 From Washington DC, it's theCUBE, covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. I'm Stu Miniman, and this is theCUBE's coverage of ScienceLogic Symposium 2019, here at the Ritz-Carlton in Washington DC. Real excited to welcome back to the program. It's the co-founder, CEO, and the headmaster of Wizarding School. Wizarding School, yes. Dave Link, thank you so much for joining us. Great to be here, Stu. All right, so Dave, first of all, congratulations. Really been enjoying the event. You kicked it off in the keynote this morning. Great energy. Really, I think, capturing where we are in IT and business today. We understand how things are changing so much, and it's a complex world, and ScienceLogic's trying to do its part to help simplify and make it easier for IT to run at the speed of business and machines. That's exactly right. What's happening in the world right now is you've got a confluence of cloud apps, traditional legacy apps, and they're colliding together. And as they collide together, you need new tools to manage that in a way that's different than what we've seen in the past. You're looking at lots of sources coming together to contextualize not just seeing what's happening, understanding how systems relate to one another, but acting upon them. Machine at machine speed means that automation is king. And the wizard hat actually relates to a storyline we had earlier today. When we think about how to educate the marketplace and the customers, we realize that we needed a very new way of communicating. So videos, e-learning, the wizard of learning has been a theme of the show to help our customers get up to speed and actually take full advantage of the application that we provide to help them deliver great service quality. Yeah, well, and we appreciate you bringing theCUBE to help with that video education of the community overall. That's right. Yeah, so look, Dave, let's step back for a second. We're going to get to the business update, but first, the company was founded in 2003. Cloud wasn't a term. Some of the underlying foundations of what became cloud existed back there. Those of us in the industry understand some of the waves that have happened there, but talk about cloud and microservices and all of these changes that are have. So give us a little bit about that evolution about the original premise of the company as we move now to the world of today and how you may manage to keep the company moving and irrelevant. I love telling this story, Stu, because it never gets old to me. A lot of the original feces that we had about where business service analysis was going, the application analysis connected to the infrastructure, our belief was we were going to move to a world where it wasn't based on devices or nodes or systems. It was really based on the service. And what we're seeing with cloud has accentuated that tenfold because services now are made up of compound things, technologies, service delivery mechanisms, as a service platforms, and they all have to work with one another. The platform we built had an architecture that was very open that could take data streams from lots of different sources, create a common information model, contextualize that, and then act upon it. So now more than ever before, we really built the right platform with multi-tenancy, with role-based access control, with all the things that were really hard problems to solve, code day one. And now the thesis that we had that it was more about the service view is as important as it's ever been with ephemeral systems that are coming and going, with really containerized systems on top of virtual machines, on top of bare metal, all these abstraction layers require a different mindset, but an open architecture is really at the heart of pulling lots of data streams together, contextualizing it, and then acting upon it. Yeah, so I'm a sucker for Venn diagrams. So you had the analyst in the keynote this morning talked about AI ops, and he said it's the intersection of IT operations, data science, and machine learning. Yes. Data at the center of everything? It's something we've had a couple of waves of trying on. Intelligence and automation are things we've been talking about for decades in IT. Give us a little bit as why some of those waves are coming together so that now, and what you're doing is the right moment to really help accelerate. You've been having great growth for a number of years and project out some really strong growth for the next few. We have, over the last five years, the company's grown over 540% from a revenue perspective, and I think that's the underpinnings of that relates to do we have the right market fit? Are we solving a problem that's material to customers that it's hard for them to solve without our product? But I really envision a future. We've been working on this for a couple decades, right? The future is one, I hope, where from an artificial intelligence at machine speed where we're getting so predictive and understanding through really smart, scalable algorithms, the future faults that may occur for, we've both been at this for a long time. We've been talking about event correlation for many years. I envision a world where you're not doing event correlation. When you've had an event, it's actually too late. Usually that's caused by a system telling you that there is a problem. So what we're really working on, what we've talked a lot about here at the show is not just predictive analytics, but really understanding what's abnormal and getting in front of a problem before there is a problem with the system with really super smart algorithms that help customers understand many different data sets converge together and what they really mean so that you can get ahead of a service outage rather than have the fault that you're then working on correlating to infrastructure to application layers. The other thing that's been interesting for me to watch is the core of where you