{"title":"DOCKERANALYZER:面向使用Docker部署的基于微服务的应用的细粒度资源弹性","authors":"M. Fourati, Soumaya Marzouk, K. Drira, M. Jmaiel","doi":"10.1109/PDCAT46702.2019.00049","DOIUrl":null,"url":null,"abstract":"This article deals with anomaly detection for microservices-based applications during elastic treatment. In elastic treatment, scaling-up resources is based on threshold. Many studies consider that threshold exceeding is caused by the increase in requests number. However, this exceeding may be caused by many problems such as specific requests requiring a lot of resources or issues related to VMs and containers. That's why, when thresholds are exceeded we propose to apply an analysis treatment that detects and identifies the root cause of the threshold exceeding, either it's caused by a problem such as specific request, VM issue, container issue or it's caused by a normal increase in request's number. This paper presents \"DOCKERANALYZER\" a software module that detects and identifies execution problems in microservices context. Experimental measurements have been conducted on an IOT platform as a real use-case presenting realistic problems and demonstrating the effectiveness of our proposed solution.","PeriodicalId":166126,"journal":{"name":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"DOCKERANALYZER : Towards Fine Grained Resource Elasticity for Microservices-Based Applications Deployed with Docker\",\"authors\":\"M. Fourati, Soumaya Marzouk, K. Drira, M. Jmaiel\",\"doi\":\"10.1109/PDCAT46702.2019.00049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article deals with anomaly detection for microservices-based applications during elastic treatment. In elastic treatment, scaling-up resources is based on threshold. Many studies consider that threshold exceeding is caused by the increase in requests number. However, this exceeding may be caused by many problems such as specific requests requiring a lot of resources or issues related to VMs and containers. That's why, when thresholds are exceeded we propose to apply an analysis treatment that detects and identifies the root cause of the threshold exceeding, either it's caused by a problem such as specific request, VM issue, container issue or it's caused by a normal increase in request's number. This paper presents \\\"DOCKERANALYZER\\\" a software module that detects and identifies execution problems in microservices context. Experimental measurements have been conducted on an IOT platform as a real use-case presenting realistic problems and demonstrating the effectiveness of our proposed solution.\",\"PeriodicalId\":166126,\"journal\":{\"name\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PDCAT46702.2019.00049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDCAT46702.2019.00049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DOCKERANALYZER : Towards Fine Grained Resource Elasticity for Microservices-Based Applications Deployed with Docker
This article deals with anomaly detection for microservices-based applications during elastic treatment. In elastic treatment, scaling-up resources is based on threshold. Many studies consider that threshold exceeding is caused by the increase in requests number. However, this exceeding may be caused by many problems such as specific requests requiring a lot of resources or issues related to VMs and containers. That's why, when thresholds are exceeded we propose to apply an analysis treatment that detects and identifies the root cause of the threshold exceeding, either it's caused by a problem such as specific request, VM issue, container issue or it's caused by a normal increase in request's number. This paper presents "DOCKERANALYZER" a software module that detects and identifies execution problems in microservices context. Experimental measurements have been conducted on an IOT platform as a real use-case presenting realistic problems and demonstrating the effectiveness of our proposed solution.