Learn how to measure memory usage of your web page in production to detect regressions.
 Brendan Kenny [GitHub](https://github.com/brendankenny) [Bluesky](https://bsky.app/profile/brendankenny.bsky.social)  Ulan Degenbaev [X](https://twitter.com/ulandev) [GitHub](https://github.com/ulan)
Browsers manage the memory of web pages automatically. Whenever a web page
creates an object, the browser allocates a chunk of memory "under the hood" to
store the object. Since memory is a finite resource, the browser performs
garbage collection to detect when an object is no longer needed and to free
the underlying memory chunk.
The detection is not perfect though, and [Alan Turing's Halting Problem](https://en.wikipedia.org/wiki/Halting_problem) proved that perfect detection is an impossible task.
Therefore browsers approximate the notion of "an object
is needed" with the notion of "an object is reachable". If the web page cannot
reach an object via its variables and the fields of other reachable objects,
then the browser can safely reclaim the object. The difference between these
two notions leads to memory leaks as illustrated by the following example.
const object = {a: new Array(1000), b: new Array(2000)};
setInterval(() => console.log(object.a), 1000);
Here the larger array `b` is no longer needed, but the browser does not
reclaim it because it is still reachable via `object.b` in the callback. Thus
the memory of the larger array is leaked.
Memory leaks are prevalent on the Web, [as can be seen from this study](https://docs.google.com/presentation/d/14uV5jrJ0aPs0Hd0Ehu3JPV8IBGc3U8gU6daLAqj6NrM/edit#slide=id.p).
It is easy to introduce one by forgetting to unregister an event listener, by
accidentally capturing objects from an iframe, by not closing a worker, by
accumulating objects in arrays, and so on. If a web page has memory leaks,
then its memory usage grows over time and the web page appears slow and
bloated to the users.
The first step in solving this problem is measuring it. The new
[`performance.measureUserAgentSpecificMemory()` API](https://github.com/WICG/performance-measure-memory) allows developers to
measure memory usage of their web pages in production and thus detect memory
leaks that slip through local testing.
## How is `performance.measureUserAgentSpecificMemory()` different from the legacy `performance.memory` API?
If you are familiar with the existing non-standard `performance.memory` API,
you might be wondering how the new API differs from it. The main difference is
that the old API returns the size of the JavaScript heap whereas the new API
estimates the memory used by the web page. This difference becomes
important when Chrome shares the same heap with multiple web pages (or
multiple instances of the same web page). In such cases, the result of the old
API may be arbitrarily off. Since the old API is defined in
implementation-specific terms such as "heap", standardizing it is hopeless.
Another difference is that the new API performs memory measurement during
garbage collection. This reduces the noise in the results, but it may take a
while until the results are produced. Note that other browsers may decide to
implement the new API without relying on garbage collection.
## Suggested use cases
Memory usage of a web page depends on the timing of events, user actions, and
garbage collections. That is why the memory measurement API is intended for
aggregating memory usage data from production. The results of individual calls
are less useful. Example use cases:
- Regression detection during rollout of a new version of the web page to catch new memory leaks.
- A/B testing a new feature to evaluate its memory impact and detect memory leaks.
- Correlating memory usage with session duration to verify presence or absence of memory leaks.
- Correlating memory usage with user metrics to understand the overall impact of memory usage.
## Browser compatibility
Browser Support
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[Source](https://developer.mozilla.org/docs/Web/API/Performance/measureUserAgentSpecificMemory)
Currently the API is supported only in Chromium-based browsers, starting in Chrome 89. The
result of the API is highly implementation dependent because browsers have
different ways of representing objects in memory and different ways of
estimating memory usage. Browsers may exclude some memory regions from
accounting if proper accounting is too expensive or infeasible. Thus, results
cannot be compared across browsers. It is only meaningful to compare the
results for the same browser.
## Using `performance.measureUserAgentSpecificMemory()`
### Feature detection
The `performance.measureUserAgentSpecificMemory` function will be unavailable or may
fail with a [SecurityError](https://developer.mozilla.org/docs/Web/API/DOMException#securityerror) if the execution environment does not fulfil
the security requirements for preventing cross-origin information leaks.
It relies on [cross-origin isolation](https://developer.mozilla.org/docs/Web/API/WindowOrWorkerGlobalScope/crossOriginIsolated), which a web page can activate
by setting [COOP+COEP headers](https://web.dev/articles/coop-coep).
Support can be detected at runtime:
if (!window.crossOriginIsolated) {
console.log('performance.measureUserAgentSpecificMemory() is only available in cross-origin-isolated pages');
} else if (!performance.measureUserAgentSpecificMemory) {
console.log('performance.measureUserAgentSpecificMemory() is not available in this browser');
} else {
let result;
try {
result = await performance.measureUserAgentSpecificMemory();
} catch (error) {
if (error instanceof DOMException && error.name === 'SecurityError') {
console.log('The context is not secure.');
} else {
throw error;
}
}
console.log(result);
}
### Local testing
Chrome performs the memory measurement during garbage collection, which means
that the API does not resolve the result promise immediately and instead waits
for the next garbage collection.
Calling the API forces a garbage collection after some timeout, which is
currently set to 20 seconds, though may happen sooner. Starting Chrome with the
`--enable-blink-features='ForceEagerMeasureMemory'` command-line flag reduces
the timeout to zero and is useful for local debugging and testing.
## Example
The recommended usage of the API is to define a global memory monitor that
samples memory usage of the whole web page and sends the results to a server
for aggregation and analysis. The simplest way is to sample periodically, for
example every `M` minutes. However, that introduces bias to the data because
memory peaks may occur between the samples.
