Speaker 1: This is Techstrong TV.
Alan Shimel: Hey everyone. We’re back here at KubeCon and it’s bustling, man. It’s a crazy big floor with a lot of people walking around, so we hope you like this. This is a little different than we usually do. Usually people can’t see the background because the cameras face this way, but we usually have sort of the typical background that you see at some of these other booths. But we wanted to give people kind of a flavor that we’re alive here.
Tucker Callaway: We’re in the middle of it.
Alan Shimel: We’re in the middle of it. So kind of like if you ever watch Sunday night football, they always have that. So that’s what we were shooting for. But anyway, let me introduce you to Tucker Callaway. Tucker is the CEO of a company called Mezmo. Now, some of you may have heard of, I think it was Log DNA.
Tucker Callaway: Before. Yep.
Alan Shimel: And they pivoted. Was it about four years ago?
Tucker Callaway: About two years ago now.
Alan Shimel: Two years ago.
Tucker Callaway: I’ve been here for four, but big change was two years ago, renamed.
Alan Shimel: Renamed to be Mezmo and a slightly different mission, let’s call it. And then I had a chance to catch up with Tucker at RSA last, I guess it was last April.
Tucker Callaway: April. Yeah.
Alan Shimel: This year it’s May. So I think it was around then last year. And for those of you who want to catch that interview, it’s actually available on Techstrong TV. If you look up RSA 2023, it’s there. But so Tucker, before we get into that, let’s back up. Mezmo. Not everyone out here. Look, not everyone out here knew Log DNA either, so don’t worry about it.
Tucker Callaway: Fair enough. Yeah.
Alan Shimel: Let’s start there. Let’s talk about the mission.
Tucker Callaway: Yeah, so the mission of Mezmo is essentially to help people with their telemetry data. So we’ve found that there’s really kind of three main problems in the telemetry data space. There’s too much of telemetry data. It’s not in the right format. It’s not in the right location. So that was kind of one of our founding kind of principles of solving.
Alan Shimel: Yeah, I think that.
Tucker Callaway: Solving the problem.
Alan Shimel: Those were three rock solid.
Tucker Callaway: Hard to debate.
Alan Shimel: Hard to debate. That’s the good way of putting that. And also, quite frankly, all three problems are like they compound each other.
Tucker Callaway: They do.
Alan Shimel: So it’s like you have too much data. That’s a big problem, but we have too much data that we don’t know how to categorize, so that exponentially makes that problem worse. So these are-
Tucker Callaway: Compounding problems. No question about it.
Alan Shimel: No doubt about it. So when we were at RSA, you felt like you were kind of on the cusp of a realization, right? You were going to help customers. Why don’t you? Well, you tell the story better than me.
Tucker Callaway: So as we were talking about earlier, we had just launched this new product capability, the telemetry pipeline at RSA. We’ve got a lot of great customers and great experience since then. When we think about the core value of what it provides, it helps people with cost, it helps people get better insights and helps people enforce compliance. What we were surprised by though in the last couple months, is how little people actually understand of their data.
In fact, we’ve put a lot of time and effort as an industry into getting control of our applications and getting control of our infrastructure, but we haven’t really gotten control of our telemetry data yet, and that’s like the big opportunity that we see. But with that, in order to get that value I described, people didn’t need to understand their data better. And so that was a big revelation for us.
And we just launched our data profiling capability that helps people categorize and understand baseline, to do the schema management for their data, which is a really strong foundation for data ops principles applied to telemetry data. Then the next thing we found after we solved that problem was now that people understood their data and they were able to optimize it because they understood it. They also realized that the context and telemetry data changes rapidly. So for example, you don’t want to store all this data because you don’t need it until you need it, and then you really need it.
Alan Shimel: I’ll take a little, they do want to store the data because people are data hoarders.
Tucker Callaway: The data hoarder. Yeah.
Alan Shimel: It’s when they get hit with the bill for storing all that data, they say, “Wait a second, I don’t need all this data. Not at that price.”
