dipstick

A fast and modular metrics library decoupling app instrumentation from reporting backend. Similar to popular logging frameworks, but with counters and timers. Can be configured for combined outputs (log + statsd), random sampling, local aggregation of metrics, recurrent background publication, etc.

Design

Dipstick's design goals are to: - support as many metrics backends as possible while favoring none - support all types of applications, from embedded to servers - promote metrics conventions that facilitate app monitoring and maintenance - stay out of the way in the code and at runtime (ergonomic, fast, resilient)

Code

Here's an example showing usage of a predefined timer with closure syntax. Each timer value is : - Written immediately to the "app_metrics" logger. - Sent to statsd immediately, one time out of ten (randomly sampled). ```rust use dipstick::*;

let appmetrics = metrics(( log("appmetrics"), sample(0.1, statsd("stats:8125")) ));

let timer = appmetrics.timer("timerb");

let value2 = time!(timer, compute_value2()); ```

In this other example, an ad-hoc timer with macro syntax is used. - Each new timer value is aggregated with the previous values. - Aggregation tracks count, sum, max and min values (locklessly). - Aggregated scores are written to log every 10 seconds.
- cache(sink) is used to prevent metrics of the same to be created multiple times.
```rust use dipstick::*; use std::time::Duration;

let (sink, source) = aggregate(); let appmetrics = metrics(cache(sink)); publish(source, log("lasttenseconds")).publishevery(Duration::from_secs(10));

let value2 = time!(appmetrics.timer("timerb"), compute_value2()); ```

Other example(s?) can be found in the /examples dir.

Performance

Predefined timers use a bit more code but are generally faster because their initialization cost is is only paid once. Ad-hoc timers are redefined "inline" on each use. They are more flexible, but have more overhead because their init cost is paid on each use. Defining a metric cache() reduces that cost for recurring metrics.

Run benchmarks with cargo +nightly bench --features bench.

TODO

Although already usable, Dipstick is still under heavy development and makes no guarantees of any kind at this point. See the following list for any potential caveats : - META turn TODOs into GitHub issues - generic publisher / sources - dispatch scopes - feature flags - derive stats - non-tokio publish scheduler - microsecond-precision intervals - heartbeat metric on publish - logger templates - configurable aggregation - non-aggregating buffers - tagged / ad-hoc metrics - framework glue (rocket, iron, gotham, indicatif, etc.) - more tests & benchmarks - complete doc / inline samples - more example apps - A cool logo - method annotation processors #[timer("name")]