 Hey everyone, welcome to SuperCloud 5, the battle for AI supremacy. I'm your host, Lisa Martin. Thrilled to welcome back one of our many time alumni to the program, Clint Sharpe is here, the CEO and co-founder of Cribble. Clint, great to see you. Thanks for coming on the program today. Yeah, thank you so much for having me, Lisa. So since we last spoke, Cribble hit a pretty big milestone. 100 million in ARR, so passing that actually. Talk about that as a milestone for the organization and some of the key lessons that you've learned along the way. Yeah, first of all, I mean, revenue is a reflection of the value that we provide to customers. And so, first and foremost, it's due to our customers and the great value that we're providing to them. We're one of the fastest growing companies in infrastructure software for that reason. It's faster than just about everybody else in the business, fourth fastest in infrastructure software behind Wiz, Hashie and Snowflake and just slightly ahead of Datadog. So it's great company to be in. Part of that reason is also our net dollar retention is 145%. That means that our customers are not only buying but they're growing and they're growing really quickly. And one third of the Fortune 100 are Cribble customers. And so we're very, very proud of what value we've been able to provide to them. I think part of the reason for that is we're also expanding. And so we're expanding from a single product company to a multi-product company. We have a great new analytics offering in our search product. We have a great new data collector product with Edge. We're expanding our cloud into Europe as well as well as expanding the company into Europe. And that's a huge milestone for us. And I think, as far as learnings go, I think the key thing is just keeping customers first and always that's one of our core values. We innovate from first principles. We do things differently here. We try to look at problems that customers have unique and different for our customers and go provide value to make it easy for them to manage the growing tide of data. Their data is growing in a 25% compound growth rate. Their budget is not. And we're there to help them with that mission in solving their data problems. I love that. That's a great alignment in terms of customer need, customer challenge. Double click a little bit. You talk about Edge. We're going to be more than double clicking into Cribble Edge in a minute. But I'd love to get your thoughts on Cribble's global expansion and why that is also an important milestone that company's achieving. Well, first, in order to expand globally, you have to be at a reasonable scale, right? I mean, expanding globally as a company, if people ever end up running a software company like I've learned to, there's a ton of work that goes into just establishing yourself in a country. Like, how do we figure out how to employ people over there? How do we figure out how to comply with the local laws? How do we find out, is the problem that we see in Germany the same as the problem that we see in the US? And so there's a lot of learnings in there. And then also expanding, since we are a SaaS company and expanding the product into Europe requires a lot of technical work behind the scenes to expand to multiple regions and expand into those territories. And I think we're providing, I think the problems that we see in EMEA are very, very similar to the problems we see in US. They have data growth problems, just like everybody else, but they also have a lot of data residency challenges and data sovereignty challenges that we're also helping them to address. And I think that's a unique set of problems that we're helping them address over there. Well, as you mentioned, the expansion is a multifaceted task and really initiative for any organization to take on its complex. Congratulations on the work that you guys have done so far. I'm sure the customers are very much appreciative of the efforts, the ongoing efforts to do that. I'd love for the audience to understand, speaking of expansion and transitions, cripples a transition from an observability pipeline company to a data engine for IT and security. That's a big transition. It's been in the cards since the very beginning. And when we started building the engine, which is the engine that powers all of our products, streams processing, analytics of data at rest, collecting data, these are all kind of multiple facets of the same problem. And so cripple software was built from the very beginning with the aim that we knew we wanted to help customers analyze data as well as move data, as well as collect data. And so the positioning update is really recognizing our transition into a multi-product company. We started with Cripple Stream. That's where we make most of our money today. It is a pipeline, it's a limited router. It allows you decouple sources and destinations and get data into wherever you want. We expanded with Edge to be able to move the ability to route data to multiple places right at the collector and manage thousands and thousands of collectors centrally. So that's a core value proposition. And we're super excited about our search product. We got more to talk about that on this interview today. The search product is the first search-in-place analytics solution that gives you the ability to analyze machine data, telemetry data, all types of classes of data that IT and security have no matter where that is. It