Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis

Root cause identification of performance degradation within distributed systems is often a difficult and time-consuming task, yet it is crucial for maintaining high performance. In this paper, we present an execution trace-driven solution that reduces the efforts required to investigate, debug, and...

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Autores principales:	Naser Ezzati-Jivan, Houssem Daoud, Michel R. Dagenais
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/1e78e75d1d1741b88f6456d5da8a9109
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id	oai:doaj.org-article:1e78e75d1d1741b88f6456d5da8a9109
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spelling	oai:doaj.org-article:1e78e75d1d1741b88f6456d5da8a91092021-11-29T00:55:52ZDebugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis1530-867710.1155/2021/8478076https://doaj.org/article/1e78e75d1d1741b88f6456d5da8a91092021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8478076https://doaj.org/toc/1530-8677Root cause identification of performance degradation within distributed systems is often a difficult and time-consuming task, yet it is crucial for maintaining high performance. In this paper, we present an execution trace-driven solution that reduces the efforts required to investigate, debug, and solve performance problems found in multinode distributed systems. The proposed approach employs a unified analysis method to represent trace data collected from the user-space level to the hardware level of involved nodes, allowing for efficient and effective root cause analysis. This solution works by extracting performance metrics and state information from trace data collected at user-space, kernel, and network levels. The multisource trace data is then synchronized and structured in a multidimensional data store, which is designed specifically for this kind of data. A posteriori analysis using a top-down approach is then used to investigate performance problems and detect their root causes. In this paper, we apply this generic framework to analyze trace data collected from the execution of the web server, database server, and application servers in a distributed LAMP (Linux, Apache, MySQL, and PHP) Stack. Using industrial level use cases, we show that the proposed approach is capable of investigating the root cause of performance issues, addressing unusual latency, and improving base latency by 70%. This is achieved with minimal tracing overhead that does not significantly impact performance, as well as Olog n query response times for efficient analysis.Naser Ezzati-JivanHoussem DaoudMichel R. DagenaisHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Naser Ezzati-Jivan Houssem Daoud Michel R. Dagenais Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
description	Root cause identification of performance degradation within distributed systems is often a difficult and time-consuming task, yet it is crucial for maintaining high performance. In this paper, we present an execution trace-driven solution that reduces the efforts required to investigate, debug, and solve performance problems found in multinode distributed systems. The proposed approach employs a unified analysis method to represent trace data collected from the user-space level to the hardware level of involved nodes, allowing for efficient and effective root cause analysis. This solution works by extracting performance metrics and state information from trace data collected at user-space, kernel, and network levels. The multisource trace data is then synchronized and structured in a multidimensional data store, which is designed specifically for this kind of data. A posteriori analysis using a top-down approach is then used to investigate performance problems and detect their root causes. In this paper, we apply this generic framework to analyze trace data collected from the execution of the web server, database server, and application servers in a distributed LAMP (Linux, Apache, MySQL, and PHP) Stack. Using industrial level use cases, we show that the proposed approach is capable of investigating the root cause of performance issues, addressing unusual latency, and improving base latency by 70%. This is achieved with minimal tracing overhead that does not significantly impact performance, as well as Olog n query response times for efficient analysis.
format	article
author	Naser Ezzati-Jivan Houssem Daoud Michel R. Dagenais
author_facet	Naser Ezzati-Jivan Houssem Daoud Michel R. Dagenais
author_sort	Naser Ezzati-Jivan
title	Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
title_short	Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
title_full	Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
title_fullStr	Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
title_full_unstemmed	Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis
title_sort	debugging of performance degradation in distributed requests handling using multilevel trace analysis
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/1e78e75d1d1741b88f6456d5da8a9109
work_keys_str_mv	AT naserezzatijivan debuggingofperformancedegradationindistributedrequestshandlingusingmultileveltraceanalysis AT houssemdaoud debuggingofperformancedegradationindistributedrequestshandlingusingmultileveltraceanalysis AT michelrdagenais debuggingofperformancedegradationindistributedrequestshandlingusingmultileveltraceanalysis
_version_	1718407756572000256

Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis

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