 Good afternoon everyone and welcome back to KubeCon where my co-host John Furrier and I are broadcasting live along with Lisa Martin from KubeCon Detroit, Michigan. We are joined this afternoon by two very interesting gentlemen who also happen to be legends on the Cube. John, how long have you known the next few? They made their mark on the Cube with Jerry Chan from Greylock who's one of our most attended Cube guests. He's a VC partner at Greylock and an investor in this company that just launched their new cloud observability platform. Should be a great segment. Well, I'm excited, are you excited? Should I swing this out just a little bit longer? No, I won't do that to you. Please welcome Martin and Jeff from Chronosphere. Martin and Jeff, thank you so much for being here. Thank you for having me. Thank you. I noticed right away that you have raised a mammoth series C, 200 million if I'm not mistaken. That is correct. Where's the company at? Yeah, so we raised that series C a year ago. In fact, we were just talking about it a year ago at KubeCon. Since then, at the time we're about 80 employees or so. Since then we've tripled the head count. So we're over 250 employees. Casual triple. Casual triple of the head count. Luckily, it was the support of Business which has also tripled in the last year. So we're very lucky from that perspective as well. And a couple of other things we're pretty proud of last year. We've had 100% customer retention which is always a great thing to have as a SaaS platform there. Is that a real metric if you've had 100%? I'm kidding. It's a good metric to put out there if you had 100% I would say. That's an A for sure. That's an A for sure. Exactly. A lot of community and L2's had 100% customer retention here at KubeCon this week. And 90% of our customers are using more of the service and therefore paying more for the service as well. So those are great signs for us and I think it shows that we're clearly doing something right on the product side I would say. And last time you were in the Kube we were talking about the right data and not so much a lot of data if I remember correctly. And that was a unique approach. It's a data world on relative observability and you guys just launched a new release of your platform, cloud-native platform. What's new in the platform? Can you share an update on what you guys released? Yeah we did and you bring up a great point. Like it's not just in observability but overall data is exploding. So three things there. It's like A, can your platform even handle the explosion of data? Can it control it over time and make sure that as your business grows the data doesn't continue to explode at the same time? And then for the end users can they make sense of all this data? Because what's the point of having it if the end users can't make sense of it? So actually our product announcement this time is a pretty big refresh of a lot of features in our platform and it actually tackles all three of these particular components. And I'll let Jeff, our head of product, talk to you. You run probably the keys to the kingdom. I do. Product roadmap, people are saying hey at this take this out. You're under a lot of pressure. What makes the platform a great observability product? So the keystone of what we do that's different is helping you control the data, right? As we're talking about, there's an infinite amount of data. The system's getting more and more and more complicated. A lot of what we do is help you understand the utility of the telemetry so that you can optimize for keeping and storing and paying for the data that's actually helpful as opposed to the stuff that isn't. What's the benefit now with observability? With all the noise out in the marketplace, there's been a shift over the past couple of years. Cloud native at scale. You're seeing a lot more automation. Almost a setup to support the growth for more application development. We had a Docker CEO on earlier today. He said there are more applications being deployed in the past year than in the history of open source. So more and more apps are being deployed. More data is being generated. What's the key to observability right now that's going to separate the winners from the losers? Yeah, I think not only are there more applications being deployed, but there are smaller and smaller applications being deployed. Mostly on containers these days more than anything else. Hence this conference gets larger and larger every year. So I think the key is A, can your system handle this data explosion is the first thing. Not only can it handle the data explosion, but APM solutions have been around for a very long time and those were really introspecting into an application. Whereas these days, what's more important is, well, how is your application interfacing with every other application in your distributed architecture there? So the use case is slightly different there. And then to what Jeff was saying is like, once the data is there, not only making use of what is actually useful to you, but then having the end user makes sense of it because we always think about the technology changes. We forget that the end users are different now. We used to have IT operations team operating everything. The developers would write the application just throw it over the wall. These days the developers have to actually operate this thing in production. So the end users of these systems are very different as well. And you can imagine these are folks, your average developer has maybe not operated things for many years in production before. So they need to pick up a new skill set, they need to use new tooling in order to do that. So yeah, it's very different. And you got the developer persona. You got a developer that's building products for builders and developers that are building products to be consumed. So they're not really infrastructure builders. They're just app developers. Exactly, exactly. That's right. And that's what a lot of the new functionality that we're introducing here at the show is all about is helping developers to build software by day and are on call by night actually get in context. There's so much data. Chances of when one of those pages goes off and your number comes up, that the problem happens to be in the part of the system that you know a lot about are pretty low. Chances are you're going to get bothered about something else. So we built a feature we call it collections. That's about putting you in the right context and connecting you into the piece of the system where the problem is to orient you and to get you started. So instead of wading through hundreds of millions of things, you're wading through this stuff that's in the immediate neighborhood