started was really working with the service fighters. I've had a chance to talk to a number of your service fighters. Hughes has been with you since the early days up to, one that just bought a couple of weeks ago and they're happy. Talk about kind of the compare contrast of the service fighters and the enterprise because cloud is impacting, the big hyper scale clouds are impacting both of those and the rate of change is affecting both of those in a lot of ways. So I'm curious as you see what's similar and what's different between going into those markets? When we thought about the problem for service providers there were two axes that we were looking at. Number one was from one instance of our platform you had to serve many customers that all had their own tendency. But on top of that you had to layer in a role-based access control. Who could see what? The customer had their view, the internal ops teams had their view. So building out a really complicated foundational model and an architecture that would support tenancy on steroids with one instance of our product was a really important linchpin of what's now incredibly important to enterprises. Because enterprises are getting into a moment where they're having to really act as service bureaus, service brokers and that means that all the different teams that support different technology silos really have to work together as one and but yet they still need their own views. So a lot of the foundational highly differentiated capabilities we built for service providers for large scale globally distributed enterprises actually meets a need profile that is very hard to find solutions that fit that profile and can give them that consolidated view but yet the deep dive view for the practitioner. And we're finding that more and more enterprises have follow the sun operations, follow the sun architecture teams, follow the sun engineering teams that need different views that is really hard to get most products that were built in this space were built for a single tenant enterprise view and that never gives you the granularity for each consumer and each persona to get the view that they need. So it's interesting that although we kind of over engineered those capabilities for the service provider needs it's becoming in vogue with the enterprises as they're looking at how do they need to do things as really a converged team working as one team across many silo disciplines. And that requires a very different way of thinking, a different tool space, a different solution to the problem that we built kind of from the ground up. It's now really appropriate for the DevOps teams, the teams that are really having to break down the silos and work as one team. Yeah, the term that often gets misused and misunderstood is scale. But if you truly can build something that's distributed architecture for scale, it really opens up a lot of opportunities. One of the things you highlighted also is that ScienceLogic puts a lot of investment into R&D and you keep working on things. Big announcement of Big Ben. It seemed I've had a chance to hear what everybody likes in the best. Talk a little bit about how you keep the development efforts going, how you put that strong and effort on it. And boy, you said you worked on the UI for three years and now it sounds, it's a bold statement to be like, okay, and everybody you're using this, you can't have the safety blanket of old way and new way for a while. You're constantly reinventing and refactoring code base to get to new outcomes for customers. We're spending between 35 and 40% of revenues on R&D. That's generally almost twice as much as many of our competitors. And we're doing that because there is so much still to do. At times we have really thought carefully, could we scale back, should we scale back R&D spend? But fortunately we've had a very supportive board of directors that believes in our vision, believes in the vision that this is a unique moment in time. The whole market is transitioning to a new tool set because of all of the crosswinds of public cloud, refactoring of applications, containerization, abstraction of the network, storage, compute. All of these things combining together require a very different way of solving this problem. We've actually seen this play out in the past which again is why we're over investing in engineering. When you look at the mainframes and the compute architecture of mainframes and then we went to client server, the tools that manage the mainframe really didn't manage the client server. We've now gone from client server to cloud, the same things happening again because the needs are so different and we're going to see a very different generation of tools rule this next gen of requirements that customers have when they have a multitude of clouds that all work together to deliver an outcome to an application that you as a user are benefiting from. All right, so talked about the growths, talked about the investment. It's a strong industry validation today also. I had Gartner up on stage, talked about the definition of AI ops. They might not be fully in sync as to how mature the market is but it's still important that they are, this is a trend and something to watch and it's on their hype cycle and Forrester released the Wave which had congratulations, ScienceLogic as the top score up in the leaders category. So congratulations on that and what does that mean? Well, we're thrilled about that because that external validation is what customers look at. It helps them with their analysis and the talk tracks that everybody's on in our industry, sometimes it's hard to discern who does what and how well each company does it. To some degree, from a marketing perspective, many people use the same words. So the good words are already used up. So sometimes it's hard to understand how each product is differentiated in the marketplace. The Forrester Wave report was so thorough, so comprehensive, put us