Tucker Callaway: Something has to give somewhere.
Alan Shimel: Exactly.
Tucker Callaway: And so what we realized though was if you take the bookend of this value, we think of as understand, optimize and respond, we talked about understand and optimize the response stage was a really important one for us. So when new context comes in, the pipeline can change its behavior and change its optimizations to account for the current flow of data and the current needs. So if you’re sampling down to 20% and you see an event, you see performance, you can rehydrate, reprocess, dynamically change the responsiveness of the pipeline and get all the data to the right location for the right people, which helps address the cost problem, but also gives you the full visibility that you need.
Alan Shimel: If one was going to do a business school case study on this, someone who’s not from this industry would say, “Hey, just the fact that you discovered that most of these organizations don’t even know how much data or what data they have would be enough to build a company around.”
Tucker Callaway: Yeah, I’d like to think so.
Alan Shimel: No, it’s logical. It makes sense, but it’s not, it’s the threshold. Because I think you’d hit the nail on the head here, Tucker, which is once they recognize that, now there’s a whole new vista of realization for them of, “Holy mackerel, I got all this data, now I want to start understanding it. Wow. I’m seeing stuff I never thought I’d see. Maybe I intuitively thought I had, but I got the goods now.”
Tucker Callaway: We like to think of that as being mesmerizing, right?
Alan Shimel: Okay, I love it. Mesmerized by Mezmo.
Tucker Callaway: I couldn’t not take the shot, but that was just-
Alan Shimel: Yeah, that was your shot.
Tucker Callaway: That’s the derivative of the name.
Alan Shimel: I feel used. I feel used.
Tucker Callaway: I got back into it a little bit.
Alan Shimel: So now you’re mesmerized and now like, “Oh my God, what can I do with this?” And that really becomes the business. And I guess that’s now where you are.
Tucker Callaway: The next step for us is clearly that. Yeah, and I think there’s two plays on that, too. There’s a, “What do I do with it? Help me, tell me what to do. Give me the best practices that from all of your customers, what should I do?” And so we’ll be coming out probably later in the spring with something that actually allows you to simulate how that data might look when optimization’s applied to it so you can start to make those decisions more effectively.
But then the second phase of that, too, is that also won’t be sufficient for certain organizations that want to look at their data as a strategic advantage. And they’re going to be looking for ways to take actions and drive more insights out of that data. And so the way we see that, we see that through recipes. We’ll give you the standard offerings, but then you have the ability to go in and edit as code and go do the things you need to do to go drive more value out of that data. If you’re ready for advanced yoga moves in the data space.
Alan Shimel: Got it, got it, got it. My background is security.
Tucker Callaway: Yep.
Alan Shimel: Started a security company in 2001, and it was right when we were moving from IDS to IPS. So intrusion detection to intrusion prevention. Same thing with vulnerability management. We were moving from just finding vulnerabilities to patching, remediating, not always patching, remediating. Seemed like who wouldn’t want that? No brainer, right? Just don’t tell me I’m getting attacked. Block the thing. By the time you tell me, the attack went through. Don’t just tell me you found a vulnerability, make sure I’m not getting exploited. But a funny thing that I learned in that was a lot of people say, “Go slow here. I can’t afford, because sometimes the vulnerability or the attack or the data that you want me to act on can affect something that I consider more valuable.”
Tucker Callaway: Yeah, fair enough.
Alan Shimel: And I like to go slow when it comes to letting a program or an application or a product, just do things. Just give me my menu and I’ll decide what I want to do. Now, of course, that was before the world of AI and ML and a lot of the automations. And quite frankly, the speed of business was probably a little slower then. Do you see a way station where people are going to want that? Just give me best practices and I’ll decide when, how, and where I want to implement it. Or do we move right to, “Hey man, make it happen for me.”
Tucker Callaway: I think there’s a way station, when we think about the data management, telemetry, data management in general, the word that’s the most important to us is trust, right? So it is one thing to optimize the data, but you have to trust that data is constantly being optimized and handled in the right way for all those varying needs you described.
