>>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.

>>Hello, and welcome back to the cubes coverage of.com. Splunk's annual conference is virtual this year. I'm John furrier, host of the cube and a very special guest Sean vice president of product and technology cube, alumni, Sean, great to see you. Thanks for coming on the cube and chatting with us. Thanks. It's great to be here. It's been a while since we chatted, you were at AWS. Now it's Splunk heading up the entire products and technology group here, um, which we've been covering sponsors 2012. So we kinda know a lot about what's going on and, and followed your career. Um, your keynote, we kind of went into this cloud vision is hitting Splunk with the data because the cloud scale, which you know a lot about and data is now taking Splunk to a whole nother level. And that's the big theme you observability multi-cloud and security excuse has been for one there for a while. What's your, what's your assessment. >>Yeah, I mean, you know, uh, you and I have talked a number of times before, and what I found is that, you know, there's a lot of companies through this pandemic that, you know, some are thriving and some are not. And the ones that are really thriving, they have this strong data foundation. Like when you, when you talk to them, they're not stuck. Like they're there. When they talk about scaling or adding capacity or building new co uh, uh, customer experiences, they can, uh, their data platform allows that to happen. But the ones that are are stuck, you know, they just can't, they can't, they can't get to the data. They can't ask those questions that they otherwise, you know, love too. So that's, you know, I think Splunk is right in the middle of that. And that's the fun part of it. >>Yeah. You told me you have the strong foundation when thinking about Splunk is every inflection point in the industry. Over the past decade, you see Splunk do something new operationalized data, do something new, operationalize it. We saw security, I think around 2015, come on the radar at.com. And then since then a whole nother level of data, you've got edge. You have now cybersecurity, even, even more advanced than ever before. And then enterprise is just trying to develop modern applications. So you have this whole rapid scale of CICB pipeline, modern applications and the role of data. Isn't just storing it and managing it. It's like making it addressable. This is like, uh, the, the new current phenomenon of cloud. >>I mean, I liked the way you just put it, it, it really, you know, making data addressable, we put it in terms of like turn data into doing so, you know, if you have data that you're storing it, oh, that's one thing. If you don't, you don't want to leave data behind because you don't know what question you may want to ask. And when, but to your point making it addressable is if you and I decided, Hey, we want to build a new customer experience where we're thinking about doing this thing, and we're going to have a million questions to ask that data is going to help you be, uh, to know whether what you're trying to do for your customers is right or wrong. So it is a, it's remarkable to see how many customers are in pursuit of really turning data into >>Doing so. We've got to you, we had the formula one team on here, McLaren, um, Zach brown. I got a little selfie with, uh, the drivers that kind of cool. My son loved it, but that's an IOT application in my mind, first, the coolest of the sports. Awesome. But like the car going in real time, you know, driving that, driving an advantage with data. So it's an IOT IOT. Then you got just the blocking and tackling >>Data warehouse in the cloud. And then you got companies who are trying to transform a data. So I have to ask you as customers out there, look at Splunk and look at the next level of their architecture with multicloud coming around the corner. How should they be thinking about data? Get the foundation with Splunk. What's the next chapter in your mind? I mean, you know, a lot of customers that I meet they're in multiple clouds. They're not just in one. It means they've got data in Amazon or Google or Azure. A lot of them still have data on prem, you know, but when I talk to customers, they don't say things to me like, Hey, I'm in different clouds, I'm on prem. Can you make sure I have different observability and security experiences for each one? Like they don't, they really, at the end of the day, they're like, look, I need a consistent observability experience, consistent security, regardless of where my data is. >>So what that means to Splunk is, you know, wherever your data is, we're going to be Splunk will just work that that's kinda, as you know, it's how we think about it. And speaking that I had dinner with Lando the other night and it was, I hadn't met Lando before, but man, what an awesome, awesome person. We were just kind of hanging out, talking about data and I ask, this is the kind of stuff you wouldn't normally get. I asked him like, Hey, if you could, if technology could do anything to help you win formula one races, what would it be? A totally open-ended question. And I wasn't sure how he was going to answer it, but he didn't pause this guy. Like you talk about, you think of these scenarios. He's very quickly. He's like, oh man, if we had data, could help me do this and this and this and this because in his business, a millisecond can be the difference between winning or losing a race. And for some of you like, oh, that can't be, but for him, that's how his mind works. So it's crazy to see how excited he was to use tech, to get to data, ask questions that can ultimately help them. >>What was the number one thing pitting the right time or tires? What was he, what did he come up there? He is. >>You know, I can't, unfortunately >>I don't want to put you on the spot. I will be. >>This is like, you know, I, I wouldn't, uh, that would put him in a bad spot, but I will tell you though, I mean, this guy is, and that whole team is really about using data to win. >>Well, you know, I was joking. Um, but these guys can, they came on. Cause you know, I'm a big fan, obviously with the Netflix special driving two survives the name of the title. They become hugely popular to a new fan base, especially techies. Um, I said, Hey, you're driving the advantage with data kind of my little, little comeback to that, but that's really kind of a real encapsulates a real world scenario. I mean, well, there are 10,000 people working on McLaren. You have the driver in the car, you have the car itself with all this instrumentation that kind of encapsulates the enterprise experience right now. They don't have the right app doing the right thing with customers. It could be the difference between having a successful digital transformation or not. So it's kind of like parallel. I mean, I know that's kind of the tie in with the, with the sponsorship, but that's the real world now. >>Yeah, it is. And I mean, if you think about it, there's two drivers per car, 10 teams. There's so many races, there's a tremendous amount of money that they're all spending. But you know, when, when your season is really composed of a certain number of races and you got millions of people tuning in you're right. There's hundreds of people working behind the seat. Could you imagine if they didn't use data and you're trying to, you're, you're trying to race and formula one against the best drivers and the best engineers in the world. I just, you know, it goes to show you're right. It is, it's a perfect example of them transforming as any other enterprise, basically using data to get an advantage. >>And just before we move on to the next topic, the e-sports thing is fascinating as well, because now they're taking this memento verse kind of vibe where they're moving people on the e-sports, where they're having the shadow competition. It's a very interesting kind of bringing the fan base in, but there's probably gonna be a lot of data involved in that as well. Maybe identify the next driver who knows, hopefully, you know, good stuff. So Sean, you're in charge of process technology. I have to ask you, um, as customers look at all the different solutions out there, I'll say multicloud check, you guys have a good vision on that. Like that observability. I mean, that's the fashion right now. Let's talk about observability that there's so many companies out there doing quote observability. How should customers think about what that means in context to the decision of they make everyone's coming into the, the CSO or the CIO saying, um, your observability solution? >>Yeah, I mean first, um, you know, what is observability? I always like to just sort of map it back to things we might understand. So back in the day, monitoring really was connect to a machine. It has a monolith app, you know this and you just try to debug this one thing. That's not the world we live in today. Today when you're building apps in the cloud, you're you, you have hundreds of these services behind the scenes. Like no one person can actually comprehend all of it. So now all of a sudden tools become, they really matter. And what I would say is from a Splunk perspective, when we talk to customers, it's not like one person there, one team is quote, you know, working and making the whole system work. Oftentimes you have different teams like network teams, app teams, security teams, and they all kind of need to work together in one way shape or another. But this is why, you know, when rebuild our systems, it's off of shared data so that, you know, if I'm an operator, you're an app developer. And if I need to work with you, at least I can share something with you in context. So we, we, while there are individual tools to do certain things, our mental model is that they all do work together. That's super, super important for any observability thing you're looking at. You just want to make sure that you can see things end to end. Otherwise you get in trouble >>Quick. You know, I'd love to get your perspective being new to Splunk as you come in and new, the industry obviously has experienced that in the cloud has been well documented, certainly in the cube. What's it like there because as you come in, it's not a utility anymore. It's not a tool anymore. It's a platform and it's getting bigger and growing. So you have probably a lot of things going on. So you walk in and you, you say, okay, let me see the price of technology. Were you blown away? What was your reaction? What can you share some, uh, color around what's uh, what was it like when you open up the doors of the kingdom of the product? >>Yeah. Well, I mean, these t-shirts are real men and there's like ponies running around this. The Splunkers love to have fun. And you know, before I came to Splunk, the one thing I noticed, anytime I asked my thoughts long, they were fired up. Like they were really, really excited about the tech, but when I got into it, the truth is, you know, you don't know what you don't know until you see it, but I was just done to, to then sort of connect the dots like wow. Splunk is in the core data plane of tens of thousands of enterprises all over the world, like the data plane for all of their architecture and applications. So with that becomes a great responsibility, as you could imagine, but it is not just a tool. It is something that customers like. I dunno, the university of Illinois, you know, with COVID, they'll they'll track, uh, they'll track 3.2 million saliva tests just for contract tracing and behind the scenes, they're using Splunk for a real thing. Or we've talked about F1 or you think of slack, like we're all kind of using slack. These days, slack is using, um, uh, Splunk to make sure that their environment of slackers and everything's building it's all secure. So th it's those stories that go on and on are just incredible. When you learn that, >>I started at Teresa Carlson yesterday, and we were talking about the growth opportunity and I spent speculating that, you know, my opinion, my opinion, that's looking, hang on the cube is that Splunk's that this new inflection point that another elbow, another kickoff, the growth, the way it's positioned. If you look at kind of where it's been, kind of where it's going with security now as a platform with the enterprises, how do you describe that growth in your mind? Because obviously this market's changing an edge real time. All these things are happening. What's, what's the, where's the growth going to be? >>Yeah, I think it's in the cloud. I mean, if you think of Splunk, I think the company is about 18, 19 years old. So its history is an almost 20 years of on-premise software. In some sense, you might go, Hey, is that a liability? But Rio, the reality is it's a strength because we're already part of these enterprise infrastructures and application stacks. And then when you now move that group to the cloud, and then you got all others coming to the cloud, that's where they're, I mean, it is just the tip of what is happening. So, you know, if I'm a customer and I moved to the cloud in the cloud, it's like, I don't have to really scale or size anything. Like it just works. And it, to me, it's just an end point and I load data. So in that context, the number of new use cases that customers are able to get after is actually pretty awesome. But really at the end of the day it's cloud. >>Well, great to have you on, I know you've got to go. Thanks for coming on the queue. One final question. What's your vision for the next year or two, what's your to do items. What's the message to the marketplace. >>You know, I'm, I'm thrilled to be here, but at the end of the day, you know, my message to the marketplaces, we're all excited to work with our customers to really help them have that strong foundation so they can turn data into doing and actually pull off these digital transformation. >>One final final question for the companies that get the cloud scale combined with putting data into action for the, for the value what's the result going to be is they can put more competitive advantage. Is it more agility? What do you see happening when you combine the cloud scale with a great data plane? >>Yeah, I think at the end of the day, these companies would tell you that they can move faster than ever before. They're more competitive there. They have confidence that their environments secure, they can build new customer experiences. And when you put all of that together, honestly, that is what these digital transformations are all >>Great to be in the product and technology business these days. Isn't it a lot of fun, a lot of action. Thanks for coming on the cube. Really appreciate it. Yeah, you bet. Good to be here. It's the cube coverage here, here at the live studio for Splunk studios, for their virtual events, the cube bring you all the action. I'm John for a, your host. Thanks for watching.

