2017/02/13 by Eric Jonas, Jonas, Eric, Qifan Pu +7 · 1 voice · 9 citations
Computer Science · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #IoT and Edge/Fog Computing #cs.DC
paper · pdf · doi:10.48550/arxiv.1702.04024
openalex publication_date 2017/02/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Distributed computing remains inaccessible to a large number of users, in spite of many open source platforms and extensive commercial offerings. While distributed computation frameworks have moved beyond a simple map-reduce model, many users are still left to struggle with complex cluster management and configuration tools, even for running simple embarrassingly parallel jobs. We argue that stateless functions represent a viable platform for these users, eliminating cluster management overhead, fulfilling the promise of elasticity. Furthermore, using our prototype implementation, PyWren, we show that this model is general enough to implement a number of distributed computing models, such as BSP, efficiently. Extrapolating from recent trends in network bandwidth and the advent of disaggregated storage, we suggest that stateless functions are a natural fit for data processing in future computing environments.