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.
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');
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" };
const latencyView = globalStats.createView(
"demo/latency",
mLatencyMs,
AggregationType.DISTRIBUTION,
[methodTagKey, statusTagKey, errorTagKey],
"The distribution of the latencies",
[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
LICENSE
Apache License 2.0
0.0.12 - 2019-05-13
- Add
defaultAttributes
config to Tracer.start(config)
- http-instrumentation: Handle incoming requests with long request url path.
- Add Cumulative (
DoubleCumulative
, LongCumulative
, , DerivedDoubleCumulative
, DerivedLongCumulative
) APIs. - Export
TracerBase
as a separate @opencensus/nodejs-base
package. - Fix(deps): update dependency nyc to v14.
- Fix(deps): update dependency grpc to ~1.20.0
- chore(package): update handlebar to avoid security vulnabirity.
- Move propagation-binaryformat package to dependencies.
- Fix(deps): update dependency @grpc/proto-loader to ^0.5.0
- http-instrumentation: fix propagation errors when using Expect header.
- Consolidate Span and RootSpan to allow Spans to recursively have children.
This release has a breaking change. Please test your code accordingly after upgrading.
- removing Tracer's
startChildSpan(name?: string, kind?: types.SpanKind)
interface
Old code
// Multi argument interface
const span = tracer.startChildSpan('my-span', types.SpanKind.SERVER);
// Or options object interface
const span = tracer.startChildSpan({
name: 'my-span',
kind: types.SpanKind.SERVER
});
New code
// Only options object interface is supported
const span = tracer.startChildSpan({
name: 'my-span',
kind: types.SpanKind.SERVER
});