>> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (intro music) >> Good afternoon, everyone. Welcome back to "theCUBE's" day three coverage of MWC23. Lisa Martin here in Spain, Barcelona, Spain with Dave Nicholson. We're going to have a really interesting conversation next. We're going to really dig into MWC, it's history, where it's going, some of the controversy here. Please welcome our guests. We have Jim Harris, International Best Selling Author of "Blindsided." And Carolina Milanese is here, President and Principle Analyst of creative strategies. Welcome to "theCUBE" guys. Thank you. >> Thanks. So great to be here. >> So this is day three. 80,000 people or so. You guys have a a lot of history up at this event. Caroline, I want to start with you. Talk a little bit about that. This obviously the biggest one in, in quite a few years. People are ready to be back, but there's been some, a lot of news here, but some controversy going on. Give us the history, and your perspective on some of the news that's coming out from this week's event. >> It feels like a very different show. I don't know if I would say growing up show, because we are still talking about networks and mobility, but there's so much more now around what the networks actually empower, versus the network themselves. And a little bit of maybe that's where some of the controversy is coming from, carriers still trying to find their identity, right, of, of what their role is in all there is to do with a connected world. I go back a long way. I go back to when Mobile World Congress was called, was actually called GSM, and it was in Khan. So, you know, we went from France to Spain. But just looking at the last full Mobile World Congress here in Barcelona, in pre-pandemic to now, very different show. We went from a show that was very much focused on mobility and smartphones, to a show that was all about cars. You know, we had cars everywhere, 'cause we were talking about smart cities and connected cars, to now a show this year that is very much focused on B2B. And so a lot of companies that are here to either work with the carriers, or also talk about sustainability for instance, or enable what is the next future evolution of computing with XR and VR. >> So Jim, talk to us a little bit about your background. You, I was doing a little sleuthing on you. You're really focusing on disruptive innovation. We talk about disruption a lot in different industries. We're seeing a lot of disruption in telco. We're seeing a lot of frenemies going on. Give us your thoughts about what you're seeing at this year's event. >> Well, there's some really exciting things. I listened to the keynote from Orange's CEO, and she was complaining that 55% of the traffic on her network is from five companies. And then the CEO of Deutsche Telecom got up, and he was complaining that 60% of the traffic on his network is from six entities. So do you think they coordinated pre, pre-show? But really what they're saying is, these OTT, you know, Netflix and YouTube, they should be paying us for access. Now, this is killer funny. The front page today of the show, "Daily," the CO-CEO of Netflix says, "Hey, we make less profit than the telcos, "so you should be paying us, "not the other way around." You know, we spend half of the money we make just on developing content. So, this is really interesting. The orange CEO said, "We're not challenging net neutrality. "We don't want more taxes." But boom. So this is disruptive. Huge pressure. 67% of all mobile traffic is video, right? So it's a big hog bandwidth wise. So how are they going to do this? Now, I look at it, and the business model for the, the telcos, is really selling sim cards and smartphones. But for every dollar of revenue there, there's five plus dollars in apps, and consulting and everything else. So really, but look at how they're structured. They can't, you know, take somebody who talks to the public and sells sim cards, and turn 'em in, turn 'em in to an app developer. So how are they going to square this circle? So I see some, they're being disrupted because they're sticking to what they've historically done. >> But it's interesting because at the end of the day, the conversation that we are having right now is the conversation that we had 10 years ago, where carriers don't want to just be a dumb pipe, right? And that's what they are now returning to. They tried to be media as well, but that didn't work out for most carriers, right? It is a little bit better in the US. We've seen, you know, some success there. But, but here has been more difficult. And I think that's the, the concern, that even for the next, you know, evolution, that's the, their role. >> So how do they, how do they balance this dumb pipe idea, with the fact that if you make the toll high enough, being a dumb pipe is actually a pretty good job. You know, sit back, collect check, go to the beach, right? So where, where, where, where does this end up? >> Well, I think what's going to happen is, if you see five to 15 X the revenue on top of a pipe, you know, the hyperscalers are going to start going after the business. The consulting companies like PWC, McKinsey, the app developers, they're... So how do you engage those communities as a telco to get more revenue? I think this is a question that they really need to look at. But we tend to stick within our existing business model. I'll just give you one stat that blows me away. Uber is worth more than every taxi cab company in North America added together. And so the taxi industry owns billions in assets in cars and limousines. Uber doesn't own a single vehicle. So having a widely distributed app, is a huge multiplier on valuation. And I look to a company like Safari in Kenya, which developed M-Pesa, which Pesa means mo, it's mobile money in Swahili. And 25% of the country's GDP is facilitated by M-Pesa. And that's not even on smartphones. They're feature phones, Nokia phones. I call them dumb phones, but Nokia would call them "feature phones." >> Yeah. >> So think about that. Like 25, now transactions are very small, and the cut is tiny. But when you're facilitating 25% of a country's GDP, >> Yeah. >> Tiny, over billions of transactions is huge. But that's not the way telcos have historically thought or worked. And so M-Pesa and Safari shows the way forward. What do you think on that? >> I, I think that the experience, and what they can layer on top from a services perspective, especially in the private sector, is also important. I don't, I never believe that a carrier, given how they operate, is the best media company in the world, right? It is a very different world. But I do think that there's opportunity, first of all, to, to actually tell their story in a different way. If you're thinking about everything that a network actually empowers, there's a, there's a lot there. There's a lot that is good for us as, as society. There's a lot that is good for business. What can they do to start talking about differently about their services, and then layer on top of what they offer? A better way to actually bring together private and public network. It's not all about cellular, wifi and cellular coming together. We're talking a lot about satellite here as well. So, there's definitely more there about quality of service. Is, is there though, almost a biological inevitability that prevents companies from being able to navigate that divide? >> Hmm. >> Look at, look at when, when, when we went from high definition 720P, very exciting, 1080P, 4K. Everybody ran out and got a 4K TV. Well where was the, where was the best 4K content coming from? It wasn't, it wasn't the networks, it wasn't your cable operator, it was YouTube. It was YouTube. If you had suggested that 10 years before, that that would happen, people would think that you were crazy. Is it possible for folks who are now leading their companies, getting up on stage, and daring to say, "This content's coming over, "and I want to charge you more "for using my pipes." It's like, "Really? Is that your vision? "That's the vision that you want to share with us here?" I hear the sound of dead people walking- (laughing) when I hear comments like that. And so, you know, my students at Wharton in the CTO program, who are constantly looking at this concept of disruption, would hear that and go, "Ooh, gee, did the board hear what that person said?" I, you know, am I being too critical of people who could crush me like a bug? (laughing) >> I mean, it's better that they ask the people with money than not consumers to pay, right? 'Cause we've been through a phase where the carriers were actually asking for more money depending on critical things. Like for instance, if you're doing business email, then were going to charge you more than if you were a consumer. Or if you were watching video, they would charge you more for that. Then they understood that a consumer would walk away and go somewhere else. So they stopped doing that. But to your point, I think, and, and very much to what you focus from a disruption perspective, look at what Chat GTP and what Microsoft has been doing. Not much talk about this here at the show, which is interesting, but the idea that now as a consumer, I can ask new Bing to get me the 10 best restaurants in Barcelona, and I no longer go to Yelp, or all the other businesses where I was going to before, to get their recommendation, what happens to them? You're, you're moving away, and you're taking eyeballs away from those websites. And, and I think that, that you know, your point is exactly right. That it's, it's about how, from a revenue perspective, you are spending a lot of money to facilitate somebody else, and what's in it for you? >> Yeah. And to be clear, consumers pay for everything. >> Always. Always. (laughs) >> Taxpayers and consumers always pay for everything. So there is no, "Well, we're going to make them pay, so you don't have to pay." >> And if you are not paying, you are the product. Exactly. >> Yes. (laughing) >> Carolina, talk a little bit about what you're seeing at the event from some of the infrastructure players, the hyperscalers, obviously a lot of enterprise focus here at this event. What are some of the things that you're seeing? Are you impressed with, with their focus in telco, their focus to partner, build an ecosystem? What are you seeing? >> I'm seeing also talk about sustainability, and enabling telco to be more sustainable. You know, there, there's a couple of things that are a little bit different from the US where I live, which is that telcos in Europe, have put money into sustainability through bonds. And so they use the money that they then get from the bonds that they create, to, to supply or to fuel their innovation in sustainability. And so there's a dollar amount on sustainability. There's also an opportunity obviously from a growth perspective. And there's a risk mitigation, right? Especially in Europe, more and more you're going to be evaluated based on how sustainable you are. So there are a lot of companies here, if you're thinking about the Ciscos of the world. Dell, IBM all talking about sustainability and how to help carriers measure, and then obviously be more sustainable with their consumption and, and power. >> Going to be interesting to see where that goes over the years, as we talk to, every company we talk to at whatever show, has an ESG sustainability initiative, and only, well, many of them only want to work with other companies who have the same types of initiative. So a lot of, great that there's focus on sustainability, but hopefully we'll see more action down the road. Wanted to ask you about your book, "Blind," the name is interesting, "Blindsided." >> Well, I just want to tag on to this. >> Sure. >> One of the most exciting things for me is fast charging technology. And Shalmie, cell phone, or a smartphone maker from China, just announced yesterday, a smartphone that charges from 0 to 100% in five minutes. Now this is using GAN FEST technology. And the leader in the market is a company called Navitas. And this has profound implications. You know, it starts with the smartphone, right? But then it moves to the laptops. And then it'll move to EV's. So, as we electrify the $10 trillion a year transportation industry, there's a huge opportunity. People want charging faster. There's also a sustainability story that, to Carolina's point, that it uses less electricity. So, if we electrify the grid in order to support transportation, like the Tesla Semi's coming out, there are huge demands over a period. We need energy efficiency technologies, like this GAN FEST technology. So to me, this is humongous. And it, we only see it here in the show, in Shalmie, saying, "Five minutes." And everybody, the consumers go, "Oh, that's cool." But let's look at the bigger story, which is electrifying transportation globally. And this is going to be big. >> Yeah. And, and to, and to double click on that a little bit, to be clear, when we talk about fast charging today, typically it's taking the battery from a, not a zero state of charge, but a relatively low state of charge to 80%. >> Yep. >> Then it tapers off dramatically. And that translates into less range in an EV, less usable time on any other device, and there's that whole linkage between the power in, and the battery's ability to be charged, and how much is usable. And from a sustainability perspective, we are going to have an avalanche of batteries going into secondary use cases over time. >> They don't get tossed into landfills contrary to what people might think. >> Yep. >> In fact, they are used in a variety of ways after their primary lifespan. But that, that is, that in and of itself is a revolutionary thing. I'm interested in each of your thoughts on the China factor. Glaringly absent here, from my perspective, as sort of an Apple fanboy, where are they? Why aren't they talking about their... They must, they must feel like, "Well we just don't need to." >> We don't need to. We just don't need to. >> Absolutely. >> And then you walk around and you see these, these company names that are often anglicized, and you don't necessarily immediately associate them with China, but it's like, "Wait a minute, "that looks better than what I have, "and I'm not allowed to have access to that thing." What happens in the future there geopolitically? >> It's a pretty big question for- >> Its is. >> For a short little tech show. (Caroline laughs) But what happens as we move forward? When is the entire world going to be able to leverage in a secure way, some of the stuff that's coming out of, if they're not the largest economy in the world yet, they shortly will be. >> What's the story there? >> Well, it's interesting that you mentioned First Apple that has never had a presence at Mobile World Congress. And fun enough, I'm part of the GSMA judges for the GLOMO Awards, and last night I gave out Best Mobile Phone for last year, and it was to the iPhone4 Team Pro. and best disruptive technology, which was for the satellite function feature on, on the new iPhone. So, Apple might not be here, but they are. >> Okay. >> And, and so that's the first thing. And they are as far as being top of mind to every competitor in the smartphone market still. So a lot of the things that, even from a design perspective that you see on some of the Chinese brands, really remind you of, of Apple. What is interesting for me, is how there wouldn't be, with the exception of Samsung and Motorola, there's no one else here that is non-Chinese from a smartphone point of view. So that's in itself, is something that changed dramatically over the years, especially for somebody like me that still remember Nokia being the number one in the market. >> Huh. >> So. >> Guys, we could continue this conversation. We are unfortunately out of time. But thank you so much for joining Dave and me, talking about your perspectives on the event, the industry, the disruptive forces. It's going to be really interesting to see where it goes. 'Cause at the end of the day, it's the consumers that just want to make sure I can connect wherever I am 24 by seven, and it just needs to work. Thank you so much for your insights. >> Thank you. >> Lisa, it's been great. Dave, great. It's a pleasure. >> Our pleasure. For our guests, and for Dave Nicholson, I'm Lisa Martin. You're watching, "theCUBE," the leader in live and emerging tech coverage coming to you day three of our coverage of MWC 23. Stick around. Our next guest joins us momentarily. (outro music)

(lively music) >> Welcome back to our coverage of Cloud Native Security Con. I'm Dave Vellante, here in our Boston studio. We're connecting today, throughout the day, with Palo Alto on the ground in Seattle. And right now I'm here with Michael Foster with Red Hat. He's on the ground in Seattle. We're going to discuss the trends and containers and security and everything that's going on at the show in Seattle. Michael, good to see you, thanks for coming on. >> Good to see you, thanks for having me on. >> Lot of market momentum for Red Hat. The IBM earnings call the other day, announced OpenShift is a billion-dollar ARR. So it's quite a milestone, and it's not often, you know. It's hard enough to become a billion-dollar software company and then to have actually a billion-dollar product alongside. So congratulations on that. And let's start with the event. What's the buzz at the event? People talking about shift left, obviously supply chain security is a big topic. We've heard a little bit about or quite a bit about AI. What are you hearing on the ground? >> Yeah, so the last event I was at that I got to see you at was three months ago, with CubeCon and the talk was supply chain security. Nothing has really changed on that front, although I do think that the conversation, let's say with the tech companies versus what customers are actually looking at, is slightly different just based on the market. And, like you said, thank you for the shout-out to a billion-dollar OpenShift, and ACS is certainly excited to be part of that. We are seeing more of a consolidation, I think, especially in security. The money's still flowing into security, but people want to know what they're running. We've allowed, had some tremendous growth in the last couple years and now it's okay. Let's get a hold of the containers, the clusters that we're running, let's make sure everything's configured. They want to start implementing policies effectively and really get a feel for what's going on across all their workloads, especially with the bigger companies. I think bigger companies allow some flexibility in the security applications that they can deploy. They can have different groups that manage different ones, but in the mid to low market, you're seeing a lot of consolidation, a lot of companies that want basically one security tool to manage them all, so to speak. And I think that the features need to somewhat accommodate that. We talk supply chain, I think most people continue to care about network security, vulnerability management, shifting left and enabling developers. That's the general trend I see. Still really need to get some hands on demos and see some people that I haven't seen in a while. >> So a couple things on, 'cause, I mean, we talk about the macroeconomic climate all the time. We do a lot of survey data with our partners at ETR, and their recent data shows that in terms of cost savings, for those who are actually cutting their budgets, they're looking to consolidate redundant vendors. So, that's one form of consolidation. The other theme, of course, is there's so many tools out in the security market that consolidating tools is something that can help simplify, but then at the same time, you see opportunities open up, like IOT security. And so, you have companies that are starting up to just do that. So, there's like these countervailing trends. I often wonder, Michael, will this ever end? It's like the universe growing and tooling, what are your thoughts? >> I mean, I completely agree. It's hard to balance trying to grow the company in a time like this, at the same time while trying to secure it all, right? So you're seeing the consolidation but some of these applications and platforms need to make some promises to say, "Hey, we're going to move into this space." Right, so when you have like Red Hat who wants to come out with edge devices and help manage the IOT devices, well then, you have a security platform that can help you do that, that's built in. Then the messaging's easy. When you're trying to do that across different cloud providers and move into IOT, it becomes a little bit more challenging. And so I think that, and don't take my word for this, some of those IOT startups, you might see some purchasing in the next couple years in order to facilitate those cloud platforms to be able to expand into that area. To me it makes sense, but I don't want to hypothesize too much from the start. >> But I do, we just did our predictions post and as a security we put up the chart of candidates, and there's like dozens, and dozens, and dozens. Some that are very well funded, but I mean, you've seen some down, I mean, down rounds everywhere, but these many companies have raised over a billion dollars and it's like uh-oh, okay, so they're probably okay, maybe. But a lot of smaller firms, I mean there's just, there's too many tools in the marketplace, but it seems like there is misalignment there, you know, kind of a mismatch between, you know, what customers would like to have happen and what actually happens in the marketplace. And that just underscores, I think, the complexities in security. So I guess my question is, you know, how do you look at Cloud Native Security, and what's different from traditional security approaches? >> Okay, I mean, that's a great question, and it's something that we've been talking to customers for the last five years about. And, really, it's just a change in mindset. Containers are supposed to unleash developer speed, and if you don't have a security tool to help do that, then you're basically going to inhibit developers in some form or another. I think managing that, while also giving your security teams the ability to tell the message of we are being more secure. You know, we're limiting vulnerabilities in our cluster. We are seeing progress because containers, you know, have a shorter life cycle and there is security and speed. Having that conversation with the C-suites is a little different, especially when how they might be used to virtual machines and managing it through that. I mean, if it works, it works from a developer's standpoint. You're not taking advantage of those containers and the developer's speed, so that's the difference. Now doing that and then first challenge is making that pitch. The second challenge is making that pitch to then scale it, so you can get onboard your developers and get your containers up and running, but then as you bring in new groups, as you move over to Kubernetes or you get into more container workloads, how do you onboard your teams? How do you scale? And I tend to see a general trend of a big investment needed for about two years to make that container shift. And then the security tools come in and really blossom because once that core separation of responsibilities happens in the organization, then the security tools are able to accelerate the developer workflow and not inhibit it. >> You know, I'm glad you mentioned, you know, separation of responsibilities. We go to a lot of shows, as you know, with theCUBE, and many of them are cloud shows. And in the one hand, Cloud has, you know, obviously made the world, you know, more interesting and better in so many different ways and even security, but it's like new layers are forming. You got the cloud, you got the shared responsibility model, so the cloud is like the first line of defense. And then you got the CISO who is relying heavily on devs to, you know, the whole shift left thing. So we're asking developers to do a lot and then you're kind of behind them. I guess you have audit is like the last line of defense, but my question to you is how can software developers really ensure that cloud native tools that they're using are secure? What steps can they take to improve security and specifically what's Red Hat doing in that area? >> Yeah, well I think there's, I would actually move away from that being the developer responsibility. I think the job is the operators' and the security people. The tools to give them the ability to see. The vulnerabilities they're introducing. Let's say signing their images, actually verifying that the images that's thrown in the cloud, are the ones that they built, that can all be done and it can be done open source. So we have a DevSecOps validated pattern that Red Hat's pushed out, and it's all open source tools in the cloud native space. And you can sign your builds and verify them at runtime and make sure that you're doing that all for free as one option. But in general, I would say that the hope is that you give the developer the information to make responsible choices and that there's a dialogue between your security and operations and developer teams but security, we should not be pushing that on developer. And so I think with ACS and our tool, the goal is to get in and say, "Let's set some reasonable policies, have a conversation, let's get a security liaison." Let's say in the developer team so that we can make some changes over time. And the more we can automate that and the more we can build and have that conversation, the better that you'll, I don't say the more security clusters but I think that the more you're on your path of securing your environment. >> How much talk is there at the event about kind of recent high profile incidents? We heard, you know, Log4j, of course, was mentioned in the Keynote. Somebody, you know, I think yelled out from the audience, "We're still dealing with that." But when you think about these, you know, incidents when looking back, what lessons do you think we've learned from these events? >> Oh, I mean, I think that I would say, if you have an approach where you're managing your containers, managing the age and using containers to accelerate, so let's say no images that are older than 90 days, for example, you're going to avoid a lot of these issues. And so I think people that are still dealing with that aspect haven't set up the proper, let's say, disclosure between teams and update strategy and so on. So I don't want to, I think the Log4j, if it's still around, you know, something's missing there but in general you want to be able to respond quickly and to do that and need the tools and policies to be able to tell people how to fix that issue. I mean, the Log4j fix was seven days after, so your developers should have been well aware of that. Your security team should have been sending the messages out. And I remember even fielding all the calls, all the fires that we had to put out when that happened. But yeah. >> I thought Brian Behlendorf's, you know, talk this morning was interesting 'cause he was making an attempt to say, "Hey, here's some things that you might not be thinking about that are likely to occur." And I wonder if you could, you know, comment on them and give us your thoughts as to how the industry generally, maybe Red Hat specifically, are thinking about dealing with them. He mentioned ChatGPT or other GPT to automate Spear phishing. He said the identity problem is still not fixed. Then he talked about free riders sniffing repos essentially for known vulnerabilities that are slow to fix. He talked about regulations that might restrict shipping code. So these are things that, you know, essentially, we can, they're on the radar, but you know, we're kind of putting out, you know, yesterday's fire. What are your thoughts on those sort of potential issues that we're facing and how are you guys thinking about it? >> Yeah, that's a great question, and I think it's twofold. One, it's brought up in front of a lot of security leaders in the space for them to be aware of it because security, it's a constant battle, constant war that's being fought. ChatGPT lowers the barrier of entry for a lot of them, say, would-be hackers or people like that to understand systems and create, let's say, simple manifests to leverage Kubernetes or leverage a misconfiguration. So as the barrier drops, we as a security team in security, let's say group organization, need to be able to respond and have our own tools to be able to combat that, and we do. So a lot of it is just making sure that we shore up our barriers and that people are aware of these threats. The harder part I think is educating the public and that's why you tend to see maybe the supply chain trend be a little bit ahead of the implementation. I think they're still, for example, like S-bombs and signing an attestation. I think that's still, you know, a year, two years, away from becoming, let's say commonplace, especially in something like a production environment. Again, so, you know, stay bleeding edge, and then make sure that you're aware of these issues and we'll be constantly coming to these calls and filling you in on what we're doing and make sure that we're up to speed. >> Yeah, so I'm hearing from folks like yourself that the, you know, you think of the future of Cloud Native Security. We're going to see continued emphasis on, you know, better integration of security into the DevSecOps. You're pointing out it's really, you know, the ops piece, that runtime that we really need to shore up. You can't just put it on the shoulders of the devs. And, you know, using security focused tools and best practices. Of course you hear a lot about that and the continued drive toward automation. My question is, you know, automation, machine learning, how, where are we in that maturity cycle? How much of that is being adopted? Sometimes folks are, you know, they embrace automation but it brings, you know, unknown, unintended consequences. Are folks embracing that heavily? Are