# Performance measurement APIs > Stability: 2 - Stable This module provides an implementation of a subset of the W3C [Web Performance APIs][] as well as additional APIs for Node.js-specific performance measurements. Node.js supports the following [Web Performance APIs][]: * [High Resolution Time][] * [Performance Timeline][] * [User Timing][] * [Resource Timing][] ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((items) => { console.log(items.getEntries()[0].duration); performance.clearMarks(); }); obs.observe({ type: 'measure' }); performance.measure('Start to Now'); performance.mark('A'); doSomeLongRunningProcess(() => { performance.measure('A to Now', 'A'); performance.mark('B'); performance.measure('A to B', 'A', 'B'); }); ``` ```cjs const { PerformanceObserver, performance } = require('node:perf_hooks'); const obs = new PerformanceObserver((items) => { console.log(items.getEntries()[0].duration); }); obs.observe({ type: 'measure' }); performance.measure('Start to Now'); performance.mark('A'); (async function doSomeLongRunningProcess() { await new Promise((r) => setTimeout(r, 5000)); performance.measure('A to Now', 'A'); performance.mark('B'); performance.measure('A to B', 'A', 'B'); })(); ``` ## `perf_hooks.performance` An object that can be used to collect performance metrics from the current Node.js instance. It is similar to [`window.performance`][] in browsers. ### `performance.clearMarks([name])` * `name` {string} If `name` is not provided, removes all `PerformanceMark` objects from the Performance Timeline. If `name` is provided, removes only the named mark. ### `performance.clearMeasures([name])` * `name` {string} If `name` is not provided, removes all `PerformanceMeasure` objects from the Performance Timeline. If `name` is provided, removes only the named measure. ### `performance.clearResourceTimings([name])` * `name` {string} If `name` is not provided, removes all `PerformanceResourceTiming` objects from the Resource Timeline. If `name` is provided, removes only the named resource. ### `performance.eventLoopUtilization([utilization1[, utilization2]])` * `utilization1` {Object} The result of a previous call to `eventLoopUtilization()`. * `utilization2` {Object} The result of a previous call to `eventLoopUtilization()` prior to `utilization1`. * Returns: {Object} * `idle` {number} * `active` {number} * `utilization` {number} This is an alias of [`perf_hooks.eventLoopUtilization()`][]. _This property is an extension by Node.js. It is not available in Web browsers._ ### `performance.getEntries()` * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime`. If you are only interested in performance entries of certain types or that have certain names, see `performance.getEntriesByType()` and `performance.getEntriesByName()`. ### `performance.getEntriesByName(name[, type])` * `name` {string} * `type` {string} * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime` whose `performanceEntry.name` is equal to `name`, and optionally, whose `performanceEntry.entryType` is equal to `type`. ### `performance.getEntriesByType(type)` * `type` {string} * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime` whose `performanceEntry.entryType` is equal to `type`. ### `performance.mark(name[, options])` * `name` {string} * `options` {Object} * `detail` {any} Additional optional detail to include with the mark. * `startTime` {number} An optional timestamp to be used as the mark time. **Default**: `performance.now()`. Creates a new `PerformanceMark` entry in the Performance Timeline. A `PerformanceMark` is a subclass of `PerformanceEntry` whose `performanceEntry.entryType` is always `'mark'`, and whose `performanceEntry.duration` is always `0`. Performance marks are used to mark specific significant moments in the Performance Timeline. The created `PerformanceMark` entry is put in the global Performance Timeline and can be queried with `performance.getEntries`, `performance.getEntriesByName`, and `performance.getEntriesByType`. When the observation is performed, the entries should be cleared from the global Performance Timeline manually with `performance.clearMarks`. ### `performance.markResourceTiming(timingInfo, requestedUrl, initiatorType, global, cacheMode, bodyInfo, responseStatus[, deliveryType])` * `timingInfo` {Object} [Fetch Timing Info][] * `requestedUrl` {string} The resource url * `initiatorType` {string} The initiator name, e.g: 'fetch' * `global` {Object} * `cacheMode` {string} The cache mode must be an empty string ('') or 'local' * `bodyInfo` {Object} [Fetch Response Body Info][] * `responseStatus` {number} The response's status code * `deliveryType` {string} The delivery type. **Default:** `''`. _This property is an extension by Node.js. It is not available in Web browsers._ Creates a new `PerformanceResourceTiming` entry in the Resource Timeline. A `PerformanceResourceTiming` is a subclass of `PerformanceEntry` whose `performanceEntry.entryType` is always `'resource'`. Performance resources are used to mark moments in the Resource Timeline. The created `PerformanceMark` entry is put in the global Resource Timeline and can be queried with `performance.getEntries`, `performance.getEntriesByName`, and `performance.getEntriesByType`. When the observation is performed, the entries should be cleared from the global Performance Timeline manually with `performance.clearResourceTimings`. ### `performance.measure(name[, startMarkOrOptions[, endMark]])` * `name` {string} * `startMarkOrOptions` {string|Object} Optional. * `detail` {any} Additional optional detail to include with the measure. * `duration` {number} Duration between start and end times. * `end` {number|string} Timestamp to be used as the end time, or a string identifying a previously recorded mark. * `start` {number|string} Timestamp to be used as the start time, or a string identifying a previously recorded mark. * `endMark` {string} Optional. Must be omitted if `startMarkOrOptions` is an {Object}. Creates a new `PerformanceMeasure` entry in the Performance Timeline. A `PerformanceMeasure` is a subclass of `PerformanceEntry` whose `performanceEntry.entryType` is always `'measure'`, and whose `performanceEntry.duration` measures the number of milliseconds elapsed since `startMark` and `endMark`. The `startMark` argument may identify any _existing_ `PerformanceMark` in the Performance Timeline, or _may_ identify any of the timestamp properties provided by the `PerformanceNodeTiming` class. If the named `startMark` does not exist, an error is thrown. The optional `endMark` argument must identify any _existing_ `PerformanceMark` in the Performance Timeline or any of the timestamp properties provided by the `PerformanceNodeTiming` class. `endMark` will be `performance.now()` if no parameter is passed, otherwise if the named `endMark` does not exist, an error will be thrown. The created `PerformanceMeasure` entry is put in the global Performance Timeline and can be queried with `performance.getEntries`, `performance.getEntriesByName`, and `performance.getEntriesByType`. When the observation is performed, the entries should be cleared from the global Performance Timeline manually with `performance.clearMeasures`. ### `performance.nodeTiming` * Type: {PerformanceNodeTiming} _This property is an extension by Node.js. It is not available in Web browsers._ An instance of the `PerformanceNodeTiming` class that provides performance metrics for specific Node.js operational milestones. ### `performance.now()` * Returns: {number} Returns the