>> Announcer: From Miami Beach, Florida it's theCUBE, covering Acronis Global Cyber Summit 2019. Brought to you by Acronis. >> Welcome back everyone to theCUBE coverage here at the Acronis Global Cyber Summit 2019 in Miami Beach at the Fontainebleau Hotel. Not a bad venue for an event. It's their first inaugural event around cyber protection. Our next guest is a great guest. He's going to go into great detail. Very fun job. Stressful job. Graeme Hackland, CIO of ROKiT Williams Racing Formula One team. Thanks for joining me. >> Thanks Joe. >> Great job you have. I mean, it's high pressure, high stakes, data's involved. You can nerd out on all the tech and it's a part of the business these days. Take a minute to explain the Williams Racing Team history and what are you guys up to these days. >> So Williams, this is Sir Frank Williams' 41st year with this team. 50 years in total he's been in Formula One. Won 16 world championships. Not recently, we want to do that again for him and that's the mission, right? Get up every day wanting to get back to the front of the grid and help Williams to win. I joined them in 2014. I've been 23 years in total in Formula One. I love the industry, the fast pace, everything you describe. There's a bit of stress obviously but I just love the industry and I joined Williams in 2014 to help with the digital transformation and it's been brilliant and now we're not using the transformation word anymore. We're on a digital journey. We've already put a lot of that infrastructure in place, moved to the cloud, and it's just been, it's been brilliant and we've had some success on the track. More recently it's been tough but we'll get back there. >> You know, I just had a conversation with Dan Havens who's the Chief Growth Officer, he's done all of the sports deals. We were talking about, you know, baseball and the other football, European football, and also Formula One. The competitive advantage edge is there in the data. AI is here, machine learning feeds AI, so now do you set up the infrastructure, you get operationalized properly. This is a big job. It's not just loading software. You got to really think about the wholistic system at work. >> That's the great thing, right? We've go to do the infrastructure right. So you've got to get the basics right. But then if we can do a better job with AI, with machine learning, with the analytic tools that are out there than the other teams are doing. We can beat them. We don't have the same funding levels that they do but we got really smart people, and people is our biggest asset. And then the second biggest is data and making sure that the right engineer has the right data at the right time so that they can do their job, so that we can set the fastest pit stop time or that we can challenge the cars in front of us. It is really important, so we put a lot of time and effort into data analytics, but especially video. Video has become huge for us and obviously then, the data size grows massively. But data and being able to analyze your competitors, analyze your own car, your two drivers against each other. There's a huge amount of data that we are dealing with. >> Without giving any secrets away Graeme, talk about some of the data dynamics that you have going on. What is some of the workflows? What are some of the things you're optimize... You said video. Where are you guys looking at? What are some of the key, cool things that you're seeing as an edge opportunity for you? >> So, Formula One team has this life cycle of a Formula One car where you start in aerodynamics, either in a wind tunnel with a physical model or you do virtual wind tunnel with computational fluid dynamics. There's CFD, so that computation power is really important. Then you go into design, CAD design, that really turns it into something that you can make so then we're into manufacturing. Then we got a race engineer, and all the tools that they use to get the optimum out of the car that they're given on a race weekend. And then you feed that back in so that every race were adding performance to the car, and all through the season. We'll add one and a half to two seconds per lap of performance onto that car every season. And so that's a really important loop that you need to be constantly doing. And if you don't, you know, we've had some issues in this year, if you don't get that completely right, you will lose time to your competitors. >> Give me an example where it didn't work out, where you've gone back to the drawing board. >> So, I think there's been, and it's been well publicized, Clay Williams has talked about it. There's been a bit of a gap between the results we were getting in the wind tunnel and the reality that was happening on the track. And so we've had to bring that back and make sure that there was a correlation between the tunnel and the track. And our engineering group will be working really hard on that, so that kind of thing can happen. >> Talk about the engineering backgrounds that are going on behind the scenes. A lot of people look at Formula One's, only the hardcore nerd that are nerding out and geeking out on the sport know that the depth but, what's going on in the engineering front because there's a lot of investment you guys are making on engineering. >> Yeah, and so, Formula One fans love the data. I think they really love to see the data and work with it and, fortunately, the people who run Formula One are opening more of that data to the fans. If you left it to the teams, we wouldn't share it with the fans because then our competitors see it and we see it as a competitor's advantage. But if something's shared for everyone then that's fair. So, I think the fans love to see the data and see what we're doing. What we're trying to look at now is automation. Humans making decisions has been