 Well, welcome to this CUBE Conversation. I'm John Furrier in the Pellawealth, those studios for theCUBE. I'm your host here with Jeremy Burton, who's the CEO of Observe, Inc. Just launched their product. They launched their company before that. They're doing great. Jeremy, great to see you. No, no, thanks. Always great to be back on. Yeah, there's certainly a lot going on. The sort of my day job, which is running, observing my night job, which is obviously working with Snowflake. And it's all great to see both going on at the same time. You've done very well with the Snowflake relationship being a board member and all and being in that ecosystem. And a lot of people are doing well on this shift. You're part of it again. You're on the inside, but also now on the outside building a business. And it's exciting because it's highly competitive. It's a big category and it's really moving fast. So give us a quick update on what's going on in the landscape and your recent launch you just had. Yeah, I mean, I think most businesses be the new businesses, cloud native businesses, as we call it, are born in the cloud businesses, are old. They're really trying to deliver like new services to reach customers. And it's harder for an incumbent business because they've got to do a lot of reinvention or modernization or I guess the term de jure is digitization. And ultimately a lot of that means, they got to start writing software again. Comes naturally maybe to the newer companies, the SaaS companies, but the biggest of the big have really got to start writing software again. And as they push a new code into production every day, they got to make sure it works. And so this new market for observability, I think really helps people troubleshoot problems with these new applications. And the goal obviously is to make sure that you avoid customer churn and any kind of a bad experience, which I think is what every SaaS company dreads. It's a big problem. You know, getting all these metrics in one place is really key. I want to get into your launch 2.0. We could bring in Dave Vellante, my co-host with theCUBE always a favorite to bring on the analysis. I know Dave dug in heavily on the launch. Dave, good to see you. Got you. Hey guys, how you doing? How you doing, Jeremy? Good to see you. Yeah, John, I mean, Jeremy, your first launch was really a company launch. Now you're giving the product update. So what do we need to know? Yeah, so I mean, you're right. When we first went out, it was sort of like, this is observable and this is what observability is. We sort of glossed over a lot of product details because I think like a lot of startups, we had a chunk of initial functionality but we knew there was a lot missing. And so, previously, in the last six months since we did that announcement, we're now trying to fill out the product. And a couple of the big features that we knew we needed, I mean, one was metrics. And although we've always been able to ingest metrics, most people maybe know time series type data, we haven't built all of the functionality in our language or in the user interface for the user to be able to manipulate them. So that was a big lift, which we got done. And then very closely related, once you've got metrics, the next thing people want to do is they want to start alerting on things. Hey, tell me when this metric is out of whack. And one of our sort of big differentiators are one of the things that we always bring to bear on any kind of data we manage is to link data together. So we're always trying to provide more context for the data that the user's looking at. So metrics and alerts, they sort of tie into our core value prop, have been able to relate data. Chairman, if I don't mind, you don't mind answering, I'd like to get your take on this because one question I ask all these analytics companies is, yeah, data is great, data lakes, and it's all good about getting the data in this kind of environment. But most people just want to shape the data and they want to just get insights out of it fast. They don't want to do a lot of prep. They want to have it in position, whether it's querying it or just having it available. And sometimes it's not always there. So they're constantly reshaping it. And so the idea of just shaping it and making it some insights, which is basically quickly distilled out of it, turns into I got to reshape, I got to go back to the well, if you will, or the lake in this case, and pull out the data. How are you guys solving that? Because this is like the simple construct, make it easy. Yeah, it's funny. I mean, even going right back to data warehouse and days of all, the big frustration is ETL, right? It was so painful to transform the data into the right shape to get into the database. I mean, some of these projects, I mean, I think like 70% of those projects never even completed. The big difference now, and certainly a lot of the data we deal with is it's unstructured inherently. It's generated by machines. We just sort of dump it all into observe and then we let users pause it on the fly. And so it can be one shape one day and a different shape the next. And then we'll backfill all of the data automatically into the new shape that the user's defined. So these systems have really got to be set up to do like ad hoc analysis. If you only did a couple of updates to your application a year, the environment wasn't that dynamic. It didn't change very much. And most of the problems you saw, you've seen before. And now with code changing every day, the application looks different every day. So the issues that you see look different every day. So it's really, really important that these systems are incredibly dynamic and don't get locked into one particular shape from the get