 from the Moscone Center, it's theCUBE. Covering AWS Summit San Francisco, 2018. Brought to you by Amazon Web Services. Hey, welcome back everyone. We're live here in San Francisco. This is theCUBE's exclusive coverage of AWS Amazon Web Services Summit 2018 with my cohost Stu Miniman, a two great guests. Hot startup from Signal FX, the CEO, Karthik Rao and the CTO, Arjit Mukherjee. Welcome to theCUBE. Good to see you again. Yeah, great to see you again. Thanks for having us. So we've been following you guys. You've been out five years, two years in stealth. Three years ago you launched on theCUBE. Right here on theCUBE. We see you guys at AWS and VMware. Cloud's changed a lot. So let's get an update. Karthik, take a minute to explain where you guys are at now, company-wise, employees, traction, momentum, product. Where are you guys at now? Yeah, absolutely. So Signal FX, first of all, let me tell you what we do. Signal FX is a real-time streaming operational intelligence solution. Basically what that means is we collect monitoring data, operational data across the entire cloud environment from the infrastructure all the way up to the applications. And we apply real-time analytics on that data to help people be a lot more proactive in their monitoring of these distributed environments. We launched the company in 2015. We come, I'll let Arjit talk about our origins. We came out of Facebook and we had a lot of experience building this at Facebook. In the past three years, we've been building up our company aggressively. We've now got hundreds of customers, including several large Fortune 500 accounts, large web-scale accounts like Acquia and HubSpot and Yelp and Kayak. And we're over 100 employees now, about 120 employees. And yeah, doing great. So Verner Vogels, the CTO, laid out on stage, especially with great Matt Wood conversation around machine learning. But the real thing that Verner laid out was the old way, the web server, multi-tier architecture stack kind of thing going on there to a more cloud DevOps horizontally scalable with sets of servers that could be spawned in parallel. Creates kind of a new kind of operating model, but also creates challenges around what the instrument, you know, as we joke, someone left the lights on implying EC2 has been running and all these kinds of things are going on. And you mentioned some of the Facebook kind of challenges that people were building their own scale. What have you guys learned and how has that applied to today's market infrastructure? I mean, what are some of the threshold challenges that companies are facing when they say, one already there or I want to get there? How do you guys look at the main issues? Yeah, so monitoring modern environments and infrastructure is actually quite a challenge. It's obviously a few things going around. One, as you mentioned, is the variety, the sheer variety of things. We are no longer just a three-tier architecture. I have cloud services, I have containers, I have lambdas, I have my own applications. I have the cloud infrastructure itself that all needs to be monitored. And things are also becoming far more numerous. So there's just many more of everything, right? And so making sense of that space is becoming a big challenge. And our company was founded on the idea that monitoring is becoming an analytics problem because it's no longer about looking at individual servers or application instances. It's more about making sense holistically over what's going on and being able to combine different types of data from different systems together to provide you with that high level view. And that's the kind of functionality that we at SignalFX have been trying to provide. What are some of the data flows volumes look like? Because I've heard mobile people talk about either Facebook or in open compute environments where there's just so much data coming in from the instrumentation that no human could actually get their arms around it. And you need to supplement it with machine learning and intelligence. I mean, is that something that you're seeing? What are some of the... Yes, so actually what we see is different prospects or customers will be in different stages of a spectrum where they are... Maybe they were in a stage one where they're sort of using traditional architectures. And they're moving to these more modern systems and as they get more modernized themselves, their use cases or the ways they want to do monitoring also gets more advanced. And so we see the whole spectrum of it. As you mentioned, so understanding analytically how competition is doing is great, but then you also want to take the human out of things as much as possible, right? And make things more automated and you want to look at the data and how things are behaving to learn from existing patterns to find outliers. So that's really a very interesting challenge. And sort of when I look at what we can do as a company going forward, like all the technological stuff that we can invest in, it's quite interesting. Kurt, take us inside your customers. How does this modern monitoring, how does it change their business? How does it impact things like feedback loops and DevOps and everything the customers are having to deal in this ever-changing environment? Well, I'll give you one example. There's a Fortune 500 company, they do product launches and this is one of our customers and their product launches drive so much traffic that they do 80% of their business in the first two minutes of a product launch. And this is not at all uncommon in today's economy. And they're leveraging a lot of modern technologies, container architectures, serverless function architectures to spin up a bunch of capacity during these launches and they were effectively flying blind most of the time because most of the traditional systems management monitoring solutions are not designed, A, to handle that volume, but B, to handle the instant discovery requirements of if you're going to do 80% of your business in the first two minutes. So the challenge is you're always playing defense, you're reacting to issues and you're mostly flying blind. By leveraging signal effects, they're getting real-time visibility, real-time discovery of these