through over 30 use case scenarios where we had to demonstrate to get the qualifications for that ranking. So it wasn't just us responding in writing and waving our arms and throwing out a few PowerPoints to get to that result, we had to prove it and it feels the satisfaction of actually proving it for our team, for our engineering team, for everybody here at the company, I'm so proud of everybody because that's really, from a product perspective, we love those product recognition awards are actually sometimes more enjoyable than the growth recognition awards because that means you're really delivering a value to the customer where they're gonna, when they deploy the product, they're gonna have a good outcome. So that's what we're focused on and having Forrester put us at the top of the Wave report is a special moment in the history of the company. All right, so Dave, this is your user conference, so I want to end on, let's talk about the customers and here's my observation as, my first time coming to your event and I've talked to a number, seen some of the interactions there, there are certain products that customers love. The relationship is an interesting and I'd say a really good one, the customers are really engaged and enjoying and liking it and it's almost like that friend that you can be like, I really like you and your friends in there for I can be like, this is how I want you to get better in science logic, this is what you've done and I'm excited once on the roadmap and this is where I want you to go even more. So it's like that friend that you can kind of hang out with and joke with and I've seen some of those relationships, it's a good, robust relationship and strong partnerships it seems that you build with your customers and I get in the right vibe, how do you look at your relationships with your customers? From a simple business perspective, I look at a couple things, this is just as a run the business metric. On average, our customers buy about 24, 25% more capacity each year, on average our customers stay with us for seven to 10 years. On average, our customers pay us within 59 days. So are we getting paid on time? Do our customers buy more capacity each and every year and do we retain our customers? We retain about 95% of our customers. So those metrics are really best in class, net subscription, retention, DSO, all of those things are really good foundational indicators of we're doing a great job for our customers but what I love is this interaction that we have with them where they're never ending pressure on us to do better, to strive for something that makes a day in their life a better day. I love that pressure, it's uncomfortable many days of the week as I mentioned in my opening presentation but it makes us a better company and everybody in the company embodies this sense of how do we capture that, synthesize it and then deliver against their needs and wants as quick as we can. So our innovation rates now are as high as they've ever been. The throughput of our development team this last quarter was the best we've ever seen in the history of the company not just because we had more people but we're getting more done in the same amount of time. So all the KPIs that I look at are pointing in a really positive direction of great momentum for the business and really good alignment with customer needs and wants. We have probably the best market fit I've ever seen with the needs and wants of a net new customer and how our product fits against that. The Forrester Wave Report was yet another independent validation of how good our market fit and our strategy is right now to solve real problems that are very painful for customers to solve without our product. All right, Dave, I can't let the head wizard gone without looking a little bit into the future. So as you look down the road what should we be looking as industry watchers to seeing from science logic, seeing from the industry? I ask customers if they had a magic wand do you know what would they do to make things better? You had a magic wand up on stage. What will you be doing to make the industry better for all of us? There's so many things that when we think about making the industry better it's a community. And that means that among the key things that everybody's focused on right now for AIOps is automation. So sharing those lessons learned, cauterizing, validating the automation opportunities whether it's with provisioning systems, with end devices, for capacity planning all the things that we're doing we're starting to work with our customers to publish that broadly so that they can benefit from one another as quick as possible to take those best practices and throughout our community put them into production. If we do that each and every day and really focus on delivering that value across the customer base even for competitive customers that compete with one another what we've seen is the spirit of cooperation and that to me is among the most satisfying parts of our customer and user community that it's a community that wants to help each other get better every day of the week and that's really our mission as well. So from a trend line for the entire industry I think we're all moving towards a moment in time where we have this autonomic capability where we know the applications are infrastructure aware the tools that help us keep those applications running are getting smarter and smarter by the day and basically move us away from a fault and event correlation storyline to a predictive automation storyline. All right, well Dave actually I said it on theCUBE a couple of years ago data holds the potential to be that flywheel of growth for many years to come really appreciate you sharing the story and thanks again for having theCUBE at the event. Thanks Stu, great to be here with you. All right, we'll be back with more coverage here from ScienceLogic Symposium 2019. I'm Stu Miniman and thank you for watching theCUBE.