Online Memory Leak Detection in the Cloud-Based Infrastructures

Anshul Jindal, Paul Staab, Jorge Cardoso, Michael Gerndt, Vladimir Podolskiy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

A memory leak in an application deployed on the cloud can affect the availability and reliability of the application. Therefore, to identify and ultimately resolve it quickly is highly important. However, in the production environment running on the cloud, memory leak detection is a challenge without the knowledge of the application or its internal object allocation details. This paper addresses this challenge of online detection of memory leaks in cloud-based infrastructure without having any internal application knowledge by introducing a novel machine learning based algorithm Precog. This algorithm solely uses one metric i.e. the system’s memory utilization on which the application is deployed for the detection of a memory leak. The developed algorithm’s accuracy was tested on 60 virtual machines manually labeled memory utilization data provided by our industry partner Huawei Munich Research Center and it was found that the proposed algorithm achieves the accuracy score of 85% with less than half a second prediction time per virtual machine.

Original languageEnglish
Title of host publicationService-Oriented Computing – ICSOC 2020 Workshops - AIOps, CFTIC, STRAPS, AI-PA, AI-IOTS, and Satellite Events, Proceedings
EditorsHakim Hacid, Fatma Outay, Hye-young Paik, Amira Alloum, Marinella Petrocchi, Mohamed Reda Bouadjenek, Amin Beheshti, Xumin Liu, Abderrahmane Maaradji
PublisherSpringer Science and Business Media Deutschland GmbH
Pages188-200
Number of pages13
ISBN (Print)9783030763510
DOIs
StatePublished - 2021
EventAIOps, CFTIC, STRAPS, AI-PA, AI-IOTS, and Satellite Events held in conjunction with 18th International Conference on Service-Oriented Computing, ICSOC 2020 - Virtual, Online
Duration: 14 Dec 202017 Dec 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12632 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceAIOps, CFTIC, STRAPS, AI-PA, AI-IOTS, and Satellite Events held in conjunction with 18th International Conference on Service-Oriented Computing, ICSOC 2020
CityVirtual, Online
Period14/12/2017/12/20

Keywords

  • Cloud
  • Linear regression
  • Memory leak
  • Memory leak patterns
  • Online memory leak detection

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