# Cadence

[![build status](https://circleci.com/gh/56quarters/cadence.svg?style=shield)](https://circleci.com/gh/56quarters/cadence)
[![docs.rs](https://docs.rs/cadence/badge.svg)](https://docs.rs/cadence/)
[![crates.io](https://img.shields.io/crates/v/cadence.svg)](https://crates.io/crates/cadence/)
[![Rust 1.60+](https://img.shields.io/badge/rust-1.60+-lightgray.svg)](https://www.rust-lang.org)

[Cadence Documentation](https://docs.rs/cadence/)

[Macros Documentation](https://docs.rs/cadence-macros/)

An extensible Statsd client for Rust!

Cadence is a fast and flexible way to emit Statsd metrics from your application.

## Features

* [Support](https://docs.rs/cadence/) for emitting counters, timers, histograms, distributions,
  gauges, meters, and sets to Statsd over UDP (or optionally Unix sockets).
* Support for alternate backends via the `MetricSink` trait.
* Support for [Datadog](https://docs.datadoghq.com/developers/dogstatsd/) style metrics tags.
* [Macros](https://docs.rs/cadence-macros/) to simplify common calls to emit metrics
* A simple yet flexible API for sending metrics.

## Install

To make use of `cadence` in your project, add it as a dependency in your `Cargo.toml` file.

```toml
[dependencies]
cadence = "x.y.z"
```

That's all you need!

## Usage

Some examples of how to use Cadence are shown below. The examples start
simple and work up to how you should be using Cadence in a production
application.

### Simple Use

Simple usage of Cadence is shown below. In this example, we just import
the client, create an instance that will write to some imaginary metrics
server, and send a few metrics.

```rust
use std::net::UdpSocket;
use cadence::prelude::*;
use cadence::{StatsdClient, UdpMetricSink, DEFAULT_PORT};
// Create client that will write to the given host over UDP.
//
// Note that you'll probably want to actually handle any errors creating
// the client when you use it for real in your application. We're just
// using .unwrap() here since this is an example!
let host = ("metrics.example.com", DEFAULT_PORT);
let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
let sink = UdpMetricSink::from(host, socket).unwrap();
let client = StatsdClient::from_sink("my.metrics", sink);

// Emit metrics!
client.incr("some.counter");
client.time("some.methodCall", 42);
client.gauge("some.thing", 7);
client.meter("some.value", 5);
```

### Buffered UDP Sink

While sending a metric over UDP is very fast, the overhead of frequent
network calls can start to add up. This is especially true if you are
writing a high performance application that emits a lot of metrics.

To make sure that metrics aren't interfering with the performance of
your application, you may want to use a `MetricSink` implementation that
buffers multiple metrics before sending them in a single network
operation. For this, there's `BufferedUdpMetricSink`. An example of
using this sink is given below.

```rust
use std::net::UdpSocket;
use cadence::prelude::*;
use cadence::{StatsdClient, BufferedUdpMetricSink, DEFAULT_PORT};

let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
socket.set_nonblocking(true).unwrap();

let host = ("metrics.example.com", DEFAULT_PORT);
let sink = BufferedUdpMetricSink::from(host, socket).unwrap();
let client = StatsdClient::from_sink("my.prefix", sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
client.incr("some.event");
```

As you can see, using this buffered UDP sink is no more complicated
than using the regular, non-buffered, UDP sink.

The only downside to this sink is that metrics aren't written to the
Statsd server until the buffer is full. If you have a busy application
that is constantly emitting metrics, this shouldn't be a problem.
However, if your application only occasionally emits metrics, this sink
might result in the metrics being delayed for a little while until the
buffer fills. In this case, it may make sense to use the `UdpMetricSink`
since it does not do any buffering.

### Queuing Asynchronous Metric Sink

To make sure emitting metrics doesn't interfere with the performance
of your application (even though emitting metrics is generally quite
fast), it's probably a good idea to make sure metrics are emitted in
in a different thread than your application thread.

To allow you to do this, there is `QueuingMetricSink`. This sink allows
you to wrap any other metric sink and send metrics to it via a queue,
as it emits metrics in another thread, asynchronously from the flow of
your application.

