@inproceedings{fae24ccd8101459c9290abb608a88c79,
title = "Cloud-scale Java profiling at alibaba",
abstract = "On the 2017 Double 11 Global Shopping Festival, Alibaba{\textquoteright}s cloud platform achieved total sales of more than 25 billion dollars and supported peak volumes of 325,000 transactions and 256,000 payments per second. Most of the cloud-based e-commerce transactions were processed by hundreds of thousands of Java applications with above a billion lines of code. It is challenging to achieve comprehensive and efficient performance profiling for large-scale, cloud-based Java applications in production. We developed ZProfiler, a fine-grained, low-overhead Java performance profiler. ZProfiler allows developers to load a profiling agent on the fly without restarting Java virtual machines, and its profiling information also facilitates code warmup. ZProfiler is developed based on Alibaba JDK (AJDK), a customized version of OpenJDK, and it has been rolled out to Alibaba{\textquoteright}s cloud platform to support large-scale performance tuning for online critical business.",
keywords = "Cloud, Code warmup, Java performance, Overhead, Profiling",
author = "Fangxi Yin and Denghui Dong and Chuansheng Lu and Tongbao Zhang and Sanhong Li and Jianmei Guo and Kingsum Chow",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 9th ACM/SPEC International Conference on Performance Engineering, ICPE 2018 ; Conference date: 09-04-2018 Through 13-04-2018",
year = "2018",
month = apr,
day = "2",
doi = "10.1145/3185768.3186295",
language = "英语",
series = "ICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering",
publisher = "Association for Computing Machinery, Inc",
pages = "99--100",
booktitle = "ICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering",
}