I've been running some numbers against our actual resource usage. The new GCP carbon reporting seems to be a thin wrapper over their existing billing data, applying a generic grid carbon intensity factor per region. This lacks the granularity needed for true accountability.
Key issues I see:
* **Instance-level granularity is missing.** It reports at the project level, not per VM, database, or storage bucket. How do I isolate the carbon cost of my stateful vs. stateless services?
* **No embodied carbon for hardware.** The model appears to only account for operational energy. Manufacturing footprint of the underlying infrastructure is excluded.
* **The "carbon-free energy" percentage is a region average, not your actual mix.** Your footprint is calculated as `(Total Energy) * (Grid CO2e/kWh) * (1 - CFE%)`. You're assigned the grid average, not the specific mix for your VM's host.
Example: My `us-central1` project shows 50% CFE. That's GCP's *regional* target, not the actual energy source for my specific `n2-standard-64` instances.
Until they provide:
* Real-time, per-resource carbon estimates
* Embodied carbon metrics
* Actual, not averaged, energy source attribution
This is more of a high-level awareness dashboard than an engineering tool for optimization. It's a start, but not actionable data.
Oh wow. The billing data point is something I hadn't considered. That makes sense.
If it's just a formula slapped on the billing export, that's barely a starting point. You're right, how are we supposed to optimize anything if we can't see which specific VM is the real problem? We'd just be guessing.
So is it even useful for internal tracking, or is it purely for PR?
Whoa, that's super detailed. So it's basically a high-level estimate, not an actual measurement? That makes the "optimization" part feel impossible.
> Instance-level granularity is missing
This part really hits. If we can't see which specific VM or database is the problem, how are we supposed to act on the data? It's just a number with no drill-down.
I guess the question is, what's the minimum granularity that would make this actually useful for engineers? Per-service? Per-deployment?
Absolutely spot on about the billing data wrapper. I've been poking at the API, and you can literally map the carbon data points back to the SKUs in your Cloud Billing export with a simple multiplier. It's just an extra column.
That lack of per-resource granularity makes it useless for pipeline optimization. My team wanted to add a carbon cost check to our deployment gate - kill the pipeline if a new VM spec pushes the service over a threshold. Can't do it. We get a project-level number a day later.
The CFE average is the real killer though. It means moving a workload to a "100% CFE" region like Iowa might not change your actual footprint at all, just the reported one. Makes any green architecture decisions feel like guesswork.
pipeline all the things