the future. Maybe it's gotta touch ID. Maybe it doesn't. Right. So even though there's been a lot of progress made, it's not quote unquote, truly passwordless, there's a group industry standards group called Fido. Right. Which is fast identity online. And what they realized was these whole registration passwords. That's really a single point of failure. Cuz if I can't recover my device, I'm in trouble. Yeah. So they just did a, a new extension to sort of what they were doing, which provides you with much more of a, like an iCloud vault, right. That you can register that device in and other devices associated with that same iPad that you can >>Get you to it. If you >>Have to. Exactly. I had >>Another have all over the place here, but I, I want to ask about ransomware. It may not be your wheelhouse. Yeah. But back in the day, Jay, remember you used to cover tape. All the, all the backup guys now are talking about ransomware. AWS mentioned it today and they showed a bunch of best practices and things you can do air gaps. Wasn't one, one of 'em. Right. I was really surprised cuz that's all, every anybody ever talks about is air gaps. And a lot of times that air gaps that air gap could be a guess to the cloud. I guess I'm not sure. What are you guys seeing on ransomware >>Apps? You know, we've done a lot of great research around ransomware as a service and ransomware and, and you know, we just had some data come out recently that I think in terms of spending and, and spend and in as a result of the Ukraine, Russia war, that ransomware assessments rate number one. And so it's something that we encourage, you know, when we talk to vendors and in our services, in our publications that we write about taking advantage of those free strategic ransomware assessments, vulnerability assessments, right. As well, and then security and training ranked very highly as well. So we wanna make sure that all of these areas are being funded well to try and stay ahead of the curve. >>Yeah. I was surprised that not the air gaps on the list, that's all everybody >>Talks about. Well, you know, the, the old model for air gaping in the, the land days, the Noel days, you took your tapes home and put 'em in the sock drawer. >>Well, it's a form of air gap security and no one's gonna go there >>Clean. And then the internet came around >>Guys. Final question. I want to ask you guys, we kind zoom out. Great, great commentary by the way. Appreciate it. As the, we've seen this in many markets, a collection of tools emerge and then there's it's tool sprawl. Oh yeah. Right? Yeah. So cyber we're seeing trend now where Mon goes up on stage of all the E probably other vendors doing the same thing where they're organizing a platform on top of AWS to be this super platform. If you super cloud ability by building more platform thing. So we're saying there's a platform war going on, cuz customers don't want the complexity. Yeah. I got a tool, but it's actually making it more complex if I buy the other tool. So the tool sprawl becomes a problem. How do you guys see this? Do you guys see this platform emerging? I mean, tools won't go away, but they have to be >>Easier. Yeah. We do see a, a consolidation of functionality and services. And we've been seeing that, I think through a 20, 20 flat security survey that we released, that that was definitely a trend. And you know, that certainly happened for many companies over the last six to 24 months, I would say. And then platformization absolutely is something we talk 'em right. About all the time. So >>More M and a couple of years ago, I called the, the Amazon tool set in rector set. Yeah. Because it really required assembly. Yeah. And you see the emphasis on training here too, right? Yeah. You definitely need to go to AWS university to be competent. It >>Wasn't Lego blocks yet. No, it was a rector set. Very good distinction rules, you know, and, and you lose a few. It's >>True. Still too many tools. Right. You see, we need more consolidation. That's getting interesting because a lot of these companies have runway and you look, you look at sale point, its stock prices held up cuz of the Toma Bravo acquisition, but all the rest of the cyber stocks have been crushed. Yeah. You know, especially the high flyers, like a Senti, a one or a crowd strike, but yeah, just still M and a opportunity >>Itself. So platform wars. Okay. Final thoughts. What do you thinks happening next? What's what's your outlook for the, the next year or so? >>So in the, in the identity space, I'll talk about Phillip can cover cloud force. You know, it really is more consolidation and more adoption of things that are beyond simple SSO, right. It was, you know, just getting on the systems and now we really need to control what you're able to get to and who you are and do it as transparently as we possibly can because otherwise, you know, people are gonna lose productivity, right. They're not gonna be able to get to what they want. And that's what causes the C-suite to say, wait a minute, you know, DevOps, they want to update the product every day. Right. Make it better. Can they do that? Or did security get in the way people every once in a while I'll call security, the department of no, right? Yeah. Well, >>Yeah. They did it on stage. Yeah. They wanna be the department of yes, >>Exactly. And the department that creates additional value. If you look at what's going on with B to C or C IAM, consumer identity, that is all about opening up new direct channels and treating people like, you know, they're old friends, right. Not like you don't know 'em you have to challenge >>'em we always say you wanna be in the boat together. It sinks or not. Yeah. Right. Exactly. >>Phillip, >>Okay. What's your take? What's your outlook for the year? >>Yeah. I think, you know, something that we've been seeing as consolidation and integration, and so, you know, companies looking at from built time to run time investing in shift left infrastructure is code. And then also in the runtime detection makes perfect sense to have both the agent and agentless so that you're covering any of the gaps that might exist. >>Awesome. Jerry, Phillip, thanks for coming on the queue with IDC and sharing >>Your oh our pleasure perspective. >>Commentary, have any insights and outlook. Appreciate it. You bet. Thank you. Okay. We've got the great direction here from IDC analyst here on the queue. I'm John for a Dave, we're back more after this shirt break.

>>Hello, everyone. Welcome to the Cube's live coverage here in Boston, Massachusetts for AWS reinforce 2022. I'm John fur, host of the cube with Dave. Valante my co-host for breaking analysis, famous podcast, Dave, great to see you. Um, Beck in Boston, 2010, we started >>The queue. It all started right here in this building. John, >>12 years ago, we started here, but here, you know, just 12 years, it just seems like a marathon with the queue. Over the years, we've seen many ways. You call yourself a historian, which you are. We are both now, historians security is doing over. And we said in 2013 is security to do where we asked pat GSK. Now the CEO of Intel prior to that, he was the CEO of VMware. This is the security show fors. It's called the reinforce. They have reinvent, which is their big show. Now they have these, what they call reshow, re Mars, machine learning, automation, um, robotics and space. And then they got reinforced, which is security. It's all about security in the cloud. So great show. Lot of talk about the keynotes were, um, pretty, I wouldn't say generic on one hand, but specific in the other clear AWS posture, we were both watching. What's your take? >>Well, John, actually looking back to may of 2010, when we started the cube at EMC world, and that was the beginning of this massive boom run, uh, which, you know, finally, we're starting to see some, some cracks of the armor. Of course, we're threats of recession. We're in a recession, most likely, uh, in inflationary pressures, interest rate hikes. And so, you know, finally the tech market has chilled out a little bit and you have this case before we get into the security piece