README.md

# Prometheus client for node.js [![Actions Status](https://github.com/siimon/prom-client/workflows/Node.js%20CI/badge.svg?branch=master)](https://github.com/siimon/prom-client/actions)

A prometheus client for Node.js that supports histogram, summaries, gauges and
counters.

## Usage

See example folder for a sample usage. The library does not bundle any web
framework. To expose the metrics, respond to Prometheus's scrape requests with
the result of `await registry.metrics()`.

### Usage with Node.js's `cluster` module

Node.js's `cluster` module spawns multiple processes and hands off socket
connections to those workers. Returning metrics from a worker's local registry
will only reveal that individual worker's metrics, which is generally
undesirable. To solve this, you can aggregate all of the workers' metrics in the
master process. See `example/cluster.js` for an example.

Default metrics use sensible aggregation methods. (Note, however, that the event
loop lag mean and percentiles are averaged, which is not perfectly accurate.)
Custom metrics are summed across workers by default. To use a different
aggregation method, set the `aggregator` property in the metric config to one of
'sum', 'first', 'min', 'max', 'average' or 'omit'. (See `lib/metrics/version.js`
for an example.)

If you need to expose metrics about an individual worker, you can include a
value that is unique to the worker (such as the worker ID or process ID) in a
label. (See `example/server.js` for an example using
`worker_${cluster.worker.id}` as a label value.)

Metrics are aggregated from the global registry by default. To use a different
registry, call
`client.AggregatorRegistry.setRegistries(registryOrArrayOfRegistries)` from the
worker processes.

## API

### Default metrics

There are some default metrics recommended by Prometheus
[itself](https://prometheus.io/docs/instrumenting/writing_clientlibs/#standard-and-runtime-collectors).
To collect these, call `collectDefaultMetrics`. In addition, some
Node.js-specific metrics are included, such as event loop lag, active handles,
GC and Node.js version. See [lib/metrics](lib/metrics) for a list of all
metrics.

NOTE: Some of the metrics, concerning File Descriptors and Memory, are only
available on Linux.

`collectDefaultMetrics` optionally accepts a config object with following entries:

- `prefix` an optional prefix for metric names. Default: no prefix.
- `register` to which registry the metrics should be registered. Default: the global default registry.
- `gcDurationBuckets` with custom buckets for GC duration histogram. Default buckets of GC duration histogram are `[0.001, 0.01, 0.1, 1, 2, 5]` (in seconds).
- `eventLoopMonitoringPrecision` with sampling rate in milliseconds. Must be greater than zero. Default: 10.

To register metrics to another registry, pass it in as `register`:

```js
const client = require('prom-client');
const collectDefaultMetrics = client.collectDefaultMetrics;
const Registry = client.Registry;
const register = new Registry();
collectDefaultMetrics({ register });
```

To use custom buckets for GC duration histogram, pass it in as `gcDurationBuckets`:

```js
const client = require('prom-client');
const collectDefaultMetrics = client.collectDefaultMetrics;
collectDefaultMetrics({ gcDurationBuckets: [0.1, 0.2, 0.3] });
```

To prefix metric names with your own arbitrary string, pass in a `prefix`:

```js
const client = require('prom-client');
const collectDefaultMetrics = client.collectDefaultMetrics;
const prefix = 'my_application_';
collectDefaultMetrics({ prefix });
```

To apply generic labels to all default metrics, pass an object to the `labels` property (useful if you're working in a clustered environment):

```js
const client = require('prom-client');
const collectDefaultMetrics = client.collectDefaultMetrics;
collectDefaultMetrics({
  labels: { NODE_APP_INSTANCE: process.env.NODE_APP_INSTANCE },
});
```

You can get the full list of metrics by inspecting
`client.collectDefaultMetrics.metricsList`.

Default metrics are collected on scrape of metrics endpoint,
not on an interval.

```js
const client = require('prom-client');

const collectDefaultMetrics = client.collectDefaultMetrics;

collectDefaultMetrics();
```

### Custom Metrics

All metric types have two mandatory parameters: `name` and `help`. Refer to
<https://prometheus.io/docs/practices/naming/> for guidance on naming metrics.

For metrics based on point-in-time observations (e.g. current memory usage, as
opposed to HTTP request durations observed continuously in a histogram), you
should provide a `collect()` function, which will be invoked when Prometheus
scrapes your metrics endpoint. `collect()` can either be synchronous or return a
promise. See **Gauge** below for an example. (Note that you should not update
metric values in a `setInterval` callback; do so in this `collect` function
instead.)