(soft music) >> Hi, everyone. Welcome back to the Cube's covers of Splunk's dot com virtual event, their annual summit. I'm John Ferry, host of the cube. We've been covering dot conf since twenty twelve. Usually a physical event in person. This year it's virtual. I'm here with Claire Hockin, the CMO of Splunk. She's been here three and a half years. Your first year as CMO, and you got to go virtual from physical. Welcome to the cube. Good to see you. >> Thank you very much, John. Great. >> I got to ask you, I mean, this has been the most impressive virtual venue, you've taken over the hotel here in Silicon valley. You're entire teams here. It feels like there's a dynamic of like the teamwork. You can kind of feel the vibe. It's almost like a little VIP Splunk event, but you're broadcasting it to the world. Tell us what's happening. >> Yeah, it's been, I think for everyone a year where we really hope to be back to having a hybrid event, so having a big virtual component, but running dot conf as we had before from Las Vegas, which wasn't possible. So what we thought in the last six weeks is that we would actually bring the Splunk studio to a physical location. So we've been live all of this week from California, where we're sitting today and really thought through bringing the best of that programming to our, you know, our amazing audience of twenty six thousand people. So we were sitting here in a studio, we have a whole live stage and we've activated the best of dot conf to bring as many Splunkers as we can. And as many external guests to make it feel as real and as vibrant as possible. So. >> I have to say I'm very impressed. Since twenty twelve we've been watching the culture evolve. Splunk has always been that next big thing. And then the next big thing again, it seems to be the theme as data becomes so bigger and more important even than ever. There's a new Splunk emerging, another kind of next big thing. And this kind of says the patterns like do something big, that's new, operationalize it and do something new again. This is a theme, big part of this culture here. Can you share more about how you see this evolving? >> Sure. And I think that's what makes Splunk such a great place to be. And I think it attracts people who like to continually challenge reinvent. And I think we've spent a lot of time this year building out our portfolio, going through this cloud transformation. It just gives you a whole new landscape of how you unlock that power of data and how customers use it. So we've had a lot of fun, always building on top of that building, you know, our partnerships, what customers do and really having fun with it. I think one of the best things about Splunk is we do have this incredibly fun and playful brand and as data just becomes something that is more and more powerful, it's really relatable. And we have fun with activating that and storytelling. So, yeah. >> And you have a new manager, Teresa Carlson came in from Amazon web services. You have a lot more messaging kind of building on previous messaging. How are you handling and looking at the aperture of, that's growing from a messaging standpoint, you have a partner verse, which has rebranded of your solution of your ecosystem, kind of a lot of action going on in your world. What's the update? >> Yeah. It keeps us busy. And I think at one end, you know, the number of people that are using Splunk inside any customer base is just growing. So you have different kinds of users. And this year we're really working hard on how to partner and position Splunk with developers, but at the top end of that, the value of data and the idea of having a data foundation is something that's incredibly compelling for CTOs. So working really hard about looking at Splunk and data from that perspective, as well as the individual uses across areas like security and observability. So. >> You know, one of the things I wanted to ask you is, I was thinking about this when I was driving in this morning, Splunk has a lot of customers and you keep your customers and you've have a lot of customers that organically came into the Splunk through the product leadership and just great product. And then as security became more important, Splunk kind of takes that territory now. Now mainstream enterprise with the platform are leaning into Splunk solutions, and now you've got an ecosystem. So it's just becoming bigger and bigger just seems that the scale of the Splunk is growing radically bigger than it was, Is that happening? And what's your take on that? >> I think that's definitely a thing, John. So I think that the power of the ecosystem is amazing. We have customers, partners, as you've seen and everything just joins up. So we're seeing more and more dot joining through data. And we're just seeing this incredible velocity in terms of what's possible and how we can co-build with our partners and do more and more with our customers. So Splunk moves incredibly quickly. And I think if anything, we're just, gaining velocity, which is fun and also really challenging. >> Cloud-scale. And certainly during the pandemic, you guys had a tailwind on the business side, talk about the journey that you've had with Splunk as in your career and also for the customers. How are they reacting and what can they expect as Splunk continues to evolve? >> I think we're working really hard to make sure that Splunk is easier to use. Everything gets every more integrated. And I think our goal and our vision is you just capture your data and you can apply it to any use case using Splunk. And to make it sort of easier see that data in action. And one of the things I love from today was the dashboard studio. They're just these beautiful visualizations that really are inspiring around how data is working in your organization. And for me, I've been a Splunker for three and a half years. And I just think there is just so much to do, and there's so much of our story ahead of us and so much potential. So just really enjoying working with customers on the next data frontier, really. >> You have the Jedi Knight from Star Wars speaking, you had the F1 car racing. Lando was here, kind of the young Jedi, the old Jedi. The generations are coming together. You're seeing that old IT world, which relied on Splunk. And now you have this new developer real-time shifting left with security DevOps now going mainstream, you kind of have the confluences of these cultures coming together. It's not really clashing. It's kind of jelling. How are you handling that? How do you see that? What's Splunk kind of doing? Because I can see the themes, am I right? >> No, no. One of the stories from this morning that really struck me is we have Cal Poly and we worked with Cal Poly on their security and they actually have their students using Splunk and they run their whole security environment. And at the very top end, you have Walmart, the Fortune one, just using Splunk at a massive, incredible scale. And I think that's the power of data. I mean, data is something that everyone should and can be able to use. And that's what we're really seeing is unlocking the ability to bring, you know, bring all of your data in service of what you're trying to do, which is fun. And it just keeps growing. >> We had Zach Brown, the CEO of F1 McLaren Racing Team, here on the queue earlier. And it was interesting cause I was like driving the advantage with data, you know, kind of cliche, but they're using data very specifically, highly competitive. It almost kind of feels like a cloud kind of scale model because we've got thousands of people working on the team. They're on the track, they're competing, they're using data, they got to be agile and they got to be fast real time. Kind of sounds like the current enterprise's these days. >> Absolutely. And I think what's interesting about McLaren that the thing I love is either they have hundreds of terabytes of data moving at just at incredible speed through Splunk Enterprise, but it all goes back to their mission control in the UK. And there are 32 people that look at all that data. And I think it's got a half second delay and they make all the decisions for the car on the track. And that I think is a great lesson to any enterprises you have to, you know, you have to bring all that data together and you have to look at it and take decisions centrally for the benefit of your whole team. And I think McLaren is a really good example of when you do that it pays dividends and the team has had a really, really great season. >> Well, I want to say congratulations for pulling off a great virtual event. I know you had your physical event was on track and literally canceled the last minute because of the pandemic with the Delta virus. But it was amazing, made for digital TV kind of event. >> Absolutely, >> This is the future of media. >> Absolutely. And it is a lot of fun. And I think I'm really proud. We have done all of this with our in-house team, the brand, the experiences that you see, which is really fantastic. And it's given us a lot of ideas for sort of, you know, digital media and how we story tell, and really connect to our twenty thousand customers or two hundred and thirty thousand community members and keep everyone connected through digital. So this has been a lot of fun and a really nice moment for us this week. >> You know it's interesting, I was saying to the team here on one of our breaks, is that when you have this kind of agility with media to tell your own story directly, you're almost telling more stories there before. And there's a lot to tell you have a lot of successful customers, the new partners. What's the coolest story that you've seen. What would you share that you think is your favorite? If you could pick one or a few of them, what are your top stories that you see happening? >> So I've talked about Cal Poly, which I love because it's students and you know, the scale of Walmart, but there are so many stories. And I think the ones that I love most are the data heroes. We talk about the data here is a lot of Splunk and the people that are able to harness that data and to take action on that data and make something amazing happen. And we just see that time and time again, across all kinds of organizations where data heroes are surfacing, those insights. Those red flags, if you like and helping organizations stay on step ahead. And Conf is really a celebration of that. I think that's why we do this every year. And we really celebrate those data heroes. So across the program, probably too many to mention, but in every industry and at every scale, people are, you know, making things happen with data and that's an incredibly exciting place to be. >> Well you have a lot of great customers to, to use as references. But I got to ask you that as you go forward this year in marketing, what are your plans to take on this new dynamic? You've got hybrid events, you've got the community is always popular and thriving with Splunk at large-scale enterprises, global system integrators, doing business deals with you guys, as you guys are continuing to grow and grow and grow, what's the strategy? How do you keep the Splunk coolness going? Cause that's, you know, you guys are growing so fast. That's your job, is to keep things on track. What's your strategy? >> I think I look at that and just, we put the customer at the heart of that. And we think, you know, who are the personas, who are the people that use Splunk? What's their experience? What are they trying to do? What are those challenges? And we design those moments to help them move forward faster. And so that I think is just a really good north star. It is really unifying and our partners and customers, and every Splunker gets really behind that. So stay focused on that. >> Thanks for coming on the Cube, really appreciate it. Congratulations for great event. And thanks for having the Cube. We love coming in and sharing our media partnership with you. Thank you for coming. >> Thank you so much. And next year is your tenth year John. So we look forward to celebrating that as well. Thank you very much. >> Thank you. Thanks for coming on. Okay it's the Cube coverage here live in the Splunk studios. We are a virtual event, but it's turning out to be a hybrid event. It's like a VIP event, a lot of great stories. Check them out online. They'll be recycling through so much digital content. This is truly a great digital event. Jeffery, hot of the Cube. Thanks for watching. (soft music)