of is the glass half full or half empty. So budgets coming into this year, it was expected. They would grow at a very robust eight point half percent CIOs have tuned that down, but it's still pretty strong at around 6%. And one of the areas that they really have no choice, but to focus on is security. They moved everything into the cloud or a lot of stuff into the cloud. >>They had to deal with remote work and that created a lot of security vulnerabilities. And they're still trying to figure that out and plug the holes with the lack of talent that they have. So it's interesting re the first reinforc that we did, which was also here in 2019, Steven Schmidt, who at the time was chief information security officer at Amazon web services said the state of cloud security is really strong. All this narrative, like the pat Gelsinger narrative securities, a do over, which you just mentioned, security is broken. It doesn't help the industry. The state of cloud security is very strong. If you follow the prescription. Well, see, now Steven Schmidt, as you know, is now chief security officer at Amazon. So we followed >>Jesse all Amazon, not just AWS. So >>He followed Jesse over and I asked him, well, why no, I, and they said, well, he's responsible now for physical security. Presumably the warehouses I'm like, well, wait a minute. What about the data centers? Who's responsible for that? So it's kind of funny, CJ. Moses is now the CSO at AWS and you know, these events are, are good. They're growing. And it's all about best practices, how to apply the practices. A lot of recommendations from, from AWS, a lot of tooling and really an ecosystem because let's face it. Amazon doesn't have the breadth and depth of tools to do it alone. >>And also the attendance is interesting, cuz we are just in New York city for the, uh, ado summit, 19,000 people, massive numbers, certainly in the pandemic. That's probably one of the top end shows and it was a summit. This is a different audience. It's security. It's really nerdy. You got OT, you got cloud. You've got on-prem. So now you have cloud operations. We're calling super cloud. Of course we're having our inaugural pilot event on August 9th, check it out. We're called super cloud, go to the cube.net to check it out. But this is the super cloud model evolving with security. And what you're hearing today, Dave, I wanna get your reaction to this is things like we've got billions of observational points. We're certainly there's no perimeter, right? So the perimeter's dead. The new perimeter, if you will, is every transaction at scale. So you have to have a new model. So security posture needs to be rethought. They actually said that directly on the keynote. So security, although numbers aren't as big as last week or two weeks ago in New York still relevant. So alright. There's sessions here. There's networking. Very interesting demographic, long hair. Lot of >>T-shirts >>No lot of, not a lot of nerds doing to build out things over there. So, so I gotta ask you, what's your reaction to this scale as the new advantage? Is that a tailwind or a headwind? What's your read? >>Well, it is amazing. I mean he actually, Steven Schmidt talked about quadrillions of events every month, quadrillions 15 zeros. What surprised me, John. So they, they, Amazon talks about five areas, but by the, by the way, at the event, they got five tracks in 125 sessions, data protection and privacy, GRC governance, risk and compliance, identity network security and threat detection. I was really surprised given the focus on developers, they didn't call out container security. I would've thought that would be sort of a separate area of focus, but to your point about scale, it's true. Amazon has a scale where they'll see events every day or every month that you might not see in a generation if you just kind of running your own data center. So I do think that's, that's, that's, that's a, a, a, a valid statement having said that Amazon's got a limited capability in terms of security. That's why they have to rely on the ecosystem. Now it's all about APIs connecting in and APIs are one of the biggest security vulnerability. So that's kind of, I, I I'm having trouble squaring that circle. >>Well, they did just to come up, bring back to the whole open source and software. They did say they did make a measurement was store, but at the beginning, Schmidt did say that, you know, besides scale being an advantage for Amazon with a quadri in 15 zeros, don't bolt on security. So that's a classic old school. We've heard that before, right. But he said specifically, weave in security in the dev cycles. And the C I C D pipeline that is, that basically means shift left. So sneak is here, uh, company we've covered. Um, and they, their whole thing is shift left. That implies Docker containers that implies Kubernetes. Um, but this is not a cloud native show per se. It's much more crypto crypto. You heard about, you know, the, uh, encrypt everything message on the keynote. You heard, um, about reasoning, quantum, quantum >>Skating to the puck. >>Yeah. So yeah, so, you know, although the middleman is logged for J heard that little little mention, I love the quote from Lewis Hamilton that they put up on stage CJ, Moses said, team behind the scenes make it happen. So a big emphasis on teamwork, big emphasis on don't bolt on security, have it in the beginning. We've heard that before a lot of threat modeling discussions, uh, and then really this, you know, the news around the cloud audit academy. So clearly skills gap, more threats, more use cases happening than ever before. >>Yeah. And you know, to your point about, you know, the teamwork, I think the problem that CISOs have is they just don't have the talent to that. AWS has. So they have a real difficulty applying that talent. And so but's saying, well, join us at these shows. We'll kind of show you how to do it, how we do it internally. And again, I think when you look out on this ecosystem, there's still like thousands and thousands of tools that practitioners have to apply every time. There's a tool, there's a separate set of skills to really understand that tool, even within AWS's portfolio. So this notion of a shared responsibility model, Amazon takes care of, you know, securing for instance, the physical nature of S3 you're responsible for secure, make sure you're the, the S3 bucket doesn't have public access. So that shared responsibility model is still very important. And I think practitioners still struggling with all this complexity in this matrix of tools. >>So they had the layered defense. So, so just a review opening keynote with Steve Schmidt, the new CSO, he talked about weaving insecurity in the dev cycles shift left, which is the, I don't bolt it on keep in the beginning. Uh, the lessons learned, he talked a lot about over permissive creates chaos, um, and that you gotta really look at who has access to what and why big learnings there. And he brought up the use cases. The more use cases are coming on than ever before. Um, layered defense strategy was his core theme, Dave. And that was interesting. And he also said specifically, no, don't rely on single security control, use multiple layers, stronger together. Be it it from the beginning, basically that was the whole ethos, the posture, he laid that down >>And he had a great quote on that. He said, I'm sorry to interrupt single controls. And binary states will fail guaranteed. >>Yeah, that's a guarantee that was basically like, that's his, that's not a best practice. That's a mandate. <laugh> um, and then CJ, Moses, who was his deputy in the past now takes over a CSO, um, ownership across teams, ransomware mitigation, air gaping, all that kind of in the weeds kind of security stuff. You want to check the boxes on. And I thought he did a good job. Right. And he did the news. He's the new CISO. Okay. Then you had lean is smart from Mongo DB. Come on. Yeah. Um, she was interesting. I liked her talk, obviously. Mongo is one of the ecosystem partners headlining game. How do you read into that? >>Well, I, I I'm, its really interesting. Right? You