 Hey, welcome back everyone to KubeCon's coverage and Cloud NativeCon theCUBE. I'm John Furrier, your host with David Nicholson, Kube analyst, cloud analyst, co-host. We've got two great guests. Kube alumni, Jerry Chen, needs no introduction. Partner at Greylock Ventures, have been on theCUBE many times. Almost like an analyst, Jerry. Great to see you. I'm like a guest analyst. And Martin Mao, who's the CEO, co-founder of Chronosphere, just closed a whopping $200 million series, Sea Round Businesses, booming. Great to see you. Thanks for coming on. Thank you. Hey, first of all, congratulations on the business transaction. Congratulations. Who would have known that observability and distributed tracing would be a big deal, Jerry? You predicted that in 2013. I think we predicted jointly Cloud was going to be a big deal in 2013, right? And I think the rise of Cloud creates all these markets behind it, right? This, you know, I would say, you got to ride a wave bigger than you. And so this ride on Cloud and scale is the macro wave. And, you know, Martin and Rob in Chronosphere, they're just drafting behind that wave. Bigger scale, higher carnality, more data, more apps. I mean, that's where the puck's gone. Yeah, Martin, all kidding aside, you know, we joke about this because we've had conversations where the philosophy of you pick the trend as your friend that you know is going to be happening. So you can kind of see the big waves coming, but you got to stay true to it. And one of the things is that we talked about is, what's the next Amazon impact going to look like? And we were watching the rise of Amazon. You go, if this continues, a new way to do things is going to be upon us. Okay, you got DevOps, now Cloud native. But observability became really a key part of that. It's like almost, I call it the network management of the cloud. In a new way. You guys have been very successful. There's a lot of solutions out there. What's different? Yeah, I'd say for Chronosphere, there's really three big differences. The first thing is that we're a platform. So we saw an observability platform. And by that, I mean, we solve the problem end to end. If you're thinking about observability and monitoring, you want to know when something's wrong, you want to be able to see how bad it is, and then you want to be able to figure out what the root cause is. Often there are solutions that do a part of that problem, might solve a part of the problem. Really, we offer a platform that does the whole thing end to end. That's really the first thing. Second thing is we're really built for, not just the cloud, but cloud-native environments. So microservices architecture on container-based infrastructure. And that is something that we perhaps saw coming maybe 2017, 2018. But luckily for us, we were already solving this problem at Uber. That's where myself and my co-founder were back in 2014, 2015. So we already had the sort of perfect technology to solve this problem ahead of where the trend was going in the industry. Therefore, a purpose-built solution for this type of environment, a lot more effective than a lot of the existing ones. It's interesting, Jerry. You know, do you invest in companies that have their problem that they have to solve themselves as the new thing versus someone who says, hey, there's a market. Let's build a solution for something I don't really know. That's kind of what's going on here, right? It's the reason why we love founders like Martin and Rob that come out of these. Hyper-Skeletal comes at Uber. It's like, we say they've seen the future. You know, like they were at Uber. They looked at the existing solutions out there trying to scale Prometheus or, you know, data dogs and the vendors. And it didn't work. It fell over. It was too expensive. And so Martin and Rob saw the future. Like, this is where the world's going. We're going to solve it. They built M3, it became Chronosphere. And so I don't take any credit for that. You know, I just like find folks that can see the future. And that was Rob and Martin. But they were solving their problem. No one else had anything. There was no general purpose software that managed service you could buy. You guys were cutting your teeth into solving the pain you had at Uber. When did you guys figure out like, oh, wow, this is pretty big? Probably about 2017, 2018 with the rise in popularity of Kubernetes. That's when we knew, oh wait, the whole world is shifting to this. It's no longer relegated to just Uber and the big tech giants of the world. And that's when we really knew, okay, the whole world is shifting here. And again, it's sheer blind luck that we already have the ideal solution for this particular environment. It wasn't planned. It wasn't what we were planning for back then, but yeah, everything sort of lined up. It makes a lot of difference when you walk into customers and say, we had this problem. I can empathize with you. Not just say we got solved. Exactly, exactly. Jerry, how do they compete in the cloud? We always talk about how Amazon and Azure want to eat up anything that they see that might, you know, something on AWS. Yeah. There's the castle in the cloud opportunity here. Castle in the cloud. I mean, you know, we talked last time about how to fight the big three, Amazon, Azure, and Google. And I think for sure they have basic offerings, right? You know, Google boss stack driver years ago, they've done basic briefs offerings, basic modern offerings. I think you have like basic simple needs. It's a great way to get started, but customers don't want kind of a piecemeal solution all the time. They want a full product. Data dog shows a better user experience, but full product is going to, you know, the better mouse trap, the world will be a path to your door. So first you can build a better product versus these kinds of point solutions. Number two is at some scale and some level complexity, those guys cannot handle like the demanding users that Kurnersphere is handling right now, like the door dash of the world. And finally, you don't want the Fox guard in the hen house. You know, you don't want to say, like, Amazon monitoring. You can't depend on Amazon service monitoring or Amazon apps or a Google service monitoring Google apps. Having something that's independent and multi cloud that can do all the things Martin said, you know, see a triage and fix your issues is kind of what you want. And that's where the market's going. So I do believe that cloud guys will have an offering the space, but in our cast on the cloud research, we saw that, yeah, there's a plenty of startups being funded. There's plenty of opportunity and the scoreboard between Splunk, DataDog and all these other companies that there's a huge amount of market and value to be created in this space. So at the time when you, you know, necessity is the mother of invention, you're at Uber, you have a practical problem to solve and you look around you and you see that you're not the only entity out there that has this problem. Where are we in that wave? So not everyone is at cloud scale. Not everyone has adopted completely Kubernetes and cloud native for everything. Are we just at the beginning of this wave? How far from the beach are we? We think we're just at the beginning of this wave right now. And if you think about most enterprises