current high resolution millisecond timestamp, where 0 represents the start of the current `node` process. ### `performance.setResourceTimingBufferSize(maxSize)` Sets the global performance resource timing buffer size to the specified number of "resource" type performance entry objects. By default the max buffer size is set to 250. ### `performance.timeOrigin` * Type: {number} The [`timeOrigin`][] specifies the high resolution millisecond timestamp at which the current `node` process began, measured in Unix time. ### `performance.timerify(fn[, options])` * `fn` {Function} * `options` {Object} * `histogram` {RecordableHistogram} A histogram object created using `perf_hooks.createHistogram()` that will record runtime durations in nanoseconds. This is an alias of [`perf_hooks.timerify()`][]. _This property is an extension by Node.js. It is not available in Web browsers._ ### `performance.toJSON()` An object which is JSON representation of the `performance` object. It is similar to [`window.performance.toJSON`][] in browsers. #### Event: `'resourcetimingbufferfull'` The `'resourcetimingbufferfull'` event is fired when the global performance resource timing buffer is full. Adjust resource timing buffer size with `performance.setResourceTimingBufferSize()` or clear the buffer with `performance.clearResourceTimings()` in the event listener to allow more entries to be added to the performance timeline buffer. ## Class: `PerformanceEntry` The constructor of this class is not exposed to users directly. ### `performanceEntry.duration` * Type: {number} The total number of milliseconds elapsed for this entry. This value will not be meaningful for all Performance Entry types. ### `performanceEntry.entryType` * Type: {string} The type of the performance entry. It may be one of: * `'dns'` (Node.js only) * `'function'` (Node.js only) * `'gc'` (Node.js only) * `'http2'` (Node.js only) * `'http'` (Node.js only) * `'mark'` (available on the Web) * `'measure'` (available on the Web) * `'net'` (Node.js only) * `'node'` (Node.js only) * `'resource'` (available on the Web) ### `performanceEntry.name` * Type: {string} The name of the performance entry. ### `performanceEntry.startTime` * Type: {number} The high resolution millisecond timestamp marking the starting time of the Performance Entry. ## Class: `PerformanceMark` * Extends: {PerformanceEntry} Exposes marks created via the `Performance.mark()` method. ### `performanceMark.detail` * Type: {any} Additional detail specified when creating with `Performance.mark()` method. ## Class: `PerformanceMeasure` * Extends: {PerformanceEntry} Exposes measures created via the `Performance.measure()` method. The constructor of this class is not exposed to users directly. ### `performanceMeasure.detail` * Type: {any} Additional detail specified when creating with `Performance.measure()` method. ## Class: `PerformanceNodeEntry` * Extends: {PerformanceEntry} _This class is an extension by Node.js. It is not available in Web browsers._ Provides detailed Node.js timing data. The constructor of this class is not exposed to users directly. ### `performanceNodeEntry.detail` * Type: {any} Additional detail specific to the `entryType`. ### `performanceNodeEntry.flags` > Stability: 0 - Deprecated: Use `performanceNodeEntry.detail` instead. * Type: {number} When `performanceEntry.entryType` is equal to `'gc'`, the `performance.flags` property contains additional information about garbage collection operation. The value may be one of: * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_NO` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_CONSTRUCT_RETAINED` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_FORCED` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_SYNCHRONOUS_PHANTOM_PROCESSING` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_ALL_AVAILABLE_GARBAGE` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_ALL_EXTERNAL_MEMORY` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_SCHEDULE_IDLE` ### `performanceNodeEntry.kind` > Stability: 0 - Deprecated: Use `performanceNodeEntry.detail` instead. * Type: {number} When `performanceEntry.entryType` is equal to `'gc'`, the `performance.kind` property identifies the type of garbage collection operation that occurred. The value may be one of: * `perf_hooks.constants.NODE_PERFORMANCE_GC_MAJOR` * `perf_hooks.constants.NODE_PERFORMANCE_GC_MINOR` * `perf_hooks.constants.NODE_PERFORMANCE_GC_MINOR_MARK_SWEEP` * `perf_hooks.constants.NODE_PERFORMANCE_GC_INCREMENTAL` * `perf_hooks.constants.NODE_PERFORMANCE_GC_WEAKCB` ### Garbage Collection ('gc') Details When `performanceEntry.type` is equal to `'gc'`, the `performanceNodeEntry.detail` property will be an {Object} with two properties: * `kind` {number} One of: * `perf_hooks.constants.NODE_PERFORMANCE_GC_MAJOR` * `perf_hooks.constants.NODE_PERFORMANCE_GC_MINOR` * `perf_hooks.constants.NODE_PERFORMANCE_GC_MINOR_MARK_SWEEP` * `perf_hooks.constants.NODE_PERFORMANCE_GC_INCREMENTAL` * `perf_hooks.constants.NODE_PERFORMANCE_GC_WEAKCB` * `flags` {number} One of: * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_NO` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_CONSTRUCT_RETAINED` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_FORCED` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_SYNCHRONOUS_PHANTOM_PROCESSING` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_ALL_AVAILABLE_GARBAGE` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_ALL_EXTERNAL_MEMORY` * `perf_hooks.constants.NODE_PERFORMANCE_GC_FLAGS_SCHEDULE_IDLE` ### HTTP ('http') Details When `performanceEntry.type` is equal to `'http'`, the `performanceNodeEntry.detail` property will be an {Object} containing additional information. If `performanceEntry.name` is equal to `HttpClient`, the `detail` will contain the following properties: `req`, `res`. And the `req` property will be an {Object} containing `method`, `url`, `headers`, the `res` property will be an {Object} containing `statusCode`, `statusMessage`, `headers`. If `performanceEntry.name` is equal to `HttpRequest`, the `detail` will contain the following properties: `req`, `res`. And the `req` property will be an {Object} containing `method`, `url`, `headers`, the `res` property will be an {Object} containing `statusCode`, `statusMessage`, `headers`. This could add additional memory overhead and should only be used for diagnostic purposes, not left turned on in production by default. ### HTTP/2 ('http2') Details When `performanceEntry.type` is equal to `'http2'`, the `performanceNodeEntry.detail` property will be an {Object} containing additional performance information. If `performanceEntry.name` is equal to `Http2Stream`, the `detail` will contain the following properties: * `bytesRead` {number} The number of `DATA` frame bytes received for this `Http2Stream`. * `bytesWritten` {number} The number of `DATA` frame bytes sent for this `Http2Stream`. * `id` {number} The identifier of the associated `Http2Stream` * `timeToFirstByte` {number} The number of milliseconds elapsed between the `PerformanceEntry` `startTime` and the reception of the first `DATA` frame. * `timeToFirstByteSent` {number} The number of milliseconds elapsed between the `PerformanceEntry` `startTime` and sending of the first `DATA` frame. * `timeToFirstHeader` {number} The number of milliseconds elapsed between the `PerformanceEntry` `startTime` and the reception of the first header. If `performanceEntry.name` is equal to `Http2Session`, the `detail` will contain the following