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//! A lightweight metrics facade. //! //! The `metrics` crate provides a single metrics API that abstracts over the actual metrics //! implementation. Libraries can use the metrics API provided by this crate, and the consumer of //! those libraries can choose the metrics implementation that is most suitable for its use case. //! //! # Overview //! `metrics` exposes two main concepts: emitting a metric, and recording it. //! //! ## Emission //! Metrics are emitted by utilizing the registration or emission macros. There is a macro for //! registering and emitting each fundamental metric type: //! - [`register_counter!`], [`increment!`], and [`counter!`] for counters //! - [`register_gauge!`] and [`gauge!`] for gauges //! - [`register_histogram!`] and [`histogram!`] for histograms //! //! In order to register or emit a metric, you need a way to record these events, which is where //! [`Recorder`] comes into play. //! //! ## Recording //! The [`Recorder`] trait defines the interface between the registration/emission macros, and //! exporters, which is how we refer to concrete implementations of [`Recorder`]. The trait defines //! what the exporters are doing -- recording -- but ultimately exporters are sending data from your //! application to somewhere else: whether it be a third-party service or logging via standard out. //! It's "exporting" the metric data somewhere else besides your application. //! //! Each metric type is usually reserved for a specific type of use case, whether it be tracking a //! single value or allowing the summation of multiple values, and the respective macros elaborate //! more on the usage and invariants provided by each. //! //! # Getting Started //! //! ## In libraries //! Libraries need only include the `metrics` crate to emit metrics. When an executable installs a //! recorder, all included crates which emitting metrics will now emit their metrics to that record, //! which allows library authors to seamless emit their own metrics without knowing or caring which //! exporter implementation is chosen, or even if one is installed. //! //! In cases where no global recorder is installed, a "noop" recorder lives in its place, which has //! an incredibly very low overhead: an atomic load and comparison. Libraries can safely instrument //! their code without fear of ruining baseline performance. //! //! ### Examples //! //! ```rust //! use metrics::{histogram, counter}; //! //! # use std::time::Instant; //! # pub fn run_query(_: &str) -> u64 { 42 } //! pub fn process(query: &str) -> u64 { //! let start = Instant::now(); //! let row_count = run_query(query); //! let delta = Instant::now() - start; //! //! histogram!("process.query_time", delta); //! counter!("process.query_row_count", row_count); //! //! row_count //! } //! # fn main() {} //! ``` //! //! ## In executables //! //! Executables, which themselves can emit their own metrics, are intended to install a global //! recorder so that metrics can actually be recorded and exported somewhere. //! //! Initialization of the global recorder isn't required for macros to function, but any metrics //! emitted before a global recorder is installed will not be recorded, so early initialization is //! recommended when possible. //! //! ### Warning //! //! The metrics system may only be initialized once. //! //! For most use cases, you'll be using an off-the-shelf exporter implementation that hooks up to an //! existing metrics collection system, or interacts with the existing systems/processes that you use. //! //! Out of the box, some exporter implementations are available for you to use: //! //! * [metrics-exporter-tcp] - outputs metrics to clients over TCP //! * [metrics-exporter-prometheus] - serves a Prometheus scrape endpoint //! //! You can also implement your own recorder if a suitable one doesn't already exist. //! //! # Development //! //! The primary interface with `metrics` is through the [`Recorder`] trait, so we'll show examples //! below of the trait and implementation notes. //! //! ## Implementing and installing a basic recorder //! //! Here's a basic example which writes metrics in text form via the `log` crate. //! //! ```rust //! use log::info; //! use metrics::{Key, Recorder, Unit}; //! use metrics::SetRecorderError; //! //! struct LogRecorder; //! //! impl Recorder for LogRecorder { //! fn register_counter(&self, key: Key, _unit: Option<Unit>, _description: Option<&'static str>) {} //! //! fn register_gauge(&self, key: Key, _unit: Option<Unit>, _description: Option<&'static str>) {} //! //! fn register_histogram(&self, key: Key, _unit: Option<Unit>, _description: Option<&'static str>) {} //! //! fn increment_counter(&self, key: Key, value: u64) { //! info!