(Upbeat music) >> Hi everyone and welcome back to the Cube's coverage of Splunk.conf 2021, virtual. We are here, live in the Splunk studios here in Silicon valley. I'm John Furrier, host of the Cube. Spiros Xanthos VP of product management of observability with Splunk is here inside the cube, Spiros, thanks for coming on. Great to see you. [Spiros Xanthos]- John, thanks for having me glad to be here. >> We love observability. Of course we love Kubernetes, but that was before observability became popular. We've been covering cube-con since it was invented even before, during the OpenStack days, a lot of open source momentum with you guys with observability and also in the customer base. So I want to thank you for coming on. Give us the update. What is the observability story its clearly in the headlines of all the stories SiliconANGLE's headline is multi-cloud observability security Splunk doubling down on all three. >> Correct. >> Big part of the story is observability. >> Correct. And you mentioned CubeCon. I was there last week as well. It seems that those observability and security are the two most common buzzwords you hear these days different from how it was when we started it. But yeah, Splank actually has made the huge investment in observability, starting with the acquisition of Victor ops three years ago, and then with Omnition and Signalfx. And last year with Plumbr synthetics company called Rigor and Flowmill and a network monitoring company. And plus a lot of organic investment we've made over the last two years to essentially build an end-to-end observability platform that brings together metrics, traces, and logs, or otherwise infrastructure monitoring, log analytics, application monitoring. Visual experience monitoring all in one platform to monitor let's say traditional legacy and modern cloud native apps. >> For the folks that know SiliconANGLE, the Cube know we've been really following this from the beginning for signal effects, remember when they started they never changed their course. they've had the right They have the right history and from spot by spot, you guys, same way open source and cloud was poo-pooed upon, people went like, oh, it's not secure, they never were. Now it's the center of all the action. [Spiros Xanthos]- Yes >> And so that's really cool. And thanks for doing that. The other thing I want to get your point on is what does end-to-end observability mean? Because there's a lot of observability companies out there right now saying, Hey, we're the solution We're the utility, we're the tool, but I haven't seen a platform. So what's your answer to that? >> Yes. So observability, in my opinion, in the context of what you're describing means two things. One is that when, when we say internal durability, it means that instead of having, let's say multiple monitoring tools that are silent, let's say one for monitoring network, one for monitoring infrastructure, a separate one for monitoring APM that do not work with each other. We bring all of these telemetry in one place we connect it and exactly because actually applications and infrastructure themselves are becoming one. You have a way to monitor all of it from one place. So that's observability. But the other thing that observability also is because these environments tend to be a lot more complex. It's not just about connecting them, right? It's also about having enough data and enough analytics to be able to make sense out of those environments and solve problems faster than you could do in the past with traditional monitoring. >> That's a great definition. I've got to then ask you one of the things coming up that came out of CoopCon was clear, is that the personnel to hire, to run this stuff, it's not everyone can get the skills gap problem. At the same time, automation is at an all time high people are automating and doing AI ops, get outs. What do you want to call this a buzz word for that basically automating the data observability into the CICB pipeline, huge trend right now. And the speed of developers is fast now. They're coding fast. They don't want to wait. >> I agree. So, and that's exactly what's happening, right? We want essentially from traditional IT where developers would develop something a little bit deployed months later by some IT professional, of course, all of this coming together, But we're not stopping that as you say, right, that the shifting left is going earlier into the pipeline. Everyone expect, essentially let's say monitoring to happen at the speed of deployment. And I guess observability again, is this not, as a requirement. Observability is this idea. Let's say that I should be able to monitor my applications in real time and, you know, get information as soon as something happens. >> With the evolution of the shift left trend. I would say for the people don't know what shift left is you put security the beginning, not bolted on at the end and developers can do it with automation, all that good stuff that they have. But how, how real is that right now in terms of it happening? Can you, can you share some vision and ideas and anecdotal data on how, how fast shift left is, or is there still bottlenecks and security groups and IT groups? >> So there are bottlenecks for sure. In my opinion, we are aware with, let's say the shift left or the dev sec ops trend, whether IT and devs maybe a few years ago. And this is both a cultural evolution that has to happen. So security teams and developers have to come closer together, understand like, say the consensus of the requirements of each other so they can work better together the way it happened with DevOps and all sorts of tooling problem, right? Like still observability or monitoring solutions are not working very well with security yet. We at Splunk of course, make this a priority. And we have the platform to integrate all the data in one place. But I don't think is generally something that we'll have achieved as well as an industry yet. And including the cultural aspects of it. >> Is that why you think end to end is important to hit that piece there so that people feel like it's all working together >> I think end to end is important for two reasons. actually one is that essentially, as you say, you hit all the pieces from the point of deployment, let's say all the way to production, but it's also because I think applications and infrastructure, FMLA infrastructure with Kubernetes, microservices are in traditional so much more complexity that you need to step function improvement in the tooling as well. Right? So that you need keep up with the complexity. So bringing everything together and applying analytics on top is the way essentially to have this step function improvement in how your monitoring solution works so that it can keep up with the complexity of the underlying infrastructure and application. >> That is a huge, huge points Spiros. I got to double down on that with you and say, let's expand that because that's the number one problem, taming the complexity without slowing down. Right? So what is the best practice for that? What do people do? Cause, I mean, I know it's evolving, it's going faster than that, but it's still getting better, but not always there, but what can people do to go faster? >> So, and I will add that it's even more complex than just what the cloud, let's say, native applications introduced because especially large enterprises have to maintain their routine, that on-prem footprint legacy applications that are still in production and then still expand. So it's additive to what they have today, right? If somebody was to start from a clean slate, let's say started with Kubernetes today, maybe yes, we have the cloud native tooling to monitor that, but that's not the reality of most, most enterprises out there. Right? So I think our goal at Splunk at least is to be able to essentially work with our customers through their digital, digital transformation and cloud journey. So to be able to support all their existing applications, but also help them bring those to the cloud and develop new applications in a cloud native fashion, let's say, and we have the tooling, I think, to support all of that, right between let's say our original data platform and our metrics and traces platform that we develop further. >> That's awesome. And then one quick question on the customer side, if I'm a customer, I want observability, I want this, I want everything you just said. How do I tell the difference between a pretender and a player, the good solution and a bad solution? What are the signals that this is the real deal, that's a fake product >> Agreed. So, I mean, everyone obviously believes that original (laughing) I'm not sure if I will. >> You don't want to name names? Here's my, my perspective on what truly is a requirement for absorb-ability right? First of all, I think we have moved past the time where let's say proprietary instrumentation and data collection was a differentiator. In fact, it actually is a problem today, if you are deploying that because it creates silos, right? If I have a proprietary instrumentation approach for my application, that data cannot be connected to my infrastructure or my logs, let's say, right. So that's why we believe open telemetry is the future. And we start there in terms of data collection. Once we standardize, let's say data collection, then the problem moves to analytics. And that's, I think where the future is, right? So observability is not just about collecting a bunch of data and that bring it back to the user. It's about making sense out of this data, right? So the name of the game is analytics and machine