>>Hello, and welcome back to the cubes coverage of splunk.com here in the virtual studios in Silicon valley broadcasting around the world's a virtual event. Um, John four-year host of the queue. We've got a great guest, Zach brown, chief executive officer of McLaren racing, really looking forward to this interview, Zach, welcome to the queue. Well, thanks for coming on. Thanks for having me. So we have a huge fan base in the tech community. A lot of geeks love the neurons. They love the tech behind the sport. Uh, and Netflix is driving to survive. Series has absolutely catapulted the popularity of F1 in the tech community. So congratulations on all the success in that program and on, and then on the >>Thank you very much, it's been a, it's been a good run. We've won our first race in a while, but we still have a ways to go to get in that, uh, world championship that, uh, >>So for the techies out there and the folks in our audience that aren't familiar with, the specifics of the racing team and the dynamics, take a minute to explain what you guys do. >>Uh, so McLaren racing, uh, which has a variety of, uh, racing teams, uh, a formula one team in indie car team and extremely team and an e-sports team. Uh, we're the second most successful form of the one team in the history of sport. Now 183 wins 182, uh, when I joined 20 world championships and, uh, we're, we're close to a thousand people to, to run a couple of racing cars and, uh, currently third in the championship, uh, with Lando Norris and, uh, Daniel, Ricardo. >>So talk about the, um, the, the dynamics of the spore. Obviously data is big part of it. Uh, we see the, a lot of the coverage. You can see anything can happen overnight. It's very quick. Um, technology has been being, uh, playing a big role in sport. What's your vision on how that's evolving? Are you happy with where things are, uh, and where do you see it going? >>Yeah, it does some interesting stats. So, um, the car that qualifies first at the beginning of the year, if you didn't touch, it would be last by the end of the year. So that's the pace of a development of a, of a formula one car. We change a, uh, and develop a new part on the car every 14 minutes, 365 days, days a year. Um, and technology plays a huge role. Uh, it's, it's probably the most technical, um, evolved sport in the world. Uh, both safety data, uh, the innovation it's it's awesome. And what a lot of people don't know is a lot of what we develop in a formula. One car ends up in other parts of the world, whether it was a ventilators that we helped develop for the UK government, uh, to working with our, uh, various partners or safety and innovation in the automotive industry. >>You know, I love it. I always loved the IOT internet of things, story around cars, because sensors or instrumentation is a big part of it. Um, and it all comes together. So it's pretty, it's not simple. No, give it feel, give it a taste a little bit about what's it. How complicated is it, how you guys pay attention to the details? What's important. Take us through some of the, some of the inside the ropes around the IOT of the sensors and all the data. >>Yeah. So we have over 300 sensors on our race car. We collect the one and a half terabytes of data. Every race weekend, we have a thousand people, um, and the strong majority of those are working around data and technology, as opposed to physically touching the car out of those thousand people, you probably only have about 60 or 70. They're actually touch the race card at a race weekend. We've been doing connected cars for about 25 years. So that's kind of a new thing here to, to most people, but we've been communicating back and forth with our race car for, for decades all around the world. And what a lot of people don't realize is it all starts in our mission control back in our factory in Woking, England. So wherever we are around the world, the racing team actually starts in England. >>So I want to ask you about the personalities on the team. How big is the staff? What's the makeup of the personnel has to get the drivers. They're critical. They're a very dynamic personalities. We'll come to the side question on that later, but what's the staff look like on when you guys put this together. So you get, you get race day and you got back office support. >>What's the team look like? Yeah. So you've got about a thousand people that, that make up the collective team. You'll have about a hundred in marketing. Uh, you'll have about a hundred in finance, HR, and then you kind of get to the, the racing team. If you'd like 800 people, you have about a hundred people traveling to each race, uh, about 50 people back at the factory, working with data and communications that are grand Prix weekend. And then everybody else is designing manufacturing, production laminating. So we run 24, 7 shifts, uh, three shifts, uh, in certain parts. Uh, we develop, uh, 85% of the car changes of what's allowed to be changed start of the year to the, the end of the year. So the development is, is unbelievable. >>I know you're here in the U S for the U S grand Prix in Austin. Um, coming up, I'm just curious how cars get transported. >>Uh, w when we're traveling around the world, uh, they, they travel on 7 47 and are flown around the world. And then when we're in Europe, we have about 18 trucks that were communing around when we're kind of in the European part of the circuit is usually in the middle of the year. But when we're going to Australia or Singapore, Bahrain, those are, those are on planes form of the one actually does that. They give us an allocation of, of space, and then we have to write a check if we need more space than where >>Yeah. We're allowed. Yeah. And that brings up the security question, because honestly, there's a lot of fans, a lot of people are into it. Also, this potentially security risks. Have you guys thought about that obviously like physical moving the supply chain around from event event, but also technology risk. Um, how do you guys think about security? >>Yeah, it's, it's critically important. We've had, uh, fortunately we've not had any breach of our technology. We have had a breach in the late nineties of our radio communications and, uh, it was in Australia, Mika Hakkinen and a fan, uh, who I think was probably having some fun and were able to break into our radio channel and actually asked Mika to pit. He pitted team wasn't ready. And fortunately, we will run in one, two, but we actually had to reverse the drivers. So security is >>Critically important, probably Katie Scrivener, and they all look, I just hack the radio, was talking to the driver. That is a funny story, but it could be serious. I mean, now you have all kinds of >>The stuff going on and, and, you know, there's a lot of money at stake, you know, so, you know, we're fortunate in this particular instance, it didn't hurt us cause we were running one, two, so we could reverse the drivers and the right guide one. Um, but you know, that could decide, uh, a world championship and you have, you know, tens of millions of dollars online, but even besides the economics, we want to win races. >>You know, what's funny is that you guys have a lot of serious on the line stakes with these races, but you're known for having a lot of fun, the team team dynamic. I have to ask you, when you finish on the podium one and two, there's a Shui with the drivers. How'd that go down. It was pretty, pretty a big spectacle online and >>Yeah, it was, it was good, fun. That's something, obviously Daniel Ricardo is kind of developed as his thing when he, uh, when he wins. And, uh, when we were, uh, before we went on the podium, he said to me, you're going to do the shoe. Yes, of course. In the car show you got to do, we have to like a bunch of 12 year old kids, uh, on the podium, but that's where we're just big kids going, motor racing and >>The end of the day. Well, I gotta say you guys come across really strong as a team, and I love the fun and, you know, competitive side. So congratulations on that, I think is good on the competitive side, take me through the advantage, driving the advantage with data, because that's really the theme here at.com, which is Splunk, which they're a big partner, as well as your other sponsors. Data's big, you know, and it's striving an advantage. Where do you see that coming from? Take us through where you guys see the advantages. Yes. >>So, you know, everything we do is, is precision and, you know, every second, every 10th counts and, um, you know, you can get all this data in, but what do you do with this data? And the humans can, uh, real, uh, react as quickly as is, you know, people like Splunk who can help us, uh, not only collect data, but help us understand data. And, um, you know, typically there's one pit stop, which can be the difference between winning and losing. Um, you have all these different scenarios playing out with weather with tire wear competition. And so, you know, we live by data. We didn't, uh, when, in, in Russia, when we, uh, could have, and it was because we got a bit emotionally caught up in the excitement of trying to win the race instead of staying disciplined and focused on, on data. And so it's a very data-driven sport when I'm on the pit wall, there's a thing called racer instinct, which is my 30 years in the sport. And, uh, your experience and your kind of your gut to make decisions. And every time our team makes a decision that I'm sitting there going, I'm not sure that was the right decision. They're staring at data. I'm not, I'm trusting my 30 years of experience. They'd beat me nine out of 10. >>Yeah. I mean, you know, this is a huge topic too, in the industry, explainable AI is one of the hottest trends in computer science where there's so much algorithms involved. The gut instinct is now coming back. What algorithms are available, knowing when to deploy what algorithms or what data to pay attention to is a huge new gut factor. Yep. Can you explain how the young drivers and the experience folks in the industry are dealing with this new instinct full data-driven? >>Yeah. That's, you know, that's what we have 50 people back at the factory doing, and they're looking at all sorts of information coming in, and then they're taking that information and they're feeding it to our head of strategy. Who's then feeding it to our racing director. Who's getting all these data points in from tire to performance, to reliability, and then the human data from both drivers coming through their engineers. And then he gets all that information in. He has to process it immediately and make decisions, but it's, it's a data-driven sport. >>I saw Lando walking around, got a selfie with them. It's great. Everyone's loving it on Twitter. My family, like get an autograph, the future of the sport. He's a young young driver. So that instincts coming in the future sport comes up all the time. The tires are a big discussion point, but also you've got a lot of presets going on, a lot of data, a lot of going on and you see the future where there's remote, you know, kind of video game you're in the pit wall and you can make decisions and deploy on behalf of the drivers. Is that something that >>Well, that technology is there and we used to do that, but now it's been outlawed because there's a real push to make sure the drivers are driving the car. So that technology is here. It has been deployed in the past. We could do it, but we're trying to find as a sport, the balance between, you know, letting the driver do it. So he, or she might make a mistake and a little bit of excitement to it. So, um, we now there are certain protocols on what we communicate. Um, we can't, um, everything has to be driver fed into the car. So we can now you'll hear all sorts of codes that we're talking through, which there are, um, about 300 different adjustments the driver can make on the steering wheel, which is unbelievable. And so that's us seeing information, getting data in coming to conclusions that we're giving him or her information that we think will help make the car >>A lot of new dimensions for drivers to think about when they're being successful with the gut, that the track data everything's kind of coming together. >>Yeah. It's amazing. Um, when you listen to these drivers on the radio, you forget that they're going 200 plus miles an hour. Cause they sound quite relaxed in this very, you know, open and easy communication of here's what I'm feeling with. Again, we're talking all these codes and then we all, because we can hear each other, there's a lot of trickery that goes on. So for a driver to be going to turn a miles an hour, taking this information and then know what code we're talking, are we kind of throwing a code out there to put the competition off is pretty amazing that they can take this all in. >>You know, I wish I was younger again, like we're old school and the younger generation, I was having a few conversations with a lot of the young audience. They wanted me to ask you, when are you guys going to metaverse the tracks? When can I get involved and participate and maybe even make the team, or how do I become more active, engaged with the McLaren racing team? >>And that technology is almost, we're actually, um, that's in development. So I, I think it won't be long before, you know, Sunday you can log on, uh, and, and race Lando around Monaco and be in the race. So that, that technology is around the corner. >>That's the shadow thing to developing. I see that. E-sports just quick. I know you've got to go on, but last minute we have here, e-sports, what's the future of e-sports with the team, >>But e-sports been great for the sport. You know, it's gone from, you know, when I was growing up, it was video games and now it's real simulation. And, uh, so we've held, I think we're going four years into it. Now we were the first team to really develop any sports platform and we've had competitors go on to help us with our simulation. So it's, it's real racially developed the race car before it goes on the racetrack it's in simulation. And that's where e-sports, >>And this is the new advantage. This is a new normal, this is where you guys see the data driving. The >>Definitely. And I think the other thing it is, you know, somewhat stick and ball sports, you can play in school. And motor racing has historically been partying, which can cost hundreds of thousands of dollars. Now with e-sports you have a less expensive platform to let young men and women around the world, but a steering wheel in their hand and go motor racing. So I think it's also going to kind of bring that younger generation of fan and >>There's so much collective intelligence, potentially competitive advantage data. Again, data coming up final word to end the segment, Splunk, big partner on the data side, obviously helping you guys financially, as well as you do need some sponsorship support to make the team run. Um, what's the relationship with Splunk? Take a minute to talk about the plug. >>It's been a, it's been great, you know, they're, they're two big contributors. We need a lot of money to run the racing team. So they're a great partner in that respect, but more importantly, they're helping us with our whole data journey, making smarter, quicker decisions. So their contribution to being part of the race team. And, uh, we used our technology. Um, it has been great. And I think, um, you know, if I look at our technology partners, uh, we have many that all contribute to making a >>Yeah. I mean, it really is nice. It's data inaction, it's teamwork, it's competitive, it's fun. That's kind of a good, good, >>I think fun is the center of everything that we do. It's the center of everything spunk does. Cause I think if you have fun, people enjoy going to working a little bit harder. We're seven days a week. And uh, you know, a lot of teammates you've got to work well together. So I think if you're having fun, you enjoy what you're doing and it doesn't feel like work. >>Congratulations on climbing up in the rankings and everything on your team. Two great drivers. Thanks for coming on the cube. We appreciate it. Thank you. All right. We're here. The key. We like to have fun here and get all the action on the tech side. Honestly, F1 is technology enabled data, driving the advantage and driving to is a great Netflix series. Check it out. McLaren's featured heavily in there and got a great team. Zach brown Siegel. Thanks for coming on. Appreciate it. I'm sure for your host. Thank you for watching.