See [**Labels**](#labels) for information on how to configure labels for all
metric types.

#### Counter

Counters go up, and reset when the process restarts.

```js
const client = require('prom-client');
const counter = new client.Counter({
  name: 'metric_name',
  help: 'metric_help',
});
counter.inc(); // Increment by 1
counter.inc(10); // Increment by 10
```

#### Gauge

Gauges are similar to Counters but a Gauge's value can be decreased.

```js
const client = require('prom-client');
const gauge = new client.Gauge({ name: 'metric_name', help: 'metric_help' });
gauge.set(10); // Set to 10
gauge.inc(); // Increment 1
gauge.inc(10); // Increment 10
gauge.dec(); // Decrement by 1
gauge.dec(10); // Decrement by 10
```

##### Configuration

If the gauge is used for a point-in-time observation, you should provide a
`collect` function:

```js
const client = require('prom-client');
new client.Gauge({
  name: 'metric_name',
  help: 'metric_help',
  collect() {
    // Invoked when the registry collects its metrics' values.
    // This can be synchronous or it can return a promise/be an async function.
    this.set(/* the current value */);
  },
});
```

```js
// Async version:
const client = require('prom-client');
new client.Gauge({
  name: 'metric_name',
  help: 'metric_help',
  async collect() {
    // Invoked when the registry collects its metrics' values.
    const currentValue = await somethingAsync();
    this.set(currentValue);
  },
});
```

Note that you should not use arrow functions for `collect` because arrow
functions will not have the correct value for `this`.

##### Utility Functions

```js
// Set value to current time in seconds:
gauge.setToCurrentTime();

// Record durations:
const end = gauge.startTimer();
http.get('url', res => {
  end();
});
```

#### Histogram

Histograms track sizes and frequency of events.

##### Configuration

The defaults buckets are intended to cover usual web/RPC requests, but they can
be overridden. (See also [**Bucket Generators**](#bucket-generators).)

```js
const client = require('prom-client');
new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
  buckets: [0.1, 5, 15, 50, 100, 500],
});
```

##### Examples

```js
const client = require('prom-client');
const histogram = new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
});
histogram.observe(10); // Observe value in histogram
```

##### Utility Methods

```js
const end = histogram.startTimer();
xhrRequest(function (err, res) {
  const seconds = end(); // Observes and returns the value to xhrRequests duration in seconds
});
```

#### Summary

Summaries calculate percentiles of observed values.

##### Configuration

The default percentiles are: 0.01, 0.05, 0.5, 0.9, 0.95, 0.99, 0.999. But they
can be overridden by specifying a `percentiles` array. (See also
[**Bucket Generators**](#bucket-generators).)

```js
const client = require('prom-client');
new client.Summary({
  name: 'metric_name',
  help: 'metric_help',
  percentiles: [0.01, 0.1, 0.9, 0.99],
});
```

To enable the sliding window functionality for summaries you need to add
`maxAgeSeconds` and `ageBuckets` to the config like this:

```js
const client = require('prom-client');
new client.Summary({
  name: 'metric_name',
  help: 'metric_help',
  maxAgeSeconds: 600,
  ageBuckets: 5,
  pruneAgedBuckets: false,
});
```

The `maxAgeSeconds` will tell how old a bucket can be before it is reset and
`ageBuckets` configures how many buckets we will have in our sliding window for
the summary. If `pruneAgedBuckets` is `false` (default), the metric value will
always be present, even when empty (its percentile values will be `0`). Set
`pruneAgedBuckets` to `true` if you don't want to export it when it is empty.

##### Examples

```js
const client = require('prom-client');
const summary = new client.Summary({
  name: 'metric_name',
  help: 'metric_help',
});
summary.observe(10);
```

##### Utility Methods

```js
const end = summary.startTimer();
xhrRequest(function (err, res) {
  end(); // Observes the value to xhrRequests duration in seconds
});
```

### Labels

All metrics can take a `labelNames` property in the configuration object. All
label names that the metric support needs to be declared here. There are two
ways to add values to the labels:

```js
const client = require('prom-client');
const gauge = new client.Gauge({
  name: 'metric_name',
  help: 'metric_help',
  labelNames: ['method', 'statusCode'],
});

// 1st version: Set value to 100 with "method" set to "GET" and "statusCode" to "200"
gauge.set({ method: 'GET', statusCode: '200' }, 100);
// 2nd version: Same effect as above
gauge.labels({ method: 'GET', statusCode: '200' }).set(100);
// 3rd version: And again the same effect as above
gauge.labels('GET', '200').set(100);
```