go. Jeremy, you took a somewhat different approach. There have been a lot of companies in this space will choose to do like a purpose built database specifically for observability and metrics and so forth. And that's talking about a heavy lift that could take many years. You're choosing to put your emphasis to your heavy lift elsewhere. That obviously gives you a time to market advantage. Can you talk a little bit about that philosophy and what that gets you? Yeah, it was probably one of the biggest decisions that we made when we founded observe was do we build our own database? Like almost everyone who'd gone before or do we go with a commercial offering? And when we first started building against Snowflake three years ago, we weren't actually sure it could do what we wanted to do. And so it was one of the biggest areas of technical risk. But certainly at this point, we've got ourselves very comfortable that it's going to be able to do what we need it to. I mean, it saves us building a database. And I mean, like this week at the Snowflake Summit, I think Snowflake just announced an additional 30% compression on data. It's like, okay, so we did nothing. And now, you know, all of those folks who are sending terabytes a day to us, they get an extra 30% compression. And so that's the value of building on a commercial platform. And Snowflake has got 300 engineers working away on their database and they deliver benefits to us. And we focus on the application. So we know, obviously, Frank, we talked to him all the time and he's unequivocal about your cloud. We're not doing a halfway house. We're not doing on-prem. But you're, I'm sure familiar with the A16Z narrative from Martín Casado and Sarah Wong. Basically the premise for those of you who don't know is that, you know, for startups and as you're growing, cloud is a no-brainer, but at scale, it becomes 50% of your cost of revenue, becomes an albatross to your operating leverage. What do you think about that? Do you buy that? Do you ever see like a Snowflake going back on-prem? What's your thoughts on that? I mean, I feel like, yeah, I mean, we used to put wells in our back gardens and generators in our basement. And you know, they're cheaper too, right? But the problem is I've got to dig a fricking well, right? And then what am I not doing while I'm digging my well? And so I don't know. I mean, I get the general premise, but I don't want half the company going and building, not just like a database, all of the infrastructure that's underneath. Why? Because it's not what our customers pay for. Like if we can add more value on top of that platform, we can charge more. So it's sort of like, well, if all those companies had actually started out building their own infrastructure and everything, would they have built the application experience that made them successful? I mean, I get the paper, I think it's very, very well-written. I'm just not sure it's a big distraction. Like we don't care about the underlying infrastructure, we just want it to be there. And if we were doing that, then we might observe might not be as good as it currently is. Well, I think it's a question to me, John, is where's the customer value? Is the customer value in the valuation of the company, or is it in what you can deliver and how fast you can deliver? Hold on, let me just put context to Martin Casado's little thing there. It's the paradox paper. So there's a paradox there. And his thesis is, do you focus on cost of goods sold, or do you drive more revenue? And his whole part point was, at some point you got to look at the cost, right? And I then weaved into him, I hit him up on Twitter immediately and I said, oh, so you must have a bunch of companies who aren't growing, right? So because if you look at what's going on on the McKinsey paper, we covered this at our last startup event, startup event is that the companies that are driving new revenue, it's coming from a lot of replatforming and refactoring, but also net new use cases. So a lot of clients are making more money by introducing new products. So that's a new revenue. So you are either going to be on one side of the paradox. You're going to be inside of, I'd rather refactor for new revenue than save money by reducing costs. So I still think we haven't cleared the runway on this growth. So I think there's plenty of trillions left to create. So I'm on the side of, I'm on the side of, if you're worried about pennies in the cloud to the well point that Jeremy mentioned, then you might either look at other things. Yeah, it's about growth. I mean, I feel certainly younger companies and observe and I mean, also Snowflake that we were just talking about. I mean, the Snowpark announcement this week of going and running Spark jobs, well, yeah, they could do that or they could go build a data center, I mean, to reduce costs. And to me, the right call is to do more with customers data. And I don't know, the somewhat, I mean, the counterpoint to that would be, well, let's make it a more profitable business. But to me, that doesn't add up for the majority of new companies. Jeremy, how should we think about this space? Because you have, you got guys like Splunk that have been doing log analytics for a while now. You got the Elk stack coming in with an open source and it's open source, but it's also brings complexity. You got big players now like Cisco who's made the acquisition of APD. You got kind of who's now a legacy in New Relic. We talked about purpose-built databases before. So everybody's coming at this from all different sides. How do you think about it, look at it and where do you fit? Yeah, I think you've got the big players. I mean, you've named quite a few of them then and look, most of my career, I've been on that