 TheCube presents HPE Discover 2022, brought to you by HPE. Welcome back to theCube's coverage of HPE Discover 2022. We're here at the Venetian Convention Center in Las Vegas, Dave Vellante for John Furrier. Cam Amir is here as the director of technical alliances at Cribble. Cam, good to see you. Good to see you too. Thanks for coming. Cribble, cool name. Tell us about it. So let's see, Cribble has been around now for about five years, selling product for the last two years. Fantastic company, lots of growth. Started there in like 2020, and we're roughly 400 employees now. So what do you do? Tell us more. Yeah, sure. So I run the technical alliances team, and what we do is we basically look to build integrations into platforms such as HPE, GreenLake and Ezraal. We also work with a lot of other companies to help get data from various sources into their destinations or, you know, other enrichments of data in that data pipeline. You know, you guys have been on theCUBE, Clint's been on many times. Ed Bailey was on our startup showcase. You guys are successful in this overfunded observability space. Yeah. So you guys have a unique approach. Tell us about why you guys are successful on the product and some of the things you've been doing there. Yeah, absolutely. So our product is very complementary to a lot of the technologies that already exist. And I used to joke around that everyone has these like pretty dashboards and reports, but they completely glaze over the fact that it's not easy to get the data from those sources to their destinations. So for us, it's this capability with Cribble Stream to get that data easily and repeatedly into these destinations. Yeah, you know, Cam, you and I are both at the Snowflake Summit, at the Johns Point, they were like a dozen observability companies there. And, you know, really beginning to be a crowded space. So explain what value you bring to that ecosystem. Yeah, sure. So the ecosystem that we see there is, there are a lot of people that are kind of sticking to like effectively getting data and showing you dashboards, reports about monitoring and things of that sort. For us, the value is how can we help customers kind of accelerate their adoption of these platforms? How to go from like your legacy sim or your legacy monitoring solution to like the next gen observability platform or the next gen security platform. And what you do really well is the integration and bring those other toolings to do that? Correct, correct. And we make it repeatable. How'd you end up here? HP? Yeah. So we actually had a customer that actually deployed our software on the HP Ezreal platform. And it was kind of a light bulb moment that, okay, this is actually a different approach than going to your traditional, you know, AWS, Google, et cetera. So we decided to kind of hunt this down and figure out how we could be a bigger player in this space. I, you saw the data fabric announcement. I don't have crazy about the term. Data fabric is an old NetApp term and then Gartner kind of twisted it. I like data mesh, but anyway, it doesn't matter. We kind of know what it is, but when you've seen announcement like that, how do you look at it? What does it mean to Cribble and your customers? So what we've seen is that, so we work with the data fabric team and we're able to kind of route our data to there as a data lake. So we can actually route the data from again, all these very sources into this data lake and then have it available for whatever customers want to do with it. So one of the big things that I know Clint talks about is we give customers this, we sell choice. So we give them the ability to choose where they want to send their data, whether that's, you know, HP's data lake and data fabric or some other object store or some other destination. They have that choice to do so. So you're saying that you can stream with any destination that customer wants? For the most of example, what are the popular destinations? Yeah, so a lot of the popular destinations are your typical object stores. So any of your cloud object stores, whether it be AWS S3, Google Cloud Storage or Azure Blob Storage. Okay, and so you can pull data from any source? I'd be very careful. But what we've seen is that a lot of people like to kind of look at traditional data sources like Syslog and they want to get it to us of the next gen SIM, but to do so, it needs to be converted to like a web hook or some sort of API call. And so, or vice versa, they have this brand new Zscaler, for example, and they want to get that data into their SIM, but there's no way to do it because the SIM only accepts it as a Syslog event. So what we can do is we actually transform the data and make it so that it lands into that SIM in the format that it needs to be and easily make that a repeatable process. So, okay, so wait. So not as a Syslog event, but in whatever format the destination requires? Correct, correct. Okay, what are the limits on that? I mean, this is... Yeah, so what we've seen is that customers will be able to take, for example, they'll take this Syslog event, it's unstructured data, but they need to put it into say, common information model for Splunk or