there risks associated around that, or are we kind of through that knothole in your view? >> Yeah, that's a great question. I would compare it to something like a smart home. You know, we sort of hit a wall. You can automate so much, but it has to actually be useful to your teams. So when we're going and deploying ACS and using a cloud service, like one, you know, you want something that's a service that you can easily set up. And then the other thing is you want to start in inform mode. So you can't just automate everything, even if you're doing runtime enforcement, you need to make sure that's very, very targeted to exactly what you want and then you have to be checking it because people start new workloads and people get onboarded every week or month. So it's finding that balance between policies where you can inform the developer and the operations teams and that they give them the information to act. And that worst case you can step in as a security team to stop it, you know, during the onboarding of our ACS cloud service. We have an early access program and I get on-calls, and it's not even security team, it's the operations team. It starts with the security product, you know, and sometimes it's just, "Hey, how do I, you know, set this policy so my developers will find this vulnerability like a Log4Shell and I just want to send 'em an email, right?" And these are, you know, they have the tools and they can do that. And so it's nice to see the operations take on some security. They can automate it because maybe you have a NetSec security team that doesn't know Kubernetes or containers as well. So that shared responsibility is really useful. And then just again, making that automation targeted, even though runtime enforcement is a constant thing that we talk about, the amount that we see it in the wild where people are properly setting up admission controllers and it's acting. It's, again, very targeted. Databases, cubits x, things that are basically we all know is a no-go in production. >> Thank you for that. My last question, I want to go to the, you know, the hardest part and 'cause you're talking to customers all the time and you guys are working on the hardest problems in the world. What is the hardest aspect of securing, I'm going to come back to the software supply chain, hardest aspect of securing the software supply chain from the perspective of a security pro, software engineer, developer, DevSecOps Pro, and then this part b of that is, is how are you attacking that specifically as Red Hat? >> Sure, so as a developer, it's managing vulnerabilities with updates. As an operations team, it's keeping all the cluster, because you have a bunch of different teams working in the same environment, let's say, from a security team. It's getting people to listen to you because there are a lot of things that need to be secured. And just communicating that and getting it actionable data to the people to make the decisions as hard from a C-suite. It's getting the buy-in because it's really hard to justify the dollars and cents of security when security is constantly having to have these conversations with developers. So for ACS, you know, we want to be able to give the developer those tools. We also want to build the dashboards and reporting so that people can see their vulnerabilities drop down over time. And also that they're able to respond to it quickly because really that's where the dollars and cents are made in the product. It's that a Log4Shell comes out. You get immediately notified when the feeds are updated and you have a policy in action that you can respond to it. So I can go to my CISOs and say, "Hey look, we're limiting vulnerabilities." And when this came out, the developers stopped it in production and we were able to update it with the next release. Right, like that's your bread and butter. That's the story that you want to tell. Again, it's a harder story to tell, but it's easy when you have the information to be able to justify the money that you're spending on your security tools. Hopefully that answered your question. >> It does. That was awesome. I mean, you got data, you got communication, you got the people, obviously there's skillsets, you have of course, tooling and technology is a big part of that. Michael, really appreciate you coming on the program, sharing what's happening on the ground in Seattle and can't wait to have you back. >> Yeah. Awesome. Thanks again for having me. >> Yeah, our pleasure. All right. Thanks for watching our coverage of the Cloud Native Security Con. I'm Dave Vellante. I'm in our Boston studio. We're connecting to Palo Alto. We're connecting on the ground in Seattle. Keep it right there for more coverage. Be right back. (lively music)

>>Hey everyone, welcome to the cube. Lisa Martin here with Kevin Depu, senior Director Future Server Architecture at hpe. Kevin, it's great to have you on the program. You're gonna be breaking down everything that's exciting and compelling about Gen 11. How are you today? >>Thanks Lisa, and I'm doing great. >>Good, good, good. So let's talk about ProLiant Gen 11, the next generation of compute. I read some great stats on hpe.com. I saw that Gen 11 added 28 new world records while delivering up to 99% higher performance and 43% more energy efficiency than the previous version. That's amazing. Talk to me about Gen 11. What makes this update so compelling? >>Well, you talked about some of the stats regarding the performance and the power efficiency, and those are excellent. We partnered with amd, we've got excellent performance on these platforms. We have excellent power efficiency, but the advantage of this platform go beyond that. Today we're gonna talk a lot about cybersecurity and we've got a lot of security capabilities in these platforms. We've built on top of the security capabilities that we've had, generation over generation, we've got some new exciting capabilities we'll be talking about. So whether it's the performance, whether it's power efficient, whether it's security, all those capabilities are in this platform. Security is part of our dna. We put it into the design from the very beginning, and we've partnered with AMD to deliver what we think is a very compelling story. >>The security piece is absolutely critical. The to, we could have a, you know, an entire separate conversation on the cybersecurity landscape and the changes there. But one of the things I also noticed in the material on Gen 11 is that HPE says it's fundamental. What do you mean by that and what's new that makes it so fundamental? >>Well, by saying it's fundamental is security is a fundamental part of the platform. You need systems that are reliable. You need systems that have excellent performance. You need systems that are, have very good power efficiency, those things you talked about before, those are all very important to have a good server, but security's a part that's absolutely critical as well. So security is one of the fundamental capabilities of the platform. I had mentioned. We built on top of capabilities, capabilities like our silicon root of trust, which ensures that the firmware stack on these platforms is not compromised. Those are continuing this platform and have been expanded on. We have our trusted supply chain and we've expanded on that as well. We have a lot of security capabilities, our platform certificates, our IEB IDs. There's just a lot of security capabilities that are absolutely fundamental to these being a good solution because as we said, security is fundamental. It's an absolutely critical part of these platforms. >>Absolutely. For companies in every industry. I wanna talk a little bit about about one of the other things that HPE describes Gen 11 as as being uncompromising. And I wanted to understand what that means and what's the value add in it for customers? >>Yeah. Well, by uncompromising means we can't compromise on security. Security to what I said before, it's fundamental. It can't be promised. You have to have security be strong on these platforms. So one of the capabilities, which we're specifically talking about when we talk about Uncompromising is a capability called spdm. We've extended our silicon root of trust, which is one of our key technologies we've had since our Gen 10 platforms. We've extended that through something called spdm. We saw a problem in the industry with the ability to authenticate option cards and other devices in the system. Silicon Root of Trust verified many pieces of firmware in the platform, but one piece that it wasn't verifying was the option cards. And we needed, we knew we needed to solve this problem and we knew we couldn't do it a hundred percent on our own because we needed to work with our partners, whether it's a storage option card, a nick, or even devices in the future, we needed to make sure that we could verify that those were what they were meant to be. >>They weren't compromised, they weren't maliciously compromised and that we could authenticate them. So we worked with industry standards bodies to create the S P M specification. And what that allows us to do is authenticate the option cards in the systems. So that's one of our new capabilities that we've added in these platforms. So we've gone beyond securing all of the things that Silicon Real Trust secured in the past to extending that to the option cards and their firmware as well. So when we boot up one of these platforms, when we hand off to the OS and to the the customers software solution, they can be, they can rest assured that all the things that have run all that, that platform is not compromised. A bad guy has not gone in and changed things and that includes a bad guy with physical access to the platform. So that's why we have unpromised security in these platforms. >>Outstanding. That sounds like great work that's been done there and giving customers that piece of mind where security is concerned is table stakes for everybody across the organization. Kevin, you mentioned partners. I know HPE is extending protection to the partner ecosystem. I wanted to get a little bit more info on that from you. >>Yeah, we've worked with our option co card vendors, numerous partners across the industry to support spdm. We were the ones who kind of went to the, the industry standards bodies and said, we need to solve this problem. And we had agreement from everybody. Everybody agrees this is a problem that had to be solved. So, but to solve it, you've gotta have a partnership. We can't just do it on our own. There's a lot of things that we HPE can solve on our own. This is not one of them to be able to get a method that we could authenticate and trust the option cards in the system. We needed to work with our option card vendors. So that's something that we, we did. And we use also some capabilities that we work with some of our processor vendor partners as well. So working with partners across the industry, we were able to deliver spdm. >>So we know that option card, whether it's a storage card or a Nick Card or, or GPUs in the future, those, those may not be there from day one, but we know that those option cards are what they intended because you could do an attack where you compromise the option card, you compromise the firmware in that option card and option cards have the ability to read and write to memory using something called dma. And if those cards are running firmware that's being created by a bad guy, they can do a lot of, of very costly attacks. I mean we, there's a lot of statistics that showed just how, how costly cybersecurity attacks are. If option cards have been compromised, you can do some really bad things. So this is how we can trust those option cards. And we had to partner with those, those partners in the industry to both define the spec and both sides had to implement to that specification so that we could deliver the solution we're delivering. >>HPE is such a strong partner ecosystem. You did a great job of articulating the value in this for customers. From a security perspective, I know that you're also doing a lot of collaboration and work with amd. Talk to me a little bit about that and the value in it for your joint customers. >>Yeah, absolutely. AMD is a longstanding partner. We actually started working with AMD about 20 years ago when we delivered our first AMD opton based platform, the HP pro, HP Pliant, DL 5 85. So we've got a long engineering relationship with AMD and we've been making products with AMD since they introduced their epic generation processor in 2017. That's when AMD really upped the secure their security game. They created capabilities with their AMD secure processor, their secure encryption virtualization, their memory encryption technologies. And we work with AMD long before platforms actually release. So they come to us with their ideas, their designs, we collaborate with them on things we think are valuable when we see areas where they can do things better, we provide feedback. So we really have a partnership to make these processors better. And it's not something where we just work with them for a short amount of time and deliver a product. >>We're working with them for years before those products come out. So that partnership allows both parties to create better platforms cuz we understand what they're capable of, they understand what our needs are as a, as a server provider. And so we help them make their processors better and they help us make our products better. And that extends in all areas, whether it's performance, power, efficiency, but very importantly in what we're talking about here, security. So they have got an excellent security story with all of their technologies. Again, memory encryption. They, they've got some exceptional technologies there. All their secure encryption, virtualization to secure virtualized environments, those are all things that they excel at. And we take advantage of those in our designs. We make sure that those so work with our servers as part of a solution >>Sounds like a very deeply technically integrated and longstanding relationship that's really symbiotic for both sides. I wanted to get some information from you on HPE server security optimized service. Talk to me about what that is. How does that help HP help its customers get around some of those supply chain challenges that are persistent? >>Yeah, what that is is with our previous generation of products, we announced something called our HPE trusted supply chain and but that was focused on the US market with the solution for gen 11. We've expanded that to other markets. It's, it's available from factories other than the ones in our us it's available for shipping products to other geographies. So what that really was is taking the HPE trusted supply chain and expanding it to additional geographies throughout the world, which provides a big, big benefit for our non-US based customers. And what that is, is we're trying to make sure that the server that we ship out of our factories is indeed exactly what that customer is getting. So try to prevent any possibility of attack in the supply chain going from our factories to the customer. And if there is an attack, we can detect it and the customer knows about it. >>So they won't deploy a system that's been compromised cuz there, there have been high profile cases of supply chain attacks. We don't want to have that with our, our customers buying our Reliant products. So we do things like enable you I Secure Boot, which is an ability to authenticate the, what's called a u i option ROM driver on option cards. That's enabled by default. Normally that's not enabled by default. We enable our high security mode in our ILO product. We include our intrusion tech detection technology option, which is an optional feature, but it's their standard when you buy one of the boxes with this, this capability, this trusted supply chain capability. So there's a lot of capabilities that get enabled at the factory. We also enable server configuration lock, which allows a customer to detect, get a bad guy, modify anything in the platform when it transits from our factory to them. So what it allows a customer to do is get that platform and know that it is indeed what it is intended to be and that it hasn't been attacked and we've now expanded that to many geographies throughout the world. >>Excellent. So much more coverage across the world, which is so incredibly important. As cyber attacks continue to rise year over year, the the ransomware becomes a household word, the ransoms get even more expensive, especially considering the cybersecurity skills gap. I'm just wondering what are some of the, the ways in which everything that you've described with Gen 11 and the HPE partner ecosystem with A and B for example, how does that help customers to get around that security skills gap that is present? >>Well, the key thing there is we care about our customer security. So as I mentioned, security is in our dna. We do, we consider security in everything. We do every update to firm where we make, when we do the hardware design, whatever we're doing, we're always considering what could a bad guy do? What could a bad guy take advantage of and attempt to prevent it. And AMD does the same thing. You can look at all the technologies they have in their AMD processor. They're, they're making sure their processor is secure. We're making sure our platform is secure so the customer doesn't have to worry about it. So that's something the customer can trust us. They can trust the amd so they know that that's not the area where they, they have to expend their bandwidth. They can extend their bandwidth on the security on other parts of the, the solution versus knowing that the platform and the CPU is secure. >>And beyond that, we create features and capabilities that they can take advantage of in the, in the case of amd, a lot of their capabilities are things that the software stack and the OS can take advantage of. We have capabilities on the client side that the software and that they can take advantage of, whether it's server configuration lock or whatever. We try to create features that are easy for them to use to make their environments more secure. So we're making things that can trust the platform, they can trust the processor, they don't have to worry about that. And then we have features and capabilities that lets them solve some of the problems easier. So we're, we're trying to, to help them with that skills gap by making certain things easier and making certain things that they don't even have to worry about. >>Right. It sounds like allowing them to be much more strategic about the security skills that they do have. My last question for you, Kevin, is Gen 11 available now? Where can folks go to get their hands on it? >>So Gen 11 was announced earlier this month. The products will actually be shipping before the end of this year, before the end of 2022. And you can go to our website and find all about our compute security. So it all that information's available on our website. >>Awesome. Kevin, it's been a pleasure talking to you, unpacking Gen 11, the value in it, why security is fundamental to the uncompromising nature with which HPE and partners have really updated the system and the rest of world coverage that you guys are enabling. We appreciate your insights on your time, Kevin. >>Thank you very much, Lisa. Appreciate >>It. And we want to let you and the audience know, check out hpe.com/info/compute for more info on 11. Thanks for watching.

foreign welcome back to re invent 2022 we're wrapping up four days well one evening and three solid days wall-to-wall of cube coverage I'm Dave vellante John furrier's birthday is today he's on a plane to London to go see his nephew get married his his great Sister Janet awesome family the furriers uh spanning the globe and uh and John I know you wanted to be here you're watching in Newark or you were waiting to uh to get in the plane so all the best to you happy birthday one year the Amazon PR people brought a cake out to celebrate John's birthday because he's always here at AWS re invented his birthday so I'm really pleased to have two really special guests uh former Cube host Cube Alum great wikibon contributor Stu miniman now with red hat still good to see you again great to be here Dave yeah I was here for that cake uh the twitterverse uh was uh really helping to celebrate John's birthday today and uh you know always great to be here with you and then with this you know Awesome event this week and friend of the cube of many time Cube often Cube contributor as here's a cube analyst this week as his own consultancy sarbj johal great to see you thanks for coming on good to see you Dave uh great to see you stu I'm always happy to participate in these discussions and um I enjoy the discussion every time so this is kind of cool because you know usually the last day is a getaway day and this is a getaway day but this place is still packed I mean it's I mean yeah it's definitely lighter you can at least walk and not get slammed but I subjit I'm going to start with you I I wanted to have you as the the tail end here because cause you participated in the analyst sessions you've been watching this event from from the first moment and now you've got four days of the Kool-Aid injection but you're also talking to customers developers Partners the ecosystem where do you want to go what's your big takeaways I think big takeaways that Amazon sort of innovation machine is chugging along they are I was listening to some of the accessions and when I was back to my room at nine so they're filling the holes in some areas but in some areas they're moving forward there's a lot to fix still it doesn't seem like that it seems like we are done with the cloud or The Innovation is done now we are building at the millisecond level so where do you go next there's a lot of room to grow on the storage side on the network side uh the improvements we need and and also making sure that the software which is you know which fits the hardware like there's a specialized software um sorry specialized hardware for certain software you know so there was a lot of talk around that and I attended some of those sessions where I asked the questions around like we have a specialized database for each kind of workload specialized processes processors for each kind of workload yeah the graviton section and actually the the one interesting before I forget that the arbitration was I asked that like why there are so many so many databases and IRS for the egress costs and all that stuff can you are you guys thinking about reducing that you know um the answer was no egress cost is not a big big sort of uh um show stopper for many of the customers but but the from all that sort of little discussion with with the folks sitting who build these products over there was that the plethora of choice is given to the customers to to make them feel that there's no vendor lock-in so if you are using some open source you know um soft software it can be on the you know platform side or can be database side you have database site you have that option at AWS so this is a lot there because I always thought that that AWS is the mother of all lock-ins but it's got an ecosystem and we're going to talk about exactly we'll talk about Stu what's working within AWS when you talk to customers and where are the challenges yeah I I got a comment on open source Dave of course there because I mean look we criticized to Amazon for years about their lack of contribution they've gotten better they're doing more in open source but is Amazon the mother of all lock-ins many times absolutely there's certain people inside Amazon I'm saying you know many of us talk Cloud native they're like well let's do Amazon native which means you're like full stack is things from Amazon and do things the way that we want to do things and you know I talk to a lot of customers they use more than one Cloud Dave and therefore certain things absolutely I want to Leverage The Innovation that Amazon has brought I do think we're past building all the main building blocks in many ways we are like in day two yes Amazon is fanatically customer focused and will always stay that way but you know there wasn't anything that jumped out at me last year or this year that was like Wow new category whole new way of thinking about something we're in a vocals last year Dave said you know we have over 200 services and if we listen to you the customer we'd have over two thousand his session this week actually got some great buzz from my friends in the serverless ecosystem they love some of the things tying together we're using data the next flywheel that we're going to see for the next 10 years Amazon's at the center of the cloud ecosystem in the IT world so you know there's a lot of good things here and to your point Dave the ecosystem one of the things I always look at is you know was there a booth that they're all going to be crying in their beer after Amazon made an announcement there was not a tech vendor that I saw this week that was like oh gosh there was an announcement and all of a sudden our business is gone where I did hear some rumbling is Amazon might be the next GSI to really move forward and we've seen all the gsis pushing really deep into supporting Cloud bringing workloads to the cloud and there's a little bit of rumbling as to that balance between what Amazon will do and their uh their go to market so a couple things so I think I think we all agree that a lot of the the announcements here today were taping seams right I call it and as it relates to the mother of all lock-in the reason why I say that it's it's obviously very much a pejorative compare Oracle company you know really well with Amazon's lock-in for Amazon's lock-in is about bringing this ecosystem together so that you actually have Choice Within the the house so you don't have to leave you know there's a there's a lot to eat at the table yeah you look at oracle's ecosystem it's like yeah you know oracle is oracle's ecosystem so so that is how I think they do lock in customers by incenting them not to leave because there's so much Choice Dave I agree with you a thousand I mean I'm here I'm a I'm a good partner of AWS and all of the partners here want to be successful with Amazon and Amazon is open to that it's not our way or get out which Oracle tries how much do you extract from the overall I.T budget you know are you a YouTube where you give the people that help you create a large sum of the money YouTube hasn't been all that profitable Amazon I think is doing a good balance of the ecosystem makes money you know we used to talk Dave about you know how much dollars does VMware make versus there um I think you know Amazon is a much bigger you know VMware 2.0 we used to think talk about all the time that VMware for every dollar spent on VMware licenses 15 or or 12 or 20 were spent in the ecosystem I would think the ratio is even higher here sarbji and an Oracle I would say it's I don't know yeah actually 1 to 0.5 maybe I don't know but I want to pick on your discussion about the the ecosystem the the partner ecosystem is so it's it's robust strong because it's wider I was I was not saying that there's no lock-in with with Amazon right AWS there's lock-in there's lock-in with everything there's lock-in with open source as well but but the point is that they're they're the the circle is so big you don't feel like locked in but they're playing smart as well they're bringing in the software the the platforms from the open source they're picking up those packages and saying we'll bring it in and cater that to you through AWS make it better perform better and also throw in their custom chips on top of that hey this MySQL runs better here so like what do you do I said oh Oracle because it's oracle's product if you will right so they are I think think they're filing or not slenders from their go to market strategy from their engineering and they listen to they're listening to customers like very closely and that has sort of side effects as well listening to customers creates a sprawl of services they have so many services and I criticized them last year for calling everything a new service I said don't call it a new service it's a feature of a existing service sure a lot of features a lot of features this is egress our egress costs a real problem or is it just the the on-prem guys picking at the the scab I mean what do you hear from customers so I mean Dave you know I I look at what Corey Quinn talks about all the time and Amazon charges on that are more expensive than any other Cloud the cloud providers and partly because Amazon is you know probably not a word they'd use they are dominant when it comes to the infrastructure space and therefore they do want to make it a little bit harder to do that they can get away with it um because um yeah you know we've seen some of the cloud providers have special Partnerships where you can actually you know leave and you're not going to be charged and Amazon they've been a little bit more flexible but absolutely I've heard customers say that they wish some good tunning and tongue-in-cheek stuff what else you got we lay it on us so do our players okay this year I think the focus was on the upside it's shifting gradually this was more focused on offside there were less talk of of developers from the main stage from from all sort of quadrants if you will from all Keynotes right so even Werner this morning he had a little bit for he was talking about he he was talking he he's job is to Rally up the builders right yeah so he talks about the go build right AWS pipes I thought was kind of cool then I said like I'm making glue easier I thought that was good you know I know some folks don't use that I I couldn't attend the whole session but but I heard in between right so it is really adopt or die you know I am Cloud Pro for last you know 10 years and I think it's the best model for a technology consumption right um because of economies of scale but more importantly