prom-client

What is prom-client?

The prom-client npm package is a client for the Prometheus monitoring tool, which allows you to collect and expose metrics from your Node.js applications. It supports various metric types, custom labels, and can be integrated with the default Node.js metrics and other systems.

What are prom-client's main functionalities?

Counter

Counters are a metric that only goes up (e.g., page views, total number of requests).

const { Counter } = require('prom-client');
const httpRequestsTotal = new Counter({
  name: 'http_requests_total',
  help: 'Total number of HTTP requests'
});

httpRequestsTotal.inc(); // Increment by 1
httpRequestsTotal.inc(5); // Increment by a given value

Gauge

Gauges are a metric that can go up or down (e.g., memory usage, number of active users).

const { Gauge } = require('prom-client');
const memoryUsageGauge = new Gauge({
  name: 'memory_usage_bytes',
  help: 'Memory usage in bytes'
});

memoryUsageGauge.set(process.memoryUsage().heapUsed); // Set to current heap used

Histogram

Histograms track the size and number of events in buckets (e.g., request durations or response sizes).

const { Histogram } = require('prom-client');
const httpRequestDuration = new Histogram({
  name: 'http_request_duration_seconds',
  help: 'Duration of HTTP requests in seconds',
  buckets: [0.1, 0.2, 0.5, 1, 5]
});

httpRequestDuration.observe(0.4); // Observe a value in seconds

Summary

Summaries calculate percentiles of observed values (e.g., long-tail request durations).

const { Summary } = require('prom-client');
const httpRequestDurationSummary = new Summary({
  name: 'http_request_duration_summary',
  help: 'Summary of HTTP request durations',
  percentiles: [0.5, 0.9, 0.99]
});

httpRequestDurationSummary.observe(0.3); // Observe a value in seconds

Default Metrics

Collect default metrics from Node.js runtime and system, such as CPU usage, event loop lag, etc.

const { collectDefaultMetrics } = require('prom-client');
collectDefaultMetrics();

Other packages similar to prom-client

metrics-client

This package is similar to prom-client in that it provides a way to collect and expose metrics for monitoring purposes. However, it is not specifically tied to Prometheus and can be used with other monitoring tools.

appmetrics-prometheus

This package is a Prometheus monitoring and metrics exporter for Node.js applications. It is similar to prom-client but is built on top of the appmetrics library, which provides additional insights into the Node.js runtime.

express-prom-bundle

This package is an Express middleware that automatically records request durations and exposes them in Prometheus format. It is similar to prom-client but is more focused on Express applications and provides out-of-the-box middleware for easy integration.

README

Prometheus client for node.js

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. 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 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 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:

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:

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:

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):

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.

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 for information on how to configure labels for all metric types.

Counter

Counters go up, and reset when the process restarts.

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.

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:

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 */);
  },
});

// 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

// Set value to current time:
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.)

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

Examples

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

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.)

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:

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

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.

Examples

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

Utility Methods

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:

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);
// 3nd 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:

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:

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

import * as client from 'prom-client';

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

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

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

Default Labels (segmented by registry)

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

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.

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.

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:

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 await 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.

const metrics = await register.clusterMetrics();

// - or -

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

Pushgateway

It is possible to push metrics via a Pushgateway.

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

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

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

// 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,
  }),
});

Bucket Generators

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

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
});

The content-type prometheus expects is also exported as a constant, both on the register and from the main file of this project, called contentType.

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.)