learning on top of the data. And of course the more data you can collect, the better it is from that perspective. And of course, then when we're talking about enterprises, scale controls, compliance all of these matter. And I think real time matters a lot as well, right? We cannot be alerting people after minutes of a problem that has happened, but within a few seconds, if we wanted to really be pro-active. >> I think one thing I like to throw out there, maybe get your reaction to it, I think maybe one other thing might be enabling the customer to code on top of it, because I think trying to own the vertical stack as well as is also risky as a vendor to sell to a company, having the ability to add programming ability on top of it. >> I completely agree actually, You do? In general giving more control to the users and how, what do they do with their data, let's say, right? And even allowing them to use open source, whatever is appropriate for them, right? In combination, maybe with a vendor solution when they don't want to invest themselves. >> Build their own apps, build your own experience. That's the way the world works. That's software. >> I agree. And again, Splunk from the beginning was about that, right? Like we'll have thousands of apps built ontop of our platform >> Awesome. Well, I want to talk about open source and the work you're doing with open telemetry. I think that's super important. Again, go back even five, 10 years ago. Oh my God. The cloud's not secure. Oh my God, open source has got security holes. It turns out it's actually the opposite now. So, you know finally through the people woke up. No, but it's gotten better. So take us through the open telemetry and what you guys are doing with that. >> Yes. So first of all, my belief, my personal belief is that if there is no future where infrastructure is anything about open source, right? Because people do not trust actually close our solutions in terms of security. They prefer open source at this point. So I think that's the future. And in that sense, a few years ago, I guess our belief was that all data collection instrumentations with standards based first of all, so that the users have control and second should be open source. That's why we, at Omnition the company I co-founded that was acquired by Splunk. We we're one of the main tenders of open sensors and that we brought together open sensors and OpenTracing in creating open telemetry. And now , Open telemetry is pretty much the de facto. Every vendor supports it, its the second most active project in CNCF. And I think it's the future, right? Both because it frees up the data and breaks up the silos, but also because, has support from all the vendors. It's impossible for any single vendor to keep up with all this complexity and compete with the entire industry when we all come together. So I think it's a great success it's I guess, kudos to everybody, kudos to CNCF as well, that was able to actually create and some others. >> And props to CNCF. Yeah. CNC has done an amazing job and been going to all those events all the years and all the innovations has been phenomenal. I got to ask what the silos, since you brought it up, come multiple times. And again, I think this is important just to kind of put an exclamation point on, machine learning is based upon data. Okay. If you have silos, you have the high risk of having bad machine learning. >> Yes. >> Okay. That's you agree with that? >> Completely. >> So customers, they kind of understand this, right. If you have silos that equals bad future >> Correct >> because machine learning is baked into everything now. >> And I will add to that. So silos is the one problem, and then not being able to have all the data is another problem, right? When it comes to being able to make sense out of it. So we're big believers in what we call full fidelity. So being able to connect every byte of data and do it in a way that makes sense, obviously economically for the customer, but also have, let's say high signal to noise ratio, right? By structuring the data at the source. Overt telemetry is another contributor to that. And by collecting all the data and by having an ability, let's say to connect the data together, metrics, traces, logs, events, incidents, then we can actually build a little more effective tooling on top to provide answers back to the user with high confidence. So then users can start trusting the answers as opposed to they themselves, always having to figure out what the problem is. And I think that's the future. And we're just starting. >> Spiros I want to ask you now, my final question is about culture And you know, when you have scale with the cloud and data, goodness, where you have people actually know the value of data and they incorporate into their application, you have advantages. You have competitive advantages in some cases, but developers were just coding love dev ops because it's infrastructure as code. They don't have to get into the weeds and do the under the hood, datas have that same phenomenon right now where people want access to data. But there's certain departments like security departments and IT groups holding back and slowing down the developers who are waiting days and weeks when they want it in minutes and seconds for have these kinds of things. So the trend is, well there's, first of all, there's the culture of people aren't getting along and they're hating each other or they're not liking each other. >> Yes >> There's a little conflict, always kind of been there, but now more than ever, because why wait? >> I agree. >> How can companies shorten that cycle? Make it more cohesive, still decouple the groups because you've got, you got compliance. How do you maximize the best of a good security group, a good IT group and enables as fast as possible developers. >> I agree with you, by the way, this is primarily cultural. And then of course there is a tooling gap as well. Right. But I think we have to understand, let's say as a security group, instead of developers, what are the needs of each other, right. Why we're doing the things we're doing because everybody has the right intentions to some extent, right? But the truth is there is pain. We are me and myself. Like as we develop our own solutions in a cloud native fashion, we see that right. We want to move as fast as possible, but at the same time, want to be compliant and secure, right. And we cannot compromise actually on security or compliance. I mean, that's really the wrong solution here. So I think we need to come together, understand what each other is trying to do and provide. And actually we need to build better tooling that doesn't get into the way. Today, oftentimes it's painful to have, let's say a compliance solution or a secure solution because it slows down development. I think we need to actually, again, maybe a step function improvement in the type of tooling we'll have in this space. So it doesn't get into the way Right? It does the work it provides. Let's say the security, the security team requires, it provides the guarantees there, but doesn't get in the way of developers. And today it doesn't happen like this most of the time. So we have some ways to go. >> And Garth has mentioning how you guys got some machine learning around different products is one policy kind of give some, you know, open, you know, guardrails for the developers to bounce around and do things until they, until they have to put a new policy in place. Is that an answer automated with automation? >> Big time. Automation is a big part of the answer, right? I think we need to have tooling that first of all works quickly and provides the answers we need. And we'll have to have a way to verify that the answer are in place without slowing down developers.Splunk is, I mean, out of a utility of DevSecOps in particular is around that, right? That we need to do it in a way that doesn't get in the way of, of let's say the developer and the velocity at which they're trying to move, but also at the same time, collect all the data and make sure, you know, we know what's going on in the environment. >> Is AI ops and dev sec ops and GET ops all the same thing in your mind, or is it all just labels >> It's not necessarily the same thing because I think AI ops, in my opinion applies, let's say to even more traditional environments, what are you going to automate? Let's say IT workflows in like legacy applications and infrastructure. Getops in my mind is maybe the equivalent when you're talking about like cloud native solutions, but as a concept, potentially they are very close I guess. >> Well, great stuff. Great insight. Thanks for coming on the Cube. Final point is what's your take this year of the live we're in person, but it's virtual, we're streaming out. It's kind of a hybrid media environment. Splunk's now in the media business with the studios, everything great announcements. What's your takeaway from the keynote this week? What's your, you got to share to the audience, this week's summary. >> First of all, I really hope next year, we're all going to be in one place, but still given the limitations we had I think it was a great production and thanks to everybody who was involved. So my key takeaway is that we truly actually have moved to the data age and data is at the heart of everything we do. Right? And I think Splunk has always been that as a company, but I think we ourselves really embraced that and everything we do is everything. Most of the problems we solve are data problems, whether it's security, observability, DevSecOps, et cetera. So. >> Yeah, and I would say, I would add to that by saying that my observations during the pandemic now we're coming, hopefully to the end of it, you guys have been continuing to ship code and with real, not vaporware real product, the demos were real. And then the success on the open source. Congratulations. >> Thank you. >> All right. Thanks for coming on and we appreciate it >> Thanks alot _Cube coverage here at dot com Splunk annual conference. Virtual is the Cube. We're here live at the studios here at Splunk studios for their event. I'm John Farrow with the Cube. Thanks for watching. (joyful tune)