components as they're coming up or the only solution that can do that. So literally within seconds of spinning up all of these containers, they're getting live streams into their dashboards and live analytics and live alerts. And what that's enabled them to do is be a lot more aggressive in effectively doing a lot more of these launches. So that's driving their business and it's helping them drive their digital strategy forward. And microservices is really enabling you guys to be more relevant because truly the signal from the noise is we're all these services reporting to you. I mean, you're talking about container madness. They're two fundamental problems. So one, there's an architecture shift, right? And that's driving massive amounts of volume. You have physical machines that will live for three years in a data center, divide it up into VMs, 10, 20 VMs per server that maybe live for a few months to now every process running in its own container that might live for a few minutes, right? So you have a massive exponential explosion in the number of components, but that's not the only problem. I was a part of an architectural shift at VMware for a number of years. We were just affecting an architecture change. What's happening now is there's a cultural change and a process change that's happening as well because with containers, your development team can push changes directly out into a production environment. And what you're finding is you're going from sequential product development to parallel product development and a massive exponential increase in the number of code pushes. The only way you can operationalize that is you have to have real-time visibility in everything that's happening. Otherwise, the left arm doesn't know what the right arm is doing. And you need prescriptive and predictive analytics. Exactly, you need predictive analytics to identify there's something unusual here. It's not a problem yet, but this is highly unusual. Maybe it's your canary release that you need to code push, so you want to roll it back. So having that level of predictiveness becomes absolutely critical. Yeah, you mentioned real-time. We used to argue what really is real-time and it was usually well in time to react to what the customer needs. What does real-time mean to your customers? Architecturally, is there something you do different to kind of understand what that means? Yes, so we actually fundamentally took a very different approach when we build the product where typically monitoring, our metrics monitoring was done with what we call a store and query or a batch-like architecture where you store all the data points that are coming in, then you query from it to run your different use cases. While what we built at SignalFX is a fully streaming end-to-end streaming architecture which is real-time, and what we mean by real-time is like two to three seconds between a data point coming through us and it's firing an alert or showing up in your chart. So that's the kind of real-time and it required us to do like lots of innovations up and down the stack and we built a lot of IP. We've got now six patents and more are coming because the approach we took was quite novel, different from what we've seen. You guys got a great management team and looking at what you guys have been done and been impressed with you guys. I want to just ask Karthik on you mentioned about all these parallel processes that are going on. Totally agree, the process change, operationalizing a whole new cultural way to create software, manage the data. I mean, it really is the perfect storm for innovation but also it could really screw people up. So I got to ask you, who are you targeting for your customer? Who's the person that you talk to? I'm assuming it's kind of a DevOps that's more like a cloud architect. Who do you target? Who do you sell to? Who's the buyer? Who uses your service? Well, we see every enterprise we see following a very similar journey. So the first stage is typically you're just getting familiar with cloud and you're probably just lifting and shifting enterprise workloads into the cloud, probably experimenting with big data on the cloud. You're not yet doing microservices or containers or DevOps. And for them, we're still selling largely to classic IT. They're just trying to get better visibility into their digital environment. You know, their cloud environment. But then what ends up happening is they very quickly get to what we call basically chaos. It's a stage two. And it has a lot of parallels to shadow IT. What happened with SaaS where you have hundreds of different SaaS tools is happening all over again with cloud, but you've got hundreds or thousands of different operational tools, different ways of doing monitoring, logging, security, and every team is doing its own thing. And so that's a big problem for enterprises who are trying to build best practices across their broader team. In that place, we're typically selling to departments because they don't have a centralized strategy yet. But what we find is that organizations at maturity have figured out that it's important to have certain centralized core services. And that doesn't mean they're forced on the end users, but they provide best practices around monitoring, logging, and such, and just make it easy for them to use those solutions. And so that's almost a new IT organization. It's a platform engineering team, platform engineering team, infrastructure engineering team, and they are effectively building best practices around the new stack, not the traditional stack. So are you are or aren't targeting the department level? Are you are or? We sell to departments, but we also sell to the teams that are standardizing across the entire organization. It depends on the stage of the cloud journey, right? And the company, exactly. From an architectural standpoint, there's virtualization, there's containers, now serverless. How do you even figure out what to monitor in serverless? How fast is that changing? How's that impacting kind of your roadmap? So serverless brings a very interesting challenge because they are very, very ephemeral. Like they are the epitome of ephemeral in some sense. So we realize there are two things. One