So I do see that the first step is a suggestion with a human in the loop. You want to hit that button still to say “go”, and then as you build trust in that data and you know that the algorithms are working, then you’ll let that go. Probably with some backstops on the side, I’m going to let it go, but I’m [inaudible 00:09:52] just in case. And then you’ll start to optimize it more and more. And I think naturally, almost like a realtime data platform, operating system will start to evolve.
Alan Shimel: So really the key there is trust.
Tucker Callaway: Key is trust.
Alan Shimel: To build trust in the next. So as the CEO, how do you build that trust?
Tucker Callaway: Well, trust is always a tough.
Alan Shimel: I’m interested, you tell me.
Tucker Callaway: Yeah. I think like anything else in life, you deliver trust through consistent delivery. And so that’s where I think that human in the loop step is important. It has to be sustaining. It can’t be a moment in time, it can’t be the very first implementation. It’s something that you earn over time where people can count on you or could count on the data or count on the ways that you treat data to get you to the outcome that you want to go through. So it’s really only through the delivery of outcomes to the customer that they will trust the systems and all those things.
Alan Shimel: Makes sense?
Tucker Callaway: Yeah.
Alan Shimel: All right. Got to do a little housekeeping.
Tucker Callaway: Okay, let’s do it.
Alan Shimel: People who want to know more about Mezmo.
Tucker Callaway: Come to the website. We’ve got an offer out there to profile anyone’s data for free right now.
Alan Shimel: Do you really?
Tucker Callaway: Yeah. Come to mezmo.com or stop by our booth.
Alan Shimel: M-E-Z-M-O.com.
Tucker Callaway: M-E-Z-M-O.com
Alan Shimel: Out there in TV land or if you hear a coupon.
Tucker Callaway: Come by the booth. I forget the number, but it’s over there.
Alan Shimel: You know what, if you look on the, I don’t have it. If you look on the back of your ID thing, you could actually look stuff up like that.
Tucker Callaway: Yeah, it’s back there. If you connected to the wifi here at KubeCon, it’s Mezmo Data.
Alan Shimel: I’ve noticed that.
Tucker Callaway: Is the wifi.
Alan Shimel: I was like, “Wow, what a cool thing.” Yeah.
Tucker Callaway: You have see us. Come see us. Profile your data will give you insight and understanding into that and talk to you about the next steps.
Alan Shimel: All right, check it out at Mezmo. Tucker, thanks.
Tucker Callaway: Thanks for having me.
Alan Shimel: Actually, we’ll see you. Are you going to be at AWS?
Tucker Callaway: Yeah, we’ll be there. Yeah, I’ll be there. Yeah.
Alan Shimel: We’ll be doing videos, not on the show floor. It’ll be a little quieter in a private suite. And then of course you’ll be at RSA.
Tucker Callaway: We’ll be at RSA.
Alan Shimel: We’ll be there as well.
Tucker Callaway: We might not be on the show floor at AWS just because of-
Alan Shimel: It’s a little crazy there isn’t it? A little pricey.
Tucker Callaway: Yeah.
Alan Shimel: Yeah, I hear you. That’s why we’ll be at the wind in the studio.
Tucker Callaway: I’ll see you there.
Alan Shimel: Come on up. I’ll have coffee.
Tucker Callaway: Sounds good.
Alan Shimel: But RSA will be at broadcast alley and we’ll be doing our DevSecOps thing on Monday. And the usual kind of RSA craziness.
Tucker Callaway: Looking forward to it.
Alan Shimel: Absolutely.
Tucker Callaway: Okay.
Alan Shimel: Check out Mezmo.com.
Tucker Callaway: Thanks everybody.
Alan Shimel: Tucker Callaway here on Tech Drunk TV. We’re going to take a break. I guess it’s almost lunchtime here, but it’s still busy.
Tucker Callaway: Near enough.
Alan Shimel: Stay tuned. We’re here all day. We’ll be back. Bye-Bye.