>> Well, hello everybody, John Walls here on theCUBE and continuing our coverage. So splunk.com for 21, you know, we talk about big data these days, you realize the importance of speed, right? We all get that, but certainly Formula One Racing understands speed and big data, a really neat marriage there. And with us to talk about that is James Hodge, who was the global vice president and chief strategy officer international at Splunk. James, good to see it today. Thanks for joining us here on theCUBE. >> Thank you, John. Thank you for having me and yeah, the speed of McLaren. Like I'm, I'm all for it today. >> Absolutely. And I find it interesting too, that, that you were telling me before we started the interview that you've been in Splunk going on nine years now. And you remember being at splunk.com, you know, back in the past other years and watching theCUBE and here you are! you made it. >> I know, I think it's incredible. I love watching you guys every single year and kind of the talk that guests. And then more importantly, like it reminds me of conf for every time we see theCUBE, no matter where you are, it reminds me of like this magical week there's dot com for us. >> Well, excellent. I'm glad that we could be a part of it at once again and glad you're a part of it here on theCUBE. Let's talk about McLaren now and the partnership, obviously on the racing side and the e-sports side, which is certainly growing in popularity and in demand. So just first off characterize for our audience, that relationship between Splunk and McLaren. >> Well, so we started the relationship almost two years ago. And for us it was McLaren as a brand. If you think about where they were, they recently, I think it's September a Monza. They got a victory P1 and P2. It was over 3200 days since their last victory. So that's a long time to wait. I think of that. There's 3000 days of continual business transformation, trying to get them back up to the grid. And what we found was that ethos, the drive to digital the, the way they're completely changing things, bringing in kind of fluid dynamics, getting people behind the common purpose that really seem to fit the Splunk culture, what we're trying to do and putting data at the heart of things. So kind of Formula One and McLaren, it felt a really natural place to be. And we haven't really looked back since we started at that partnership. It's been a really exciting last kind of 18 months, two years. >> Well, talk a little bit about, about the application here a little bit in terms of data cars, the, the Formula One cars, the F1 cars, they've got hundreds of sensors on them. They're getting, you know, hundreds of thousands or a hundred thousand data points almost instantly, right? I mean, there's this constant processing. So what are those inputs basically? And then how has McLaren putting them to use, and then ultimately, how is Splunk delivering on that from McLaren? >> So I learned quite a lot, you know, I'm, I'm, I been a childhood Formula One fan, and I've learned so much more about F1 over the last kind of couple of years. So it actually starts with the car going out on the track, but anyone that works in the IT function, the car can not go out on track and less monitoring from the car actually is being received by the garage. It's seen as mission critical safety critical. So IT, when you see a car out and you see the race engineer, but that thumbs up the mechanical, the thumbs up IT, get their vote and get to put the thumbs up before the car goes out on track there around about 300 sensors on the car in practice. And there were two sites that run about 120 on race day that gets streamed on a two by two megabits per second, back to the FIA, the regulating body, and then gets streams to the, the garage where they have a 32 unit rack near two of them that have all of their it equipment take that data. They then stream it over the internet over the cloud, back to the technology center in working where 32 race engineers sit in calm conditions to be able to go and start to make decisions on when the car should pit what their strategy should be like to then relate that back to the track side. So you think about that data journey alone, that is way more complicated and what you see on TV, you know, the, the race energy on the pit wall and the driver going around at 300 kilometers an hour. When we look at what Splunk is doing is making sure that is resilient. You know, is the data coming off the car? Is it actually starting to hit the garage when it hits that rack into the garage, other than streaming that back with the right latency back to the working technology center, they're making sure that all of the support decision-making tools there are available, and that's just what we do for them on race weekend. And I'll give you one kind of the more facts about the car. So you start the beginning of the season, they launched the car. The 80% of that car will be different by the end of the season. And so they're in a continual state of development, like constantly developing to do that. So they're moving much more to things like computational fluid dynamics applications before the move to wind tunnel that relies on digital infrastructure to be able to go and accelerate that journey and be able to go make those assumptions. That's a Splunk is becoming the kind of underpinning of to making sure those mission critical applications and systems are online. And that's kind of just scratching the surface of kind of the journey with McLaren. >> Yeah. So, so what would be an example then maybe on race day, what's a stake race day of an input that comes in and then mission control, which I find fascinating, right? You've got 32 different individuals processing this input and then feeding their, their insights back. Right. And so adjustments are being made on the fly very much all data-driven what would be an example of, of an actual application of some information that came in that was quickly, you know, recorded, noted, and then acted upon that then resulted in an improved performance? >> Well, the most important one is pit stop strategy. It can be very difficult to overtake on track. So starting to look at when other teams go into the pit lane and when they come out of the, the pit lane is incredibly important because it gives you a choice. Do you stay also in your current set of tires and hope to kind of get through that team and kind of overtake them, or do you start to go into the pits and get your fresh sets of tires to try and take a different strategy? There are three people in mission control that have full authority to go and make a Pit lane call. And I think like the thing that really resonated for me from learning about McLaren, the technology is amazing, but it's the organizational constructs on how they turn data into an action is really important. People with the right knowledge and access to the data, have the authority to make a call. It's not the team principle, it's not the person on the pit wall is the person with the most amount of knowledge is authorized and kind of, it's an open kind of forum to go and make those decisions. If you see something wrong, you are just as likely to be able to put your hand up and say, something's wrong here. This is my, my decision than anyone else. And so when we think about all these organizations that are trying to transform the business, we can learn a lot from Formula One on how we delegate authority and just think of like technology and data as the beginning of that journey. It's the people in process that F1 is so well. >> We're talking a lot about racing, but of course, McLaren is also getting involved in e-sports. And so people like you like me, we can have that simulated experience to gaming. And I know that Splunk has, is migrating with McLaren in that regard. Right. You know, you're partnering up. So maybe if you could share a little bit more about that, about how you're teaming up with McLaren on the e-sports side, which I'm sure anybody watching this realizes there's a, quite a big market opportunity there right now. >> It's a huge market opportunity is we got McLaren racing has, you know, Formula One, IndyCar and now extreme E and then they have the other branch, which is e-sports so gaming. And one of the things that, you know, you look at gaming, you know, we were talking earlier about Ted Lasso and, you know, the go to the amazing game of football or soccer, depending on kind of what side of the Atlantic you're on. I can go and play something like FIFA, you know, the football game. I can be amazing at that. I have in reality, you know, in real life I have two left feet. I am never going to be good at football however, what we find with e-sports is it makes gaming and racing accessible. I can go and drive the same circuits as Lando Norris and Daniel Ricardo, and I can improve. And I can learn like use data to start to discover different ways. And it's an incredibly expanding exploding industry. And what McLaren have done is they've said, actually, we're going to make a professional racing team, an e-sports team called the McLaren Shadow team. They have this huge competition called the Logitech KeyShot challenge. And when we looked at that, we sort of lost the similarities in what we're trying to achieve. We are quite often starting to merge the physical world and the digital world with our customers. And this was an amazing opportunity to start to do that with the McLaren team. >> So you're creating this really dynamic racing experience, right? That, that, that gives people like me, or like our viewers, the opportunity to get even a better feel for, for the decision-making and the responsiveness of the cars and all that. So again, data, where does that come into play there? Now, What, what kind of inputs are you getting from me as a driver then as an amateur driver? And, and how has that then I guess, how does it express in the game or expressed in, in terms of what's ahead of me to come in a game? >> So actually there are more data points that come out of the F1 2021 Codemasters game than there are in Formula One car, you get a constant stream. So the, the game will actually stream out real telemetry. So I can actually tell your tire pressures from all of your tires. I can see the lateral G-Force longitudinal. G-Force more importantly for probably amateur drivers like you and I, we can see is the tire on asphalt, or is it maybe on graphs? We can actually look at your exact position on track, how much accelerator, you know, steering lock. So we can see everything about that. And that gets pumped out in real time, up to 60 Hertz. So a phenomenal amount of information, what we, when we started the relationship with McLaren, Formula One super excited or about to go racing. And then at Melbourne, there's that iconic moment where one of the McLaren team tested positive and they withdrew from the race. And what we found was, you know, COVID was starting and the Formula One season was put on hold. The FIA created this season and called i can't remember the exact name of it, but basically a replica e-sports gaming F1 series. We're using the game. Some of the real drivers like Lando, heavy gamer was playing in the game and they'd run that the same as race weekends. They brought celebrity drivers in there. And I think my most surreal zoom call I ever was on was with Lando Norris and Pierre Patrick Aubameyang, who was who's the arsenal football captain, who was the guest driver in the series to drive around Monaco and Randy, the head of race strategy as McLaren, trying to coach him on how to go drive the car, what we ended up with data telemetry coming from Splunk. And so Randy could look out here when he pressing the accelerator and the brake pedal. And what was really interesting was Lando was watching how he was entering corners on the video feed and intuitively kind of coming to the same conclusions as Randy. So kind of, you could see that race to intuition versus the real stats, and it was just incredible experience. And it really shows you, you know, racing, you've got that blurring of the physical and the virtual that it's going to be bigger and bigger and bigger. >> So to hear it here, as I understand what you were just saying now, the e-sports racing team actually has more data to adjust its performance and to modify its behaviors, then the real racing team does. Yep. >> Yeah, it completely does. So what we want to be able to do is turn that into action. So how do you do the right car setup? How do you go and do the right practice laps actually have really good practice driver selection. And I think we're just starting to scratch the surface of what really could be done. And the amazing part about this is now think of it more like a digital twin, what we learn on e-sports we can actually say we've learned something really interesting here, and then maybe a low, you know, if we get something wrong, it may be doesn't matter quite as much as maybe getting an analytics wrong on race weekend. >> Right. >> So we can actually start to look and improve through digital and then start to move that support. That's over to kind of race weekend analytics and supporting the team. >> If I could, you know, maybe pun intended here, shift gears a little bit before we run out of time. I mean, you're, you're involved on the business side, you