A Framework for SLO, Carbon, and Wastewater-Aware Sustainable FaaS Cloud Platform Management
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866917804485115904 |
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| author | Qi, Sirui Moore, Hayden Hogade, Ninad Milojicic, Dejan Bash, Cullen Pasricha, Sudeep |
| author_facet | Qi, Sirui Moore, Hayden Hogade, Ninad Milojicic, Dejan Bash, Cullen Pasricha, Sudeep |
| contents | Function-as-a-Service (FaaS) is a growing cloud computing paradigm that is expected to reduce the user cost of service over traditional serverful approaches. However, the environmental impact of FaaS has not received much attention. We investigate FaaS scheduling and scaling from a sustainability perspective in this work. We find that the service-level objectives (SLOs) of FaaS and carbon emissions conflict with each other. We also find that SLO-focused FaaS scheduling can exacerbate water use in a datacenter. We propose a novel sustainability-focused FaaS scheduling and scaling framework to co-optimize SLO performance, carbon emissions, and wastewater generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11875 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Framework for SLO, Carbon, and Wastewater-Aware Sustainable FaaS Cloud Platform Management Qi, Sirui Moore, Hayden Hogade, Ninad Milojicic, Dejan Bash, Cullen Pasricha, Sudeep Distributed, Parallel, and Cluster Computing Artificial Intelligence Machine Learning Function-as-a-Service (FaaS) is a growing cloud computing paradigm that is expected to reduce the user cost of service over traditional serverful approaches. However, the environmental impact of FaaS has not received much attention. We investigate FaaS scheduling and scaling from a sustainability perspective in this work. We find that the service-level objectives (SLOs) of FaaS and carbon emissions conflict with each other. We also find that SLO-focused FaaS scheduling can exacerbate water use in a datacenter. We propose a novel sustainability-focused FaaS scheduling and scaling framework to co-optimize SLO performance, carbon emissions, and wastewater generation. |
| title | A Framework for SLO, Carbon, and Wastewater-Aware Sustainable FaaS Cloud Platform Management |
| topic | Distributed, Parallel, and Cluster Computing Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2410.11875 |