properties: * `bytesRead` {number} The number of bytes received for this `Http2Session`. * `bytesWritten` {number} The number of bytes sent for this `Http2Session`. * `framesReceived` {number} The number of HTTP/2 frames received by the `Http2Session`. * `framesSent` {number} The number of HTTP/2 frames sent by the `Http2Session`. * `maxConcurrentStreams` {number} The maximum number of streams concurrently open during the lifetime of the `Http2Session`. * `pingRTT` {number} The number of milliseconds elapsed since the transmission of a `PING` frame and the reception of its acknowledgment. Only present if a `PING` frame has been sent on the `Http2Session`. * `streamAverageDuration` {number} The average duration (in milliseconds) for all `Http2Stream` instances. * `streamCount` {number} The number of `Http2Stream` instances processed by the `Http2Session`. * `type` {string} Either `'server'` or `'client'` to identify the type of `Http2Session`. ### Timerify ('function') Details When `performanceEntry.type` is equal to `'function'`, the `performanceNodeEntry.detail` property will be an {Array} listing the input arguments to the timed function. ### Net ('net') Details When `performanceEntry.type` is equal to `'net'`, the `performanceNodeEntry.detail` property will be an {Object} containing additional information. If `performanceEntry.name` is equal to `connect`, the `detail` will contain the following properties: `host`, `port`. ### DNS ('dns') Details When `performanceEntry.type` is equal to `'dns'`, the `performanceNodeEntry.detail` property will be an {Object} containing additional information. If `performanceEntry.name` is equal to `lookup`, the `detail` will contain the following properties: `hostname`, `family`, `hints`, `verbatim`, `addresses`. If `performanceEntry.name` is equal to `lookupService`, the `detail` will contain the following properties: `host`, `port`, `hostname`, `service`. If `performanceEntry.name` is equal to `queryxxx` or `getHostByAddr`, the `detail` will contain the following properties: `host`, `ttl`, `result`. The value of `result` is same as the result of `queryxxx` or `getHostByAddr`. ## Class: `PerformanceNodeTiming` * Extends: {PerformanceEntry} _This property is an extension by Node.js. It is not available in Web browsers._ Provides timing details for Node.js itself. The constructor of this class is not exposed to users. ### `performanceNodeTiming.bootstrapComplete` * Type: {number} The high resolution millisecond timestamp at which the Node.js process completed bootstrapping. If bootstrapping has not yet finished, the property has the value of -1. ### `performanceNodeTiming.environment` * Type: {number} The high resolution millisecond timestamp at which the Node.js environment was initialized. ### `performanceNodeTiming.idleTime` * Type: {number} The high resolution millisecond timestamp of the amount of time the event loop has been idle within the event loop's event provider (e.g. `epoll_wait`). This does not take CPU usage into consideration. If the event loop has not yet started (e.g., in the first tick of the main script), the property has the value of 0. ### `performanceNodeTiming.loopExit` * Type: {number} The high resolution millisecond timestamp at which the Node.js event loop exited. If the event loop has not yet exited, the property has the value of -1. It can only have a value of not -1 in a handler of the [`'exit'`][] event. ### `performanceNodeTiming.loopStart` * Type: {number} The high resolution millisecond timestamp at which the Node.js event loop started. If the event loop has not yet started (e.g., in the first tick of the main script), the property has the value of -1. ### `performanceNodeTiming.nodeStart` * Type: {number} The high resolution millisecond timestamp at which the Node.js process was initialized. ### `performanceNodeTiming.uvMetricsInfo` * Returns: {Object} * `loopCount` {number} Number of event loop iterations. * `events` {number} Number of events that have been processed by the event handler. * `eventsWaiting` {number} Number of events that were waiting to be processed when the event provider was called. This is a wrapper to the `uv_metrics_info` function. It returns the current set of event loop metrics. It is recommended to use this property inside a function whose execution was scheduled using `setImmediate` to avoid collecting metrics before finishing all operations scheduled during the current loop iteration. ```cjs const { performance } = require('node:perf_hooks'); setImmediate(() => { console.log(performance.nodeTiming.uvMetricsInfo); }); ``` ```mjs import { performance } from 'node:perf_hooks'; setImmediate(() => { console.log(performance.nodeTiming.uvMetricsInfo); }); ``` ### `performanceNodeTiming.v8Start` * Type: {number} The high resolution millisecond timestamp at which the V8 platform was initialized. ## Class: `PerformanceResourceTiming` * Extends: {PerformanceEntry} Provides detailed network timing data regarding the loading of an application's resources. The constructor of this class is not exposed to users directly. ### `performanceResourceTiming.workerStart` * Type: {number} The high resolution millisecond timestamp at immediately before dispatching the `fetch` request. If the resource is not intercepted by a worker the property will always return 0. ### `performanceResourceTiming.redirectStart` * Type: {number} The high resolution millisecond timestamp that represents the start time of the fetch which initiates the redirect. ### `performanceResourceTiming.redirectEnd` * Type: {number} The high resolution millisecond timestamp that will be created immediately after receiving the last byte of the response of the last redirect. ### `performanceResourceTiming.fetchStart` * Type: {number} The high resolution millisecond timestamp immediately before the Node.js starts to fetch the resource. ### `performanceResourceTiming.domainLookupStart` * Type: {number} The high resolution millisecond timestamp immediately before the Node.js starts the domain name lookup for the resource. ### `performanceResourceTiming.domainLookupEnd` * Type: {number} The high resolution millisecond timestamp representing the time immediately after the Node.js finished the domain name lookup for the resource. ### `performanceResourceTiming.connectStart` * Type: {number} The high resolution millisecond timestamp representing the time immediately before Node.js starts to establish the connection to the server to retrieve the resource. ### `performanceResourceTiming.connectEnd` * Type: {number} The high resolution millisecond timestamp representing the time immediately after Node.js finishes establishing the connection to the server to retrieve the resource. ### `performanceResourceTiming.secureConnectionStart` * Type: {number} The high resolution millisecond timestamp representing the time immediately before Node.js starts the handshake process to secure the current connection. ### `performanceResourceTiming.requestStart` * Type: {number} The high resolution millisecond timestamp representing the time immediately before Node.js receives the first byte of the response from the server. ### `performanceResourceTiming.responseEnd` * Type: {number} The high resolution millisecond timestamp representing the time immediately after Node.js receives the last byte of the resource or immediately before the transport connection is closed, whichever comes first. ### `performanceResourceTiming.transferSize` * Type: {number} A number representing the size (in octets) of the fetched resource. The size includes the response header fields plus the response payload body. ### `performanceResourceTiming.encodedBodySize` * Type: {number} A number representing the size (in octets) received from the fetch (HTTP or cache), of the payload body, before removing any applied content-codings. ### `performanceResourceTiming.decodedBodySize` * Type: {number} A number representing the size (in octets) received from the fetch (HTTP or cache), of the message body, after removing any applied content-codings. ### `performanceResourceTiming.toJSON()` Returns a `object` that is the JSON representation of the `PerformanceResourceTiming` object ## Class: `PerformanceObserver` ### `PerformanceObserver.supportedEntryTypes` * Type: {string\[]} Get supported types. ### `new PerformanceObserver(callback)` * `callback` {Function} * `list` {PerformanceObserverEntryList} * `observer` {PerformanceObserver} `PerformanceObserver` objects provide notifications when new `PerformanceEntry` instances have been added to the Performance Timeline. ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((list, observer) => { console.log(list.getEntries()); performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['mark'], buffered: true }); performance.mark('test'); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const obs = new PerformanceObserver((list, observer) => { console.log(list.getEntries()); performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['mark'], buffered: true }); performance.mark('test'); ``` Because `PerformanceObserver` instances introduce their own additional performance overhead, instances should not be left subscribed to notifications indefinitely. Users should disconnect observers as soon as they are no longer needed. The `callback` is invoked when a `PerformanceObserver` is notified about new `PerformanceEntry` instances. The callback receives a `PerformanceObserverEntryList` instance and a reference to the `PerformanceObserver`. ### `performanceObserver.disconnect()` Disconnects the `PerformanceObserver` instance from all notifications. ### `performanceObserver.observe(options)` * `options` {Object} * `type` {string} A single {PerformanceEntry} type. Must not be given if `entryTypes` is already specified. * `entryTypes` {string\[]} An array of strings identifying the types of {PerformanceEntry} instances the observer is interested in. If not provided an error will be thrown. * `buffered` {boolean} If true, the observer callback is called with a list global `PerformanceEntry` buffered entries. If false, only `PerformanceEntry`s created after the time point are sent to the observer callback. **Default:** `false`. Subscribes the {PerformanceObserver} instance to notifications of new {PerformanceEntry} instances identified either by `options.entryTypes` or `options.type`: ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((list, observer) => { // Called once asynchronously. `list` contains three items. }); obs.observe({ type: 'mark' }); for (let n = 0; n < 3; n++) performance.mark(`test${n}`); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const obs = new PerformanceObserver((list, observer) => { // Called once asynchronously. `list` contains three items. }); obs.observe({ type: 'mark' }); for (let n = 0; n < 3; n++) performance.mark(`test${n}`); ``` ### `performanceObserver.takeRecords()` * Returns: {PerformanceEntry\[]} Current list of entries stored in the performance observer, emptying it out. ## Class: `PerformanceObserverEntryList` The `PerformanceObserverEntryList` class is used to provide access to the `PerformanceEntry` instances passed to a `PerformanceObserver`. The constructor of this class is not exposed to users. ### `performanceObserverEntryList.getEntries()` * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime`. ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntries()); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 81.465639, * duration: 0, * detail: null * }, * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 81.860064, * duration: 0, * detail: null * } * ] */ performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ type: 'mark' }); performance.mark('test'); performance.mark('meow'); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntries()); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 81.465639, * duration: 0, * detail: null * }, * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 81.860064, * duration: 0, * detail: null * } * ] */ performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ type: 'mark' }); performance.mark('test'); performance.mark('meow'); ``` ### `performanceObserverEntryList.getEntriesByName(name[, type])` * `name` {string} * `type` {string} * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime` whose `performanceEntry.name` is equal to `name`, and optionally, whose `performanceEntry.entryType` is equal to `type`. ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntriesByName('meow')); /** * [ * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 98.545991, * duration: 0, * detail: null * } * ] */ console.log(perfObserverList.getEntriesByName('nope')); // [] console.log(perfObserverList.getEntriesByName('test', 'mark')); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 63.518931, * duration: 0, * detail: null * } * ] */ console.log(perfObserverList.getEntriesByName('test', 'measure')); // [] performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['mark', 'measure'] }); performance.mark('test'); performance.mark('meow'); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntriesByName('meow')); /** * [ * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 98.545991, * duration: 0, * detail: null * } * ] */ console.log(perfObserverList.getEntriesByName('nope')); // [] console.log(perfObserverList.getEntriesByName('test', 'mark')); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 63.518931, * duration: 0, * detail: null * } * ] */ console.log(perfObserverList.getEntriesByName('test', 'measure')); // [] performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['mark', 'measure'] }); performance.mark('test'); performance.mark('meow'); ``` ### `performanceObserverEntryList.getEntriesByType(type)` * `type` {string} * Returns: {PerformanceEntry\[]} Returns a list of `PerformanceEntry` objects in chronological order with respect to `performanceEntry.startTime` whose `performanceEntry.entryType` is equal to `type`. ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntriesByType('mark')); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 55.897834, * duration: 0, * detail: null * }, * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 56.350146, * duration: 0, * detail: null * } * ] */ performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ type: 'mark' }); performance.mark('test'); performance.mark('meow'); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const obs = new PerformanceObserver((perfObserverList, observer) => { console.log(perfObserverList.getEntriesByType('mark')); /** * [ * PerformanceEntry { * name: 'test', * entryType: 'mark', * startTime: 55.897834, * duration: 0, * detail: null * }, * PerformanceEntry { * name: 'meow', * entryType: 'mark', * startTime: 56.350146, * duration: 0, * detail: null * } * ] */ performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ type: 'mark' }); performance.mark('test'); performance.mark('meow'); ``` ## `perf_hooks.createHistogram([options])` * `options` {Object} * `lowest` {number|bigint} The lowest discernible value. Must be an integer value greater than 0. **Default:** `1`. * `highest` {number|bigint} The highest recordable value. Must be an integer value that is equal to or greater than two times `lowest`. **Default:** `Number.MAX_SAFE_INTEGER`. * `figures` {number} The number of accuracy digits. Must be a number between `1` and `5`. **Default:** `3`. * `halfLife` {number} The EWMA half-life in number of samples. When set to a value greater than 0, the histogram tracks an exponentially weighted moving average and standard deviation, accessible via `histogram.ewmaMean` and `histogram.ewmaStddev`. After `halfLife` recordings, a value's influence has decayed to 50%. **Default:** `0` (disabled). * `threshold` {number} An SLO threshold value. When set together with `halfLife`, the histogram tracks a smoothed error rate for values exceeding this threshold, accessible via `histogram.ewmaErrorRate` and `histogram.burnRate()`. **Default:** `0` (disabled). * Returns: {RecordableHistogram} Returns a {RecordableHistogram}. ## `perf_hooks.eventLoopUtilization([utilization1[, utilization2]])` * `utilization1` {Object} The result of a previous call to `eventLoopUtilization()`. * `utilization2` {Object} The result of a previous call to `eventLoopUtilization()` prior to `utilization1`. * Returns: {Object} * `idle` {number} * `active` {number} * `utilization` {number} The `eventLoopUtilization()` function returns an object that contains the cumulative duration of time the event loop has been both idle and active as a high resolution milliseconds timer. The `utilization` value is the calculated Event Loop Utilization (ELU). If bootstrapping has not yet finished on the main thread the properties have the value of `0`. The ELU is immediately available on [Worker threads][] since bootstrap happens within the event loop. Both `utilization1` and `utilization2` are optional parameters. If `utilization1` is passed, then the delta between the current call's `active` and `idle` times, as well as the corresponding `utilization` value are calculated and returned (similar to [`process.hrtime()`][]). If `utilization1` and `utilization2` are both passed, then the delta is calculated between the two arguments. This is a convenience option because, unlike [`process.hrtime()`][], calculating the ELU is more complex than a single subtraction. ELU is similar to CPU utilization, except that it only measures event loop statistics and not CPU usage. It represents the percentage of time the event loop has spent outside the event loop's event provider (e.g. `epoll_wait`). No other CPU idle time is taken into consideration. The following is an example of how a mostly idle process will have a high ELU. ```mjs import { eventLoopUtilization } from 'node:perf_hooks'; import { spawnSync } from 'node:child_process'; setImmediate(() => { const elu = eventLoopUtilization(); spawnSync('sleep', ['5']); console.log(eventLoopUtilization(elu).utilization); }); ``` ```cjs const { eventLoopUtilization } = require('node:perf_hooks'); const { spawnSync } = require('node:child_process'); setImmediate(() => { const elu = eventLoopUtilization(); spawnSync('sleep', ['5']); console.log(eventLoopUtilization(elu).utilization); }); ``` Although the CPU is mostly idle while running this script, the value of `utilization` is `1`. This is because the call to [`child_process.spawnSync()`][] blocks the event loop from proceeding. Passing in a user-defined object instead of the result of a previous call to `eventLoopUtilization()` will lead to undefined behavior. The return values are not guaranteed to reflect any correct state of the event loop. ## `perf_hooks.monitorEventLoopDelay([options])` * `options` {Object} * `samplePerIteration` {boolean} When `true`, samples are taken once per event loop iteration. **Default:** `false`. * `resolution` {number} The sampling rate in milliseconds for interval-based sampling. Must be greater than zero. This option is ignored when `samplePerIteration` is `true`. **Default:** `10`. * Returns: {ELDHistogram} _This property is an extension by Node.js. It is not available in Web browsers._ Creates a histogram object that samples and reports the event loop delay over time. The delays will be reported in nanoseconds. By default, the histogram is updated by a timer using the configured `resolution`. When `samplePerIteration` is `true`, samples are taken once per event loop iteration using `uv_prepare_t` and `uv_check_t` hooks. In that mode, the histogram does not keep the loop alive or force additional iterations when the application is idle. The two sampling modes produce significantly different results and should not be compared directly. ```mjs import { monitorEventLoopDelay } from 'node:perf_hooks'; const h = monitorEventLoopDelay({ resolution: 20 }); h.enable(); // Do something. h.disable(); console.log(h.min); console.log(h.max); console.log(h.mean); console.log(h.stddev); console.log(h.percentiles); console.log(h.percentile(50)); console.log(h.percentile(99)); ``` ```cjs const { monitorEventLoopDelay } = require('node:perf_hooks'); const h = monitorEventLoopDelay({ resolution: 20 }); h.enable(); // Do something. h.disable(); console.log(h.min); console.log(h.max); console.log(h.mean); console.log(h.stddev); console.log(h.percentiles); console.log(h.percentile(50)); console.log(h.percentile(99)); ``` ## `perf_hooks.timerify(fn[, options])` * `fn` {Function} * `options` {Object} * `histogram` {RecordableHistogram} A histogram object created using `perf_hooks.createHistogram()` that will record runtime durations in nanoseconds. _This property is an extension by Node.js. It is not available in Web browsers._ Wraps a function within a new function that measures the running time of the wrapped function. A `PerformanceObserver` must be subscribed to the `'function'` event type in order for the timing details to be accessed. ```mjs import { timerify, performance, PerformanceObserver } from 'node:perf_hooks'; function someFunction() { console.log('hello world'); } const wrapped = timerify(someFunction); const obs = new PerformanceObserver((list) => { console.log(list.getEntries()[0].duration); performance.clearMarks(); performance.clearMeasures(); obs.disconnect(); }); obs.observe({ entryTypes: ['function'] }); // A performance timeline entry will be created wrapped(); ``` ```cjs const { timerify, performance, PerformanceObserver, } = require('node:perf_hooks'); function someFunction() { console.log('hello world'); } const wrapped = timerify(someFunction); const obs = new PerformanceObserver((list) => { console.log(list.getEntries()[0].duration); performance.clearMarks(); performance.clearMeasures(); obs.disconnect(); }); obs.observe({ entryTypes: ['function'] }); // A performance timeline entry will be created wrapped(); ``` If the wrapped function returns a promise, a finally handler will be attached to the promise and the duration will be reported once the finally handler is invoked. ## Class: `Histogram` ### `histogram.count` * Type: {number} The number of samples recorded by the histogram. ### `histogram.countBigInt` * Type: {bigint} The number of samples recorded by the histogram. ### `histogram.ccdf(value)` * `value` {number} The value to query. * Returns: {number} A probability between 0.0 and 1.0. Returns the complementary cumulative distribution function (CCDF) value for the given value, representing the probability that a recorded value will exceed `value`. Equivalent to `1 - histogram.cdf(value)`. ### `histogram.cdf(value)` * `value` {number} The