Towards Energy-Efficient Serverless Computing with Hardware Isolation
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arXiv
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| Format: | Preprint |
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2025
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| author | Carl, Natalie Pfandzelter, Tobias Bermbach, David |
| author_facet | Carl, Natalie Pfandzelter, Tobias Bermbach, David |
| contents | Serverless computing provides just-in-time infrastructure provisioning with rapid elasticity and a finely-grained pricing model. As full control of resource allocation is in the hands of the cloud provider and applications only consume resources when they actually perform work, we believe that serverless computing is uniquely positioned to maximize energy efficiency.
However, the focus of current serverless platforms is to run hundreds or thousands of serverless functions from different tenants on traditional server hardware, requiring expensive software isolation mechanisms and a high degree of overprovisioning, i.e., idle servers, to anticipate load spikes. With shared caches, high clock frequencies, and many-core architectures, servers today are optimized for large, singular workloads but not to run thousands of isolated functions.
We propose rethinking the serverless hardware architecture to align it with the requirements of serverless software. Specifically, we propose using hardware isolation with individual processors per function instead of software isolation resulting in a serverless hardware stack that consumes energy only when an application actually performs work. In preliminary evaluation with real hardware and a typical serverless workload we find that this could reduce energy consumption overheads by 90.63% or an average 70.8MW. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_08180 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Energy-Efficient Serverless Computing with Hardware Isolation Carl, Natalie Pfandzelter, Tobias Bermbach, David Distributed, Parallel, and Cluster Computing Serverless computing provides just-in-time infrastructure provisioning with rapid elasticity and a finely-grained pricing model. As full control of resource allocation is in the hands of the cloud provider and applications only consume resources when they actually perform work, we believe that serverless computing is uniquely positioned to maximize energy efficiency. However, the focus of current serverless platforms is to run hundreds or thousands of serverless functions from different tenants on traditional server hardware, requiring expensive software isolation mechanisms and a high degree of overprovisioning, i.e., idle servers, to anticipate load spikes. With shared caches, high clock frequencies, and many-core architectures, servers today are optimized for large, singular workloads but not to run thousands of isolated functions. We propose rethinking the serverless hardware architecture to align it with the requirements of serverless software. Specifically, we propose using hardware isolation with individual processors per function instead of software isolation resulting in a serverless hardware stack that consumes energy only when an application actually performs work. In preliminary evaluation with real hardware and a typical serverless workload we find that this could reduce energy consumption overheads by 90.63% or an average 70.8MW. |
| title | Towards Energy-Efficient Serverless Computing with Hardware Isolation |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2510.08180 |