side, right? And typically what you do as a big company is it's harder to innovate. And so you use your balance sheet for innovation. You go buy innovation and then you try and integrate. And that, I mean, it's very, very doable. But it just takes a long time. And the risk is that as you integrate, you're never really getting your architecture on a solid foot and you're sort of bandating things together and we're selling multiple things to the same customer versus really coming back to first principles and saying, well, how should this really have been built? So I actually tend to worry a little bit less about the bigger companies. And then look, there's a set of startups that have from like Observe from first principles thought, well, if we were to build a system to look at all the telemetry data that applications and infrastructure generate, then how would we do it? So, we certainly banking on the fact that the more modern architecture, as time goes by, because I still think we're in baseball terms, we're probably in the first inning still of observability, that modern architecture will come to bear over time. We'll be able to do things that the other guys won't be able to do. And one of those is actually the simple task of relating data, why? Because all of our data is in one place and it's in a relational database, it's that simple. I think one of the things that's worth calling out and it's pointing out is that you guys are also on the snowflake, so you're riding that wave to your point about, I agree with by the way, you're in, you're focusing on innovation, not kind of moving the deck chairs around on stuff. But I want to get a question about this event you had because one of the things that you guys are becoming known for is to eliminate the headaches for SREs and DevOps engineers who have been conditioned to accept the old ways of kind of hand-crafting and the people who do it first tend to be the most bloody when they come out of it. But as it becomes easier, right, and we discovered this at the Red Hat Summit, Dave, and Jeremy is that this notion of an SRE is becoming more prominent in engineering schools and computer science programs as kind of a replacement for IT. I don't mean like IT is dead, but like IT is turning into AI ops, GitOps, whatever people want to call it, it's cloud native. So the notion of an SRE is on the teams of these modern development teams. So you're seeing this end-to-end workflow visibility. So that means that if they're going to have that, they're going to have these new team members, SREs and Dev and Sec together, and they need the data. So this is where you guys are, and I think you guys hit this, and correct me if I'm wrong, if you don't mind explaining, how does the observability equation change when the teams change? Because teams are changing in the modern architecture. Yeah, I mean, it's probably a cliche, but there's tooling and then there's process change. And as people move to things like continuous delivery, they get maniacally focused on delivery of new features and new capabilities to the customer, and then focused on the experience that the customers have in. And I think the role of the SRE becomes critical because they try and understand not just what the customer is doing with the application, but the problems that the customer is experiencing. And that's got to work hand in glove with the engineering team, who ultimately is going to implement the new features that the customers want. And one of our sort of big missions here is to lessen the burden on the DevOps team, which has been provided in essentially the infrastructure and tooling for the SRE and engineering teams to use. Right now, they're overwhelmed to deliver just the basics. And candidly, the engineering and SRE teams are not happy with what's been delivered. So if we can lighten the burden on the DevOps team, you should then get a richer experience for the SRE and engineering teams for them to do ultimately what they want to do, which is customer satisfaction and engage the customers in new ways. And it's just the quality of what is surface to those teams right now is just not very good because it's hard. So, Jeremy, you mentioned the first inning. So your uniforms are still white. You got the starting picture. How's it feeling? How's the arm feel? What's the early customer interactions like? Where are you getting traction? Yeah, it's been interesting because when you start with no customers, I mean, obviously we've been on the wall here at work, our first customer, 2,500 bucks. And I've never been so thrilled to get a sales order for $2,500. But no, we've targeted largely SaaS companies or tech-centric companies. And one of the guys that we're going to be highlighting is Topgolf, which I'm sure anyone who's been there and enjoys going and hitting the golf ball around and playing Angry Birds. But look, they're a tech-centric company. Customer experience for them is everything. They're not in the IT business per se, but IT enables them to deliver these amazing customer experiences. And so when they've got issues, when they need to troubleshoot problems, they need to do it quickly. And so we tend to help those kind of companies improve the experience they're providing. But yeah, we've got about 20 paying customers so far. It's very different actually getting a customer paying you money versus a sort of friend or family member saying, yeah, I'll give that a whirl. It certainly shut up and it's the point on the feedback. And really that's what we need right now. I mean, I think every startup strives to get to what we call market fit, which is can we sell this product repeatedly to thousands of customers? I don't think we're quite there yet, but we certainly have got the volume of