could be in your existing solutions. It could be in your existing indexing solutions. It could be in a data lake. And that's where we're seeing the biggest opportunity is customers want to store petabytes up to exabytes of data cheaply in the cloud, in object storage. And so we're giving them the ability to analyze massive amounts of data at rest very cost-effectively. Because again, their data is growing so rapidly and their budget is not growing so rapidly that they're having to come up with a portfolio of ways of managing this data at rest. And search is really aimed at helping them solve that problem. Can you talk a little bit more, Clint, about how customers are influential in the direction that Kribble is going and some of the decisions that it's making from a search perspective, for example? I imagine you guys are a lockstep with customers helping you really kind of define the direction. Absolutely. And so at our conference over the summer, my co-founder and CTO asked the audience, how many of our features did we develop? Do you think we're done in collaboration with customers? And we confidently said 100%. There's not a single thing that we're building here that is not directly in alignment. And we're also our own internal customers as well. So Kribble Cloud is one of the largest customers of Kribble Edge and Kribble Search. And so our SREs operate a service just like everybody else operates a service. And so we get learnings from there. We get learnings from the unique requirements of selling into financial services, into government, into telecommunications, into online services. And all these people have unique requirements. So it's really, really important that we listen first and then act second so that we can build them the products that are gonna provide them the most value. I love that, listen first, act second. All right, let's talk about some of the news here. Kribble just announced support for Amazon EKS. Talk about what that means for customers. You obviously talked about the huge focus on customers and their needs that you guys have. But what does it mean for them? And why is this important? So obviously Kubernetes is a maturing engine for running compute. All the major cloud providers have a version of hosted Kubernetes. But we find that the problem is just not yet solved for our customers. Getting data out of their Kubernetes clusters remains a challenge. And there's a lot of competition in data collection for getting data out of Kubernetes. There's a lot of open source agents. There's a lot of proprietary agents. But I think what makes Kribble Edge different than everything else that we've seen in the market is the ability to centrally manage, the ability to teleport into an in node to introspect and understand what the running workloads are happening there in real time. The ability to be paired with Kribble Search so that we can search data at the edge directly without having to egress it. In a lot of cases, a lot of this data that they're using especially for troubleshooting purposes has a pretty rapidly decaying value over time. I need to search it right now, but 24 hours from now it's just not really all that interest anymore. I don't tend to go back like long periods of time. So the ability to have a rotating buffer at the edge that you can search and never have to go store actually provides them a lot higher value. They don't have to centralize that data. They can decentralize that data. And it's also working hand in hand with our partnership in Amazon Security Lake. So we can easily grab all the data out of the Kubernetes clusters, get that data in Amazon Security Lake, and Search can also work well with that because we can search the data in place in Amazon Security Lake. Unlike anything other solution in the market we don't have to move the data out of Security Lake. And so our customers are seeing a ton of value with pairing up data collection with their security efforts. Open up that hood if you will, Clint, in terms of some of the key business benefits that customers are going to be able to get from Cribble Edge and search and their unique combination. Yeah, so it's all about, I've got way more data than I have money. And so how can I reuse the resources that I'm already paying for? So if I have a Kubernetes cluster, that is a sunk cost. I'm running my compute workloads there. I'm running my applications on top of those compute workloads. And if I have to move log data, metric data, tracing data to another solution, I'm now paying for that data again. I'm paying for that data to be stored somewhere else. I'm paying for that data to be processed somewhere else. So if I can utilize, and by the way, the average utilization in most of these clusters is not 100%. It's usually more like 30, 50, 70%. So I have compute capacity and I have storage capacity that's sitting there that is a sunk cost, that I can now move my observability workloads, my security workloads onto, and be able to get a significantly more cost effective way of managing this massive amount of data. So the cost benefit savings seem pretty significant in terms of what you're talking about. What are some of the other key features that are delivering big business impact for your customers? Yeah, so data routing is at the core of what Edge and Stream do. And so if you ask me what Cribel sells, I usually say choice. It's the ability for customers to live in a complex ecosystem full of many, many, many