>> From Union Square in downtown San Francisco, it's theCUBE covering PagerDuty Summit '18. Now here's Jeff Frick. >> Hey welcome back everybody. Jeff Frick here with theCUBe. We're at PagerDuty Summit at the Westin St. Francis in Union Square, historic venue. Our second time to this show, there's about 900 people here talking about kind of the future of dev ops, but going a lot further than dev ops. And we're excited to have a couple of CUBE alumni here at the conference from SignalFX. We've got Arjit Mukarji. >> Mukarji, yeah. >> Thank you. And Karthik Rao, co-founder and CEO of Signal FX. Gentlemen, welcome. >> Thank you very much. >> So what do you do at PagerDuty Summit? >> Well we've been partners with PagerDuty for a long time now, we've known them since the very early days, we share a common investor. But we both operate very squarely in the same space, which is companies moving towards dev ops development and deployment methodologies, leveraging cloud and native architectures. We solve a different part of the problem around monitoring and observation and we partner with them very closely around incident management Once a problem is detected, we typically integrate in with PagerDuty and trigger whatever incident management paths that our customers are orchestrating by PagerDuty. So, it's been really an integral part of our entire work flow since we started the company. So we're very close partners with them. >> Yeah, it's interesting 'cause Jen announced they have 300 integrations or 300+ integrations, whatever the number is, and to the outside looking in, it might look like a lot of those are competitive, like there's a lot of work flow and notification types of partners in that ecosystem, but in fact, lots of different people with lots of different slices of the pie. >> That is good. >> Yeah, absolutely. It's a really big problem space that everyone is trying to solve in this day and age. Some of our competitors are in that list, but you know we partner very closely with PagerDuty. As I mentioned earlier, our focus really is around problem detection and leveraging the most intelligent algorithms, statistical models in real time to detect patterns that are occurring in a production environment and triggering an alert, and typically we're integrating in with PagerDuty and PagerDuty deals with the human elements of once something has been detected, how do you manage that incident? How do you router to the appropriate people? One of the things that's really interesting as this world is changing towards these dev ops models is the number of people that have to get involved is substantially greater than it was before. In the old days, you would have an alert go into a knock and you have a specialist group of people with very specific runbooks because your software wasn't changing very often. In today's world, your software is changing sometimes on a daily basis, and it could be changing across dozens of teams, hundreds of teams in larger organizations. And so, there's a problem on the detection side because companies like SignalFX have to do a really great job of detecting problems as they emerge across these disparate teams, across a much, much, much, larger environment with much larger volumes of data and then companies like PagerDuty really have to deal with a far more complex set of requirements around making sure the right people get notified at the right time. And so they're two very different problems and we're very happy to- and have been partnering with them for a number of years now. >> And again, the complexity around the APIs where the app is running, there's so many levels now of new complexity compared to when it was just one app, running on one system, probably in your own data center, probably that you wrote, compared to this kind of API centric multi-cloud world that we live in today. >> That is exactly right because what's happening is our application architectures are changing 'cause we used to have these monoliths, we used to have three tiers and whatnot, and we're replacing that with the micro-services, loosely cabled systems, and whatnot. At the same time, the substrate on which we are running those services, those are also changing. Right, so instead of servers, now we have virtual machines, we have cloud distances and containers and pods and what-have-you. So in a way, we are sort of growing below too in some sense and so that's why sort of monitoring this kind of complex, more numerous environment is becoming a harder challenge. We're doing this for a good cause, because we want to move faster, we want to innovate faster, but at the same time, it's also making the established problems harder, which is sort of what requires newer tools, which sort of brings companies like us into the picture. >> Right, yep. And then just the shear scale, volume, number of data that's flowing through the pipes now on all these different applications is growing exponentially, right? We see time and time again, so it really begs for a smarter approach. >> Absolutely, I mean on two levels right? The number of minutes of software consumption is up exponentially, right? Since the smartphone came out in 2007, you've got billions of people connected to software now, connected all the time, so the load is up order sum magnitude which is driving, even if you didn't change the architectures, you would have to build out substantially more back-end systems, but now the architectures are changing as well, where every physical server is now parceled up into VMs which are parceled up into containers. And so the number of systems are also up by order sum magnitude. And so there's no possible way for a human to respond to individual alerts happening on individual systems, you're just going to drown in noise. So the requirements of this new world really are, you have to have an analytic spaced approach to monitoring and more automation, more intelligence around detecting the patterns that really matter. >> Right. Which is such a great opportunity for artificial intelligence, right, a machine learning. And we talk about it all the time, everyone wants to talk about those, kind of as a vendor-led something that you buy. Yeah, that's kind of okay, but really where the huge benefit is, companies like you guys and PagerDuty using that technology, integrated in with what you deliver on your core to do a much better job in this crazy increasing scale of volume that's run with these machines. >> Yes, because the systems are becoming so complex that even if you asked a human to go and set up the