okay up until probably the last couple of years where some errors have been made in strategy, in real-time where you've got a few seconds to make a decision. Are you going to pit? Virtual safety car has just been called. You've got three seconds to make a decision. Sometimes the humans are making the wrong decision. So we see automation, AI, as really having a role in that real-time decision making. But we think AI can help us in our factory. The things that we're making, something happens at the track, and now we have to change that design. We think introducing automation and AI into that process will really help us as well. >> Yeah, sports market, sports teams, and sports franchises, to me, optimize digital transformation or digital journey because the fans want it. >> Graeme: Yeah. >> There's competitive advantage in running the team. There's the player's decision making whether it's baseball or a driver. >> Graeme: Yup. >> And then there's the fans. So, I got to ask ya on, what are you guys thinking about the fan experience because now you got some data opening up, you got visualization, potentially apps that show you that cars in 3D space and some virtual reality potential. >> Yup. >> The old experience was, ooh, there's a car, goes by again, hey we're (giggles) comes by again. So, bringing, extending the digital fan-based experience, what do you guys, what's your view there? >> Oh, there's a huge amount of work happening in Formula One and it's great to see the people who are running Formula One talking about a digital transformation, not just the teams, right. And it was all about the fan experience. We want the fan to feel like they're a part of it. So Williams did a couple of experiments with virtual reality, so that you could either be one of the pit crews, so you could be the person holding the gun, feel the car coming in, and changing the tire. >> That's awesome. >> Or you could have the driver's view. So the cameras that are on the car are above the driver's head so you don't get an accurate view. So we brought that down into the helmet and now you're getting the view of what it's like to be the driver. >> Wow. >> So, there's been a lot of focus on that fan experience and making sure that you're not at a disadvantage sitting in this, you know, at the track, compared to someone who's at home with two televisions or multiple devices that they're tracking the data on. And the GPS data of where the cars are and hearing some of the commentary of why they're making the decisions they are and when the driver's challenge their engineers, I love that bit. So the engineers got all that data, tells the driver we're going to do this strategy and the driver challenges it because they're in the car feeling how the car feels. >> I think you guys have a great opportunity as an industry because, you look at Esports and the gaming culture, the confluence of that experience based product coming to Formula One. >> Graeme: Yup. >> It's just the perfect fit. >> Well, it's gone, the Esports Formula One has gone huge. We run a team as well. Most of the Formula One teams now have an Esports team. And actually, the people who are driving in the Esports teams, their skills are transferrable. I remember one of the competitions a couple of years ago was to win a drive in the simulator. You became a development driver for one of the Formula One teams. And that shows that those skills are transferrable, so it's great. >> Yeah, that's beautiful stuff. All right, I want to get back to the Acronis cyber.. >> Yup. >> Global Cyber Summit 2019. You're here talking to folks, also sharing knowledge, you guys were hit with ransomware. >> Graeme: Yup. >> Not once, but twice. >> Graeme: Yup. >> I think you had just joined, I think at that time before.. >> It was during 2014 when I first joined and we would, I know, we had put as much investment as we could into our cyber security and to our protection. But we had gaps and I think, so the first ransomware that we got hit by was inside our network and it encrypted 50,000 files before we discovered it. Now we were lucky. We were able to recover all the data from back-up, but we knew that, because it had happened in the middle of the day, someone had looked at some websites during their lunch break and within a couple of hours we had discovered it, contained it, corrected it, restored the data. But the second time we got hit, it was an individual on their computer off network, and we lost data. And that's the thing I hate the most. That data is so precious to us. Losing it was really upsetting. And so we went out into the market, how can we make sure that our data is being backed up? But more than that, how can we make sure that backed up data is protected? And there's a number of reasons we want to protect it. We want to protect it from things like ransomware, but also, the thing that people often don't thing about with their data is, how do we make sure that it's not tampered with at any point? So, when we're at the track, and the car's running around the track, we're pushing data locally, inside the network. We're pushing it to the cloud to do computation and we're sending it back to the UK so that engineers at base can work with it. >> Yeah. >> What it someone was in those stream of data tampering with it? >> Yeah. >> And we then had fake data? And as we go to more machine learning and automation, if those decisions are being made on bad data, that's going to be a real problem. So, we wanted to make sure that our data couldn't be tampered with, so we can adopt new technology. So that was really important. But, Williams also have an advanced engineering company, so beyond Formula One, we apply that knowledge and know how, to all sorts of other industries. From healthcare to retail to automotive. We've been helping Unilever