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reporting framework for reporting data point information to aggregators (like Graphite)","maintainers":[{"name":"ysa23","email":"ysa.angel@gmail.com"}],"readme":"# Metrics\r\nMetrics is a time series reporting framework for aggregators and metrics collectors such as [Graphite](https://graphiteapp.org/).\r\n\r\n[![npm][npm-image]][npm-url]\r\n![Lint and tests](https://github.com/ysa23/metrics-reporter/workflows/Lint%20and%20tests/badge.svg)\r\n![Node.js Publish to NPM](https://github.com/ysa23/metrics-reporter/workflows/Node.js%20Publish%20to%20NPM/badge.svg)\r\n\r\n## Highlights\r\n* Time series reporting\r\n* Plugin based: Support different aggregators with pluggable reporters\r\n* Built in [reporters](#Reporters):\r\n  * [Graphite (statsd)](#Graphite)\r\n  * [DataDog](#DataDog)\r\n  * [Prometheus (experimental)](#prometheus-experimental)\r\n  * [String](#String)\r\n  * [Console](#Console)\r\n  * [InMemory (for testing)](#InMemory)\r\n* Simple, easy to use API\r\n* Focused on performance for high throughput applications and services\r\n\r\n## Table of Contents\r\n* [Getting Started](#getting-started)\r\n    * [Installations](#installation)\r\n    * [Configuration](#configuration)\r\n    * [Reporting metrics](#reporting-metrics)\r\n        * [Execution time](#execution-time)\r\n        * [Value](#value)\r\n        * [Increment](#increment)\r\n        * [Tagging support](#tagging-support)\r\n     * [Reporters](#reporters)\r\n        * [Graphite](#Graphite)\r\n        * [DataDog](#DataDog)\r\n        * [Prometheus (experimental)](#prometheus-experimental)\r\n        * [String](#String)\r\n        * [Console](#Console)\r\n        * [InMemory](#InMemory)\r\n    * [Building new reporters](#building-new-reporters)\r\n* [Development](#development)\r\n    * [How to contribute](#how-to-contribute)\r\n    * [Running tests](#running-tests)\r\n\r\n## Getting started\r\n### Installation\r\n[![npm (scoped)](https://img.shields.io/npm/v/metrics-reporter.svg)](https://www.npmjs.com/package/metrics-reporter)\r\n\r\n### Configuration\r\nImport metrics package:\r\n```js\r\nconst { Metrics } = require('metrics-reporter');\r\n```\r\nInitialize the metrics instance with the required reporters:\r\n```js\r\nconst { StringReporter, ConsoleReporter } = require('metrics-reporter');\r\n\r\nconst stringReporter = new StringReporter({ action: metricString => {\r\n        // Do something\r\n    }});\r\nconst consoleReporter = new ConsoleReporter();\r\n\r\nconst reporters = [stringReporter, consoleReporter];// Array of reporters to trigger when a metrics should be reported\r\nconst errback = (err) => { console.error(err);};    // Optional - A function to be called when an error occurs\r\nconst tags = { tag1: 'value1' };                    // Optional - key-value pairs to be appanded to all the metrics reported\r\n\r\nconst metrics = new Metrics({ \r\n  reporters,\r\n  tags,\r\n  errback \r\n});\r\n```\r\n\r\n### Reporting Metrics\r\nUse the `space` method on the `Metrics` instance to report custom metrics. `space` creates a new key to report:\r\n```js\r\nconst metric = metrics.space('http');\r\n```\r\nSpaces can be nested:\r\n```js\r\nconst metric = metrics.space('http').space('requests'); // http.requests\r\n```\r\n\r\n#### Execution time\r\nUse the `meter` method on a `Space` to report execution time of a function:\r\n```javascript\r\n// Callback function\r\nconst wrapper = metrics.space('users.get').meter(function(userIds, callback) {\r\n\t// read users from database\r\n\tcallback(...);\r\n});\r\n\r\nwrapper([1, 2, 3], (err, result) => { console.log(result); });\r\n```\r\nThe `meter` method can receive:\r\n* A function with a callback (as the last parameter)\r\n* Promise\r\n* Async function\r\n\r\n`meter` returns a **wrapper** around the object that was sent.\r\nIn order to start measuring **invoke** it according to its type. For example:\r\n```javascript\r\n// Sync invocation\r\nconst wrapperSync = metrics.space('add').meter((a, b) => a + b);\r\nconst result = wrapperSync(1, 2);\r\n\r\n// Promise invocation\r\nconst wrapperPromise = metrics.space('timeout').meter(new Promise(function(resolve) {\r\n  setTimeout(() => console.log('hello'), 10000);\r\n}));\r\nawait wrapperPromise();\r\n```\r\n\r\nThe meter function will run your code, while measuring the time it took to execute, and report it to the configured reporters.