didn't see snowflake up there. Right? You see data breaks up there. You had Mongo up there and I'm curious is her and she's coming on the cube tomorrow is her primary role sort of securing Mongo internally? Is it, is it securing the Mongo that's running across clouds. She's obviously here talking about AWS. So what I make of it is, you know, that's, it's a really critical partner. That's driving a lot of business for AWS, but at the same time it's data, they talked about data security being one of the key areas that you have to worry about and that's, you know what Mongo does. So I'm really excited. I talked to her >>Tomorrow. I, I did like her mention a big idea, a cube alumni, yeah. Company. They were part of our, um, season one of our eight of us startup showcase, check out AWS startups.com. If you're watching this, we've been doing now, we're in season two, we're featuring the fastest growing hottest startups in the ecosystem. Not the big players, that's ISVs more of the startups. They were mentioned. They have a great product. So I like to mention a big ID. Um, security hub mentioned a config. They're clearly a big customer and they have user base, a lot of E C, two and storage going on. People are building on Mongo so I can see why they're in there. The question I want to ask you is, is Mongo's new stuff in line with all the upgrades in the Silicon. So you got graviton, which has got great stuff. Um, great performance. Do you see that, that being a key part of things >>Well, specifically graviton. So I I'll tell you this. I'll tell you what I know when you look at like snowflake, for instance, is optimizing for graviton. For certain workloads, they actually talked about it on their earnings call, how it's lowered the cost for customers and actually hurt their revenue. You know, they still had great revenue, but it hurt their revenue. My sources indicate to me that that, that Mongo is not getting as much outta graviton two, but they're waiting for graviton three. Now they don't want to make that widely known because they don't wanna dis AWS. But it's, it's probably because Mongo's more focused on analytics. But so to me, graviton is the future. It's lower cost. >>Yeah. Nobody turns off the database. >>Nobody turns off the database. >><laugh>, it's always cranking C two cycles. You >>Know the other thing I wanted to bring, bring up, I thought we'd hear, hear more about ransomware. We heard a little bit of from Kirk Coel and he, and he talked about all these things you could do to mitigate ransomware. He didn't talk about air gaps and that's all you hear is how air gap. David Flo talks about this all the time. You must have air gaps. If you wanna, you know, cover yourself against ransomware. And they didn't even mention that. Now, maybe we'll hear that from the ecosystem. That was kind of surprising. Then I, I saw you made a note in our shared doc about encryption, cuz I think all the talk here is encryption at rest. What about data in motion? >>Well, this, this is the last guy that came on the keynote. He brought up encryption, Kurt, uh, Goel, which I love by the way he's VP of platform. I like his mojo. He's got the long hair >>And he's >>Geeking out swagger, but I, he hit on some really cool stuff. This idea of the reasoning, right? He automated reasoning is little pet project that is like killer AI. That's next generation. Next level >>Stuff. Explain that. >>So machine learning does all kinds of things, you know, goes to sit pattern, supervise, unsupervised automate stuff, but true reasoning. Like no one connecting the dots with software. That's like true AI, right? That's really hard. Like in word association, knowing how things are connected, looking at pattern and deducing things. So you predictive analytics, we all know comes from great machine learning. But when you start getting into deduction, when you say, Hey, that EC two cluster never should be on the same VPC, is this, this one? Why is this packet trying to go there? You can see patterns beyond normal observation space. So if you have a large observation space like AWS, you can really put some killer computer science technology on this. And that's where this reasoning is. It's next level stuff you don't hear about it because nobody does it. Yes. I mean, Google does it with metadata. There's meta meta reasoning. Um, we've been, I've been watching this for over two decades now. It's it's a part of AI that no one's tapped and if they get it right, this is gonna be a killer part of the automation. So >>He talked about this, basically it being advanced math that gets you to provable security, like you gave an example. Another example I gave is, is this S3 bucket open to the public is a, at that access UN restricted or unrestricted, can anyone access my KMS keys? So, and you can prove, yeah. The answer to that question using advanced math and automated reasoning. Yeah, exactly. That's a huge leap because you used to be use math, but you didn't have the data, the observation space and the compute power to be able to do it in near real time or real time. >>It's like, it's like when someone, if in the physical world real life in real life, you say, Hey, that person doesn't belong here. Or you, you can look at something saying that doesn't fit <laugh> >>Yeah. Yeah. >>So you go, okay, you observe it and you, you take measures on it or you query that person and say, why you here? Oh, okay. You're here. It doesn't fit. Right. Think about the way on the right clothes, the right look, whatever you kind of have that data. That's deducing that and getting that information. That's what reasoning is. It's it's really a killer level. And you know, there's encrypt, everything has to be data. Lin has to be data in at movement at rest is one thing, but you gotta get data in flight. Dave, this is a huge problem. And making that work is a key >>Issue. The other thing that Kirk Coel talked about was, was quantum, uh, quantum proof algorithms, because basically he put up a quote, you're a hockey guy, Wayne Greski. He said the greatest hockey player ever. Do you agree? I do agree. Okay, great. >>Bobby or, and Wayne Greski. >>Yeah, but okay, so we'll give the nada Greski, but I always skate to the where the puck is gonna be not to where it's been. And basically his point was where skating to where quantum is going, because quantum, it brings risks to basically blow away all the existing crypto cryptographic algorithms. I, I, my understanding is N just came up with new algorithms. I wasn't clear if those were supposed to be quantum proof, but I think they are, and AWS is testing them. And AWS is coming out with, you know, some test to see if quantum can break these new algos. So that's huge. The question is interoperability. Yeah. How is it gonna interact with all the existing algorithms and all the tools that are out there today? So I think we're a long way off from solving that problem. >>Well, that was one of Kurt's big point. You talking about quantum resistant cryptography and they introduce hybrid post quantum key agreements. That means KMS cert certification, cert manager and manager all can manage the keys. This was something that's gives more flexibility on, on, on that quantum resistance argument. I gotta dig into it. I really don't know how it works, what he meant by that in terms of what does that hybrid actually mean? I think what it means is multi mode and uh, key management, but we'll see. >>So I come back to the ho the macro for a second. We've got consumer spending under pressure. Walmart just announced, not great earning. Shouldn't be a surprise to anybody. We have Amazon meta and alphabet announcing this weekend. I think Microsoft. Yep. So everybody's on edge, you know, is this gonna ripple through now? The flip side of that is BEC because the economy yeah. Is, is maybe not in, not such great shape. People are saying maybe the fed is not gonna raise after September. Yeah. So that's, so that's why we come back to this half full half empty. How does that relate to cyber security? Well, people are prioritizing cybersecurity, but it's not an unlimited budget. So