>> Announcer: Live from the Moscone Center. It's theCUBE! Covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. (upbeat techno music) >> 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 co-host Stu Miniman. We have two great guests. Hot startup from SingleFx, the CEO, Karthik Rau, and the CTO, Arijit Mukherji. Welcome to theCUBE. Good to see you again. >> Karthik: 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. >> Karthik: Right here on theCUBE. >> We see you 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? >> Karthik: Yeah, absolutely. So, SignalFx, first of all, let me tell you what we do. SignalFx is a realtime 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 realtime 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 Arijit talk about our origins. We came out of Facebook. And we had a lot of experience building this to 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, Werner Vogels, the CTO, laid out on stage plus a great Matt Wood conversation about machine learning but the real thing that Werner 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 where sets of servers that could be spawned in parallel creates a new kind of operating model but also creates challenges around what to instrument. You know, as we would joke, someone left the lights on, implying EC2s been running. And all these kinds of things are going on. And you mentioned some of the Facebook kind of challenges. People were building their own scale. What have you guys learned and how does that apply today's modern infrastructure? 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? >> Karthik: Do you want to take that? >> Yeah, so monitoring modern environments and infrastructure is actually quite a challenge. There's obviously a few things going around. One, as you mentioned, is the variety, the sheer variety of things. No longer just the 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. So, it's no longer about looking at individual servers or applications 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. Cause I've heard multiple 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 maybe they were in a stage one where they're sort of using traditional architectures and then moving to these more modern systems. And as they get more modernized themselves, their use cases or the ways they wanted to do monitoring also gets more advanced. And so, we see the whole spectrum of it, as you mentioned. And so, understanding analytically how what we're is doing is great. But then you also want to take the human out of things as much as possible, right? >> Yeah. >> 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 outlines. So, that's really a very interesting challenge. And what 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. >> Yeah, Karthik, 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 that customers are having to deal in this kind of ever changing environment? >> Yeah, well I'll give you an 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 SignalFx, they're getting realtime visibility, realtime discovery of these components as they're coming up. We're 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 and 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 where all these services reporting to? >> Karthik: Yeah. >> You talk about container madness. >> Karthik: There are two fundamental problems. So, one there's an architecture shift. 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'll maybe live for a few months. To now every process running in it's own container that might live for a few minutes. So, you have a massive exponential explosion in the number of components. But that's not the only problem. I was part of an architectural shift at VMware for a number of years. We weren't 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 realtime visibility in everything that's happening. Otherwise, the left arm doesn't know what the right arm is doing. >> John: And you need prescriptive and predictive analytics. >> Exactly. And you need predictive analytics to identify there's something unusual here. It's not a problem yet. But this is highly unusual and maybe it's your canary release. We need to do a code push. So, you want to roll it back. So, having that level of predictiveness becomes absolutely critical. >> Yeah, you mentioned realtime. We used to argue what really is realtime. And it was usually well in time to react to what the customer needs. What does realtime mean to your customers? Architecturally, is there something you do different to kind of understand what that means? >> Arijit: Yeah, so we actually fundamentally took a very different approach when we build a product. Where, typically, monitoring our metrics, monitoring was done with what we call a store and create or a batch-like architecture where you store all the data points that are coming in, then you create from it to any other use cases. While what we build at SignalFx is a fully end-to-end streaming architecture which is realtime. And what we mean by realtime 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 realtime. And it requires us to do lots of innovations up and down the stack. And we've built a lot of IP. We've got now patterns. And more are coming because the approach we took was quite novel. Different from-- >> John: You guys got a great management team. And looking at what you guys have done. I've been impressed with you guys. I want to just ask, Karthik, you mentioned about all these parallel processes that are going on. Totally agree. The process change, operationalizing an all new cultural way to create software manage the data. I mean, it really is the perfect storm for innovation. But also, it could literally screw people up. So, I got to ask you, who are you targeting for your customer? Who is the person that you talk to? Assuming it's kind of DevOps, so it's more like a cloud architect. Who do you target? Who do you sell to? Who's the buyer? Who