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Paper Abstract and Keywords
Presentation 2022-01-27 13:00
Proposal and Evaluation of a Methodology to Estimate Cause of Failure Based on Multiple Monitoring Data on Microservice Systems
Shun Matsumoto, Masaru Sakai, Kensuke Takahashi, Satoshi Kondoh (NTT) ICM2021-33 LOIS2021-31
Abstract (in Japanese) (See Japanese page) 
(in English) Microservice architecture, which divides service components into small components and provides services by having each component cooperate with each other, is becoming more and more popular. While it is expected to bring benefits such as faster development, it also tends to increase the burden of operation management due to increased system complexity and monitoring data. In order to support operation management, techniques for batch management of monitoring data and methods for fault detection and fault occurrence microservice estimation have been proposed, but there is no method for estimating fault-causing resources such as CPU and memory. Therefore, in this paper, we proposed a method that can perform failure detection and failure occurrence microservice estimation as well as failure cause resource estimation at once. In addition, we conducted an evaluation experiment using six pseudo-failure data generated on a microservice system, and showed that the method can successfully detect failures, estimate the microservices causing failures, and estimate the resources causing failures for five pseudo-failures.
Keyword (in Japanese) (See Japanese page) 
(in English) microservice / failure detection / deep learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 354, ICM2021-33, pp. 1-6, Jan. 2022.
Paper # ICM2021-33 
Date of Issue 2022-01-20 (ICM, LOIS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee LOIS ICM  
Conference Date 2022-01-27 - 2022-01-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Practical Use of Lifelog, Office Information System, Business Management, etc. 
Paper Information
Registration To ICM 
Conference Code 2022-01-LOIS-ICM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposal and Evaluation of a Methodology to Estimate Cause of Failure Based on Multiple Monitoring Data on Microservice Systems 
Sub Title (in English)  
Keyword(1) microservice  
Keyword(2) failure detection  
Keyword(3) deep learning  
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1st Author's Name Shun Matsumoto  
1st Author's Affiliation NTT Corporation (NTT)
2nd Author's Name Masaru Sakai  
2nd Author's Affiliation NTT Corporation (NTT)
3rd Author's Name Kensuke Takahashi  
3rd Author's Affiliation NTT Corporation (NTT)
4th Author's Name Satoshi Kondoh  
4th Author's Affiliation NTT Corporation (NTT)
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Speaker Author-1 
Date Time 2022-01-27 13:00:00 
Presentation Time 25 minutes 
Registration for ICM 
Paper # ICM2021-33, LOIS2021-31 
Volume (vol) vol.121 
Number (no) no.354(ICM), no.355(LOIS) 
Page pp.1-6 
#Pages 6 
Date of Issue 2022-01-20 (ICM, LOIS) 

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