know, you've got, you know, you're in the middle east Africa, right? You've got, you know, quite an international portfolio on your plate. Now let's talk about just some of the data trends there for our viewers here in the U S who maybe aren't as familiar with what's going on overseas, just in terms of, especially post COVID, you know, what, what concerns there are, or, or what direction you're trying to get your clients to, to be taking in terms of getting back to work in terms of, you know, looking at their workforce opportunities and strengths and all those kinds of things. >> I think we've seen a massive shift. I think we've seen that people it's not good enough just to be storing data its how do you go and utilize that data to go and drive your business forwards I think a couple of key terms we're going to see more and more over the next few years is operational resilience and business agility. And I'd make the assertion that operational resilience is the foundation for the business agility. And we can dive into that in a second, but what we're seeing take the Netherlands. For example, we run a survey last year and we found that 87% of the respondents had created new functions to do with data machine learning and AI, as all they're trying to do is go and get more timely data to front line staff to go. And next that the transformation, because what we've really seen through COVID is everything is possible to be digitized and we can experiment and get to market faster. And I think we've just seen in European markets, definitely in Asia Pacific is that the kind of brand loyalty is potentially waning, but what's the kind of loyalty is just to an experience, you know, take a ride hailing app. You know, I get to an airport, I try one ride hailing app. It tells me it's going to be 20 minutes before a taxi arrives. I'm going to go straight to the next app to go and stare. They can do it faster. I want the experience. I don't necessarily want the brand. And we're find that the digital experience by putting data, the forefront of that is really accelerating and actually really encouraging, you know, France, Germany are actually ahead of UK. Let's look, listen, their attitudes and adoption to data. And for our American audience and America, America is more likely, I think it's 72% more likely to have a chief innovation officer than the rest of the world. I think I'm about 64% in EMEA. So America, you are still slightly ahead of us in terms of kind of bringing some of that innovation that. >> I imagine that gap is going to be shrinking though I would think. >> It is massively shrinking. >> So before we, we, we, we are just a little tight on time, but I want to hear about operational resilience and, and just your, your thought that definition, you know, define that for me a little bit, you know, put a little more meat on that bone, if you would, and talk about why, you know, what that is in, in your thinking today and then why that is so important. >> So I think inputting in, in racing, you know, operational resilience is being able to send some response to what is happening around you with people processing technology, to be able to baseline what your processes are and the services you're providing, and be able to understand when something is not performing as it should be, what we're seeing. Things like European Union, in financial services, or at the digital operational resilience act is starting to mandate that businesses have to be operational in resilient service, monitoring fraud, cyber security, and customer experience. And what we see is really operational resilience is the amount of change that can be absorbed before opportunities become risk. So having a stable foundation of operational resilience allows me to become a more agile business because I know my foundation and people can then move and adjust quickly because I have the awareness of my environment and I have the ability to appropriately react to my environment because I've thought about becoming a resilient business with my digital infrastructure is a theme. I think we're going to see in supply chain coming very soon and across all other industries, as we realize digital is our business. Nowadays. >> What's an exciting world. Isn't it, James? That you're, that you're working in right now. >> Oh, I, I love it. You know, you said, you know, eight and an eight and a half years, nine years at Splunk, I'm still smiling. You know, it is like being at the forefront of this diesel wave and being able to help people make action from that. It's an incredible place to be. I, is liberating and yeah, I can't even begin to imagine what's, you know, the opportunities are over the next few years as the world continually evolves. >> Well, every day is a school day, right? >> It is my favorite phrase >> I knew that. >> And it is, James Hodge. Thanks for joining us on theCUBE. Glad to have you on finally, after being on the other side of the camera, it's great to have you on this side. So thanks for making that transition for us. >> Thank you, John. You bet James Hodge joining us here on the cube coverage of splunk.com 21, talking about McLaren racing team speed and Splunk.

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> Welcome back. Rush hours started a little bit early here in New York City, with over 10,000 people in attendance for any of US Summit in New York City. I'm stupid, and my co host for today is Corey Quinn. Having a welcome to the program to first time guests from our host Amazon Web service is to my right. Here is Deepak Singh, who is the director of Compute Service's. To his right is Aaron Cow, Who's the senior manager product marketing Gentlemen, thanks so much for joining us. Thank >> you for having us >> for having us, all right, so we know that every day we wake up and there's new announcements coming from Amazon, and the only way most of us keep up with it is trying to re Cory's newsletter here. But in your group and computer, we know there's a lot going on and quite a few announcements. So, Aaron, what do you kick us off with? Some of the hard news that went >> through this morning? Yeah, we just launched Amazon event. Bridgette's Ah, serverless event boss that allows youto connect your applications with data from sources like sass applications. A devious resource is in your own applications. >> All right, So Deepak would look to dig into that a little bit. I like you said, you that Amazon. You learned a lot from cloudwatch in building this tool. Everybody looking at kind of lambda and the service faces, Like Okay, how all these pieces together is that all? Amazon service is all the time. And, of course, Amazon has a huge ecosystem. But help help us understand a layer down. You know how this works. >> Yeah. So, you know, a dress service send events watchman consumer event from one of the best ways to do it is through Lando. Lando. One of London's biggest trends is the number off integration we have with events both taking in events and triggering event. But to your point there already events inside database system. I think one of the things as a service owner, that really excites me about event. How now? Customers of access, not just two ventricles inside eight of us were awesome apartments extended so that the application you can build will be really exciting. >> Quite a few other announcements maybe August or someone CK >> is another announcement where it's open. Source. Software development framework allows you to model your applications using programming language like typescript Job a python and got that. You know the whole thing with building in the cloud. It's slightly different. You usedto take your coat. Put it on a servant. Run it. Now people are building things a little more distributed. Using a lot of different resource is for their applications, so it's getting provisioning. Your infrastructure is a little bit harder, right? Either Have to do a lot of things manually. Are maybe you're writing. A lot of scripts are using a domain specific language, But with CD Kay, you're now able to use the programming languages that you're hurting your applications with two model and provisions your infrastructure. So it's super helpful. Really think it's gonna help developers increase their development velocity? They're able to use things like loops, conditions, object oriented programming. They don't have to do context switching and just a few lines of code. They're able to do a lot more. All right, >> I want I want a playing with it a little bit when it was in review, and one of things that I found that it was extremely helpful was it was a lot easier for me to write something in using CD kay and then see what that rendered down to in terms of cloud formation. And then, oh, I guess that's how I do it in cloud formation, which was great. The counterpoint, though, is it also felt, at times like it was super wordy. So if I read that what it generates compared to what I normally right, which is admittedly awful. But it's all right, we'll start to feel like I'm doing it wrong with that. And then with amplify and with Sam and the rest. There's a lot of higher level abstractions that build cloud formation for you. But then it renders down in a few different key ways under the hood. How much are these products that you're coming out with starting to shape the direction of confirmation itself? Or is that mostly baked and done? >> There's a lot of products that we're building that you know are complimenting information. Information is the template ing modeling language to provisional abusive resource is put on top of that. We have things like Sam, right? That provides a declared of ATM or high level abstracted declared way to build on topical information. You know, we have amplified also use this information to help you build mobile applications in front development and then finally have see decay for general use other things. They're all complimenting and you know are things customers are asking for helping us >> get the ecosystem. Deepak. The container space, of course, has been You know what one of these tidal waves that we've been watching on It's fundamentally changing the way people architect their applications. That huge impact on your product line Give us the update. If you could just start with some of the high level. Remember first when I talk to you. A couple of years ago, the whole kubernetes piece was sorting out. So you know, e c s E. K s usedto have a much longer name that Cory >> Cory. Finally, you fix the compensation problem where someone was getting compensated based upon number of syllables in a service name. So good on you on that one. >> Right on. Uh, you know, acronym, am I? Maybe you can you know, settle once and for all. You know how how we pronounce that >> I'm old school in love with the Army. >> But what what walk us through? Kind of. You know, your container service is, >> I think, the great thing about container, I said, adoption is everywhere on what we find. It brought a VCs the growth of cares where they're running it on to our fargate. Everything is growing like crazy because people find new interesting ways to run applications based on what they know. One what they're comfortable with their customers. Customers like Snap. There's no community well, and they're building on their building a big chunk of their new infrastructure on kneecaps or need to be with, and it basically helped develop a velocity. On the flip side, your customers like Turner Broadcasting that run a lot of their Web service is the comedy central content properties like that on Fargate because they can just stamp them out. They all you know, it's about time. It's a service that you can just keep expanding. So it boils down to one of the key things that you're comfortable with. One of the reasons you fix something if you are running like snap across. You know, in many different looks places you are likely to choose community and standardize on that. So that's the best part for me is people have choices and then the pic based on what they need. At that point in time, it can be two different teams at the same place. Picking a different solution. I will add that one of the areas that we are focused on now is a dub ability and develop experience, though the areas that our customers have been asking for CD Kay played into that record in the demo this morning. And with the probability with container inside on with the fluid that be announced, I think though that area, they do a lot more >> going forward, right? That was one of those cloudwatch container insights. Just explain what that one is >> so historically, when you do cloudwatch look very bm centric, you're looking at CPU memory. You're zooming application. We are instances run for a particular period of time. At the container world you have service is with the underlying tasks. Come and go all you know, a very different rate container inside. It's meant to be a world aware of the fact that you're containerized application that fast service is and part, they're able to get more fine grained metrics on the things that container customers care about. And you're not trying to use the BM centric language to look at the content. That's the biggest reason for doing that. And then on the floor in bedside Boy, our customers want loud rounding to whatever they want to do it on where they