本文選題：云計(jì)算 + 平臺(tái)即服務(wù)　； 參考：《計(jì)算機(jī)集成制造系統(tǒng)》2017年05期

【摘要】：為了彌補(bǔ)現(xiàn)有的容器化PaaS平臺(tái)監(jiān)控方式在監(jiān)控粒度和深度上的不足,研究并實(shí)現(xiàn)了一種智能監(jiān)控方法。在該方法中,監(jiān)控模塊通過(guò)動(dòng)態(tài)調(diào)整采樣周期,使采樣點(diǎn)集中于應(yīng)用系統(tǒng)資源占用狀況波動(dòng)幅度較大的時(shí)段;對(duì)于波動(dòng)幅度超過(guò)閾值的情況,采集應(yīng)用系統(tǒng)調(diào)用級(jí)別的數(shù)據(jù)并加以分析;將統(tǒng)計(jì)分析結(jié)果及原始監(jiān)測(cè)數(shù)據(jù)按時(shí)序整合并對(duì)外提供查詢接口,進(jìn)而為用戶定位異�；虬l(fā)現(xiàn)性能瓶頸提供幫助。相較于現(xiàn)有的監(jiān)控方案,該方法能更加細(xì)粒度地反映應(yīng)用運(yùn)行時(shí)狀態(tài)的變化,同時(shí)動(dòng)態(tài)的數(shù)據(jù)采集機(jī)制能有效節(jié)省計(jì)算和存儲(chǔ)資源的開銷。
[Abstract]:In order to make up for the deficiency of the existing monitoring methods of container PaaS platform in monitoring granularity and depth, an intelligent monitoring method is studied and implemented. In this method, the monitoring module dynamically adjusts the sampling period to make the sampling point concentrate on the period in which the resource occupation of the application system fluctuates greatly, and for the situation where the fluctuation amplitude exceeds the threshold, The data of application system call level are collected and analyzed, and the statistical analysis results and the original monitoring data are integrated according to the time sequence and the query interface is provided to help the user locate the exception or find the performance bottleneck. Compared with the existing monitoring scheme, this method can reflect the change of the application runtime state more fine-grained, and the dynamic data acquisition mechanism can effectively save the cost of computing and storage resources.
【作者單位】： 浙江大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;衢州職業(yè)技術(shù)學(xué)院信息工程學(xué)院;
【基金】：浙江省重大科技專項(xiàng)資助項(xiàng)目(2015C01027) 浙江省自然科學(xué)基金資助項(xiàng)目(LY17F020014)~~
【分類號(hào)】：TP277;TP393.09

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