(upbeat inspirational music) >> Hello everyone, I'm John Furrier in the Palo Alto Studios for Cube Conversation. I'm here with David Link who's the CEO of ScienceLogic. David, thanks for coming in. Good to see you. >> Great to be here, John. >> So, thanks for coming in. You came in from D.C., that's where your headquarters and ScienceLogic, you guys are having good business run right now. You're self-funded early on, now you get to venture back. Take a minute to explain how you guys got started, what does the company do? >> So, this is the classic story of entrepreneurship. We started in the garage. Myself and a couple of co-founders believed that IT management operations was broken and it was broken because a lot of the industry had really focused on having silos of data, the silos of data, the network, the application, the security, the storage, now cloud, containers and every technology had its own data silo of manageability. We believe that that was intrinsically wrong to understand how the service that combined all these different applications and technologies was behaving. We wanted a service view, so we brought it all together, kicked off, really the first seven years we boot strapped the company, the first year and a half we coded, got the product to market, it grew very quickly, got to the Inc. 500 a couple times, and then we attracted a lot of financing options. We had about 250 companies approach us. We never made one outbound call and fortunately, we had some really great and strong investors in EA, then Intel Capital, and three and a half years ago, our last round of financing was with Goldman Sachs and they've really been a great catalyst to help us continue our growth over the last five years. I think we've grown about 540% on the revenue side, so it's been an exciting time. >> Well congratulations. It's always a good success story to be a hot deal when you don't have to make any calls, they come to you. >> Yes. >> And that's good, that's part of growth, but I got to ask you what year did you start the company up? >> 2003. >> So, it's not obvious then, it's obvious to you as a visionary, but now people now know IT operations is broken. Cloud highlights it in a big way. The lights get turned on, the cockroaches are running around, but web services were still booming at that time. You start to see the beginning of the whole web services movement, you guys saw this early. Now, it's well recognized that IT operations can be automated away and Cloud certainly has an automations vibe to it. AI has been a big part of the AI operations. Is this kind of where you guys started with that vision? Was the original vision kind of where it is today? Take us through kind of what you saw and what's happening today. >> So, thematically we have this next wave of the computer architecture, Cloud computer architecture, edge computing where the way you manage that kind of infrastructure is different than the classic client server. There are different needs, different requirements, and that thematically has led with the change of infrastructure. Applications are changing and applications are now more infrastructure-aware. When we started the company, usually applications sat on one system or a cluster of systems and they weren't widely distributed. So now that the applications profile is changing, the architects are changing to microservices, that really puts huge strain on our industry. The industry, the total adjustable market, is about 25 billion dollars a year annual spent on tools. John, if you can imagine that. 25 billion a year is spent. It's going through an amazing, I would say, tectonic shift because why? Infrastructure's shifting and as more people move workloads to the Cloud into what I would call ephemeral workloads where they're moving around, that causes all kinds of pressure on the systems and record to manage that so that you understand what is happening at this moment in time. Where is it? What Cloud is it running on? How's the application performing? And you really need to tie the application to the infrastructure real-time. >> I want to get your thoughts on this. I interviewed a CIO this past week for a big company. I won't say the name 'cause we haven't published the video yet, but he told me candidly, he said that, look it, we outsourced everything and we outsourced our way into oblivion and what he meant by that was is that the core competency of IT, and he reference the book, Nick Carr, IT Doesn't Matter, which kind of was true, but wasn't true. Now, IT has a competitive advantage and essentially, they had this anemic IT department that was outsourced and they lost their competitive advantage, so he's like the reinvestment in IT is more than ever now because of Cloud, because of these new environments. So, I kind of believe that to be true. I'm sure you do too, but the reaction really is is you've got a lot of Legacy vendors that were dictating how to do things. >> Yes. >> I'm IBM, I'm Oracle, you got to do it this way and you were kind of constrained, IT was constrained by that. Now, you got to be much more agile, you have workloads that are dynamic, provisioning, orchestration, this is a whole new dynamic. What's the impact to the IT buyer, the IT environment with this new model, this new modern dynamic, new modern era? >> When you think about CIOs and CEOs, the pressure that they have to be Cloud first. Cloud first is such a strong... At the Board level, there's pressure. The adoption of Cloud now is happening faster and more rapidly than the adoption of virtualization, maybe it's doubling in the