The following example shows how to
do unbiased memory measurements using a [Poisson process](https://en.wikipedia.org/wiki/Poisson_point_process), which
guarantees that samples are equally likely to occur at any point in time
([demo](https://performance-measure-user-agent-specific-memory.glitch.me/), [source](https://glitch.com/edit/#!/performance-measure-user-agent-specific-memory?path=public%2Fmeasure-memory.js)).
First, define a function that schedules the next memory measurement using
`setTimeout()` with a randomized interval.
function scheduleMeasurement() {
// Check measurement API is available.
if (!window.crossOriginIsolated) {
console.log('performance.measureUserAgentSpecificMemory() is only available in cross-origin-isolated pages');
console.log('See https://web.dev/coop-coep/ to learn more')
return;
}
if (!performance.measureUserAgentSpecificMemory) {
console.log('performance.measureUserAgentSpecificMemory() is not available in this browser');
return;
}
const interval = measurementInterval();
console.log(`Running next memory measurement in ${Math.round(interval / 1000)} seconds`);
setTimeout(performMeasurement, interval);
}
The `measurementInterval()` function computes a random interval in milliseconds
such that on average there is one measurement every five minutes. See [Exponential
distribution](https://en.wikipedia.org/wiki/Exponential_distribution#Random_variate_generation) if you are interested in the math behind the function.
function measurementInterval() {
const MEAN_INTERVAL_IN_MS = 5 * 60 * 1000;
return -Math.log(Math.random()) * MEAN_INTERVAL_IN_MS;
}
Finally, the async `performMeasurement()` function invokes the API, records
the result, and schedules the next measurement.
async function performMeasurement() {
// 1. Invoke performance.measureUserAgentSpecificMemory().
let result;
try {
result = await performance.measureUserAgentSpecificMemory();
} catch (error) {
if (error instanceof DOMException && error.name === 'SecurityError') {
console.log('The context is not secure.');
return;
}
// Rethrow other errors.
throw error;
}
// 2. Record the result.
console.log('Memory usage:', result);
// 3. Schedule the next measurement.
scheduleMeasurement();
}
Finally, begin measuring.
// Start measurements.
scheduleMeasurement();
The result may look as follows:
// Console output:
{
bytes: 60_100_000,
breakdown: [
{
bytes: 40_000_000,
attribution: [{
url: 'https://example.com/',
scope: 'Window',
}],
types: ['JavaScript']
},
{
bytes: 20_000_000,
attribution: [{
url: 'https://example.com/iframe',
container: {
id: 'iframe-id-attribute',
src: '/iframe',
},
scope: 'Window',
}],
types: ['JavaScript']
},
{
bytes: 100_000,
attribution: [],
types: ['DOM']
},
],
}
The total memory usage estimate is returned in the `bytes` field. This value is
highly implementation-dependent and cannot be compared across browsers. It may
even change between different versions of the same browser. The value includes
JavaScript and DOM memory of all iframes, related windows, and web workers in
the current process.
The `breakdown` list provides further information about the used memory. Each
entry describes some portion of the memory and attributes it to a set of
windows, iframes, and workers identified by URL. The `types` field lists
the implementation-specific memory types associated with the memory.
It is important to treat all lists in a generic way and to not hardcode
assumptions based on a particular browser. For example, some browsers may
return an empty `breakdown` or an empty `attribution`. Other browsers may
return multiple entries in `attribution` indicating they could not distinguish
which of these entries owns the memory.
## Feedback
The [Web Performance Community Group](https://www.w3.org/community/webperfs/) and the Chrome team would love
to hear about your thoughts and experiences with
`performance.measureUserAgentSpecificMemory()`.
### Tell us about the API design
Is there something about the API that doesn't work as expected? Or are there
missing properties that you need to implement your idea? File a spec issue on
the [performance.measureUserAgentSpecificMemory() GitHub repo](https://github.com/WICG/performance-measure-memory/issues) or add
your thoughts to a existing issue.
### Report a problem with the implementation
Did you find a bug with Chrome's implementation? Or is the implementation
different from the spec? File a bug at [new.crbug.com](https://issues.chromium.org/issues/new?noWizard=true&template=2031629&component=1456231). Be sure to
include as much detail as you can, provide simple instructions for reproducing
the bug, and have **Components** set to `Blink>PerformanceAPIs`.
### Show support
Are you planning to use `performance.measureUserAgentSpecificMemory()`? Your public support
helps the Chrome team prioritize features and shows other browser vendors how
critical it is to support them. Send a tweet to [@ChromiumDev](https://twitter.com/chromiumdev)
and let us know where and how you're using it.
## Helpful links
- [Explainer](https://github.com/WICG/performance-measure-memory)
- [Demo](https://performance-measure-user-agent-specific-memory.glitch.me/) \| [Demo source](https://glitch.com/edit/#!/performance-measure-user-agent-specific-memory?path=public%2Fmeasure-memory.js)
- [Tracking bug](https://bugs.chromium.org/p/chromium/issues/detail?id=1085129)
- [ChromeStatus.com entry](https://www.chromestatus.com/feature/5685965186138112)
- [Changes since Origin Trial API](https://github.com/WICG/performance-measure-memory/blob/master/ORIGIN_TRIAL.md#result-differences)
- [Concluded Origin Trial](https://developers.chrome.com/origintrials/#/view_trial/1281274093986906113)
## Acknowledgements
Big thanks to Domenic Denicola, Yoav Weiss, Mathias Bynens for API design reviews,
and Dominik Inführ, Hannes Payer, Kentaro Hara, Michael Lippautz for code reviews
in Chrome. I also thank Per Parker, Philipp Weis, Olga Belomestnykh, Matthew
Bolohan, and Neil Mckay for providing valuable user feedback that greatly
improved the API.