>> Narrator: From theCUBE studios in Palo Alto in Boston connecting with that leaders all around the world, this is a CUBE Conversation. >> Hello and welcome to this special CUBE Conversation. I'm John Furrier, your host. We're here for a special series, Leading with Observability, and this segment is: End-to-end observability drives great digital experiences. We've got a great guest here, Craig Hyde, senior director of product management for Splunk. Craig, great to see you. Thanks for coming on. >> And thanks for having me. This is great. >> So this series, Leading with Observability is a super hot topic obviously with cloud native. In the pandemic, COVID-19 has really kind of shown cloud native trend has been a tailwind for people who invested in it, who have been architecting for cloud on premises where data is a key part of that value proposition and then there's people who haven't been doing it. So, and out of this trend, the word observability has become a hot segment. And for us insiders in the industry, we know observability is just kind of network management on steroids in the cloud, so it's about data and all this. But at the end of the day, there's value that's enabled from observability. So I want to talk to you about that value that's enabled in the experience of the end user whether it's in a modern application or user inside the enterprise. Tell us what you think about this end user perspective. >> Sure, yeah thanks a lot for that intro. And I would actually argue that observability wouldn't even just be machine data or network data, it's more of a broader context where you can see everything that's going on inside the application and the digital user experience. From a user experience or a digital experience management perspective, I believe the metrics that you pull from such a thing are the most useful and ubiquitous metrics that you have and visibility in all of technology. And when done right, it can tell you what the actual end result of all this technology that you're piecing together, the end result of what's getting delivered to the user, both quantitatively and qualitatively. So, my background, I actually started a company in this domain. It was called Rigor and we focused purely on looking at user experience and digital experience. And the idea was that, you know, this was 10 years ago, we were just thinking, look, 10 years from now, more and more people are going to do business digitally, they're going to work more digitally and at the same time we saw the legacy data centers being shut down and things were moving to the cloud. So we said, look, the future is in the users, and where it all comes together is on the user's desktop or on their phone, and so we set out to focus specifically on that space. Fast forward 10 years, we're now a part of Splunk and we're really excited to bolt this onto an overall observability strategy. You know, I believe that it's becoming more and more popular, like you said, with the pandemic and COVID-19, it was already on a tear from a digital perspective, the adoption was going through the roof and people were doing more and more remote, they were buying more and more offline, but the pandemic has just pushed it through the roof. And I mean, wow, like the digital business genie's out of the bottle and there's no putting it back now. But, you know, there's also other things that are driving the need for this and the importance of it and part of it comes with the way technology is growing. It's becoming much more complex in terms of moving parts. Where an app used to be run off three different tiers in a data center, now it could be across hundreds of machines and opaque networks, opaque data centers all over the world, and the only time you often see things, how they come together, is on the user's desktop. And so that's where we really think you got to start from the user experience and work back. And, you know, all the drive in computing is all about making things better, faster and cheaper, but without this context of the user, often the customer and the experience gets left out from reaping the rewards from all these gains. So that's sort of like encapsulates my overall view of the space and why we got into it and why I'm so excited about it. >> Well Craig, I got to ask on a personal level. I mean, you look at what happened with the pandemic, I mean, you're a pioneer, you had a vision. Folks that are on the entrepreneurial side say, hey digital businesses is coming and they get it and it's slowly gets known in the real world, becomes more certain, but with the pandemic, it just happened all of a sudden so fast for everybody because everyone's impacted. Teachers, students, families, work, everyone's at home. So the entire user experience was impacted in the entire world. What was going through your mind when you saw all this happening and you see the winners obviously were people had invested in cloud native and data-driven technologies, what was your take on all this when you saw this coming? >> Well, the overall trend has been going on for decades, right? And so the direction of it isn't that surprising, but the magnitude and the acceleration, there's some stats out there from Forbes where the e-commerce adoption doubled within the first six months of the pandemic. So we're talking, you know, 10, 12 years of things ticking up and then within six months, a doubling of the adoption of e-commerce. And so like anybody else, you first freeze and say, what does this mean? But when people start working remote and people start ordering things from Amazon and all the other websites, it's quick to see like, aha! It no longer matters what chairs somebody is sitting in when they're doing work or that they're close to a store and you have a physical storefront when you're trying to buy something, it's all about that digital experience and it needs to be ubiquitous. So it's been interesting to see the change over the past few months for sure. But again, it doesn't change the trend, it just magnified it and I don't see it going back anytime soon. >> Yeah I mean, digital transformation has always been a buzz word that everyone kind of uses as a way to kind of talk about the big picture. >> Right. >> It's actually transforming and there's also share shifts that happen in every transformation, in any market shift. Obviously that's happening with cloud. Cloud native edge is becoming super important. In all of these, and by the way, in all the applications that sit on that infrastructure which is now infrastructure as code, has a data requirement that observability piece becomes super critical, not just from identifying and resolving, but also for training machine learning and AI, right? So, again, you have this new flywheel observability that's really at the heart of digital transformation. What should companies think about when they associate observability to digital transformation as they're sitting around whether they're CXOs or CSOs or solution architects going, okay, how does observability plug into my plans? >> Yeah, absolutely. I mean, my recommendation and the approach that I would take is that you want to start with the end in mind and it's all about how you set your goals when you're setting out in getting into digital transformation. And, you know, the late Steve Jobs, to borrow one of his quotes, he said that you have to start with the customer experience in mind and work backwards to the technology. And so I think that applies when you get into an observability strategy. So without understanding what the actual user experience is, you don't have a good enough yardstick to go out there and start working towards. So availability on a server or CPU time or transaction time in a database, like, those are all great, but without the context of what is the goal you're actually going after, it's kind of useless. So, like I said, it's not uptime, it's not server time, it's not any of that stuff, and it's user experience and these things are different. So they're like visual metrics, right? So what a user sees, because all kinds of things are going on in the background, but if it can see that the person can see and their experience is that they're getting some kind of response from the machine, then that's how you measure where the end point is and what the overall goal is. And so like to keep kind of going on with that, it's like you start with the end in mind, you use that end to set your goals, you use that domain and that visibility to troubleshoot faster. So when the calls start rolling in then they say, hey, I'm stuck at home and I'm on a slow internet connection, I can't get on the app and core IT is taking a phone call, You can quickly look and instrument that user and see exactly what they're seeing. So when you're troubleshooting, you're looking at the data from their perspective and then working backwards to the technology. >> That's super exciting. I want to get your thoughts on that. So just to double down on that because I think this highlights the trend that we were just talking about. But I'll break it down into three areas that