("counter '{}' -> {}", key, value); //! } //! //! fn update_gauge(&self, key: Key, value: f64) { //! info!("gauge '{}' -> {}", key, value); //! } //! //! fn record_histogram(&self, key: Key, value: u64) { //! info!("histogram '{}' -> {}", key, value); //! } //! } //! //! // Recorders are installed by calling the [`set_recorder`] function. Recorders should provide a //! // function that wraps the creation and installation of the recorder: //! //! static RECORDER: LogRecorder = LogRecorder; //! //! pub fn init() -> Result<(), SetRecorderError> { //! metrics::set_recorder(&RECORDER) //! } //! # fn main() {} //! ``` //! ## Keys //! //! All metrics are, in essence, the combination of a metric type and metric identifier, such as a //! histogram called "response_latency". You could conceivably have multiple metrics with the same //! name, so long as they are of different types. //! //! As the types are enforced/limited by the [`Recorder`] trait itself, the remaining piece is the //! identifier, which we handle by using [`Key`]. //! //! [`Key`] itself is a wrapper for [`KeyData`], which holds not only the name of a metric, but //! potentially holds labels for it as well. The name of a metric must always be a literal string. //! The labels are a key/value pair, where both components are strings as well. //! //! Internally, `metrics` uses a clone-on-write "smart pointer" for these values to optimize cases //! where the values are static strings, which can provide significant performance benefits. These //! smart pointers can also hold owned `String` values, though, so users can mix and match static //! strings and owned strings for labels without issue. Metric names, as mentioned above, are always //! static strings. //! //! Two [`Key`] objects can be checked for equality and considered to point to the same metric if //! they are equal. Equality checks both the name of the key and the labels of a key. Labels are //! _not_ sorted prior to checking for equality, but insertion order is maintained, so any [`Key`] //! constructed from the same set of labels in the same order should be equal. //! //! It is an implementation detail if a recorder wishes to do an deeper equality check that ignores //! the order of labels, but practically speaking, metric emission, and thus labels, should be //! fixed in ordering in nearly all cases, and so it isn't typically a problem. //! //! ## Registration //! //! Recorders must handle the "registration" of a metric. //! //! In practice, registration solves two potential problems: providing metadata for a metric, and //! creating an entry for a metric even though it has not been emitted yet. //! //! Callers may wish to provide a human-readable description of what the metric is, or provide the //! units the metrics uses. Additionally, users may wish to register their metrics so that they //! show up in the output of the installed exporter even if the metrics have yet to be emitted. //! This allows callers to ensure the metrics output is stable, or allows them to expose all of the //! potential metrics a system has to offer, again, even if they have not all yet been emitted. //! //! As you can see from the trait, the registration methods treats the metadata as optional, and //! the macros allow users to mix and match whichever fields they want to provide. //! //! When a metric is registered, the expectation is that it will show up in output with a default //! value, so, for example, a counter should be initialized to zero, a histogram would have no //! values, and so on. //! //! ## Emission //! //! Likewise, records must handle the emission of metrics as well. //! //! Comparatively speaking, emission is not too different from registration: you have access to the //! same [`Key`] as well as the value being emitted. //! //! For recorders which temporarily buffer or hold on to values before exporting, a typical approach //! would be to utilize atomic variables for the storage. For counters and gauges, this can be done //! simply by using types like [`AtomicU64`](std::sync::atomic::AtomicU64). For histograms, this can be //! slightly tricky as you must hold on to all of the distinct values. In our helper crate, //! [`metrics-util`][metrics-util], we've provided a type called [`AtomicBucket`][AtomicBucket]. For //! exporters that will want to get all of the current values in a batch, while clearing the bucket so //! that values aren't processed again, [AtomicBucket] provides a simple interface to do so, as well as //! optimized performance on both the insertion and read side. //! //! ## Installing recorders //! //! In order to actually use