@opencensus/core

What is @opencensus/core?

The @opencensus/core package is a set of libraries for collecting, processing, and exporting telemetry data (metrics and traces) for analysis to improve the performance and reliability of applications. It is part of the OpenCensus project, which aims to provide a single, high-quality telemetry collection framework across multiple languages.

What are @opencensus/core's main functionalities?

Tracing

This feature allows the collection and export of trace data, which helps in understanding the flow of requests through various services and in identifying bottlenecks and latency issues.

const { Tracing } = require('@opencensus/core');
const tracing = Tracing.instance;

// Configure tracing
tracing.start({samplingRate: 1});

// Create a custom span
const rootSpan = tracing.tracer.startRootSpan({name: 'main'}, rootSpan => {
  // Do work within the span
  rootSpan.end(); // End the span
});

Metrics

This feature enables the collection and aggregation of metrics data, such as counts or latencies, which can be used for monitoring application performance and health.

const { Metrics, MeasureUnit } = require('@opencensus/core');
const metrics = Metrics.instance;

// Create a measure
const requestCountMeasure = metrics.createMeasureInt64('request_count', MeasureUnit.UNIT, 'Count of requests received');

// Create and register a view to aggregate the data
metrics.createView('request_count_view', requestCountMeasure, 'count', [], 'The count of requests', []);

// Record data
metrics.record([{measure: requestCountMeasure, value: 1}]);

Other packages similar to @opencensus/core

prom-client

The prom-client package is specifically designed for creating metrics in the Prometheus format. It focuses solely on metrics collection and exposition, unlike @opencensus/core, which supports both tracing and metrics. This makes prom-client a good choice if you are specifically looking for Prometheus support, but it lacks the tracing capabilities of @opencensus/core.

README

OpenCensus Core Node.js

OpenCensus for Node.js is an implementation of OpenCensus, a toolkit for collecting application performance and behavior monitoring data. It currently includes 3 apis: stats, tracing and tags.

The library is in alpha stage and the API is subject to change.

Installation

Install the opencensus-core package with NPM:

npm install @opencensus/core

Usage

Get the global Stats manager instance.

To enable metrics, we’ll import a few items from OpenCensus Core package.

const { globalStats, MeasureUnit, AggregationType, TagMap } = require('@opencensus/core');

// The latency in milliseconds
const mLatencyMs = globalStats.createMeasureDouble(
  "repl/latency",
  MeasureUnit.MS,
  "The latency in milliseconds"
);

Create Views and Tags:

We now determine how our metrics will be organized by creating Views. We will also create the variable needed to add extra text meta-data to our metrics – methodTagKey, statusTagKey, and errorTagKey.

const methodTagKey = { name: "method" };
const statusTagKey = { name: "status" };
const errorTagKey = { name: "error" };

// Create & Register the view.
const latencyView = globalStats.createView(
  "demo/latency",
  mLatencyMs,
  AggregationType.DISTRIBUTION,
  [methodTagKey, statusTagKey, errorTagKey],
  "The distribution of the latencies",
  // Bucket Boundaries:
  // [>=0ms, >=25ms, >=50ms, >=75ms, >=100ms, >=200ms, >=400ms, >=600ms, >=800ms, >=1s, >=2s, >=4s, >=6s]
  [0, 25, 50, 75, 100, 200, 400, 600, 800, 1000, 2000, 4000, 6000]
);
globalStats.registerView(latencyView);

Recording Metrics:

Now we will record the desired metrics. To do so, we will use globalStats.record() and pass in measurements.

const [_, startNanoseconds] = process.hrtime();
const tags = new TagMap();
tags.set(methodTagKey, { value: "REPL" });
tags.set(statusTagKey, { value: "OK" });

globalStats.record([{
  measure: mLatencyMs,
  value: sinceInMilliseconds(startNanoseconds)
}], tags);

function sinceInMilliseconds(startNanoseconds) {
  const [_, endNanoseconds] = process.hrtime();
  return (endNanoseconds - startNanoseconds) / 1e6;
}

Measures can be of type Int64 or DOUBLE, created by calling createMeasureInt64 and createMeasureDouble respectively. Its units can be:

MeasureUnit	Usage
UNIT	for general counts
BYTE	bytes
KBYTE	Kbytes
SEC	seconds
MS	millisecond
NS	nanosecond

Views can have agregations of type SUM, LAST_VALUE, COUNT and DISTRIBUTION. To know more about Stats core concepts, please visit: https://opencensus.io/core-concepts/metrics/

See Quickstart/Metrics for a full example of registering and collecting metrics.

Useful links

• For more information on OpenCensus, visit: https://opencensus.io/
• To checkout the OpenCensus for Node.js, visit: https://github.com/census-instrumentation/opencensus-node
• For help or feedback on this project, join us on gitter

LICENSE

Apache License 2.0