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Node.js client library for SignalFx

This is a programmatic interface in JavaScript for SignalFx's metadata and ingest APIs. It is meant to provide a base for communicating with SignalFx APIs that can be easily leveraged by scripts and applications to interact with SignalFx or report metric and event data to SignalFx.

Installation

To install using npm:

$ npm install signalfx

Usage

API access token

To use this library, you need a SignalFx API access token, which can be obtained from the SignalFx organization you want to report data into.

Create client

There are two ways to create an ingest client object:

  • The default constructor Ingest. This constructor uses Protobuf to send data to SignalFx. If it cannot send Protobuf, it falls back to sending JSON.
  • The JSON constructor IngestJson. This constructor uses JSON format to send data to SignalFx.
var signalfx = require('signalfx');

// Create default client
var client = new signalfx.Ingest('MY_SIGNALFX_TOKEN', {options});
// or create JSON client
var clientJson = new signalfx.IngestJson('MY_SIGNALFX_TOKEN', {options});

Object options is an optional map and may contains following fields:

  • enableAmazonUniqueId - boolean, false by default. If true, library will retrieve Amazon unique identifier and set it as AWSUniqueId dimension for each datapoint and event. Use this option only if your application deployed to Amazon
  • dimensions - object, pre-defined dimensions for each datapoint and event. This object has key-value format { dimension_name: dimension_value, ...}
  • ingestEndpoint - string, custom url to send datapoints in format http://custom.domain/api/path
  • timeout - number, sending datapoints timeout in ms (default is 5000ms)
  • batchSize - number, batch size to group sending datapoints
  • userAgents - array of strings, items from this array will be added to 'user-agent' header separated by comma
  • proxy - string, defines an address and credentials for sending metrics through a proxy server. The string should have the following format http://<USER>:<PASSWORD>@<HOST>:<PORT>

Reporting data

This example shows how to report metrics to SignalFx, as gauges, counters, or cumulative counters.

var signalfx = require('signalfx');

var client = new signalfx.Ingest('MY_SIGNALFX_TOKEN');

client.send({
           cumulative_counters:[
             {  metric: 'myfunc.calls_cumulative', 
                value: 10,
                timestamp: 1442960607000},
             ...
           ],
           gauges:[
             {  metric: 'myfunc.time', 
                value: 532,
                timestamp: 1442960607000},
             ...
           ],
           counters:[
             {  metric: 'myfunc.calls', 
                value: 42,
                timestamp: 1442960607000},
             ...
           ]});

The timestamp must be a millisecond precision timestamp; the number of milliseconds elapsed since Epoch. The timestamp field is optional, but strongly recommended. If not specified, it will be set by SignalFx's ingest servers automatically; in this situation, the timestamp of your datapoints will not accurately represent the time of their measurement (network latency, batching, etc. will all impact when those datapoints actually make it to SignalFx).

Sending multi-dimensional data

Reporting dimensions for the data is also optional, and can be accomplished by specifying a dimensions parameter on each datapoint containing a dictionary of string to string key/value pairs representing the dimensions:

var signalfx = require('signalfx');

var client = new signalfx.Ingest('MY_SIGNALFX_TOKEN');

client.send({
          cumulative_counters:[
            { 'metric': 'myfunc.calls_cumulative', 
              'value': 10, 
              'dimensions': {'host': 'server1', 'host_ip': '1.2.3.4'}},
            ...
          ],
          gauges:[
            { 'metric': 'myfunc.time', 
              'value': 532, 
              'dimensions': {'host': 'server1', 'host_ip': '1.2.3.4'}},
            ...
          ],
          counters:[
            { 'metric': 'myfunc.calls', 
              'value': 42, 
              'dimensions': {'host': 'server1', 'host_ip': '1.2.3.4'}},
            ...
          ]});

Sending events

Events can be send to SignalFx via the sendEvent function. The event param objects must be specified. Event param object is an optional map and may contains following fields:

  • eventType (string) - Required field. The event type (name of the event time series).
  • category (int) - the category of event. Choose one from EVENT_CATEGORIES list. Different categories of events are supported.Available categories of events are USER_DEFINED, ALERT, AUDIT, JOB, COLLECTD, SERVICE_DISCOVERY, EXCEPTION. For mode details see proto/signal_fx_protocol_buffers.proto file. Value by default is USER_DEFINED
  • dimensions (dict) - a map of event dimensions, empty dictionary by default
  • properties (dict) - a map of extra properties on that event, empty dictionary by default
  • timestamp (int64) - a timestamp, by default is current time Also please specify event category: for that get option from dictionary client.EVENT_CATEGORIES.
var signalfx = require('signalfx');

var client = new signalfx.Ingest('MY_SIGNALFX_TOKEN');

client.sendEvent({
          category: '[event_category]',
          eventType: '[event_type]',
          dimensions: {
              'host': 'myhost',
              'service': 'myservice',
              'instance': 'myinstance'
          },
          properties: {
              'version': 'event_version'},
          timestamp: timestamp})