The requirements for the wrapped metric sink are that it is thread
safe, meaning that it implements the `Send` and `Sync` traits. If
you're using the `QueuingMetricSink` with another sink from Cadence,
you don't need to worry: they are all thread safe.

An example of using the `QueuingMetricSink` to wrap a buffered UDP
metric sink is given below. This is the preferred way to use Cadence
in production.

```rust
use std::net::UdpSocket;
use cadence::prelude::*;
use cadence::{StatsdClient, QueuingMetricSink, BufferedUdpMetricSink, DEFAULT_PORT};

let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
socket.set_nonblocking(true).unwrap();

let host = ("metrics.example.com", DEFAULT_PORT);
let udp_sink = BufferedUdpMetricSink::from(host, socket).unwrap();
let queuing_sink = QueuingMetricSink::from(udp_sink);
let client = StatsdClient::from_sink("my.prefix", queuing_sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
```

In the example above, we use the default constructor for the queuing
sink which creates an **unbounded** queue, with no maximum size, to connect
the main thread where the client sends metrics to the background thread
in which the wrapped sink is running. If instead, you want to create a
**bounded** queue with a maximum size, you can use the `with_capacity`
constructor. An example of this is given below.

```rust
use std::net::UdpSocket;
use cadence::prelude::*;
use cadence::{StatsdClient, QueuingMetricSink, BufferedUdpMetricSink,
              DEFAULT_PORT};

// Queue with a maximum capacity of 128K elements
const QUEUE_SIZE: usize = 128 * 1024;

let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
socket.set_nonblocking(true).unwrap();

let host = ("metrics.example.com", DEFAULT_PORT);
let udp_sink = BufferedUdpMetricSink::from(host, socket).unwrap();
let queuing_sink = QueuingMetricSink::with_capacity(udp_sink, QUEUE_SIZE);
let client = StatsdClient::from_sink("my.prefix", queuing_sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
client.incr("some.event");
```

Using a `QueuingMetricSink` with a capacity set means that when the queue
is full, attempts to emit metrics via the `StatsdClient` will fail. While
this is bad, the alternative (if you instead used an unbounded queue) is
for unsent metrics to slowly use up more and more memory until your
application exhausts all memory.

Using an **unbounded** queue means that the sending of metrics can absorb
slowdowns of sending metrics until your application runs out of memory.
Using a **bounded** queue puts a cap on the amount of memory that sending
metrics will use in your application. This is a tradeoff that users of
Cadence must decide for themselves.

It is also possible to supply an error handler for a `QueuingMetricSink` to
be called whenever the wrapped sink cannot send metrics for whatever reason.

```rust
use std::net::UdpSocket;
use cadence::prelude::*;
use cadence::{StatsdClient, QueuingMetricSink, BufferedUdpMetricSink,
              DEFAULT_PORT};

// Queue with a maximum capacity of 128K elements
const QUEUE_SIZE: usize = 128 * 1024;

let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
socket.set_nonblocking(true).unwrap();

let host = ("metrics.example.com", DEFAULT_PORT);
let udp_sink = BufferedUdpMetricSink::from(host, socket).unwrap();
let queuing_sink = QueuingMetricSink::builder()
    .with_capacity(QUEUE_SIZE)
    .with_error_handler(|e| {
         eprintln!("Error while sending metrics: {:?}", e);
    })
    .build(udp_sink);
let client = StatsdClient::from_sink("my.prefix", queuing_sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
```

### Use With Tags

Adding tags to metrics is accomplished via the use of each of the `_with_tags`
methods that are part of the Cadence `StatsdClient` struct. An example of using
these methods is given below. Note that tags are an extension to the Statsd
protocol and so may not be supported by all servers.

See the [Datadog docs](https://docs.datadoghq.com/developers/dogstatsd/) for
more information.

```rust
use cadence::prelude::*;
use cadence::{Metric, StatsdClient, NopMetricSink};

let client = StatsdClient::from_sink("my.prefix", NopMetricSink);

let res = client.count_with_tags("my.counter", 29)
    .with_tag("host", "web03.example.com")
    .with_tag_value("beta-test")
    .try_send();

assert_eq!(
    concat!(
        "my.prefix.my.counter:29|c|#",
        "host:web03.example.com,",
        "beta-test"
    ),
    res.unwrap().as_metric_str()
);
```

### Default Tags

Default tags can be added to a `StatsdClient` when constructed using the builder.
Default tags are added to every metric emitted by the `StatsdClient` without any
extra work after building the client. Note that tags are an extension to the Statsd
protocol and so may not be supported by all servers.