speed in the time warp, but what that means is that most CIOs are dealing with as many as nine to 11 Clouds, not one. You have a federation of Clouds: Private Clouds, public Clouds, software as a service Clouds, and that's your IT landscape, so it's changing so quickly that you have to think of it in a more federated approach. That means that the way you used to manage your private systems, and now your public systems, are really different and you've got to look at them more holistically because often they're communicating with one another in hybrid architectures. So, that's really the heart at our mission, to provide the context of how all the services you're trying to deliver as a CIO are behaving. What's their availability? What's the risk of the service having a problem? And knowing that real-time is ultimately what you want to do with your Cloud first strategy, but you need the right tooling operationally to affect that kind of outcome for your team. >> So, what's the core problem that you guys are solving? 'Cause obviously, there's a lot of complexity now, it's a new environment, so I still got the baggage of some Legacy environments. Is it monitoring you're solving? I guess, what's the core problem is my question that you guys are solving? If you had to kind of finish that, the core problem is blank. >> The core problem is visibility. The Holy Grail is application to infrastructure and the problem is that's becoming so complicated because everything is moving around. The more abstraction layers where it's a container, which is abstracted on top of a virtual machine, which is on top of bare-metal server. SD-WAN is an abstraction on top of an MPLS network. So, you have all of these layers that get from a software-defined perspective, they get abstracted away from the actual equipment that it's running on. Well, when that happens, where is the problem? Because it's moving around. The problem isn't in one place. So, that application to infrastructure awareness, it's almost like one of the things that we've looked at in the world of Facebook. You've got a lot of relationships, you've got videos, you've got friends, you've got all these different connections that are constantly moving around with data streams. What we do as a company is pull all these different data streams from the technologies themselves, from the Cloud providers, from the application layer, pull it together in a data hub that we can then understand how they all relate to one another so you can really, truly understand service impact and that is the crux of the problem most companies are dealing with now. You've got to fight with your Legacy, 'cause you still have that and it's not going away tomorrow, so you've got to make sure you're good at that, you've also got Cloud, the Cloud first initiative, and then you've got in between systems that are using both. That's really where we play. We're really good at the Legacy, we're good at Cloud, and connecting the two together and that is a really tough space because most Legacy providers really didn't get good with managing hyperactive ephemeral Cloud estates. The guys who started over the last five years building tools to manage the Cloud are really good at Cloud, but they don't cover Legacy. They're not going to cover a net app or hyper-converge, typically. So, we combine the both, Legacy and Cloud together in one management system, monitoring management paradigm, and then there's an automation engine where we actually proactively remediate problems real-time. So, the three together is where algorithmic operations, AI Ops, comes together. >> David, I want to dig into the offering, but before we get there, I want to get your thoughts on two trends: one is multi-Cloud. Recently, we've seen a lot of hybrid Cloud discussion, but now the big hubbub is multi-Cloud and the other one is AI Operations. So, I've been saying on The Cube, everyone who's in IT Operations is screwed, going to get automated away by AI. It's kind of tongue in cheek, but it's kind of a reality is that those old business models that were based upon certain service levels are going to be done in software. Now, you've got multi-Cloud. So, first question is what is multi-Cloud definition that you have for that? What does it mean? What is multi-Cloud? >> In our world, multi-Cloud is... Most large organizations use more than one Cloud and half of that is driven by what Cloud is best to operate a particular application profile? Amazon's really good at a lot of application profiles, but Azure might be better at certain Microsoft profiles, and then Google has profiles, and IBM Watson has profiles. Depending upon what you're trying to do with the application, where it was born, how it's living, how it's been re-factored, you're going to use one Cloud or the other, but most customers that we see have many Clouds. There really isn't one Cloud management scape when you're using... Vendors are still reasonably proprietary in the public hyper-scales. >> Some are better than others. >> And some are better. It depends on the use case. So, we try to bring all that together so that you're not looking at four panels, you're looking at one. >> So, you make it easy with one dash port. Okay, AI Operations. This is a hot trend, a lot of venture capitals are funding companies that have AI Ops in it, machine-learning obviously booming, no doubt software automation is coming. I'm seeing it everywhere. What does that mean? What is the definition of AI Operations? I mean, I'm bombastic at saying the industry sectors is going to crumble. I kind of think it will, but