Valentino Stoll
speaker
350 appearances
6 recordings
1 series
first heard Sep 2024
last heard Oct 2024
Valentino Stoll’s voice in public audio — every appearance, attributed to the second.
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Where do you find like I mean, background jobs are like kind of like I feel like the first instance where people realize like, oh, like we need to start looking at, you know, what it's doing. Right. Like you start throwing stuff in the background. You're like, OK, great. Like it's doing the work.
Uh, and then you don't maybe realize if you're on the same node, like, well, those, you know, slow requests can block the web requests. Uh, right. And then, okay, well, if you split those up, finally you got that resolved, but then, okay, well, one problematic, you know, job can back up a queue that it's on. Uh, you know, like where do you, uh,
To me, like the background processing aspect is like why we have tracing to begin with, because it does like it's concurrency. Right. So it's like that's where everybody like ends up hitting their pitfalls is as soon as you start doing things like all at once, like and thinking, oh, like we just throw it in the background and like process things as they come.
And as things start to scale, it causes more problems as you try and figure out timing and stuff like that. Where do you find the most important pieces of making sure that you are capturing the right segments and the right flows in that process?
Yeah, I mean, it's more of like an open question. I guess like when trying to think about like one of my biggest debugging pitfalls is like trying to like reconstruct the state of what happened when something went wrong. It's like I feel like that's like one of the most typical things. It's like, OK, something happened. Like, well, like it's the data has changed since something had happened.
Maybe the change resolved the issue. But like, you know, trying to figure out what that is and going running through those questions. Right. Like. How do you think about like reconstructing data or reconstructing the state of an issue? Like, is that not the right way to go about it? Or do you try and like do something else?
Okay, so there'll be a lot of- Wait, what are the three pillars?
Okay.
I think that you're making some great points of capturing the transactional like user information or user's actions. Yes.
I guess I do have like maybe some specific instances where metrics alone can help like identify things. And that's more where it's like the granular metrics are the things that you're actually looking like care about. Right.
Like, let's say, for example, like back to the sidekick background jobs example, like if you notice like your queues piling up and you happen to have your dashboard of metrics just looking at queue size and looking at throughput, like you can easily say, oh, like there's something blocking it and gives you kind of a point of confidence. where to look at in this specific instance.
Or as an example, like also, you know, you can notice like there's a leak in memory by monitoring, you know, your memory consumption of the app and just looking at the metrics for that and getting an alert and saying, why is the memory not stopping growing after a certain amount of time? I mean, these are like, you know, very specific examples that I'm giving, but like, uh, I agree.
Like if, if you're looking for like, you know, it's not going to tell you like if your users are like back to your like token expiration, like are people having a problem with our application that we've made? Like, Uh, you know, and like, we keep getting these, you know, client, uh, you know, emails coming in like, oh, I can't like sign into your app. Like what's happening.
You know, you can't just like take that and be like, oh yeah, it's obviously the tokens like expiration, right? Like it's your customers emails aren't going to like translate directly to that. And you're not going to know right away, uh, without having your tracing in place. Uh,
I mean, I would love to dig more into tracing in general and maybe more of the distributed aspect of it. Because I think what you're talking about is very important. Like, If we're just talking about tracing through a single request in a Rails app, it's not as useful as maybe where tracing really comes into play is where there's multiple things that start happening.
Once you start having more than one application and the you know, the data starts trickling from one application to the other, uh, even in sidekick example, right? If you're throwing stuff into the background, how does that data snapshot transition through the background jobs? Especially if you have ones that start depending on each other, how do you then manage the queue?
Like in the making sure that you know where it started and you know where it's going, because sometimes you can catch a problem before it starts, uh, by having the traces in play and know where it's heading. Right. Uh, And so I would love to dig into those aspects.
Like where do you, like what tooling, or maybe we shouldn't talk about tooling specifically, but like what aspects of tracing are most important for like holistically looking at your system outside of like, you know, running through your question. Like I think at this point we're beyond like having your questions of what you're trying to look at and that you already know what those
questions are and where do you start setting up tracing? Because I know at Doximity we use open tracing as an open standard for tracing and observability across platforms, languages, and things like that. Do you find that the industry standards are heading in the right direction or where are the pitfalls there? Because I know it just introduces a lot
of dependencies once you start to adopt a lot of these things.
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