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Cloudflare vs Akamai

Side-by-side uptime and reliability comparison based on real monitoring data.

Cloudflare
Partial Outage
Akamai
Operational
FeatureCloudflareAkamai
Current StatusPartial OutageOperational
24-Hour Uptime100.00%—
7-Day Uptime100.00%—
30-Day Uptime100.00%—
90-Day Uptime100.00%—
Recent Incidents (total)10029
Active Incidents50
Avg. Resolution Time15h 40m55h 36m
Tracked Components47342

Cloudflare vs Akamai: Uptime and Reliability Analysis

When evaluating cdn services for your stack, uptime and reliability are critical factors. Both Cloudflare and Akamai are widely used in the cdn space, but how do they compare on actual measured reliability?

Based on DevHelm's continuous monitoring of their official status pages, Cloudflare currently reports a 30-day uptime of 100.00% while Akamai reports —. Uptime data may not be available for all periods.

Incident Frequency

Over the recent monitoring window, Cloudflare has logged 100 incidents while Akamai has recorded 29 incidents. Fewer incidents generally indicates more stable infrastructure, though the severity and duration of each incident matter as much as the raw count.

Mean Time to Resolution

Cloudflare resolves incidents in an average of 15h 40m. Akamai averages 55h 36m per incident. Lower resolution times mean less disruption to your application and users.

Component Coverage

Cloudflare exposes 473 trackable components on their status page, compared to 42 for Akamai. More components means more granular visibility into which parts of the service are affected during an outage. This is especially useful for targeted alerting and incident response.

Which Should You Choose?

Both Cloudflare and Akamai are production-grade cdn services used by thousands of companies. Your choice should factor in reliability alongside features, pricing, and ecosystem fit. DevHelm tracks both services continuously — add them to your workspace to receive real-time alerts when either experiences issues.

Methodology

DevHelm monitors the official status pages of both services and computes uptime from their self-reported component status data. Uptime percentages reflect the proportion of time all components reported operational status. Incident counts and resolution times come from vendor-published incident timelines. This comparison uses the same data source and methodology for both services to ensure a fair comparison. Data is refreshed every few minutes and aggregated daily.

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