I see happening in the marketplace. Number one, availability and performance. That's on everyone's mind. You just hit that, right? Number two, integrations. There's more integrations going on within platforms or tools or systems, whether it's an API over here, people are working together digitally, right? And you're seeing e-commerce. And third is the user patterns and the expectations are changing. So when you unpack those kinds of like trends, there's features of observability underneath each. Could you talk about that because I think that seems to be the common pattern that I'm seeing? Okay, high availability, okay, check. Everyone has to have that. Almost table stakes. But it's hard when you're scaling, right? And then integrations, all kinds of API is being slinged around. You've got microservices, you've got Kubernetes, people are integrating data flows, control planes, whatever, and then finally users. They want new things. New patterns emerge, which is new data. >> Yeah, absolutely. And to just kind of talk about that, it reminds me of like a Maslow's hierarchy of needs of visibility, right? Like, okay, the machine is on, check. Like you said, it's table stakes, make sure it's up and running. That's great. Then you want to see sort of the applications that are running on the machine, how they're talking to each other, are other components that you're making API calls to, are they timing out or are they breaking things? And so you get that visibility of like, okay, they're on, what's going on top of those machines are inside of them or in the containers or the virtual machines or whatever segment of computing that you're looking at, And then that cherry on top, the highest point is like, how is that stack of technology serving your customer? How's it serving the user and what's the experience? So those are sort of the three levels that we kind of look at when we're thinking of user experience. And so, it's a different way to look at it, but it's sort of the way that kind of we see the world is that three tier, that three layer cake. >> It's interesting. >> And you need all the layers. >> It's super relevant. And again, it's better together, but you can mix and match and have product in there. So I want to get into the Splunk solution. You guys have the digital experience monitoring solution. Can you explain what that is and how that fits into all this and what's in it for the customers, what's the benefit? >> Right, sure. So with the digital experience monitoring and the platform that we have, we're giving people the ability to basically do what I was talking about, where it enables you to take a look at what the user's experience are and pull metrics and then correlate them from the user all the way through the technical journey to the back end, through the different tiers of the application and so on. So that technology is called real user monitoring where we instrument the users. And then we also layer in synthetic monitoring which is the sort of robot users that are always on for when you're in lower level environments and you want to see, you know, what experience is going to look like when you push out new software, or when nobody's on the application, did something break? So a couple of those two together and then we feed that into our overall observability platform that's fed with machine data, we have all the metrics from all the components that you're looking at in that single pane of glass. And the idea is that we're also bringing you not only just the metrics and the events from logs and all the happenings, but we're also trying to help tease out some of these problems for you. So many problems that happen in technology have happened before, and we've got a catalog with our optimization platform of 300 plus things that go wrong when webpages or web applications or API calls start acting funky. And so we can provide, based on our intelligence that's built into the platform, basically run books for people to fix things faster and build those playbooks into the release process so you don't break the applications to begin with and you can set flags to where people understand what performance is before when it's being delivered to the customer, and if there are problems, let's fix them before we break the experience and lose the trust of the user. So again, it's the metrics from the stats that are coming across the wire of everything all the way to the users, it's the events from the logs that are coming in so you can see context, and then it's that user experience, it's a trace level data from where you can double click into each of the tiers and say, like, what's going on in here? What's going on in the browser? What's going on in the application? What's going on in the backend? And so you can sort of pool all that together in a single pane of glass and find problems faster, fix them faster and prevent users from having problems to begin with. And to do this properly, you really need it all under one roof and so that's why we're so excited to bring this all together. >> Yeah, I've been sitting on theCUBE for 10 years now. We've been 11 years, on our 11th year doing theCUBE. Digital you can measure everything. So why not? There should be no debate if done properly. So that brings up this whole concept that you guys are talking about full fidelity. Can you just take a minute to explain what that is? What is full fidelity mean? >> Sure, you know, full fidelity really comes down to a lot about these traces. So when we talk about metrics, logs and traces, it's all about getting all the activity that goes on in an application and looking at it. So when you or I interact with our company's app online and there's problems, that the person who's going to fix this problem, they can actually see specifically me. They can look at my experience and look at what it would look like in my browser, you know, what were all the services that I was interacting with and what was going on in the application, what code was being called, what services were being called, and look at specifically me as opposed to an aggregate of all the domains all put together. And it really is important from a troubleshooting standpoint. It's really important from an understanding of the actuals because without full fidelity and capturing all of the data, you're kind of going, you know, you're taking guesses and it eliminates a lot of the guesswork. And so that's something that's special with our platform is that ability to have the full fidelity. >> When does a client, a customer not have full fidelity? I might think I have it, someone sold me a product, What's the tell sign that I don't have full fidelity? >> Oh yeah, well with observability, there's a lot of tricks in the game. And so you see a lot of summary data that looks like, hey, this is that one call, but usually it's knitted together from a bunch of different calls. So that summary data just from, because this stuff takes up a lot of storage and there's a lot of problems with scale, and so when you might see something that looks like it's this call, it's actually like, in general, when a call like this happens, this is what it looks like. And so you've got to say like, is this the exact call? And, you know, it makes a big difference from a troubleshooting perspective and it's really hard to implement and that's something that Splunk's very good at, right? It's data at scale. It's the 800 pound gorilla in collecting and slicing apart machine data. So like, you have to have something of that scale in order to ingest all this information. It's a hard problem for sure. >> Yeah, totally. And I appreciate that. While I got you here, you're an expert, I got to ask you about Open Telemetry. We've heard that term kicked around. What does that mean? Is it an open source thing, is it an open framework? What is Open Telemetry and what does it mean for your customers or the marketplace? >> Yeah, I think of Open Telemetry as finally creating a standard for how we're collecting data from applications across AP- In the past, it's been onesie-twosie, here and there each company coming up with it themselves and there are never any standards of how to look at transactions across data, across applications and across tiers. And so Open Telemetry is the attempt and it's a consortium, so there's many people involved in pushing this together, but think of like a W3C, which creates the standards for how websites operate, and without it, the web wouldn't be what it is today. And now Open Telemetry is coming behind and doing that same thing from an observability standpoint. So you're not just totally locked into one vendor in the way that they do it and you're held hostage to only looking at that visibility. We're trying to set the standards to lower the barrier of entry into getting to application performance monitoring, network performance monitoring and just getting that telemetry where there are standards across the board. And so it's an open source project. We commit to it, and it's a really important project for observability in general. >> So does that speak to like, the whole more data you have, the less blind spots you might have? Is that the same concept? Is that some of the thinking behind this? >> It enables you to get more data faster. Now, if you think about, if there are no standards and there are no rules on the road and everybody can get on the road and they can decide if they want to drive in the left lane or the right lane today, it makes getting places a lot harder. And the same is true with Open Telemetry. without the standards of what, you know, the naming conventions, where you instrument, how you