\r\n\r\nNote:\r\n* In a callback: Metrics are reported only **after** the callback is called\r\n* In a promise and async function: Metrics are reported once the promise fulfills (either success or failure)\r\n\r\nIf an async function is measured, you can await on it and get its returned value:\r\n```js\r\nconst result = await metrics.space('users.get').meter(async () => {\r\n    // Some async code here\r\n})();\r\n```\r\n**Please note the invocation on the return value.**\r\n\r\n#### Value\r\nUse the `Metrics` instance to report a value:\r\n```js\r\nmetrics.space('api.response.size').value(512);\r\n```\r\n\r\n#### Increment\r\nUse the `Metrics` instance to increment a key:\r\n```js\r\nmetrics.space('api.requests').increment();\r\n```\r\n\r\n#### Tagging support\r\nTags are specified per space, as an object:\r\n```js\r\nmetrics.space('http.requests', { path: 'users_get' }).increment();\r\n```\r\nWhen nesting spaces, the tags are aggregated:\r\n```js\r\nmetrics\r\n    .space('http', { verb: 'GET' })\r\n    .space('requests', { path: 'users' })\r\n    .increment(); \r\n    // will increment 'http.requests' with 'verb:GET,path:users' tags\r\n```\r\nUse `tags` function to create a space with the same key and additional tags:\r\n```js\r\nmetrics\r\n    .space('http', { verb: 'GET' })\r\n    .tags({ path: 'users' })\r\n    .increment(); \r\n    // will increment 'http' with 'verb:GET,path:users' tags\r\n```\r\n\r\n##### Note\r\nWhen the same tag is specified when creating nested spaces, the last value will be reported\r\n\r\n#### Error handling\r\nMetrics support error handling. When creating a Metric object you can send an error callback:\r\n```js\r\nconst metrics = new Metrics({ \r\n  reporters: [new ConsoleReporter()],\r\n  errback: e => {\r\n    // e is a javascript Error object. You can log it on any standard logging framework:\r\n    logger.error(e);\r\n  }\r\n});\r\n```\r\nThe error callback receives a single parameter - an Error instance. The callback will be triggered when any error occurs during the metrics reporting.\r\n\r\n**Please note:** Some reporters require their own error handler. Make sure to initialize `errback` with them as well.  \r\n\r\n### Reporters\r\nMetrics comes with several built-in reporters\r\n#### Graphite\r\nReports metrics to a graphite server (via statsd):\r\n```js\r\nconst { Metrics, GraphiteReporter } = require('metrics-reporter');\r\n\r\nconst graphiteHost = '1.1.1.1';         // Graphite server IP address\r\nconst graphitePort = 8125;              // Optional - port number. Defaults to 8125\r\nconst spacePrefix = 'My.Project';       // Optional - prefix to all metrics spaces\r\nconst batch = true;                     // Optional - Default `true` - Indicates that metrics will be sent in batches\r\nconst maxBufferSize = 500;              // Optional - Default `1000` - Size of the buffer for sending batched messages. When buffer is filled it is flushed immediately\r\nconst flushInterval = 1000;             // Optional - Default `1000` (1s) - Time in milliseconds. Indicates how often the buffer is flushed in case batch = true\r\nconst errback = (err) => {              // Optional - function to be triggered when an error occurs \r\n    console.error(err) \r\n};\r\n\r\nconst graphiteReporter = new GraphiteReporter({\r\n  host: graphiteHost,\r\n  port: graphitePort,\r\n  prefix: spacePrefix,\r\n  batch,\r\n  maxBufferSize,\r\n  flushInterval,\r\n  errback,\r\n});\r\n\r\nconst metrics = new Metrics({ reporters: [graphiteReporter] });\r\n\r\ngraphiteReporter.close(); // close should be called when the application terminates\r\n```\r\n\r\n#### DataDog\r\nReports metrics to a [DataDog](https://www.datadoghq.com/) (via [DogStatsD](https://docs.datadoghq.com/developers/dogstatsd/?tab=hostagent)):\r\n```js\r\nconst { Metrics, DataDogReporter } = require('metrics-reporter');\r\n\r\nconst agentHost = '1.1.1.1';            // DataDog agent IP address\r\nconst port = 8125;                      // Optional - Default `8125` - port number. Defaults to 8125\r\nconst spacePrefix = 'My.Project';       // Optional - prefix to all metrics spaces\r\nconst batch = true;                     // Optional - Default `true` - Indicates that metrics will be sent in batches\r\nconst maxBufferSize = 500;              // Optional - Default `1000` - Size of the buffer for sending batched messages. When buffer is filled it is flushed immediately\r\nconst flushInterval = 1000;             // Optional - Default `1000` (1s) - Time in milliseconds. Indicates how often