understand three or elasticsearch. We do that with data borrows. So we basically wrote a bunch of open source plug in for fluent, but they just end your log where you want them to go. That's kind of maybe a >> Yeah, I view it as more of a log router than I do. Almost anything else? Yeah, a question of where did it come from? Where does it go? How do you do? Keep straight. It's at this point. What is it out? What is it output to these days of their various destination options? Third party vendors cloudwatch history >> to plug in 14315413 because so many people in the center there with three the other one was like Anita. There. Apart from there, you can send it to read, Chef, you can send it todo you can send it to elasticsearch. So based on what however you want and I'll analyze it, you can send it to a custom resource. So you want you're using some third party provider. You can just send your logs over to those. >> Corey, you know, you're dealing with a lot of customers. You know, there's so many, you know, different instance types and some of some of the pieces. You know, what's the feedback you're giving? You know, Amazon these days >> entire depends upon the service teams, and it ranges from This is amazing. Excellent job, too. Okay, it's a good start, and it's always a question, though. It's when you have what 200 service options are darn near. It at this point aren't 70. It's impossible to wind up with something that is evenly consistent, and you have service is that air sub components of other service is built on top. I mean, I think the uh, I guess the feedback I've been giving almost universally across the board is assume that I am about 20% as smart as you right now seem to think I am and then explain it to me, and then I'll probably understand it a lot better. It comes down to service the storytelling more or less of meeting people of various points along their journey, and that I was mentioning in our editorial session just before this segment that that's something that AWS has markedly improved on the last two or three years, where you have customer stories that are rapidly moving up the up the stack as Faras Leverage Service's It's not just we took the EMS, and now we run them somewhere else. Now it's about building of extremely volume intensive applications on top of a whole bunch of managed service is and these air serious cos these air regulators. It's not just Twitter for pets anymore. >> Nothing wrong with that. No, >> So way were discussing like Enron was a great case this morning, and they talked about in the four years that they've been on, they re architected three times, you know, how do you balance all of these new wins is coming out with, you know, how do we make sure that I deploy something today that I've got the flexibility to change. But, you know, I want to be able to lock in my pricing and make it easier. >> Actually, we think about that quite a bit. One of the reasons we met, the way we did something that sits outside a container orchestrator. What? It doesn't lock you into choosing one or the other or even using an architecture. You can start over the monolith, start putting sidecars on it. It's getting with the ability to all your traffic portions of applications. You can start breaking out. You can put them on target. You can put them on PCs. You can put them on it, too. I think that is something we did very consciously because so many of our customers are in that position. And I think more and more are going to go higher up the stock using managed databases. You think lambda. But it's not decision they need to make all up front. They can do it piecemeal, and we see a custom fender. The good example there done that. >> I think one of the >> philosophies of like eight of us is giving customers building blocks the buildings on, so the whole thing is here's a new primitive that you can use. Then you can take it out, replace something with something else, depending on your needs. So we give customers flexibility and choice. >> And part of the problem is that that very much becomes a double edged sword. I mean, most recently you've had effectively declared war on alphabet. I don't mean the large cloud provider that turns things off for a living. I'm talking about the English alphabet where you take a look at all the different ec2 instance types. I think in US East one. Now there's over. What is it? 100 90 different instances you can pick from. It leads to analysis paralysis. Which one do I pick? What's the right answer? What am I committing to? What am I not? And you see that? That's a microcosm. The larger service problem. I want to build a Web app that does a thing. Which service is do I use? You open up the service listing and you just get this sort of sinking sensation. I get that. I can't imagine what someone new to the space is getting to >> you, and this is where things like amplify fargate aws patch. You don't need to select an instance where you just tell us for your requirements are on Batch makes that collection for you the core building. What's important because you can't really figure out what to do. But then you see us too much more about the attack to help people get there. It's an ongoing thing that will keep trying to tackle, but you see a lot more of that. >> It's controversial. One of my favorite things about Lambda, for example, is there's one knob ram, and as you turn that up, other performance characteristics increase and people complain about it. But I love the simplicity because I don't have to sit and think and make all these different decisions. It's one access, >> but if you want more knob, you can you fuck it. So I think that that's the beauty ofit that you do have that choice. >> Yeah, one lines there, and I really liked it. Borders keynote. Is he said way? Really? You know my words, commoditized. I t We all have access to all of the tools now, you know that was you know what big date originally file. It also was used to have to be a nation state 4100 to be able to do some of these things. So, you know, what do you hear from customers? How do they make sure you know, they're staying competitive and ahead on their four in that relationship between the business and I T. What do you hear from your customers these days? >> In terms of that? Well, I think, um, for you know, for customers like I think of Emperor age is a, uh, a pretty good example off that in terms of customers asking us for ability to, you know, integrate their SAS providers and a great a lot of different things and not have thio you No, no, no. >> I have >> to do a lot of undifferentiated heavy lifting and things like that. And customers are increasingly moving towards, like avenger oven architectures. And they asked us, Hey, we really like cloudwatch events and how you do things with a iittie automation and then bringing SAS providers and on way wantto you know, we don't want to build a polling infrastructure and orderto access athe eyes and do all all the heavy lifting. What we did was we built out way took cloudwatch events and added new features for SAS applications and build that into a separate service for people to use. That's like, you know, a lot of the relationships we have our customers listening to what they need and giving them what they want. >> I think that that's a very valuable thing. We used to say, You know, five years ago you would talk about, you know, let's get rid of indifferent, heavy lifting Well, now it's like, No, no, let's enable you know some thing that you would have thought was heavy lifting and we're daunted to be able to do it. But now hopefully it's easier because a lot of this stuff, you know, he said, This is still a little bit daunting, and you know, you've got a lot of ecosystem and service providers, and service is help us. You take care of, you know, because it's the paradox of choice. With all the options that you >> have on. I think that's the beauty of what I'm in a customer that smart. They managed to find interesting ways to keep challenging us and keep us busy. But I also think that really, really many of them the ones who've been able to be successful. I figured out what it needs to be. Take all the tools to give them which other ones where they want to completely hand it over to AWS and give us the responsibility. And then which ones today really feeling, get they care about and the ones who can find their balance of the ones that we see moving faster. I think that's what we're trying to >> write that one thing that does absolutely permeates virtually every service team I've worked with that AWS. I mean, I've had this experience with you where I talk about how my use case isn't a terrific fit for your product, and your response is always well, what is your use case? It's not. Is starting off on the baseline assumption that my use cases ridiculous, which, let's face it, it probably is. But being able to address a customer need to understand that even if it doesn't dictate, road map is incredibly valuable, and I don't find there are too many players in any space, let alone this one that are willing to have the patience to listen to. Frankly, some loud person wearing a suit. >> Way try. I mean, I think you heard me say this so much like a big junk. 85 90% of a road map. Customer request. I would say that even though remember remaining 10% maybe not think that they're directly asked for but think that you observed their running to or that we run into working with, you know, the one of the customers go ahead of the pack. Okay. They have this problem, Baker. How do you generalize that? And we try and understand what it means. One of the reasons to be made the container road map public was This space is moving so quickly. It's almost impossible for us to talk to enough customers to figure that out. So, like, okay, that gives us an avenue for them to come to us and just tell us and get have >> issues. Yeah, s o right. Final question for both of you directions. Looking forward, you know, the road map we love when there is publicly facing material, not under the NBA's that we normally have to be able to hear. So what are you hearing from your customers? What direction are they pulling you towards and that we should expect tow watch aws kind of a cz we head towards reinvent later this year. Yeah, >> like customers are asking us for different things for developer experience, especially event driven architectures. I think there's gonna be a lot of interesting things happening in the land of space and that entire space >> on to add to that. I think your point earlier helping the simplified choices is going to be a big part of it. Meeting them where they are in their ideas with the cooling is a big part of what you'll see us do. So you know, I think you saw examples today. We'll keep building on top of >> All right. Well, send our congratulations to the two pizza teams that worked on all of the projects that were announced today. Look forward to seeing you. You know, down the road in tracking down. Thanks so much. And welcome to be in Cuba one night having us Deepak, you know, from AWS. He's Cory Quinn on student back with lots more coverage from 80 West Summit here in New York City. Thanks for watching

(soft electronic music) >> Announcer: Live from Vancouver, Canada, it's theCUBE. Covering OpenStack Summit North America 2018. Brought to you by Red Hat, the OpenStack Foundation, and it's ecosystem partners. >> Welcome back, I'm Stu Miniman here with my cohost John Troyer and you're watching theCUBE's exclusive coverage of OpenStack Summit 2018 in Vancouver. Happy to welcome you back to the program, off the keynote stage this morning, Mark Shuttleworth, the founder of Canonical. Thank you so much for joining us. >> Stu, thanks for the invitation. >> Alright, so you've been involved in this OpenStack stuff for quite a bit. >> Right, since the beginning. >> I remember three years ago we were down in the other hall talking about the maturity of the platform. I think three years ago, it was like this container thing was kind of new and the basic infrastructure stuff was starting to get, in a nice term, boring. Because that meant we could go about business and be on the buzz of there's this cool new thing and we're going to kill Amazon, kill VMware, whatever else things that people thought that had a misconceived notion. So bring us forward to where we are 2018, what you're hearing from customers as you look at OpenStack and this community. >> Well, I think you pretty much called it. OpenStack very much now is about solving a real business problem, which is the automation of the data center and the cost parody of private data centers with public data centers. So I think we're at a time now where people understand the public cloud is a really good thing. It's great that you have these giant companies dueling it out to deliver better quality infrastructure at a better price. But then at the same time, having your own private infrastructure that runs cost-effectively is important. And OpenStack really is the only approach to that that exists today. And it's important to us that the conversation is increasingly about what we think really matters, which is the economics of owning it, the economics of running it, and how people can essentially keep that in line with what they get from the public cloud providers. >> Yeah, one of the barometers I use for