elastic common schema for elastic search or just JSON formatted for elastic. And so what we can do is we can actually convert those events so that they land in that transformed state, but we can also route a copy of that event in unharmed fashion to like an S3 bucket for object store for that long-term compliancies. And you can route it to any, basically any object store, is that right, is that always the sort of target? Correct, correct. So on the message here at HPE, first of all, I'll get to the marketplace point in a second, but it's cloud to edge is kind of their theme. So data streaming sounds expensive. I mean, you know, so how do you guys deal with the streaming egress issue? What does that mean to customers? You guys claim that you can save money on that piece. It's a hotly contested discussion point. So one of the things that we actually just announced in our 3.5.0 release yesterday is the capability of getting data from Windows events or from Windows hosts, I'm sorry. So a product that we also have is called Cribble Edge. So our capability of being able to collect data from the edge and then transit it out to whether it be an on-prem or self-hosted deployment of Cribble or maybe some sort of other destination object store. What we do is we actually take the data in transit and reduce the volume of events. So we can do things like remove white space or remove events that are not really needed and compress or optimize that data so that the egress costs to your point are actually lowered. And your data reduction approach is compression? It's a compression algorithm? It's a- So it's a combination. Yeah, so it's a combination. So there are some people they'll do is they'll aggregate the events. So sometimes, for example, VPC flow logs are very chatty and you don't need to have all those events. So instead, you convert those to metrics. So suddenly you reduce those events from high volume events to metrics that are so small and you still get the same value because you still see the trends and everything. And if later on down the road, you need to reinvestigate those events, you can rehydrate that data with Cribble Replay. And you'll do the streaming in real time? Is that right? Yeah. So Kafka, is that what you would use or other tooling? So we are complementary to a Kafka deployment. A customer's already deployed and they've invested in Kafka. We can read off of Kafka and feedback in the Kafka. If not, you can use your tooling. If not, we can be placed in that. Ken, talk about your observations in the multi-cloud hybrid world because hybrid, obviously everyone knows it's a steady state now on public cloud, on premise edge, all one thing. Cloud operations, DevOps, data as code, all the things we talk about. What's the customer view? You guys have a unique position. What's going on in the customer base? How are they looking at hybrid and specifically multi-cloud? Is it stitching together multiple hybrids or how do you guys work across those landscapes? So what we've seen is a lot of customers are in multiple clouds. That's gonna happen. But what we've seen is that if they want to egress data from say one cloud to another, the way that we've architected our solution is that we have these worker nodes that reside within these hybrid, these other clouds I should say. So that transiting data first egress costs are lowered but being able to have this kind of easy way to collect the data and also stitch it back together, join it back together to a single place or single location is one option that we offer customers. Another solution that we've kind of announced recently is search. So not having to move the data from all these disparate data sources and data lakes and actually just search the data in place, that's another capability that we think is kind of popular in this hybrid approach. And talk about now your relationship with HPE, you guys obviously had customers drove you to the Green Lake, obviously what's your experience with them? And also talk about the marketplace presence, is that new? How long has that been going on? Have you seen any results? Yeah, so we've actually just started our journey into this HPE world. So the first thing was obviously the customers bringing us into this ecosystem and now our capabilities of, I guess getting ready to be on the marketplace. So having a presence on the marketplace has been huge, giving us kind of access to just people that don't even know who we are, being that we're a five-year-old company. So it's really good to have that exposure. So that's... So you're going to get customers out of this? That's the idea. HPE is going to bring in a mark, that's the idea of their Green Lake is that partners fill in. What's your impression so far of Green Lake because there seems to be great momentum around HPE and opening up their channel, their Salesforce, their customer base? Yeah, so it's been very beneficial for us. Again, being a smaller company, and we are a channel-first company, so that obviously helps bring out the word with other channel partners. But HPE has been very open-armed, kind of getting us into the ecosystem and obviously giving the good word about Cribble to their customers. So