Dave Rosenthal

Yeah, one of the things that we're seeing is that in the past, people had separate systems where they had like logs on servers written files. They were maybe sending some metrics to Datadog or something like that or some other system. They were monitoring for errors with some product, maybe with Sentry.

But more and more what we see is people want all of these sources of telemetry logically tied together somehow. And that's really what we're pursuing at Sentry now. We have this concept of a trace ID, which is kind of a key that ties together all of the pieces of data that are associated with the user action.

So if a user loads a web page, we want to tie together all the server requests that happened, any errors that happened, any metrics that were collected. And what that allows on the back end You don't just have to look at like three different graphs and sort of line them up in time and try to draw your own conclusions.

You can actually like analyze and slice and dice the data and say, hey, what did this metric look like for people with this operating system versus this metric look like for people with this operating system and actually get into those details. So this kind of idea of.

tying all of the telemetry data together using this concept of a trace ID or basically some key, I think is a big win for developers trying to diagnose and debug real-world systems and something that is, we're kind of charged the path for that for everybody.

Let's see you get there.

Yeah, I mean, I guess again, I'll just keep saying it maybe, but I think it kind of goes back to this debugability experience. When you are digging into an issue, you know, having a sort of a richer data model that's, you know, your logs are structured, they're sort of this hierarchical structure with spans.

And not only is it just the spans that are structured, they're tied to errors, they're tied to other things. So when you have the data model that's kind of interconnected, it opens up all different kinds of analysis that were just kind of either very manual before, kind of guessing that maybe this log happened at the same time as this other thing, or we're just impossible.

We get excited not only about the new kinds of issues that we can detect with that interconnected data model, but also just for every issue that we do detect, how easy it is to get to the bottom of it.

Carl George. Go ahead, Jared. You got one teed up. I was just trying to get his name on the record here, just in case he says something. He might run away.

Any thoughts, Jared? Where are you at with this? I guess I'm just still confused. Not because you're not doing a good job.

It's a lot of information. It's a lot of information. And maybe I do need a diagram, perhaps. Yes. Because I'm jumping kind of from noun to noun. I can put a diagram in your show notes. Yeah, that would probably be helpful.

Yes. Where are the open source lines drawn across these distributions, like Fedora, CentOS Stream?

I want to hear about the future, man. Yeah. Juicy. Juicy future stuff. Well, real quick before that, how does Meta get their support when their CentOS stream doesn't do what it needs to do? Like, what do they do?

Max Howell, creator of Homebrew, creator of Tea Protocol. Did I cover all the gamut, or is there more?

There you go. I do like to hit on what people care about. Now, I think... The last time you and I crossed paths was some sort of announcement around T, I think. And maybe that was TXCL or something. There's more to it. It's been a while. But I remember you put something out. I covered it on Change Dog News. And I wrote something about it, like, I feel like they're trying to boil the ocean.

I don't know what I said. Oh, yeah, yeah. And that affected your game plans by some way, right?

Right. The people beneath the people beneath the people, right? Like the dependency of the dependency and letting that value chain trickle down or trickle up, whatever direction you're looking at it from. So how does that work then?

Right. Because if they received a bunch of token for their package getting popular and they went to go sell it and they were just dumping on the market and the demand wasn't there, then the price would crash and you'd have your typical peaks and valleys of the crypto sphere. So you're trying to stabilize the coin, basically? Or what's the tokenomics?

You're trying to stabilize the value of the token?