value to query. * Returns: {number} A probability between 0.0 and 1.0. Returns the cumulative distribution function (CDF) value for the given value, representing the probability that a recorded value will be less than or equal to `value`. This is the inverse operation of `histogram.percentile()`. ### `histogram.cliffsD(other)` * `other` {Histogram} The histogram to compare against. * Returns: {number} A value between -1.0 and 1.0. Computes [Cliff's delta][], a non-parametric effect size measure. Returns the probability that a random value from this histogram exceeds a random value from `other`, minus the reverse probability. A value of 1 means every value in this histogram exceeds every value in `other`; -1 means the opposite; 0 means no tendency in either direction. ### `histogram.cohensD(other)` * `other` {Histogram} The histogram to compare against. * Returns: {number} The effect size. Computes [Cohen's d][] effect size, the standardized difference between the means of this histogram and `other`, using the pooled standard deviation. Positive values indicate this histogram has a higher mean. By convention, |d| < 0.2 is a small effect, 0.5 is medium, and 0.8 or greater is large. Both histograms must have at least 2 recorded values; otherwise returns 0. ### `histogram.countAt(value)` * `value` {number} The value to query. * Returns: {number} Returns the number of recorded values that fall within the equivalent value range of the given value. ### `histogram.exceeds` * Type: {number} The number of times the event loop delay exceeded the maximum 1 hour event loop delay threshold. ### `histogram.exceedsBigInt` * Type: {bigint} The number of times the event loop delay exceeded the maximum 1 hour event loop delay threshold. ### `histogram.ewmaMean` * Type: {number} The exponentially weighted moving average of recorded values. Only active when the histogram was created with a `halfLife` option greater than 0. Returns `0` when EWMA is disabled or no values have been recorded. ### `histogram.ewmaStddev` * Type: {number} The exponentially weighted moving standard deviation. Only active when the histogram was created with a `halfLife` option greater than 0. Returns `0` when EWMA is disabled or no values have been recorded. ### `histogram.ewmaErrorRate` * Type: {number} The EWMA-smoothed probability of a recorded value exceeding the configured `threshold`. Only active when the histogram was created with both `halfLife` and `threshold` options. Returns `0` when not enabled or no values have been recorded. ### `histogram.burnRate(sloTarget)` * `sloTarget` {number} The SLO target as a fraction between 0 and 1 (exclusive). For example, `0.999` for a 99.9% SLO. * Returns: {number} Returns the SLO burn rate: `ewmaErrorRate / (1 - sloTarget)`. A burn rate of 1 means the error budget will be exactly exhausted over the SLO window. A burn rate greater than 1 means it is being consumed faster than allowed. Requires the histogram to have been created with both `halfLife` and `threshold` options. ```js const { createHistogram } = require('node:perf_hooks'); // Track latency with a 200ms SLO threshold, half-life of 100 samples const h = createHistogram({ halfLife: 100, threshold: 200_000_000 }); // ... record latency values ... // Check burn rate against a 99.9% SLO const rate = h.burnRate(0.999); if (rate > 1) { console.log(`SLO burn rate: ${rate.toFixed(2)}x — error budget depleting`); } ``` ### `histogram.ksTest(other)` * `other` {Histogram} The histogram to compare against. * Returns: {number} The KS D-statistic, between 0.0 and 1.0. Computes the Kolmogorov-Smirnov test statistic comparing this histogram's distribution to `other`. A value of 0 indicates identical distributions; values close to 1 indicate completely disjoint distributions. Useful for detecting performance regressions by comparing before/after histograms. ### `histogram.kurtosis` * Type: {number} The excess kurtosis of the recorded values. Measures the heaviness of the distribution's tails relative to a normal distribution. Positive values indicate heavier tails (more extreme outliers); negative values indicate lighter tails. ### `histogram.linearBuckets(stepSize)` * `stepSize` {number} The width of each linear bucket. * Returns: {Map} A map of bucket boundary values to counts. Returns the histogram data rebucketed into linearly-spaced intervals of `stepSize`. Useful for visualization and export. ### `histogram.logBuckets(firstBucket, base)` * `firstBucket` {number} The value of the first bucket boundary. * `base` {number} The logarithmic base for bucket width growth. Must be > 1. * Returns: {Map} A map of bucket boundary values to counts. Returns the histogram data rebucketed into logarithmically-spaced intervals, where each bucket's width is multiplied by `base`. Useful for visualization and export. ### `histogram.mannWhitneyTest(other)` * `other` {Histogram} The histogram to compare against. * Returns: {Object} * `uStatistic` {number} The Mann-Whitney U statistic. * `zScore` {number} The z-score (normal approximation). * `pValue` {number} Two-tailed p-value. Performs a [Mann-Whitney U test][] comparing whether this histogram tends to produce larger or smaller values than `other`. Unlike `welchTest()`, this is a non-parametric test that makes no assumptions about the shape of the distributions. Uses the normal approximation with tie correction for the p-value. ### `histogram.max` * Type: {number} The maximum recorded event loop delay. ### `histogram.maxBigInt` * Type: {bigint} The maximum recorded event loop delay. ### `histogram.mean` * Type: {number} The mean of the recorded event loop delays. ### `histogram.min` * Type: {number} The minimum recorded event loop delay. ### `histogram.minBigInt` * Type: {bigint} The minimum recorded event loop delay. ### `histogram.percentile(percentile)` * `percentile` {number} A percentile value in the range (0, 100]. * Returns: {number} Returns the value at the given percentile. ### `histogram.percentileBigInt(percentile)` * `percentile` {number} A percentile value in the range (0, 100]. * Returns: {bigint} Returns the value at the given percentile. ### `histogram.percentileCI(percentile[, options])` * `percentile` {number} A percentile value in the range (0, 100]. * `options` {Object} * `confidence` {number} The confidence level for the interval, between 0 and 1 (exclusive). **Default:** `0.95`. * Returns: {Object} * `value` {number} The point estimate (same as `histogram.percentile()`). * `lower` {number} The lower bound of the confidence interval. * `upper` {number} The upper bound of the confidence interval. Returns a confidence interval for the given percentile using the exact binomial method. With fewer samples, the interval will be wider, reflecting the greater uncertainty in the percentile estimate. Requires at least 2 recorded values; with fewer than 2, `lower` and `upper` will equal `value`. ```js const { createHistogram } = require('node:perf_hooks'); const h = createHistogram(); for (let i = 0; i < 1000; i++) { h.record(Math.floor(Math.random() * 100)); } const ci = h.percentileCI(99); console.log(ci.value); // The p99 point estimate console.log(ci.lower); // The lower bound (95% confidence) console.log(ci.upper); // The upper bound (95% confidence) ``` ### `histogram.percentiles` * Type: {Map} Returns a `Map` object detailing the accumulated percentile distribution. ### `histogram.percentilesBigInt` * Type: {Map} Returns a `Map` object detailing the accumulated percentile