See the [Datadog docs](https://docs.datadoghq.com/developers/dogstatsd/) for
more information.

```rust
use cadence::prelude::*;
use cadence::{Metric, StatsdClient, NopMetricSink};

let client = StatsdClient::builder("my.prefix", NopMetricSink)
    .with_tag("env", "prod")
    .with_tag("app", "auth")
    .build();

let res = client.count_with_tags("my.counter", 29)
    .with_tag("host", "web03.example.com")
    .with_tag_value("beta-test")
    .try_send();

assert_eq!(
    concat!(
        "my.prefix.my.counter:29|c|#",
        "env:prod,",
        "app:auth,",
        "host:web03.example.com,",
        "beta-test"
    ),
    res.unwrap().as_metric_str()
);
```

### Value Packing

Value packing allows multiple values to be sent as a single metric for histograms,
distributions, and timer types. The Cadence client accepts `Vec<T>` for histogram,
distribution, and timer methods and will format multiple values as described below.
Note that this feature is a Datadog extension and so may not be supported by your
server. It is supported by versions `>=v6.25.0 && <v7.0.0` or `>=v7.25.0` of the
Datadog agent.

Packed metrics have the following format:
```text
<METRIC_NAME>:<VALUE1>:<VALUE2>:<VALUE3>|<TYPE>|#<TAG_KEY_1>:<TAG_VALUE_1>,<TAG_2>`
```

See the [Datadog Docs](https://docs.datadoghq.com/developers/dogstatsd/datagram_shell/?tab=metrics#dogstatsd-protocol-v11)
for more information.

```rust
use cadence::prelude::*;
use cadence::{Metric, StatsdClient, NopMetricSink};

let client = StatsdClient::from_sink("my.prefix", NopMetricSink);

let res = client.distribution_with_tags("my.distribution", vec![29, 30, 31, 32])
    .with_tag("host", "web03.example.com")
    .with_tag_value("beta-test")
    .try_send();

assert_eq!(
    concat!(
        "my.prefix.my.distribution:29:30:31:32|d|#",
        "host:web03.example.com,",
        "beta-test"
    ),
    res.unwrap().as_metric_str()
);
```

### Implemented Traits

Each of the methods that the Cadence `StatsdClient` struct uses to send
metrics are implemented as a trait. There is also a trait that combines
all of these other traits. If we want, we can just use one of the trait
types to refer to the client instance. This might be useful to you if
you'd like to swap out the actual Cadence client with a dummy version
when you are unit testing your code or want to abstract away all the
implementation details of the client being used behind a trait and
pointer.

Each of these traits are exported in the prelude module. They are also
available in the main module but aren't typically used like that.

```rust
use cadence::prelude::*;
use cadence::{StatsdClient, UdpMetricSink, DEFAULT_PORT};

pub struct User {
    id: u64,
    username: String,
    email: String
}

// Here's a simple DAO (Data Access Object) that doesn't do anything but
// uses a metric client to keep track of the number of times the
// 'getUserById' method gets called.
pub struct MyUserDao {
    metrics: Box<dyn MetricClient>
}

impl MyUserDao {
    // Create a new instance that will use the StatsdClient
    pub fn new<T: MetricClient + 'static>(metrics: T) -> MyUserDao {
        MyUserDao { metrics: Box::new(metrics) }
    }

    /// Get a new user by their ID
    pub fn get_user_by_id(&self, id: u64) -> Option<User> {
        self.metrics.incr("getUserById");
        None
    }
}

// Create a new Statsd client that writes to "metrics.example.com"
let host = ("metrics.example.com", DEFAULT_PORT);
let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
let sink = UdpMetricSink::from(host, socket).unwrap();
let metrics = StatsdClient::from_sink("counter.example", sink);

// Create a new instance of the DAO that will use the client
let dao = MyUserDao::new(metrics);

// Try to lookup a user by ID!
match dao.get_user_by_id(123) {
    Some(u) => println!("Found a user!"),
    None => println!("No user!")
};
```

### Quiet Metric Sending and Error Handling

When sending metrics sometimes you don't really care about the `Result` of
trying to send it or maybe you just don't want to deal with it inline with
the rest of your code. In order to handle this, Cadence allows you to set a
default error handler. This handler is invoked when there are errors sending
metrics so that the calling code doesn't have to deal with them.

