A/B Testing Uptime Per-User Calculator FAQ
Answers to common questions about A/B test uptime, expected per-user downtime, traffic weighting, lost user-hours, and result limits.
Use this FAQ to understand the calculator's inputs, output meanings, formula assumptions, and practical limits. Results are availability estimates and should be considered alongside observed reliability and experiment data.
General A/B Test Uptime Questions
Core definitions for variant availability and user exposure.
What does the A/B Testing Uptime Per-User Calculator estimate?
It estimates traffic-weighted uptime, expected downtime per user, the uptime difference between variants, and total lost user-hours during a test.
What is per-user uptime?
Per-user uptime is the availability a typical user is expected to experience based on the variant assignment and the experiment traffic split.
What is the difference between uptime and downtime?
Uptime is the percentage of time a service is available. Downtime is the remaining percentage converted into hours over the selected test period.
Can both variants have the same uptime?
Yes. When uptime is the same for both variants, the traffic split does not change the weighted uptime or average downtime result.
Inputs and Formula Questions
How calculator inputs are used in the calculation.
How is the traffic split used?
The Variant A allocation is converted to a decimal share. Variant B receives the remainder, and both shares weight their respective uptime and downtime values.
Why is test duration entered in days?
The calculator converts days to hours so it can estimate unavailable hours per user during the test.
How is expected downtime per user calculated?
It calculates downtime for each variant from its uptime and the test hours, then takes a traffic-weighted average of those downtime values.
How is the uptime difference calculated?
The calculator subtracts Variant A uptime from Variant B uptime. The output is shown in percentage points.
How are total lost user-hours calculated?
Total lost user-hours equal expected downtime per user multiplied by the total number of test users.
Understanding Results
How to interpret the availability outputs without overstating what they measure.
What does a negative B versus A difference mean?
A negative result means Variant B has lower uptime than Variant A by the displayed number of percentage points.
Does a high weighted uptime mean every user has that uptime?
No. It is an average across the allocated population. Users assigned to each variant are estimated using that variant's own uptime.
Are lost user-hours the same as affected users?
No. Lost user-hours combine time across users. One user with two unavailable hours and two users with one unavailable hour each both equal two lost user-hours.
Why can total lost user-hours rise while average uptime stays unchanged?
Increasing the test duration or total users increases aggregate exposure even when the uptime percentages and traffic split do not change.
Accuracy and Limitations
Important assumptions that may cause observed results to differ from the estimate.
Does the calculator predict real incidents?
No. It applies entered uptime percentages to the planned test period; it does not predict when or whether incidents will occur.
Does it account for partial outages or error severity?
No. The calculation treats unavailable time as a single availability measure and does not model severity, affected workflows, or recovery quality.
Does it account for regional or device-specific reliability?
No. It uses one uptime input per variant. Separate estimates may be useful when reliability differs by region, platform, or user segment.
Should uptime be the only reliability metric used for an A/B test?
No. Availability can be reviewed alongside observed error rates, latency, completion of key flows, support signals, and experiment outcomes.
How is average uptime in an A/B test calculated?
Average uptime is the weighted sum of Variant A and Variant B uptime, using each variant's share of test traffic.
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