It is also possible to use timers with labels, both before and after the timer
is created:

```js
const end = startTimer({ method: 'GET' }); // Set method to GET, we don't know statusCode yet
xhrRequest(function (err, res) {
  if (err) {
    end({ statusCode: '500' }); // Sets value to xhrRequest duration in seconds with statusCode 500
  } else {
    end({ statusCode: '200' }); // Sets value to xhrRequest duration in seconds with statusCode 200
  }
});
```

#### Zeroing metrics with Labels

Metrics with labels can not be exported before they have been observed at least
once since the possible label values are not known before they're observed.

For histograms, this can be solved by explicitly zeroing all expected label values:

```js
const histogram = new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
  buckets: [0.1, 5, 15, 50, 100, 500],
  labels: ['method'],
});
histogram.zero({ method: 'GET' });
histogram.zero({ method: 'POST' });
```

#### Strongly typed Labels

Typescript can also enforce label names using `as const`

```typescript
import * as client from 'prom-client';

const counter = new client.Counter({
  name: 'metric_name',
  help: 'metric_help',
  // add `as const` here to enforce label names
  labelNames: ['method'] as const,
});

// Ok
counter.inc({ method: 1 });

// this is an error since `'methods'` is not a valid `labelName`
// @ts-expect-error
counter.inc({ methods: 1 });
```

#### Default Labels (segmented by registry)

Static labels may be applied to every metric emitted by a registry:

```js
const client = require('prom-client');
const defaultLabels = { serviceName: 'api-v1' };
client.register.setDefaultLabels(defaultLabels);
```

This will output metrics in the following way:

```
# HELP process_resident_memory_bytes Resident memory size in bytes.
# TYPE process_resident_memory_bytes gauge
process_resident_memory_bytes{serviceName="api-v1"} 33853440 1498510040309
```

Default labels will be overridden if there is a name conflict.

`register.clear()` will clear default labels.

### Exemplars

The exemplars defined in the OpenMetrics specification can be enabled on Counter
and Histogram metric types. The default metrics have support for OpenTelemetry,
they will populate the exemplars with the labels `{traceId, spanId}` and their
corresponding values.

The format for `inc()` and `observe()` calls are different if exemplars are
enabled. They get a single object with the format
`{labels, value, exemplarLabels}`.

When using exemplars, the registry used for metrics should be set to OpenMetrics
type (including the global or default registry if no registries are specified).

### Registry type

The library supports both the old Prometheus format and the OpenMetrics format.
The format can be set per registry. For default metrics:

```js
const Prometheus = require('prom-client');
Prometheus.register.setContentType(
  Prometheus.Registry.OPENMETRICS_CONTENT_TYPE,
);
```

Currently available registry types are defined by the content types:

**PROMETHEUS_CONTENT_TYPE** - version 0.0.4 of the original Prometheus metrics,
this is currently the default registry type.

**OPENMETRICS_CONTENT_TYPE** - defaults to version 1.0.0 of the
[OpenMetrics standard](https://github.com/OpenObservability/OpenMetrics/blob/d99b705f611b75fec8f450b05e344e02eea6921d/specification/OpenMetrics.md).

The HTTP Content-Type string for each registry type is exposed both at module
level (`prometheusContentType` and `openMetricsContentType`) and as static
properties on the `Registry` object.

The `contentType` constant exposed by the module returns the default content
type when creating a new registry, currently defaults to Prometheus type.

### Multiple registries

By default, metrics are automatically registered to the global registry (located
at `require('prom-client').register`). You can prevent this by specifying
`registers: []` in the metric constructor configuration.

Using non-global registries requires creating a Registry instance and passing it
inside `registers` in the metric configuration object. Alternatively you can
pass an empty `registers` array and register it manually.

Registry has a `merge` function that enables you to expose multiple registries
on the same endpoint. If the same metric name exists in both registries, an
error will be thrown.