instrument, it becomes very hard to put some things in a single pane of glass because they just look differently everywhere. And so that's the idea behind it. >> Well Craig, great to have you on. You're super smart on this, and Leading with Observability, it's a hot topic. It's super cool and relevant right now with digital transformation as companies are looking to rearchitect and change how they're going to flip the script on software development, modern applications, modern infrastructure, edge, all of this is on top of mind of everyone's thing on their plans. And we certainly want to have you back in some of our conversations that we have around this on our editorial side as well with when we have these clubhouses we are going to start doing a lot of those. We definitely want to bring you in. I'll give you a final word here. Tell us what you're most excited about. Put the commercial for Splunk. Why Splunk? Why you guys are excited. Take a minute to get the plug in. >> It's so easy. Splunk has the base to make this possible. Splunk is, like I said, it's an 800 pound gorilla in machine data and taking in data at scale. And when you start going off into the observability abyss, the really, really hard part about it is having the scale to not only go broad in the levels of technology that you can collect, but also go deep. And that depth, when we talked about that full fidelity, it's really important when you get down to brass tacks and you start implementing changes and troubleshooting things and turning that data that you have in to doing, so understanding what you can do with it. And Splunk is fully committed to going, not only broad to get everything under one roof, but also deep so that you can make all of the information that you collect actionable and useful. And it's something that I haven't seen anybody even attempt and I'm really excited to be a part of building towards that vision. >> Well, I've been covering Splunk for, man, many, many years. 10 years plus, I think, since it's been founded, and really the growth and the vision and the mission still is the same. Leveraging data, making use of it, unlocking the power of data as it evolves and there's more of it. And it gets more complicated when data is involved in the user experience end-to-end from cybersecurity to user flows and new expectations. So congratulations. Great product. Thanks for coming on and sharing. >> Thanks again for having us. >> Okay, this is John Furrier in theCUBE. Leading with Observability is the theme of this series and this topic was End-to-end observability to enable great digital experiences. Thanks for watching. (lighthearted music)

live from San Francisco it's the cube covering micron insight 2018 brought to you by micron welcome back to the San Francisco Bay everybody we saw the Sun rise in the bay this morning of an hour so we're gonna see the Sun set this gorgeous setting here at Pier 27 Nob Hills up there the Golden Gate Bridge over there and of course we have this gorgeous view of the bay you're watching the cube the leader in live tech coverage we're covering micron insight 2018 ai accelerating intelligence a lot of talk on on on memory and storage but a lot more talk around the future of AI so we got a great discussion here on the auto business and how AI is powering that business Jeff Bader is here is the corporate vice president and general manager of the embedded business unit at micron good to see you again Jeff thanks for coming on and Simon and rigor is the vice president BMW and he's also joined by Vijay Nadkarni who was the global head of AI and augmented reality at Visteon which is a supplier to Automobile Manufacturers gentlemen welcome to the cube thanks so much for coming on thank you so you guys had a panel earlier today which was pretty extensive and just a lot of talk about AI how AI will be a platform for interacting with the vehicle the consumer the driver interacting with the vehicle also talked a lot about autonomous vehicles but Simon watch you kick it off your role at BMW let's let's just start there it will do the same for Vijay and then get into it research portion that we do globally in which is represented here in North America and so obviously we're working on autonomous vehicles as well as integrating assistance into the car and basically what we're trying to do is to get use AI as much as possible in all of the behavioral parts of the vehicle that uses have an expectations towards being more personalized and having a personalized experience whereas we have a solid portion of the vehicle is going to be as a deterministic anesthetic as we have it before like all of the safety aspects for example and that is what we're working on here right now Vijay Visteon is a supplier to BMW and other auto manufacturers yes we are a tier 1 supplier so we basically don't make cars but we supply auto manufacturers of which BMW is one and my role is essentially AI technology adversity on and also augmented reality so in AI there are basically two segments that we cater to and one of them is that almost driving which is fully our biggest segment and the second one is infotainment and in that the whole idea is to give the driver a better experience in the car by way of recommendations or productivity improvements and such so that is so my team basically develops the technology and then we centrally integrate that into our products so so not necessarily self-driving it's really more about the experience inside the vehicle that is the and then on the autonomous driving side we of course very much are involved with the autonomous driving technology which is tested with detecting objects are also making the proper maneuvers for the Waker and we're definitely going to talk about that now Jeff you sell to the embedded industry of fooding automobile manufacturers we hear that cars have I forget the number of microprocessors but there's also a lot of memory and storage associate yeah I mean if you follow the chain you have our simon representing the OEMs Vijay represented the Tier one suppliers were supplier to those Tier one suppliers in essence right so so we're providing memory and storage that then goes in to the car in as you said across all of the different sort of control and engine drone and computing units within the car in particular into that infotainment application and increasingly into the a TAS or advanced driver assistance systems that are leading toward autonomous driving so there's a lot of AI or some AI anyway in vehicles today right presumably yeah affected David who did a wonderful job on the panel he was outstanding but he kind of got caught up in having multiple systems like a like an apple carplay your own system I actually have a bit about kind of a BMW have a mini because I'm afraid it's gonna be self-driving cars and I just want to drive a drive on car for this take it away from me though but but you push a button if you want to talk to a Syrian yeah push another button if you want to talk to the mini I mean it's it's gonna use it for different use cases right exactly may I is also about adaption and is also about integrating so AI is is is coming with you with the devices that you have with you anyway right so your might be an Alexa user rather than a Google assistant user and you would have that expectation to be able to ask to chat with your Alexa in your car as well that's why we have them in the vehicle also we have an own voice assistant that we recently launched in Paris Motorshow which augments the experience that you have with your own assistants because it factors in all of the things you can do with the car so you can say there is a solid portion of AI already in the vehicle it's mainly visible in the infotainment section right and of course I remember the first time I'm sure you guys experienced to that the the car braked on my behalf and then kind of freaked me out but then I kind of liked it too and that's another form of machine intelligence well that out well that counts for you that had not that has not necessarily been done by AI because in in in let's say self-driving there is a portion of pretty deterministic rule based behavior and exactly that one like hitting an object at parking you don't need AI to determine to hit the right there is no portion or of AI necessary in order to improve that behavior whereas predicting the best driving strategy for your 20-mile ride on the highway this is where AI is really beneficial in fact I was at a conference last week in Orlando it's the Splunk show and it was a speaker from BMW talking about what you're doing in that regard yeah it's all about the data right learning about it and and in turning data into insights into better behavior yes into better expected behavior from whatever the customer wants so Vijay you were saying before that you actually provide technology for autonomous vehicles all right I got a question for you could it autonomous - could today's state of autonomous vehicles pass a driver's test no no would you let it take one no it depends I mean there are certain companies like way mo for example that do a lot but I still don't think way mo can take a proper driver's test as of today but it is of course trying to get there but what we are essentially doing is taking baby steps first and I think you may be aware of the SAE levels so level 1 level 2 level 3 level 4 SF and a 5 so we and most of the companies in the industry right now are really focusing more on the level 2 through level 4 and a few companies like Google or WAV or other and uber and such are focusing on the level 5 we actually believe that the level 2 through 4 is