of where the problem is. Yeah, to your point about data, you can't let it go unchecked. That's right. You got to understand that and we were talking about containers, again with Docker, nuance point, but oh scan your container but not everyone's scanning the containers. Security nightmare. Right, right. Well, I think one of the things that I loved in reading the notes in preparation for you coming up is you've actually created cloud native observability with the goal of eliminating engineering burnout. And what you're talking about there is actually the cognitive burden of when things happen. We're not just designing for when everything goes right. You need to be prepared for when everything goes wrong and that poor lonely individual in the middle of the night has to navigate that. And observability is just one thing. You know what I mean, like security is another thing. So so many more things have been piled on top of the developer in addition to actually creating the application. It is, there is a lot and observability is one of those key things that you need to do your job. So as much as we can make that easier, that's the better bit. But like there are so many things being piled on right now. That's the holy grail right there because they don't want to be doing good work. They're not observability experts. Exactly, automating that in. So where do you guys weigh in on the automation wave? Everything's automation. Is that kind of a hand waving? Or what's going on? What's the reality? What's actually happening? Yeah, I think automation I think is key. You hear a lot of AI ML ops are there. I don't know if I really believe in that by having a machine self heal itself or anything like that. But I think automation is key because there are a lot of repeatable tasks in a lot of what you're doing. So once you detect that something goes wrong, generally, if you've seen it before, you know what the fix is. So I think automation plays a key role in the sense that once you detect it again the second time, the third time. Okay, I know what I did the previous time. Let's make sure we can do that again. So automation I think is key. I think it helps a lot with the burnout. I don't know if I'd go as far as to say. Burnout's a big deal. Well there's an example again in the stuff we're releasing this week, a new feature we call Query Accelerator. That's a form of automation. Problem is, you got all this data, mountain of data. Put you in the right context so you're at least in the right neighborhood. But now you need to query it. You got to get the data to actually inform the specific problem you're trying to solve. And the burden on the developer in that situation is really high. You have to know what you're looking for and you have to know how to efficiently ask for it so you're not waiting for a long time. We built a feature. You tell us what you want. We will figure out how to get it for you efficiently. That's the kind of automation that we're focused on is how can we accelerate and optimize what you are going to do anyway rather than trying to read your mind or predict the future? Yes, Savannah. It's a community forward. Yeah, so I'm curious. You clearly lead with a lot of empathy, both of you, and putting your, well you probably have experience with this as well, but putting yourself in the mind of the developer, what's that like for me from a product development standpoint? Are you doing a lot of community engagement? Are you talking to developers to try and anticipate whether they're going to be needing next in terms of your offering or how does that work for you? Oh, for sure. So I run product. I have a lot of product managers who work for me. Somebody that I used to work with, she was accusing me of what she called me an anthropologist of a product manager. I get these kind of very good design school vibes from you, both of you, which is cool. And the reason why, she said the way you do this is you go and you live with them in order to figure out what a day in their life is really like, what the job is really like, what's easy, what's hard. And that's what we try to aim at and try to optimize for. So that's very much the way that we do all of our work. And that's really also highlights the fact that we're in a market that requires acute real-time data from the customer. And it's all new data. Well yeah, it's all changing. The tools change every day. I mean, if we're not watching how. To your point, you need it in real-time as well, right? The whole point of moving to cloud native is you have a reliable product or service there. And like, if you need to wait a few minutes to even know that something's wrong, like you've already lost at that point, you've already lost a ton of customers. Potentially you've already lost a ton of business. To your point about the community earlier, one other thing we're trying to do is also give back to the community a little bit. So actually two days ago, we just announced the open source of a tool that we've been using in our product for a very long time. But of course our product is a paid product, right? But actually open source, a part of that tool, thoughts that the broader community can benefit as well. And that tool actually, it's called Prom Lens. It's actually, the Prometheus project is the open source metrics project that everybody uses. So this is a query builder that helps developers understand how to create queries in a much more efficient way. We've had it in our product for a long time, but we're like, let's give that back to the community so that the broader community of developers out there can have a much easier time creating these queries as well. What's been the feedback? We only, now it's two days ago, so I'm not exactly sure. I imagine it's great. They're probably planning with it right now as we talk. Exactly, exactly, for sure. I imagine great. You guys mentioned burnout before and we've heard this a lot. Now, you mentioned in terms of data, we've been hearing and reporting about it against the security world, which is also data-specific. Observability ties right into security. Yep. How does a company figure out, first of all, burnout's a big problem. It's more and more data coming. It's like, it doesn't stop. And the breaches are coming too. How does a company know when they need that their observability strategy's broken? Is there signs of burnout? Is there signs of breaches? I mean, what are some of the tell signs that if I'm a CISO, I go, you know what? Maybe I should check out Chronosphere. When do you guys match in and go, we're a perfect fit to solve that problem? Yeah, I would say, you know, because we're focused on the observability side, less on the security side, some of those signals are like, how