Chad Whitacre

Yeah, one of the things that we're seeing is that in the past, people had separate systems where they had logs on servers written to 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.

Yeah, one of the things that we're seeing is that in the past, people had separate systems where they had logs on servers written to 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.

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 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.

So if 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.

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 in something that is, we're kind of charged the path for that for everybody.

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 in something that is, we're kind of charged the path for that for everybody.

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.

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.

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.

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.

So at Assembly, we're building industry-leading speech AI models for various tasks like speech-to-text, streaming speech-to-text, speech understanding, to help developers easily convert voice data, whether it's live or pre-recorded, into super accurate text. And then to help developers extract a ton of information and metadata around voice data or even around the text that they just recorded.

So at Assembly, we're building industry-leading speech AI models for various tasks like speech-to-text, streaming speech-to-text, speech understanding, to help developers easily convert voice data, whether it's live or pre-recorded, into super accurate text. And then to help developers extract a ton of information and metadata around voice data or even around the text that they just recorded.

We're able to convert from that audio data. So these are things like picking out entities or PII that was spoken in voice files or summarizing voice and audio data down into custom summaries. It's things like being able to detect how many speakers spoke and who said what and what the names of different speakers were.

We're able to convert from that audio data. So these are things like picking out entities or PII that was spoken in voice files or summarizing voice and audio data down into custom summaries. It's things like being able to detect how many speakers spoke and who said what and what the names of different speakers were.