Tucker Callaway, Mezmo | KubeCon + CloudNativeCon North America 2023

This is Textron tv. Hey everyone. We're back here at Q Con and it's, it's bustling, man.

It's a crazy big, uh, floor with a lot of people walking around. So we hope you like this. You know, this is a little different than we usually do.

We usually, people can't see the background 'cause the camera's 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're In the middle of it.

We're In the middle of it. So kind like if you ever watch Thursday, Sunday night football at the end, you know? Mm-Hmm.

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 smo. Now, some of you may have heard of, I think it was Log DNA Before. Yep.

And they, you know, they pivoted, was it about four years ago? About two years ago now. Two years ago.

Yeah. I've been here for four. But we, the, the big change was two years ago, renamed and Renamed to SMO and, you know, a slightly different mission, let's call it.

Mm-Hmm. And then I, I had a chance to catch up with Tucker at RSA last, uh, I guess it was last April. Yeah, late April.

April. April. Yeah.

April This year. It's May. So I think it was okay.

April last year. Around then last year. And, 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. Med Smo.

Not everyone out here. Look, not everyone out here knew Log DNA either, so don't worry about it. Fair enough.

Yeah. Let's, let's give them, let's start there. Let's talk about the mission.

Yeah. So, uh, the mission of me SMO is essentially to help people with their telemetry data. So we've found that there's really, uh, kind of three main problems in the telemetry data space.

You're like, you don't, uh, 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 our, one of our founding kind of principles of Yeah, I, I think that solving the problem, those were three rock solid. Hard to, hard to Debate. Hard to debate.

That's the good way of putting that. Yeah. And, and, and, and also, quite frankly, all three problems are like, they compound each other.

They do. So it's like, you know, you have too much data. That's a big problem.

Yeah. But we have too much data that we don't know how to categorize, so that exponentially makes that problem worse. Yeah.

Whereas, so these are like Compounding problems. Yeah. No question about it.

No doubt about it. Yeah. So when we were at RSA, you felt like you were kind of on the, uh, on the cusp of a realization, right?

You were gonna help customers. Why don't you, well, you tell the story better Than me. Me?

Yeah. So we, so as we were talking about earlier, like we had just launched this new product capability, the telemetry pipeline at RSA. Uh, 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, uh, is how little people actually understand their data. In fact, like, like we've put a lot of, uh, 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, 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 real revelation for us.

And we just launched our data profiling capability that helps people categorize and understand baseline to get, do the schema management for their data, which is a really strong foundation for kind of data ops principles applied to telemetry data. Then the next thing we found after we solved that problem was now that people were, they understood their data and they were able to optimize it because they understood it. They also realized that like the context and telemetry data changes rapidly.

Mm-Hmm. So for example, like 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. Yeah.

So, I I I'll take a little Yeah. They do want to store the data. Yeah.

'cause people are ho data hoarders the Data hoarder. Yeah. No, 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.

Yeah. Not at that price. So Something has to give somewhere.

Exactly. And so what we realized though is like kind of, if you take the, 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 in 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. So, you know, if one was gonna do like a, a business school case study on this Yeah. 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.

Yeah. I'd like to think so. No, I, yeah, it's logical.

Yeah. Makes sense. It makes sense.

Yeah. But it's not, it's the threshold. Yeah.

Because like, I, 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 of realization Yeah. For them. Yeah.

Of holy mackerel, I got all this data, now I want to start understanding it. Wow. Yeah.

I'm seeing stuff I never thought I'd see. Maybe I intuitively thought I had, you know, but I got the goods. Now We like to think of that as being mesmerizing.

Right. Okay. I love it.

Which Is, which is the truth Mesmerizing mes mo, Which is, I could not take the shot, but that was Just Yeah. That was your shot. That's, that's the derivative of The name I feel used, I feel used Back into It.

I feel. Yeah. But so now you're mesmerized.

Yeah. And now like, oh my God, what can I do with this? And that, that really becomes the business.

And I guess that's now where you are. The next step for us is clearly that. Yeah.

Yeah. And there, and I, I think there's two, there's two, uh, plays on that too. There's a, what do I do with it?

Uh, help me, tell me what to do. Gimme the best practices that you know from all of your customers. What should I do?