because of division of labor because of specialization because you can't afford to hire the best security people the best you know the arm chip designers uh you can't you know there's one actually I came up with a bumper sticker you guys talked about bumper sticker I came up with that like last couple of weeks The Innovation favorite scale they have scale they have Innovation so that's where the Innovation is and it's it's not there again they actually say the market sets the price Market you as a customer don't set the price the vendor doesn't set the price Market sets the price so if somebody's complaining about their margins or egress and all that I think that's BS um yeah I I have a few more notes on the the partner if you you concur yeah Dave you know with just coming back to some of this commentary about like can Amazon actually enable something we used to call like Community clouds uh your companies like you know Goldman and NASDAQ and the like where Industries will actually be able to share data uh and you know expand the usage and you know Amazon's going to help drive that API economy forward some so it's good to see those things because you know we all know you know all of us are smarter than just any uh single company together so again some of that's open source but some of that is you know I think Amazon is is you know allowing Innovation to thrive I think the word you're looking for is super cloud there well yeah I mean it it's uh Dave if you want to go there with the super cloud because you know there's a metaphor for exactly what you described NASDAQ Goldman Sachs we you know and and you know a number of other companies that are few weeks at the Berkeley Sky Computing paper yeah you know that's a former supercloud Dave Linthicum calls it metacloud I'm not really careful I mean you know I go back to the the challenge we've been you know working at for a decade is the distributed architecture you know if you talk about AI architectures you know what lives in the cloud what lives at the edge where do we train things where do we do inferences um locations should matter a lot less Amazon you know I I didn't hear a lot about it this show but when they came out with like local zones and oh my gosh out you know all the things that Amazon is building to push out to the edge and also enabling that technology and software and the partner ecosystem helps expand that and Pull It in it's no longer you know Dave it was Hotel California all of the data eventually is going to end up in the public cloud and lock it in it's like I don't think that's going to be the case we know that there will be so much data out at the edge Amazon absolutely is super important um there some of those examples we're giving it's not necessarily multi-cloud but there's collaboration happening like in the healthcare world you know universities and hospitals can all share what they're doing uh regardless of you know where they live well Stephen Armstrong in the analyst session did say that you know we're going to talk about multi-cloud we're not going to lead with it necessarily but we are going to actually talk about it and that's different to your points too than in the fullness of time all the data will be in the cloud that's a new narrative but go ahead yeah actually Amazon is a leader in the cloud so if they push the cloud even if they don't say AWS or Amazon with it they benefit from it right and and the narrative is that way there's the proof is there right so again Innovation favorite scale there are chips which are being made for high scale their software being tweaked for high scale you as a Bank of America or for the Chrysler as a typical Enterprise you cannot afford to do those things in-house what cloud providers can I'm not saying just AWS Google cloud is there Azure guys are there and few others who are behind them and and you guys are there as well so IBM has IBM by the way congratulations to your red hat I know but IBM won the award um right you know very good partner and yeah but yeah people are dragging their feet people usually do on the change and they are in denial denial they they drag their feet and they came in IBM director feed the cave Den Dell drag their feed the cave in yeah you mean by Dragon vs cloud deniers cloud deniers right so server Huggers I call them but they they actually are sitting in Amazon Cloud Marketplace everybody is buying stuff from there the marketplace is the new model OKAY Amazon created the marketplace for b2c they are leading the marketplace of B2B as well on the technology side and other people are copying it so there are multiple marketplaces now so now actually it's like if you're in in a mobile app development there are two main platforms Android and Apple you first write the application for Apple right then for Android hex same here as a technology provider as and I I and and I actually you put your stuff to AWS first then you go anywhere else yeah they are later yeah the Enterprise app store is what we've wanted for a long time the question is is Amazon alone the Enterprise app store or are they partner of a of a larger portfolio because there's a lot of SAS companies out there uh that that play into yeah what we need well and this is what you're talking about the future but I just want to make a point about the past you talking about dragging their feet because the Cube's been following this and Stu you remember this in 2013 IBM actually you know got in a big fight with with Amazon over the CIA deal you know and it all became public judge wheeler eviscerated you know IBM and it ended up IBM ended up buying you know soft layer and then we know what happened there and it Joe Tucci thought the cloud was Mosey right so it's just amazing to see we have booksellers you know VMware called them books I wasn't not all of them are like talking about how great Partnerships they are it's amazing like you said sub GC and IBM uh with the the GSI you know Partnership of the year but what you guys were just talking about was the future and that's what I wanted to get to is because you know Amazon's been leading the way I I was listening to Werner this morning and that just reminded me of back in the days when we used to listen to IBM educate us give us a master class on system design and decoupled systems and and IO and everything else now Amazon is you know the master educator and it got me thinking how long will that last you know will they go the way of you know the other you know incumbents will they be disrupted or will they you know keep innovating maybe it's going to take 10 or 20 years I don't know yeah I mean Dave you actually you did some research I believe it was a year or so ago yeah but what will stop Amazon and the one thing that worries me a little bit um is the two Pizza teams when you have over 202 Pizza teams the amount of things that each one of those groups needs to take care of was more than any human could take care of people burn out they run out of people how many amazonians only last two or three years and then leave because it is tough I bumped into plenty of friends of mine that have been you know six ten years at Amazon and love it but it is a tough culture and they are driving werner's keynote I thought did look to from a product standpoint you could say tape over some of the seams some of those solutions to bring Beyond just a single product and bring them together and leverage data so there are some signs that they might be able to get past some of those limitations but I still worry structurally culturally there could be some challenges for Amazon to keep the momentum going especially with the global economic impact that we are likely to see in the next year bring us home I think the future side like we could talk about the vendors all day right to serve the community out there I think we should talk about how what's the future of technology consumption from the consumer side so from the supplier side just a quick note I think the only danger AWS has has that that you know Fred's going after them you know too big you know like we will break you up and that can cause some disruption there other than that I think they they have some more steam to go for a few more years at least before we start thinking about like oh this thing is falling apart or anything like that so they have a lot more they have momentum and it's continuing so okay from the I think game is on retail by the way is going to get disrupted before AWS yeah go ahead from the buyer's side I think um the the future of the sort of Technology consumption is based on the paper uh use and they actually are turning all their services to uh they are sort of becoming serverless behind the scenes right all analytics service they had one service left they they did that this year so every service is serverless so that means you pay exactly for the amount you use the compute the iops the the storage so all these three layers of course Network we talked about the egress stuff and that's a problem there because of the network design mainly because Google has a flatter design and they have lower cost so so they are actually squeezing the their their designing this their services in a way that you don't waste any resources as a buyer so for example very simple example when early earlier In This Cloud you will get a VM right in Cloud that's how we started so and you can get 20 use 20 percent of the VM 80 is getting wasted that's not happening now that that has been reduced to the most extent so now your VM grows as you grow the usage and if you go higher than the tier you picked they will charge you otherwise they will not charge you extra so that's why there's still a lot of instances like many different types you have to pick one I think the future is that those instances will go away the the instance will be formed for you on the fly so that is the future serverless all right give us bumper sticker Stu and then Serb G I'll give you my quick one and then we'll wrap yeah so just Dave to play off of sharp G and to wrap it up you actually wrote about it on your preview post for here uh serverless we're talking about how developers think about things um and you know Amazon in many ways you know is the new default server uh you know for the cloud um and containerization fits into the whole serverless Paradigm uh it's the space that I live in uh you know every day here and you know I was happy to see the last few years serverless and containers there's a blurring a line and you know subject we're still going to see VMS for a long time yeah yeah we will see that so give us give us your book Instagram my number six is innovation favorite scale that's my bumper sticker and and Amazon has that but also I I want everybody else to like the viewers to take a look at the the Google Cloud as well as well as IBM with others like maybe you have a better price to Performance there for certain workloads and by the way one vendor cannot do it alone we know that for sure the market is so big there's a lot of room for uh Red Hats of the world and and and Microsoft's the world to innovate so keep an eye on them they we need the competition actually and that's why competition Will Keep Us to a place where Market sets the price one vendor doesn't so the only only danger is if if AWS is a monopoly then I will be worried I think ecosystems are the Hallmark of a great Cloud company and Amazon's got the the biggest and baddest ecosystem and I think the other thing to watch for is Industries building on top of the cloud you mentioned the Goldman Sachs NASDAQ Capital One and Warner media these all these industries are building their own clouds and that's where the real money is going to be made in the latter half of the 2020s all right we're a wrap this is Dave Valente I want to first of all thank thanks to our great sponsors AWS for for having us here this is our 10th year at the cube AMD you know sponsoring as well the the the cube here Accenture sponsor to third set upstairs upstairs on the fifth floor all the ecosystem partners that came on the cube this week and supported our mission for free content our content is always free we try to give more to the community and we we take back so go to thecube.net and you'll see all these videos go to siliconangle com for all the news wikibon.com I publish weekly a breaking analysis series I want to thank our amazing crew here you guys we have probably 30 35 people unbelievable our awesome last session John Walls uh Paul Gillen Lisa Martin Savannah Peterson John Furrier who's on a plane we appreciate Andrew and Leonard in our ear and all of our our crew Palo Alto Boston and across the country thank you so much really appreciate it all right we are a wrap AWS re invent 2022 we'll see you in two weeks we'll see you two weeks at Palo Alto ignite back here in Vegas thanks for watching thecube the leader in Enterprise and emerging Tech coverage [Music]

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

(upbeat music) >> Okay, welcome back everyone, Cube coverage live on the floor in the Moscone center in San Francisco, California. I'm John Furrier host of the Cube. AWS summit 2022 is here in San Francisco, we're back in live events. Of course, Amazon summit in New York city is coming, Amazon summit this summer we'll be there as well. We've got a great guest Mike Miller, GN of AI devices at AWS always one of my favorite interviews. We've got a little prop here, we got the car, DeepRacer, very popular at the events. Mike, welcome to the Cube. Good to see you. >> Hey John, thank you for having me. It's really exciting to be back and chat with you a little bit about DeepRacer. >> Well I want to get into the prop in a second, not the prop, the product. >> Yeah. >> So DeepRacer program, you got the race track here. Just explain what it is real quick, we'll get that out of the way. >> Absolutely so, well, you know that AI, AWS is passionate about making AI and ML more accessible to developers of all skill levels. So DeepRacer is one of our tools to do that. So DeepRacer is a 3D cloud-based racing simulator, a 1/18th scale autonomously driven car and a league to add a little spicy competition into it. So developers can start with the cloud-based simulator where they're introduced to reinforcement learning which basically teaches the, our car to drive around a track through trial and error and of course you're in a virtual simulator so it's easy for it to make mistakes and restart. Then once that model is trained, it's downloaded to the car which then can drive around a track autonomously, kind of making its own way and of course we track lap time and your successful lap completions and all of that data feeds into our league to try to top the leaderboard and win prizes. >> This is the ultimate gamification tool. (chuckles) >> Absolutely >> Making it fun to learn about machine learning. All right, let's get into the car, let's get into the showcase of the car. show everyone what's going on. >> Absolutely. So this is our 1/18th scale autonomously driven car. It's built off of a monster truck chassis so you can see it's got four wheel drive, it's got steering in the front, we've got a camera on the front. So the camera is the, does the sensing to the compute board that's driven by an Intel atom a processor on the, on the vehicle, that allows it to make sense of the in front of it and then decide where it wants to drive. So you take the car, you download your trained model to it and then it races around the track. >> So the front is the camera. >> The front is the camera, that's correct. >> Okay, So... >> So it's a little bit awkward but we needed to give it plenty of room here so that I can actually see the track in front of it. >> John: It needs eyes. >> Yep. That's exactly right. >> Awesome. >> Yes. >> And so I got to buy that if I'm a developer. >> So, developers can start in two ways, they can use our virtual racing experience and so there's no hardware cost for that, but once you want the experience, the hands on racing, then the car is needed but if you come to one of our AWS summits, like here in San Francisco or anywhere else around the world we have one or more tracks set up and you can get hands on, you can bring the model that you trained at home download it to a car and see it race around the track. >> So use a car here. You guys are not renting cars, but you're letting people use the cars. >> Absolutely. >> Can I build my own car or does it have to be assembled by AWS? >> Yeah, we, we sell it as a, as a kit that's already assembled because we've got the specific compute board in there, that Intel processor and all of the software that's already built on there that knows how to drive around the track. >> That's awesome, so talk about the results. What's going on? What's the feedback from developers? Obviously it's a nerd dream, people like race cars, people love formula one now, all the racing there. IOT is always an IOT opportunity as well. >> Absolutely, and as you said, gamification, right? And so what we found and what we thought we would find was that adding in those sort of ease of learning so we make it the on-ramp to machine learning very easy. So developers of all skill levels can take advantage of this, but we also make it fun by kind of gamifying it. We have different challenges every month, we have a leader board so you can see how you rank against your peers and actually we have split our league into two, there's an open division which is more designed for novices so you'll get rewarded for just participating and then we have a pro league. So if you're one of the top performers in the open league each month, you graduate and you get to race against the big boys in the pro leagues. >> What's the purse? >> Oh, the, (John laughing) we definitely have cash and prizes that happen, both every month. We have prizes cause we do races every month and those winners of those races all get qualified to race at the championship, which of course happens in Las Vegas at re:Invent. So we bring all the winners to re:Invent and they all race against each other for the grand prize the big trophy and the, and the, and the cash prize. >> Well, you know, I'm a big fan of what you guys are doing so I'm kind of obviously biased on this whole program but you got to look at trend of what's going on in eSports and the online engagement is off the charts, are there plans to kind of make this more official and bigger? Is there traction there or is this just all part of the Amazon goodness, love that you guys give back? I mean, obviously it's got traction. >> Yeah. I mean, the thing that's interesting about eSports is the number of young people who are getting into it and what we saw over the last couple years is that, there were a lot of students who were adopting DeepRacer but there were some hurdles, you know, it wasn't really designed for them. So what we did was we made some changes and at the beginning of this year we launched a student focused DeepRacer program. So they get both free training every month, they get free educational materials and their own private league so they know students can race against other students, as part of that league. >> John: Yeah. >> So that was really our first step in kind of thinking about those users and what do we need to do to cater to their kind of unique needs? >> Tell about some of the power dynamics or the, or not power dynamics, the group dynamics around teams and individuals, can I play as an individual? Do I, do I have to be on a team? Can I do teams? How does that look? How do you think about those things? >> Yeah, absolutely. Great, great question. The primary way to compete is individually. Now we do have an offering that allows companies to use DeepRacer to excite and engage their own employees and this is where operating as a team and collaborating with your coworkers comes into play so, if, if I may there's, you know, Accenture and JPMC are a couple big customers of ours, really strong partners. >> John: Yeah. >> Who've been able to take advantage of DeepRacer to educate their workforce. So Accenture ran a 24 hour round the, round the globe race a couple years ago, encouraging their employees to collaborate and form teams to race and then this past year JPMC, had over 3000 of their builders participate over a three month period where they ran a private league and they went on to win the top two spots, first place and second place. >> John: Yeah. >> At reinvent last year. >> It reminds me the NASCAR and all these like competitions, the owners have multiple cars on the race. Do you guys at re:Invent have to start cutting people like, only two submissions or is it free for all? >> Well, you have to qualify to get to the races at re:invent so it's very, it's very cutthroat leading up to that point. We've got winners of our monthly virtual contests, the winners like of the summit races will also get invited. So it's interesting, this dynamic, you'll have some people who won virtual races, some people who won physical races, all competing together. >> And do you guys have a name for the final cup or is it like what's the, what's the final, how do you guys talk about the prizes and the... >> It's, it's the DeepRacer Championship Cup of course. >> John: Of course. (laughter) >> Big silver cup, you get to hoist it and... >> Are the names inscribed in it, is it like the Stanley cup or is it just one. >> It's a unique one, so you get to hold onto it each year. The champion gets their own version of the cup. >> It's a lot of fun. I think it's really kind of cool. What's the benefits for a student? Talk about the student ones. >> Yeah. Yeah. >> So I'm a student I'm learning machine learning, what's in it for me is a career path and the fund's obvious, I see that. >> Yeah absolutely. You know, the, for students, it's a hands on way that's a very easy on-ramp to machine learning and you know, one of the things, as I mentioned we're passionate about making it accessible to all. Well, when we mean all we were really do mean all. So, we've got a couple partners who are passionate about the same thing, right? Which is how do we, if, if AI and ML is going to transform our world and solve our most challenging problems, how can we get the right minds from all walks of life and all backgrounds to learn machine learning and get engaged? So with two of our partners, so with Udacity and with Intel we launched a $10 million AWS, AI and ML scholarship program and we built it around DeepRacer. So not only can students who are college and high school students, age 16 and over can use DeepRacer, can learn about machine learning and then get qualified to win one of several thousand scholarships. >> Any other promotions going on that people should know about? >> Yeah, one, one final one is, so we talked about enterprises like JPMC and Accenture, so we've got a promotion that we just started yesterday. So if you are an enterprise and you want to host a DeepRacer event at your company to excite your employees and get 'em collaborating more, if you have over 50 employees participating, we're going to give you up to a hundred thousand dollars in AWS credits, to offset the costs of running your DeepRacer event at your, at your company so >> That's real money. >> Yeah. Real, real, real exciting I think for companies now to pick up DeepRacer. >> So, I mean, honestly, I know Andy Jassy, I have many sports car conversations with him. He's a sports guy, he's now the CEO of Amazon, gets to go all the sporting events, NFL. I wish I could bring the Cube there but, we'll stick with with cloud for now. You got to look at the purse kind of thing. I'm interested in like the whole economic point of cause I mean, forget the learning for side for a second which is by the way awesome. This is great competition. You got leader boards, you got regional activities, you got a funneling system laddering up to the final output. >> And we've really done a decent job and, and of adding capabilities into that user experience to make it more engaging. You can see the countries that the different competitors are from, you can see how the lap times change over time, you know, we give awards as I mentioned, the two divisions now. So if you're not super competitive, we'll reward you for just participating in that open league but if you want to get competitive, we'll even better rewards monthly in the Pro League. >> Do you guys have any conversations internally like, this is getting too big, we might have to outsource it or you keep it in inside the fold? (laughter) >> We, we love DeepRacer and it's so much fun running this, >> You see where I'm going with this. You see where I'm going with this right? The Cube might want to take this over. >> Hey. >> And you know >> We're always looking for partners and sponsors who can help us make it bigger so, absolutely. >> It's a good business opportunity. I just love it. Congratulations, great stuff. What's the big learning in this, you know, as a as an executive, you look back you got GM, AI super important and, and I think it is great community, communal activity as well. What's the learning, what have you learned from this over the years besides that it's working but like what's the big takeaway? >> Yeah, I mean. We've got such a wide range of developers and builders who are customers that we need to provide a variety of opportunities for people to get hands on and there's no better way to learn a complex technology like AI and ML than getting hands on and seeing, you know, physically the result of the AI and I think that's been the biggest learning, is that just having the hands on and the sort of element of watching what it does, just light bulbs go off. When, when developers look at this and they start piecing the, the puzzle pieces together, how they can benefit. >> So I have to ask the question that might be on other peoples minds, maybe it's not, maybe I'm just thinking really dark here but gamers love to hack and they love cheat codes, they love to get, you know, get into the system, any attempts to do a little hacking to win the, the the game, have you guys, is there, you know? >> Well, well, you know, last year we, we we released an open source version of the vehicle so that people could start using it as a platform to explore and do that kind of hacking and give them an opportunity build on top of it. >> So using mods, mods modules, we can mod out on this thing. >> Yeah, absolutely. If you go to deepracer.com, we have sort of extensions page there, and you can see, somebody mounted a Nerf cannon onto the top of this, somebody built a computer vision model that could recognize you know, rodents and this thing would kind of drive to scare 'em, all kinds of fun topics. >> So it's a feature, not a bug. >> Absolutely. >> Open it up. >> Yeah. >> And also on transparency, if you have the source code out there you guys can have some review. >> Yeah. The whole idea is like, let's see what developers, >> It's really not hackable. It's not hackable. >> Yeah, I mean, for the, if you think about it when we do the races, we bring the cars ourselves, the only way a developer interacts is by giving us their trained models so... >> And you, do you guys review the models? Nothing to review, right? >> Yeah. There's nothing really to review. It's all about, you know, there, there was a model that we saw one time where the car went backwards and then went forwards across the finish line but we, we, we gently told them, well that's really not a valid way to race. >> That was kind of a hack, not really a hack. That was a hack hack. (laughter) That was just a growth hack. >> Exactly, but everybody just has a lot of fun with it across the board. >> Mike, great, thanks for coming on. Love the prop. Thanks for bringing the car on, looks great. Success every year. I want to see the purse, you know, big up to $1,000,000 you know, the masters, you know, tournament. >> Someday. (John chuckles) >> You guys.. >> Thank you for having me John. >> DeepRacer again, Fun Start has a great way to train people on machine learning, IOT device, turns into a league of its own. Great stuff for people to learn, especially students and people in companies, but the competitive juices flowing. That's what it's all about, having fun, learning. It's the Cube here in San Francisco. Stay with us for more coverage after this short break. (gentle music)

