A node.js port of codahale's metrics library: https://github.com/codahale/metrics
Metrics provides an instrumentation toolkit to measure the behavior of your critical systems while they're running in production.
The MIT License (MIT) Copyright (c) 2012 Mike Ihbe
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Import Metrics
metrics = require('metrics');
Typical production deployments have multiple node processes per server. Rather than each process exposing metrics on different ports, it makes more sense to expose the metrics from the "master" process. Writing a thin wrapper around this api to perform the process communication is trivial, with a message passing setup, the client processes could look something like this:
var Metric = exports = module.exports = function Metrics(messagePasser, eventType) {
this.messagePasser = messagePasser;
this.eventType = eventType;
}
Metric.prototype.newMetric = function(type, eventType) {
this.messagePasser.sendMessage({
method: 'createMetric'
, type: type
, eventType: eventType
});
}
Metric.prototype.forwardMessage = function(method, args) {
this.messagePasser.sendMessage({
method: 'updateMetric'
, metricMethod: method
, metricArgs: args
, eventType: this.eventType
});
}
Metric.prototype.update = function(val) { return this.forwardMessage('update', [val]); }
Metric.prototype.mark = function(n) { return this.forwardMessage('mark', [n]); }
Metric.prototype.inc = function(n) { return this.forwardMessage('inc', [n]); }
Metric.prototype.dec = function(n) { return this.forwardMessage('dec', [n]); }
Metric.prototype.clear = function() { return this.forwardMessage('clear'); }
And the server side that receives the createMetric and updateMetric rpcs could look something like this:
{
createMetric: function(msg) {
if (metricsServer) {
msg.type = msg.type[0].toUpperCase() + msg.type.substring(1)
metricsServer.addMetric(msg.eventType, new metrics[msg.type]);
}
}
updateMetric: function(msg) {
if (metricsServer) {
var namespaces = msg.eventType.split('.')
, event = namespaces.pop()
, namespace = namespaces.join('.');
var metric = metricsServer.trackedMetrics[namespace][event];
metric[msg.metricMethod].apply(metric, msg.metricArgs);
}
}
For multiple server deployments, you have more options, but the best approach will be highly application dependent. Best of luck, and always be tracking! Using the metrics server you can hit the server on your configured port and you'll get a json representation of your metrics. You should collect these periodically to generate timeseries to monitor the longterm health of your application. The metrics.Reporting object would let you write to a log periodically or however else you'd like to expose your metrics.