GreenOps is the practice of applying sustainability metrics to your IT trade-off decisions. It puts energy, carbon and water next to cost and performance every time your teams choose an instance, a region or an AI model, so cloud and AI get more efficient without slowing anyone down.
GreenOps brings sustainability into the decisions that engineering, DevOps, FinOps and sustainability teams already make about cloud computing and AI. Teams see the energy consumption, carbon emissions and water use of each workload at the same level of detail as its cloud costs, rather than in a yearly report nobody can act on.
The aim is more value from the cloud resources you run and less waste. Many businesses find the same changes also improve efficiency and performance.
To learn how to put GreenOps into practice, take a course with the GreenOps Academy.
GreenOps unleashes new business opportunities for cloud vendors, not only to reduce users’ cloud waste and emissions, but also to generate revenue as businesses are more willing to purchase and extend their contracts from green brands. In this context, Greenpixie plays a key role in the GreenOps space for its capability to generate granular data through accurate carbon algorithms while embedding FinOps and delivering business value.
Filippo VanaraSenior Research Analyst, IDC European CloudOpsFinOps manages the cost of cloud and GreenOps manages its environmental impact. FinOps and GreenOps overlap more than they differ: most cloud waste costs money and produces emissions, so removing it helps both.
GreenOps follows the same Inform, Optimise and Operate phases as the FinOps Framework, and the FinOps Foundation includes sustainability as a capability in that framework. Teams that already practise FinOps start fastest, because the billing data and tagging are in place. Ownership usually sits with FinOps, DevOps, IT sustainability or cloud engineering, often working together as one GreenOps team.
Carbon data adds a second reason to act. It helps engineering and leadership approve optimisations that cost savings alone haven’t pushed through, and gives sustainability teams numbers they can defend in an audit.
That is up from 27% and the first rise in five years, driven mainly by AI workloads.
Source: Flexera, State of the Cloud 2026
Enterprises across industries with large public cloud estates produce enough carbon emissions to matter in reporting and audit.
For companies buying cloud services, cloud emissions sit in Scope 3, usually under Category 1 (purchased goods and services) of the GHG Protocol. European regulation, customer requests and audits all need methodology that holds up, and spend-based estimates that can’t be checked risk accusations of greenwashing.
In the environments we see, AI inference volume is doubling in some cases. Without guardrails, that growth pushes cloud carbon past the targets an organisation has already committed to. Read our guide to AI energy consumption.
Sustainable IT, sometimes called green IT, covers the carbon footprint of all technology, from laptops to data centres. GreenOps is the cloud and AI part: the fastest-growing, and the hardest to measure.
A cloud bill has millions of line items, and the carbon tools from AWS, Azure and Google Cloud each report monthly figures with their own method. Here is how they compare with Greenpixie data.
Swipe to compare →
Cloud provider tools |  | |
|---|---|---|
| Granularity | Monthly, by service and region | Every line item, by SKU, region and workload |
| Methodology | Each provider uses its own method, so results don’t compare | One published method across all three, ISO 14064-3 verified for cloud |
| Coverage | One provider | AWS, Azure, GCP and 500+ AI models |
| Metrics | Carbon (with water on AWS only) | Energy, water and Scope 1, 2 and 3 carbon on every provider |
| Independence | Run by the provider being measured | Independent |
Mastercard got these results by adding Greenpixie data to work its teams were already doing.
Mastercard's cloud cost optimisations had stalled. Cost alone wasn't enough to get engineering teams to act.
Greenpixie adds energy, carbon and water data to Mastercard's AWS and Azure billing data and FinOps recommendations, so every saving now shows its carbon impact too. That gave teams a second reason to act.
Greenpixie data enabled $2M in cloud cost reductions, and Mastercard exceeded its cloud carbon reduction target.
Interested in exploring what GreenOps can do for you?
Book a callGreenpixie adds energy, carbon and water figures to every line of your cloud bill and every AI model call, so teams can analyse cloud usage across their cloud infrastructure in the same detail as cost, and act on the insights.
See the energy, carbon and water behind your cloud and AI. Get started for free in the app, or book a call with our team.