they may have to steal from other places. >>It's a double whammy. Dave, it's a double whammy on the spend side and also the macroeconomic. So, okay. We're gonna have a, a recession that's predicted the issue >>On, so that's bad on the one hand, but it's good from a standpoint of not raising interest rates, >>It's one of the double whammy. It was one, it's one of the double whammy and we're talking about here, but as we sit on the cube two weeks ago at <inaudible> summit in New York, and we did at re Mars, this is the first recession where the cloud computing hyperscale is, are pumping full cylinder, all cylinders. So there's a new economic engine called cloud computing that's in place. So unlike data center purchase in the past, that was CapEx. When, when spending was hit, they pause was a complete shutdown. Then a reboot cloud computer. You can pause spending for a little bit, make, might make the cycle longer in sales, but it's gonna be quickly fast turned on. So, so turning off spending with cloud is not that hard to do. You can hit pause and like check things out and then turn it back on again. So that's just general cloud economics with security though. I don't see the spending slowing down. Maybe the sales cycles might go longer, but there's no spending slow down in my mind that I see. And if there's any pause, it's more of refactoring, whether it's the crypto stuff or new things that Amazon has. >>So, so that's interesting. So a couple things there. I do think you're seeing a slight slow down in the, the, the ex the velocity of the spend. When you look at the leaders in spending velocity in ETR data, CrowdStrike, Okta, Zscaler, Palo Alto networks, they're all showing a slight deceleration in spending momentum, but still highly elevated. Yeah. Okay. So, so that's a, I think now to your other point, really interesting. What you're saying is cloud spending is discretionary. That's one of the advantages. I can dial it down, but track me if I'm wrong. But most of the cloud spending is with reserved instances. So ultimately you're buying those reserved instances and you have to spend over a period of time. So they're ultimately AWS is gonna see that revenue. They just might not see it for this one quarter. As people pull back a little bit, right. >>It might lag a little bit. So it might, you might not see it for a quarter or two, so it's impact, but it's not as severe. So the dialing up, that's a key indicator get, I think I'm gonna watch that because that's gonna be something that we've never seen before. So what's that reserve now the wild card and all this and the dark horse new services. So there's other services besides the classic AC two, but security and others. There's new things coming out. So to me, this is absolutely why we've been saying super cloud is a thing because what's going on right now in security and cloud native is there's net new functionality that needs to be in place to handle multiple clouds, multiple abstraction layers, and to do all these super cloudlike capabilities like Mike MongoDB, like these vendors, they need to up their gain. And that we're gonna see new cloud native services that haven't exist. Yeah. I'll use some hatchy Corp here. I'll use something over here. I got some VMware, I got this, but there's gaps. Dave, there'll be gaps that are gonna emerge. And I think that's gonna be a huge wild >>Cup. And now I wanna bring something up on the super cloud event. So you think about the layers I, as, uh, PAs and, and SAS, and we see super cloud permeating, all those somebody ask you, well, because we have Intuit coming on. Yep. If somebody asks, why Intuit in super cloud, here's why. So we talked about cloud being discretionary. You can dial it down. We saw that with snowflake sort of Mongo, you know, similarly you can, if you want dial it down, although transaction databases are to do, but SAS, the SAS model is you pay for it every month. Okay? So I've, I've contended that the SAS model is not customer friendly. It's not cloudlike and it's broken for customers. And I think it's in this decade, it's gonna get fixed. And people are gonna say, look, we're gonna move SAS into a consumption model. That's more customer friendly. And that's something that we're >>Gonna explore in the super cloud event. Yeah. And one more thing too, on the spend, the other wild card is okay. If we believe super cloud, which we just explained, um, if you don't come to the August 9th event, watch the debate happen. But as the spending gets paused, the only reason why spending will be paused in security is the replatforming of moving from tools to platforms. So one of the indicators that we're seeing with super cloud is a flight to best of breeds on platforms, meaning hyperscale. So on Amazon web services, there's a best of breed set of services from AWS and the ecosystem on Azure. They have a few goodies there and customers are making a choice to use Azure for certain things. If they, if they have teams or whatever or office, and they run all their dev on AWS. So that's kind of what's happened. So that's, multi-cloud by our definition is customers two clouds. That's not multi-cloud, as in things are moving around. Now, if you start getting data planes in there, these customers want platforms. If I'm a cybersecurity CSO, I'm moving to platforms, not just tools. So, so maybe CrowdStrike might have it dial down, but a little bit, but they're turning into a platform. Splunk trying to be a platform. Okta is platform. Everybody's scale is a platform. It's a platform war right now, Dave cyber, >>A right paying identity. They're all plat platform, beach products. We've talked about that a lot in the queue. >>Yeah. Well, great stuff, Dave, let's get going. We've got two days alive coverage. Here is a cubes at, in Boston for reinforc 22. I'm Shante. We're back with our guests coming on the queue at the short break.

>> Announcer: TheCube presents HPE Discover 2022, brought to you by HPE. >> Welcome back to HPE Discover 2022, theCube's continuous wall to wall coverage, Dave Vellante with John Furrier. Keith Basil is here as the General Manager for the Edge Business Unit at SUSE. Keith, welcome to theCube, man good to see you. >> Great to be here, it's my first time here and I've seen many shows and you guys are the best. >> Thanks you. >> Thank you very much. >> Big fans of SUSE you know, we've had Melissa on several times. >> Yes. >> Let's start with kind of what you guys are doing here at Discover. >> Well, we're here to support our wonderful partner HPE, as you know SUSE's products and services are now being integrated into the GreenLake offering. So that's very exciting for us. >> Yeah. Now tell us about your background. It's quite interesting you've kind of been in the mix in some really cool places. Tell us a little bit about yourself. >> Probably the most relevant was I used to work at Red Hat, I was a Product Manager working in security for OpenStack and OpenShift working with DOD customers in the intelligence community. Left Red Hat to go to Rancher, started out there as VP of Edge Solutions and then transitioned over to VP of Product for all of Rancher. And then obviously we know SUSE acquired Rancher and as of November 1st, of 2020, I think it was. >> Dave: 2020. >> Yeah, yeah time is flying. I came over, I still remained VP of Product for Rancher for Cloud Native Infrastructure. And I was working on the edge strategy for SUSE and about four months ago we internally built three business units, one for the Linux business, one for enterprise container management, basically the Rancher business, and then the newly minted business unit was the Edge business. And I was offered the role to be GM for that business unit and I happily accepted it. >> Very cool. I mean the market dynamics since the 2018 have changed dramatically, IBM bought Red Hat. A lot of customers said, "Hmm let's see what other alternatives are out there." SUSE popped its head up. You know, Melissa's been quite, you know forthcoming about that. And then you acquire Rancher in 2020, IPO in 2021. That kind of gives you another tailwind. So there's a new