perfect monitoring or perfect alerting, et cetera, it might be quite a hard challenge, right? So, as a result sort of automation, computer intelligence, et cetera needs to be brought in to bear, because again, it's a more complex system, we need higher order systems that have dealed with them. >> Right. >> You are very, very right, yes. And that's a trend we are starting to see within the product, we are actually focusing a lot on sort of data science capabilities which too are sort of making them more and more sort of machine running and automation. In the future, we have capabilities in the product that can look at populations and identify outliers, look at cyclical problems and identify outliers again. So the idea is to make it easy for users to monitor a complex system without having to get into the guts, so to speak. >> Right. >> And to do it on various sorts of data, right? I think you have an interesting use case that we've been experimenting with recently. >> That's right. >> If you want to talk about that. >> Yeah, so I actually have a talk tomorrow, it's called "Interesting One." It's about monitoring social signals, monitoring humans. So we have these systems, we have these metrics platforms and they are quite generic, the tools that we have nowadays and are sort of available to us are quite powerful, and the set of inputs need not be isolated to what the computers are telling me. Why not look at other things, why not look at business signals? In my case, I'm going to talk about monitoring what the humans are doing on Slack as a way for me to know whether there's something of interest that's going on in my infrastructure, in my service that I need to be aware of, right? And you'll be shocked how surprisingly accurate it tends to be. It's just an interesting thing, and it makes one wonder what else is out there for us to sort of look at? Why confine ourselves, right? >> Right. It's funny because we hear about sentiment analysis in social media all the time, but more in the context of Pepsi or a big consumer brand that's trying to figure out how people feel. But to do it inside your own company on your own internal tool, like a Slack, that's a whole different level of insight. >> You'd be surprised at the number of companies that monitor Twitter to understand whether they have an adage. >> That's right. >> Yeah, because in this day and age, users are on Twitter within seconds if something is perceived to be slow, or something is perceived to be down, they're on Twitter. So there are all sorts of other interesting signals to potentially pull from. >> Right, right. Well and guess what, we were just at AT&T Spark yesterday and the 5G's coming and it's 100x more data'll be flowing through the mobiles, so the problem's not going to get any smaller any time soon. >> No. >> Absolutely. >> So what else have you guys been up to since we last spoke? Continuing to grow, making some interesting moves. >> Absolutely- >> Crossing oceans. >> We've been very, very busy, one of the big areas of investment for us has been international growth, so we've been investing quite a bit in Europe. We have just introduced an instance of our service that's based in a European data center. For a lot of our European-based clients, they prefer to have data locality, data residency within the European Union, so that's something new that we just introduced last month, continue to have a ton of momentum, outed AMIA, they're very much on the cloud journey, and embracing cloud and embracing dev ops, so it's really great to see that momentum out there. >> Right, and clearly with GDPR and those types of things, you have to have a presence for certain types of customers, certain types of data. Anything surprising in that move that you didn't expect or? >> No, I don't know, I'll let you. >> Not in that move, but it's just interesting to see how quickly some of these modern technologies are getting adopted and how- one of the things sort of we talk about a lot in our trade is ephemeral, right? So how things are short-lived nowadays, and you used to lease these servers that used to stay in your data center for three years, then you went to Amazon and you leased your instances, which probably lived for a few months or a few days, then they became containers, and the containers sometimes only for a few hours or for- you know. And then, if you think about serverless and whatnot, it's in a whole different level, and the amount of ephemeral that's going on, especially in the more cloud native companies, was a little bit of a surprise in the sense that, it actually poses a very interesting challenge in how do you monitor something that's changing so fast? And we had to have a lot of engineering put in to sort of make that problem more tractable for us. And it continues to be an area of investment. That to me, was something that was a little bit of a surprise when we started off. Much of this doctorization and coordinating was not yet in place, and so that was an interesting technical challenge as well as a surprise. >> Well I'm curious too as instances, right so there's the core instances that are running core businesses that don't change that much, but it's a promotion, it's a this or that, right? It's a spin up app and a spin down app. Are those even going up on the same infrastructure from the first time they do it to the second time they do it. I mean, how much are you learning that you can leverage as people are doing things differently over and over again as their objectives change, their applications change, they're going to go to market around that specific application. That's changing all the time as well. >> Yeah, so I think the challenge there is to sort of build, at least from a technical point of view, from SignalFX point of view, is build something that is versatile enough to handle these different use cases. We've got new use cases, new ways of doing things are going to continue to happen, probably going to keep on accelerating. So the challenge for us is good and bad, is how do we make a platform that is generic, that can be used for anything that may come down the pike, not only just now. At the second time, how do we innovate to continue to be up to speed with the latest of that's what's going on in terms of infrastructure trends, software delivery trends, and whatnot. Because if we're not able to do that, then that puts us sort of behind. >> Right, right. >> So it's a sort of lot of phonetic innovation, but it's also exciting at the same time. >> Right, right, right. And just the whole concept