Five workloads. Measured. Published.
Before placemy was a product, the engine inside it was a dissertation project. These are the five test cases from that evaluation, reproduced without rounding and without cherry-picking. Your workloads will look different — every cloud estate does — but the technique that produced these numbers is the same one running inside the CLI today.
Five real workloads, measured savings
Range 23.9%–67.4%. Median 63.6%.
| Case | Workload | Current | Before / mo | Recommendation | After / mo | Saving |
|---|---|---|---|---|---|---|
| TC-01 | Over-provisioned t3.micro (idle, 0.07% avg CPU) AWS t3.micro, eu-west-2 | AWS t3.micro eu-west-2 | $8.61 | AWS t4g.nano EU (Stockholm) | $3.14 | −63.6% |
| TC-02 | Under-provisioned B1s (22% avg, 94% peak CPU) Azure Standard_B1s, northeurope | Azure Standard_B1s northeurope | $8.25 | Azure B2pts v2 swedencentral | $6.28 | −23.9% |
| TC-03 | Idle B1s (0.4% avg CPU, 25.7% peak) Azure Standard_B1s, italynorth | Azure Standard_B1s italynorth | $8.76 | AWS t4g.nano EU (Stockholm) | $3.14 | −64.2% |
| TC-04 | Residency-constrained t3.micro (Ireland) AWS t3.micro, eu-west-1 | AWS t3.micro eu-west-1 | $8.32 | AWS t4g.micro EU (Stockholm) | $6.28 | −24.6% |
| TC-05 | Stable web B2s (13.7% avg, spiky pattern) Azure Standard_B2s, switzerlandnorth | Azure Standard_B2s switzerlandnorth | $38.54 | AWS t4g.small EU (Stockholm) | $12.56 | −67.4% |
Real workloads on real AWS and Azure accounts in EU regions, scanned with the same pipeline shipping in placemy today. Published in the 2025 MSc dissertation (L00162129). On-demand pricing; your results will vary by workload pattern.
What the numbers cover
Each test case is a real workload scanned before any placemy recommendation was applied (the “Before” column) and re-scanned after applying the highest-confidence recommendations (the “After” column). We did not apply every recommendation — only the ones the engine flagged with high confidence and low blast radius. The delta is the monthly saving, not a projection.
What the numbers don't cover
Implementation time, engineering review, regression testing. The savings figures are the ceiling of what the placemy engine surfaces — the floor depends on how your team chooses to act on the report. We think that's the honest way to talk about it.
Peer-reviewed methodology
The multi-cloud right-sizing methodology behind these results is being presented as an IEEE paper at the 2026 IEEE International Conference in Bristol, UK (September 2026). The paper covers the P95-based sizing algorithm, cross-cloud candidate filtering, and the evaluation methodology used to produce the figures above.