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omrdev1 merged 2 commits into from
Mar 28, 2026
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feat: v0.5.0 — multi-cloud support (AWS + Azure + GCP) #11

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feat: v0.5.0 — multi-cloud support (AWS + Azure + GCP)
omrdev1 Mar 28, 2026
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feat: v0.5.0 — multi-cloud support (AWS + Azure + GCP)
omrdev1 Mar 28, 2026
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1 change: 1 addition & 0 deletions .gitignore
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Expand Up @@ -16,6 +16,7 @@ tfplan*.json
# Ad-hoc & Demo Files
launch_*.md
research.*.md
upgrade_*.py
*.log

# OS generated files
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181 changes: 113 additions & 68 deletions METHODOLOGY.md
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@@ -1,18 +1,30 @@
# GreenOps Methodology Ledger v1.3.0
# GreenOps Methodology Ledger v2.0.0

**Methodology transparency is the only defence against greenwashing.**

All maths in GreenOps is open, auditable, and reproducible from `factors.json`. This document defines the exact formulas, assumptions, and data sources used in every calculation.

---

## Cloud Provider Coverage

| Provider | Regions | Instances | Status |
|---|---|---|---|
| AWS | 14 | 40 | ✅ Full coverage |
| Azure | 17 | 16 | ✅ Full coverage |
| GCP | 15 | 15 | ✅ Full coverage |

Run `greenops-cli --coverage` to see the full instance and region list per provider.

---

## Emission Scopes Covered

| Scope | What it measures | GreenOps status |
|---|---|---|
| Scope 2 — Operational | CPU power draw × grid carbon intensity | ✅ Tracked |
| Scope 3 — Embodied | Hardware manufacturing lifecycle | ✅ Tracked (v1.3.0) |
| Water consumption | Data centre cooling water withdrawal | ✅ Tracked (v1.3.0) |
| Scope 3 — Embodied | Hardware manufacturing lifecycle | ✅ Tracked |
| Water consumption | Data centre cooling water withdrawal | ✅ Tracked |
| Scope 3 — Supply chain | Software, logistics, employee travel | ❌ Out of scope |
| Scope 1 — Direct | On-site combustion | ❌ Not applicable (cloud) |

Expand Down Expand Up @@ -40,18 +52,33 @@ energy_kwh = W_effective × PUE × hours_per_month / 1000
co2e_grams = energy_kwh × grid_intensity_gco2e_per_kwh
```

Where:
- `PUE` = Power Usage Effectiveness (1.13 for AWS, from AWS sustainability reports)
- `hours_per_month` = 730 (365 days × 24h / 12 months)
- `grid_intensity_gco2e_per_kwh` = regional annual average from Electricity Maps 2024
### PUE by Provider

| Provider | PUE | Source |
|---|---|---|
| AWS | 1.13 | AWS sustainability reports |
| Azure | 1.125 | Microsoft sustainability reports |
| GCP | 1.10 | Google sustainability reports |

GCP's 1.10 PUE is the best in class among the three major providers, producing ~3% less overhead energy per unit of compute.

### Worked Example — m5.large in us-east-1 at 50% utilisation
### Worked Example — AWS m5.large in us-east-1 at 50% utilisation

1. **Power:** `W = 6.8 + (20.4 - 6.8) × 0.50 = 13.6W`
2. **Energy:** `13.6W × 1.13 PUE × 730h / 1000 = 11.219 kWh/month`
3. **Carbon:** `11.219 × 384.5 = 4,313.6g CO2e/month = 4.31kg CO2e/month`
3. **Carbon:** `11.219 × 384.5 = 4,313.6g CO2e/month`

This is the exact value asserted in `engine.test.ts`.
### Worked Example — Azure Standard_D2s_v3 in eastus at 50% utilisation

1. **Power:** `W = 6.8 + (20.4 - 6.8) × 0.50 = 13.6W`
2. **Energy:** `13.6W × 1.125 PUE × 730h / 1000 = 11.178 kWh/month`
3. **Carbon:** `11.178 × 380.0 = 4,244.2g CO2e/month`

### Worked Example — GCP n2-standard-2 in us-central1 at 50% utilisation

1. **Power:** `W = 6.8 + (20.4 - 6.8) × 0.50 = 13.6W`
2. **Energy:** `13.6W × 1.10 PUE × 730h / 1000 = 10.921 kWh/month`
3. **Carbon:** `10.921 × 340.0 = 3,713.1g CO2e/month`

---

Expand All @@ -73,116 +100,134 @@ embodied_gco2e_per_month = (server_total_embodied_gco2e / lifespan_hours / vcpus
| Server total embodied CO2e | 1,200,000 gCO2e | CCF DELL R740 baseline |
| Server lifespan | 4 years = 35,040 hours | AWS/CCF assumption |
| vCPUs per physical server | 48 | Dual-socket Xeon baseline |
| ARM architecture discount | 0.80 (20% lower) | Graviton smaller die + lower TDP |
| ARM architecture discount | 0.80 (20% lower) | Graviton/Ampere smaller die + lower TDP |

### Per-vCPU rate
### Per-vCPU rates