[Music] welcome everyone to thecube's presentation of the aws startup showcase data as code this is season two episode two of our ongoing series covering exciting startups in the aws ecosystem to talk about data and analytics i'm your host lisa martin i have a cube alumni here with me socket sarah the ceo and founder of nexla he's here to talk about a future of automated data engineering socket welcome back great to see you lisa thank you for having me pleasure to be here again let's dig into nexla's mission ready to use data in the hands of every user what does that mean that means that you know every organization what what are they trying to do with data they want to make use of data they want to make decisions from data they want to make data a part of their business right the challenge is that every function in an organization today needs to leverage data whether it is finance whether it is hr whether it is marketing sales or product the problem for companies is that for each of these users into each of these teams the data is not ready for them to use as it is there is a lot that goes on before the data can be in their hands and it's in the tools that they like to work with and that's where a lot of data engineering happens today i would say that is by far one of the biggest bottlenecks today for companies in accelerating their business and being you know truly data-driven so talk to me about what makes nexla unique when you're in customer conversations as every company these days in every industry has to be a data company what do you tell them about what differentiates you yeah one of the biggest challenges out there is that the variety of data that companies work with is growing tremendously you know every sas application you use becomes a data source every type of database every type of user event anything can be a source of data now it is a tremendous engineering challenge for companies to make the data usable and the biggest challenge there is people companies just cannot have enough people to write that code to make the data engineering happen and where we come in with a very unique value is how to start thinking about making this whole process much faster much more automated at the end of the day lisa time to value and time to results is by far the number one thing on top of mind for customers time to value is critical we're all thin on patients these days whether we're in our consumerizer our business lives but being able to get access to data to make intelligent decisions whether it's on something that you're going to buy or a product or service you're going to deliver is really critical give me a snapshot of some of the users of nexla yeah the users of nexla are actually across different industries one of the main one of the interesting things is that the data challenges whether you are in financial services whether you are in retail e-commerce whether you are in healthcare they are very similar is basically getting connected to all these data systems and having the data now what people do with the data is very specific to their industry so for example within the e-commerce world or retail world itself you know companies from the likes of bed bath beyond and forever 21 and poshmark which are retailers or e-commerce companies they use nexla today to bring a lot of data in uh so do delivery companies like dodash and instacart and you know so do for example logistics providers like you know narwhal or customer loyalty and customer data companies like yacht pro so across the board for example just in retail we cover a whole bunch of companies got it now let's dig into you're here to talk about the future of automated data engineering talk to me about data engineering what is it let's define it and crack it open yeah um data engineering is i would say by far one of the hottest areas of work today the one of the hardest people to hire if you're looking for one data engineering is basically um all the code you know the process and the people that is basically connecting to their system so just to give a very practical example right for um for somebody in e-commerce let's say a take-off case of door dash right it's extremely important for them to have data as to which stores have what products what is available is this something they can list for people to go and buy is this something that they can therefore deliver right this is data that changes all the time now imagine them getting data from hundreds of different merchants across the board so it is the task of data engineering to then consume that data from all these different places different formats different apis different systems and then somehow unify all the data so that it can be used by the applications that they are building so data engineering in this case becomes taking data from different places and making it useful again back to what i was talking about ready to use data it is a lot of code it's a lot of people not just that it is something that runs every single day so it means it has monitoring it has reliability um it has performance it has every aspect of engineering as we know going into it you mentioned it's a hot topic which it is but it's also really challenging to accomplish how does nexla help enable that yeah data engineering is quite interesting in that one it is difficult to implement you know the the necessary sort of pieces but it is also very repetitive at some level right i mean when you connect to say 10 systems and get data from them you know that's not the end of it you have 10 more and 10 more and 10 more and then at some point you have thousands of such you know data connectivity and data flows happening it's hard to maintain them right as well so the way nexla gets into the whole picture is looking at what can we understand about data what can we observe about the data systems what can be done from that and then start to automate certain pieces of data engineering so that we are helping those teams just accelerate a lot faster and it i would say comes down to more people being able to do these tasks rather than only very very specialized people more people being able to do the tasks more users kind of democratization of data really there can you talk to us in more detail about how naxa is automating data engineering yeah i think um you know i think this is best shared through a visual so let me walk you through that a little bit as to how we automated engineering right so if we think about data engineering three of the most core components are many parts to it but three of the most core components of that are integrating with data systems preparing and transforming data and then monitoring that right so automating data engineering happens in you know three different ways first of all connecting connecting to data is is basically about the gateway to data the ability to read and write data from different systems this is where the data journey starts but it is extremely complex because people have to write code to connect to different systems one part that we have automated is generating these connectors so that you don't have to write code for that also making them bi-directional is extremely valuable because now you can read and write from any system the second part is that the gateway the connector has read the data but how do you represent it to the user so anybody can understand it and that's where the concept of data product comes in so we also look at auto generating data products these become the common language and entity that people can understand and work with and then the third part is taking all this automation and bringing the human in the loop no automation is perfect and therefore bringing the human in the loop means that somebody who is an expert in data who can look at it and understand it can now do things which only data systems experts were able to do before so bringing in that user of data directly into the into the picture is one important part but let's not forget data challenges are very diverse and very complex so the same system also becomes accessible to the engineers who are experts in that and now both of these can work together while an engineer will come through apis and sdk and command interfaces a data user comes in through a nice no code user interface and all of these things coming together are what is accelerating back to that time to value that really everybody cares about so if i'm in marketing and i'm a data user i'm able to have a collaborative workflow with the data engineer yeah yeah for the first time that is actually possible and everybody's focuses on their expertise and their know-how so you know um somebody who for example in financial services really understands portfolio and transactions and different type of asset classes they have the data in front of them the engineers who understand the underlying real-time data feeds and those they are still involved in the loop but now they are not doing that back and forth you know as the user of data i'm not going to the engineer saying hey can you do this for me can you get the data here and that back and forth is not only time taking it's frustrating and the number one hold back right yeah that and that's time that nobody has to waste as we know for many reasons talk to me about when you look into your crystal ball which i'm sure you have one what is the future of of data engineering from nexus perspective you talked about the automation what's the future hold i think the future of data engineering becomes that we up level this at a point where um companies don't have to be slowed down for it um i think a lot of tooling is already happening the way to think about this is that here in 2022 if we think that our data challenges are you know like x they will be a thousand x in five years right i mean this complexity is just increasing very rapidly so we think that this becomes one of those fundamental layers you know and you know as i was saying maybe the last time this is like the road you know you don't feel it you just move on it you do your job you build your products deliver your services as a company this just works for you um and that's where i think the future is and that's where i think the future should be we all need to work towards that we're not there yet not there yet a lot of a lot of potential a lot of opportunity and a lot of momentum speaking of momentum i want to talk about data mesh that is a topic of a lot of excitement a lot of discussion let's unpack that yeah i think uh you know the idea that data should be democratized that people should get access to the data and it's all coming back to that sort of basic concept of scale companies can scale only when more people can do the relevant jobs without depending on each other right so the idea of data democratization has been there for a long time but you know recently in the last couple of years the concept of data mesh was introduced by zamak digani and thoughtworks and that has really caught the attention of people and the imagination of leadership as well the idea that data should be available as a product you know that democratization can happen what is the entity of the democratization that's data presented as a product that people can use and collaborate is extremely powerful um i think a lot of companies are gravitating towards that and that's why it's exciting this is promising a future that is you know possible so second speaking of data products we talked a little bit about this last time but can you really help us understand see smell touch feel what a data product is and give us that context yeah absolutely i think uh best to orient ourselves with the general thinking of how we consider something as a product right a product is something that we find ready to use for example this table that i'm using right now made out of raw materials wood metal screws somebody designed it somebody produced it and i'm using it right now when we think about data products we think about data as the raw material so for example a spreadsheet an api a database query those are the raw raw materials what is a data product is something that further enriches and enhances that entity to be much more usable ready to use right um let me illustrate that with a little bit of a visual actually and that might help okay um the idea of the data product and this is how a data product looks like in next lab for a user to write as you see the concept of a data product is something that first of all it's a logical entity this simply means that it's not a new copy of data just like containers or logical compute units you know these data products are logical entities but they represent data in the same consistent fashion regardless of where the data comes from what format it is in they provide the user the idea of what the structure of data is what the sample data looks like what the characteristics of data are it allows people to have some documentation around it what does the data mean what do these attributes you know mean and how to interpret them how to validate that data something that users often know in an industry how is my data looking like well this value can never be negative because it's a price for example right um then the ability to take these data products that you know we automate by generating as i was mentioning earlier automatically creating these data products taking these data products to create new data products now that's something that's very unique about data you could take data off about an order for a from a company and say well the order data has an order id and a user id but i need to look up shipping address so i can combine user and order data to get that information in one place so you know creating new data products giving people access hey i've designed a data product i think you'll find it useful you can go use that as it is you don't have to go from scratch so all of those things together make a data product something that people can find ready to use again and this is this is also usable by the again that example where i'm in marketing uh or i'm in sales this is available to me as a general user as a general user in the tool of your choice so you can say oh no i am most familiar with using data in a spreadsheet i would like it there or i prefer my data in a tableau or a looker to visualize it and you can have it there so these data products give multiple interfaces for the end user to make use of it got it i like it you're meeting the user where they are with relevant data that helps them understand so much more contextually i'm curious when you're in customer conversations customers that come to you saying saka we need to build the data mesh how is nexl relevant they're how what is your conversation like yeah when people want to build a data mesh they're really looking for how their organization will scale into the future uh there are multiple components to building a data mesh there's a tooling part of it the technology portion there are people and processes right i mean unless you train people in certain processes and say hey when you build a data product you know make sure you have taken care of privacy or compliance to certain rules or who do you give access to is something you have to follow some rules about so we provide the technology component of it and then the people and process is something that companies you know then as they adopt and do that right so the concept of data product becomes core to building the data mesh having governance on it uh having all this be self-serve it's an essential part of that so that's where we come into the picture as a as a technology component to the whole story and working to deliver on that mission to getting data in the hands of every user you mentioned i want to dig into in the last few minutes here that we have uh the target audience you mentioned a few by name big names customers that nexla has you i heard retail i heard e-commerce i think i heard logistics but talk to me about the target customer for nexla any verticals in particular or any company's sizes in particular as well yeah you know the one of the top three banks in the country is a big user of nexla as part of their data stack uh we actually sit as part of their enterprise-wide ai platform providing data to their data scientists um we're not allowed to share their name unfortunately but um you know there are multiple other companies in asset management area for example they work with a lot of data in markets portfolio and so on um the leading medical devices companies using nexla data scientists there are using data coming in real time or streaming for medical devices to train and um and combine that with other data to do sort of clinical trial related research that they do um we have you know the companies for example linkedin is an excellent customer linkedin is by far the largest social network um their marketing team leverages nexla to bring data from different type of systems together as well um you know so are companies in education space like nerdy is a public company that uses nexla for you know student enrollment education data as they collaborate with school districts for example um you know there are companies across the board in marketing live brand you know for example uses nexla so we are um we are you know from who uses nexla is today mostly mid to large to very large enterprises today leverage nexla as a very critical component and often mission critical data for which they leverage us do you see that changing anytime soon as every company these days has to be a data company we expect that as consumers whether it's my grocery store um or my local coffee shop that they've got to use data to deliver me that personalized experience do you see the target audience kind of shifting down to more into mid-market smb space for next level oh yeah absolutely look we started the journey of the company with the thinking that the most complex data challenges exist in the large enterprise and if we can make it no code self-serve easy to use for them we can bring the same high-end technology to everybody and this is exactly why we recently launched in the amazon marketplace so anybody can go there get access to nexla and start to use it and you will see more and more of that happen where we will be bringing even some free versions of our product available so you're absolutely right every company needs to leverage data and i think people are getting much better at it you know especially in the last couple of years i've seen that teams have become much more sophisticated yes even if you are a coffee shop and you're running campaigns you know getting people yelp reviews and so on this data that you can use and understand better your demographic your customer and run your business better so one day yes we will absolutely be in the hands of every single person here a lot more opportunity to delight a lot more consumers and customers socket thank you so much for joining me on the program during the startup showcase you did a great job of helping us understand the future of automated data engineering we appreciate your insights thank you so much lisa it's a pleasure talking to you likewise for soccer sarah i'm lisa martin you're watching thecube's coverage of the aws startup showcase season two episode two stick around more great content coming up from the cube the leader in hybrid tech event coverage [Music]

>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.

>> Narrator: From around the globe, It's theCUBE! Covering Fortinet Security Summit, brought to you by Fortinet. >> And welcome to the cube coverage here at the PGA champion-- Fortinet championship, where we're going to be here for Napa valley coverage of Fortinet's, the championships security summit, going on Fortinet, sponsoring the PGA, but a great guest Merritt Baer, who's the principal in the office of the CISO at Amazon web services. Great to see you. Thanks for coming on. >> Merritt: Thank you for having me. It's good to be here. >> So Fortinet, uh, big brand now, sponsoring the PGA. Pretty impressive that they're getting out there with the golf. It's very enterprise focused, a lot of action. A lot of customers here. >> Merritt: It seems like it, for sure. >> Bold move. Amazon, Amazon web services has become the gold standard in terms of cloud computing, seeing DevOps people refactoring. You've seen the rise of companies like Snowflake building on Amazon. People are moving not only to the cloud, but they're refactoring their business and security is top of mind for everyone. And obviously cybersecurity threats that Fortinet helps cover, you guys are partnering with them, is huge. What is your state of the union for cyber? What's the current situation with the threat landscape? Obviously there's no perimeter in the cloud. More end points are coming on board. The Edge is here. 5G, wavelength with outpost, a lot happening. >> That was a long question, but I'll, I'll try. So I think, you know, as always business in innovation is the driver. And security needs to be woven into that. And so I think increasingly we're seeing security not be a no shop, but be an enabler. And especially in cloud, when we're talking about the way that you do DevOps with security, I know folks don't like the term DevSecOps, but you know, to be able to do agile methodology and be able to do the short sprints that are really agile and, and innovative where you can-- So instead of nine months or whatever, nine week timelines, we're talking about short sprints that allow you to elastically scale up and down and be able to innovate really creatively. And to do that, you need to weave in your security because there's no like, okay, you pass go, you collect $200. Security is not an after the fact. So I think as part of that, of course the perimeter is dead, long live the perimeter, right? It does matter. And we can talk about that a little bit. You know, the term zero trust is really hot right now. We can dig into that if that's of interest. But I think part of this is just the business is kind of growing up. And as you alluded to we're at the start of what I think is an S curve that is just at the beginning. >> You know, I was really looking forward to Reinforced this year. It was got canceled last year, but the first inaugural event was in Boston. I remember covering that. This year it was virtual, but the keynote Steven gave was interesting, security hubs at the center of it. And I want to ask you, because I need you to share your view on how security's changed with the cloud, because there's now new things that are there to take advantage of if you're a business or an enterprise, yeah on premises, there's a standard operating procedure. You have the perimeter, et cetera. That's not there anymore, but with the cloud, there's a new, there's new ways to protect and security hub is one. What are some of the new things that cloud enables for security? >> Well, so just to clarify, like perimeters exist logically just like they do physically. So, you know, a VPC for example, would be a logical perimeter and that is very relevant, or a VPN. Now we're talking about a lot of remote work during COVID, for example. But one of the things that I think folks are really interested with Security Hub is just having that broad visibility and one of the beauties of cloud is that, you get this tactile sense of your estate and you can reason about it. So for example, when you're looking at identity and access management, you can look at something like access analyzer that will under the hood be running on a tool that our, our group came up with that is like reasoning about the permissions, because you're talking about software layers, you're talking about computer layer reasoning about security. And so another example is in inspector. We have a tool that will tell you without sending a single packet over the network, what your network reach ability is. There's just like this ability to do infrastructure as code that then allows you to do security as code. And then that allows for ephemeral and immutable infrastructures so that you could, for example, get back to a known good state. That being said, you know, you kill a, your web server gets popped and you kill it and you spin up a new one. You haven't solved your problem, right? You need to have some kind of awareness of networking and how principals work. But at the same time, there's a lot of beauties about cloud that you inherit from a security perspective to be able to work in those top layers. And that's of course the premise of cloud. >> Yeah, infrastructure as code, you mentioned that, it's awesome. And the program ability of it with, with server-less functions, you're starting to see new ways now to spin up resources. How is that changing the paradigm and creating opportunities for better security? Is it, is it more microservices? Is it, is, are there new things that people can do differently now that they didn't have a year ago or two years ago? Because you're starting to see things like server-less functions are very popular. >> So yes, and yes, I think that it is augmenting the way that we're doing business, but it's especially augmenting the way we do security in terms of automation. So server-less, under the hood, whether it's CloudWatch events or config rules, they are all a Lambda function. So that's the same thing that powers your Alexa at home. These are server-less functions and they're really simple. You can program them, you can find them on GitHub, but they are-- one way to really scale your enterprise is to have a lot of automation in place so that you put those decisions in ahead of time. So your gray area of human decision making is scaled down. So you've got, you know, what you know to be allowable, what you know to be not allowable. And then you increasingly kind of whittled down that center into things that really are novel, truly novel or high stakes or both. But the focus on automation is a little bit of a trope for us. We at Amazon like to talk about mechanisms, good intentions are not enough. If it's not someone's job, it's a hope and hope is not a plan, you know, but creating the actual, you know, computerized version of making it be done iteratively. And I think that is the key to scaling a security chain because as we all know, things can't be manual for long, or you won't be able to grow. >> I love the AWS reference. Mechanisms, one way doors, raising the bar. These are all kind of internal Amazon, but I got to ask you about the Edge. Okay. There's a lot of action going on with 5G and wavelength. Okay, and what's interesting is if the Edge becomes so much more robust, how do you guys see that security from a security posture standpoint? What should people be thinking about? Because certainly it's just a distributed Edge point. What's the security posture, How should we be thinking about Edge? >> You know, Edge is a kind of catch all, right, we're talking about Internet of Things. We're talking about points of contact. And a lot of times I think we focus so much on the confidentiality and integrity, but the availability is hugely important when we're talking about security. So one of the things that excites me is that we have so many points of contact and so many availability points at the Edge that actually, so for example, in DynamoDB, the more times you put a call on it, the more available it is because it's fresher, you've already been refreshing it, there are so many elements of this, and our core compute platform, EC2, all runs on Nitro, which is our, our custom hardware. And it's really fascinating, the availability benefits there. Like the best patching is a patching you don't have to do. And there are so many elements that are just so core to that Greengrass, you know, which is running on FreeRTOS, which has an open source software, for example, is, you know, one element of zero trust in play. And there are so many ways that we can talk about this in different incarnations. And of course that speaks to like the breadth and depth of the industries that use cloud. We're talking about automotive, we're talking about manufacturing and agriculture, and there are so many interesting use cases for the ways that we will use IOT. >> Yeah. It's interesting, you mentioned Nitro. we also got Annapurna acquisition years ago. You got latency at the Edge. You can handle low latency, high volume compute with the data. That's pretty powerful. It's a paradigm shift. That's a new dynamic. It's pretty compelling, these new architectures, most people are scratching their heads going, "okay, how do I do this, like what do I do?" >> No, you're right. So it is a security inheritance that we are extremely calculated about our hardware supply chain. And we build our own custom hardware. We build our own custom Silicon. Like, this is not a question. And you're right in that one of the things, one of the north stars that we have is that the security properties of our engineering infrastructure are built in. So there just is no button for it to be insecure. You know, like that is deliberate. And there are elements of the ways that nature works from it running, you know, with zero downtime, being able to be patched running. There are so many elements of it that are inherently security benefits that folks inherit as a product. >> Right. Well, we're here at the security summit. What are you excited for today? What's the conversations you're having here at the Fortinet security summit. >> Well, it's awesome to just meet folks and connect outside. It's beautiful outside today. I'm going to be giving a talk on securing the cloud journey and kind of that growth and moving to infrastructure as code and security as code. I'm excited about the opportunity to learn a little bit more about how folks are managing their hybrid environments, because of course, you know, I think sometimes folks perceive AWS as being like this city on a hill where we get it all right. We struggle with the same things. We empathize with the same security work. And we work on that, you know, as a principal in the office of the CISO, I spend a lot of my time on how we do security and then a lot of my time talking to customers and that empathy back and forth is really crucial. >> Yeah. And you've got to be on the bleeding edge and have the empathy. I can't help but notice your AWS crypto shirt. Tell me about the crypto, what's going on there. NFT's coming out, is there a S3 bucket at NFT now, I mean. (both laughing) >> Cryptography never goes out of style. >> I know, I'm just, I couldn't help-- We'll go back to the pyramids on that one. Yeah, no, this is not a, an advertisement for cryptocurrency. It is, I'm a fangirl of the AWS crypto team. And as a result of wearing their shirts, occasionally they send me more shirts. And I can't argue with that. >> Well, love, love, love the crypto. I'm big fan of crypto, I think crypto is awesome. Defi is amazing. New applications are going to come out. We think it's going to be pretty compelling, again, let's get today right. (laughing) >> Well, I don't think it's about like, so cryptocurrency is just like one small iteration of what we're really talking about, which is the idea that math resolves, and the idea that you can have value in your resolution that the math should resolve. And I think that is a fundamental principle and end-to-end encryption, I believe is a universal human right. >> Merritt, thank you for coming on the cube. Great, great to have you on. Thanks for sharing that awesome insight. Thanks for coming on. >> Merritt: Thank you. >> Appreciate it. Okay. CUBE coverage here in Napa valley, our remote set for Fortinet's security cybersecurity summit here as part of their PGA golf Pro-Am tournament happening here in Napa valley. I'm John Furrier. Thanks for watching.