the market would be ready for that essentially in the shorter term whereas the level 5 will take a little while to get that so everybody Christmas and everyone we're gonna have autonomous because I'm not gonna ask you that question because there's such a spectrum of self-driving but I want to ask you the question differently and I ask each of you when do you think that driving your own car will become the exception rather than than the rule well I'd rather prefer actually to rephrase the question maybe to where not when because we're on a highway setting this question can be answered precisely in roughly two to three years the the functionality will kick in and then it's going to be the renewal of the vehicles so if you answer if you if you ask where then there is an answer within the next five years definitely if we talk about an urban downtown scenario the question when is hard to answer yeah well so my question is more of a social question it is a technology question because I'm not giving up my stick shift high example getting my 17 year old to get his permit was like kicking a bird out of the nest I did drive his permanent driver on staff basically with me right so why but I mean when I was a kid that was freedom 16 years old you racing out and there is a large generational group growing up right now that doesn't necessarily see it as a necessity right so not driving your own car I think car share services right share who bore the so and so forth are absolutely going to solve a large portion of the technology of the transportation challenge for a large portion of the population I think but I agree with the the earlier answers of it's gonna be where you're not driving as opposed to necessarily win and I think we heard today of course the you know talking about I think the number is 40,000 fatalities on the roadways in the u.s. in the u.s. yeah everybody talks about how autonomous vehicles are going to help attack that problem um but it strikes me talk about autonomous cars it why don't we have autonomous carts like in a hospital or even autonomous robots that aren't relying on lines or stripes or beacons you one would think that that would come before in our autonomous vehicle am I missing something are there are there there there systems out there that that I just haven't seen well I don't know if you've ever seen videos of Amazon distribution centers yeah but they're there they're going to school on lines and beacons and they are they're not really autonomous yeah that's fair that's fair yeah so will we see autonomous carts before we see autonomous cars I think it's a question what problem that solves necessarily yeah it's just as easy for them to know where something is yeah you think about microns fabs every one of our fabs is is completely automated as a material handling system that runs up and down around the ceilings handling all the wafers and all the cartridges the wafers moving it from one tool to the next tool to the next tool there's not people anymore carrying that around or even robots on the floor right but it's a guided track system that only can go to certain you know certain places well the last speaker today ii was talking about it I remember when robots couldn't climb stairs and now they can do backflips and you know you think about the list of things that humans can do that computers can't do it let's get smaller and smaller every year so it's kind of scary to think about one hand is that does the does the concept of Byzantine fault-tolerance you guys familiar with that does that does that come into play here you guys know what that's about I don't know what it is exactly so that's a problem and I first read about it with it's the Byzantine general problem if you have nine generals for one Oh attack for one retreat and the ninth sends a message to half to retreat or not and then you don't have the full force of the attack so the concept is if you're in a self-driving boat within the vehicle and within the ecosystem around the city then you're collectively solving the problem so there these are challenging math that need to be worked out and and I'm not saying I'm a skeptic but I just wanted more I read about it the more hurdles we have there's some isolated examples of where AI I think fits really well and is gonna solve problems today but this singularity of vehicle seems to be we have a highly regulated environment obviously public transportation or public roads right are a highly regulated environment so it's like it's different than curating playlists or whatever right this is not so much regulated traffic and legislation isn't there yet so especially and it's it's designed for humans right traffic cars roads are designed for human to use them and so the adoption to they the design of any legislation any public infrastructure would be completely different if we didn't drive as humans but we have it we have machines drive them so why are robots and carts not coming because the infrastructure really is designed for humans and so I think that's what's going to be the ultimate slow down is how fast we as a society that comes up with legislation with acceptance of behavioral aspects that are driven by AI on how fast we adopt it technically I think it can happen faster than yeah yeah it's not a technology problem as much as it is the public policy insurance companies think about one of the eventually you can think of from from let's say even level four capable car on a highway is platooning yeah right instead of having X number of car lengths to the turn fryer you just stack them up and they're all going on in a row that sounds great until Joe Blow with their 20 year old Honda you know starts to pull into that Lane right so you either say this Lane is not allowed for that or you create special infrastructure essentially that isn't designed for humans there is more designed specifically for the for the machine driven car right how big is this market it's it feels like it's enormous I don't know how do you look at the tan we can talk to the memory I can talk the memory storage part of it right but today memory and storage all of memory storage for automotive is about a two and a half billion dollar market that is gonna triple in the next three years and probably beyond that my visibility is not so good maybe yours is better for sure but it then really driven by adoption rate and how fast that starts to penetrate through the car of OAM lines and across the different car in vijay your firm is when were you formed how long you've been around or vistas be around basically since around 2001 okay we were part of relatively old spun out whiskey on that at work right okay so so alright so that's been around forever yeah for this Greenfield for you for your your group right where's the aw this is transitional right so is it is it is it you try not to get disrupted or you trying to be the disrupter or is it just all sort of incremental as a 101 year old company obviously people think about you as being ripe for disruption and I think we do quite well in terms of renewing ourselves coming from aeroplane business to a motorcycle business to garbage and so I think the answer is are we fast enough I'll be fast enough in adoption and on the other hand it's fair to say that BMW with all of its brands is part of a premium thing and so it's not into the mass transportation so everything that's going to be eaten up by something like multi occupancy vehicle mass transportation in a smaller effort right this is probably not going to hurt the premium brand so much as a typical econo type of boxy car exciting time so thanks so much for coming on the cube you got a run appreciate thank you so much okay thanks for watching everybody we are out from San Francisco you've watched the cube micron inside 2018 check out Silicon angle comm for all the published research the cube dotnet as well you'll find these videos will keep on calm for all the research thanks for watching everybody we'll see you next time you

>> Live from Las Vegas. It's the cute covering knowledge sixteen Brought to you by service. Now here your host, Dave, Alon and Jeffrey. >> Welcome back to knowledge. Sixteen. Everybody, This is the Cube, Cuba Silicon Angles Flagship program. We go out to the events and we extract the signal from the noise We're here. This is Day two for us. Will be going wall to wall for three days. That knowledge sixteen hashtag No. Sixteen. Chris Beatty is Here's the CEO. Relatively new CEO. It's service now. Chris, Thanks for coming on the Cube. It's going to be here. So you are hosting the CEO Decisions event Yesterday >> I was an event. We had a lot of CEOs, a lot of energy in the room, you know, one of the main main themes. Wass. You know, technology change happens all the time, but really one of the leadership challenge is right and what courage is required of leaders to really break through the status quo and get to that next level. We talked a lot about the importance of getting the right culture right within it, and that's a and what it really means to have a service mindset right throughout the enterprise. And as our vocabulary becomes the same inside it and across all the departments, right, as a leader, how do you enact that change so really a lot about the human element, as opposed to, you know, the technology part of it? >> Yes. So a lot of discussions over the past several service now knowledge comes in one year, Frank said. He sort of threw down the gauntlet and CEOs. They have to be business leaders. No longer Is that just a technology roll? Others have come on. The Cuban said. Well, you know, CEOs role. They gotta choose. They're