A/B Testing Memory Requirement Calculator Examples
Worked examples showing how A/B test traffic, tracking volume, retention, and replication affect annual storage estimates.
These examples use the calculator's binary GiB conversion and show how different experiment programs can produce very different storage needs. They are planning illustrations rather than platform capacity guarantees.
Small product experiment with short retention
A product team has 2,000 daily test visitors, records 6 events per visitor, stores 1 KB records, keeps data for 90 days, and uses two copies.
Input Summary
Daily test visitors
2,000
Variants
2
Events per visitor
6
Event size
1 KB
Retention
90 days
Replication factor
2
Calculation Breakdown
- 1Daily records2,000 × 612,000 records/day
- 2Daily raw data12,000 × 1 ÷ 1,048,5760.0114 GiB/day
- 3Annual replicated storage0.0114 × 365 × 28.35 GiB/year
- 4Peak retained storage0.0114 × 90 × 22.06 GiB
Result Summary
Peak retained storage
2.06 GiB
A/B Testing Memory Requirement Calculator
The program generates about 8.35 GiB of replicated data per year but retains about 2.06 GiB at one time under a 90-day policy.
Standard web A/B test with annual retention
A team has 10,000 daily test visitors, records 10 events per visitor, uses 2 KB records, retains data for 365 days, and stores two copies.
Input Summary
Daily test visitors
10,000
Variants
2
Events per visitor
10
Event size
2 KB
Retention
365 days
Replication factor
2
Calculation Breakdown
- 1Daily records10,000 × 10100,000 records/day
- 2Daily raw data100,000 × 2 ÷ 1,048,5760.1907 GiB/day
- 3Annual replicated storage0.1907 × 365 × 2139.24 GiB/year
- 4Visitors per variant10,000 ÷ 25,000 visitors/day
Result Summary
Visitors per variant
5,000 visitors/day
A/B Testing Memory Requirement Calculator
This setup requires an estimated 139.24 GiB of replicated storage per year and has 5,000 average daily visitors per variant.
High-traffic multivariate testing program
A platform has 250,000 daily test visitors across five variants, stores 18 events per visitor, uses 1.5 KB records, retains 180 days, and has a replication factor of 3.
Input Summary
Daily test visitors
250,000
Variants
5
Events per visitor
18
Event size
1.5 KB
Retention
180 days
Replication factor
3
Calculation Breakdown
- 1Daily records250,000 × 184,500,000 records/day
- 2Daily raw data4,500,000 × 1.5 ÷ 1,048,5766.4373 GiB/day
- 3Annual replicated storage6.4373 × 365 × 37,048.50 GiB/year
- 4Peak retained storage6.4373 × 180 × 33,476.13 GiB
- 5Visitors per variant250,000 ÷ 550,000 visitors/day
Result Summary
Visitors per variant
50,000 visitors/day
A/B Testing Memory Requirement Calculator
The estimate is 7,048.50 GiB of replicated data generated annually and 3,476.13 GiB retained at the 180-day limit.
How to Read Your Results
Daily data ingestion is the unreplicated event payload written on an average day.
Annual storage shows the volume generated over 365 days after applying replication.
Peak retained storage uses the retention window and represents the estimated maximum payload held at one time.
Visitors per variant is an even-split reference, not a prediction of actual allocation.
Add separate headroom for platform overhead, growth, indexes, backups, and operational needs.
Assumptions & Important Notes
- Examples assume daily traffic and event rates remain constant.
- Event sizes represent stored records, not necessarily network payloads.
- The calculation uses 1 GiB = 1,048,576 KB.
- Replication is modeled as a direct multiplier of stored event payload.
Related Examples
Frequently Asked Questions
Why can annual storage be larger than peak retained storage?
When retention is shorter than one year, older records leave the active retention window while new records continue to be generated.
What happens if I double events per visitor?
Daily ingestion, annual storage, and peak retained storage all double if the other inputs stay the same.
Can I use a fractional event size in KB?
Yes. A stored average event size such as 0.5 KB or 1.5 KB can be used when it reflects measured or estimated storage.
Why is traffic per variant shown separately?
It helps assess average experiment traffic allocation. It does not increase total storage when the same visitors are divided among variants.
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