>>As we've been reporting, the pandemic has called CSOs to really shift their spending priorities towards securing remote workers. Almost overnight. Zero trust has gone from buzzword to mandate. What's more as we wrote in our recent cybersecurity breaking analysis, not only Maseca pro secured increasingly distributed workforce, but now they have to be wary of software updates in the digital supply chain, including the very patches designed to protect them against cyber attacks. Hello everyone. And welcome to this Q conversation. My name is Dave Vellante and I'm pleased to welcome Derek manky. Who's chief security insights, and global threat alliances for four guard labs with fresh data from its global threat landscape report. Derek. Welcome. Great to see you. >>Thanks so much for, for the invitation to speak. It's always a pleasure. Multicover yeah, >>You're welcome. So first I wonder if you could explain for the audience, what is for guard labs and what's its relationship to fortunate? >>Right. So 40 grand labs is, is our global sockets, our global threat intelligence operation center. It never sleeps, and this is the beat. Um, you know, it's, it's been here since inception at port in it. So it's it's 20, 21 years in the making, since Fortinet was founded, uh, we have built this in-house, uh, so we don't go yum technology. We built everything from the ground up, including creating our own training programs for our, our analysts. We're following malware, following exploits. We even have a unique program that I created back in 2006 to ethical hacking program. And it's a zero-day research. So we try to meet the hackers, the bad guys to their game. And we of course do that responsibly to work with vendors, to close schools and create virtual patches. Um, and, but, you know, so it's, it's everything from, uh, customer protection first and foremost, to following, uh, the threat landscape and cyber. It's very important to understand who they are, what they're doing, who they're, uh, what they're targeting, what tools are they using? >>Yeah, that's great. Some serious DNA and skills in that group. And it's, it's critical because like you said, you can, you can minimize the spread of those malware very, very quickly. So what, what now you have, uh, the global threat landscape report. We're going to talk about that, but what exactly is that? >>Right? So this a global threat landscape report, it's a summary of, uh, all, all the data that we collect over a period of time. So we released this, that biannually two times a year. Um, cyber crime is changing very fast, as you can imagine. So, uh, while we do release security blogs, and, uh, what we call threat signals for breaking security events, we have a lot of other vehicles to release threat intelligence, but this threat landscape report is truly global. It looks at all of our global data. So we have over 5 million censorship worldwide in 40 guard labs, we're processing. I know it seems like a very large amount, but North of a hundred billion, uh, threat events in just one day. And we have to take the task of taking all of that data and put that onto scale for half a year and compile that into something, um, that is, uh, the, you know, that that's digestible. That's a, a very tough task, as you can imagine, so that, you know, we have to work with a huge technologies back to machine learning and artificial intelligence automation. And of course our analyst view to do that. >>Yeah. So this year, of course, there's like the every year is a battle, but this year was an extra battle. Can you explain what you saw in terms of the hacker dynamics over the past? Let's say 12 months. I know you do this twice a year, but what trends did you see evolving throughout the year and what have you seen with the way that attackers have exploited this expanded attack surface outside of corporate network? >>Yeah, it was quite interesting last year. It certainly was not normal. Like we all say, um, and that was no exception for cybersecurity. You know, if we look at cyber criminals and how they pivoted and adapted to the scrap threat landscape, cyber cyber criminals are always trying to take advantage of the weakest link of the chain. They're trying to always prey off here and ride waves of global trends and themes. We've seen this before in, uh, natural disasters as an example, you know, um, trying to do charity kind of scams and campaigns. And they're usually limited to a region where that incident happened and they usually live about two to three weeks, maybe a month at the most. And then they'll move on to the next to the next trip. That's braking, of course, because COVID is so global and dominant. Um, we saw attacks coming in from, uh, well over 40 different languages as an example, um, in regions all across the world that wasn't lasting two to three weeks and it lasted for the better part of a year. >>And of course, what they're, they're using this as a vehicle, right? Not preying on the fear. They're doing everything from initial lockdown, uh, fishing. We were as COVID-19 movers to, um, uh, lay off notices then to phase one, reopenings all the way up to fast forward to where we are today with vaccine rollover development. So there's always that new flavor and theme that they were rolling out, but because it was so successful for them, they were able to, they didn't have to innovate too much, right. They didn't have to expand and shifted to new to new trends. And themes are really developed on new rats families as an example, or a new sophisticated malware. That was the first half of the year and the second half of the year. Um, of course people started to experience COVID fatigue, right? Um, people started to become, we did a lot of education around this. >>People started to become more aware of this threat. And so, um, cyber criminals have started to, um, as we expected, started to become more sophisticated with their attacks. We saw an expansion in different ransomware families. We saw more of a shift of focus on, on, um, uh, you know, targeting the digital supply chain as an example. And so that, that was, that was really towards Q4. Uh, so it, it was a long lived lead year with success on the Google themes, um, targeting healthcare as an example, a lot of, um, a lot of the organizations that were, you know, really in a vulnerable position, I would say >>So, okay. I want to clarify something because my assumption was that they actually did really increase the sophistication, but it sounds like that was kind of a first half trends. Not only did they have to adapt and not have to, but they adapt it to these new vulnerabilities. Uh, my sense was that when you talk about the digital supply chain, that that was a fairly sophisticated attack. Am I, am I getting that right? That they did their sort of their, their, their increased sophistication in the first half, and then they sort of deployed it, did it, uh, w what actually happened there from your data? >>Well, if we look at, so generally there's two types of attacks that we look at, we look at the, uh, the premeditated sophisticated attacks that can have, um, you know, a lot of ramp up work on their end, a lot of time developing the, the, the, the weaponization phase. So developing, uh, the exploits of the sophisticated malware that they're gonna use for the campaign reconnaissance, understanding the targets, where platforms are developed, um, the blueprinting that DNA of, of, of the supply chain, those take time. Um, in fact years, even if we look back to, um, uh, 10 plus years ago with the Stuxnet attacks, as an example that was on, uh, nuclear centrifuges, um, and that, that had four different zero-day weapons at the time. That was very sophisticated, that took over two years to develop as an example. So some of these can take years of time to develop, but they're, they're, uh, very specific in terms of the targets are going to go after obviously the ROI from their end. >>Uh, the other type of attack that we see is as ongoing, um, these broad, wide sweeping attacks, and the reality for those ones is they don't unfortunately need to be too sophisticated. And those ones were the ones I was talking about that were really just playing on the cool, the deem, and they still do today with the vaccine road and development. Uh, but, but it's really because they're just playing on, on, um, you know, social engineering, um, using, uh, topical themes. And in fact, the weapons they're using these vulnerabilities are from our research data. And this was highlighted actually the first pop landscape before last year, uh, on average were two to three years old. So we're not talking about fresh vulnerabilities. You've got to patch right away. I mean, these are things that should have been patched two years ago, but they're still unfortunately having success with that. >>So you mentioned stuck next Stuxnet as the former sort of example, of one of the types of attacks that you see. And I always felt like that was a watershed moment. One of the most sophisticated, if not the most sophisticated attack that we'd ever seen. When I talk to CSOs about the recent government hack, they, they, they suggest I infer maybe they don't suggest it. I infer that it was of similar sophistication. It was maybe thousands of people working on this for years and years and years. Is that, is that accurate or not necessarily? >>Yeah, there's definitely a, there's definitely some comparisons there. Uh, you know, one of the largest things is, uh, both attacks used digital circuits certificate personation, so they're digitally signed. So, you know, of course that whole technology using cryptography is designed by design, uh, to say that, you know, this piece of software installed in your system, hassles certificate is coming from the source. It's legitimate. Of course, if that's compromised, that's all out of the window. And, um, yeah, this is what we saw in both attacks. In fact, you know, stocks in that they also had digitally designed, uh, certificates that were compromised. So when it gets to that level of students or, uh, sophistication, that means definitely that there's a target that there has been usually months of, of, uh, homework done by cyber criminals, for reconnaissance to be able to weaponize that. >>W w what did you see with respect to ransomware? What were the trends there over the past 12 months? I've heard some data and it's pretty scary, but what did you see? >>Yeah, so we're actually, ransomware is always the thorn in our side, and it's going to continue to be so, um, you know, in fact, uh, ransomware is not a new itself. It was actually first created in 1989, and they demanded ransom payments through snail mail. This was to appeal a box, obviously that, that, that didn't take off. Wasn't a successful on the internet was porn at the time. But if you look at it now, of course, over the last 10 years, really, that's where it ran. The ransomware model has been, uh, you know, lucrative, right? I mean, it's been, um, using, uh, by force encrypting data on systems, so that users had to, if they were forced to pay the ransom because they wanted access to their data back data was the target currency for ransomware. That's shifted now. And that's actually been a big pivotal over the last year or so, because again, before it was this let's cast a wide net, in fact, as many people as we can random, um, and try to see if we can hold some of their data for ransom. >>Some people that data may be valuable, it may not be valuable. Um, and that model still exists. Uh, and we see that, but really the big shift that we saw last year and the threat landscape before it was a shift to targeted rats. So again, the sophistication is starting to rise because they're not just going out to random data. They're going out to data that they know is valuable to large organizations, and they're taking that a step further now. So there's various ransomware families. We saw that have now reverted to extortion and blackmail, right? So they're taking that data, encrypting it and saying, unless you pay us as large sum of money, we're going to release this to the public or sell it to a buyer on the dark web. And of course you can imagine the amount of, um, you know, damages that can happen from that. The other thing we're seeing is, is a target of going to revenue services, right? So if they can cripple networks, it's essentially a denial of service. They know that the company is going to be bleeding, you know, X, millions of dollars a day, so they can demand Y million dollars of ransom payments, and that's effectively what's happening. So it's, again, becoming more targeted, uh, and more sophisticated. And unfortunately the ransom is going up. >>So they go to where the money is. And of course your job is to, it's a lower the ROI for them, a constant challenge. Um, we talked about some of the attack vectors, uh, that you saw this year that, that cyber criminals are targeting. I wonder if, if, you know, given the work from home, if things like IOT devices and cameras and, you know, thermostats, uh, with 75% of the work force at home, is this infrastructure more vulnerable? I guess, of course it is. But what did you see there in terms of attacks on those devices? >>Yeah, so, uh, um, uh, you know, unfortunately the attack surface as we call it, uh, so the amount of target points is expanding. It's not shifting, it's expanding. We still see, um, I saw, I mentioned earlier vulnerabilities from two years ago that are being used in some cases, you know, over the holidays where e-commerce means we saw e-commerce heavily under attack in e-commerce has spikes since last summer, right. It's been a huge amount of traffic increase everybody's shopping from home. And, uh, those vulnerabilities going after a shopping cart, plugins, as an example, are five to six years old. So we still have this theme of old vulnerabilities are still new in a sense being attacked, but we're also now seeing this complication of, yeah, as you said, IOT, uh, B roll out everywhere, the really quick shift to work from home. Uh, we really have to treat this as if you guys, as the, uh, distributed branch model for enterprise, right. >>And it's really now the secure branch. How do we take, um, um, you know, any of these devices on, on those networks and secure them, uh, because yeah, if you look at the, what we highlighted in our landscape report and the top 10 attacks that we're seeing, so hacking attacks hacking in tabs, this is who our IPS triggers. You know, we're seeing attempts to go after IOT devices. Uh, right now they're mostly, uh, favoring, uh, well in terms of targets, um, consumer grade routers. Uh, but they're also looking at, um, uh, DVR devices as an example for, uh, you know, home entertainment systems, uh, network attached storage as well, and IP security cameras, um, some of the newer devices, uh, what, the quote unquote smart devices that are now on, you know, virtual assistance and home networks. Uh, we actually released a predictions piece at the end of last year as well. So this is what we call the new intelligent edge. And that's what I think is we're really going to see this year in terms of what's ahead. Um, cause we always have to look ahead and prepare for that. But yeah, right now, unfortunately, the story is, all of this is still happening. IOT is being targeted. Of course they're being targeted because they're easy targets. Um, it's like for cybercriminals, it's like shooting fish in a barrel. There's not just one, but there's multiple vulnerabilities, security holes associated with these devices, easy entry points into networks. >>I mean, it's, um, I mean, attackers they're, they're highly capable. They're organized, they're well-funded they move fast, they're they're agile, uh, and they follow the money. As we were saying, uh, you, you mentioned, you know, co vaccines and, you know, big pharma healthcare, uh, where >>Did you see advanced, persistent >>Threat groups really targeting? Were there any patterns that emerged in terms of other industry types or organizations being targeted? >>Yeah. So just to be clear again, when we talk about AP teams, um, uh, advanced, specific correct group, the groups themselves they're targeting, these are usually the more sophisticated groups, of course. So going back to that theme, these are usually the target, the, um, the premeditated targeted attacks usually points to nation state. Um, sometimes of course there's overlap. They can be affiliated with cyber crime, cyber crime, uh, uh, groups are typically, um, looking at some other targets for ROI, uh, bio there's there's a blend, right? So as an example, if we're looking at the, uh, apt groups I had last year, absolutely. Number one I would say would be healthcare. Healthcare was one of those, and it's, it's, it's, uh, you know, very unfortunate, but obviously with the shift that was happening at a pop up medical facilities, there's a big, a rush to change networks, uh, for a good cause of course, but with that game, um, you know, uh, security holes and concerns the targets and, and that's what we saw IPT groups targeting was going after those and, and ransomware and the cyber crime shrine followed as well. Right? Because if you can follow, uh, those critical networks and crippled them on from cybercriminals point of view, you can, you can expect them to pay the ransom because they think that they need to buy in order to, um, get those systems back online. Uh, in fact, last year or two, unfortunately we saw the first, um, uh, death that was caused because of a denial of service attack in healthcare, right. Facilities were weren't available because of the cyber attack. Patients had to be diverted and didn't make it on the way. >>All right. Jericho, sufficiently bummed out. So maybe in the time remaining, we can talk about remediation strategies. You know, we know there's no silver bullet in security. Uh, but what approaches are you recommending for organizations? How are you consulting with folks? >>Sure. Yeah. So a couple of things, um, good news is there's a lot that we can do about this, right? And, um, and, and basic measures go a long way. So a couple of things just to get out of the way I call it housekeeping, cyber hygiene, but it's always worth reminding. So when we talk about keeping security patches up to date, we always have to talk about that because that is reality as et cetera, these, these vulnerabilities that are still being successful are five to six years old in some cases, the majority two years old. Um, so being able to do that, manage that from an organization's point of view, really treat the new work from home. I don't like to call it a work from home. So the reality is it's work from anywhere a lot of the times for some people. So really treat that as, as the, um, as a secure branch, uh, methodology, doing things like segmentations on network, secure wifi access, multi-factor authentication is a huge muscle, right? >>So using multi-factor authentication because passwords are dead, um, using things like, uh, XDR. So Xers is a combination of detection and response for end points. This is a mass centralized management thing, right? So, uh, endpoint detection and response, as an example, those are all, uh, you know, good security things. So of course having security inspection, that that's what we do. So good threat intelligence baked into your security solution. That's supported by labs angles. So, uh, that's, uh, you know, uh, antivirus, intrusion prevention, web filtering, sandbox, and so forth, but then it gets that that's the security stack beyond that it gets into the end user, right? Everybody has a responsibility. This is that supply chain. We talked about. The supply chain is, is, is a target for attackers attackers have their own supply chain as well. And we're also part of that supply chain, right? The end users where we're constantly fished for social engineering. So using phishing campaigns against employees to better do training and awareness is always recommended to, um, so that's what we can do, obviously that's, what's recommended to secure, uh, via the endpoints in the secure branch there's things we're also doing in the industry, um, to fight back against that with prime as well. >>Well, I, I want to actually talk about that and talk about ecosystems and collaboration, because while you have competitors, you all want the same thing. You, SecOps teams are like superheroes in my book. I mean, they're trying to save the world from the bad guys. And I remember I was talking to Robert Gates on the cube a couple of years ago, a former defense secretary. And I said, yeah, but don't, we have like the best security people and can't we go on the offensive and weaponize that ourselves. Of course, there's examples of that. Us. Government's pretty good at it, even though they won't admit it. But his answer to me was, yeah, we gotta be careful because we have a lot more to lose than many countries. So I thought that was pretty interesting, but how do you collaborate with whether it's the U S government or other governments or other other competitors even, or your ecosystem? Maybe you could talk about that a little bit. >>Yeah. Th th this is what, this is what makes me tick. I love working with industry. I've actually built programs for 15 years of collaboration in the industry. Um, so, you know, we, we need, I always say we can't win this war alone. You actually hit on this point earlier, you talked about following and trying to disrupt the ROI of cybercriminals. Absolutely. That is our target, right. We're always looking at how we can disrupt their business model. Uh, and, and in order, there's obviously a lot of different ways to do that, right? So a couple of things we do is resiliency. That's what we just talked about increasing the security stack so that they go knocking on someone else's door. But beyond that, uh, it comes down to private, private sector collaborations. So, uh, we, we, uh, co-founder of the cyber threat Alliance in 2014 as an example, this was our fierce competitors coming in to work with us to share intelligence, because like you said, um, competitors in the space, but we need to work together to do the better fight. >>And so this is a Venn diagram. What's compared notes, let's team up, uh, when there's a breaking attack and make sure that we have the intelligence so that we can still remain competitive on the technology stack to gradation the solutions themselves. Uh, but let's, let's level the playing field here because cybercriminals moved out, uh, you know, um, uh, that, that there's no borders and they move with great agility. So, uh, that's one thing we do in the private private sector. Uh, there's also, uh, public private sector relationships, right? So we're working with Interpol as an example, Interfor project gateway, and that's when we find attribution. So it's not just the, what are these people doing like infrastructure, but who, who are they, where are they operating? What, what events tools are they creating? We've actually worked on cases that are led down to, um, uh, warrants and arrests, you know, and in some cases, one case with a $60 million business email compromise fraud scam, the great news is if you look at the industry as a whole, uh, over the last three to four months has been for take downs, a motet net Walker, uh, um, there's also IE Gregor, uh, recently as well too. >>And, and Ian Gregor they're actually going in and arresting the affiliates. So not just the CEO or the King, kind of these organizations, but the people who are distributing the ransomware themselves. And that was a unprecedented step, really important. So you really start to paint a picture of this, again, supply chain, this ecosystem of cyber criminals and how we can hit them, where it hurts on all angles. I've most recently, um, I've been heavily involved with the world economic forum. Uh, so I'm, co-author of a report from last year of the partnership on cyber crime. And, uh, this is really not just the pro uh, private, private sector, but the private and public sector working together. We know a lot about cybercriminals. We can't arrest them. Uh, we can't take servers offline from the data centers, but working together, we can have that whole, you know, that holistic effect. >>Great. Thank you for that, Derek. What if people want, want to go deeper? Uh, I know you guys mentioned that you do blogs, but are there other resources that, that they can tap? Yeah, absolutely. So, >>Uh, everything you can see is on our threat research blog on, uh, so 40 net blog, it's under expired research. We also put out, uh, playbooks, w we're doing blah, this is more for the, um, the heroes as he called them the security operation centers. Uh, we're doing playbooks on the aggressors. And so this is a playbook on the offense, on the offense. What are they up to? How are they doing that? That's on 40 guard.com. Uh, we also release, uh, threat signals there. So, um, we typically release, uh, about 50 of those a year, and those are all, um, our, our insights and views into specific attacks that are now >>Well, Derek Mackie, thanks so much for joining us today. And thanks for the work that you and your teams do. Very important. >>Thanks. It's yeah, it's a pleasure. And, uh, rest assured we will still be there 24 seven, three 65. >>Good to know. Good to know. And thank you for watching everybody. This is Dave Volante for the cube. We'll see you next time.