gonna choose a technical path or a business path or data path. Even Chief Date officer. What do you thoughts on the >> I mean, >> there's a >> lot of press about the role. The CEO, right? And if you go back years and anything from Seo's dead, it is a relevant right. It's going the way of the dodo bird. Teo CEOs Morse strategic than ever, disrupting and creating new business models. I think the answer is somewhere in between, and it's probably changes, you know, depending on the day of the week. Right. So CEOs have a base job which is running, you know, the technology infrastructure of any company running the applications. But I do agree with Frank in terms of CEOs up, leveling their responsibilities and taking on the responsibility for more. I could tell you what I take responsibility for, right And yes, it's I t. But the overall velocity of our business. How fast can we run with everything Hiring employees, closing our books. Every single process in the company is powered by an IT platform, right? And so high tea is really in a unique position, and it has a bird's eye view of the organization to really help. Dr Velocity and Velocity is everything. How can you outflank your competition? The other thing I see think CEOs need to take responsibility for is maximizing the productivity of every single employee in the company. Right now, if you take that on, you start to look at things a little bit differently. It's not about projects, it's really about outcomes. And you know what measurable things are we delivering? And last and certainly not least, I think, the responsibility for customer experiences again. Customer experiences are powered by platform CEOs have the ability that influence every single one of those experiences and make it great and more and more as we look towards the future with things like automated bots and augmented reality customer. Your actions are going to become human to platform, and that's going to increase its relevance in that >> so and thinking about CIA imperatives of, you know, the bromide of eighty percent of the dollars we spend is on keeping the lights on twenty percent of innovation of That's a real number, No, but nobody seems to argue with it. Yeah, you >> hear that number a lot, but I think the good organizations actually do measure that number so they actually they will know what their number is and that service. Now we've done a lot of work, so our ratio is actually sixty percent run the business forty percent on innovation, and we're driving that down. So it's uneven. Fifty fifty split. I think that where you don't want to go is spending too little time on what I call the utility computing because that's the fabric that gets work done right. It's everything from networking and email and all those basic services you still need to have. Those aren't going anywhere collaboration services. >> I'd like to split it up into a little finer grain. I wonder if you could comment run the business grow the business transformed the business. Now maybe you're maybe you're always transforming your business, I don't know. But in >> terms of have to be >> in terms of but specific spending on initiatives to transform the business is that a reasonable, reasonable way to look at your portfolio was >> absolutely right. And I think if you're not doing things that transform your business, you're you're not acting with enough urgency. So my view on it is identify the big rocks right that we need to knock down, make sure we make room for those, even if it's at the cost of the grow or run part of the budget. Because if you're not getting those things done again, back to that getting left behind things were moving too quick. You got to keep pace. So make room for the transformation somehow, and that means squeezing every bit of automation that you can. How did the run part of the business, which is something I've used service now for in my past. I used to be a customer. I bought the platform twice over before I joined the company, and we did it a lot, and I'm doing it now, now that I'm at service now, >> that's one of Frank's requirements to become a CEO. I think. How >> do you >> measure that? That split. You said you're sixty today. Like to be a fifty, a lot of CEOs going. I have no idea how to measure that. I look at my projects are, but guess how do you do it? >> And it's tough we actually use. Not surprisingly, are Ownit Financial Management module to do that. And so technology's technology would we take all of our G L data and we map it to a taxonomy of business services in certain business services we know are not transformative, but they're a run part of the business, and we do that mapping once than every month. We can look at actuals against it. We can look at our unit costs, but the other begin put his projects right, which is again also in our platform, so able to look at those two things together and data driven segmentation of our spend too many times I see ninety organizations. They do it as one time exercise as part of annual planning. Then they don't look at it again until the next year. Annual planning. But there's a lot of runway in between and decisions we're making every day, which you should be making based upon data. But instead you're doing on perhaps nine months ago information. >> So you essentially categorize the business process, the business services as run or Growler training farm and on an ongoing basis. >> Absolutely. And you do the math and the most dynamic part of it, his projects. So every one of our projects, when we look at our portfolio, we look at our project portfolio by business areas, the sales marketing HR finance so on. But then we also do categorize our portfolio by Is this just sort of keep the lights on activity? But it's a project we still need to dio, or is it growing the business in somewhere? Is it truly helping us transform the way we operate >> on reasonable people? Khun, sit down and agree on sort of what those look like and >> short, and we also adjust accordingly. Also, do a top down allocation of what percentage do we want to go into each bucket, and that's not the same for each area because different parts of our business are different maturity cars, different pressures on them. I wouldn't want to be very transfer meitiv with RGL, right? That's not an area I want to innovate on. But with our sales and marketing organization, absolutely. We want to be in high innovation. Hi, experimentation, whatever we can do to help dry. >> So that's a top down bottom up exercise with the executive team says Okay, >> sideways inputs from everywhere. You know, one of the things I think CEOs it is a coming to fund CEOs to dio is manage spend. But more importantly, where people spending their time right, that's inarguably a fixed costs. We have a set of people where they spending their time and are they spending their time on the right things? And if you get that right, the rest could get a lot easier. >> So Secretary Gates last night speaking Teo, you know, maybe roughly one hundred CEOs and your your CEO decisions Conference gave the thumbs down on consensus management, and I sense just a little bit of discomfort in the room because CEOs is a hard job. But you serve a lot of different masters if you will, and as well you've got heads of application development you got, you know, architects, you got the business to serve, and so there's a lot of consensus building. And so he got questions on How do you do it? What was your reaction to that? Your colleagues, You know, which >> one was your science? They asked him a question. And because he said Consensus building doesn't work into an outside person looking in, it would seem like by nature. Everything in the government is consensus oriented. He had a lot of examples actually, where he did things against his own team's conviction, but he felt like that change was necessary. So it's two things I think Dr Gates has dealt with monumental organizations, right? Texas A and M is the smallest organization of those the CIA and the D. O D. Department of Defense has three million people, so the scale is unlike what most enterprise CEOs are leaders have seen. So when when he talked about not being consensus oriented, he viewed it as a requirement, and I actually agree with him. If you're trying to disrupt the status quo, you can't be consensus oriented. I don't think you'LL move fast enough, and most of time you won't get very far. So I think it's incumbent upon leaders to be the ones that break the status quo and say, We've got to change. And But what? What Dr Gates did describe is that if people are informed about why, from their leader enough, even if they disagree, they can get on board. And he brought up numerous examples of where he had conversations with Congress and people within the d. O d about change. He wanted to drive, and even though they were very opposed to it, they got on board because they intellectually could understand why. And over time, he won over hearts and minds >> about your priorities. So you come in relatively new tow service now. So first of all first impressions, any any surprises, pleasant or unpleasant? And what your priorities. >> So coming in no surprises. I had had a lot of admiration for the company as a customer, and now that I'm here, I love the culture. The culture is very execution oriented, get stepped on, very customer focused. You know, when we when we talk about our go to market, we really talk a lot about what's going to be most important for our customers. What pressures are customers under what problems can be solved for him? It's really not a discussion around squeezing. You know, the maximum