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mongo-metrics

When its comes to metrics, aggregations plays a huge role. If that fails, then there is no use of collecting metrics. Here is the how mongo-metrics thinks about it.

  • There are sources who generate metrics
  • metrics will be collected with the awareness of the source
  • When it comes aggregations, metrics will be aggregated in 2 steps
  • It will first aggregate values in each source, then result will be aggregated
  • function which used to aggregate metrics can be specified in runtime
  • result will be grouped into time resolutions

Design Decisions

  • Cloud Ready
  • Portable and Flexible Design
  • Simple to use

Dependencies

  • Mongodb (2.1+)
  • NodeJs

Tracking Metrics

Currently tracking is only supported for nodejs apps. For other apps, you have to wait for UDP and HTTP APIs (patches are welcome)

	var MongoMetrics = require('mongo-metrics');

	var MONGODB_URL = "mongodb://localhost/test";
	var metrics = new MongoMetrics(MONGODB_URL);

	metrics.track('no-of-users', 344, 'my-source', function(err) {

	});

Aggregate Metrics

This API is for developer who need to play with metrics. Use dashboard(see below) which build on top of this API

API

@param {String} name - name of the metric
    @param {Constant} resolution - resolution type
        possible values: "DAY", "HOUR", "MINUTE", "FIVE_SECS"
    @param {String} valueAggregator - aggregation function to be used for aggregating metric of the each source
        possible values: "sum", "avg", "min", "max"
    @param {String} sourceAggregator - aggregation function to be used for the aggregating sources(value from metricsAggregation)
        possible values: "sum", "avg", "min", "max"
    @param {Object} query - mongodb query for filtering out metrics
        only supports date and source only
    @param {Function} callback - callback function
        callback(err, results)

MongoMetrics.aggregate = function(name, resolution, valueAggregator, sourceAggregator, query, callback){}

Example

	
var MongoMetrics = require('mongo-metrics');

var MONGODB_URL = "mongodb://localhost/test";
var metrics = new MongoMetrics(MONGODB_URL);

metrics.aggregate('no-of-users', 'hour', 'avg', 'sum', {date: { $gte: 1361030882576 }}, function(err, result) {

});

Dashboard

With Dashboard you can correlate and visualize your metrics. There are few ways you can access the dashboard.

Dashboard

1. Standalone App

Install mongo-metrics binary via npm
npm install mongo-metrics -g
Start Dashboard
mongo-metrics -m <mongodb url>

2. With NodeJS

var dashboard = require('mongo-metrics/dashboard');

var MONGO_URL = "mongodb://localhost/test";
var PORT = 5005;
dashboard.listen(MONGO_URL, PORT);

3. Embed with an existing express webapp

var express     = require('express');
var dashboard   = require('mongo-metrics/dashboard');
var webapp      = express();

var MONGO_URL = "mongodb://localhost/test";
dashboard.listen(MONGO_URL, webapp);

webapp.listen(5005);

Defining Graphs

Dashboard

Inside the Dashboard you can create as many graphs as you need. You can correlate metrics too. (use area chart type)

There is no UI for defining graphs. But we have simple and flexible syntax to define them.

We simply did no use JSON since, it is too heavy for taking user inputs

Syntax

Here is how you define a graph.

<title for graph> | <graph-type> | <metric-name> | <value-aggregator>, <source-aggregator> | <resolution> | <time-length>

eg:- CPU Usage | area | cpu | avg, sum | five_secs | 1000 * 60 * 15

  • Supported values for graph-type : area, line
  • Supported values for value-aggregator : sum, avg, min, max
  • Supported values for source-aggregator : sum, avg, min, max
  • Supported values for resolution : five_secs, minute, hour, day
  • You can use multiple lines to specify multiple graphs
  • Empty lines add empty block to dashboard instead of the graph

Permalink URLs

  • Configuration you do will be saved in the URL.
  • So you can simply copy URL and share with others.
  • You can http://bit.ly or http://goo.gl to shorten the URL

Todo

See: Issues

About

Metrics tracking and aggregation with MongoDB

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