market when you go from 2018 to 2022, it's a completely changed dynamic. >> Yes and I'm going to answer your question from the Rancher perspective first, because as we were at Rancher, we had experimented with different flavors of the underlying OS underneath Kubernetes or Kubernetes offerings. And we had, as I said, different flavors, we weren't really operating system people for example. And so post-acquisition, you know, one of my internal roles was to bring the two halves of the house together, the philosophies together where you had a cloud native side in the form of Rancher, very progressive leading innovative products with Rancher with K3s for example. And then you had, you know, really strong enterprise roots around compliance and security, secure supply chain with the enterprise grade Linux. And what we found out was SUSE had been building a version of Linux called SLE Micro, and it was perfectly designed for Edge. And so what we've done over that time period since the acquisition is that we've brought those two things together. And now we're using Kubernetes directives and philosophies to manage all the way down to the operating system. And it is a winning strategy for our customers. And we're really excited about that. >> And what does that product look like? Is that a managed service? How are customers consuming that? >> It could be a managed service, it's something that our managed service providers could embrace and offer to their customers. But we have some customers who are very sophisticated who want to do the whole thing themselves. And so they stand up Rancher, you know at a centralized location at cloud GreenLake for example which is why this is very relevant. And then that control plane if you will, manages thousands of downstream clusters that are running K3s at these Edge locations. And so that's what the complete stack looks like. And so when you add the Linux capability to that scenario we can now roll a new operating system, new kernel, CVE updates, build that as an OCI container image registry format, right? Put that into a registry and then have that thing cascade down through all the downstream clusters and up through a rolling window upgrade of the operating system underneath Kubernetes. And it is a tremendous amount of value when you talk to customers that have this massive scale. >> What's the impact of that, just take us through what happens next. Is it faster? Is it more performant? Is it more reliable? Is it processing data at the Edge? What's the impact of the customer? >> Yes, the answer is yes to that. So let's actually talk about one customer that we we highlighted in our keynote, which is Home Depot. So as we know, Kubernetes is on fire, right? It is the technology everybody's after. So by being in demand, the skills needed, the people shortage is real and people are commanding very high, you know, salaries. And so it's hard to attract talent is the bottom line. And so using our software and our solution and our approach it allows people to scale their existing teams to preserve those precious human resources and that human capital. So that now you can take a team of seven people and manage let's say 3000 downstream stores. >> Yeah it's like the old SRE model for DevOps. >> Correct. >> It's not servers they're managing one to many. >> Yes. >> One to many clusters. >> Correct so you've got the cluster, the life cycle of the cluster. You already have the application life cycle with the classic DevOps. And now what we've built and added to the stack is going down one step further, clicking down if you will to managing the life cycle of the operating system. So you have the SUSE enterprise build chain, all the value, the goodness, compliance, security. Again, all of that comes with that build process. And now we're hooking that into a cloud native flow that ends up downstream in our customers. >> So what I'm hearing is your Edge strategy is not some kind of bespoke, "Hey, I'm going after Edge." It connects to the entire value chain. >> Yes, yeah it's a great point. We want to reuse the existing philosophies that are being used today. We don't want to create something net new, cause that's really the point in leverage that we get by having these teams, you know, do these things at scale. Another point I'm going to make here is that we've defined the Edge into three segments. One is the near Edge, which is the realm of the-- >> I was going to ask about this, great. >> The telecommunications companies. So those use cases and profiles look very different. They're almost data center lite, right? So you've had regional locations, central offices where they're standing up gear classic to you machines, right? So things you find from HPE, for example. And then once you get on the other side of the access device right? The cable modem, the router, whatever it is you get into what we call the far Edge. And this is where the majority of the use cases reside. This is where the diversity of use cases presents itself as well. >> Also security challenges. >> Security challenges. Yes and we can talk about that following in a moment. And then finally, if you look at that far Edge as a box, right? Think of it as a layer two domain, a network. Inside that location, on that network you'll have industrial IOT devices. Those devices are too small to run a full blown operating system such as Linux and Kubernetes in the stack but they do have software on them, right? So we need to be able to discover those devices and manage those devices and pull data from those devices and do it in a cloud native way. So that's what we called the tiny Edge. And I stole that name from the folks over at Microsoft. Kate and Edrick are are leading a project upstream called Akri, A-K-R-I, and we are very much heavily involved in Akri because it will discover the industrial IOT devices and plug those into a local Kubernetes cluster running at that location. >> And Home Depot would fit into the near edge is that correct? >> Yes. >> Yeah okay. >> So each Home Depot store, just to bring it home, is a far Edge location and they have over 2,600 of these locations. >> So far Edge? You would put far Edge? >> Keith: Far Edge yes. >> Far edge, okay. >> John: Near edge is like Metro. Think of Metro. >> And Teleco, communication, service providers MSOs, multi-service operators. Those guys are-- >> Near Edge. >> The near edge, yes. >> Don't you think, John's been asking all week about machine learning and AI, in that tiny Edge. We think there's going to be a lot of AI influencing. >> Keith: Oh absolutely. >> Real time. And it actually is going to need some kind of lighter weight you know, platform. How do you fit into that? >> So going on this, like this model I just described if you go back and look at the SUSECON 2022 demo keynote that I did, we actually on stage stood up that exact stack. So we had a single Intel nook running SLE Micro as we mentioned earlier, running K3s and we plugged into that device, a USB camera which was automatically detected and it loaded Akri and gave us a driver to plug it into a container. Now, to answer your question, that is the point in time where we bring in the ML and the AI, the inference and the pattern recognition, because that camera when you showed the SUSE plush doll, it actually recognized it and put a QR code up on the screen. So that's where it all comes together. So we tried to showcase that in a complete demo. >> Last week, I was here in Vegas for an event Amazon and AWS put on called re:Mars, machine learning, automation, robotics, and space. >> Okay. >> Kind of but basically for me was an industrial edge show. Cause The space is the ultimate like glam to edge is like, you're doing stuff in space that's pretty edgy so to speak, pun intended. But the industrial side of the Edge is going to, we think, accelerate with machine learning. >> Keith: Absolutely. >> And with these kinds of new portable I won't say flash compute or just like connected power sources software. The industrial is going to move really fast. We've been kind of in a snails pace at the Edge, in my opinion. What's your reaction