the buffer is flushed in case batch = true\r\nconst errback = (err) => {              // Optional - function to be triggered when an error occurs \r\n  console.error(err)\r\n};\r\n\r\nconst datadogReporter = new DataDogReporter({\r\n  host: agentHost,\r\n  port,\r\n  prefix: spacePrefix,\r\n  batch,\r\n  maxBufferSize,\r\n  flushInterval,\r\n  errback,\r\n});\r\n\r\nconst metrics = new Metrics({ reporters: [datadogReporter] });\r\n\r\ndatadogReporter.close(); // close should be called when the application terminates\r\n```\r\nNote that you'll need a running [DataDog agent](https://docs.datadoghq.com/agent/). In the `/docker` folder there's a simple docker compose for datadog to get you started\r\n\r\n#### Console\r\nConsole reporter comes in handy when you need to debug metrics calls:\r\n```js\r\nconst { Metrics, ConsoleReporter } = require('metrics-reporter');\r\n\r\nconst consoleReporter = new ConsoleReporter();\r\n\t\r\nconst metrics = new Metrics({ reporters: [consoleReporter] });\r\n```\r\nWhen a metrics will be reported, a message will appear in the terminal, that includes the key and the value reported.\r\n\r\n#### String\r\n```js\r\nconst { Metrics, StringReporter } = require('metrics-reporter');\r\nconst fs = require('fs');\r\n\r\nconst stringReporter = new StringReporter({\r\n    action: metricString => {\r\n        fs.appendFile('metrics.log', metricsString);\r\n    },\r\n});\r\n\t\r\nconst metrics = new Metrics({ reporters: [stringReporter] });\r\n```\r\nHere, `StringReporter` is used to build a log file from the metrics reports.\r\n\r\n#### InMemory\r\nInMemoryReporter can be used for testing purposed, in order to make sure your code reports metrics as expected.\r\n```js\r\nconst { Metrics, InMemoryReporter } = require('metrics-reporter');\r\n\r\nconst metricsStorage = [];\r\n\r\nconst memoryReporter = new InMemoryReporter({ buffer: metricsStorage });\r\n\r\nconst metrics = new Metrics({ reporters: [memoryReporter], errback: error => { /* Do something on error */ } });\r\n```\r\nWhen a metric is reported, an object with `key`, `value` and `tags` properties is pushed to the array.<br/>\r\nThen, the array can be used in order to validate the report.\r\n\r\n#### Prometheus (experimental)\r\nPrometheusReporter is an experimental reporter that generates metrics in the [Prometheus text exposition format](https://prometheus.io/docs/instrumenting/exposition_formats/) without any external dependencies:\r\n```js\r\nconst { Metrics, PrometheusReporter } = require('metrics-reporter');\r\nconst express = require('express');\r\n\r\nconst prefix = 'myapp_';                // Optional - prefix for all metric names\r\nconst softLimit = 5000;                 // Optional - Default `5000` - Reset metrics after scrape when exceeded\r\nconst hardLimit = 10000;                // Optional - Default `10000` - Force reset to prevent OOM\r\nconst warnAt = 4000;                    // Optional - Default `4000` - Log warning when approaching soft limit\r\nconst buckets = [10, 50, 100, 250];     // Optional - Custom histogram buckets (ms)\r\nconst logCallback = (logEvent) => {     // Optional - function to handle log events\r\n  console.log(`[${logEvent.level.toUpperCase()}] ${logEvent.message}`, logEvent.params);\r\n};\r\n\r\nconst prometheusReporter = new PrometheusReporter({\r\n  prefix,\r\n  softLimit,\r\n  hardLimit,\r\n  warnAt,\r\n  buckets,\r\n  logCallback,\r\n});\r\n\r\nconst metrics = new Metrics({ reporters: [prometheusReporter] });\r\n\r\n// Expose metrics endpoint for Prometheus to scrape\r\nconst app = express();\r\napp.get('/metrics', (req, res) => {\r\n  res\r\n    .type('text/plain')\r\n    .send(prometheusReporter.getMetrics());\r\n});\r\n\r\napp.listen(3000);\r\n```\r\n\r\n##### Design Principles\r\nThe PrometheusReporter implements a **double-threshold strategy** to prevent memory issues common with high-cardinality metrics:\r\n\r\n1. **Soft Limit** (default 5000): When the number of unique metrics exceeds this limit, they are reset **after** the next scrape, ensuring Prometheus receives the data before clearing.\r\n\r\n2. **Hard Limit** (default 10000): An emergency threshold that immediately resets all metrics to prevent out-of-memory errors, even if Prometheus hasn't scraped yet.\r\n\r\n3. **Warning Threshold** (default 4000): Logs a warning when approaching the soft limit, helping identify cardinality issues before they become critical.