vendors these days is in this multi-cloud world, where do you sit? Do you play with the HyperScalers? Are you a public cloud denier? Or, like most people you're, most people are somewhere in-between. In your keynote this morning, you were talking a bit about all of the HyperScalers that use your products as well as-- >> Ubuntu is at the heart of all of the major public cloud operations at multiple levels. So we see them as great drivers of innovation, great drivers of exposure of Ubuntu into the enterprise. We're still, by far, the number one platform used in public cloud by enterprises. It's hard to argue that public cloud is testing Dev now. It really, really isn't and so most of that is still Ubuntu. And now we're seeing that pendulum swing, all of those best practices, that consumption of Ubuntu, that understanding of what a leaner, meaner Enterprise Linux looks like. Bringing that back to the data center is exciting. For us, it's an opportunity to help enterprises rethink the data center to make it fully automated from the ground up. OpenStack is part of that, Kubernetes is part of that and now the cherry on top is really AI where people understand they have to be able to do it on public cloud, on private infrastructure and at the Edge. >> Mark, I wanted to talk about open source. Marketing open source, for a minute. We are obviously here, we're part of an open source community. Open source, defacto, has won the cloud technology stack wars. So there's one way of selling OpenStack where you pound on open a lot. >> I'm always a bit nervous about projects that put open. It sounds like they're sort of trying to gloss over something or wash over something or prove a point. They shouldn't have to. >> There's one about the philosophy of open source, which certainly has to stay there, right. Because that's what drove the innovation but I was kind of impressed about on the stage today, you talked about the benefits. You didn't say, well the venture's open. You said, well, we're facilitating these benefits. Speed to market, cost, et cetera. Can you talk about your approach, Canonical's approach to talking about this open source product in terms of its benefits? >> Sure, look, open source is a license. Under that license, there's room for a huge spectrum of interest and opinions and approaches. And I'd say that I certainly see an enormous amount of value in what I would call the passion-based open source story. Now, OpenStack is not that. It's too big, too complicated, to be one person's deep passion. It really isn't. But there's still a ton of innovation that happens in our world, across the full spectrum of what we see with open source, which is really experts trying to do something beautiful and elegant. And I still think that's really important in open source. You also have a new kind of dimension, which is almost like industrial trench warfare with open source. Which is huge organizations leveraging effectively their ability go get something widespread, widely adopted, quickly and efficiently by essentially publishing it as open source. And often, people get confused between these two ends of the spectrum. There's a bunch in between. What I like about OpenStack is that I think it's over the industrial trench warfare phase. You know, you just don't see a ton of people showing up here to throw parties and prove to everyone how cool they are. They've moved on to other open source projects. The people who are here are people who essentially have the real problem of I want to automate my data center, I want to have, essentially, a cloud that runs cost-effectively in my data center that I can use as part of a multi-cloud strategy. And so now I think we're in to that sort of, a more mature place with OpenStack. We're not either sort of artisan or craftsmen oriented, nor are we a guns blazing brand oriented. It's kind of now just solving the problems. >> Mark, there's still some nay-sayers out in the marketplace. Either they say that this never matured, there's a certain analyst firm that put out a report a couple of months ago that, it kind of denigrated what's happening here. And then there's others that, as you said, off chasing that next big wave of open source. What are you hearing from your customers? You've got a good footprint around the globe. >> So that report is nonsense, for a start. They're always wrong, right. If they're hyping something, they're wrong and if they're dissing something then they're usually wrong too. >> Stu: They have a cycle for that, I believe. (chuckling) >> Exactly. Selling gold at the barroom. Here's how I see it. I think that enterprises have a real problem, which is how do they create private cloud infrastructure. OpenStack had a real problem in that it had too many opinions, too many promises. Essentially a governing structure not a leadership structure. Our position on this has always been focus on the stuff that is really necessary. There was a ton of nonsense in OpenStack and that stuff is all failing. And so what? It was never essential to the mission. The mission is stand up a data center in an automated way, provide it, essentially, as resources, as a service to everybody who you think is authorized to be there, effectively. Segment and operate that efficiently. There's only a small part of OpenStack that was ever really focused on that. That's the stuff that's succeeding, that's the stuff we deliver. That's the stuff, we think very carefully about how to automate it so that, essentially, anybody can consume it at reasonable prices. Now, we have learned that it's better for us to do the operations almost. It's better for us actually to take it to people as a solution, say look, explain your requirements to us then let us architect that cloud with you then let us build that cloud then let us operate that cloud. Until it's all stable and the economics are good, then you can take over. I think what we have seen is that you ask every single different company to build OpenStack, they will make a bunch of mistakes and then they'll say OpenStack is the problem. OpenStack's not the problem. Because we do it again and again and again, because we do it in many different data centers, because we do it with many different industries, we're able to essentially put it on rails. When you consume OpenStack that way it's super cheap. These aren't my numbers, analysts have studied the costs of public infrastructure, the cost of the established, incumbent enterprise, virtualization solutions and so on. And they found that when you consume OpenStack from Canonical it is much, much cheaper than any of your other options in your own private data center. And I think that's a success that OpenStack should be proud of. >> Alright, you've always done a good job at poking at some of the discussions happening in the industry. I wouldn't say I was surprised but you were highlighting AI as something that was showing a lot of promise. People have been a little hot and cold depending on what part of the market you're at. Tell us about AI and I'd love to hear your thoughts in general. Kubernetes, Serverless, and ask you to talk about some of those new trends that are out there. >> Sure, the big problem with data science was always finding the right person to ask the right question. So you could get all the data in the world in a data lake but now you have to hire somebody who instinctively has to ask the right question that you can test out of that data. And that's a really hard problem. What machine learning does is kind of inverts the problem. It says, well, why don't we put all that data through a pattern matching system and then we'll end up with something that reflects the underlying patterns, even if we don't know what they are. Now, we can essentially say if you saw this, what would you expect? And that turns out to be a very powerful way to deal with huge amounts of data that, previously, you had to kind of have this magical intuition to kind of get to the bottom of. So I think machine learning is real, it's valuable in almost every industry, and the challenges now are really about standardizing underlying operations so that the people who focus on the business problems can, essentially, use them. So that's really what I wanted to show today is us working with, in that case it was Google, but you can generalize that. To standardize the experience for an institution who wants to hire developers, have them effectively build machine-driven models if they can then put those into production. There's a bunch of stuff I didn't show that's interesting. For example, you really want to take the learnings from machine-learning and you want to put those at the Edge. You want to react to what's happening as close to where it's happening as possible. So there's a bunch of stuff that we're working on with various companies. It's all about taking that AI outcome right to the Edge, to IOT, to Edge Cloud but we don't have time to get in to all of that today. >> Yeah, and Ubuntu is at the Edge, on the mobile platform. >> So we're in a great position that we're on the Cloud. Now you see what we're doing in the data center for enterprises, effectively recrafting the data center has a much leaner, more automated machine. Really driving down the cost of the data center. And yes, we're on the higher-end things. We're never going to be on the LightBulb. We're a full general-purpose operating system. But you can run Ubuntu on a $10 board now and that means that people are taking it everywhere. Amazon, for example, put Ubuntu on the DeepLens so that's a great example of AI at the edge. It's super exciting. >> So the Kubernetes, Serverless-type applications, what are your thinkings around there? >> Serverless is a lovely way to think about the flow of code in a distributed system. It's a really nice way to solve certain problems. What we haven't yet seen is we haven't seen a Serverless framework that you can port. We've seen great Serverless experiences being built inside the various public clouds but there's nothing consistent about them. Everything that you invest in a particular place is very useful there but you can't imagine taking that anywhere else. I think that's fine. >> Stu: Today's primarily Lando. >> And I think the other clouds have done a credible job of getting there quickly. But kudos to Amazon for kind of pioneering that. I do think we'll see generalized Serverless, it just doesn't exist at the moment and as soon as it does we'll be itching to get it into people's hands. >> Okay, yeah? >> Well, I just wanted to pull out something that you had said in case people miss it, you talked about managed OpenStack. And that, I think, managed Kubernetes has been a trend over the last year. Managed OpenStack now. Has been trans-- >> With these complex pieces of infrastructure, you could easily drown in learning it all and if you're only ever going to do one, maybe it makes sense to have somebody else do it for a while. You can always take it over later. So we're unusual in that we will essentially standup something complex like an OpenStack or a Kubernetes, operate it as long as people want and then train them to take over. So we're not exclusively managed and we're not exclusively arms-length. We're happy to start the one way and then hand over. >> I think that's an important development, though, that's been developing as the systems get more complicated. One UNIX admin needs a whole new skill set or broader skill set now that we're orchestrating a whole cloud so that's, I think that's great. And that's interesting. Anything else you're looking forward to, in terms of operation models. I guess we've said, Ubuntu everywhere from the edge to the center and now managed, as well. Anything else we're looking at in terms of operators should be looking at? >> Well, I think it just is going to stay sort of murky for a while simply because each different group inside a large institution has a boundary of their authority and to them, that's the edge. (chuckling) And so the term is heavily overloaded. But I would say, ultimately, there are a couple of underlying problems that have to be solved and if you look at the reference architectures that the various large institutions are putting out, they all show you how they're trying to attack these patterns using Ubuntu. One is physical provisioning. The one thing that's true with every Edge deployment is there are no humans there. So you can't kind of Band-Aid over the idea that when something breaks you need to completely be able to reset it from the ground up. So MAAS, Middle as a Service, shows up in the reference architectures from AT&T and from SoftBank and from Dorich Telecom and a bunch of others because it solves their problem. It's the smallest piece of software you can use to take one server or 10 servers or 100 servers and just reflash them with Windows or CentOS or whatever you need. That's one thing. The other thing that I think is consistently true in all these different H-Cloud permutations or combinations is that overhead's really toxic. If you need three nodes of overhead for a hundred node OpenStack, it's 3%. For a thousand node OpenStack, it's .3%. It's nothing, you won't notice it. If you need three nodes of OpenStack for a nine node Edge Cloud, well then that's 30% of your infrastructure costs. So really thinking through how to get the overhead down