>>As we've been reporting, the pandemic has called CSOs to really shift their spending priorities towards securing remote workers. Almost overnight. Zero trust has gone from buzzword to mandate. What's more as we wrote in our recent cybersecurity breaking analysis, not only Maseca pro secured increasingly distributed workforce, but now they have to be wary of software updates in the digital supply chain, including the very patches designed to protect them against cyber attacks. Hello everyone. And welcome to this Q conversation. My name is Dave Vellante and I'm pleased to welcome Derek manky. Who's chief security insights, and global threat alliances for four guard labs with fresh data from its global threat landscape report. Derek. Welcome. Great to see you. >>Thanks so much for, for the invitation to speak. It's always a pleasure. Multicover yeah, >>You're welcome. So first I wonder if you could explain for the audience, what is for guard labs and what's its relationship to fortunate? >>Right. So 40 grand labs is, is our global sockets, our global threat intelligence operation center. It never sleeps, and this is the beat. Um, you know, it's, it's been here since inception at port in it. So it's it's 20, 21 years in the making, since Fortinet was founded, uh, we have built this in-house, uh, so we don't go yum technology. We built everything from the ground up, including creating our own training programs for our, our analysts. We're following malware, following exploits. We even have a unique program that I created back in 2006 to ethical hacking program. And it's a zero-day research. So we try to meet the hackers, the bad guys to their game. And we of course do that responsibly to work with vendors, to close schools and create virtual patches. Um, and, but, you know, so it's, it's everything from, uh, customer protection first and foremost, to following, uh, the threat landscape and cyber. It's very important to understand who they are, what they're doing, who they're, uh, what they're targeting, what tools are they using? >>Yeah, that's great. Some serious DNA and skills in that group. And it's, it's critical because like you said, you can, you can minimize the spread of those malware very, very quickly. So what, what now you have, uh, the global threat landscape report. We're going to talk about that, but what exactly is that? >>Right? So this a global threat landscape report, it's a summary of, uh, all, all the data that we collect over a period of time. So we released this, that biannually two times a year. Um, cyber crime is changing very fast, as you can imagine. So, uh, while we do release security blogs, and, uh, what we call threat signals for breaking security events, we have a lot of other vehicles to release threat intelligence, but this threat landscape report is truly global. It looks at all of our global data. So we have over 5 million censorship worldwide in 40 guard labs, we're processing. I know it seems like a very large amount, but North of a hundred billion, uh, threat events in just one day. And we have to take the task of taking all of that data and put that onto scale for half a year and compile that into something, um, that is, uh, the, you know, that that's digestible. That's a, a very tough task, as you can imagine, so that, you know, we have to work with a huge technologies back to machine learning and artificial intelligence automation. And of course our analyst view to do that. >>Yeah. So this year, of course, there's like the every year is a battle, but this year was an extra battle. Can you explain what you saw in terms of the hacker dynamics over the past? Let's say 12 months. I know you do this twice a year, but what trends did you see evolving throughout the year and what have you seen with the way that attackers have exploited this expanded attack surface outside of corporate network? >>Yeah, it was quite interesting last year. It certainly was not normal. Like we all say, um, and that was no exception for cybersecurity. You know, if we look at cyber criminals and how they pivoted and adapted to the scrap threat landscape, cyber cyber criminals are always trying to take advantage of the weakest link of the chain. They're trying to always prey off here and ride waves of global trends and themes. We've seen this before in, uh, natural disasters as an example, you know, um, trying to do charity kind of scams and campaigns. And they're usually limited to a region where that incident happened and they usually live about two to three weeks, maybe a month at the most. And then they'll move on to the next to the next trip. That's braking, of course, because COVID is so global and dominant. Um, we saw attacks coming in from, uh, well over 40 different languages as an example, um, in regions all across the world that wasn't lasting two to three weeks and it lasted for the better part of a year. >>And of course, what they're, they're using this as a vehicle, right? Not preying on the fear. They're doing everything from initial lockdown, uh, fishing. We were as COVID-19 movers to, um, uh, lay off notices then to phase one, reopenings all the way up to fast forward to where we are today with vaccine rollover development. So there's always that new flavor and theme that they were rolling out, but because it was so successful for them, they were able to, they didn't have to innovate too much, right. They didn't have to expand and shifted to new to new trends. And themes are really developed on new rats families as an example, or a new sophisticated malware. That was the first half of the year and the second half of the year. Um, of course people started to experience COVID fatigue, right? Um, people started to become, we did a lot of education around this. >>People started to become more aware of this threat. And so, um, cyber criminals have started to, um, as we expected, started to become more sophisticated with their attacks. We saw an expansion in different ransomware families. We saw more of a shift of focus on, on, um, uh, you know, targeting the digital supply chain as an example. And so that, that was, that was really towards Q4. Uh, so it, it was a long lived lead year with success on the Google themes, um, targeting healthcare as an example, a lot of, um, a lot of the organizations that were, you know, really in a vulnerable position, I would say >>So, okay. I want to clarify something because my assumption was that they actually did really increase the sophistication, but it sounds like that was kind of a first half trends. Not only did they have to adapt and not have to, but they adapt it to these new vulnerabilities. Uh, my sense was that when you talk about the digital supply chain, that that was a fairly sophisticated attack. Am I, am I getting that right? That they did their sort of their, their, their increased sophistication in the first half, and then they sort of deployed it, did it, uh, w what actually happened there from your data? >>Well, if we look at, so generally there's two types of attacks that we look at, we look at the, uh, the premeditated sophisticated attacks that can have, um, you know, a lot of ramp up work on their end, a lot of time developing the, the, the, the weaponization phase. So developing, uh, the exploits of the sophisticated malware that they're gonna use for the campaign reconnaissance, understanding the targets, where platforms are developed, um, the blueprinting that DNA of, of, of the supply chain, those take time. Um, in fact years, even if we look back to, um, uh, 10 plus years ago with the Stuxnet attacks, as an example that was on, uh, nuclear centrifuges, um, and that, that had four different zero-day weapons at the time. That was very sophisticated, that took over two years to develop as an example. So some of these can take years of time to develop, but they're, they're, uh, very specific in terms of the targets are going to go after obviously the ROI from their end. >>Uh, the other type of attack that we see is as ongoing, um, these broad, wide sweeping attacks, and the reality for those ones is they don't unfortunately need to be too sophisticated. And those ones were the ones I was talking about that were really just playing on the cool, the deem, and they still do today with the vaccine road and development. Uh, but, but it's really because they're just playing on, on, um, you know, social engineering, um, using, uh, topical themes. And in fact, the weapons they're using these vulnerabilities are from our research data. And this was highlighted actually the first pop landscape before last year, uh, on average were two to three years old. So we're not talking about fresh vulnerabilities. You've got to patch right away. I mean, these are things that should have been patched two years ago, but they're still unfortunately having success with that. >>So you mentioned stuck next Stuxnet as the former sort of example, of one of the types of attacks that you see. And I always felt like that was a watershed moment. One of the most sophisticated, if not the most sophisticated attack that we'd ever seen. When I talk to CSOs about the recent government hack, they, they, they suggest I infer maybe they don't suggest it. I infer that it was of similar sophistication. It was maybe thousands of people working on this for years and years and years. Is that, is that accurate or not necessarily? >>Yeah, there's definitely a, there's definitely some comparisons there. Uh, you know, one of the largest things is, uh, both attacks used digital circuits certificate personation, so they're digitally signed. So, you know, of course that whole technology using cryptography is designed by design, uh, to say that, you know, this piece of software installed in your system, hassles certificate is coming from the source. It's legitimate. Of course, if that's compromised, that's all out of the window. And, um, yeah, this is what we saw in both attacks. In fact, you know, stocks in that they also had digitally designed, uh, certificates that were compromised. So when it gets to that level of students or, uh, sophistication, that means definitely that there's a target that there has been usually months of, of, uh, homework done by cyber criminals, for reconnaissance to be able to weaponize that. >>W w what did you see with respect to ransomware? What were the trends there over the past 12 months? I've heard some data and it's pretty scary, but what did you see? >>Yeah, so we're actually, ransomware is always the thorn in our side, and it's going to continue to be so, um, you know, in fact, uh, ransomware is not a new itself. It was actually first created in 1989, and they demanded ransom payments through snail mail. This was to appeal a box, obviously that, that, that didn't take off. Wasn't a successful on the internet was porn at the time. But if you look at it now, of course, over the last 10 years, really, that's where it ran. The ransomware model has been, uh, you know, lucrative, right? I mean, it's been, um, using, uh, by force encrypting data on systems, so that users had to, if they were forced to pay the ransom because they wanted access to their data back data was the target currency for ransomware. That's shifted now. And that's actually been a big pivotal over the last year or so, because again, before it was this let's cast a wide net, in fact, as many people as we can random, um, and try to see if we can hold some of their data for ransom. >>Some people that data may be valuable, it may not be valuable. Um, and that model still exists. Uh, and we see that, but really the big shift that we saw last year and the threat landscape before it was a shift to targeted rats. So again, the sophistication is starting to rise because they're not just going out to random data. They're going out to data that they know is valuable to large organizations, and they're taking that a step further now. So there's various ransomware families. We saw that have now reverted to extortion and blackmail, right? So they're taking that data, encrypting it and saying, unless you pay us as large sum of money, we're going to release this to the public or sell it to a buyer on the dark web. And of course you can imagine the amount of, um, you know, damages that can happen from that. The other thing we're seeing is, is a target of going to revenue services, right? So if they can cripple networks, it's essentially a denial of service. They know that the company is going to be bleeding, you know, X, millions of dollars a day, so they can demand Y million dollars of ransom payments, and that's effectively what's happening. So it's, again, becoming more targeted, uh, and more sophisticated. And unfortunately the ransom is going up. >>So they go to where the money is. And of course your job is to, it's a lower the ROI for them, a constant challenge. Um, we talked about some of the attack vectors, uh, that you saw this year that, that cyber criminals are targeting. I wonder if, if, you know, given the work from home, if things like IOT devices and cameras and, you know, thermostats, uh, with 75% of the work force at home, is this infrastructure more vulnerable? I guess, of course it is. But what did you see there in terms of attacks on those devices? >>Yeah, so, uh, um, uh, you know, unfortunately the attack surface as we call it, uh, so the amount of target points is expanding. It's not shifting, it's expanding. We still see, um, I saw, I mentioned earlier vulnerabilities from two years ago that are being used in some cases, you know, over the holidays where e-commerce means we saw e-commerce heavily under attack in e-commerce has spikes since last summer, right. It's been a huge amount of traffic increase everybody's shopping from home. And, uh, those vulnerabilities going after a shopping cart, plugins, as an example, are five to six years old. So we still have this theme of old vulnerabilities are still new in a sense being attacked, but we're also now seeing this complication of, yeah, as you said, IOT, uh, B roll out everywhere, the really quick shift to work from home. Uh, we really have to treat this as if you guys, as the, uh, distributed branch model for enterprise, right. >>And it's really now the secure branch. How do we take, um, um, you know, any of these devices on, on those networks and secure them, uh, because yeah, if you look at the, what we highlighted in our landscape report and the top 10 attacks that we're seeing, so hacking attacks hacking in tabs, this is who our IPS triggers. You know, we're seeing attempts to go after IOT devices. Uh, right now they're mostly, uh, favoring, uh, well in terms of targets, um, consumer grade routers. Uh, but they're also looking at, um, uh, DVR devices as an example for, uh, you know, home entertainment systems, uh, network attached storage as well, and IP security cameras, um, some of the newer devices, uh, what, the quote unquote smart devices that are now on, you know, virtual assistance and home networks. Uh, we actually released a predictions piece at the end of last year as well. So this is what we call the new intelligent edge. And that's what I think is we're really going to see this year in terms of what's ahead. Um, cause we always have to look ahead and prepare for that. But yeah, right now, unfortunately, the story is, all of this is still happening. IOT is being targeted. Of course they're being targeted because they're easy targets. Um, it's like for cybercriminals, it's like shooting fish in a barrel. There's not just one, but there's multiple vulnerabilities, security holes associated with these devices, easy entry points into networks. >>I mean, it's, um, I mean, attackers they're, they're highly capable. They're organized, they're well-funded they move fast, they're they're agile, uh, and they follow the money. As we were saying, uh, you, you mentioned, you know, co vaccines and, you know, big pharma healthcare, uh, where >>Did you see advanced, persistent >>Threat groups really targeting? Were there any patterns that emerged in terms of other industry types or organizations being targeted? >>Yeah. So just to be clear again, when we talk about AP teams, um, uh, advanced, specific correct group, the groups themselves they're targeting, these are usually the more sophisticated groups, of course. So going back to that theme, these are usually the target, the, um, the premeditated targeted attacks usually points to nation state. Um, sometimes of course there's overlap. They can be affiliated with cyber crime, cyber crime, uh, uh, groups are typically, um, looking at some other targets for ROI, uh, bio there's there's a blend, right? So as an example, if we're looking at the, uh, apt groups I had last year, absolutely. Number one I would say would be healthcare. Healthcare was one of those, and it's, it's, it's, uh, you know, very unfortunate, but obviously with the shift that was happening at a pop up medical facilities, there's a big, a rush to change networks, uh, for a good cause of course, but with that game, um, you know, uh, security holes and concerns the targets and, and that's what we saw IPT groups targeting was going after those and, and ransomware and the cyber crime shrine followed as well. Right? Because if you can follow, uh, those critical networks and crippled them on from cybercriminals point of view, you can, you can expect them to pay the ransom because they think that they need to buy in order to, um, get those systems back online. Uh, in fact, last year or two, unfortunately we saw the first, um, uh, death that was caused because of a denial of service attack in healthcare, right. Facilities were weren't available because of the cyber attack. Patients had to be diverted and didn't make it on the way. >>All right. Jericho, sufficiently bummed out. So maybe in the time remaining, we can talk about remediation strategies. You know, we know there's no silver bullet in security. Uh, but what approaches are you recommending for organizations? How are you consulting with folks? >>Sure. Yeah. So a couple of things, um, good news is there's a lot that we can do about this, right? And, um, and, and basic measures go a long way. So a couple of things just to get out of the way I call it housekeeping, cyber hygiene, but it's always worth reminding. So when we talk about keeping security patches up to date, we always have to talk about that because that is reality as et cetera, these, these vulnerabilities that are still being successful are five to six years old in some cases, the majority two years old. Um, so being able to do that, manage that from an organization's point of view, really treat the new work from home. I don't like to call it a work from home. So the reality is it's work from anywhere a lot of the times for some people. So really treat that as, as the, um, as a secure branch, uh, methodology, doing things like segmentations on network, secure wifi access, multi-factor authentication is a huge muscle, right? >>So using multi-factor authentication because passwords are dead, um, using things like, uh, XDR. So Xers is a combination of detection and response for end points. This is a mass centralized management thing, right? So, uh, endpoint detection and response, as an example, those are all, uh, you know, good security things. So of course having security inspection, that that's what we do. So good threat intelligence baked into your security solution. That's supported by labs angles. So, uh, that's, uh, you know, uh, antivirus, intrusion prevention, web filtering, sandbox, and so forth, but then it gets that that's the security stack beyond that it gets into the end user, right? Everybody has a responsibility. This is that supply chain. We talked about. The supply chain is, is, is a target for attackers attackers have their own supply chain as well. And we're also part of that supply chain, right? The end users where we're constantly fished for social engineering. So using phishing campaigns against employees to better do training and awareness is always recommended to, um, so that's what we can do, obviously that's, what's recommended to secure, uh, via the endpoints in the secure branch there's things we're also doing in the industry, um, to fight back against that with prime as well. >>Well, I, I want to actually talk about that and talk about ecosystems and collaboration, because while you have competitors, you all want the same thing. You, SecOps teams are like superheroes in my book. I mean, they're trying to save the world from the bad guys. And I remember I was talking to Robert Gates on the cube a couple of years ago, a former defense secretary. And I said, yeah, but don't, we have like the best security people and can't we go on the offensive and weaponize that ourselves. Of course, there's examples of that. Us. Government's pretty good at it, even though they won't admit it. But his answer to me was, yeah, we gotta be careful because we have a lot more to lose than many countries. So I thought that was pretty interesting, but how do you collaborate with whether it's the U S government or other governments or other other competitors even, or your ecosystem? Maybe you could talk about that a little bit. >>Yeah. Th th this is what, this is what makes me tick. I love working with industry. I've actually built programs for 15 years of collaboration in the industry. Um, so, you know, we, we need, I always say we can't win this war alone. You actually hit on this point earlier, you talked about following and trying to disrupt the ROI of cybercriminals. Absolutely. That is our target, right. We're always looking at how we can disrupt their business model. Uh, and, and in order, there's obviously a lot of different ways to do that, right? So a couple of things we do is resiliency. That's what we just talked about increasing the security stack so that they go knocking on someone else's door. But beyond that, uh, it comes down to private, private sector collaborations. So, uh, we, we, uh, co-founder of the cyber threat Alliance in 2014 as an example, this was our fierce competitors coming in to work with us to share intelligence, because like you said, um, competitors in the space, but we need to work together to do the better fight. >>And so this is a Venn diagram. What's compared notes, let's team up, uh, when there's a breaking attack and make sure that we have the intelligence so that we can still remain competitive on the technology stack to gradation the solutions themselves. Uh, but let's, let's level the playing field here because cybercriminals moved out, uh, you know, um, uh, that, that there's no borders and they move with great agility. So, uh, that's one thing we do in the private private sector. Uh, there's also, uh, public private sector relationships, right? So we're working with Interpol as an example, Interfor project gateway, and that's when we find attribution. So it's not just the, what are these people doing like infrastructure, but who, who are they, where are they operating? What, what events tools are they creating? We've actually worked on cases that are led down to, um, uh, warrants and arrests, you know, and in some cases, one case with a $60 million business email compromise fraud scam, the great news is if you look at the industry as a whole, uh, over the last three to four months has been for take downs, a motet net Walker, uh, um, there's also IE Gregor, uh, recently as well too. >>And, and Ian Gregor they're actually going in and arresting the affiliates. So not just the CEO or the King, kind of these organizations, but the people who are distributing the ransomware themselves. And that was a unprecedented step, really important. So you really start to paint a picture of this, again, supply chain, this ecosystem of cyber criminals and how we can hit them, where it hurts on all angles. I've most recently, um, I've been heavily involved with the world economic forum. Uh, so I'm, co-author of a report from last year of the partnership on cyber crime. And, uh, this is really not just the pro uh, private, private sector, but the private and public sector working together. We know a lot about cybercriminals. We can't arrest them. Uh, we can't take servers offline from the data centers, but working together, we can have that whole, you know, that holistic effect. >>Great. Thank you for that, Derek. What if people want, want to go deeper? Uh, I know you guys mentioned that you do blogs, but are there other resources that, that they can tap? Yeah, absolutely. So, >>Uh, everything you can see is on our threat research blog on, uh, so 40 net blog, it's under expired research. We also put out, uh, playbooks, w we're doing blah, this is more for the, um, the heroes as he called them the security operation centers. Uh, we're doing playbooks on the aggressors. And so this is a playbook on the offense, on the offense. What are they up to? How are they doing that? That's on 40 guard.com. Uh, we also release, uh, threat signals there. So, um, we typically release, uh, about 50 of those a year, and those are all, um, our, our insights and views into specific attacks that are now >>Well, Derek Mackie, thanks so much for joining us today. And thanks for the work that you and your teams do. Very important. >>Thanks. It's yeah, it's a pleasure. And, uh, rest assured we will still be there 24 seven, three 65. >>Good to know. Good to know. And thank you for watching everybody. This is Dave Volante for the cube. We'll see you next time.