Examples

Complete code example for Reporting data

var signalfx = require('signalfx');

var myToken = 'MY_SIGNALFX_TOKEN';

var client = new signalfx.Ingest(myToken);
var gauges = [{
        metric: 'test.cpu',
        value: 10
      }];

var counters = [{
        metric: 'cpu_cnt',
        value:  2
      }];
      
client.send({gauges: gauges, counters: counters});

Complete code example for Sending events

var signalfx = require('signalfx');

var myToken = '[MY_SIGNALFX_TOKEN]';

var client = new signalfx.Ingest(myToken);

var eventCategory = client.EVENT_CATEGORIES.USER_DEFINED
var eventType = 'deployment'
var dimensions = {
     host: 'myhost',
     service: 'myservice',
     instance: 'myinstance'
  };
var properties = {version: '[EVENT-VERSION]'};

client.sendEvent({category: eventCategory, 
            eventType: eventType, 
            dimensions: dimensions, 
            properties:properties});

See example/generic_usage.js for a complete code example for Reporting data. Set your SignalFx token and run example

$ node path/to/example/generic_usage.js

SignalFlow API

API access token

To use the SignalFlow library, you need a SignalFx user access token, which can be obtained from the SignalFx via the REST API(https://developers.signalfx.com/docs/session)

SignalFlow

Examples

Complete code example for executing a computation

var signalfx = require('signalfx');

var myToken = '[MY_SIGNALFX_TOKEN]';

var client = new signalfx.SignalFlow(myToken);

var handle = client.execute({
            program: "data('cpu.utilization').mean().publish()",
            start: Date.now() - 60000,
            stop: Date.now() + 60000,
            resolution: 10000,
            immediate: false});

handle.stream(function(err, data) { console.log(data); });

Please note that a token created via the REST API is necessary to use this API. API Access tokens intended for ingest are not allowed.

API Options

Parameters to the execute method are as follows :

  • program (string) - Required field. The signalflow to be run.
  • start (int | string) - A milliseconds since epoch number or a string representing a relative time : e.g. -1h. Defaults to now.
  • stop (int | string) - A milliseconds since epoch number or a string representing a relative time : e.g. -30m. Defaults to infinity.
  • resolution (int) - The interval across which to calculate, in 1000 millisecond intervals. Defaults to 1000.
  • maxDelay (int) - The maximum time to wait for a datapoint to arrive, in 10000 millisecond intervals. Defaults to dynamic.
  • bigNumber (boolean) - True if returned values require precision beyond MAX_SAFE_INTEGER. Returns all values in data messages as bignumber objects as per https://www.npmjs.com/package/bignumber.js Defaults to false.
  • immediate (boolean) - Whether to adjust the stop timestamp so that the computation doesn't wait for future data to be available.

Computation Objects

The returned object from an execute call possesses the following methods:

  • stream (function (err, data)) - accepts a function and will call the function with computation messages when available. It returns multiple types of messages, detailed below. This follows error first callback conventions, so data is returned in the second argument if no errors occurred.
  • close () - terminates the computation.
  • get_known_tsids () - gets all known timeseries ID's for the current computation
  • get_metadata (string) - gets the metadata message associated with the specific timeseries ID.

Stream Message Types

  • Metadata
{
  type : "metadata",
  channel : "<CHID>",
  properties : {
    sf_key : [<String>]
    sf_metric: <String>
    ...
  }, 
  tsId : "<ID>"
}
  • Data
{
  type : "data",
  channel : "<CHID>",
  data : [
    {
      tsId : "<ID>",
      value : <Number>
    }, 
    ...
  ],
  logicalTimestampMs : <Number>
}
  • Event
{
  tsId : "<ID>",
  timestampMs: 1461353198000,
  channel: "<CHID>",
  type: "event",
  properties: {
    incidentId: "<ID>",
    "inputValues" : "{\"a\":4}",
    was: "ok",
    is: "anomalous"
  }
}

More information about messages can be found at https://developers.signalfx.com/v2/docs/stream-messages-specification

Usage in a Web Browser

The signalflow client can be built for usage in a browser. This is accomplished via the following commands.

$ npm install
$ gulp browserify
The output can be found at ./build/signalfx.js

It can then be loaded as usual via a script tag

<script src="build/signalfx.js" type="text/javascript"></script>

Once loaded, a signalfx global will be created(window.signalfx). Note that only the SignalFlow package is included in this built file.

Browser Usage Example using D3

First ensure your current working directory is the root of the nodejs repository clone, then do the following :

Make the following changes to example/index.html

replace 'YOUR USER TOKEN' with your own token.
replace 'cpu.utilization' with an appropriate metric as necessary.

Execute the following commands

$ npm install
$ gulp browserify
$ node example/server.js

Finally, open http://localhost:8888/example/index.html

License

Apache Software License v2 © SignalFx

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