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# OpenCensus Core Node.js
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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:
```bash
npm install @opencensus/core
```
## Usage
#### Get the global Stats manager instance.
To enable metrics, we’ll import a few items from OpenCensus Core package.
```javascript
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```.
```javascript
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.
```javascript
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/](https://opencensus.io/core-concepts/metrics/)
See [Quickstart/Metrics](https://opencensus.io/quickstart/nodejs/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](https://gitter.im/census-instrumentation/Lobby)
[gitter-image]: https://badges.gitter.im/census-instrumentation/lobby.svg
[gitter-url]: https://gitter.im/census-instrumentation/lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
[npm-url]: https://www.npmjs.com/package/@opencensus/core
[npm-img]: https://badge.fury.io/js/%40opencensus%2Fcore.svg
[node-img]: https://img.shields.io/node/v/@opencensus/core.svg
[license-image]: https://img.shields.io/badge/license-Apache_2.0-green.svg?style=flat
[dependencies-status]: https://david-dm.org/census-instrumentation/opencensus-node/status.svg?path=packages/opencensus-core
[devdependencies-status]:
https://david-dm.org/census-instrumentation/opencensus-node/dev-status.svg?path=packages/opencensus-core
## LICENSE
Apache License 2.0
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