eprintid: 10141655 rev_number: 15 eprint_status: archive userid: 608 dir: disk0/10/14/16/55 datestamp: 2022-01-11 07:56:08 lastmod: 2022-10-19 06:10:46 status_changed: 2022-01-11 07:56:08 type: article metadata_visibility: show creators_name: Wen, J creators_name: Liu, Y creators_name: Chen, Z creators_name: Chen, J creators_name: Ma, Y title: Characterizing commodity serverless computing platforms ispublished: inpress divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: Science & Technology, Technology, Computer Science, Software Engineering, Computer Science, commodity platform, empirical study, serverless computing note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Serverless computing has become a new trending paradigm in cloud computing, allowing developers to focus on the development of core application logic and rapidly construct the prototype via the composition of independent functions. With the development and prosperity of serverless computing, major cloud vendors have successively rolled out their commodity serverless computing platforms. However, the characteristics of these platforms have not been systematically studied. Measuring these characteristics can help developers to select the most adequate serverless computing platform and develop their serverless-based applications in the right way. To fill this knowledge gap, we present a comprehensive study on characterizing mainstream commodity serverless computing platforms, including AWS Lambda, Google Cloud Functions, Azure Functions, and Alibaba Cloud Function Compute. Specifically, we conduct both qualitative analysis and quantitative analysis. In qualitative analysis, we compare these platforms from three aspects (i.e., development, deployment, and runtime) based on their official documentation to construct a taxonomy of characteristics. In quantitative analysis, we analyze the runtime performance of these platforms from multiple dimensions with well-designed benchmarks. First, we analyze three key factors that can influence the startup latency of serverless-based applications. Second, we compare the resource efficiency of different platforms with 16 representative benchmarks. Finally, we measure their performance difference when dealing with different concurrent requests and explore the potential causes in a black-box fashion. Based on the results of both qualitative and quantitative analysis, we derive a series of findings and provide insightful implications for both developers and cloud vendors. date: 2021-10-18 date_type: published publisher: WILEY official_url: https://doi.org/10.1002/smr.2394 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1895769 doi: 10.1002/smr.2394 lyricists_name: Chen, Zhenpeng lyricists_id: ZCHEM62 actors_name: Chen, Zhenpeng actors_id: ZCHEM62 actors_role: owner full_text_status: public publication: Journal of Software: Evolution and Process article_number: e2394 pages: 23 issn: 2047-7481 citation: Wen, J; Liu, Y; Chen, Z; Chen, J; Ma, Y; (2021) Characterizing commodity serverless computing platforms. Journal of Software: Evolution and Process , Article e2394. 10.1002/smr.2394 <https://doi.org/10.1002/smr.2394>. (In press). Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10141655/1/slsmeasure_revision.pdf