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feat: Publish Web-Perf Wednesday 006
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### More Web-Perf Wednesdays
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<ol reversed>
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<li><a href="/2026/08/web-perf-wednesday-006-faster-browser-releases-change-your-rum-population/">Web-Perf Wednesday 006 – Faster Browser Releases Change Your RUM Population</a></li>
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<li><a href="/2026/08/web-perf-wednesday-005-rum-needs-more-than-a-percentile/">Web-Perf Wednesday 005 – RUM Needs More Than a Percentile</a></li>
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<li><a href="/2026/08/web-perf-wednesday-004-a-quiet-week-is-time-to-investigate/">Web-Perf Wednesday 004 – A Quiet Week Is Time to Investigate</a></li>
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<li><a href="/2026/08/web-perf-wednesday-003-native-spa-metrics-have-arrived/">Web-Perf Wednesday 003 – Native SPA Metrics Have Arrived</a></li>
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---
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layout: post
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title: "Web-Perf Wednesday 006 – Faster Browser Releases Change Your RUM Population"
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date: 2026-08-26 12:00:00 +0100
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categories: Web Development
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main: ""
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meta: "Chrome and Firefox are moving to two-week releases, making browser cadence part of how teams interpret RUM and plan performance testing."
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---
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Quite a lot has changed since last week, but the browser calendar is the one
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most likely to alter performance data without anybody deploying a thing.
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Chrome and Firefox are both preparing to release major versions every two
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weeks, Chrome DevTools can now show Core Web Vitals for soft navigations in
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Live Metrics, and my latest field-data investigation exposes time inside TTFB
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that our usual breakdowns can’t explain. Taken together, this is another week
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where understanding the population matters as much as reading the percentile.
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## Faster Chrome Releases Change Your RUM Population
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[Chrome will move from a four-week to a two-week release
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cycle](https://developer.chrome.com/blog/chrome-two-week-release) from Chrome
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153, whose Stable release is scheduled for 8 September. A new Beta and Stable
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version will arrive every two weeks on Desktop, Android, and iOS; Dev and
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Canary are unchanged, while Extended Stable keeps its existing eight-week
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cycle. Chrome also says each Beta will precede Stable by three weeks.
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The schedule is Chrome’s; the RUM implications are my own and are something I’d
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expect teams to test. Browser version is about to become a faster-moving RUM
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dimension.
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Segmenting by exact Chrome major will probably produce smaller, shorter-lived
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cohorts, particularly on lower-traffic routes or when browser, device, country,
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and experiment dimensions are combined. A 28-day chart will contain more
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release boundaries, and a movement that appears between two dates may reflect
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a different mixture of Chrome versions rather than a product release. Extended
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Stable will add a longer-lived cohort of managed users to that mixture.
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This also changes how teams should compare before-and-after data. A fortnightly
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cadence can put two Chrome milestones inside one reporting window, so a
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browser-specific p75 may be dominated by whichever version had enough samples
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on that day. Set minimum sample and completion thresholds before slicing by
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major, and fall back to a broader Chrome cohort when the exact-version view is
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too thin. Otherwise, the segmentation intended to explain one movement can
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manufacture a second, noisier chart.
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None of this makes a percentile wrong; it changes the questions needed to
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interpret it. If LCP moves while application and delivery releases remain
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quiet, compare Chrome-major distribution, sample count, device mix, and metric
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completion before declaring a regression. Keep an unsegmented series as the
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view of users’ overall experience, but retain enough browser detail to explain
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why its population changed.
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Release annotations will also need a named owner. With a major version every
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fortnight, adding browser dates only after a graph has moved is too late. Pull
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the Chrome schedule into the same release calendar used for application, CDN,
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tag-manager, and RUM changes; record Beta and Stable dates; and preserve the
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instrumentation version alongside each page view. A careful [RUM
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strategy](/consultancy/) should let an analyst distinguish a site change from
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a browser-population change without rebuilding the history by hand. Treat the
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date as an annotation rather than a claim that every user updated at once;
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chart the actual version share alongside it.
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The three-week Beta lead time matters too. Test the real journeys and
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instrumentation in Beta, including route detection, metric completion,
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bfcache, and any browser-specific dimensions, rather than treating Beta as a
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late compatibility check. Faster releases reduce the time between a browser
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change reaching users and its effect appearing in production RUM. The calendar
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now belongs in the measurement model.
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## Firefox Is Moving Fortnightly Too
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Mozilla has also [set out its move to a two-week Firefox release
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cycle](https://blog.mozilla.org/sumo/2026/08/19/firefox-new-release-cadence-and-what-to-expect/).
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Firefox 155 is due on 1 September, two weeks earlier than originally planned;
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Mozilla says this doesn’t mean twice as many features, and dot releases may
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still happen when needed. The [underlying
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announcement](https://groups.google.com/a/mozilla.org/g/dev-platform/c/qlaQ1YSlOP8)
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describes the change as an experiment for Firefox Desktop and Android.
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Teams will need the same release-aware analysis for Firefox. Keep its calendar
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beside Chrome’s, check whether exact major-version cohorts remain large enough
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to trust, and make Beta coverage a routine part of [team performance
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testing](/workshops/). The useful question isn’t merely which version a slow
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visit used, but whether a release changed the make-up of visits entering the
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chart.
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## Soft-Navigation Vitals Reach Live Metrics
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[Chrome 152 DevTools](https://developer.chrome.com/blog/new-in-devtools-152)
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now reports Core Web Vitals for client-side soft navigations in the Performance
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panel’s Live Metrics view by default, powered by `web-vitals` v6. That gives SPA
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teams a much quicker way to inspect a route transition locally before comparing
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it with RUM.
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The same release notes now document the Network panel’s pinned ‘Request #’
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column, which [last week](/2026/08/web-perf-wednesday-005-rum-needs-more-than-a-percentile/)
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was verified only in Canary while the public issue remained in progress. Both
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make routine debugging easier: one makes route-level performance visible, and
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the other makes the requests behind it easier to reference. Live Metrics still
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isn’t a production population, so use it to reproduce and explain field
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evidence rather than as a replacement for it.
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## Start Accounting for TTFB’s Missing Time
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In [my new article on Unattributed Navigation
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Overhead](/2026/08/uno-is-underrated/), I show how to calculate the part of
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TTFB left after subtracting the redirect, DNS, connection, and
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request-to-response phases exposed by [Navigation
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Timing](https://w3c.github.io/navigation-timing/). In one client dataset, I
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found 7,131,737 UNO observations beside only 166 visible redirects. That
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doesn’t make every unexplained millisecond a hidden redirect; it shows how much
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navigation time a redirect count alone can miss.
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Add UNO to RUM as both a duration and an occurrence count, then segment it by
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landing page, campaign, referrer, browser, and connection. When it rises, use a
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[performance investigation](/performance-audits/) to reproduce representative
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journeys and identify whether redirects, browser work, cache access, or another
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gap explains it. A named remainder is not a diagnosis, but it stops missing
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time from quietly being assigned to the server.
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## Need Help Keeping Browser Releases and RUM Aligned?
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If browser releases are changing the make-up of your RUM population faster than
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the team can explain the graphs, I can help build a measurement model that
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keeps browser, instrumentation, application, and delivery changes together. We
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can check whether version cohorts are statistically useful, decide which
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release dates need annotations, and test the journeys most likely to expose a
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collection or attribution change.
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The aim is to keep faster browser delivery from turning every unexplained RUM
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movement into a product incident. If your charts are changing while your site
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isn’t, [get in touch](/contact/).
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{% include web-perf-wednesdays.md %}

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