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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.09645 |
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| _version_ | 1866914833937465344 |
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| author | Schneider, Ian Mattia, Taylor |
| author_facet | Schneider, Ian Mattia, Taylor |
| contents | This paper presents a methodology for allocating energy consumption to multiple users of shared data center machines, infrastructure, and software. Google uses this methodology to provide carbon reporting data for enterprise customers of multiple Google products, including Google Cloud and Workspace. The approach documented here advances the state-of-the-art of large scale Cloud carbon reporting systems. It uses detailed, granular measurement data on machine energy consumption. In addition, it uses physical factors for allocating energy consumption and carbon emissions--preferred by the Greenhouse Gas Protocol's Scope 3 Reporting Standard. Specifically, the approach described here allocates machine energy consumption based on a combination of data center resource reservations and hourly measured resource usage. It also accounts for Google's own internal use of shared software services, reallocating energy use to the users of those shared services. Finally, it uses hourly, location-specific estimates of carbon intensity to precisely measure carbon emissions of users in a global fleet of data centers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_09645 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Carbon accounting in the Cloud: a methodology for allocating emissions across data center users Schneider, Ian Mattia, Taylor Software Engineering This paper presents a methodology for allocating energy consumption to multiple users of shared data center machines, infrastructure, and software. Google uses this methodology to provide carbon reporting data for enterprise customers of multiple Google products, including Google Cloud and Workspace. The approach documented here advances the state-of-the-art of large scale Cloud carbon reporting systems. It uses detailed, granular measurement data on machine energy consumption. In addition, it uses physical factors for allocating energy consumption and carbon emissions--preferred by the Greenhouse Gas Protocol's Scope 3 Reporting Standard. Specifically, the approach described here allocates machine energy consumption based on a combination of data center resource reservations and hourly measured resource usage. It also accounts for Google's own internal use of shared software services, reallocating energy use to the users of those shared services. Finally, it uses hourly, location-specific estimates of carbon intensity to precisely measure carbon emissions of users in a global fleet of data centers. |
| title | Carbon accounting in the Cloud: a methodology for allocating emissions across data center users |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2406.09645 |