\r\n\r\nThis approach provides **memory safety** while maintaining **data integrity**, unlike traditional Prometheus clients that can suffer from unbounded memory growth.\r\n\r\n##### Metric Type Mapping\r\n- `increment()` → Counter (with `_total` suffix)\r\n- `value()` → Gauge\r\n- `report()` → Histogram (with buckets, sum, and count)\r\n\r\n##### Configuration Recommendations\r\nConfiguration should be according to your use-case, use these as guidelines to an initial configuration and tweak as needed:\r\n- **Low traffic**: Use defaults (soft: 5000, hard: 10000)\r\n- **High traffic**: Increase limits (soft: 20000, hard: 50000)\r\n- **Microservices**: Lower limits (soft: 1000, hard: 2000)\r\n- **Development**: Very low limits for testing (soft: 100, hard: 200)\r\n\r\n##### Log Events\r\nThe PrometheusReporter provides structured logging through an optional `logCallback` function. This allows you to handle log events programmatically instead of relying on console output.\r\n\r\n```js\r\nconst prometheusReporter = new PrometheusReporter({\r\n  logCallback: (logEvent) => {\r\n    // Handle log events with your preferred logging library\r\n    logger.log(logEvent.level, logEvent.message, {\r\n      code: logEvent.code,\r\n      params: logEvent.params,\r\n      reporter: logEvent.reporter,\r\n      timestamp: logEvent.timestamp\r\n    });\r\n  }\r\n});\r\n```\r\n\r\n**Log Event Structure:**\r\n- `level`: 'error' | 'warn' | 'info' | 'debug'\r\n- `code`: Event code for programmatic handling\r\n- `message`: Human-readable message\r\n- `params`: Additional parameters relevant to the event\r\n- `timestamp`: Unix timestamp in milliseconds\r\n- `reporter`: Always 'PrometheusReporter'\r\n\r\n**Event Codes:**\r\n- `APPROACHING_SOFT_LIMIT`: Warning when approaching the soft limit threshold\r\n- `SOFT_LIMIT_EXCEEDED`: Info when soft limit exceeded during getMetrics()\r\n- `HARD_LIMIT_REACHED`: Error when hard limit forces immediate reset\r\n\r\nWe recommend monitoring these events, as threshold violations can cause metric data loss.\r\n\r\n### Building new reporters\r\nMetrics support creating new reports according to an application needs.\r\n\r\nA reporter must contain three methods:\r\n* `report` - for reporting time\r\n* `value` - for reporting a single value (size of response for example)\r\n* `increment` - for an incremented value over time (number of requests for example\r\n\r\nThe methods get the following parameters:\r\n * `key` (mandatory) - the metric to report\r\n * `value` (mandatory) - the value to report (ms, count or increment for example)\r\n * `tags` (optional) - an object that contains the tags to report on the metric as properties\r\n\r\nFor example, lets see how to implement a reporter for redis:\r\n```js\r\nconst client = require('redis').createClient();\r\n\r\nfunction RedisReporter({\r\n    channel, \r\n    errback\r\n}) {\r\n  function report(key, val, tags) { \r\n    client.publish(channel, JSON.stringify({ key, value: val, tags  }));\r\n  }\r\n\r\n  function value(key, val, tags) {\r\n    client.set(key, val, (err) => {\r\n        if (!err || !errback) {\r\n            return;\r\n        }\r\n        \r\n        errback(err);\r\n    });\r\n  }\r\n \r\n  function increment(key, value, tags) {\r\n    const multi = client.multi();\r\n    for(let i = 0; i < value; i++) {\r\n        multi.incr(key);\r\n    }   \r\n        \r\n    multi.exec((err) => {\r\n      if (!err || !errback) {\r\n        return;\r\n      }\r\n\r\n      errback(err);\r\n    });\r\n  }\r\n  \r\n  return {\r\n    report,\r\n    value,\r\n    increment,\r\n  }\r\n};\r\n\r\nmodule.exports = {\r\n  RedisReporter,\r\n};\r\n```\r\nThe new reporter will publish a message to a specified channel in redis when a metric is reported.\r\n\r\n## Development\r\n\r\n### How to contribute\r\nWe encourage contribution via pull requests on any feature you see fit.\r\n\r\nWhen submitting a pull request make sure to do the following:\r\n* Run all unit and integration tests to ensure no existing functionality has been affected\r\n* Write unit or integration tests to test your changes. All features and fixed bugs must have tests to verify they work\r\n\r\nRead [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more details about creating pull requests\r\n\r\n### Running tests\r\nTo run tests, in command line run `npm test`\r\n\r\n[npm-image]: https://img.shields.io/npm/v/metrics-reporter.svg?style=rounded-square\r\n[npm-url]: https://npmjs.org/package/metrics-reporter\r\n","readmeFilename":"README.md"}