Continuous benchmarking of serverless cloud providers 2
To date, there is no standard benchmarking methodology to quantita- tively compare the performance of different serverless cloud providers. This project aims to design a framework that regularly runs a set of var- ious microbenchmarks on multiple providers, including AWS Lambda, Azure Functions,...
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| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2024
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/175156 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | To date, there is no standard benchmarking methodology to quantita-
tively compare the performance of different serverless cloud providers.
This project aims to design a framework that regularly runs a set of var-
ious microbenchmarks on multiple providers, including AWS Lambda,
Azure Functions, Google Cloud Run, and Cloudflare. This project ana-
lyzes cold start delays, including snapshots and boot-based techniques,
and the implications of the language runtime on the cold delay by
extending an open-source serverless benchmarking tool, Serverless
Tail-Latency Analyzer (STeLLAR). STeLLAR’s compatibility has been
expanded to include more Cloud Providers as well as provider-specific
features, and the existing system of automated daily experiments using
STeLLAR has been extended to encompass new Cloud Providers and
experiments, and enhanced with fault-tolerant features in the event of
experiment failure. |
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