```
x86_64: (1,200,000 / 35,040 / 48) × 730 = 520.8g CO2e/vCPU/month
arm64: 520.8 × 0.80 = 416.7g CO2e/vCPU/month
```

### Worked Example — m5.large (2 vCPU, x86_64)

```
embodied = 2 × 520.8 = 1,041.7g CO2e/month
```

### Worked Example — m6g.large (2 vCPU, ARM64)

```
embodied = 2 × 416.7 = 833.3g CO2e/month
```

ARM64 saves 208.4g CO2e/month in embodied carbon alone — before any operational savings.
The ARM discount applies equally to AWS Graviton, Azure Ampere (Dps-series), and GCP T2A instances — all use Arm Neoverse cores with comparable manufacturing profiles.

---

## Water Consumption

Water is consumed by data centre cooling systems. GreenOps uses AWS's published **WUE (Water Usage Effectiveness)** metric, defined as litres of water withdrawn per kWh of IT load.

### Formula

```
energy_kwh_IT = W_effective × hours / 1000 (IT load, before PUE)
water_litres = energy_kwh_IT × WUE_litres_per_kwh
```

Note: WUE is applied to IT load (before PUE multiplication), matching the AWS definition.
WUE is applied to IT load (before PUE multiplication), matching the AWS/Azure/Google definition.

### Worked Example — m5.large in us-east-1
### Regional WUE Values

```
energy_IT = 13.6W × 730h / 1000 = 9.928 kWh/month
water = 9.928 × 0.46 = 4.57 litres/month
```
#### AWS regions

### Regional WUE Values
| Region | Location | WUE (L/kWh) |
|---|---|---|
| us-east-1 | N. Virginia | 0.46 |
| us-east-2 | Ohio | 0.52 |
| us-west-1 | N. California | 0.38 |
| us-west-2 | Oregon | 0.18 |
| eu-west-1 | Ireland | 0.22 |
| eu-west-2 | London | 0.25 |
| eu-central-1 | Frankfurt | 0.28 |
| eu-north-1 | Stockholm | **0.10** |
| ap-southeast-1 | Singapore | 0.58 |
| ap-southeast-2 | Sydney | 0.45 |
| ap-northeast-1 | Tokyo | 0.50 |
| ap-south-1 | Mumbai | 0.72 |
| ca-central-1 | Canada | 0.20 |
| sa-east-1 | São Paulo | 0.35 |

#### Azure regions

| Region | Location | WUE (L/kWh) |
|---|---|---|
| swedencentral | Sweden Central | **0.10** |
| westus2 | West US 2 | 0.18 |
| northeurope | Ireland | 0.22 |
| canadacentral | Canada Central | 0.20 |
| westeurope | Netherlands | 0.20 |
| uksouth | London | 0.25 |

| Region | Location | WUE (L/kWh) | Source |
|---|---|---|---|
| us-east-1 | N. Virginia | 0.46 | AWS 2023 Sustainability Report |
| us-east-2 | Ohio | 0.52 | AWS 2023 Sustainability Report |
| us-west-1 | N. California | 0.38 | AWS 2023 Sustainability Report |
| us-west-2 | Oregon | 0.18 | AWS 2023 Sustainability Report |
| eu-west-1 | Ireland | 0.22 | AWS 2023 Sustainability Report |
| eu-west-2 | London | 0.25 | AWS 2023 Sustainability Report |
| eu-central-1 | Frankfurt | 0.28 | AWS 2023 Sustainability Report |
| eu-north-1 | Stockholm | 0.10 | AWS 2023 Sustainability Report |
| ap-southeast-1 | Singapore | 0.58 | AWS 2023 Sustainability Report |
| ap-southeast-2 | Sydney | 0.45 | AWS 2023 Sustainability Report |
| ap-northeast-1 | Tokyo | 0.50 | AWS 2023 Sustainability Report |
| ap-south-1 | Mumbai | 0.72 | AWS 2023 Sustainability Report |
| ca-central-1 | Canada | 0.20 | AWS 2023 Sustainability Report |
| sa-east-1 | São Paulo | 0.35 | AWS 2023 Sustainability Report |

`eu-north-1` (Stockholm) has both the lowest grid carbon intensity (8.8 gCO2e/kWh) and the lowest WUE (0.10 L/kWh) of any supported region, making it the optimal target for both climate impact dimensions.
#### GCP regions

| Region | Location | WUE (L/kWh) |
|---|---|---|
| europe-north1 | Finland | **0.12** |
| northamerica-northeast1 | Montreal | 0.20 |
| us-west1 | Oregon | 0.18 |

Source: AWS 2023 Sustainability Report, Microsoft 2023 Environmental Sustainability Report, Google 2023 Environmental Report.

---

## Recommendation Engine

GreenOps evaluates two strategies per resource and selects the highest-scoring option:

**Strategy 1 — ARM upgrade:** Switch x86_64 → ARM64 (same vCPU/RAM class). Only recommended if both CO2e and cost decrease.
**Strategy 1 — ARM upgrade:** Switch x86_64 → ARM64 (same vCPU/RAM class). Only recommended if both CO2e and cost decrease. Supported across all three providers.

**Strategy 2 — Region shift:** Move to the lowest grid-intensity region that has pricing data for this instance. Only recommended if CO2e reduction exceeds 15% of baseline.
**Strategy 2 — Region shift:** Move to the lowest grid-intensity region within the same provider that has pricing data for this instance. Only recommended if CO2e reduction exceeds 15% of baseline.

**Scoring (when both strategies qualify):**
**Scoring:**