with some really interesting projects to make ice cream better and more efficiently and to help with soap powder. We got to make sure that that customer data is never tampered with. If we're going to put technology into road cars, that's a very different challenge to Formula One. >> John: Yeah. >> We got to make sure that, that whole, the IP chain, how we develop that technology can be proven and isn't tampered with. >> It's interesting, supply chain concepts data protection merging together. Data protection used to be thought after.. Oh, we've got a design. Well let's brush up, we'll get back it, bolt it on. Not anymore. >> Now having to build it into the solutions up front. As we're preparing technology for customers, we're having to make sure that we're thinking about the data challenge. So if it's in a car, so we did battery technology, we won the supply for the first ever gas to electric model, right. As that car is driving around, there's going to be data that's important around the health of the battery. >> John: Yeah. >> And information that is going to be needed by the driver, but also for later for when they're doing the servicing on the car. We got to make sure that that data is protected properly. >> You guys are pushing the envelope on instrumentation, sensors, data, real-time telemetry? >> To be honest, Formula One has always been like that. We put our first data logger in 1979 on a Formula One car. Honestly, it's been an IOT device since then. (laughs) It's not a new thing for F Ones. I think we are really experienced. Our electronics group are real experienced in how to protect that data as it comes off the car and we've applied that knowledge to road cars as well. >> Well you, what's great about you guys and the whole industry is that, that innovation for the sport is now translating as a benefit for society. >> Exactly. >> And I think that is really kind of a, I think, an example of where innovation can come from. Places you least expect it. The people doing hard work pays off. >> It always worried me that Formula One, we spend all the money we spend, right, hundred million pounds, three hundred million pounds per year. And at the end of the year, the product that we created gets retired and we create a whole new product. It always worried me that that technology wasn't reused. Williams are reusing it. You know, we take the carbon fiber that we use to protect a driver in a Formula One car. We've now applied that to babies in hospitals when they get moved around. We built a carbon fiber unit that moves them around. Aerodynamics design, we've applied to fridges to make them more efficient. If you've got an open fridge, the cold air doesn't come out into the aisle of the supermarket. We push it back into the fridges. I love that. Reuse, taking loose end leaf batteries and putting them into a unit that you bought on the side of a house and it helps to power the house over night. >> You know, it's interesting Graeme, you mentioned digital transformation versus digital journey, you guys are operationalize it as it's used. >> Graeme: Exactly. >> Difference, there's nuance but transformation. You have yet transformed. >> Graeme: Yup. >> You guys up transformed so you're on a journey. I got to ask you, what is some learnings in your operationalize digital? I mean, obviously you got your sport, but now it's translating out to other areas. What's the big learnings that you take away from, as a professional and as an individual in the industry, from all this? >> I think, initially, we were quite conservative and we only went with big players that we were convinced were going to be around in three to five years. I think, there's a lot more established cloud providers now but early on we only went with the big guys because we wanted to make sure we could get our data out. If they disappeared, we weren't going to lose our data. I think what the partnership with Acronis and other partnerships we've done has helped us to be more aggressive in terms of our approach towards CAD vendors. We can now take risks with a smaller player. We've got a really niche product but it's something that could give us a competitive advantage for half a season, three, four races sometimes. We'd go for it. Whereas, I think we were a bit conservative at first. I think all CIOs have to think about what's their appetite for risk. We did a really good process of mapping that out, discussing it all the way to board level. What exactly are we prepared to risk? There's some things, you know, car data, we're just not prepared to risk that. >> Yeah. >> But there are some things that we can afford to take risks with. And I've talked to CIOs at finance institutes, they're starting to take risks now. There's core data that they won't be able to, either by regulation or just doesn't make sense. But there's a lot you can commoditize and put out into the cloud. >> And if you have a cyber protection foundation, you can take those risks. >> Graeme: Exactly. >> You don't want to be looking over your shoulder worrying. >> Because you own the data. And sometimes when you go with a cloud provider, it feels almost like they own the data. But when you've got a partnership like the one we have with Acronis, we know that we own the data. We're backing that data away from the cloud vendor so we can always get it back. >> Graeme, thanks so much for the insight. Love this conversation. I think it's really innovative, cutting edge, and great fun to talk about. Thanks for coming on theCUBE, appreciate it. >> Thank you very much, cheers. >> CUBE coverage here at Miami Beach at the Fontainebleau Hotel for Acronis Global Cyber Security 2019 Summit, I'm John Ferrier, stay with us for more CUBE day two coverage after this short break. (fun music)

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.