tools. My background was as a practitioner prior to becoming a software vendor and it used to annoy me to no end that vendors come in and say, hey look, just replace everything you have with my thing. And that's just not the reality of most of our customers are enterprises, mature enterprises that have been making decisions for decades. And all those decisions were the right decision at the time that they made that decision. And so Cribel I think is a little unique as a vendor in that we really are Switzerland. We believe in working with everybody in the space. And so the routing capabilities of Stream and Edge really allowed them to say, hey look, I need this data to go to multiple places. My security team has one set of tools. My observability team has another set of tools. Why do I need two data collectors? Why do I need two data processors? Let's be able to take one feed, put it in the right place and manage the data in the right place for the right data. So you're Switzerland, you're living in reality as Cribel. What's been some of the feedback from the developers so far and the security folks? Yeah, I think it's really, what I hear from our customers as they're using our products is like, you guys really get me. Like this product feels like it was built by somebody who actually knows what problems I'm solving. And it's intuitive and it works. And that delights me to know in because I use the products, everybody at the company who's technical in some way uses the products, the majority of our company internally has taken our own education. They've been certified in how to use these products. And so they're really just crafted with love for the particular set of people that we sell to. They're under sold to. They're under marketed to. They're just not, there's not a lot of vendors who are focused on kind of SRE, DEVA. I mean, certainly there's a lot of observability vendors et cetera, but from a data company perspective, most people think of data as tabular. And we see all the different types of data that our customers have. And we give them functions and operators and ways to work with that data that go after the very unique different types of data that they have that, that is not the same type of data that the business has. I feel like this is a, Jerry McGuire, you had me at hello moments planning with your customers there. I couldn't pass that up. But I'd love to understand the AWS partnerships ongoing, talk about that and really kind of the impact that it delivers to Chicoville as a business and your customers. For sure. So I mean, AWS, we run our whole cloud on AWS. They're the leading cloud provider for a reason. But they do not universally solve all challenges for their customers. And so they're a very partner friendly organization. And I've always liked that about working with AWS. So one of the key partnerships that I mentioned earlier is on Amazon Security Lake. And I think that that's just a really great new product offering from them. And I'm hearing from my customers out in the field of all the announcements that have happened over the last couple of years. That's repeated back to me. The customers are very interested in the value proposition of Amazon Security Lake. And we help them in two ways. One, we help them get data to Amazon Security Lake so we can get data to them in OCSF format so that all of the tools that are designed to read data out of Security Lake can have the data properly formatted as you're getting in there. And we have integrations for a dozen or more different vendors that are not natively supported by Security Lake to get data into Security Lake. And then as I mentioned earlier, search is the first of its kind to do search in place where we give people the ability to analyze the data in Amazon Security Lake without having to move it. Most of the solutions in the market today take the data that's at rest in Security Lake, they lift it up and then they send it to another solution for processing. So you're really storing the data twice. And so with Gribble Search, you can performantly analyze terabytes to petabytes of data at rest in Security Lake without having to move it. And you pay only for the compute that you're consuming. So you're paying us, it's like a light switch. You're paying us literally for the usage. So if you're not getting value out of it, you stop paying. That sounds like a massive differentiator plan. Double click on that. I'd love to learn for the audience to learn a little bit more on that. Yeah, so it gets a little technical, but in Security Lake, the data is stored in what's called parquet format. And parquet is an optimized columnar format for doing analysis of very, very large data sets. AWS, things like Athena can analyze this data natively. That's like a SQL-centric interface. And so usually that's what you find with more like business analysts. But our customers are security customers, our operational customers are used to a more search-centric experience for getting that data. So we offer you an experience that's a pipe-delimited query language. It's very familiar with products that you've used in the past. And we can performantly analyze that data because AWS is already making the data available in a format that very easy to analyze, massive data sets very rapidly, but you have to support being able to analyze that data in S3 at rest. And we built search very specifically to help people get value out of data and data lakes. And so, you