an exporter, it must be installed as the "global" recorder. This is a //! static recorder that the registration and emission macros refer to behind-the-scenes. `metrics` //! provides a few methods to do so: [`set_recorder`], [`set_boxed_recorder`], and [`set_recorder_racy`]. //! //! Primarily, you'll use [`set_boxed_recorder`] to pass a boxed version of the exporter to be //! installed. This is due to the fact that most exporters won't be able to be constructed //! statically. If you could construct your exporter statically, though, then you could instead //! choose [`set_recorder`]. //! //! Similarly, [`set_recorder_racy`] takes a static reference, but is also not thread safe, and //! should only be used on platforms which do not support atomic operations, such as embedded //! environments. //! //! [metrics-exporter-tcp]: https://docs.rs/metrics-exporter-tcp //! [metrics-exporter-prometheus]: https://docs.rs/metrics-exporter-prometheus //! [metrics-util]: https://docs.rs/metrics-util //! [AtomicBucket]: https://docs.rs/metrics-util/0.4.0-alpha.6/metrics_util/struct.AtomicBucket.html #![deny(missing_docs)] #![cfg_attr(not(feature = "std"), no_std)] #![cfg_attr(docsrs, feature(doc_cfg), deny(broken_intra_doc_links))] extern crate alloc; use proc_macro_hack::proc_macro_hack; mod common; pub use self::common::*; mod cow; mod key; pub use self::key::*; mod label; pub use self::label::*; mod recorder; pub use self::recorder::*; /// Registers a counter. /// /// Counters represent a single monotonic value, which means the value can only be incremented, not /// decremented, and always starts out with an initial value of zero. /// /// Metrics can be registered with an optional unit and description. Whether or not the installed /// recorder does anything with the description is implementation defined. Labels can also be /// specified when registering a metric. /// /// # Example /// ``` /// # use metrics::register_counter; /// # use metrics::Unit; /// # fn main() { /// // A basic counter: /// register_counter!("some_metric_name"); /// /// // Providing a unit for a counter: /// register_counter!("some_metric_name", Unit::Bytes); /// /// // Providing a description for a counter: /// register_counter!("some_metric_name", "total number of bytes"); /// /// // Specifying labels: /// register_counter!("some_metric_name", "service" => "http"); /// /// // We can combine the units, description, and labels arbitrarily: /// register_counter!("some_metric_name", Unit::Bytes, "total number of bytes"); /// register_counter!("some_metric_name", Unit::Bytes, "service" => "http"); /// register_counter!("some_metric_name", "total number of bytes", "service" => "http"); /// /// // And all combined: /// register_counter!("some_metric_name", Unit::Bytes, "number of woopsy daisies", "service" => "http"); /// /// /// We can also pass labels by giving a vector or slice of key/value pairs. In this scenario, /// // a unit or description can still be passed in their respective positions: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// register_counter!("some_metric_name", &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::register_counter; /// Registers a gauge. /// /// Gauges represent a single value that can go up or down over time, and always starts out with an /// initial value of zero. /// /// Metrics can be registered with an optional unit and description. Whether or not the installed /// recorder does anything with the description is implementation defined. Labels can also be /// specified when registering a metric. /// /// # Example /// ``` /// # use metrics::register_gauge; /// # use metrics::Unit; /// # fn main() { /// // A basic gauge: /// register_gauge!("some_metric_name"); /// /// // Providing a unit for a gauge: /// register_gauge!("some_metric_name", Unit::Bytes); /// /// // Providing a description for a gauge: /// register_gauge!("some_metric_name", "total number of bytes"); /// /// // Specifying labels: /// register_gauge!("some_metric_name", "service" => "http"); /// /// // We can combine the units, description, and labels arbitrarily: /// register_gauge!("some_metric_name", Unit::Bytes, "total number of bytes"); /// register_gauge!("some_metric_name", Unit::Bytes, "service" => "http"); /// register_gauge!("some_metric_name", "total number of bytes", "service" => "http"); /// /// // And all combined: /// register_gauge!("some_metric_name", Unit::Bytes, "total number of bytes", "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs. In this scenario, /// // a unit or description can still be passed in their respective positions: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// register_gauge!