it will shift, but what is the impact to IT Operations with AI and what is AI Ops? >> We like to think of it as a life cycle. So, when you look at the life cycle of operations you have at the beginning of the life cycle, provisioning, so when we think about algorithmic, there's many different layers of automation: machine learning, cognitive learning, and you're going to use different parts of algorithmic operations for different parts of the life cycle. So at the very beginning, you're going to connect generally to a provisioning system so you know what's been provisioned or de-provisioned so we can automatically align a manageability template because nobody can be on a keyboard now, John. This has to be all machine to machine. So, once then it gets provisioned, then there's the run operate part and how do you learn from the normal operating conditions that you're looking for? The anomalies that you would look for to detect things aren't behaving appropriately? And then, once you understand those anomalies and the patterns, you can remediate them proactively, adding resources, decreasing resources, changing configurations, those are the things that kind of that last tier, and then that final tier, when there is a problem, if there is a problem, you've got to then raise a ticket, you've got to then work through the incident management of that ticket so there's another multi-step layers of automation to the incident management orchestration layer of solving problems, closing out a ticket. So, we have so many different layers across that life cycle that we plug into, most of which are native to our core platform. >> And your secret sauce is managing all the workloads that are moving around really fast, so to complicate that even further, you've got a lot of stuff moving around to track it all. I love what you said about not typing on the keyboard anymore, but essentially I'll translate that from what I heard was command line interface of CLIs has been the primary mechanism for dealing with either network and or storage, which is moving packets from here to there and moving storage from now to then, storing stuff. So, CLI is moving to a programmable model? This is the big takeaway. So, I totally think this is the mega trend. The command line interface mode of operation is moving to programmable, which hits your run and operate. >> Correct. >> This is the mega trend. Your thoughts? >> It is and that's one of the layers of complication because instead of a CLI, it's an API, and it's usually a restful API or a graph API. Those APIs are very different in construct and instead of talking to one device, that one device is virtualized into a hundred or a thousand and so with one API call, you actually create a thousand devices versus one device and understanding how one system is behaving, like a CLI would be to one system, right? So, that is a layer of complication where when we make an API call, we break it up into hundreds of things that then we track and understand the tenancy of what is a multi-tenant nature of that? What is the organization? What is the service view for all these little components that are part of one API call? And that abstraction layer makes it really difficult for the enterprise because the one thing about our API economy right now, there is no standard. Every vendor chooses their own formats for their products and in some cases, many formats for products in a product family. So, that layer of complexity, John, is what we're really solving for. The customer doesn't have to worry about that. We take care of that for them, but you're right, the API has become the CLI and it's just a level of complexity beyond what most enterprises are wanting to deal with themselves. That's why they bring us in to help. >> That is so important too that the data's in the API. >> That's right. >> That's key and Cloud's got orchestration challenges, state and state-less applications. All right, let's get into ScienceLogic's offering. So, what do you guys provide to customers? Talk about the product. How do you guys deliver it? Is it software, is it Cloud, is it service, is it appliance? Take us through the offering. What's the key secret sauce? How do people buy and use your product? >> So, our product's delivered as a service. You can use it in the Cloud. We deliver it as a service in our Cloud, but we also provide it if customers are using Amazon or IBM or Google or Microsoft. They can put our product, same code-base, same product, they subscribe to it, it's a subscription license model, so it's a pay-as-you-go and you pay for the number of devices that are under management. Typically, there are some customers, whether it's in the government, financial services, or international locations where they might want to deploy our product on premise, so we offer the same mode, either in the Cloud or on premise, but most customers now are choosing to deploy the product in the Cloud and that is a really easy... It's easy to get >> That's good for you guys. >> It's great for us because there's consistency of operations, we can keep everything up to date, and most customers want technology delivered as a service. They just want it to work. They want it to solve the business problem and do it easily, efficiently, even better, solve complex problems in an easy format. >> Give some customer examples or benefits or anecdotal stories around customers that have used your service that extracted benefits and value out of it, and second part of that question is when does someone know they need your product? What are the smoke signals? Is