know, these are new, like the, you know, Security Lake is a pretty new product. Data lakes in general are pretty new in observability. And so we are early to market, but I think that this is where the market is going. And it's definitely a future of how we're going to analyze this type of data. I love that early to market, really being led by the customers, but also the ecosystem. We talked about AWS, but I know that Kerbal's partner ecosystem has had a lot of expansion this year, CrowdStrike, Exibeme, Elastic. Talk about why these partnerships and the ecosystem is so important to Kerbal and its direction. For sure, back to those choices. Customers made a choice. Maybe they're, you know, let's take EDR, for example. There's a lot of competition in that marketplace. I think CrowdStrike, we've got a great partnership with them. We've done an OEM deal to help on their log scale offering to help get data into log scale. But maybe they're a Microsoft customer. Maybe they're Sentinel one customer. Maybe they're, maybe you're an AWS shop. Maybe you're an Azure shop. Maybe your, you know, customers make the choices that are well outside the control of what we can tell them to do. And so we really believe in meeting the customers where they're at. If you're an Exibeme customer, great. Like Exibeme has a fantastic solution. We just announced a brand new partnership with Elastic that I'm really, really excited about. Elastic is a phenomenal vendor. They're providing, you know, excellent security and observability solutions across the market. And so we really just want to meet our customers where at it's all about being customers first and we're going to work with anybody in the space if we can help our customers get more value out of their solutions. I love that. It's all about meeting customers where they are interoperability and choice best for customers. I know that's critical to the DNA at Cribble. Talk about some of the, as we were kind of wrapping up here, what are some of the key trends that you guys are paying attention to as we round out 2023 and head into 2024? One that I like to talk about that I think is interesting is that the cloud migration is far from over. And I think, you know, the press especially, you know, tends to grab things in the first part of the hype cycle. So we're all talking about generative AI and we're definitely making investments here and you'll see product announcements from us in the coming months around generative AI. But, you know, when I was a customer, you know, in the practitioner side in the late 2000s and early 2010s, we had to have a cloud strategy. Those companies that were starting to talk about cloud strategy in the early 2010s are just now starting to actually move to cloud it. So we're seeing, you know, very large institutions, which were staunchly on-premises institution, saying like, okay, nope, now's the time. Like we're actually going to go to cloud. And one of the interesting trends that I've seen is that security departments are actually leading here. And so historically they've been somewhat, you know, kind of reserved about going to cloud, but now they've seen, hey, the business is making a decision that we're going to cloud. So I'm going to put my workloads in there first. And one of the first workloads that they're moving are logs. Logs are big, they're expensive. It's most of the data that we process. And so the allure of being able to store data cheaply in object storage or in Amazon security lake, et cetera, is so important to them that can save so much money by going to this approach that security is actually leading in the transition to cloud, which is not something I'm hearing a whole bunch of people talk about elsewhere, but it's something that I'm certainly observing amongst our customers. Do you see some like significant title shifts? We're going to have to have you come back on and talk about that. But I'd love to know in terms of title shifts or even kind of what's next, your crystal ball, your magic eight ball for Cribble over the next six to 12 months. What do you see that you can share with us? Yeah, so I mean, as I mentioned, search what is early to market and it's in our cloud product. It's available in a consumption model. Working to get as many people, we have a free tier by the way. So anybody who thinks this is interesting and what I'm talking about, you can go to Cribble.cloud, you can sign up and driving adoption of our cloud products of our search products, our international expansion. We've kind of laid all this groundwork. Now it's time for us to really go out and take it to market, get customers on that product, get them talking about it, getting them talking to other customers and talking about all the value that they're getting out of there. And any developer, any end user who thinks that analyzing data at rest in S3, analyzing data at the edge sounds interesting. I encourage them to go, sign up for our free tier and get some value. I love this, Clint. Thank you so much for joining us on the program talking about Cribble, its evolution, Cribble Edge, Cribble Search, what you're doing to really meet customers where they are and help them solve problems. Thank you so much for joining us. Once again, on theCUBE, we appreciate your insights and your time. Thanks, Lisa. It was a pleasure and I had so much fun. Absolute pleasure. We want to thank you for watching SuperCloud 5, the battle for AI supremacy. We'll see you next.