```
score = (|co2e_delta| / baseline_co2e) × 0.60
+ (|cost_delta| / baseline_cost) × 0.40
```

Carbon reduction is weighted at 60%, cost at 40%, both normalised to percentage-of-baseline for fair comparison across instance sizes.
Carbon reduction is weighted at 60%, cost at 40%, both normalised to percentage-of-baseline.

### ARM Upgrade Maps

| AWS (x86 → ARM64) | Azure (x86 → ARM64) | GCP (x86 → ARM64) |
|---|---|---|
| t3/t3a → t4g | Standard_D2s_v3 → Standard_D2ps_v5 | n2 → t2a |
| m5/m5a → m6g | Standard_D4s_v3 → Standard_D4ps_v5 | n2d → t2a |
| c5/c5a → c6g | Standard_D8s_v3 → Standard_D8ps_v5 | e2 → t2a |
| r5/r5a → r6g | Standard_D2s_v4 → Standard_D2ps_v5 | | |

---

## Data Sources

| Data | Source | Version |
|---|---|---|
| Instance TDP (idle/max watts) | Cloud Carbon Footprint hardware coefficients | v3 |
| AWS instance TDP | Cloud Carbon Footprint hardware coefficients | v3 |
| Azure instance TDP | Cloud Carbon Footprint Azure coefficients | v3 |
| GCP instance TDP | Cloud Carbon Footprint GCP coefficients | v3 |
| Embodied carbon per server | CCF DELL R740 baseline | v3 |
| Grid carbon intensity | Electricity Maps annual averages | 2024 |
| PUE | AWS sustainability reports | 2023 |
| WUE | AWS sustainability reports | 2023 |
| On-demand pricing | AWS public pricing API | Q1 2026 |
| AWS grid carbon intensity | Electricity Maps annual averages | 2024 |
| Azure grid carbon intensity | Electricity Maps annual averages | 2024 |
| GCP grid carbon intensity | Electricity Maps annual averages | 2024 |
| AWS PUE | AWS sustainability reports | 2023 |
| Azure PUE | Microsoft sustainability reports | 2023 |
| GCP PUE | Google sustainability reports | 2023 |
| AWS WUE | AWS 2023 Sustainability Report | 2023 |
| Azure WUE | Microsoft 2023 Environmental Sustainability Report | 2023 |
| GCP WUE | Google 2023 Environmental Report | 2023 |
| AWS pricing | AWS public pricing API | Q1 2026 |
| Azure pricing | Azure public pricing API | Q1 2026 |
| GCP pricing | GCP public pricing API | Q1 2026 |

---

## Known Limitations

- **CPU-only power model.** Memory power draw is tracked in `factors.json` (`memory_gb`) but not yet included in calculations. This is a known underestimate, consistent with the CCF baseline approach.
- **Scope 2 only for region recommendations.** The recommendation engine uses Scope 2 operational emissions for scoring. Embodied carbon does not change when shifting regions, so it is correctly excluded from the region-shift calculation.
- **CPU-only power model.** Memory power draw is tracked in `factors.json` (`memory_gb`) but not yet included in calculations.
- **Scope 2 only for region recommendations.** Embodied carbon does not change when shifting regions, so it is correctly excluded from the region-shift scoring.
- **Annual average grid intensity.** Real-time marginal emissions are not used. Annual averages are more stable and reproducible, consistent with CCF methodology.
- **WUE at data centre level.** Water figures cover direct data centre cooling withdrawal only — not supply chain water or water embedded in hardware manufacturing.
- **Provider alias regions.** Terraform configurations using aliased providers (e.g. `provider "aws" { alias = "secondary" }`) may not resolve correctly. Standard single-provider configs are fully supported.
- **WUE at data centre level.** Water figures cover direct data centre cooling withdrawal only.
- **Azure and GCP coverage is initial.** AWS has 40 instance types; Azure and GCP each have 15–16. Enterprise-scale instance families (M-series, X-series, A2 High Memory) are not yet in the ledger.
- **Provider alias regions.** Multi-aliased provider configs may not resolve correctly. Standard single-provider configs are fully supported.

---

## Licence

The methodology, coefficients, and source code are MIT-licensed. The maths are fully reproducible: every assertion in `engine.test.ts` includes a commented math trace derivable from this document and `factors.json`.
The methodology, coefficients, and source code are MIT-licensed. Every assertion in `engine.test.ts` includes a commented math trace derivable from this document and `factors.json`.
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