something breaking or is it just pain? When do they know to call you guys? So first one is customer examples or stories and then how does someone know who's watching this, hey I might need these guys? >> There are four segments that we cover. We have customers all over the world. There's enterprise customers. This is really a product for large enterprise, Fortune 1000 companies, so Clorox would be a customer, Hughes Satellite would be a customer, Cisco Systems out here in the valley is a customer, Dell, EMC, so it depends on what problem we're trying to solve for the customer. >> So large IT deployments basically? >> Very large, multinational, big networks, hundreds of thousands of devices, tens of thousands of devices is where those companies have immense complexity, lots of heterogeneous technology that comes together to deliver a service. They need a really robust solution to manage that proactively. So, enterprise customers, service providers, so a lot of managed service providers, infrastructure service providers, Telcos, they all use it, so I think we have about 60% of the infrastructure as a service providers use our product to deliver managed services to their customers and then the federal government all over the world, we have government customers around the world. I think right now about 70,000 organizations use our product every day and it's fairly evenly split, AMIA and AsiaPac, and then the US is our biggest market. >> You know, it's interesting you mention heterogeneous. I always kind of smile because you mentioned client server earlier. Every wave has their reflection point and I think what's going on with Cloud and I'd love to get your reaction is that Cloud, where it's winning, is it's a scale out, large scale, pool of resources. We look at what's going on with Amazon, all this, is that you don't need to know what service they have, just get more servers, so you're scaling out. >> Yes. >> But now, you need to have heterogeneous components. It's not just X-86. You could have a GPU, you have other stuff, AI going on, so heterogeneous is different now, but it's still the same came, it's still complex, it needs to be abstracted away. Is this kind of the key area that you're riding on? Is that right? What's your thoughts about that concept? >> Well to a large degree, John, the Cloud providers have really provided a layer for you to not have to worry about that, but we've seen customers actually with hyper-converged environments that they build in-house and or systems that they built because of geo-fencing in different countries that need the data kept in the country. There are requirements that drive people to build their own system, so the real thing that we're seeing a tremendous struggle with right now is that context, understanding what connects to what. All the different technologies that come together, all the heterogeneity that comes together to deliver a service, and whether you buy best in class technologies to solve one part of the stack, the landscape of whether it's your load balancer or a caching server or the database or the server, the network, all those different components, the security layer, those components that come together, often people have chosen specific technologies to solve those problems. The Cloud kind of abstracts that away with they hyper-scalers, but often you're putting infrastructure that you have on prem combined with infrastructure in the Cloud to deliver an aggregate solution so that multi-tiered architecture, just like back in the day, a three-tiered architecture, we're seeing those emerging again with public Cloud because you might want the data that actually generates the information on the web client's side to be in your data center, but you still have to understand how the service is behaving. So, we really look at all layers of the stack to solve the problem and that's really hard to do. >> Well David, great to have this conversation. Before we end, I want you to get a quick plug in for the company. How many employees, offices? What's the revenue like? What's your goals? You don't have to share the revenue if you don't want to, but if you want to, you can. Give a plug for the company. What's happening? >> Well, I'm really proud of what the team's done. We've got a great team of employees, about 370 employees today, full-time, they're spread all over the world, probably 80% are here in the Americas and the vision for the company, we think that this is a big opportunity. We are far from done. We really started the company to disrupt the industry 'cause the industry, as I said, was a silo industry and it really is, 20 years later, it's still that way. It's not really converged into a unified solution. We have great aspirations. Every year we've been growing the business 40, 50% a year for the last several years, and this year, we'll round over 100 million within the next 12 months of our run rate, so it's an exciting time for the company. >> Well, you've got a great model, SAS, in a massively growing and changing market, complex market, heterogeneous networks, apps are all being abstracted away and automation's driving this, so I think it's a perfect storm of innovation. Congratulations and thanks for chatting on The Cube here in Palo Alto. >> Love to be here, John. Thanks for having me. >> John Ferrier here, Cube Conversation, and we're here with David Link, CEO of ScienceLogic, and also the founder. Self-funded, big venture rounds, growing like a weed, based in D.C. This is the Cube Conversation. I'm John Furrier. Thanks for watching. (dramatic inspirational music)