An example of configuring an error handler and an example of when it might
be invoked is given below.

```rust
use cadence::prelude::*;
use cadence::{MetricError, StatsdClient, NopMetricSink};

fn my_error_handler(err: MetricError) {
    println!("Metric error! {}", err);
}

let client = StatsdClient::builder("prefix", NopMetricSink)
    .with_error_handler(my_error_handler)
    .build();

// When sending metrics via the `MetricBuilder` used for assembling tags,
// callers may opt into sending metrics quietly via the `.send()` method
// as opposed to the `.try_send()` method
client.count_with_tags("some.counter", 42)
    .with_tag("region", "us-east-2")
    .send();
```

### Custom Metric Sinks

The Cadence `StatsdClient` uses implementations of the `MetricSink`
trait to send metrics to a metric server. Most users of the Cadence
library probably want to use the `QueuingMetricSink` wrapping an instance
of the `BufferedMetricSink`.

However, maybe you want to do something not covered by an existing sink.
An example of creating a custom sink is below.

```rust
use std::io;
use cadence::prelude::*;
use cadence::{StatsdClient, MetricSink, DEFAULT_PORT};

pub struct MyMetricSink;

impl MetricSink for MyMetricSink {
    fn emit(&self, metric: &str) -> io::Result<usize> {
        // Your custom metric sink implementation goes here!
        Ok(0)
    }
}

let sink = MyMetricSink;
let client = StatsdClient::from_sink("my.prefix", sink);

client.count("my.counter.thing", 42);
client.time("my.method.time", 25);
client.incr("some.other.counter");
```

### Custom UDP Socket

Most users of the Cadence `StatsdClient` will be using it to send metrics
over a UDP socket. If you need to customize the socket, for example you
want to use the socket in blocking mode but set a write timeout, you can
do that as demonstrated below.

```rust
use std::net::UdpSocket;
use std::time::Duration;
use cadence::prelude::*;
use cadence::{StatsdClient, UdpMetricSink, DEFAULT_PORT};

let socket = UdpSocket::bind("0.0.0.0:0").unwrap();
socket.set_write_timeout(Some(Duration::from_millis(1))).unwrap();

let host = ("metrics.example.com", DEFAULT_PORT);
let sink = UdpMetricSink::from(host, socket).unwrap();
let client = StatsdClient::from_sink("my.prefix", sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
client.incr("some.event");
client.set("users.uniques", 42);
```

### Unix Sockets

Cadence also supports using Unix datagram sockets with the `UnixMetricSink`  or
`BufferedUnixMetricSink`. Unix sockets can be used for sending metrics to a server
or agent running on the same machine (physical machine, VM, containers in a pod)
as your application. Unix sockets are somewhat similar to UDP sockets with a few
important differences:

* Sending metrics on a socket that doesn't exist or is not being listened to will
  result in an error.
* Metrics sent on a connected socket are guaranteed to be delievered (i.e. they are
  reliable as opposed to UDP sockets). However, it's still possible that the metrics
  won't be read by the server due to a variety of environment and server specific
  reasons.

An example of using the sinks is given below.

```rust
use std::os::unix::net::UnixDatagram;
use cadence::prelude::*;
use cadence::{StatsdClient, BufferedUnixMetricSink};

let socket = UnixDatagram::unbound().unwrap();
socket.set_nonblocking(true).unwrap();
let sink = BufferedUnixMetricSink::from("/run/statsd.sock", socket);
let client = StatsdClient::from_sink("my.prefix", sink);

client.count("my.counter.thing", 29);
client.time("my.service.call", 214);
client.incr("some.event");
client.set("users.uniques", 42);
```

NOTE: This feature is only available on Unix platforms (Linux, BSD, MacOS).

## Other

For more information about Cadence, see the [README in the repository root](../README.md).