This is quite cool piece of work. Would you please make a comparison between uptrace and jaeger?
UI-wise, Uptrace does not have service dependency analysis, because I don't find it very useful/interesting (let me know if I am wrong). I believe Jaeger does not have span grouping, percentiles, and filters/aggregation are much much simpler.
Jaeger has remote sampling which can be a powerful feature if users are ready to spend their time configuring it. Would be nice to hear if that is the case and if many people are using it.
I've also seen some work on in-memory tail-based sampling, but I don't know if that is ready to use or not. I plan to add tail-based sampling to Uptrace too.
That is about as much I know :)
I don't provide direct comparison, because it is hard to judge which features are relevant. For example, the few people I've asked told me that they don't use "service dependency analysis" and I don't find that functionality useful myself. But you will find that feature in most products so perhaps I've asked the wrong people :)
The benefit of remote sampling, as I understand it, is that the sample rata doesn't need to be configured in each app. So in principle, you could have a little slider in the UI to adjust the sample rate for each individual app, perhaps increasing it during a particular incident to capture more traffic data.
Without remote sampling, you'd have to hard-code the rate into the app's config or code, which then requires a redeploy to change the setting. With a lot of microservices to maintain, it seems a lot simpler to have a central location for such settings.
Uptrace looks fantastic, by the way. It's about time someone gives Zipkin and Jaeger some competition. And Clickhouse makes a lot more sense as a backend than Cassandra.