{"ID":2893785,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.11929","arxiv_id":"2507.11929","title":"Making Serverless Computing Extensible: A Case Study of Serverless Data Analytics","abstract":"Serverless computing has attracted a broad range of applications due to its ease of use and resource elasticity. However, developing serverless applications often poses a dilemma -- relying on general-purpose serverless platforms can fall short of delivering satisfactory performance for complex workloads, whereas building application-specific serverless systems undermines the simplicity and generality. In this paper, we propose an extensible design principle for serverless computing. We argue that a platform should enable developers to extend system behaviors for domain-specialized optimizations while retaining a shared, easy-to-use serverless environment. We take data analytics as a representative serverless use case and realize this design principle in Proteus. Proteus introduces a novel abstraction of decision workflows, allowing developers to customize control-plane behaviors for improved application performance. Preliminary results show that Proteus's prototype effectively optimizes analytical query execution and supports fine-grained resource sharing across diverse applications.","short_abstract":"Serverless computing has attracted a broad range of applications due to its ease of use and resource elasticity. However, developing serverless applications often poses a dilemma -- relying on general-purpose serverless platforms can fall short of delivering satisfactory performance for complex workloads, whereas build...","url_abs":"https://arxiv.org/abs/2507.11929","url_pdf":"https://arxiv.org/pdf/2507.11929v1","authors":"[\"Minchen Yu\",\"Yinghao Ren\",\"Jiamu Zhao\",\"Jiaqi Li\"]","published":"2025-07-16T05:52:32Z","proceeding":"cs.DC","tasks":"[\"cs.DC\"]","methods":"[]","has_code":false}