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//! High-speed metrics collection library. //! //! hotmic provides a generalized metrics collection library targeted at users who want to log //! metrics at high volume and high speed. //! //! # Design //! //! The library follows a pattern of "senders" and a "receiver." //! //! Callers create a [`Receiver`], which acts as a contained unit: metric registration, //! aggregation, and summarization. The [`Receiver`] is intended to be spawned onto a dedicated //! background thread. //! //! From a [`Receiver`], callers can create a [`Sink`], which allows registering facets -- or //! interests -- in a given metric, along with sending the metrics themselves. All metrics need to //! be pre-registered, in essence, with the receiver, which allows us to know which aspects of a //! metric to track: count, value, or percentile. //! //! A [`Sink`] can be cheaply cloned and does not require a mutable reference to send metrics, and //! so callers have great flexibility in being able to control their resource consumption when it //! comes to sinks. [`Receiver`] also allows configuring the capacity of the underlying channels to //! finely tune resource consumption. //! //! Being based on [`crossbeam-channel`] allows us to process close to fifteen million metrics per //! second on a single core, with very low ingest latencies: 100ns on average at full throughput. //! //! # Metrics //! //! hotmic supports counters, gauges, and histograms. //! //! A counter is a single value that can be updated with deltas to increase or decrease the value. //! This would be your typical "messages sent" or "database queries executed" style of metric, //! where the value changes over time. //! //! A gauge is also a single value but does not support delta updates. When a gauge is set, the //! value sent becomes _the_ value of the gauge. Gauges can be useful for metrics that measure a //! point-in-time value, such as "connected clients" or "running queries". While those metrics //! could also be represented by a count, gauges can be simpler in cases where you're already //! computing and storing the value, and simply want to expose it in your metrics. //! //! A histogram tracks the distribution of values: how many values were between 0-5, between 6-10, //! etc. This is the canonical way to measure latency: the time spent running a piece of code or //! servicing an operation. By keeping track of the individual measurements, we can better see how //! many are slow, fast, average, and in what proportions. //! //! ``` //! # extern crate hotmic; //! use hotmic::Receiver; //! use std::{thread, time::Duration}; //! let receiver = Receiver::builder().build(); //! let sink = receiver.get_sink(); //! //! // We can update a counter. Counters are signed, and can be updated either with a delta, or //! // can be incremented and decremented with the [`Sink::increment`] and [`Sink::decrement`]. //! sink.update_count("widgets", 5); //! sink.update_count("widgets", -3); //! sink.increment("widgets"); //! sink.decrement("widgets"); //! //! // We can update a gauge. Gauges are unsigned, and hold on to the last value they were updated //! // to, so you need to track the overall value on your own. //! sink.update_gauge("red_balloons", 99); //! //! // We can update a timing histogram. For timing, you also must measure the start and end //! // time using the built-in `Clock` exposed by the sink. The receiver internally converts the //! // raw values to calculate the actual wall clock time (in nanoseconds) on your behalf, so you //! // can't just pass in any old number.. otherwise you'll get erroneous measurements! //! let start = sink.clock().start(); //! thread::sleep(Duration::from_millis(10)); //! let end = sink.clock().end(); //! let rows = 42; //! //! // This would just set the timing: //! sink.update_timing("db.gizmo_query", start, end); //! //! // This would set the timing and also let you provide a customized count value. Being able to //! // specify a count is handy when tracking things like the time it took to execute a database //! // query, along with how many rows that query returned: //! sink.update_timing_with_count("db.gizmo_query", start, end, rows); //! //! // Finally, we can update a value histogram. Technically speaking, value histograms aren't //! // fundamentally different from timing histograms. If you use a timing histogram, we do the //! // math for you of getting the time difference, and we make sure the metric name has the right //! // unit suffix so you can tell it's measuring time, but other than that, nearly identical! //! let buf_size = 4096; //! sink.update_value("buf_size", buf_size); //! ``` //! //! # Scopes //! //! Metrics can be scoped, not unlike loggers, at the [`Sink`] level. This allows sinks to easily //! nest themselves without callers ever needing to care about where they're located. //! //! This feature is a simpler approach to tagging: while not as semantically rich, it provides the //! level of detail necessary to distinguish a single metric between multiple callsites. //! //! An important thing to note is: registered metrics are only good for the scope they were //! registered at. If you create a scoped [`Sink`], you must register, or reregister, the metrics //! you will be sending to it. //! //! For example, after getting a [`Sink`] from the [`Receiver`], we can easily nest ourselves under //! the root scope and then send some metrics: //! //! ``` //! # extern crate hotmic; //! use hotmic::Receiver; //! let receiver = Receiver::builder().build(); //! //! // This sink has no scope aka the root scope. The metric will just end up as "widgets". //! let root_sink = receiver.get_sink(); //! root_sink.update_count("widgets", 42); //! //! // This sink is under the "secret" scope. Since we derived ourselves from the root scope, //! // we're not nested under anything, but our metric name will end up being "secret.widgets". //! let scoped_sink = root_sink.scoped("secret"); //! scoped_sink.update_count("widgets", 42); //! //! // This sink is under the "supersecret" scope, but we're also nested! The metric name for this //! // sample will end up being "secret.supersecret.widget". //! let scoped_sink_two = scoped_sink.scoped("supersecret"); //! scoped_sink_two.update_count("widgets", 42); //! //! // Sinks retain their scope even when cloned, so the metric name will be the same as above. //! let cloned_sink = scoped_sink_two.clone(); //! cloned_sink.update_count("widgets", 42); //! //! // This sink will be nested two levels deeper than its parent by using a slightly different //! // input scope: scope can be a single string, or multiple strings, which is interpreted as //! // nesting N levels deep. //! // //! // This metric name will end up being "super.secret.ultra.special.widgets". //! let scoped_sink_three = scoped_sink.scoped(&["super", "secret", "ultra", "special"]); //! scoped_sink_two.update_count("widgets", 42); //! ``` #[macro_use] extern crate derivative; mod configuration; mod control; mod data; mod helper; mod receiver; mod scopes; mod sink; pub use self::{ configuration::Configuration, control::{Controller, SnapshotError}, data::Percentile, receiver::Receiver, sink::{Sink, SinkError}, }; pub mod snapshot { pub use super::data::snapshot::{SimpleSnapshot, Snapshot, SummarizedHistogram, TypedMeasurement}; }