many incidents do you have? How many outages do you have? What's the occurrence of these things and how long does it take to recover from these particular incidents? How upset are your customers? Which one? How upset are your customers? Exactly. And one trend was a year. A lot of churn happening. Exactly. One trend we're seeing in the industry is that 68% of companies are saying that they're having more incidents over time, right? And if you have more incidents, you can imagine more engineers are being paid, you're being woken up and they're being put under more stress. And one thing you said that would be very interesting is, you know, I think generally in the observability world, you ideally actually don't want to figure out the problem when it goes wrong. Ideally what you want to do these days is figure out how do I remediate this and get the business back to a running state as quickly as I can? And then when the business isn't burning, let me go and figure out what the underlying root cause is. So the strategy there has changed as well from the APM days where like, I don't want to figure out the problem in real time. I want to make sure my business and my services running as it should be. And then separately from that, once it is, then I want to go and dig it in. Understand that as soon as it's going to happen, that we're ready to close that. Isolate the fire. Exactly, exactly. And you know, you can imagine, you know, the whole movement towards the ICD, like generally when you don't touch a system, nothing goes wrong. You deploy a change. First thing you do is not figure out why you change break anything, get that back, like, underplay that change, roll that change back, get your business back to a state. And then take the time where you're not under pressure, you're not going to be burnt out to figure out what was it about my change that broke everything. So, yeah, got it. Well, it's not surprising that you've added some new exciting customers to the roster. We have, we have. You want to tell the audience who they might be? Yes, it's been a few big names and last year we're pretty excited about. One is Snapchat. I think everybody knows that application and one is Robin Hood. So, you know, you can imagine very large, I would say tech-forward companies that have completed their migrations to Cloud Native or well on their way to Cloud Native and we like helping those customers for sure. We also like helping a lot of startups out there because they start off in the Cloud Native world. Like, if you're going to build a business today, you're going to use Kubernetes from day one, right? But what I've actually interestingly seen more and more of is traditional enterprises who are just early, pretty early on in their Cloud Native migration, they're now starting to adopt Cloud Native at scale and now they're running to the same problems as well. The Gartner data last year was something like 85% of companies had not made that transformation. So, I mean, that's looking at larger scale companies, obviously, so you're finished right on the pulse. They have finished it, but a lot of them are starting it. So we're seeing pilot projects and testing and cadence and I imagine it's a bit of a different pace when you're working with some of those transforming companies versus those startups that are just getting rolling. And you know, you have a lot of legacy use cases you have to like, if you're a startup, you can imagine there's no baggage, there's no legacy. You're just starting brand new, right? If you're a large enterprise, you have to really think about, okay, well, how do I get my active business moved over? But yeah. And how do you guys see the whole Cloud Native scale moving with the hyperscales like AWS? You got a lot of multi-Cloud conferences. We call it SuperCloud in our narrative, but there's now this new set of common services being identified. We're seeing a lot more people recognizing with Kubernetes that you know what, you can get some common services maybe across clouds. Wasabi's doing storage. We got Minio's doing some storage. Yeah. Cloudflare, I mean, starting to see a lot more non-hyperscale systems. Yeah, I mean, and I think that's the pattern there. And I think it's especially for enterprise at the top end, right? See, a lot of companies are trying to de-risk by saying, hey, I don't want to bet maybe on one cloud provider. I sort of need to hedge my bets a little bit. And Kubernetes is a great tool to go do that. You can imagine some of these other tools you mentioned is a great way to do that. Observability is another great way to do that. All the cloud providers have their observability or monitoring tooling, but it's really optimized just for that cloud provider, just for those services there. So if you're really trying to run either your custom applications or a multi-cloud approach, you really can't use one cloud provider's solution to go solve that problem. Do you guys see yourselves in that unifying layer? We are a little bit as that lay because it's agnostic to each of the cloud providers. And the other thing is we actually like to understand where our customers run and then try to run their observability stack on a different cloud provider because we use the cloud ourselves. We're not running our own data centers, of course, but it's an interesting thing where everybody has a common dependency on the cloud providers. So when USA1 of AWS, I hate to call them out, but when USA1 of AWS goes down, imagine half the internet goes down, right? And that's the time that you actually need observability and every other tooling there. So we try to find out where do you run and then we try to actually run you elsewhere. But yeah. I like that. And nobody wants to see the ugly bits anyway. And we all know when we're all using someone when everything stops as people on the internet. So I really love that. Martin, Jeff, thank you so much for being here with us. What's next? How do people find out? How do they get one of the jobs since you're 3Xing your employee growth here? We're hiring a lot. I think the best thing is to go check out our website, chronosphere.io. You'll find out a lot about our careers, our job openings, the culture we're trying to build here. Find out a lot about the product as well if you do have an observability problem. That's the best place to go to find out about that as well. Fantastic. Well, if you want to join a quarter of a billion dollar rocket ship over here and certainly a unicorn, get in touch with Martin and Jeff. John, thank you so much for joining me for this very special edition. And thank all of you for tuning in to theCUBE, live here from Motor City. My name's Savannah Peterson and we'll see you in a little bit.