to that? Do you think we're going to see a mass acceleration of growth at the Edge industrial, basically physical, the physical world. >> Yes, first I agree with your assessment okay, wholeheartedly, so much so that it's my strategy to go after the tiny Edge space and be a leader in the industrial IOT space from an open source perspective. So yes. So a few things to answer your question we do have K3s in space. We have a customer partner called Hypergiant where they've launched satellites with K3s running in space same model, that's a far Edge location, probably the farthest Edge location we have. >> John: Deep Edge, deep space. >> Here at HPE Discover, we have a business unit called SUSE RGS, Rancher Government Services, which focuses on the US government and DOD and IC, right? So little bit of the world that I used to work in my past career. Brandon Gulla the CTO of of that unit gave a great presentation about what we call the tactical Edge. And so the same technology that we're using on the commercial and the manufacturing side. >> Like the Jedi contract, the tactical military Edge I think. >> Yes so imagine some of these military grade industrial IOT devices in a disconnected environment. The same software stack and technology would apply to that use case as well. >> So basically the tactical Edge is life? We're humans, we're at the Edge? >> Or it's maintenance, right? So maybe it's pulling sensors from aircraft, Humvees, submarines and doing predictive analysis on the maintenance for those items, those assets. >> All these different Edges, they underscore the diversity that you were just talking Keith and we also see a new hardware architecture emerging, a lot of arm based stuff. Just take a look at what Tesla's doing at the tiny Edge. Keith Basil, thanks so much. >> Sure. >> For coming on theCube. >> John: Great to have you. >> Grateful to be here. >> Awesome story. Okay and thank you for watching. This is Dave Vellante for John Furrier. This is day three of HPE Discover 2022. You're watching theCube, the leader in enterprise and emerging tech coverage. We'll be right back. (upbeat music)

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's coverage of HPE. Discover 22 live from the Sans expo center in Las Vegas. Lisa Martin, here with Dave Velante. We've an alumni back joining us to talk about high performance computing and AI, Justin ARD, EVP, and general manager of HPC and AI at HPE. That's a mouthful. Welcome back. >>It is no, it's great to be back and wow, it's great to be back in person as well. >>It's it's life changing to be back in person. The keynote this morning was great. The Dave was saying the energy that he's seen is probably the most out of, of any discover that you've been at and we've been feeling that and it's only day one. >>Yeah, I, I, I agree. And I think it's a Testament to the places in the market that we're leading the innovation we're driving. I mean, obviously the leadership in HPE GreenLake and, and enabling as a service for, for every customer, not just those in the public cloud, providing that, that capability. And then obviously what we're doing at HPC and AI breaking, uh, you know, breaking records and, uh, advancing the industry. So >>I just saw the Q2 numbers, nice revenue growth there for HPC and AI. Talk to us about the lay of the land what's going on, what are customers excited about? >>Yeah. You know, it's, it's a, it's a really fascinating time in this, in this business because we're, you know, we just, we just delivered the first, the world's first exo scale system. Right. And that's, uh, you know, that's a huge milestone for our industry, a breakthrough, you know, 13 years ago, we did the first Petta scale system. Now we're doing the first exo scale system, huge advance forward. But what's exciting too, is these systems are enabling new applications, new workloads, breakthroughs in AI, the beginning of being able to do proper quantum simulations, which will lead us to a much, you know, brighter future with quantum and then actually better and more granular models, which have the ability to really change the world. >>I was telling Lisa that during the pandemic we did, uh, exo scale day, it was like this co yep. You know, produce event. And we weren't quite at exo scale yet, but we could see it coming. And so it was great to see in frontier and, and the keynote you guys broke through that, is that a natural evolution of HPC or is this we entering a new era? >>Yeah, I, I think it's a new era and I think it's a new era for a few reasons because that, that breakthrough really, it starts to enable a different class of use cases. And it's combined with the fact that I think, you know, you look at where the rest of the enterprises data set has gone, right? We've got a lot more data, a lot more visibility to data. Um, but we don't know how to use it. And now with this computing power, we can start to create new insights and new applications. And so I think this is gonna be a path to making HPC more broadly available. And of course it introduces AI models at scale. And that's, that's really critical cause AI is a buzzword. I mean, lots of people say they're doing AI, but when you know, to, to build true intelligence, not, not effectively, you know, a machine that learns data and then can only handle that data, but to build true intelligence where you've got something that can continue to learn and understand and grow and evolve, you need this class of system. And so I think we're at, we're at the forefront of a lot of exciting innovation. H how, >>In terms of innovation, how important is it that you're able to combine as a service and HPC? Uh, what does that mean for, for customers for experimentation and innovation? >>You know, a couple things I've been, I've actually been talking to customers about that over the last day and a half. And, you know, one is, um, you think about these, these systems are, they're very large and, and they're, they're pretty, you know, pretty big bets if you're a customer. So getting early access to them right, is, is really key, making sure that they're, they can migrate their software, their applications, again, in our space, most of our applications are custom built, whether you're a, you know, a government or a private sector company, that's using these systems, you're, you're doing these are pretty specialized. So getting that early access is important. And then actually what we're seeing is, uh, with the growth and explosion of insight that we can enable. And some of the diversity of, you know, new, um, accelerator partners and new processors that are on the market is actually the attraction of diversity. And so making things available where customers can use multimodal systems. And we've seen that in this era, like our customer Lumi and Finland number, the number three fastest system in the world actually has two sides to their system. So there's a compute side, dense compute side and a dense accelerator side. >>So Oak Ridge national labs was on stage with Antonio this morning, the, the talking about frontier, the frontier system, I thought what a great name, very apropo, but it was also just named the number one to the super computing, top 500. That's a pretty big accomplishment. Talk about the impact of what that really means. >>Yeah. I, I think a couple things, first of all, uh, anytime you have this breakthrough of number one, you see a massive acceleration of applications. And if you really, if you look at the applications that were built, because when the us department of energy funded these Exoscale products or platforms, they also funded app a set of applications. And so it's the ability to get more accurate earth models for long term climate science. It's the ability to model the electrical grid and understand better how to build resiliency into that grid. His ability is, um, Dr. Te Rossi talked about a progressing, you know, cancer research and cancer breakthroughs. I mean, there's so many benefits to the world that we can bring with these systems. That's one element. The other big part of this breakthrough is actually a list, a lesser