is kind of a key for us. And all the projects with telcos in particular that we're working, that's really what we bring is that underlying understanding and some of those really lightweight tools to solve those problems. On top of that, they're all different, right. Kubenetes here, Lixti there, OpenStack on the next one. AI everywhere. But those two problems, I think, are the consistent things we see as a pattern in the Edge. >> Alright, so Mark, last question I have for you. Company update. So last year we talked a little bit about focusing, where the company's going, talked a bit about the business model and you said to me, "Developers should never have to pay for anything." It's the governance people and everything like that. Give us the company update, everything from rumors from hey, maybe you're IPO-ing to what's happening, what can you share? >> Right, so the twin areas of focus, IOT and cloud infrastructure. IOT continues to be an area of R and D for us so we're still essentially underwriting an IOT investment. I'm very excited about that. I think it's the right thing to be doing at the moment. I think IOT is the next wave, effectively, and we're in a special position. We really can get down, both economically and operationally, into that sort of small itch kind of scenario. Cloud, for us, is a growth story. I talked a little bit about taking Ubuntu and Canonical into the finance sector. In one year, we closed deals with 20% of the top 20 banks in the world to build Ubuntu base and open infrastructure. That's a huge shift from the traditional dependence exclusively on VMware Red Hat. Now, suddenly, Ubuntu's in there, Canonical's in there. I think everybody understands that telcos really love Ubuntu and so that continues to grow for us. Commercially, we're expanding both in Emir and here in the Americas. I won't talk more about our corporate plans other than to say I see no reason for us to scramble to cover any other areas. I think cloud infrastructure and IOT is plenty for one company. For me, it's a privilege to combine that kind of business with what happens in the Ubuntu community. I'm still very passionate about the fact that we enable people to consume free software and innovate. And we do that without any friction. We don't have an enterprise version of Ubuntu. We don't need an enterprise version of Ubuntu, the whole thing's enterprise. Even if you're a one-person startup. >> Mark Shuttleworth, always a pleasure to catch up. Thank you so much for joining us. >> Mark: Thank you, Stu. >> For John Troyer, I'm Stu Miniman. Back with lots more coverage here from OpenStack Summit 2018 in Vancouver. Thanks for watching theCUBE. (soft electronic music)

>> Announcer: Live from Las Vegas It's theCube covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back to our live coverage. theCube here at AWS re:Invent 2017 Our fifth year covering Amazon Web Services and their massive growth. I'm John Furrier, my co-host Lisa Martin. Here our next guest is CTO of WANdisco, Jugane Sundar. Welcome back to theCube. >> Thank you John. >> You guys are everywhere. WANdisco around the table and all these deals so you guys have been doing extremely well with (indistinct talking) property. What's new? You got some news? >> Yes we do, we recently announced integration with Amazon's AWS Snowball device which gives you the ability to do migration of on-premises workload into the Cloud without down time, and then the end result is a hybrid cloud environment that you can have an active for right environment on both sides. That's a unique capability, nobody else can do that today. >> What does it mean for AWS and their customers 'cause they're very customer focused. What are you guys bringing to the table? >> We bring a whole lot of big data workloads, analytics workloads, IoT workloads into their Cloud. And the beauty of the cloud is that you may have a 20 node cluster on-premises but you can run analytics with a 1000 nodes up in the Cloud on demand and pay just for that use. We think it's a very powerful value proposition. >> Where are you seeing the most traction? We've talking about the massive growth at 18 billion dollar annual runway that fit AWS and Andy's conversation with you John the other day said we haven't gotten that big on startups alone. So even some of the things like the advertising that AWS is now starting to do suggests they're going up the stack to the Enterprise and to the Sea Suites. Where are you guys seeing the most traction with AWS? Is it in the Enterprise space, is it in the start up space, both? >> So somewhat because of our route, what we're finding is that the large majority of Big Data customers and analytics customers from the last two, three years are all considering some form of addition of a cloud to their environment. If it's not a wholesale migration, it's a hybrid environment. It's bursting out into the cloud type of use case and what you're finding is that growth of on-premise Big Data and analytics systems is slowing down because once you get to the Cloud, the plethora of tools you have, the facilities that the scale brings to you is just unmatched. That's the trend we really see in the market. >> We've seen a lot of people go and use it in the marketplace. Juniper Networks for instance, are seeing some activity at the network. Who would have thought a network player is gonna to pick it in the Cloud, but this is what industrial-strength cloud looks like. You guys have the active active. Where does that fit in for the customers who wanna leverage the apps, and don't wanna worry about the networks? >> Exactly, the traditional model of thinking was use the Cloud for back up. You have your on-premise stuff. The cheapest way to back it up is into the Cloud. But that's really just scratching the tip of the iceberg. Once you put your data up in the Cloud, you have the ability to have it strongly consistently replicated then you can do amazing things from the Cloud. You can do a whole new analytics system. Perhaps you want to experiment with Spark in the Cloud and have it on on high on-premise that works very well. Now that both sides are actively writeable, you can create partitions of your data that are dynamically generated written to both sides. These are things that people did not consider. Once they stumble upon it, it just opens their mind to a whole new way of operating. >> Business Park, I've heard some rumors and rumblings in the developer community here that they're running Spark on Lando. People always hacking with new stuff. So Lando server list I think is coming down. How does that relate to some of things that are driving WANdisco's, how do you relate to that? Does that help you? Does that hurt you guys? >> It helps us, the way we look at it. We're all about strong replication of storage. Lando is no storage, you talk to the underlying storage of some kind. It's S3, it's EBS volumes whatever. So long as the storage comes through our system. Any growth, any simple easy way for applications to be written is hugely positive for us. >> What are the start ups out there? We've seen a lot of start ups really missed the mark. They misfired on the Cloud and you seen some stars that have played it well. They've got in the tornadoes as we say. In fact, Geoffrey Moore, I think is rewriting his book Inside the Tornado, which is a management paradigm. But there really seems to be a new business model. You guys are like ever green at WANdisco because you're unique (indistinct talking) property. How are you guys working with that business model and what are some of the things you're seeing with start ups and companies who are trying to play the cloud but are misfiring? >> Right so WANdisco as you know stands for Wide Area Network Distributed Computing, and the Cloud is like a huge bonus to it. It's all about the Wide Area Network. We are now consolidating a bunch of work in the cloud, but guess what? It's gonna go back to going to go into the edge in some way 'cause the edges are getting smarter. You need replication between those. We see a lot of that coming up in the next two, three, five years. IoT workloads and use cases all involve somewhat of edge smart computing. We replicate between those really well. >> Lisa, we always talk about the trend is your friend. In your case, Cloud is your friend. >> Indeed, it is. The Cloud is all about wide area network computing and we are the ones who can really replicate-- >> How does a customer know what to do when it comes down to getting involved with WANdisco? It's not obvious. Spell it out, why do they need you guys? When do you get involved? What specific things should be red flags to a potential customer or a customer who says I'm gonna go in on the Cloud. Unpack that. >> Let me give you a simple example. We look at Amazon S3, it's a Cloud service storage. But do you know that it's actually on a per region basis. When you create a bucket to put objects into the bucket, it's located in one region. If you want it replicated elsewhere, they have cross-region replication which is an eventually consistent replication system that doesn't give you the consistent results that you want. If you have such a situation employing our technology immediately gives you consistent replication. Be it Cloud regions, Cloud to Cloud or on-premise to Cloud. The end result is the minute you step into replication across the land, every solution out there doesn't do it consistently and that's our core-- >> And that's your unique IP. >> Indeed, it is. >> Okay so I'm seeing Amazon racing their roll out regions. They got one coming in China, one in the Middle East. That's a big part of the strategy. Does that help you or what does that do? >> Absolutely it helps us a great deal, partly because customers now do not look at their applications as a single region applications. That doesn't fly anymore. The the notion that my banking app cannot work because a data center went down is just not acceptable in the modern world anymore. The fact that we depend so much on the services means they need to be up all the time. More regions, more data replication. That's why we step in. >> So that sounds like a lot of symbiosis here. You talk about S3 and replication challenges. So tell us how WANdisco is actually helping AWS. That's one example but help you us understand the symbiosis with your relationship with AWS. >> The best example I can give you is a large travel service company in the internet. They had to Adobe infrastructure that was growing out of control. They wanted to manage costs by moving some workloads to Amazon but didn't really know where to start, because you can't do such a thing as take a copy of the data, ship it off on a Snowball into the Cloud and tell the users of that data, stop writing to it now. It's gonna be available in the Cloud, a week, 10 days from now. Then you can start writing again. That's just not acceptable. This is live data problem. The problem here is that you need to be able to ship out your data on Snowballs, continue to write the on-premise storage. When it shows up in the Cloud, start writing that. Both are consistently replicated, you have a proper hybrid Cloud environment. So this was a great bonus to them. As for AWS, they watched this and they look at it as a easy way to move vast majority of data from on-premise big Data analytics systems. >> Have they been a fuel to your fire, in a sense that they've been on this incredible acceleration of their innovation and as Andy Joci said many times to you John. It's speed and customer focus. So how has their accelerated pace of innovation helped fuel WANdisco's so that like you were saying the unique value. How have they really ignited that? >> So they started off with just plain Snowball two years ago. Last year they announced Snowball Edge which is a pretty improved device. Now they have in the works, capability to do some compute on those boxes. That's very interesting to us. Now our services can decide on the Snowball, It arrives at a customer site. He plugs it in, turns it on instant replication capabilities Those are fueled both by Amazon's drive and extreme speed and our own capabilities. So Amazon is a wonderful partner for us partly because their charge to us innovation is quite amazing. >> Snowball, snow mobile, it's gonna be a white Christmas for you guys. Business is good. >> Business is great. >> Okay, final question. What's the conversations you're having here this year, share with us some of the quick conversations you're having in the hallways, meetings, Amazon got execs, partners. >> So most of the conversation are about moving workloads from on-premise into the Cloud. I personally am very interested in IoT use cases because I see the volume of data and the ability for us to do some interesting replications at being critical. That's where our focus is right now. >> Jugane Sundar, CTO of WANdisco. Big announcement, partnership with Amazon Web Services and Snowball replication active active. Great solution for replication. You got regions across regions. Check out WANdisco. Thanks for coming by, great to see you again. Congratulations on all your success. This is theCube, live coverage day one. It's coming down to an end. The halls open, we got two more days of packed two Cubes. Stay tuned for more, we got some great guest coming up, stay with us. (uptempo techno music)