pprof-rs VS tracing

On top of others' specific recommendations, don't forget to profile! Tools like perf on Linux and pprof within Rust will tell you which functions are taking the most time.

https://github.com/tikv/pprof-rs: Seems to work nicely per se, but I cant seem to find any useful information in the flamegraph for my setting. I see mostly functions in std::thread but cant find the time it costs to render stuff or to do the actual computations which should be the most time consuming things. Not sure whether this is necessarily something wrong with pprof-rs, maybe I'm just bad at finding stuff in the flamegraph svg or bevys ECS is making this hard.

Have you looked into using pprof?

The library doesn't actually do any profiling (The profiler for Rust is pprof-rs: https://github.com/tikv/pprof-rs) but it's goal is to manage data returned by profilers (abstracted behind a Backend) and send this data to a Pyroscope Server (or exported to flamegraph, though this is being implemented in the commandline application).

The libunwind part is actually not related to overhead, this is just a nuance of the way that pprof-rs unwinds stack traces.

The video description is as follows:

In this stream, we peel back the crust on the tracing crate — https://github.com/tokio-rs/tracing/ — and explore its interface, structure, and mechanisms. We talk about spans, events, their attributes and fields, and how to think about them in async code. We also dig into what subscribers are, how they pick up events, and how you can construct your own subscribers through the layer abstraction. For more details about tracing, see https://docs.rs/tracing/latest/tracing/.

> What's been your biggest issues around ergonomics/amenities for OpenTelemetry?

I can't speak generally, but in the Rust ecosystem the various crates don't play well together. Here's one example: <https://github.com/tokio-rs/tracing/issues/2648> There are four crates involved (tracing-attributes, tracing-opentelemetry, opentelemetry, and opentelemetry-datadog) and none of them fit properly into any of the others.

The tracing (logging) mechanism in an asynchronous codebase (tracing).

Tracing is Tokio's alternative for async code.

At a technical level, in Rust, both [tracing]https://crates.io/crates/tracing) and log are entire ecosystems (though for the latter at least there's also third party logging frameworks), and there's at least a bridge from log to tracing.

I am using https://github.com/tokio-rs/tracing for logging purposes in my application. I would like to develop a feature wherein logs should be saved to a database table (via sea-orm). Something similar is this, but it does not solve my needs fully.

I've used the tracing infrastructure with tracing_flame to profile some hot paths in async code: https://github.com/tokio-rs/tracing/tree/master/tracing-flame

Oh nice! IIRC when I checked, it was the Unicode tables that smashed the code size. I recently hit the same issue with the tracing crate, where a crate feature (for env var filtering) pulled in regex and my binary was suddenly 1MB bigger.

I know about tools such as tracing, jaeger or tracy. While having a complete tracing could be a potential solution, these tools don't work with no_std.

tracing by itself only outputs log data, you need to consume them in a subscriber, the tracing-subscriber crate exists for this. (example)