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Cloud providers are adapting datacenter (DC) capacity to reduce carbon emissions. With hyperscale datacenters exceeding 100 MW individually, and in some grids exceeding 15% of power load, DC adaptation is large enough to harm power grid dynamics, increasing carbon emissions, power prices, or reduce grid reliability. To avoid harm, we explore coordination of DC capacity change varying scope in space and time. In space, coordination scope spans a single datacenter, a group of datacenters, and datacenters with the grid. In time, scope ranges from online to day-ahead. We also consider what DC and grid information is used (e.g. real-time and day-ahead average carbon, power price, and compute backlog). For example, in our proposed PlanShare scheme, each datacenter uses day-ahead information to create a capacity plan and shares it, allowing global grid optimization (over all loads, over entire day). We evaluate DC carbon emissions reduction. Results show that local coordination scope fails to reduce carbon emissions significantly (3.2%–5.4% reduction). Expanding coordination scope to a set of datacenters improves slightly (4.9%–7.3%). PlanShare, with grid-wide coordination and full-day capacity planning, performs the best. PlanShare reduces DC emissions by 11.6%–12.6%, 1.56x–1.26x better than the best local, online approach’s results. PlanShare also achieves lower cost. We expect these advantages to increase as renewable generation in power grids increases. Further, a known full-day DC capacity plan provides a stable target for DC resource management.
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An Agile Pathway Towards Carbon-aware Clouds
Climate change is a pressing threat to planetary well-being that can be addressed only by rapid near-term actions across all sectors. Yet, the cloud computing sector, with its increasingly large carbon footprint, has initiated only modest efforts to reduce emissions to date; its main approach today relies on cloud providers sourcing renewable energy from a limited global pool of options. We investigate how to accelerate cloud computing's efforts. Our approach tackles carbon reduction from a software standpoint by gradually integrating carbon awareness into the cloud abstraction. Specifically, we identify key bottlenecks to software-driven cloud carbon reduction, including (1) the lack of visibility and disaggregated control between cloud providers and users over infrastructure and applications, (2) the immense overhead presently incurred by application developers to implement carbon-aware application optimizations, and (3) the increasing complexity of carbon-aware resource management due to renewable energy variability and growing hardware heterogeneity. To overcome these barriers, we propose an agile approach that federates the responsibility and tools to achieve carbon awareness across different cloud stakeholders. As a key first step, we advocate leveraging the role of application operators in managing large-scale cloud deployments and integrating carbon efficiency metrics into their cloud usage workflow. We discuss various techniques to help operators reduce carbon emissions, such as carbon budgets, service-level visibility into emissions, and configurable-yet-centralized resource management optimizations.
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- Award ID(s):
- 2104548
- PAR ID:
- 10505208
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- HotCarbon '23: Proceedings of the 2nd Workshop on Sustainable Computer Systems
- ISBN:
- 9798400702426
- Page Range / eLocation ID:
- 1 to 8
- Format(s):
- Medium: X
- Location:
- Boston MA USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3604930.3605722
