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A/B Testing CPU Requirement Calculator Examples

Worked A/B test CPU sizing examples for small launches, high-traffic experiments, multi-variant tests, and conservative capacity planning.

These examples show how traffic share, peaks, CPU work per request, utilization limits, and headroom change an A/B test CPU estimate. They are planning illustrations rather than production capacity guarantees.

1

Small feature experiment with two variants

A product team exposes a new interface to 25% of traffic while control and treatment are deployed separately.

Input Summary

Daily active users

20,000 users

Requests per user per day

12 requests

Traffic included in test

25%

Peak traffic multiplier

CPU time per request

10 CPU ms

Variants

2

Target CPU utilization

70%

Headroom

25%

Calculation Breakdown

  1. 1Average application rate20000 × 12 ÷ 864002.78 requests/sec
  2. 2Peak test rate2.78 × 0.25 × 21.39 requests/sec
  3. 3Raw CPU demand1.39 × 10 ÷ 10000.014 cores
  4. 4Recommended capacityceil((0.014 ÷ 0.70) × 1.25)1 total core

Result Summary

Recommended capacity

1 total core

A/B Testing CPU Requirement Calculator

The formula recommends 1 total CPU core. Separately deployed control and treatment versions may each need a practical minimum allocation.

2

Half-traffic experiment on a busy application

An application places 50% of its traffic into an experiment during a period when the relevant request rate reaches four times the daily average.

Input Summary

Daily active users

500,000 users

Requests per user per day

30 requests

Traffic included in test

50%

Peak traffic multiplier

CPU time per request

18 CPU ms

Variants

2

Target CPU utilization

70%

Headroom

25%

Calculation Breakdown

  1. 1Average application rate500000 × 30 ÷ 86400173.61 requests/sec
  2. 2Peak test rate173.61 × 0.50 × 4347.22 requests/sec
  3. 3Raw CPU demand347.22 × 18 ÷ 10006.25 cores
  4. 4Recommended capacityceil((6.25 ÷ 0.70) × 1.25)12 total cores
  5. 5Even-split variant estimateceil(12 ÷ 2)6 cores per variant

Result Summary

Even-split variant estimate

6 cores per variant

A/B Testing CPU Requirement Calculator

The experiment requires an estimated 12 total CPU cores, or about 6 cores per evenly split variant.

3

Four-variant experiment with uneven operational risk

A team tests four recommendation approaches across 80% of traffic and wants extra capacity for traffic variability and deployment overlap.

Input Summary

Daily active users

1,000,000 users

Requests per user per day

25 requests

Traffic included in test

80%

Peak traffic multiplier

CPU time per request

12 CPU ms

Variants

4

Target CPU utilization

60%

Headroom

50%

Calculation Breakdown

  1. 1Average application rate1000000 × 25 ÷ 86400289.35 requests/sec
  2. 2Peak test rate289.35 × 0.80 × 3694.44 requests/sec
  3. 3Raw CPU demand694.44 × 12 ÷ 10008.33 cores
  4. 4Capacity before headroom8.33 ÷ 0.6013.89 cores
  5. 5Recommended capacityceil(13.89 × 1.50)21 total cores
  6. 6Even-split variant estimateceil(21 ÷ 4)6 cores per variant

Result Summary

Even-split variant estimate

6 cores per variant

A/B Testing CPU Requirement Calculator

The result is 21 total CPU cores, with an approximate 6-core allocation for each separately deployed variant.

4

Low test share with CPU-heavy requests

A service tests a CPU-intensive personalization routine on 10% of traffic, using a high peak multiplier from observed campaign periods.

Input Summary

Daily active users

150,000 users

Requests per user per day

16 requests

Traffic included in test

10%

Peak traffic multiplier

CPU time per request

80 CPU ms

Variants

2

Target CPU utilization

75%

Headroom

20%

Calculation Breakdown

  1. 1Average application rate150000 × 16 ÷ 8640027.78 requests/sec
  2. 2Peak test rate27.78 × 0.10 × 513.89 requests/sec
  3. 3Raw CPU demand13.89 × 80 ÷ 10001.11 cores
  4. 4Recommended capacityceil((1.11 ÷ 0.75) × 1.20)2 total cores

Result Summary

Recommended capacity

2 total cores

A/B Testing CPU Requirement Calculator

The calculator estimates 2 total CPU cores for the experiment traffic.

How to Read Your Results

Peak test request rate is the estimated busy-period rate handled by the experiment, not the average rate across the full day.

Raw peak CPU demand represents the core demand before applying a utilization target or extra capacity buffer.

Recommended total cores is a planning estimate for experiment-serving application CPU capacity after the selected adjustments.

Estimated cores per variant assumes an even traffic split and is most relevant when variants have separate CPU allocations.

If measured CPU time differs by variant, calculate each variant separately instead of relying on an even split.

Assumptions & Important Notes

  • Examples treat CPU time per request as CPU processing work and exclude most external waiting time.
  • All variants are assumed to receive equal traffic and have similar CPU cost unless the scenario states otherwise.
  • Request rates are treated as evenly distributed within the estimated peak period.
  • Results use whole-core rounding and do not include capacity for separate infrastructure components.

Related Examples

Frequently Asked Questions

Why can a small A/B test still show a one-core requirement?

The formula rounds the final capacity up to a whole core. Separate containers or services may also have minimum CPU allocations regardless of calculated load.

Can I use different CPU times for control and treatment?

Yes. When variants have materially different CPU costs, estimate their peak traffic and CPU demand separately, then assess the combined and individual allocations.

What happens if I increase test traffic from 25% to 50%?

With other inputs unchanged, the experiment request rate and raw CPU demand double. The rounded final result may not double exactly.

Does more headroom always produce more cores?

It increases the unrounded capacity estimate. Whether the displayed whole-core result changes depends on where the estimate falls relative to the next whole core.

Should I use average or peak CPU time per request?

Use a representative measured CPU time for the workload expected at peak, and test sensitivity if CPU time changes with payload, cache behavior, or feature usage.

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