too, where I think what's best practice quickly becomes expected baseline really, really fast. I mean, what's cutting edge, innovative now unfortunately or fortunately, that become the benchmark by which everything else is measured overnight. That's the thing that just amazes me, what was magical yesterday is just expected, boring behavior today. Alright good, so as we get to the end of the year a lot of exciting stuff, you guys said you're going to be at Reinvent, we will see you there. Anything else that you're looking forward to over the next couple months? >> Just, we're really excited about Reinvent's big show for us, and we'll have some good announcements around the show. And yeah, looking forward to just continuing to do what we've been doing and deliver more rally to our customers. >> Love it, just keep working hard. >> Yep. >> Alright. Arjit, hope your throat gets better before your big talk tomorrow. >> Yeah, that's right. >> Alright, thanks for stopping by Karthik, it was great to see you. >> Great to see you. >> I'm Jeff, you're watching theCUBE, we're at PagerDuty Summit at the Westin St. Francis in San Francisco. Thanks for watching, see you next time.

hi Jeff Rick here with the cube welcome were excited to to get out and talk to startups people that are founding companies when they come out of stealth mode we're in a great position that we get a chance to talk to him early and we're really excited to have a cute conversation with karthik rao the founder and CEO of signal effects just coming out of stealth congratulations thank you Jeff so how long you've been working behind the scenes trying to get this thing going yeah we've been at it for two years now so two years a founder and I started the company in February of 2013 so excited to finally launch and make our product available to the world all right excellent congratulations that's always a great thing we've launched a few companies on the cube so hopefully this will be another great success so talk a little bit about first off you and your journey we have a lot of entrepreneurs that watch a show and I think it's it's an interesting topic as to how do you get to the place where you basically found in launched a company yeah absolutely I started my career at a company at a cloud company before cloud really exists this is a market there's a company called loud cloud oh yeah Marc Andreessen right recent horse or two of the company and we were trying to do what the public cloud vendors are doing today before the market was really all that big and before the technologies really existed to do it well but that was my first introduction to cloud o came out of college and that's where I met my co-founder Phillip Lou as well Phil and I were both working on the monitoring products at loud cloud from there I ended up at VMware for a good run of about seven years where I ran product had always wanted to start a company and then a couple of years ago Phil and I thought the timing was right and we had a great idea and decided to go build signal effects together okay so what was kind of the genesis of the idea you know a lot of times it's a cool technology looking for a problem to solve a lot of times it's a problem that you know and if I only had one of these they would solve my problems so how did the how did that whole process work yeah it was rooted in personal experience my co-founder phil was at Facebook for several years and was responsible for building the monitoring systems at Facebook and through our personal experience and what we'd seen in the marketplace we had a fundamental belief and a vision that monitoring for modern applications is now an analytics problem modern applications are distributed they're not you know a single database running on is system you know even small companies now have hundreds of VMs running on public cloud infrastructure and so the only way to really understand what's happening across all of these distributed applications is to collect the data centrally and use analytics and so that was our fundamental insight when we started signal effects what we saw in the marketplace was that most of the monitoring technologies haven't really evolved in the past 15 or 20 years and they're still largely designed for traditional static enterprise applications where if you get an alert when an individual node is down or a static thresholds been passed that's enough but that doesn't really work for modern apps because they're so distributed right if one node out of your twenty nodes is having a problem it doesn't necessarily mean that your application is having a trough having a problem and so the only way to really draw that insight is to collect the data and do analytics on it and that's what signal okay really because that distributed nature of modern of modern apps and modern architecture yes there are three things that are fundamentally different number one modern applications are distributed in nature and so you really have to look at patterns across many systems number two they're changing for more frequently than traditional enterprise apps because they're hosted for the most part route applications so you can push changes out every day if you want to and then third they're typically operated by product organizations and not IT organizations so you have developers or DevOps organizations that are actually operating the software and those three changes are quite substantial and require a new set of products right and so the other guys are just they're still kind of in the you know fire off the pager alert something is going down it's very noisy yes when you're firing off alerts every time an individual alert goes off when you've got thousands of a DM and we all know that the trend these days is towards micro services architectures you know small componentized you know containers or VMs and so you don't have to have a very sophisticated large application to have a lot of systems it's so do you fit into other existing kind of infrastructure monitoring systems or kind of infrastructure management systems so I'm sure you know it's another tool right guys got to manage a lot of stuff how does that work yeah we are focused on the analytics part of the problem okay so we collect data from any sources so our customers are typically sending us data you know infrastructure data that they're collecting using their own agents we have agents that we can provide to collect it a lot of the developers are instrumenting their own metrics that they care about so for example they might care about latency metrics