distribution. ### `histogram.percentilesAt(percentiles)` * `percentiles` {number\[]} An array of percentile values in the range (0, 100]. * Returns: {Map} A map of percentile values to their corresponding histogram values. Returns the values at the specified percentiles, computed in a single efficient pass over the histogram data. More efficient than calling `histogram.percentile()` multiple times. ### `histogram.reset()` Resets the collected histogram data. ### `histogram.skewness` * Type: {number} The skewness of the recorded values. Measures the asymmetry of the distribution. A positive value indicates a right-skewed distribution (longer right tail, common for latency data); a negative value indicates a left-skewed distribution. ### `histogram.stddev` * Type: {number} The standard deviation of the recorded event loop delays. ### `histogram.welchTest(other[, options])` * `other` {Histogram} The histogram to compare against. * `options` {Object} * `confidence` {number} Confidence level for the interval, between 0 and 1. **Default:** `0.95`. * Returns: {Object} * `tStatistic` {number} The Welch t-statistic. * `degreesOfFreedom` {number} Welch-Satterthwaite degrees of freedom. * `pValue` {number} Two-tailed p-value. * `confidenceInterval` {Object} * `lower` {number} Lower bound of the confidence interval on the difference of means. * `upper` {number} Upper bound. Performs [Welch's t-test][] comparing the means of this histogram and `other`. The p-value indicates the probability of observing a difference at least this extreme under the null hypothesis that the two distributions have the same mean. Both histograms must have at least 2 recorded values; otherwise the result has `pValue` 1 and `tStatistic` 0. ## Class: `ELDHistogram extends Histogram` A `Histogram` that records event loop delay, returned by [`perf_hooks.monitorEventLoopDelay()`][]. ### `histogram.disable()` * Returns: {boolean} Disables event loop delay sampling. Returns `true` if sampling was stopped, `false` if it was already stopped. ### `histogram.enable()` * Returns: {boolean} Enables event loop delay sampling. Returns `true` if sampling was started, `false` if it was already started. ### `histogram[Symbol.dispose]()` Disables event loop delay sampling when the histogram is disposed. ```js const { monitorEventLoopDelay } = require('node:perf_hooks'); { using hist = monitorEventLoopDelay({ resolution: 20 }); hist.enable(); // The histogram will be disabled when the block is exited. } ``` ### Cloning an `ELDHistogram` {ELDHistogram} instances can be cloned via {MessagePort}. On the receiving end, the histogram is cloned as a plain {Histogram} object that does not implement the `enable()` and `disable()` methods. ## Class: `RecordableHistogram extends Histogram` ### `histogram.add(other)` * `other` {RecordableHistogram} Adds the values from `other` to this histogram. ### `histogram.record(val)` * `val` {number|bigint} The amount to record in the histogram. ### `histogram.recordDelta()` Calculates the amount of time (in nanoseconds) that has passed since the previous call to `recordDelta()` and records that amount in the histogram. ### `histogram.recordCorrected(val, expectedInterval)` * `val` {number|bigint} The value to record. * `expectedInterval` {number|bigint} The expected recording interval. Records a value with coordinated omission correction. When a system stall prevents timely recording, this method backfills intermediate values at `expectedInterval` steps between the previously recorded value and `val`. This compensates for measurement gaps that would otherwise underrepresent latency. ### `histogram.subtract(other)` * `other` {RecordableHistogram} Subtracts the values of `other` from this histogram. Both histograms should have compatible configurations. Bucket counts that would become negative are clamped to zero. ## Histogram analysis examples The `Histogram` class provides statistical analysis methods useful for performance monitoring, SLO enforcement, and regression detection. ### Distribution shape analysis ```js const { createHistogram } = require('node:perf_hooks'); const h = createHistogram(); // Simulate a right-skewed latency distribution for (let i = 0; i < 1000; i++) { h.record(Math.ceil(Math.random() * 100)); } // Add some outliers for (let i = 0; i < 10; i++) { h.record(500 + Math.ceil(Math.random() * 500)); } console.log('Skewness:', h.skewness.toFixed(4)); // Positive = right-skewed console.log('Kurtosis:', h.kurtosis.toFixed(4)); // Positive = heavy tails ``` ### SLO monitoring with CDF ```js const { createHistogram } = require('node:perf_hooks'); const latency = createHistogram(); // Record request latencies (in nanoseconds)... // "What fraction of requests complete within 100ms?" const withinSLO = latency.cdf(100_000_000); console.log(`${(withinSLO * 100).toFixed(1)}% of requests within SLO`); // "What fraction of requests exceed 500ms?" const violating = latency.ccdf(500_000_000); console.log(`${(violating * 100).toFixed(1)}% of requests violating SLO`); ``` ### SLO burn rate monitoring ```js const { createHistogram } = require('node:perf_hooks'); // Track latency with EWMA (half-life 100 samples) and a 200ms SLO threshold const latency = createHistogram({ halfLife: 100, threshold: 200_000_000, // 200ms in nanoseconds }); // Record request latencies... // Smoothed error rate: probability of exceeding the threshold console.log(`Error rate: ${(latency.ewmaErrorRate * 100).toFixed(2)}%`); // Burn rate against a 99.9% SLO // >1 means the error budget is depleting faster than allowed const rate = latency.burnRate(0.999); console.log(`Burn rate: ${rate.toFixed(2)}x`); // EWMA mean and stddev track the smoothed latency console.log(`EWMA latency: ${latency.ewmaMean.toFixed(0)}ns`); console.log(`EWMA stddev: ${latency.ewmaStddev.toFixed(0)}ns`); ``` ### Regression detection with KS test ```js const { createHistogram } = require('node:perf_hooks'); const baseline = createHistogram(); const current = createHistogram(); // Record baseline and current latencies... // D-statistic: 0 = identical, 1 = completely different const d = baseline.ksTest(current); if (d > 0.1) { console.log(`Possible regression detected (D=${d.toFixed(4)})`); } ``` ### Batch percentile queries ```js const { createHistogram } = require('node:perf_hooks'); const h = createHistogram(); // Record values... // Efficiently query common monitoring percentiles in one pass const p = h.percentilesAt([50, 75, 90, 95, 99, 99.9]); console.log('p50:', p.get(50)); console.log('p99:', p.get(99)); ``` ### Snapshot diffing with subtract ```js const { createHistogram } = require('node:perf_hooks'); const total = createHistogram(); const snapshot = createHistogram(); // Record values into total... // Periodically snapshot for "last interval" analysis: snapshot.add(total); // Later, take a new snapshot and diff: const newSnapshot = createHistogram(); newSnapshot.add(total); newSnapshot.subtract(snapshot); // newSnapshot now contains only the values recorded since the last snapshot console.log('Recent p99:', newSnapshot.percentile(99)); ``` ### Benchmark comparison with Welch's t-test ```js const { createHistogram } = require('node:perf_hooks'); const baseline = createHistogram(); const candidate = createHistogram(); // Record operation rates from the old and new builds... const result = baseline.welchTest(candidate); const improvement = ((candidate.mean - baseline.mean) / baseline.mean * 100); console.log(`Improvement: ${improvement.toFixed(2)}%`); console.log(`p-value: ${result.pValue.toFixed(6)}`); console.log(`95% CI: [${result.confidenceInterval.lower.toFixed(2)}, ` + `${result.confidenceInterval.upper.toFixed(2)}]`); if (result.pValue < 0.05) { const d = baseline.cohensD(candidate); console.log(`Statistically significant (Cohen's d = ${d.toFixed(4)})`); } ``` ### Effect size with Cliff's delta ```js const { createHistogram } = require('node:perf_hooks'); const before = createHistogram(); const after = createHistogram(); // Record latencies before and after a change... const delta = before.cliffsD(after); // A delta > 0: before tends to produce larger values (improvement) // A delta < 0: after tends to produce larger values (regression) console.log(`Cliff's delta: ${delta.toFixed(4)}`); ``` ## Examples ### Measuring the duration of async operations The following example uses the [Async Hooks][] and Performance APIs to measure the actual duration of a Timeout operation (including the amount of time it took to execute the callback). ```mjs import { createHook } from 'node:async_hooks'; import { performance, PerformanceObserver } from 'node:perf_hooks'; const set = new Set(); const hook = createHook({ init(id, type) { if (type === 'Timeout') { performance.mark(`Timeout-${id}-Init`); set.add(id); } }, destroy(id) { if (set.has(id)) { set.delete(id); performance.mark(`Timeout-${id}-Destroy`); performance.measure(`Timeout-${id}`, `Timeout-${id}-Init`, `Timeout-${id}-Destroy`); } }, }); hook.enable(); const obs = new PerformanceObserver((list, observer) => { console.log(list.getEntries()[0]); performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['measure'], buffered: true }); setTimeout(() => {}, 1000); ``` ```cjs const async_hooks = require('node:async_hooks'); const { performance, PerformanceObserver, } = require('node:perf_hooks'); const set = new Set(); const hook = async_hooks.createHook({ init(id, type) { if (type === 'Timeout') { performance.mark(`Timeout-${id}-Init`); set.add(id); } }, destroy(id) { if (set.has(id)) { set.delete(id); performance.mark(`Timeout-${id}-Destroy`); performance.measure(`Timeout-${id}`, `Timeout-${id}-Init`, `Timeout-${id}-Destroy`); } }, }); hook.enable(); const obs = new PerformanceObserver((list, observer) => { console.log(list.getEntries()[0]); performance.clearMarks(); performance.clearMeasures(); observer.disconnect(); }); obs.observe({ entryTypes: ['measure'] }); setTimeout(() => {}, 1000); ``` ### Measuring how long it takes to load dependencies The following example measures the duration of `require()` operations to load dependencies: ```mjs import { performance, PerformanceObserver } from 'node:perf_hooks'; // Activate the observer const obs = new PerformanceObserver((list) => { const entries = list.getEntries(); entries.forEach((entry) => { console.log(`import('${entry[0]}')`, entry.duration); }); performance.clearMarks(); performance.clearMeasures(); obs.disconnect(); }); obs.observe({ entryTypes: ['function'], buffered: true }); const timedImport = performance.timerify(async (module) => { return await import(module); }); await timedImport('some-module'); ``` ```cjs const { performance, PerformanceObserver, } = require('node:perf_hooks'); const mod = require('node:module'); // Monkey patch the require function mod.Module.prototype.require = performance.timerify(mod.Module.prototype.require); require = performance.timerify(require); // Activate the observer const obs = new PerformanceObserver((list) => { const entries = list.getEntries(); entries.forEach((entry) => { console.log(`require('${entry[0]}')`, entry.duration); }); performance.clearMarks(); performance.clearMeasures(); obs.disconnect(); }); obs.observe({ entryTypes: ['function'] }); require('some-module'); ``` ### Measuring how long one HTTP round-trip takes The following example is used to trace the time spent by HTTP client (`OutgoingMessage`) and HTTP request (`IncomingMessage`). For HTTP client, it means the time interval between starting the request and receiving the response, and for HTTP request, it means the time interval between receiving the request and sending the response: ```mjs import { PerformanceObserver } from 'node:perf_hooks'; import { createServer, get } from 'node:http'; const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['http'] }); const PORT = 8080; createServer((req, res) => { res.end('ok'); }).listen(PORT, () => { get(`http://127.0.0.1:${PORT}`); }); ``` ```cjs const { PerformanceObserver } = require('node:perf_hooks'); const http = require('node:http'); const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['http'] }); const PORT = 8080; http.createServer((req, res) => { res.end('ok'); }).listen(PORT, () => { http.get(`http://127.0.0.1:${PORT}`); }); ``` ### Measuring how long the `net.connect` (only for TCP) takes when the connection is successful ```mjs import { PerformanceObserver } from 'node:perf_hooks'; import { connect, createServer } from 'node:net'; const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['net'] }); const PORT = 8080; createServer((socket) => { socket.destroy(); }).listen(PORT, () => { connect(PORT); }); ``` ```cjs const { PerformanceObserver } = require('node:perf_hooks'); const net = require('node:net'); const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['net'] }); const PORT = 8080; net.createServer((socket) => { socket.destroy(); }).listen(PORT, () => { net.connect(PORT); }); ``` ### Measuring how long the DNS takes when the request is successful ```mjs import { PerformanceObserver } from 'node:perf_hooks'; import { lookup, promises } from 'node:dns'; const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['dns'] }); lookup('localhost', () => {}); promises.resolve('localhost'); ``` ```cjs const { PerformanceObserver } = require('node:perf_hooks'); const dns = require('node:dns'); const obs = new PerformanceObserver((items) => { items.getEntries().forEach((item) => { console.log(item); }); }); obs.observe({ entryTypes: ['dns'] }); dns.lookup('localhost', () => {}); dns.promises.resolve('localhost'); ``` [Async Hooks]: async_hooks.md [Cliff's delta]: https://en.wikipedia.org/wiki/Effect_size#Cliff's_delta [Cohen's d]: https://en.wikipedia.org/wiki/Effect_size#Cohen's_d [Fetch Response Body Info]: https://fetch.spec.whatwg.org/#response-body-info [Fetch Timing Info]: https://fetch.spec.whatwg.org/#fetch-timing-info [High Resolution Time]: https://www.w3.org/TR/hr-time-2 [Mann-Whitney U test]: https://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U_test [Performance Timeline]: https://w3c.github.io/performance-timeline/ [Resource Timing]: https://www.w3.org/TR/resource-timing-2/ [User Timing]: https://www.w3.org/TR/user-timing/ [Web Performance APIs]: https://w3c.github.io/perf-timing-primer/ [Welch's t-test]: https://en.wikipedia.org/wiki/Welch%27s_t-test [Worker threads]: worker_threads.md#worker-threads [`'exit'`]: process.md#event-exit [`child_process.spawnSync()`]: child_process.md#child_processspawnsynccommand-args-options [`perf_hooks.eventLoopUtilization()`]: #perf_hookseventlooputilizationutilization1-utilization2 [`perf_hooks.monitorEventLoopDelay()`]: #perf_hooksmonitoreventloopdelayoptions [`perf_hooks.timerify()`]: #perf_hookstimerifyfn-options [`process.hrtime()`]: process.md#processhrtimetime [`timeOrigin`]: https://w3c.github.io/hr-time/#dom-performance-timeorigin [`window.performance.toJSON`]: https://developer.mozilla.org/en-US/docs/Web/API/Performance/toJSON [`window.performance`]: https://developer.mozilla.org/en-US/docs/Web/API/Window/performance