Carbon
What it costs the planet to ship a feature here, measured for every request that went live, using the Software Carbon Intensity method (ISO/IEC 21031:2024).
"g CO₂e" means grams of carbon dioxide equivalent: one unit that puts different greenhouse gases on the same scale as CO₂. Shipyard measures it to show what shipping each feature costs the planet.
Per shipped feature, average of 15
13.1 g CO₂e
Up to 112.0 g if AI model calls cost ten times our estimate. About 22 minutes of CI and 79 model calls each.
-
CI runners
1.88 g, 14% -
AI model calls
10.99 g, 84% -
Hardware
0.26 g, 2%
What the design avoided
Routing decisions made in plain code, not by an AI model
360
About 50.1 g CO₂e avoided across these features.
Requests declined at triage, before any code was written
11
About 125.0 g CO₂e avoided: each one cost a triage run instead of the full build.
Every launched feature
Serving a page
Every visit has a cost too. The pipeline measures what each page transfers on every release and applies the Sustainable Web Design Model v4: 122 g CO₂e per GB.
| Page | First visit | Repeat visit | mg CO₂e, first visit |
|---|---|---|---|
| / | 15.0 kB | 4.0 kB | 1.82 |
| /roadmap | 16.1 kB | 5.2 kB | 1.96 |
| /changelog | 13.1 kB | 2.2 kB | 1.60 |
| /carbon | 14.9 kB | 3.9 kB | 1.81 |
| /incidents | 13.1 kB | 2.2 kB | 1.60 |
| /requests/1 | 13.6 kB | 2.6 kB | 1.65 |
The live roadmap checks for changes every 20 seconds. When nothing changed, the answer is an empty "not modified" reply; when something did, 3.5 kB, so an hour of watching costs at most about 76 mg CO₂e. Pages are compressed, styles and scripts are cached for a year, and the pipeline fails any change that makes a first visit heavier than 50 kB, so agents can't quietly bloat the site.
How it's measured
SCI = (E × I + M) per R
- R, the unit
- One feature request that reached production.
- E, energy
- Runner time of every pipeline the feature caused, read from GitLab: agent runs, merge request pipelines and the pipeline that deployed it. Each runner has 2 vCPUs and 8 GB, drawing 8.92 W at 50% utilisation, including a PUE of 1.1. AI model calls are estimated at one per 5 seconds of agent run time, 0.24 Wh each.
- I, grid intensity
- 579.44 g CO₂e per kWh, location-based, for Google Cloud us-east1 where GitLab's runners run. The same value is assumed for model inference, whose location isn't published.
- M, embodied emissions
- The runner's share of the server's manufacturing footprint: 1200 kg CO₂e per 96-vCPU server over a 4-year life.
- Outside the boundary
- Serving visitors, because it grows with traffic, not with shipping. It's measured separately, per page view, above.
- Serving, per page view
- Sustainable Web Design Model v4: bytes transferred × energy per GB for data centres, networks and devices, operational and embodied. The data-centre share uses Montréal's grid (11 g CO₂e per kWh), where the site runs; networks, devices and all embodied energy use the global average (494 g).
The weakest number is the AI model energy: GitLab doesn't report it per run, so it is estimated and shown with a ten-times upper bound. Everything else is measured.
Sources
- SCI specification (Green Software Foundation, ISO/IEC 21031:2024)
- Cloud Carbon Footprint methodology
- Cloud Carbon Footprint embodied emissions
- Google Cloud region carbon data
- GitLab-hosted Linux runners
- Google: measuring the environmental impact of AI inference (Aug 2025)
- Sustainable Web Design Model, version 4