>>From around the globe, it's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Oh, welcome back to the cube. As we continue our coverage of AWS reinvent 2020, you know, I know you're familiar with Moneyball, the movie, Brad Pitt, starting as Billy Bean, the Oakland A's general manager, where the A's were all over data, right. With the Billy Bean approach, it was a very, uh, data driven approach to building his team and a very successful team. Well, AWS is taking that to an extraordinary level and with us to talk about that as Matt Hearst, who was the head of global sports marketing and communications at AWS and Matt, thanks for joining us here on the queue. >>John is my pleasure. Thanks so much for having me. You >>Bet. Um, now we've already heard from a couple of folks, NFL folks, uh, at re-invent, uh, about the virtual draft. Um, but for those of our viewers who maybe aren't up to speed on that, or having a chance to see, uh, what those folks had to say, uh, let's just talk about that as an opener, um, about your involvement with the NFL and particularly with, with the draft and, and what that announcement was all about. >>Sure. We, we saw, we've seen a great evolution with our work with the NFL over the past few years. And you mentioned during the infrastructure keynote where Michelle McKenna who's, the CIO for the NFL talks about how they were able to stage the 2020 virtual draft, which was the NFL is much most watched ever, uh, you know, over 55 million viewers over three days and how they were unable to do it without the help and the power of AWS, you know, utilizing AWS is reliability, scalability, security, and network connectivity, where they were able to manage thousands of live feeds to flow to the internet and go to ESPN, to airline. Um, but additionally, Jennifer LinkedIn, who's the SVP of player health and innovation at the NFL spoke during the machine learning keynote during reinvent. And she talked about how we're working with the NFL, uh, to co-develop the digital athlete, which is a computer simulation model of a football player that can replicate infinite scenarios in a game environment to help better foster and understanding of how to treat and rehabilitate injuries in the short term and in the long-term in the future, ultimately prevent, prevent and predict injuries. >>And they're using machine learning to be able to do that. So there's, those are just a couple of examples of, uh, what the NFL talked about during re-invent at a couple of keynotes, but we've seen this work with the NFL really evolve over the past few years, you know, starting with next gen stats. Those are the advanced statistics that, uh, brings a new level of entertainment to football fans. And what we really like to do, uh, with the NFL is to excite, educate, and innovate. And those stats really bring fans closer to the game to allow the broadcasters to go a little bit deeper, to educate the fans better. And we've seen some of those come to life through some of our ads, uh, featuring Deshaun Watson, Christian McCaffrey, um, these visually compelling statistics that, that come to life on screen. Um, and it's not just the NFL. AWS is doing this with some of the top sports leagues around the world, you know, powering F1 insights, Buddhist league, and match facts, six nations, rugby match stats, all of which utilize AWS technology to uncover advanced stats and really help educate and engage fans around the world in the sports that they love. >>Let's talk about that engagement with your different partners then, because you just touched on it. This is a wide array of avenues that you're exploring. You're in football, you're in soccer, you're in sailing, uh, you're uh, racing formula one and NASCAR, for example, all very different animals, right? In terms of their statistics and their data and of their fan interest, what fans ultimately want. So, um, maybe on a holistic basis first, how are you, uh, kind of filtering through your partner's needs and their fans needs and your capabilities and providing that kind of merger of capabilities with desires >>Sports, uh, for AWS and for Amazon are no different than any other industry. And we work backwards from the customer and what their needs are. You know, when we look at the sports partners and customers that we work with and why they're looking to AWS to help innovate and transform their sports, it's really the innovative technologies like machine learning, artificial intelligence, high performance computing, internet of things, for example, that are really transforming the sports world and some of the best teams and leagues that we've talked about, that you touched on, you know, formula one, NASCAR, NFL, Buena, Sligo, six nations, rugby, and so on and so forth are using AWS to really improve the athlete and the team performance transform how fans view and engage with sports and deliver these real-time advanced statistics to give fans, uh, more of that excitement that we're talking about. >>Let me give you a couple of examples on some of these innovative technologies that our customers are using. So the Seattle Seahawks, I built a data Lake on AWS to use it for talent, evaluation and acquisition to improve player health and recovery times, and also for their game planning. And another example is, you know, formula and we talk about the F1 insights, those advanced statistics, but they're also using AWS high-performance computing that helped develop the next generation race car, which will be introduced in the 2022 season. And by using AWS F1 was able to reduce the average time to run simulations by 70% to improve the car's aerodynamics, reducing the downforce loss and create more wheel to wheel racing, to bring about more excitement on the track. And a third example, similar to, uh, F1 using HPC is any of those team UK. So they compete in the America's cup, which is the oldest trophy in international sports. And endosteum UK is using an HPC environment running on Amazon, easy to spot instances to design its boat for the upcoming competition. And they're depending on this computational power on AWS needing 2000 to 3000 simulations to design the dimension of just a single boat. Um, and so the power of the cloud and the power of the AWS innovative technologies are really helping, uh, these teams and leagues and sports organizations around the world transform their sport. >>Well, let's go back. Uh, you mentioned the Seahawks, um, just as, uh, an example of maybe, uh, the kind of insights that that you're providing. Uh, let's pretend I'm there, there's an outstanding running back and his name's Matt Hearst and, uh, and he's at a, you know, a college let's just pretend in California someplace. Um, what kind of inputs, uh, are you now helping them? Uh, and what kind of insights are you trying to, are you helping them glean from those inputs that maybe they didn't have before? And how are they actually applying that then in terms of their player acquisition and thinking about draft, right player development, deciding whether Matt Hertz is a good fit for them, maybe John Wallace is a good fit for them. Um, but what are the kinds of, of, uh, what's that process look like? >>So the way that the Seahawks have built the data Lake, they built it on AWFs to really, as you talk about this talent, evaluation and acquisition, to understand how a player, you know, for example, a John Walls could fit into their scheme, you know, that, that taking this data and putting it in the data Lake and figuring out how it fits into their schemes is really important because you could find out that maybe you played, uh, two different positions in high school or college, and then that could transform into, into the schematics that they're running. Um, and try to find, I don't want to say a diamond in the rough, but maybe somebody that could fit better into their scheme than, uh, maybe the analysts or others could figure out. And that's all based on the power of data that they're using, not only for the talent evaluation and acquisition, but for game planning as well. >>And so the Seahawks building that data Lake is just one of those examples. Um, you know, when, when you talk about a player, health and safety, as well, just using the NFL as the example, too, with that digital athlete, working with them to co-develop that for that composite NFL player, um, where they're able to run those infinite scenarios to ultimately predict and prevent injury and using Amazon SageMaker and AWS machine learning to do so, it's super important, obviously with the Seahawks, for the future of that organization and the success that they, that they see and continue to see, and also for the future of football with the NFL, >>You know, um, Roger Goodell talks about innovation in the national football league. We hear other commissioners talking about the same thing. It's kind of a very popular buzz word right now is, is leagues look to, uh, ways to broaden their, their technological footprint in innovative ways. Again, popular to say, how exactly though, do you see AWS role in that with the national football league, for example, again, or maybe any other league in terms of inspiring innovation and getting them to perhaps look at things differently through different prisms than they might have before? >>I think, again, it's, it's working backwards from the customer and understanding their needs, right? We couldn't have predicted at the beginning of 2020, uh, that, you know, the NFL draft will be virtual. And so working closely with the NFL, how do we bring that to life? How do we make that successful, um, you know, working backwards from the NFL saying, Hey, we'd love to utilize your technology to improve Clare health and safety. How are we able to do that? Right. And using machine learning to do so. So the pace of innovation, these innovative technologies are very important, not only for us, but also for these, uh, leagues and teams that we work with, you know, using F1 is another example. Um, we talked about HPC and how they were able to, uh, run these simulations in the cloud to improve, uh, the race car and redesign the race car for the upcoming seasons. >>But, uh, F1 is also using Amazon SageMaker, um, to develop new F1 insights, to bring fans closer to the action on the track, and really understand through technology, these split-second decisions that these drivers are taking in every lap, every turn, when to pit, when not to pit things of that nature and using the power of the cloud and machine learning to really bring that to life. And one example of that, that we introduced this year with, with F1 was, um, the fastest driver insight and working F1, worked with the Amazon machine learning solutions lab to bring that to life and use a data-driven approach to determine the fastest driver, uh, over the last 40 years, relying on the years of historical data that they store in S3 and the ML algorithms that, that built between AWS and F1 data scientists to produce this result. So John, you and I could sit here and argue, you know, like, like two guys that really love F1 and say, I think Michael Schumacher is the fastest drivers. It's Lewis, Hamilton. Who's great. Well, it turned out it was a arts incentive, you know, and Schumacher was second. And, um, Hamilton's third and it's the power of this data and the technology that brings this to life. So we could still have a fun argument as fans around this, but we actually have a data-driven results through that to say, Hey, this is actually how it, how it ranked based on how everything works. >>You know, this being such a strange year, right? With COVID, uh, being rampant and, and the major influence that it has been in every walk of global life, but certainly in the American sports. Um, how has that factored into, in terms of the kinds of services that you're looking to provide or to help your partners provide in order to increase that fan engagement? Because as you've pointed out, ultimately at the end of the day, it's, it's about the consumer, right? The fan, and giving them info, they need at the time they want it, that they find useful. Um, but has this year been, um, put a different point on that for you? Just because so many eyeballs have been on the screen and not necessarily in person >>Yeah. T 20, 20 as, you know, a year, unlike any other, um, you know, in our lifetimes and hopefully going forward, you know, it's, it's not like that. Um, but we're able to understand that we can still bring fans closer to the sports that they love and working with, uh, these leagues, you know, we talk about NFL draft, but with formula one, we, uh, in the month of may developed the F1 Pro-Am deep racer event that featured F1 driver, uh, Daniel Ricardo, and test driver TA Sianna Calderon in this deep racer league and deep racers, a one 18th scale, fully autonomous car, um, that uses reinforcement learning, learning a type of machine learning. And so we had actual F1 driver and test driver racing against developers from all over the world. And technology is really playing a role in that evolution of F1. Um, but also giving fans a chance to go head to head against the Daniel Ricardo, which I don't know that anyone else could ever say that. >>Yeah, I raced against an F1 driver for head to head, you know, and doing that in the month of may really brought forth, not only an appreciation, I think for the drivers that were involved on the machine learning and the technology involved, but also for the developers on these split second decisions, these drivers have to make through an event like that. You know, it was, it was great and well received. And the drivers had a lot of fun there. Um, you know, and that is the national basketball association. The NBA played in the bubble, uh, down in Orlando, Florida, and we work with second spectrum. They run on AWS. And second spectrum is the official optical provider of the NBA and they provide Clippers court vision. So, uh, it's a mobile live streaming experience for LA Clippers fans that uses artificial intelligence and machine learning to visualize data through on-screen graphic overlays. >>And second spectrum was able to rely on, uh, AWS is reliability, connectivity, scalability, and move all of their equipment to the bubble in Orlando and still produce a great experience for the fans, um, by reducing any latency tied to video and data processing, um, they needed that low latency to encode and compress the media to transfer an edit with the overlays in seconds without losing quality. And they were able to rely on AWS to do that. So a couple of examples that even though 2020 was, uh, was a little different than we all expected it to be, um, of how we worked closely with our sports partners to still deliver, uh, an exceptional fan experience. >>So, um, I mean, first off you have probably the coolest job at AWS. I think it's so, uh, congratulations. I mean, it's just, it's fascinating. What's on your want to do less than in terms of 20, 21 and beyond and about what you don't do now, or, or what you would like to do better down the road, any one area in particular that you're looking at, >>You know, our, our strategy in sports is no different than any other industry. We want to work backwards from our customers to help solve business problems through innovation. Um, and I know we've talked about the NFL a few times, but taking them for, for another example, with the NFL draft, improving player health and safety, working closely with them, we're able to help the NFL advance the game both on and off the field. And that's how we look at doing that with all of our sports partners and really helping them transform their sport, uh, through our innovative technologies. And we're doing this in a variety of ways, uh, with a bunch of engaging content that people can really enjoy with the sports that they love, whether it's, you know, quick explainer videos, um, that are short two minute or less videos explaining what these insights are, these advanced stats. >>So when you see them on the screening and say, Oh yeah, I understand what that is at a, at a conceptual level or having blog posts from a will, Carlin who, uh, has a long storied history in six nations and in rugby or Rob Smedley, along story history and F1 writing blog posts to give fans deeper perspective as subject matter experts, or even for those that want to go deeper under the hood. We've worked with our teams to take a deeper look@howsomeofthesecometolifedetailingthetechnologyjourneyoftheseadvancedstatsthroughsomedeepdiveblogsandallofthiscanbefoundataws.com slash sports. So a lot of great rich content for, uh, for people to dig into >>Great stuff, indeed. Um, congratulations to you and your team, because you really are enriching the fan experience, which I am. One of, you know, hundreds of millions are enjoying that. So thanks for that great work. And we wish you all the continued success down the road here in 2021 and beyond. Thanks, Matt. Thanks so much, Sean.

>>from around the globe. It's the Cube with digital coverage of workplace next made possible by Hewlett Packard Enterprise. >>Hello, everyone. We're here covering workplace next on the Cube For years, you know, we've talked about new ways to work, and it was great thought exercise. And then overnight the pandemic heightened the challenges of creating an effective work force. Most of the executives that we talked to in our survey say that productivity actually has improved since the work from Home Mandate was initiative. But, you know, we're talking not just about productivity, but the well being of our associates and managing the unknown. We're going to shift gears a little bit now. We've heard some interesting real world examples of how organizations are dealing with the rapid change in workplace, and we've heard about some lessons to take into the future. But now we're going to get more practical and look at some of the tools that are available to help you navigate. The changes that we've been discussing and with me to talk about these trends related to the future of work are are are Qadoura, who's the vice president of worldwide sales and go to market for Green Lake at HP Sadat Malik is the VP of I O t and Intelligent Edge at HP and Satish Yarra Valley is the global cloud and infrastructure practice Head at Whip Probe guys welcomes. Good to see you. Thanks for coming on. >>Thanks for having us. >>You're very welcome. Let me start with Sadat. You're coming from Austin, Texas here. So thank you. Stay crazy. As they say in Austin, for the uninitiated, maybe you could talk a little bit about h p E point. Next. It's a strategic component of H p. E. And maybe tell us a little bit about those services. >>Thank you so much for taking the time today. Appreciate everybody's participation here. So absolutely so point Next is HP Services on. This is the 23,000 strong organization globally spread out, and we have a very strong ecosystem of partners that be leveraged to deliver services to our customers. Um, our organization differentiates itself in the market by focusing on digital digital transformation journeys for our customers. For customers looking toe move to a different way off, engaging with its customers, transforming the way its employees work, figuring out a different way off producing the products that it sells to. His customers are changing the way it operationalize these things. For example, moving to the cloud going to a hybrid model, we help them achieve any of these four transformation outcomes. So point next job is toe point. What is next in this digital transformation journey and then partner with our customers to make that happen? So that's what we do. >>Thank you for that. I mean, obviously, you're gonna be seeing a lot of activity around workplace with shift from work from home, changes in the network changes in security. I mean the whole deal. What are some of your top takeaways that you can share with our audience? >>Yeah, they're >>so a lot has been happening in the workplace arena lately. So this is not new, right? This is not something that all of a sudden side happening when Kobe 19 hit, uh, the digital workplace was already transforming before over 19 happened. What over 19 has done is that it has massively accelerated the pace at which this change was happening. So, for example, right remote work was already there before over 19. But now everybody is working remotely so, in many ways, the solution that we have for remote work. They have been strained to appoint, never seen before. Networks that support these remote work environments have been pushed to their limits. Security was already there, right? So security was a critical piece off any off the thinking, any of the frameworks that we had. But now security is pivotal and central. Any discussion that we're having about the workplace environment data is being generated all across the all across the environment that we operated, right? So it's no longer being generated. One place being stored. Another. It's all over the place now. So what Kobe, 19 has done is that the transformation that was already underway in the digital workplace, it has taken that and accelerated it massive. The key take away for me is right that we have to make sure that when we're working with our customers, our clients, we don't just look at the technology aspect of things. We have to look at all the other aspect as well the people in the process aspect off this environment. It is critical that we don't assume that just because the technology is there to address these challenges that I just mentioned. Our people and our processes would be able to handle that as well. We need to bring everybody along. Everybody has different needs, and we need to be able to cater to those needs effectively. So that's my biggest take away. Make sure that the process and the people aspect of things was hand in glove with the technology that we were able to bring to bear here. >>Got it. Thank you. So, ah, let's go to San Francisco, bringing our war to the conversation. You're one of your areas of focus is is HP Green Lake. You guys were early on with the as a service model. Clearly, we've seen Mawr interest in cloud and cloud like models. I wonder if you could just start by sharing. What's Green Lake all about? Where does it fit into this whole workplace? Next, Uh, conversation that we're having? >>Yeah, absolutely. Um HP Green lake effectively is the cloud that comes to your data center to your Coehlo or to your edge, right? We saw with Public Cloud. The public cloud brought a ton of innovations, um, into the sort of hyper scale model. Now, with HP. What we've done is we've said, Look, customers need this level of innovation and this level of, you know, pay as you go economics the, you know, management layer the automation layer not just in a public cloud environment, but also in our customers data center or to the other potential edges or Coehlo scenarios. And what we've done is we've brought together Asada just mentioned the best of our point next services our software management layer as well as H. P. E s rich portfolio of hardware to come together to create that cloud experience. Um, of course, we can't do this without the rich ecosystem around us as well. And so everything from you know, some of our big S I partners like we bro, who also have the virtual desktop expertise or virtual desk that then come together to start helping us launch some of these new workloads supported cloud services such as D. D i eso for my perspective, v. D. I is the most important topic for a lot of our customers right now, especially in sectors like financial services, um, advanced engineering scenarios and health care where they need access to those, uh to their data centers in a very secure way and in a highly cost optimized way as well. >>Well, okay. Thank you. And then let's let's bring in, uh, petition talk a little bit about the ecosystem. I mean, we're pro. That's really kind of your wheelhouse. We've been talking a lot on the cube about moving from an industry of point products to platforms and now ecosystem innovation, Uh, are are mentioned VD I we saw that exploding eso teach. Maybe you could weigh in here and and share with us what you're seeing in the market and specifically around ecosystem. >>As we all know, the pandemic has redefined the way we collaborate to support this collaboration. We have set up huge campuses and office infrastructure In summary, our industry has centralized approach. Now, the very premise of the centralization bringing people together for work has changed. This evolving workspace dynamics have triggered the agency to reimagine the workspace strategy. CEO, CEO S and C H R ose are all coming together to redefine the business process and find new ways off engaging with customers and employees as organizations embrace work from home for the foreseeable future. Customer need to create secure by design workspaces for remote working environments. With the pro virtual disk platform, we can help create such seamless distal workspaces and enable customers to connect, collaborate and communicate with ease from anywhere securely. They're consistent user experience. Through this platform led approach, we are able to utter the market demands which are focused on business outcomes. >>Okay, and this is the specifics of this hard news that you're talking about Video on demand and Citrix coming together with your ecosystem. H p E were pro and again, the many partners that you work with is that correct? >>Well, actually, Dave, we see a strong playoff ecosystem partners coming together to achieve transformative business outcomes. As Arbor said earlier, HP and Wipro have long standing partnership, and today's announcement around HP Green Lake is an extension off this collaboration, where we provide leverage HP Green Leg Andre Pro, which elders platform to offer video as a service in a paper user model. Our aim is to enable customers fast track there. It is still works based transformation efforts by eliminating the need to support upfront capital investments and old provisioning costs while allowing customers to enjoy the benefit off compromise, control, security and compliance. Together, we have implemented our solution across various industry segments and deliver exceptional customer experiences by helping customer businesses in their workspace. Transformation journeys by defining their workspace strategy with an intelligent, platform led approach that enables responsiveness, scalability and resilience. It's known that Wipro is recognized as a global leader in the distal workspace and video I, with HP being a technology leader, enabling us with high level of program ability on integration capabilities. We see tremendous potential to jointly address the industry challenges as we move forward. >>Excellent. Uh, sad. I wanna come back to you. We talk a lot about the digital business, the mandate for digital business, especially with the pandemic. Let's talk about data. Earlier this year, HP announced the number of solutions that used data to help organizations work more productively safely. You know, the gamut talk about data and the importance of data and what you guys were doing there specifically, >>Yeah, that's a great question. So that is fundamental to everything that we're doing in the workplace arena, right? So from a technology perspective that provides us with the wherewithal to be able to make all the changes that we want to make happen for the people in the process side of things. So the journey that we've been on this past year is a very interesting one. Let me share with the audience a little bit of what's been going on on the ground with our customers. Um, what's what's been happening in the field? So when the when Kobe 19 hit right, a lot of our customers were subjected to these shutdown, which were very pervasive, and they had to stop their operations. In many cases, they had to send their employees home. So at that point, HB stepped in the point. Next organization stepped in and helped these customers set up remote work out options, which allowed them to keep their businesses going while they handle these shutdowns. Fast forward. Six months and the shutdown. We're starting to get lifted and our customers were coming back to us and saying to us that Hey, we would now like to get a least a portion off our workforce back to the normal place of work. But we're concerned that if we do that, it's gonna jeopardize their safety because off the infection concerned that were there. So what we did was that we built a cities or five solutions using various types of video analytics and data analysis analysis technologies that allowed these customers to make that move. So these five solutions, uh, let me walk, walk our customers and our clients and audience through those. The first two of these solutions are touchless entry and fever detection. So this is the access control off your premise, right? So to make sure that whoever is entering the building that's in a safe manner and any infection concerned, we stop it at the very get go once the employees inside the workplace, the next thing that we have is a set of two solutions. What one is social distance tracing and tracking, and the other one is workplace alerting. What these two solutions do is that they use video analytics and data technology is to figure out if there is a concern with employees adhering to the various guidelines that are in place on alerting the employees and the employers if there is any infringement happening which could risk overall environment. Finally, we realized right that irrespective off how much technology and process we put in place. Not everybody will be able to come into the normal place of work. So what we have done is that the first solution that we have is augmented reality and visual remote guidance. This solution uses a our technologies allow. People were on site to take advantage of the expertise that resides offsite to undertake complex task task, which could be as complex as overhauling a machine on ah factory floor using augmented reality where somebody off site who's an expert in that machine is helping somebody on site data has become central to a lot of the things that we do. But as I said, technology is one aspect of things. So ultimately the people process technology continuum has to come together to make these solutions real for our customers. >>Thank you, Arwa. We just have just about 30 seconds left and I wonder if you could close on. We're talking about cloud hybrid. Uh, everybody's talking about hybrid. We're talking about the hybrid workplace. What do you see for the for the future over the next 2345 years? >>Absolutely. And I think you're right, Dave. It is, ah, hybrid world. It's a multi cloud world. Ultimately, what our customers want is the choice and the flexibility to bring in the capabilities that drive the business outcomes that they need to support. And that has multiple dimensions, right? It's making sure that they are minimizing their egress costs, right. And many of our on Prem solutions do give them that flexibility. It is the paper use economics that we talked about. It is about our collective capability as an ecosystem to come together. You know, with Citrix and NVIDIA with R s I partner we pro and the rich heritage of HP es services as well as hardware to bring together these solutions that are fully managed on behalf of our customers so that they can focus their staff their i t capabilities on the products and services they need to deliver to their customers. >>Awesome. Guys, I wish we had more time. We got to go day volonte for the cube. Keep it right there. Lots of great more content coming your way. >>Yeah,