Merging registries of different types is undefined. The user needs to make sure
all used registries have the same type (Prometheus or OpenMetrics versions).

```js
const client = require('prom-client');
const registry = new client.Registry();
const counter = new client.Counter({
  name: 'metric_name',
  help: 'metric_help',
  registers: [registry], // specify a non-default registry
});
const histogram = new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
  registers: [], // don't automatically register this metric
});
registry.registerMetric(histogram); // register metric manually
counter.inc();

const mergedRegistries = client.Registry.merge([registry, client.register]);
```

If you want to use multiple or non-default registries with the Node.js `cluster`
module, you will need to set the registry/registries to aggregate from:

```js
const AggregatorRegistry = client.AggregatorRegistry;
AggregatorRegistry.setRegistries(registry);
// or for multiple registries:
AggregatorRegistry.setRegistries([registry1, registry2]);
```

### Register

You can get all metrics by running `await register.metrics()`, which will return
a string in the Prometheus exposition format.

#### Getting a single metric value in Prometheus exposition format

If you need to output a single metric in the Prometheus exposition format, you
can use `await register.getSingleMetricAsString(*name of metric*)`, which will
return a string for Prometheus to consume.

#### Getting a single metric

If you need to get a reference to a previously registered metric, you can use
`register.getSingleMetric(*name of metric*)`.

#### Removing metrics

You can remove all metrics by calling `register.clear()`. You can also remove a
single metric by calling `register.removeSingleMetric(*name of metric*)`.

#### Resetting metrics

If you need to reset all metrics, you can use `register.resetMetrics()`. The
metrics will remain present in the register and can be used without the need to
instantiate them again, like you would need to do after `register.clear()`.

#### Cluster metrics

You can get aggregated metrics for all workers in a Node.js cluster with
`await register.clusterMetrics()`. This method returns a promise that resolves
with a metrics string suitable for Prometheus to consume.

```js
const metrics = await register.clusterMetrics();

// - or -

register
  .clusterMetrics()
  .then(metrics => {
    /* ... */
  })
  .catch(err => {
    /* ... */
  });
```

### Pushgateway

It is possible to push metrics via a
[Pushgateway](https://github.com/prometheus/pushgateway).

```js
const client = require('prom-client');
let gateway = new client.Pushgateway('http://127.0.0.1:9091');

gateway.pushAdd({ jobName: 'test' })
	.then(({resp, body}) => {
		/* ... */
	})
	.catch(err => {
		/* ... */
	})); //Add metric and overwrite old ones
gateway.push({ jobName: 'test' })
	.then(({resp, body}) => {
		/* ... */
	})
	.catch(err => {
		/* ... */
	})); //Overwrite all metrics (use PUT)
gateway.delete({ jobName: 'test' })
	.then(({resp, body}) => {
		/* ... */
	})
	.catch(err => {
		/* ... */
	})); //Delete all metrics for jobName

//All gateway requests can have groupings on it
gateway.pushAdd({ jobName: 'test', groupings: { key: 'value' } })
	.then(({resp, body}) => {
		/* ... */
	})
	.catch(err => {
		/* ... */
	}));

// It's possible to extend the Pushgateway with request options from nodes core
// http/https library. In particular, you might want to provide an agent so that
// TCP connections are reused.
gateway = new client.Pushgateway('http://127.0.0.1:9091', {
  timeout: 5000, //Set the request timeout to 5000ms
  agent: new http.Agent({
    keepAlive: true,
    keepAliveMsec: 10000,
    maxSockets: 5,
  }),
});
```

Some gateways such as [Gravel Gateway](https://github.com/sinkingpoint/prometheus-gravel-gateway) do not support grouping by job name, exposing a plain `/metrics` endpoint instead of `/metrics/job/<jobName>`. It's possible to configure a gateway instance to not require a jobName in the options argument.

```js
gravelGateway = new client.Pushgateway('http://127.0.0.1:9091', {
  timeout: 5000,
  requireJobName: false,
});
gravelGateway.pushAdd();
```

### Bucket Generators

For convenience, there are two bucket generator functions - linear and
exponential.

```js
const client = require('prom-client');
new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
  buckets: client.linearBuckets(0, 10, 20), //Create 20 buckets, starting on 0 and a width of 10
});

new client.Histogram({
  name: 'metric_name',
  help: 'metric_help',
  buckets: client.exponentialBuckets(1, 2, 5), //Create 5 buckets, starting on 1 and with a factor of 2
});
```

### Garbage Collection Metrics

To avoid native dependencies in this module, GC statistics for bytes reclaimed
in each GC sweep are kept in a separate module:
https://github.com/SimenB/node-prometheus-gc-stats. (Note that that metric may
no longer be accurate now that v8 uses parallel garbage collection.)