today, they're still using on, they're not even in perhaps in the cloud at all, right? You're still using like perhaps APM solutions on premise. So if you look at that wave, we're just at the beginning of it, but when we talk to a lot of these companies and you ask them for their three year vision, Kubernetes is a huge piece of that because everyone wants to be multicloud, everyone wants to be hybrid eventually and that's going to be the enabler of that. So we're just in the beginning now, but it seems like an inevitable wave that is coming. So obviously people evaluated that exactly the way you're evaluating that. Thus, the funding. Because no one makes that kind of investment without thinking that there is a multiplier on that over time. So that's a pretty exciting place to be. Yeah, I think to your point, a lot of companies are running into that situation right now and they're looking at existing solutions there. For us, it was a necessity because there wasn't anything out there. Now that there is, a lot of companies are not using their sort of precious engineering resources to build their own, they would prefer to buy a solution because this is something that we can offer to all the companies and it's not necessarily business differentiating technology for the businesses themselves. So you guys have distributed tracing in that observability platform, that's the news. And you mentioned you got this in good bid, you're doing some good business. Is scale the big differentiator for you guys or is it the functionality? Because it sounds like with clients like DoorDash, it looks a lot like Uber, they're doing a lot of stuff too. I'm sure everyone, Instacart and other people do the same kind of thing. That's scale, massive amount of consumer data coming in on the edge. Is that the differentiation or do you work for the old, one main street enterprise? Right, that is simply part of the differentiation and for our product thus far before we added distributed tracing for monitoring and metric data, that was the main differentiation is the sheer volume of data that gets produced so much higher. I'm really excited about distributed tracing because that's actually not just a scale problem, it's a space that everybody can see the potential of distributed tracing, yet no one has really realized that potential. So our offering right now is fairly unique, it does things that no other vendors out there can do and we're really excited about that because we think that that fundamentally solves the problem differently, not just at a larger scale. Yeah, well I got you here because you're an expert. What is distributed tracing? Yeah, it's a great question. So really if you look at distributed tracing it captures the details of a particular request. So a particular customer interaction with your business and it captures how that request flows through your complex architecture, right? So you have every detail of that at every step of the way and you can imagine this data is extremely rich and extremely useful to figure out what the underlying root causes of issues are. The problem with that is it's very bit boasts, it's a lot of data gets produced, a ton of data gets produced, every interaction, every request. So one of the main issues in this space is that people can't afford cost effectively to store all of this data, right? So one of the main differentiates for our product is we made it cost-efficient enough to store everything and when you have all of the data you have far better analytics and you have far- Machine learning is better, everything's better with data. That's the thesis, right? Yeah. Right. What's the blind spot out there for customers as cybersecurity is always looking for corners and threats that some people say it's not what you don't, it's what you don't see that kills you. That's a tracing issue, that's a data problem. How do you see that evolving in your customer base of clients trying to get a handle of the visibility into the data? Yeah, I think right now again it's very early in the space of people just getting started here and you're completely correct where you need that visibility and again, this is why it's such a differentiator to have all the data. If you can imagine with only 10% of the data or 1% of the data, how can you actually detect any of these particular issues, right? So data is key to solving that problem. Well, great to have you guys on expert and congratulations on the funding, Jerry. Great to see you. Take a minute to give a plug for the company. What do you guys do? And I'll see you close around the funding. $200 million, congratulations. What are you looking for, for hiring? What are your milestones? What's on your plan? Plan. Yeah, so with the spanning it's really to continue to grow the company, right? So we're sort of hiring, as I told you earlier, we are, we grew our revenue this year by 10x in the 10 months of this year thus far. So our team hasn't really grown 10x. So we need to keep up with that growth. So hiring across the board on engineering side, on the go-to-market side, and just continuing to meet that demand. And you have a headquarters, you're virtual, you don't mind. Yeah, we've gone completely distributed now. We're mostly in the U.S., have a bunch of folks in Seattle and in New York. However, we're gone completely remote. So hiring anyone in the U.S., anywhere in Europe at all. Jerry, well, I got you here. What's your investment thesis now? You've got Castles in the Cloud. By the way, if you haven't seen the research from Greylock, Jerry and the team called Castles in the Cloud, you can Google it. What's your thesis now? What are you investing in? You know, it is hard to always predict the next wave. I mean, my job is to find the great founders. But I'd say the three core areas are still the same. One is this cloud disruption. To Martin's point, we're so early days of the wave. I'd say number two, these vertical apps, different SaaS applications be finance, healthcare, construction, all are changing. I think healthcare, especially the past couple of years through COVID, we've seen that's a market that needs to be digitized. And finally, FinTech, we talked about this before, everything becomes a payments company, right? And that's why Stripe is such a huge juggernaut. You know, I don't think the world's all Stripe, but be it insurance, payments, you know, stuff from crypto, whatever. I think FinTech still has a lot of market to grow. Making things easier is a good formula right now. If you can reduce complexity and make something easy in every market, you're going to see to be the formula. What's aligned like the next great thing is making today's crappy thing better, right? So the next great show is making this cube crappy thing better. We're getting better. We're working every day. On our 11th season or year, we're calling things Seasons now. Episodes and Seasons are streaming. I can't wait to all the Seasons drop on Netflix, which has been to awesome all. The Cube Plus and NFTs for our early videos. They'll be worth something because they're not that good. Jerry, of course you're great. Thank you for coming on. Thank you guys. Thanks for having us. Thanks for coming on. Cube's coverage here in a physical event, 2021 Cloud Media.com, CubeCon. I'm John Furrier, Dave Nicholson. Thanks for watching.