uses your service? >> Karthik: 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. There just trying to get better visibility into their digital environment, you know, they're cloud environment. But then, what ends up happening is they very quickly get to what we call basically chaos. It's stage two. And it has a lot of parallels to shadow IT. What happened with SAS, where you have hundreds of different SAS 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 it's 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 centralize strategy yet. But what we find is the 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. So, that's almost a new IT organization. It's platform engineering -- >> John: Is that a cloud architect? >> Platform engineering team, infrastructure engineering team, and they are effectively building best practices around the new stack not the traditional stack. >> So, you are or aren't targeting department level? Are you are? >> We sell to departments. But we also sell to the teams that are standardizing across the entire organization. >> So, cloud architects, for instance? >> Depends on the stage of the cloud journey. >> Or company. >> And the company, exactly. >> From an architectural standpoint, you talked that there's virtualization, there's containers, now serverless. How do you even figure out what to monitor in serverless? How fast is that changing? And how is that impacting your road map? >> So, serverless brings a very interesting challenge because they are very, very ephemeral. Like they're ephemeral in some sense. So, we realize there are two things. One is serverless, there's a reason why things are moving faster. It's 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, etc. and telemetry from these serverless environments in a very fast fashion. And that's something that we've done. The second thing we are doing that really works for this environment is afterall it's not about how many times a serverless function ran, it's about the value that it's providing the application that's running on it. And by focusing on a platform that let's 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 ... >> John: And talk about the ecosystems. One of the things I want to ask you guys because we've been seeing a collision between a lot of the different clouds. Clients want multicloud. Well, obviously, we're here at Amazon. They believe they should be the only cloud. But I think most customers would look at either legacy systems with some instrumentation and operational data to edge of the network, for instance. I mean, 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 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. We're kicking the tires on Google. And I got this whole IoT Edge project. SignalFx, instrument that for me. (laughs) 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, the larger companies we see looking at multiple clouds. And they have different workloads running in different clouds, depending on 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 that most of the larger companies want to separate their business process solutions from their runtime architectures. Because they want to have a solution like SignalFx that it doesn't matter who you're using. If you choose to have your analytics intensive workloads in Google Cloud and your eCommerce workloads in Amazon, but you only want one system that will page 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. We provide a lot of that glue across the different environments. >> Do you see that as the preferred architecture with most customers? Cause that makes a lot of sense. I mean, whether you're doing other data services, it kind of makes sense to separate out. Is that consistent? >> To have different applications >> Yeah. >> 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 a portfolio of platforms and 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. >> John: All right, final question. What's the secret sauce for the company? Tell us about the secret sauce. >> Arijit: I think-- >> We got the patents. I heard patents. You don't have to show all this exactly. 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, sort of allows us to address very, very different use cases, including this hybrid environments and what not, 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. Karthik, I've got one last one for you. What's it like being a CEO of a software company in the cloud era today compared to what it's been earlier in our career? >> Well, it's moving very, very quickly, right? I mean, technology always move 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. You know, when we started our company five years ago, that was the first year that AWS eclipsed a billion dollars in sales and Dagra hadn't even launched. It launched a month after we started the company. And then serverless came. And now function architecture is all there. 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 cause the markets are moving way faster, I think, then they were 15 years ago. >> John: Well, Karthik, thanks so much. We appreciate you guys coming on, SignalFx. 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 SignalFx that they should know about. >> Well, I think what people may not realize is how realtime we can actually get. I think most people are used to doing all their monitoring and observation, and they think of realtime in the order of minutes, or if you can get stuff every 30 seconds. We really are the only realtime solution. That's why we say real realtime. We're on the order of seconds. You can build really, really sophisticated analytics and get visibility like you can't anywhere else. So, it's real, realtime. >> And that's soon to be table stakes. TheCUBE is realtime. We're live right here, on theCUBE here, in San Francisco at Amazon Web Services, AWS Summit 2018. 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. (upbeat techno music) (gentle instrumental music)