A/B Testing CPU Requirement Calculator
Estimate the CPU cores needed to run an A/B test based on traffic, request volume, processing time, peak demand and capacity headroom.
Overview
Use this A/B Testing CPU Requirement Calculator to estimate the CPU capacity needed for experiment traffic. Enter expected daily users, requests per user, the share of traffic in the test, peak demand, CPU work per request, and your preferred utilization buffer.
How it works
The calculator converts daily user activity into an average requests-per-second rate and applies the experiment traffic share. It then multiplies this by the peak traffic factor and CPU milliseconds per request to estimate raw CPU demand. Finally, it increases capacity to stay within the target utilization and adds the selected headroom before rounding up to whole CPU cores. The per-variant figure assumes an even traffic split.
How to use this calculator
- 1Enter the expected number of daily active users.
- 2Add the average relevant requests generated by each user per day.
- 3Set the percentage of traffic assigned to the A/B test.
- 4Enter a peak traffic multiplier based on observed traffic patterns.
- 5Add measured CPU milliseconds per request and choose the number of variants.
- 6Set your target CPU utilization and extra capacity headroom, then review the recommended cores.
Example Calculation
Daily active users
100000
Requests per user per day
20
Traffic included in test
50%
Peak traffic multiplier
3
CPU time per request
15
Number of variants
2
Target CPU utilization
70%
Additional capacity headroom
25%
Recommended CPU cores
1 cores
This scenario produces about 34.7 peak test requests per second. Raw CPU demand is about 0.52 cores; after the utilization target and headroom, the calculator recommends 1 total CPU core, with at least 1 core allocated per variant where separate allocations are required.
Frequently asked questions
What CPU time per request should I use?
Use CPU time measured from representative application monitoring or load tests. It should reflect CPU processing, not total request latency, because latency can include waiting on databases or network services.
Why does the calculator use a peak traffic multiplier?
Daily averages can hide short busy periods. The multiplier increases the average request rate to reflect the higher load your service may see during peak periods.
Does running an A/B test always double CPU requirements?
No. Splitting the same total traffic between two variants does not automatically double total serving CPU. CPU demand rises when the experiment adds processing, duplicates work, reduces cache efficiency, or sends extra requests.
Should I calculate CPU capacity for each variant separately?
If variants run in isolated services, containers, or deployments, review the per-variant estimate as well as the total. A small traffic share may still require a practical minimum allocation for each deployment.
Does this include database and cache capacity?
No. The calculation focuses on application CPU used to handle requests. Plan database, cache, network, queue, and background-worker capacity separately.
How much headroom should I add?
The appropriate buffer depends on traffic volatility, autoscaling speed, deployment practices, and service criticality. Use monitoring and load-test results to select a buffer that fits your environment.
Explore Related Calculators
Assumptions and warnings
Assumptions
- Traffic is distributed evenly across variants.
- The entered CPU time per request represents CPU work rather than network, database, or other waiting time.
- Peak traffic is represented adequately by the selected peak traffic multiplier.
- The result estimates application-serving CPU capacity and excludes separate workers, databases, caches, and infrastructure overhead unless included in the CPU-time estimate.
- Capacity is rounded up to whole CPU cores after applying the utilization target and headroom.
Warnings
- This calculator provides a capacity-planning estimate only; validate it with production-like load testing and monitoring before a launch.
- Uneven traffic allocation, cache misses, slow dependencies, retries, and background jobs can increase actual CPU demand.