measured-core

What is measured-core?

The measured-core npm package provides a set of tools for measuring and monitoring various metrics in your Node.js applications. It includes features for creating counters, histograms, meters, and timers, which can be used to track performance and other metrics.

What are measured-core's main functionalities?

Counter

Counters are used to count events. You can increment or decrement the counter and retrieve the current count.

const { Counter } = require('measured-core');
const counter = new Counter();
counter.inc();
counter.dec();
console.log(counter.toJSON());

Histogram

Histograms measure the distribution of values in a stream of data. You can update the histogram with new values and retrieve statistical information about the distribution.

const { Histogram } = require('measured-core');
const histogram = new Histogram();
histogram.update(1);
histogram.update(2);
histogram.update(3);
console.log(histogram.toJSON());

Meter

Meters measure the rate of events over time. You can mark events and retrieve the rate of events per second.

const { Meter } = require('measured-core');
const meter = new Meter();
meter.mark();
meter.mark(2);
console.log(meter.toJSON());

Timer

Timers measure the duration of events. You can start and stop the timer to measure how long an operation takes and retrieve statistical information about the durations.

const { Timer } = require('measured-core');
const timer = new Timer();
const end = timer.start();
setTimeout(() => {
  end();
  console.log(timer.toJSON());
}, 1000);

Other packages similar to measured-core

prom-client

The prom-client package is a Prometheus client for Node.js that provides similar functionality for measuring and monitoring metrics. It includes features for creating counters, gauges, histograms, and summaries. Compared to measured-core, prom-client is specifically designed to work with Prometheus, a popular monitoring and alerting toolkit.

statsd-client

The statsd-client package is a StatsD client for Node.js that allows you to send metrics to a StatsD server. It supports counters, timers, gauges, and sets. Compared to measured-core, statsd-client is designed to work with StatsD, a network daemon that listens for statistics and aggregates them for visualization.

node-statsd

The node-statsd package is another StatsD client for Node.js. It provides similar functionality to statsd-client, allowing you to send metrics to a StatsD server. It supports counters, timers, gauges, and sets. Compared to measured-core, node-statsd is also designed to work with StatsD for metric aggregation and visualization.

README

Measured Core

The core measured library that has the Metric interfaces and implementations.

Install

npm install measured-core

What is in this package

Metric Implemenations

The core library has the following metrics classes:

Gauge

Values that can be read instantly via a supplied call back.

SettableGauge

Just like a Gauge but its value is set directly rather than supplied by a callback.

CachedGauge

Like a mix of the regular and settable Gauge it takes a call back that returns a promise that will resolve the cached value and an interval that it should call the callback on to update its cached value.

Counter

Counters are things that increment or decrement.

Timer

Timers are a combination of Meters and Histograms. They measure the rate as well as distribution of scalar events.

Histogram

Keeps a reservoir of statistically relevant values to explore their distribution.

Meter

Things that are measured as events / interval.

Registry

The core library comes with a basic registry class

Collection

that is not aware of dimensions / tags and leaves reporting up to you.

See the measured-reporting module for more advanced and featured registries.

Other

See The measured-core modules for the full list of exports for require('measured-core').

Usage

Step 1: Add measurements to your code. For example, lets track the requests/sec of a http server:

var http  = require('http');
var stats = require('measured').createCollection();

http.createServer(function(req, res) {
  stats.meter('requestsPerSecond').mark();
  res.end('Thanks');
}).listen(3000);

Step 2: Show the collected measurements (more advanced examples follow later):

setInterval(function() {
  console.log(stats.toJSON());
}, 1000);

This will output something like this every second:

{ requestsPerSecond:
   { mean: 1710.2180279856818,
     count: 10511,
     'currentRate': 1941.4893498239829,
     '1MinuteRate': 168.08263156623656,
     '5MinuteRate': 34.74630977619571,
     '15MinuteRate': 11.646507524106095 } }

Step 3: Aggregate the data into your backend of choice. Here are a few time series data aggregators.

• Graphite
  • A free and open source, self hosted and managed solution for time series data.
• SignalFx
  • An enterprise SASS offering for time series data.
• Datadog
  • An enterprise SASS offering for time series data.