>> From the CUBE studios in Palo Alto in Boston, bringing you data-driven insights from the CUBE in ETR. This is breaking analysis with Dave Vellante. >> Earlier these week, the U S department of justice, along with attorneys general from 11 States filed a long expected antitrust lawsuit, accusing Google of being a monopoly gatekeeper for the internet. The suit draws on section two of the Sherman antitrust act, which makes it illegal to monopolize trade or commerce. Of course, Google is going to fight the lawsuit, but in our view, the company has to make bigger moves to diversify its business and the answer we think lies in the cloud and at the edge. Hello everyone. This is Dave Vellante and welcome to this week's Wiki Bond Cube insights powered by ETR. In this Breaking Analysis, we want to do two things. First we're going to review a little bit of history, according to Dave Vollante of the monopolistic power in the computer industry. And then next, we're going to look into the latest ETR data. And we're going to make the case that Google's response to the DOJ suit should be to double or triple its focus on cloud and edge computing, which we think is a multi-trillion dollar opportunity. So let's start by looking at the history of monopolies in technology. We start with IBM. In 1969 the U S government filed an antitrust lawsuit against Big Blue. At the height of its power. IBM generated about 50% of the revenue and two thirds of the profits for the entire computer industry, think about that. IBM has monopoly on a relative basis, far exceeded that of the virtual Wintel monopoly that defined the 1990s. IBM had 90% of the mainframe market and controlled the protocols to a highly vertically integrated mainframe stack, comprising semiconductors, operating systems, tools, and compatible peripherals like terminal storage and printers. Now the government's lawsuit dragged on for 13 years before it was withdrawn in 1982, IBM at one point had 200 lawyers on the case and it really took a toll on IBM and to placate the government during this time and someone after IBM made concessions such as allowing mainframe plug compatible competitors to access its code, limiting the bundling of application software in fear of more government pressure. Now the biggest mistake IBM made when it came out of antitrust was holding on to its mainframe past. And we saw this in the way it tried to recover from the mistake of handing its monopoly over to Microsoft and Intel. The virtual monopoly. What it did was you may not remember this, but it had OS/2 and Windows and it said to Microsoft, we'll keep OS/2 you take Windows. And the mistake IBM was making with sticking to the PC could be vertically integrated, like the main frame. Now let's fast forward to Microsoft. Microsoft monopoly power was earned in the 1980s and carried into the 1990s. And in 1998 the DOJ filed the lawsuit against Microsoft alleging that the company was illegally thwarting competition, which I argued at the time was the case. Now, ironically, this is the same year that Google was started in a garage. And I'll come back to that in a minute. Now, in the early days of the PC, Microsoft they were not a dominant player in desktop software, you had Lotus 1-2-3, WordPerfect. You had this company called Harvard Presentation Graphics. These were discreet products that competed very effectively in the market. Now in 1987, Microsoft paid $14 million for PowerPoint. And then in 1990 launched Office, which bundled Spreadsheets, Word Processing, and presentations into a single suite. And it was priced far more attractively than the some of the alternative point products. Now in 1995, Microsoft launched Internet Explorer, and began bundling its browser into windows for free. Windows had a 90% market share. Netscape was the browser leader and a high flying tech company at the time. And the company's management who pooed Microsoft bundling of IE saying, they really weren't concerned because they were moving up the stack into business software, now they later changed that position after realizing the damage that Microsoft bundling would do to its business, but it was too late. So in similar moves of ineptness, Lotus refuse to support Windows at its launch. And instead it wrote software to support the (indistinct). A mini computer that you probably have never even heard of. Novell was a leader in networking software at the time. Anyone remember NetWare. So they responded to Microsoft's move to bundle network services into its operating systems by going on a disastrous buying spree they acquired WordPerfect, Quattro Pro, which was a Spreadsheet and a Unix OS to try to compete with Microsoft, but Microsoft turned the volume and kill them. Now the difference between Microsoft and IBM is that Microsoft didn't build PC hardware rather it partnered with Intel to create a virtual monopoly and the similarities between IBM and Microsoft, however, were that it fought the DOJ hard, Okay, of course. But it made similar mistakes to IBM by hugging on to its PC software legacy. Until the company finally pivoted to the cloud under the leadership of Satya Nadella, that brings us to Google. Google has a 90% share of the internet search market. There's that magic number again. Now IBM couldn't argue that consumers weren't hurt by its tactics. Cause they were IBM was gouging mainframe customers because it could on pricing. Microsoft on the other hand could argue that consumers were actually benefiting from lower prices. Google attorneys are doing what often happens in these cases. First they're arguing that the government's case is deeply flawed. Second, they're saying the government's actions will cause higher prices because they'll have to raise prices on mobile software and hardware, Hmm. Sounds like a little bit of a threat. And of course, it's making the case that many of its services are free. Now what's different from Microsoft is Microsoft was bundling IE, that was a product which was largely considered to be crap, when it first came out, it was inferior. But because of the convenience, most users didn't bother switching. Google on the other hand has a far superior search engine and earned its rightful place at the top by having a far better product than Yahoo or Excite or Infoseek or even Alta Vista, they all wanted to build portals versus having a clean user experience with some non-intrusive of ads on the side. Hmm boy, is that part changed, regardless? What's similar in this case with, as in the case with Microsoft is the DOJ is arguing that Google and Apple are teaming up with each other to dominate the market and create a monopoly. Estimates are that Google pays Apple between eight and $11 billion annually to have its search engine embedded like a tick into Safari and Siri. That's about one third of Google's profits go into Apple. And it's obviously worth it because according to the government's lawsuit, Apple originated search accounts for 50% of Google search volume, that's incredible. Now, does the government have a case here? I don't know. I'm not qualified to give a firm opinion on this and I haven't done enough research yet, but I will say this, even in the case of IBM where the DOJ eventually dropped the lawsuit, if the U S government wants to get you, they usually take more than a pound of flesh, but the DOJ did not suggest any remedies. And the Sherman act is open to wide interpretation so we'll see. What I am suggesting is that Google should not hang too tightly on to it's search and advertising past. Yes, Google gives us amazing free services, but it has every incentive to appropriate our data. And there are innovators out there right now, trying to develop answers to that problem, where the use of blockchain and other technologies can give power back to us users. So if I'm arguing that Google shouldn't like the other great tech monopolies, hang its hat too tightly on the past, what should Google do? Well, the answer is obvious, isn't it? It's cloud and edge computing. Now let me first say that Google understandably promotes G Suite quite heavily as part of its cloud computing story, I get that. But it's time to move on and aggressively push into the areas that matters in cloud core infrastructure, database, machine intelligence containers and of course the edge. Not to say that Google isn't doing this, but there are areas of greatest growth potential that they should focus on. And the ETR data shows it. But let me start with one of our favorite graphics, which shows the breakdown of survey respondents used to derive net score. Net score remembers ETR's quarterly measurement of spending velocity. And here we show the breakdown for Google cloud. The lime green is new adoptions. The forest green is the percentage of customers increasing spending more than 5%. The gray is flat and the pinkish is decreased by 6% or more. And the bright red is we're replacing or swapping out the platform. You subtract the reds from the greens and you get a net score at 43%, which is not off the charts, but it's pretty good. And compares quite favorably to most companies, but not so favorite with AWS, which is at 51% and Microsoft which is at 49%, both AWS and Microsoft red scores are in the single digits. Whereas Google's is at 10%, look all three are down since January, thanks to COVID, but AWS and Microsoft are much larger than Google. And we'd like to see stronger across the board scores from Google. But there's good news in the numbers for Google. Take a look at this chart. It's a breakdown of Google's net scores over three survey snapshots. Now we skip January in this view and we do that to provide a year of a year context for October. But look at the all important database category. We've been watching this very closely, particularly with the snowflake momentum because big query generally is considered the other true cloud native database. And we have a lot of respect for what Google is doing in this area. Look at the areas of strength highlighted in the green. You've got machine intelligence where Google is a leader AI you've got containers. Kubernetes was an open source gift to the industry, and linchpin of Google's cloud and multi-cloud strategy. Google cloud is strong overall. We were surprised to see some deceleration in Google cloud functions at 51% net scores to be on honest with you, because if you look at AWS Lambda and Microsoft Azure functions, they're showing net scores in the mid to high 60s. But we're still elevated for Google. Now. I'm not that worried about steep declines, and Apogee and Looker because after an acquisitions things kind of get spread out around the ETR taxonomy so don't be too concerned about that. But as I said earlier, G Suite may just not that compelling relative to the opportunity in other areas. Now I won't show the data, but Google cloud is showing good momentum across almost all interest industries and sectors with the exception of consulting and small business, which is understandable, but notable deceleration in healthcare, which is a bit of a concern. Now I want to share some customer anecdotes about Google. These comments come from an ETR Venn round table. The first comment comes from an architect who says that "it's an advantage that Google is "not entrenched in the enterprise." Hmm. I'm not sure I agree with that, but anyway, I do take stock in what this person is saying about Microsoft trying to lure people away from AWS. And this person is right that Google essentially is exposed its internal cloud to the world and has ways to go, which is why I don't agree with the first statement. I think Google still has to figure out the enterprise. Now the second comment here underscores a point that we made earlier about big query customers really like the out of the box machine learning capabilities, it's quite compelling. Okay. Let's look at some of the data that we shared previously, we'll update this chart once the company's all report earnings, but here's our most recent take on the big three cloud vendors market performance. The key point here is that our data and the ETR data reflects Google's commentary in its earning statements. And the GCP is growing much faster than its overall cloud business, which includes things that are not apples to apples with AWS the same thing is true with Azure. Remember AWS is the only company that provides clear data on its cloud business. Whereas the others will make comments, but not share the data explicitly. So these are estimates based on those comments. And we also use, as I say, the ETR survey data and our own intelligence. Now, as one of the practitioners said, Google has a long ways to go as buddy an eighth of the size of AWS and about a fifth of the size of Azure. And although it's growing faster at this size, we feel that its growth should be even higher, but COVID is clear a factor here so we have to take that into consideration. Now I want to close by coming back to antitrust. Google spends a lot on R&D, these are quick estimates but let me give you some context. Google shells out about $26 billion annually on research and development. That's about 16% of revenue. Apple spends less about 16 billion, which is about 6% of revenue, Amazon 23 billion about 8% of the top line, Microsoft 19 billion or 13% of revenue and Facebook 14 billion or 20% of revenue, wow. So Google for sure spends on innovation. And I'm not even including CapEx in any of these numbers and the hype guys as you know, spend tons on CapEx building data centers. So I'm not saying Google cheaping out, they're not. And I got plenty of cash in there balance sheet. They got to run 120 billion. So I can't criticize they're roughly $9 billion in stock buybacks the way I often point fingers at what I consider IBM's overly wall street friendly use of cash, but I will say this and it was Jeff Hammerbacher, who I spoke with on the Cube in the early part of last decade at a dupe world, who said "the best minds of my generation are spending there time, "trying to figure out how to get people to click on ads." And frankly, that's where much of Google's R&D budget goes. And again, I'm not saying Google doesn't spend on cloud computing. It does, but I'm going to make a prediction. The post cookie apocalypse is coming soon, it may be here. iOS 14 makes you opt in to find out everything about you. This is why it's such a threat to Google. The days when Google was able to be the keeper of all of our data and to house it and to do whatever it likes with that data that ended with GDPR. And that was just the beginning of the end. This decade is going to see massive changes in public policy that will directly affect Google and other consumer facing technology companies. So my premise is that Google needs to step up its game and enterprise cloud and the edge much more than it's doing today. And I like what Thomas Kurian is doing, but Google's undervalued relative to some of the other big tech names. And I think it should tell wall street that our future is in enterprise cloud and edge computing. And we're going to take a hit to our profitability and go big in those areas. And I would suggest a few things, first ramp up R&D spending and acquisitions even more. Go on a mission to create cloud native fabric across all on-prem and the edge multicloud. Yes, I know this is your strategy, but step it up even more forget satisfying investors. You're getting dinged in the market anyway. So now's the time the moon wall street and attack the opportunity unless you don't see it, but it's staring you right in the face. Second, get way more cozy with the enterprise players that are scared to death of the cloud generally. And they're afraid of AWS in particular, spend the cash and go way, way deeper with the big tech players who have built the past IBM, Dell, HPE, Cisco, Oracle, SAP, and all the others. Those companies that have the go to market shops to help you win the day in enterprise cloud. Now, I know you partner with these companies already, but partner deeper identify game-changing innovations that you can co-create with these companies and fund it with your cash hoard. I'm essentially saying, do what you do with Apple. And instead of sucking up all our data and getting us to click on ads, solve really deep problems in the enterprise and the edge. It's all about actually building an on-prem to cloud across cloud, to the edge fabric and really making that a unified experience. And there's a data angle too, which I'll talk about now, the data collection methods that you've used on consumers, it's incredibly powerful if applied responsibly and correctly for IOT and edge computing. And I don't mean to trivialize the complexity at the edge. There really isn't one edge it's Telcos and factories and banks and cars. And I know you're in all these places Google because of Android, but there's a new wave of data coming from machines and cars. And it's going to dwarf people's clicks and believe me, Tesla wants to own its own data and Google needs to put forth a strategy that's a win-win. And so far you haven't done that because your head is an advertising. Get your heads out of your ads and cut partners in on the deal. Next, double down on your open source commitment. Kubernetes showed the power that you have in the industry. Ecosystems are going to be the linchpin of innovation over the next decade and transcend products and platforms use your money, your technology, and your position in the marketplace to create the next generation of technology leveraging the power of the ecosystem. Now I know Google is going to say, we agree, this is exactly what we're doing, but I'm skeptical. Now I think you see either the cloud is a tiny little piece of your business. You have to do with Satya Nadella did and completely pivot to the new opportunity, make cloud and the edge your mission bite the bullet with wall street and go dominate a multi-trillion dollar industry. Okay, well there you have it. Remember, all these episodes are available as podcasts, so please subscribe wherever you listen. I publish weekly on Wikibond.com and Siliconangle.com and I post on LinkedIn each week as well. So please comment or DM me @DVollante, or you can email me @David.Vollante @Siliconangle.com. And don't forget to check out etr.plus that's where all the survey action is. This is Dave Vollante for the Cube Insights powered by ETR. Thanks for watching everybody be well. And we'll see you next. (upbeat instrumental)

>>Hello. Everyone were here it the Data Cloud summit and we had a real treat for you. I call it the CMO Power Panel. We're gonna explore how data is transforming marketing, branding and promotion, and with me, a three phenomenal marketing pros and chief marketing officers. Denise Person is the CMO Snowflakes Kat Holden of Thought spot and Laura Langdon of Whip pro Folks. Great to see you. Thanks so much for coming on the Cube. >>Great to be with you, David. >>Awesome. Denise, let's let's start with you. I want to talk about the role and the changing role of the CMO. It's changed a lot, you know, sports, of course, with all this data, but I wonder what you're experiencing and can you share us share with us? Why marketing, especially, is being impacted by data? >>Well, data is really what has helped us marketers turn ourselves into revenue drivers instead instead of call centers, and that's definitely a much better place to be. We come today measure things that were never possible before. What a person most excited about is the rial time access to data we have today. In the past, we used to get stale reports, you know, weeks after a marketing program was over. Today we get data in real time as our campaigns are up and running. And this is really what enables us to make those riel time adjustments to our investments in real time. And that is really have a profound impact on the results were having. And also today, you know, more than ever, adaptability is truly the superpower or marketing today and day. That's really what allows us to adapt to our customers preferences in real time. And that's really critical at this time. >>That's interesting what you say because, you know, in tough times used to be okay. Sales and engineering put a brick wall around those and you know the name it. Marketing, Say Okay, cut. But now it's like you go to marketing and say, Okay, what's the data say? How do we have to pivot and Scott? I wonder what of data and cloud really brought to the modern marketer that you might not have had before this modern era? >>Well, it Z this era. I don't think there's ever been a better time to be a marketer than there is right now, and The primary reason is that we have access to data and insights like we've never had, and I'm not exaggerating. When I say that I have 100 times more access to data, then I had a decade. It's just phenomenal when you look at the power of cloud search, ai These new consumer experiences for analytics. We can do things in seconds that used to take days and so it's B comments did he said. Ah, superpower for us toe. Have access to so much data and it's, you know, Kobe has been hard. Ah, lot of our marketing teams who've never worked harder, making this pivot from the physical world to the virtual world. But there, you know, at least we're working, and three other part of it is that digital she's created this phenomenal opportunity for us because the beauty of digital and digital transformation is that everything now is trackable, which makes it measurable and means that we can actually get insights that we can act on in a smarter way. And you know, it's worth giving an example. If you just look at this show right, like this event that we're doing in a physical world, all of you watching at home, you'd be in front of us in a room and we'd be able to know if you're in the room, right? We tracking the scanners when you walked in. But that's basically it. At that point, we don't really get a good sense for how much you like what we're saying. Uh, maybe you filled out a survey, but only 5 to 10% of people ever do that in the digital world. We know how long you stick around, and as a result, like it's easy people could just with the click, you know, change the channel. And so the bar for content has gone way up as we do these events. But we know how long people are sticking around. And that's what's so special about it. You know Denise and her team as the host of this show, they're going to know how long people watch this segment and that knowing is powerful. I mean, it's simple as using a product like thought spot. You could just ask a question. How many you know, what's the average view? Time by session and boom and sharp pops up. You're gonna know what's working, what's not. And that's something that you could take and act on in the future. And that's what our That's what customers were doing. So you know, snowflake in the spot that we share a customer with Lulu and they're tracking programs. So what people are watching at home, how long they're watching what they're watching next, and they're able to do that in a super granular way and improve their content as a result. And that's the power of this new world we live in. Uh, that's made the cloud and data so accessible to folks like us. >>Well, thank you for that. And I want to come back to that notion to understand how you're bringing data into your marketing office. But I wanna bring Laura and Laura were pro You guys partner with a lot of brands, a lot of companies around the world. I mean, thousands of partners, obviously snowflake and thought spot are, too. How are you using data to optimize these co marketing relationships? You know specifically, what are the trends that you're seeing around around things like customer experience? >>So, you know, we used data for all of our marketing decisions our own as well as with our partners. And I think what's really been interesting about partner marketing data is we can we can feed that back to our sales team, right? So it's very directional for them as well in their efforts moving forward. So I think that's a place where specifically to partners, it's really powerful. We can also use our collective data to go out to customers to better effect. And then, you know, regarding these trends, we just did a survey on the state of the intelligent enterprise. We we interviewed 300 companies, US and UK, and there were three Interesting. I thought statistics relevant to this, um, Onley 22% of the companies that we interviewed felt that their marketing was where it needed to be from an automation standpoint. So lots of room for us to grow right. Lots of space for us to play. And 61% of them believed that it was critical that they implement this technology to become a more intelligent enterprise. But when they ranked readiness by function, marketing came in six right, so H R R and D finance were all ahead of marketing. It was followed by sales, you know, And then the final data point that I think was interesting was 40% of those agreed that while the technology was the most important thing, that thought leadership was critical, you know? And I think that's where marketers really could bring. You know, our tried and true experience to bear and merging with this technology. >>Great. Thank you. So so did he say I've been getting the Kool Aid injection this week around Data Cloud have been pushing people, But now that I have the CMO in front of me, I wanna ask about the data cloud and what it means specifically for the customers. And what are some of the learnings? Maybe that you've experienced that can support some of the things that that Laura and Scott were just discussing. >>Yeah. Scott said before, right, he had 100 times more data than he ever has before. And that's again, if you look at all the companies we talked to around the world, it's not about the amount of data that they have. That is the problem is the ability to access that data that data for most companies is trapped across Silas across the organization. It's It's in data applications, systems of records. Some of that data sits with your partners that you want access, and that's really what the data clouds camps in. Data Cloud is really mobilizing that data for you. It brings all that data together for you in one place so you can finally access that data and really provide ubiquitous access to that data to everyone in your organization that needs it and can truly unlock the value off that data. And from a marketing perspective, I mean, we are responsible for the customer experience, you know, we provide to our customers. And if you have access toe all the data on your customers, that's when you have that customer 3 60 that we've all been talking about for so many years. And if you have all that data, you can truly, you know, look at their, you know, buying behaviors, put all those dots together and create those exceptional customer experiences. You can do things such as the retailers do in terms of personal decision, for instance, rights and those are the type of experiences in our customers are expecting today. They are expecting a 100% personalized experience for them all the time. And if you don't have all the data, you can't really put those experiences together at scale. And that is really where the data cloud comes in again. The data cloud is not only about mobilizing your own data within your enterprise. It's also about having access to data from your partners or extending access to your own data in a secure way to your partners within your ecosystems. >>Yeah, So I'm glad you mentioned a couple of things. I've been writing about this a lot, and particularly the 3 60 that we would dying for but haven't really been able to tap. I didn't call it the Data Cloud. I don't have a marketing gene. I had another sort of boring name for it, but I think there's, you know, similar vectors there. So I appreciate that. Scott, I wanna come back to this notion of building data DNA in your marketing, you know, fluency on and how you put data at the core of your marketing ops. I've been working with a lot of folks in banking and manufacturing and other industries that air that are struggling to do this. How are you doing it? What are some of the challenges that you can share and maybe some advice for your peers out there? >>Yeah, sure, it's, um Well, you brought up this concept of data fluency and it zone important one. And there's been a lot of talking industry about data literacy and being able to read data. But I think it's more important to be able to speak data to be fluent. And as marketers, we're all storytellers. And when you combine data with storytelling, magic happens. And so getting a data fluency is a great goal for us toe have for all of the people in our companies. And to get to that end, I think one of the things that's happening is that people are hiring wrong and they're thinking about it. They're making some mistakes. And so a couple of things come to mind when, especially when I look at marketing teams that I'm familiar with, they're hiring a lot of data analysts and data scientists, and those folks are amazing and every team needs them. Uh, but if you go to big on that, you do yourself a disservice. The second key thing is that you're basically giving your front lines, focus your marketing managers or people on the front lines. An excuse not to get involved data. And I think that's a big mistake because it used to be really hard. But with the technologies available to us now, these new consumer like experiences for Data Analytics, anybody can do it. And so we as leaders have to encourage them to do it. And I'll give you just a you know, an example. You know, I've got about 32 people on my marketing team, and I don't have any data analysts on my team across our entire company. We have a couple of analysts and a couple of data engineers, and what's happening is the world is changing where those folks, their enablers, they architect the system, they bring in the different status forces they use. Technologies like snowflake has been so great at making it easier for people. The folks technology together, and they get data out of it quickly. But they're pulling it together, and then we'll simple things like, Hey, I just want to see this weekly instead of monthly. You don't need to waste your expensive data science talent. Gartner puts a stand out there that 50% of data scientists are doing basic visualization work. That's not a good use of their time. You The products are >>easy >>enough now that everyday marketing managers could do that. And when you have a marketing manager come to you and say, You know, I just figured out this this campaign, which looks great on the surface, is doing poorly. From our perspective, that's a magic moment. And so we all need to coach our teams to get there. And I would say, you know, lead by example, give them an opportunity Thio access data and turn it into a story that's really powerful. And then, lastly, praised people who do it, use it as something to celebrate inside our companies is a great way to kind of get this initiative. >>E love it. You're talking about democratizing data, making it self service. People feel ownership, you know, Laura did. He starts talking about the ecosystem, and you're kind of the ecosystem pro here. How does the ecosystem help marketers succeed? Maybe you could talk about the power of many versus the resource of of one. >>Sure, you know, I think it's a it's a game changer and it will continue to be. And I think it's really the next level for marketers to harness this. This power that's out there and use it. You know, it's something that's important to us. But it's also something we're starting to see our customers demand, you know, we went from a one size fits all solution, Thio. They want to bring the best in class to their organization. We all need to be really agile and flexible right now. And I think this ecosystem allows that, you know, you think about the power of a snow plate snowflake mining data for you, and then a thought spot really giving you the dashboard toe, have what you want. And then, of course, um, implementation partner like a whip Roh coming in and really being able to plug in whatever else you need, um, to deliver. And, uh, I think it's really super powerful. And I think it gives us, you know, it just gives us so much to play with. And so much room to grow is market. >>Thank you. Did he say why don't you bring us home? We're almost out of time here, but marketing, art, science both. What do you thoughts? >>Definite? Both. I think that's exciting. Part about marketing. It is a balancing act between art and science. Clearly, it's problem or science today than it used to be. But the art part is really about inspiring change. It's about changing people's people's behavior and challenging the status quo, right? That's the art part. The science part. That's about making the right decisions all the time, right? Making sure we are truly investing in what's gonna drive revenue for us. >>Guys, thanks so much for coming on the Cube. Great discussion. Really appreciate it. Thank you for watching everybody. We're here at the data clouds summit. A lot of great content, so keep it right there. We'll be right back right after this short break.