{"updated":"2025-01-19T09:50:53.946580+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00234255","sets":["1164:4088:11480:11609"]},"path":["11609"],"owner":"44499","recid":"234255","title":["Pod間通信の可視化によるマイクロサービスの障害根本原因分析支援機能提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-05-23"},"_buckets":{"deposit":"79b4ca28-26a4-4997-a2f3-6e5713caa511"},"_deposit":{"id":"234255","pid":{"type":"depid","value":"234255","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Pod間通信の可視化によるマイクロサービスの障害根本原因分析支援機能提案","author_link":["638027","638028","638026","638029"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Pod間通信の可視化によるマイクロサービスの障害根本原因分析支援機能提案"},{"subitem_title":"Proposal of microservice failure root cause analysis support tool by visualization of inter-pod communication","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ICM2","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-05-23","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社日立製作所研究開発グループ"},{"subitem_text_value":"株式会社日立製作所研究開発グループ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hitachi Ltd, Research & Development Group","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd, Research & Development Group","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/234255/files/IPSJ-IOT24065018.pdf","label":"IPSJ-IOT24065018.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IOT24065018.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"43"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"30d9e302-b908-468f-a190-303e71bd9462","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hu, Shizhen"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西島, 直"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shizhen, Hu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nao, Nishijima","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12326962","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8787","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"マイクロサービス障害発生時の初期対応では，障害の原因をアプリケーション側とインフラ基盤側のどちらにあるか切り分ける必要がある．Kubernetes の環境では，従来の根本原因分析において，監視データから仮説を作り，それを検証するプロセスが非効率という課題がある．異常 Pod の分布特徴を活用することで，仮説の範囲を絞ることが可能である．監視データから異常が発生している Pod の分布特徴から障害原因の仮説を検証する機能を提案・実装し，運用チームからフィードバックで効果を検証した．本稿では，Pod 間通信の可視化によるマイクロサービスの障害原因分析支援の機能検討について報告する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In the initial response to microservice failures, it is necessary to determine whether the cause of the failure is on the application side or the infrastructure side. In the K8s environment, the traditional root cause analysis process of creating and testing hypotheses based on monitoring data is inefficient. By using the distribution characteristics of anomaly pods, it is possible to narrow the scope of the hypothesis. We proposed and implemented a function to test the hypothesis of failure causes based on the distribution characteristics of anomaly pods from the monitoring data. We then verified the effectiveness of the function with feedback from the operations team. In this report, we report the results of our study to support the root cause analysis of microservice failures by visualizing the inter-pod communication.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告インターネットと運用技術（IOT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-05-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"18","bibliographicVolumeNumber":"2024-IOT-65"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:35:59.474283+00:00","id":234255,"links":{}}