and knowing Layton sees by customer by region so they'll send us all that data and then we provide a very rich analytics solution and platform for them to monitor all of this and and in real time detect patterns and anomalies so you just said you have customers but you coming out stealth so you have some beta customers already yes we have great customers already now just beta customers right are great console customers awesome yes congratulation thank you very much they're very excited about our product and we you know they range from small startups to fairly large web companies that are sending in tens of billions of data points every day into signal effects right right and again in the interest of sharing the knowledge with all of our entrepreneurs out there you know when did they get involved in the process how much of the kind of product development definition did they did they participate in you said you've been at it for a couple years yeah we've had a lot of conviction about this space from the very beginning because we our team had solved this problem for themselves and in previous experiences but we did include we've been in beta for about six months but better to launch and so over the course of those six months we recalibrated based on feedback we got from customers but on the whole we you know are we philosophy and the approach that we took was was pretty much validated by the early customers that we engaged with okay excellent and so um I assume your venture funded we are can you can you talk about who your who your backers are yes we raised twenty eight and a half million dollars eight million dollars yeah twenty-eight point five million dollars from andreessen horowitz okay with Ben Horowitz on our board okay and Charles River ventures with a lurker on our board and how big are you now time in terms of the company well we're just getting started now right at this is 1 million all that money - well we we've got a great group of engineers or our company is you know and still in the few dozen people stage at this point ok we're planning to invest aggressively in building out our team both on R&D and on the go-to-market side this excellent once you detect patterns and anomalies what's kind of the action steps you work with with other systems to swap stuff out together because now I hear like it's these huge data centers they don't swap out this they don't swap out machines they swap out racks it's soon they'll be swapping out data centers so what are some of the prescriptive things that people are using they couldn't do before by using your yeah I'll give you a great example of that one of our early beta customers they do code pushes very aggressively you know once a week they'll push out changes into their environment and they had a signal effects console open which and we're a real-time solution so every second they're seeing updates of what was happening in their infrastructure they pushed out their code and they immediately detected a memory leak and they saw their memory usage just growing immediately after they did their code Bush and they were able to roll it back before any of their users noticed any issues and so that's an example of these days a lot of problems introduced into environments are human driven problems it's a code push it's a new user gets onboard it or a new customer gets onboard and all of a sudden there's 10x the load onto your systems and so when you have a product like signal effects where you can in real time understand everything that's happening in your environment you can quickly detect these changes and determine what the appropriate next step is and that appropriate next step will depend on your application and who you are and what you're building right so our key philosophies we get out of your way but we give you all of the insights and the tools to figure out what's happening in your arm right it's interesting that really kind of two comes from from your partners you know kind of Facebook experience right because they're pushing out new code all the time when there's no fast and break things right right exactly and then you're at VMware so you know kind of the enterprise site so what if you could speak a little bit about kind of this consumerization of IT on the enterprise side and not so much the way that the look and feel of the thing works but really taking best practices from a consumer IT companies like Facebook like Amazon that really changed the game because it used to be the big enterprise software guys had the best apps now it's it's really flipped for people like Google and Netflix and those guys have the best apps and even more importantly they drive the expectation of the behavior of an application every Enterprise is finally getting it and then are they really embracing it we're definitely seeing a growth in new application development I think you know when I spend a lot of time talking to CIOs at enterprises as well and they all understand that in order to be competitive you have to invest in applications it's not enough to just view IT as a cost center and they're all beginning to invest in application development and in some cases these are digital media teams that are separate from traditional IT and other places it's you know they're they're more closely tied together but we absolutely see a kind of growth in application development in many of these end up looking a lot like the development teams that we see here in the Bay Area you know and companies that are building staffs and consumer cloud apps yeah exciting time so you should coming out of stealth what's kind of your your next kind of milestone that you're looking forward to you have a big some announcements you got show you're gonna kind of watch out we're we're we're gonna see you make a big splash well for us it's it's steadily building our business and so we hope to you know we're launching now and we've got a lot of great customers already and hope to sign on several more and help our customers build great applications about that's our focus again congratulations two years that's a big development project Karthik thank growl the founder and CEO of signal effects just launching their company coming out of stealth we'd love to get them on the cube share the knowledge with you guys both the people that are trying to start your own company take a little inspiration as well as as the people that need the service tomorrow with the cloud with a modern application thanks a lot thank you Jeff thank you you're watching Jeff Rick cube conversation see you next time