is serverless, there's a reason why things are moving faster is because you want to be able to move faster, but then you also need to be able to monitor faster. It's no good monitoring serverless at five minutes later, for example. So one of the things we invested in was how to get metrics, et cetera, telemetry from these serverless environments in a very fast fashion. There's something that we've done. The second that we are doing that really works for these environments is, after all, it's not about how many times a serverless function ran. It's about the value that is providing the application that's running on it. And by focusing on a platform that lets you send these application metrics in great detail and then be able to monitor and analyze them, I think really amplifies the value in some sense. So those are the two of two. And talk about the ecosystems. One of the things I want to ask you guys because we've been seeing the collision between a lot of the different clouds, clients want multi-cloud. Well, obviously, we're here at Amazon. They believe they should be the only cloud, but most customers would look at their either legacy systems with some instrumentation and operational data to edge of the network, for instance. When you look at the edge of the network, that's just an extension of the data center depending on how you look at it. So how do you guys view that kind of direction where a customer says, hey, you know, I got a cloud architect. We're on Amazon. Of course, we have some old Microsoft stuff. So we've got Azure going up there. Googles, we're kicking the tires on Google. And I got this whole IoT edge project. SignalFX, instrument that for me. Do you, is that what you do? Or how do you deal with that? How would you deal with that kind of conversation? Well, I think most enterprises, that the larger companies, we see looking at multiple clouds, right? And they have different workloads running in different clouds depending on, you know, the needs and what they're looking to do. So the nice thing about a solution like SignalFX is we span all of these different architectures. And what we find is most of the larger companies want to separate their business process solutions from their runtime architectures, right? Because they want to have a solution like SignalFX that, you know, it doesn't matter who you're using. If you choose to have your analytics-intensive workloads in Google Cloud and your e-commerce workloads in Amazon, but you only want one system that will pay someone in the middle of the night if there's a problem, then you have SignalFX to do that. And then you have your choice of runtime environments depending on what your developers need or what the business demands. So, you know, we provide a lot of that glue across the different environments. Do you see that as the preferred architecture with most customers? Does that makes a lot of sense? I mean, whether you're doing other data services, it kind of makes sense. Does this separate out? Is that consistent? To have different applications in different clouds? It depends. I mean, I think we see some people who are more comfortable running on a single cloud vendor and they make the decision based on what's the portfolio of platform as a service features that are available. And they really like those and they say it's easy to just go with one. But more often we find people wanting to at least have some percentage running in a different cloud vendor. All right, final question. What's the secret sauce for the company? What, tell us about the secret sauce. I think- Look at the patents, I heard patents. You know, the show all the exact same. But what is the secret DNA of the tech? What's the magic? I think it's our very unique architecture. It's entirely different from what you have. It's streaming and it focuses on scale, on timeliness, as well as on analytics capability. I think that unique combination is very special for us. And that in a way, it sort of allows us to address very, very different use cases, including like these hybrid environments and whatnot in a very effective way. So it's a very, very powerful platform that can be used for many use cases. All right, so that was John's final question. Kartik, I've got one last one for you. I had one more. What's it like being a CEO of a software company in the cloud era today, compared to what has been earlier in our career? Well, it's moving very, very quickly, right? I mean, the technology always moves very quickly. But I think compared to when I was at VMware in the mid-2000s, it just feels like every 18 months there's a new technology wave. When we started our company five years ago, that was the first year that AWS eclipsed a billion dollars in sales. And Docker hadn't even launched. It launched a month after we started the company. And then serverless came and now function architectures all the way. So there's just so much change happening and it's happening so quickly. It forces vendors like us to really be on the cutting edge and forward looking and making sure that you're keeping an eye out for what's coming because the markets are moving way faster, I think, than they were 15 years ago. Well, Kartik, thanks so much. Really appreciate you guys coming on, Signal FX. I'll give you the final word on the interview. Take a minute to share something with the audience that they might not know about Signal FX that they should know about. Well, I think what people may not realize is how real time you can actually get. I think most people are used to doing all their monitoring and observation and they think of real time in the order of minutes or if you can get stuff every 30 seconds. We really are the only real time solution. That's why we say real real time where on the order of seconds you can build really, really sophisticated analytics and get visibility like you can anywhere else. So it's real real time. And that's soon to be table stakes. The Cube is real time. We're live right here in the Cube here in San Francisco at Amazon Web Services AWS Summit 2018. Of course, we've been covering all the Amazon re-invents since it started, of course. I'm John Furrier with Stu Miniman. Back with more live coverage after this short break.