And so we'll be, um, we'll be coming out, uh, probably later in the spring with something that actually allows you to simulate how you might, how that data might look when, when optimization's applied to it. So you can start to make those decisions more effectively. But then the second, the second phase of that too, is that also won't be sufficient for certain organizations that wanna look at their data as a strategic advantage.

And they're gonna 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 outta that data. If you're like, ready for advanced yoga moves in the data space.

Got it. Got it. Got it.

Um, so in, you know, my background security Yep. Started a security company in 2001 that we, and it was right when we were moving from like IDS to IPS. Okay.

So intrusion detection to intrusion prevention, same thing with vulnerability management. We were moving from just finding vulnerabilities to patching. Mm-Hmm.

Remediating remedi. Yeah. Not always patching, remediating seemed like who, who wouldn't want that?

Right. No brainer, right? Yeah.

Just don't tell me I'm getting attacked. Block the damn thing. 'cause by the time you tell me the attack went true, don't just tell me you found a vulnerability.

Make sure I'm not getting exploited. But a funny thing that we learned, 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 Mm-Hmm.

That you want me to act on can affect something that I consider more valuable. Yeah, fair enough. Yeah.

And I like to go slow when it comes to letting a program or an application. Mm-Hmm. 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, and quite frankly, the speed of business was probably a little slower then.

Mm-Hmm. Do you see a way station where people are gonna want that? Just gimme like best practices and I'll decide when, how and where I want to implement it.

Yeah. Or do we move right to hey, may make it happen for me, I think, I think there's a way station. Like I, when we think about the data management, telemetry, data management in general, the, the word that's the most important to us is trust.

Right. So it's, it's one thing to optimize the data, but you have to trust that data is constantly being optimized and, and handled in the right way for all those varying needs you described. So I do see that the first step is like a suggestion with a human in the loop.

You know, like, like, like you want to hit that button still to say go, 'cause you don't. 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, some like, you know, backstops on the side, like, I'm gonna let it go, but I'm gonna it S3 just in case. And then you'll start to optimize it more and more.

And I think naturally, like, almost like a realtime data platform, operating system will start to evolve. So really the key there is trust. Key is trust To build trust in in the next um, so is the CEO, how do you build that trust?

Well, trust is always a tru. Trust is always, I'm Interested, you tell me, But yeah, you, I think like anything else in life, you uh, you deliver trust through consistent delivery. Right.

And uh, so that's where I think that human loop step is important. 'cause you have to like, 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.

Makes sense? Yeah. Alright.

Gotta do a little housekeeping. Okay. Let's Do it.

People who want to know about more about mes o Come to the website. Uh, we've got an offer out there to profile anyone's data for free right now. So do you really?

So go Yeah. com or stop by a booth. com.

M-E-Z-M-O do com Out there in TV land. Or if you hear a cube coupon come by the booth. Come by the booth.

Uh, I forget the number but it's over there. 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 like, like that.

Yeah. It's back there. If you connected to the wifi here at Cube coupon, it's mes mode data.

Is it? I noticed that is the wifi. Yeah.

I was like, wow. What a cool thing. Yeah.

Yeah. So, uh, come see us Tucker. Yeah.

Cool. Come see us profile your data will give you insight and understanding into that. And, uh, talk to you about the next steps.

Alright. Check it out at Meds Mill Tucker. Thanks for, thanks For having Me.

Actually, we'll see you. Are you gonna be at AWS Uh, yeah, we'll be there. Yeah, I'll be there.

Yeah. So we'll be doing videos. Okay.

Not on the show floor. Yeah. It'll be a little quieter in a private suite.

Yes. And then of course you'll be at RSA, We'll be at RSA, We'll be there as well. We Might not be on the show floor at aws just 'cause of uh, It's a little crazy there, isn't it?

Yeah. A little pricey. Yeah.

Yeah. I hear ya. That's why we'll be at the wind in the studio.

I'll see you there. Come on up. I'll have coffee in Ish.

Good. But, uh, but RSA will be a broadcast alley and we'll be doing our DevSecOps thing on Monday and everything. The usual kind of RSA craziness.

Looking forward to it. Absolutely. Okay.

com. Thanks everybody. Doug Calloway here on Tech Drunk tv.

We're gonna take a break. It's, I guess it's almost lunchtime here, but it's still busy near enough. Stay tuned.

We're here all day. We'll be back. Bye-Bye.