you'll be monetizing on Green Lake, right? That's the goal. That's the goal. What do you have to do to get into a position? Obviously, you got a relationship, you're in the marketplace, do you have to write to their APIs or do you just have to, is that a checkbox? Describe what you have to do to monetize. Sure, so we have to first get validated on the platform. So the validation process validates that we can work on the as we're all Green Lake platform. Once that's been completed, then the idea is to have our logo show up on the marketplace so customers say, hey look, I need to have a way to get transit data or do stuff with data, specifically around laws, metrics, and traces into my logging solution or my SIM. And then what we do with them on the back end is we'll see this transaction occur right to their API to basically say who this customer is. Because again, the idea is to have almost a zero-touch kind of involvement. But we will actually have that information given to us and then we can actually monetize on top of it. And the visualization component will come from the observability vendor, is that right? Or is that somewhat, do you guys do some of that? So the visualization is, right now we're basically just the glue that gets the data to the visualization engine. As we kind of grow and progress our search product, that's probably will have more of a visualization component. Do you think your customers are going to predominantly use an observability platform for that visualization? I mean, obviously you're going to get there. Are they going to use Grafana? I mean, or some other tool? Yeah, yeah. I think a lot of customers, obviously depending on what data and what they're trying to accomplish, they will have that choice now to choose, you know, Grafana for their metrics logs, et cetera, or some sort of security product for their security events. But same data, two different kind of use cases and we can help enable that. Cam, I want to ask you a question. You mentioned you were at Splunk and Clint, the CEO, co-founders, was at Splunk too. That brings up the question I want to get your perspective on. We're seeing a modern network here with HPE, with Aruba, obviously cloud's kind of going next level. You've got on-premises, Edge, all one thing, distributed computing basically. Cyber security, a data problem that's solved a lot by you guys and people in this business. Things your data's available. Machine learnings are growing and powering AI like you read about. What's changed in this business? Because, you know, Splunking logs is kind of old hat, you know, and now you've got observability, unification is a big topic. What's changed now? What's different about the market today around data and these platforms and tools? What's your perspective on that? I think one of the biggest things is people have seen the amount of volume of data that's coming in. When I was at Splunk, when we hit like a one terabyte deal, that was a big deal. Now it's kind of standard, you're going to do a terabyte of data per day. So one of the big things I've seen is just the explosion of data growth. But getting value out of that data is very difficult and that's kind of why we exist because getting all that volume of data is one thing, but being able to actually assert value from it, that's kind of... And that's the streaming core product, that's the whole. Get data to where it needs to be for whatever application needs, whether it's cyber or something else. Correct. What's the customer uptake? What's the customer base like for you guys now? How many customers you guys have? What are they doing with the data? What are some of the common things you're seeing? Yeah, I mean, it's the basic blocking and tackling. We've significantly grown our customer base and they all have the same problem. They come to us and say, look, I just need to get data from here to there. And literally the routing use case is our biggest use case because it's simple. And you take someone that's an expensive engineer and an operations engineer, instead of having them going and doing the plumbing of data of just getting logs from one source to another, we come in and actually make that a repeatable process and make that easy. And so that's kind of just our very basic value add right from the beginning. Automate that, automate that, make it repeatable. I said, what's in a name? Where'd the name come from? So Cribble, if you look it up, it's actually kind of an old shiv to get to siphon dirt from gold, right? So basically just, that's kind of what we do. We filter out all the dirt and leave you the gold bits so you can get value. It's kind of what we do on theCUBE. It's kind of the gold nuggets. Get all these highlights. Hit Twitter, the gold nuggets, these things. Great to have you on. Okay, thank you. Thank you for coming on, explaining that sort of you guys are filling that gap between, hey, all the observability claims, which are all wonderful, but then you got to get there. They got to have a route to get there. That's what you guys do. Cribble rhymes with Cribble. Dave Vellante for John Furrier. Covering HPE Discover 2022. You're watching theCUBE. We'll be right back.