customers and the feedback coming back to engineering that can get, we know what to build, put it that way to get us to that point. Well, smart what you do when you're starting with the SaaS companies, the service providers. So you're not jumping off the cliff into the enterprise for every custom deal. Get the product market fit and then understand the retention and then expand your TAM from there. Yeah, you try and build a solid foundation and you know when you go to the enterprise, you're going to need features like role-based access control and more of the manageability capabilities. But if you were to build all of that out first, then you wouldn't know whether you've got a compelling experience for an SRE or an engineering team. And so what you tend to do is defer a lot of the management type capabilities, try and build compelling features. When you see the features are compelling, then you sort of build out the supporting infrastructure that allows you to go to bigger companies. So it's, I mean, the enterprise is why I've always dealt in sort of enterprise software is it's not easy. And my old boss Joe Tucci had a great saying on this, like, you know, if you're in a hurry, take a bit more time. And I think that sort of our mantra right now, we're in a hurry, everyone wants to go, but like if we don't get the product right, it'll bite us later. You know, the other expression in the enterprise is everyone makes it all complicated and everything. It's all too complicated. Which is the enterprise, if it's not complicated, they make it more complicated, right? So welcome to the edge too. No, there's every edge case you can think of, which is why you've got to be careful early on because we can't afford, we don't have time to deal with edge cases. We've got to deal with, you know, what's up the power alley. And then once we've got that going, then you can start to deal with more of the edge cases. Yeah, we're in the same boat on our end too. Chairman, I'd like to get to end the segment here by giving a quick update and recap of the event real quick and what you guys are doing as a company and what you did at the launch. And where your sweet spot is, what are you looking for? What's the type of customers that you're looking for right now? What is that power alley that you're focused on? Yeah, three to 4,000 SaaS companies in North America is where we're after. And we tend to help folks on more efficient troubleshooting of applications. We help them with tool consolidation and we help them with security audit and compliance. So there, if you like the key use cases that our initial customers have brought us into. And yeah, we started off really focusing on logging and log analytics. And then yesterday we added to that, you know, the metrics, the time series, data analysis and also the alerting. And we've also got really running in-house the more APM like visualizations around tracing. So maybe a little bit of a hint of what's coming in later this year. Yeah, I want to get your thoughts too. There's been some commentary on Twitter. Like, you know, we want to get things simpler, a little bit more calmer. I think there's a comment like it's not the mid, we want more of the Midwest vibe, not so much that the coastal elite Silicon Valley, shiny new toy. What's your take on that? Because it's culturally the shift. People want to reduce the tools. I mean, they got the tool shed of, you know, every single tool that's been shipped to every company comes out is selling a tool. Don't be a fool with a tool as the, as the expression says. No, no, if we're not careful observability, we can define it to be this nichey thing. And, you know, in Silicon Valley out here, it's probably the worst because there's almost this attitude of, well, I'm not sure you're smart enough to do observability. You're doing it all wrong. And our approach, I think, and I think the market in general wants, like they've got issues and our approach needs to be, well, show us what you're doing today. Give us the data that you're generating today. We'll make that better and then we'll show you where the blind spots are. And so you can have a much more iterative approach to get into that desired end goal, but we've got to stop defining observability as almost this niche that Silicon Valley companies use. I mean, I always joke that we want more of our customers watching Netflix, not listening to engineers from Netflix explain observability. Yeah, I tell you, they call it the flyover enterprise now. It's a new category of enterprise. Yeah, I want to encourage people to go check out the launch. I presume it's up in your website, Jeremy. So now it's a typical mumbo jumbo. You guys have a lot of fun. You start it off, you're like, what? And it's just, it's pretty hilarious. And then, you know, you get into the meat of it, but so good job on that. Yeah, thanks. Yeah, we had a local San Francisco comedian and that helped us out. She was awesome. I think it's been a software engineer at Survey Monkey back in the days. Right, right. Always great stuff, Jeremy. Thanks for coming on theCUBE. Thanks for the update. And we'll see you around. See you in real life soon, very soon. Great, thanks guys. Always a pleasure to be on. Okay, it's theCUBE conversation. I'm Chevrolet Dave Vellante on analysis on this CUBE conversation segment. Soon we'll be in real life. We'll be at Mobile World Congress for our first physical event in a long, long time. First event since 2019 for Mobile World Congress. A lot has changed since that time. And we'll be on there for the first hybrid event. And then we have two more hybrid events coming up as well. Adios Reinforce as well as Adios Reinvent. CUBE Virtual and CUBE Physical all together. Stay with us. Thanks for watching.