margin out of each customer, which I think is fantastic way drive pretty hard. But but we're also very team oriented culture, so that's been great. My priorities at service. Now, when I think about my six strategic themes that I'm focused on growth eyes hugely important that service now. Right now, it's a lot of time I spend, fails and marketing effectiveness and innovation. And what can we do to drive, help, drive growth from a night perspective? Working with our partner organization, helping our partners? I do business with us easier things like partner portals and things like that. Ah, velocity. I mentioned earlier driving velocity through every department at the Enterprise at service now and really maniacally going after business process automation. And the great thing is, we have a platform that makes it easy, right and Ivax full access to that platform. So self service catalogs and knowledge base, but really going department by department saying, How do we do that? Analytics. Obviously we want to continue to measure and improve our business. But we're starting to do a lot more with Predictive Analytics, right? And how can we use data to really predict next best actions in a variety of arenas? Uh, security is the gift that keeps on giving for every CEO never ending. It's >> just one of those things that'll Teo you got, you >> got, you got to accept it and then really focus on team, right? I think talent and team and culture hugely important. You could have the best plans, you know, on paper. But if you don't have the right talent and culture within your team to get it done, I don't think you're getting very far operational. Rigor is a big one for me and a Metrix based approach to managing our business and driving outcomes. So when I look at projects that I execute for the organization on time and on budget, that's fine. That's table stakes. Really. What I'm after is on benefit, right? Are we delivering the benefits that we said we were going to get? And last, but certainly not least a part of my job is now on now. What? What we mean by now? On now is me being our best in first customer. And that's a very strategic level, working with product management to help them, you know, with roadmap features and things like that that I think all of our CEO's would need also upgrading early. So hopefully we can iron out the bugs before all of our customers and then consuming our own your products and implement it internally, learning the lessons within our four walls that we can inform our fields they could help our customers. >> How about on benefit? What percentage of projects are on benefit? That's another one of these things. Seventy percent of the projects fail. It was a number one on the market research, even >> that even that's a problem that fail is identified as not being on time or on. But right now, I view that is interesting but not compelling. Are you delivering the outcome? And so we're early. I've only been at service now six months, but I know in the past, through rigor and even making it a metric that's important have gotten to an eighty five percent hit rate on benefit. Certainly you could do better, but some of the benefits we have realised, with our platform eighty three percent increase in productivity. Leveraging R R R R application, but examples outside of Ice D, where we've eliminated forty five hundred hours of work from our financial close by putting email and manual checklist on your platform. Eighty five percent reduction in time that we spent hours spent on on boarding new employees. I mean, the list goes on and on, but it's a requirement in my organisation. When you're doing a project, you gotta have an outcome and set an aspirational outcome. Because if you talk about ten percent improvement and anything, that's sort of easy to get it. If you tell yourself I need to get a seventy percent improvement, it forces you to really rethink things and think differently. And I think that's our job. Is leaders to set those set the bar really high and then sharp teams have the resources to go after it. >> So even if you're late and over budget, if you get that, I didn't say that I later over, but I was asked, so that's got three. So that's a that's a prerequisite to be on time and on budget, >> and we're not perfect, but our target is to be ninety five percent on time, ninety five percent on budget, knowing you're gonna have five percent, you know, wiggle room and ninety five percent on benefit. >> What is on. So when you talk to the board, switch topics about security, what should be on the CEO's checklist for communicating to the board about security? So So >> I think it's really about risk, right? And what risks do we think we have? What's the likelihood of those risks? And what's the plan to mitigate those risk? I don't think security should be talked about in a This is Donner. That's done because you're never really done right. It's risk management, and the bad guys continue to innovate faster than the good guys. So what's your current security posture? What's the state of your risks and how are you mitigating them and in what time frame you know the stuff about? You know, we have a deal. P. We have ideas. We have I ps. I mean, the list of acronyms is interesting at a more tactical level, but at a board level, I think it's really risk management. >> So I promise I wanted before Ortiz talk about mitigating risk. But is there a place for a narrative that says you'd only mitigate so much? You're going to get penetrated. It's how you respond absolutely is critical. And I can I, as the CEO can lead that response or whomever is the >> appropriate person? I think you you have to do everything you possibly can Teo secure your perimeter. But it's known that you are going to get breach. Just a fact. So then it really becomes How quickly can you identify the fact that you have anomalous activity happening on your network of data? How quickly can you mitigate it? And in the past, when I was at various sign JD issue, a lot of that was manual right You have. You know, you have a piece of bad malware on the Enterprise. You may even know what assets. Um, it's on where you think you know. Usually I think you know, and then you really find out later where it's gone. But tying those assets to risk meaning what? Business services, it is it my CFO's laptop? Or is it? You know, the the you know, the person in AP. So you treated a little bit differently. And is it the infrastructure that supports our badge reader? Or is it our ear piece system? Right, So that's the missing piece. And I do thank our security organization and our our business unit, Shawn, because they've actually built a solution. Help solve that where you can go from security incident. Piece of Alberto Asset to Business service to employ within minutes, which that used to be half a day, at least half a day is a long time in a security incident. >> Yeah, so there's that magic number of whatever it is two hundred five days to detect a penetration? Yes, very. Do you feel like your organization can compress that? Is that a viable metric to be focused on? >> It's certainly a viable metric to focus on in terms of knowledge, off again anomalous activity. I don't think we're near two hundred five days, but absolutely we are focused on it because we need to secure not only our data but the data that our customers in trust without trust, >> meaning you feel as though you could detect much in a much shorter time frame, and they have some interesting. You haven't depending >> on the wrist right? Without getting into a lot of the details. >> Yeah, So we'll see you. But implicit in that is that you have a sense of the value of your data, your assets your I p what you're saying you've got a pretty good visibility on. >> Is that right? Yeah, we d'Oh. We spent a lot of time making sure our security posture is solid again customers and trust us with their data. We take that responsibility very seriously. >> Not speaking for service now, but just general knowledge of your colleagues Do you feel as though the lack of ability to value data assets negatively affect people's ability? T appropriately spend resources >> on security? It's tough because one of the first things you need to do in security say, what do I need to secure first? And then you say, OK, well, that's my core. I pee. Where's my core I pee stored? I would argue that a lot of companies don't even know because it's scattered on different file shares and different servers, and then you don't know whether people are putting it on box or drop box or one of the many storied sites out there so keep key. First step, I think for a lot of organizations is really just getting a handle on where their I P is. >> Right? All right, Count Chris, Thank you very much. Appreciate you coming on last. Give the last word. Uh, knowledge sixteen for you. What's the kind of bumper sticker? Is the truck's pulling away from its been awesome. I mean, >> just talking with customers and fellow CEOs. You know, we're all in this journey together towards this service enabled enterprise, but it is about leadership and just courage to bust through this current status quo that were in within the enterprise to get to that next level of efficiency. >> Thanks a lot of fun. Well, congratulations on the new role on DH hosting at a hostel conference just caught the tail end of it. But it looked like great energy >> because a lot of >> had some really good discussions with some of your colleagues. So really great coming on. Thank you. Alright. Keep right there, buddy. That's the Cuba bit back from knowledge. Sixteen, Las Vegas. Right after this >> every once in a while.