Automating instrumentation choices for performance problems in distributed applications with VAIF
Automating instrumentation choices for performance problems in distributed applications with VAIF
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使用 VAIF 自动选择仪器来解决分布式应用程序中的性能问题
DOI:
10.1145/3472883.3487000
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发表时间:
2021
期刊:
影响因子:
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通讯作者:
Sambasivan, Raja R.
中科院分区:
文献类型:
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作者:
Toslali, Mert;Ates, Emre;Ellis, Alex;Zhang, Zhaoqi;Huye, Darby;Liu, Lan;Puterman, Samantha;Coskun, Ayse K.;Sambasivan, Raja R.
Developers use logs to diagnose performance problems in distributed applications. However, it is difficult to know a priori where logs are needed and what information in them is needed to help diagnose problems that may occur in the future. We present the Variance-driven Automated Instrumentation Framework (VAIF), which runs alongside distributed applications. In response to newly-observed performance problems, VAIF automatically searches the space of possible instrumentation choices to enable the logs needed to help diagnose them. To work, VAIF combines distributed tracing (an enhanced form of logging) with insights about how response-time variance can be decomposed on the critical-path portions of requests' traces. We evaluate VAIF by using it to localize performance problems in OpenStack and HDFS. We show that VAIF can localize problems related to slow code paths, resource contention, and problematic third-party code while enabling only 3-34% of the total tracing instrumentation.
DOI:
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发表时间:
2010
期刊:
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影响因子:
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作者:
B. Sigelman;L. Barroso;M. Burrows;Patrick Stephenson;Manoj Plakal;Donald Beaver;Saul Jaspan;C. Shanbh
通讯作者:
B. Sigelman;L. Barroso;M. Burrows;Patrick Stephenson;Manoj Plakal;Donald Beaver;Saul Jaspan;C. Shanbh
DOI:
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发表时间:
2005
期刊:
影响因子:
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作者:
Emre Kıcıman;L. Subramanian
通讯作者:
L. Subramanian