("some_metric_name", &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::register_gauge; /// Records a histogram. /// /// Histograms measure the distribution of values for a given set of measurements, and start with no /// initial values. /// /// Metrics can be registered with an optional unit and description. Whether or not the installed /// recorder does anything with the description is implementation defined. Labels can also be /// specified when registering a metric. /// /// # Example /// ``` /// # use metrics::register_histogram; /// # use metrics::Unit; /// # fn main() { /// // A basic histogram: /// register_histogram!("some_metric_name"); /// /// // Providing a unit for a histogram: /// register_histogram!("some_metric_name", Unit::Nanoseconds); /// /// // Providing a description for a histogram: /// register_histogram!("some_metric_name", "request handler duration"); /// /// // Specifying labels: /// register_histogram!("some_metric_name", "service" => "http"); /// /// // We can combine the units, description, and labels arbitrarily: /// register_histogram!("some_metric_name", Unit::Nanoseconds, "request handler duration"); /// register_histogram!("some_metric_name", Unit::Nanoseconds, "service" => "http"); /// register_histogram!("some_metric_name", "request handler duration", "service" => "http"); /// /// // And all combined: /// register_histogram!("some_metric_name", Unit::Nanoseconds, "request handler duration", "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs. In this scenario, /// // a unit or description can still be passed in their respective positions: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// register_histogram!("some_metric_name", &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::register_histogram; /// Increments a counter by one. /// /// Counters represent a single monotonic value, which means the value can only be incremented, not /// decremented, and always starts out with an initial value of zero. /// /// # Example /// ``` /// # use metrics::increment; /// # fn main() { /// // A basic increment: /// increment!("some_metric_name"); /// /// // Specifying labels: /// increment!("some_metric_name", "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// increment!("some_metric_name", &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::increment; /// Increments a counter. /// /// Counters represent a single monotonic value, which means the value can only be incremented, not /// decremented, and always starts out with an initial value of zero. /// /// # Example /// ``` /// # use metrics::counter; /// # fn main() { /// // A basic counter: /// counter!("some_metric_name", 12); /// /// // Specifying labels: /// counter!("some_metric_name", 12, "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// counter!("some_metric_name", 12, &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::counter; /// Updates a gauge. /// /// Gauges represent a single value that can go up or down over time, and always starts out with an /// initial value of zero. /// /// # Example /// ``` /// # use metrics::gauge; /// # fn main() { /// // A basic gauge: /// gauge!("some_metric_name", 42.2222); /// /// // Specifying labels: /// gauge!("some_metric_name", 66.6666, "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// gauge!("some_metric_name", 42.42, &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::gauge; /// Records a histogram. /// /// Histograms measure the distribution of values for a given set of measurements, and start with no /// initial values. /// /// # Implicit conversions /// Histograms are represented as `u64` values, but often come from another source, such as a time /// measurement. By default, `histogram!` will accept a `u64` directly or a /// [`Duration`](std::time::Duration), which uses the nanoseconds total as the converted value. /// /// External libraries and applications can create their own conversions by implementing the /// [`IntoU64`] trait for their types, which is required for the value being passed to `histogram!`. /// /// # Example /// ``` /// # use metrics::histogram; /// # use std::time::Duration; /// # fn main() { /// // A basic histogram: /// histogram!("some_metric_name", 34); /// /// // An implicit conversion from `Duration`: /// let d = Duration::from_millis(17); /// histogram!("some_metric_name", d); /// /// // Specifying labels: /// histogram!("some_metric_name", 38, "service" => "http"); /// /// // We can also pass labels by giving a vector or slice of key/value pairs: /// let dynamic_val = "woo"; /// let labels = [("dynamic_key", format!("{}!", dynamic_val))]; /// histogram!("some_metric_name", 1337, &labels); /// # } /// ``` #[proc_macro_hack] pub use metrics_macros::histogram;