known list from the top 500 called the green 500. >>And that's where we measure performance over power consumption. And what's a huge breakthrough in this system. Is that not only to frontier debut at number one on the top 500, it's actually got the top two spots, uh, because it's got a small test system that also is up there, but it's got the top two spots on the green 500 and that's actually a real huge breakthrough because now we're doing a ton more computation at far lesser power. And that's really important cuz you think about these systems, ultimately you can, you can't, you know, continue to consume power linearly with scaling up performance. There's I mean, there's a huge issue on our impact on our environment, but it's the impact to the power grid. It's the impact to heat dissipation. There's a lot of complexities. So this breakthrough with frontier also enables us no pun intended to really accelerate, you know, the, the capacity and scale of these systems and what we can deliver. >>It feels like we're entering a new Renaissance of HPC. I mean, I'm old enough to remember. I, it was, it wasn't until recently my wife, not recently, maybe five, six years ago, my wife threw out my, my green thinking machines. T-shirt that Danny Hillis gave you guys probably both too young to remember, but you had thinking machines, Ken to square research convex tried to mini build a mini computer HPC. Okay. And there was a lot of innovation going on around that time and then it just became too expensive and, and, and other things X 86 happened. And, and, but it feels like now we're entering a, a new era of, of HPC. Is that valid or is it true? What's that mean for HPC as an industry and for industry? >>Yeah, I think, I think it's a BR I think it's a breadth. Um, it's a market that's opening and getting much more broader the number of applications you can run, you know, and we've traditionally had, you know, scientific applications, obviously there's a ton in energy and, and you know, physics and some of the traditional areas that obviously the department of energy sponsor, but, you know, we saw this with, with even the COVID pandemic, right? Our, our supercomputers were used to identify the spike protein to, to help and validate and test these vaccines and bring them to market and record time. We saw some of the benefits of these breakthroughs. And I think it's this combination of that, that we actually have the data, you know, it's, it's digital, it's captured, um, we're capturing it at, you know, at the edge, we're capturing it and, and storing it obviously more broadly. So we have the access to the data and now we have the compute power to run it. And the other big thing is the techniques around artificial intelligence. I mean, what we're able to do with neural networks, computer vision, large language models, natural language processing. These are breakthroughs that, um, one require these large systems, but two, as you give them a large systems, you can actually really enable acceleration of how sophisticated these, these applications can get. >>Let's talk about the impact of the convergence of HPC and AI. What are some of the things that you're seeing now and what are some of the things that we're gonna see? >>Yeah. So, so I, one thing I like to talk about is it's, it's really, it's not a convergence. I think it's it. Sometimes it gets a little bit oversimplified. It's actually, it's traditional modeling and simulation leveraging machine learning to, to refine the simulation. And this is a, is one of the things we talk about a lot in AI, right? It's using machine learning to actually create code in real time, rather than humans doing it, that ability to refine the model as you're running. So we have an example. We did a, uh, we, we actually launched an open source solution called smart SIM. And the first application of that was climate science. And it's what it's doing is it's actually learning the data from the model as the simulation is running to provide more accurate climate prediction. But you think about that, that could be run for, you know, anything that has a complex model. >>You could run that for financial modeling, you can use AI. And so we're seeing things like that. And I think we'll continue to see that the other side of that is using modeling and simulation to actually represent what you see in AI. So we were talking about the grid. This is one of the Exoscale compute projects you could actually use once you actually get, get the data and you can start modeling the behavior of every electrical endpoint in a city. You know, the, the meter in your house, the substation, the, the transformers, you can start measuring the FX of that. You can then build equations. Well, once you build those equations, you can then take a model, cuz you've learned what actually happens in the real world, build the equation. And then you can provide that to someone who doesn't need a extra scale supercomputer to run it, but that, you know, your local energy company can better understand what's happening and they'll know, oh, there's a problem here. We need to shift the grid or respond more, more dynamically. And hopefully that avoids brownouts or, you know, some of the catastrophic outages we've >>Seen so they can deploy that model, which, which inherently has that intelligence on sort of more cost effective systems and then apply it to a much broader range. Do any of those, um, smart simulations on, on climate suggest that it's, it's all a hoax. You don't have to answer that question. <laugh> um, what, uh, >>The temperature outside Dave might, might give you a little bit of an argument to that. >>Tell us about quantum, what's your point of view there? Is it becoming more stable? What's H HPE doing there? >>Yeah. So, so look, I think there's, there's two things to understand with quantum there's quantum hardware, right? Fundamentally, um, how, um, how that runs very differently than, than how we run traditional computers. And then there's the applications. And ultimately a quantum application on quantum hardware will be far more efficient in the future than, than anything else. We, we see the opportunity for, uh, much like we see with, you know, with HPC and AI, we just talked about for quantum to be complimentary. It runs really well with certain applications that fabricate themselves as quantum problems and some great examples are, you know, the, the life sciences, obviously quantum chemistry, uh, you see some, actually some opportunities in, in, uh, in AI and in other areas where, uh, quantum has a very, very, it, it just lends itself more naturally to the behavior of the problem. And what we believe is that in the short term, we can actually model quantum effectively on these, on these super computers, because there's not a perfect quantum hardware replacement over time. You know, we would anticipate that will evolve and we'll see quantum accelerators much. Like we see, you know, AI accelerators today in this space. So we think it's gonna be a natural evolution in progression, but there's certain applications that are just gonna be solved better by quantum. And that's the, that's the future we'll we'll run into. And >>You're suggesting if I understood it correctly, you can start building those applications and, and at least modeling what those applications look like today with today's technology. That's interesting because I mean, I, I think it's something rudimentary compared to quantum as flash storage, right? When you got rid of the spinning disc, it changed the way in which people thought about writing applications. So if I understand it, new applications that can take advantage of quantum are gonna change the way in which developers write, not one or a zero it's one and virtually infinite <laugh> combinations. >>Yeah. And I actually, I think that's, what's compelling about the opportunity is that you can, if you think about a lot of traditional the traditional computing industry, you always had to kind of wait for the hardware to be there, to really write, write, and test the application. And we, you know, we even see that