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RealUptime Outages vs Downdetector

Downdetector is the household name for is-it-down: crowdsourced problem reports at a scale nobody else matches, run by Ookla under Ziff Davis, with a sale of the Ookla group to Accenture announced in March 2026. Its outage signal is built from user reports; we found no indication it probes the services it tracks. RealUptime Outages starts from the opposite end: every service in our catalog is actively measured by our own probes, user reports are shown separately from measurements rather than blended in, and the full detection method is published.

The short version

Downdetector tells you what people are reporting; RealUptime Outages tells you what our probes actually measured, and shows both separately.

Downdetector's scale is real and worth respecting: over a decade of crowd reports across dozens of countries is not something we claim to match. But its signal is, at bottom, a sentiment estimate: user complaints, which skew loud and consumer-shaped. An API that only machines call can be down for an hour before a human files a report. RealUptime Outages measures: every service in the catalog is probed by us directly, per-region readings are shown next to the user reports rather than blended into one number, and the method that turns both into an outage call is published in full. If you want the biggest crowd, Downdetector has it. If you want to see how the answer was reached, that is the product we built.

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Verified August 24, 2026. Sources: Accenture: agreement to acquire Ookla (Speedtest, Downdetector), Wikipedia: Downdetector, RealUptime Outages methodology.

Crowdsourced outage reports

Have

one-tap reports on every tracked service, shown separately from measurements

Have

the category leader by reach; its data is built from user outage reports collected on its own pages and social media, per its Wikipedia-documented self-description

Independent probing of every tracked service

Have

our own probes measure every catalog service from four regions on a 60-second-to-30-minute cadence by service popularity, so a quiet outage still gets caught

Not published

no first-party probing or synthetic measurement is described in any Downdetector or Ookla material we could find

Per-region measured readings

Have

each outage page shows what every probe region measured, not just a report heatmap

Partial

a map of where reports come from, which reflects where people are complaining rather than where the service is failing

Published detection methodology

Have

the full method, thresholds included, is public at /outages/methodology

Not published

we could not locate a Downdetector-authored methodology page with published thresholds

Service coverage breadth

Partial

a curated catalog, every entry actively probed; far narrower than Downdetector today

Have

roughly 12,000 services across 45 countries, per Wikipedia's account of its own claims

Free for readers, without ads

Have

no ads, no trackers, no paywall on outage pages

Partial

free to read and ad-supported, with a paid enterprise product (Downdetector Explorer) alongside

Looking for a Downdetector alternative?

For the reasoning behind checking from more than one region at all, see why a status page can show all green during a real outage. Comparing more than just this one alternative? The status page tool checklist covers what to test before committing to any of them.

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