with our customers and HPC and, and AI, right? They, they build a model and then they, they actually have to optimize it across the hardware once they deploy it at scale. And with quantum what's interesting is you can actually, uh, you can actually model and, and, and make progress on the software. And then, and then as the hardware becomes available, optimize it. And that's, you know, that's why we see this. We talk about this concept of quantum accelerators as, as really interesting, >>What are the customer conversations these days as there's been so much evolution in HPC and AI and the technology so much change in the world in the last couple of years, is it elevating up the CS stack in terms of your conversations with customers wanting to become familiar with Exoscale computing? For example? >>Yeah. I, I think two things, uh, one, one is we see a real rise in digital sovereignty and Exoscale and HPC as a core fund, you know, fundamental foundation. So you see what, um, you know, what Europe is doing with the, the, the Euro HPC initiative, as one example, you know, we see the same kind of leadership coming out of the UK with the system. We deployed with them in Archer two, you know, we've got many customers across the globe deploying next generation weather forecasting systems, but everybody feels, they, they understand the foundation of having a strong supercomputing and HPC capability and competence and not just the hardware, the software development, the scientific research, the, the computational scientists to enable them to remain competitive economically. It's important for defense purposes. It's important for, you know, for helping their citizens, right. And providing, you know, providing services and, and betterment. >>So that's one, I'd say that's one big theme. The other one is something Dave touched on before around, you know, as a service and why we think HP GreenLake will be, uh, a beautiful marriage with our, with our HPC and AI systems over time, which is customers also, um, are going to scale up and build really complex models. And then they'll simplify them and deploy them in other places. And so there's a number of examples. We see them, you know, we see them in places like oil and gas. We see them in manufacturing where I've gotta build a really complex model, figure out what it looks like. Then I can reduce it to a, you know, to a, uh, certain equation or application that I can then deploy. So I understand what's happening and running because you, of course, as much as I would love it, you're not gonna have, uh, every enterprise around the world or every endpoint have an exit scale system. Right. So, so that ability to, to, to really provide an as a service element with HP GreenLake, we think is really compelling. >>HP's move into HPC, the acquisitions you've made it really have become a differentiator for the company. Hasn't it? >>Yeah. And I, and I think what's unique about us today. If you look at the landscape is we're, we're really the only system provider globally. Yeah. You know, there are, there are local players that we compete with. Um, but we are the one true global system provider. And we're also the only, I would say the only holistic innovator at the system level to, to, you know, to credit my team on the work they're doing. But, you know, we're, we're also very committed to open standards. We're investing in, um, you know, in a number of places where we contribute the dev the software assets to open source, we're doing work with standards bodies to progress and accelerate the industry and enable the ecosystem. And, uh, and I think that, you know, ultimately the, the, the last thing I'd say is we, we are so connected in, um, with, through our, through the legacy or the, the legend of H Hewlett Packard labs, which now also reports into me that we have these really tight ties into advanced research and that some of that advanced research, which isn't just, um, around kind of core processing Silicon is really critical to enabling better applications, better use cases and accelerating the outcomes we see in these systems going forward. >>Can >>You double click on that? I, I, I wasn't aware that kind of reported into your group. Yeah. So, you know, the roots of HP are invent, right? Yeah. HP labs are, are renowned. It kinda lost that formula for a while. And now it's sounds like it's coming back. What, what, what are some of the cool things that you guys are working on? Well, >>You know, let me, let me start with a little bit of recent history. So we just talked about the exo scale program. I mean, that was a, that's a great example of where we had a public private partnership with the department of energy and it, and it wasn't just that we, um, you know, we built a system and delivered it, but if you go back a decade ago, or five years ago, there were, there were innovations that were built, you know, to accelerate that system. One is our Slingshot fabric as an example, which is a core enable of, of acceler, you know, of, of this accelerated computing environment, but others in software applications and services that allowed us to, you know, to really deliver a, a complete solution into the market. Um, today we're looking at things around trustworthy and ethical AI, so trustworthy AI in the sense that, you know, the models are accurate, you know, and that's, that's a challenge on two dimensions, cuz one is the, model's only as good as the data it's studying. >>So you need to validate that the data's accurate and then you need to really study how, you know, how do I make sure that even if the data is accurate, I've got a model that then, you know, is gonna predict the right things and not call a, a dog, a cat, or a, you know, a, a cat, a mouse or whatever that is. But so that's important. And, uh, so that's one area. The other is future system architectures because, um, as we've talked about before, Dave, you have this constant tension between the fabric, uh, you know, the interconnect, the compute and the, and the storage and, you know, constant, constantly balancing it. And so we're really looking at that, how do we do more, you know, shared memory access? How do we, you know, how do we do more direct rights? Like, you know, looking at some future system architectures and thinking about that. And we, you know, we think that's really, really critical in this part of the business because these heterogeneous systems, and not saying I'm gonna have one monolithic application, but I'm gonna have applications that need to take advantage of different code, different technologies at different times. And being able to move that seamlessly across the architecture, uh, we think is gonna be the, you know, a part of the, the hallmark of the Exoscale era, including >>Edge, which is a completely different animal. I think that's where some disruption is gonna gonna bubble up here in the next decade. >>So, yeah know, and, and that's, you know, that's the last thing I'd say is, is we look at AI at scale, which is another core part of the business that can run on these large clusters. That means getting all the way down to the edge and doing inference at scale, right. And, and inference at scale is, you know, I, I was, um, about a month ago, I was at the world economic forum. We were talking about the space economy and it's a great, you know, to me, it's the perfect example of inference, because if you get a set of data that you know, is, is out at Mars, it doesn't matter whether, you know, whether you wanna push all that data back to, uh, to earth for processing or not. You don't really have a choice, cuz it's just gonna take too long. >>Don't have that time. Justin, thank you so much for spending some of your time with Dave and me talking about what's going on with HBC and AI. The frontier just seems endless and very exciting. We appreciate your time on your insights. >>Great. Thanks so much. Thanks. >>Yes. And don't call a dog, a cat that I thought I learned from you. A dog at no, Nope. <laugh> Nope. <laugh> for Justin and Dave ante. I'm Lisa Martin. 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