JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance

Darlan Noetzold; Anubis Graciela de Moraes Rossetto; Luis Augusto Silva; Paul Crocker; Valderi Reis Quietinho Leithardt

doi:10.1016/j.softx.2024.101933

JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance

Darlan Noetzold, Anubis Graciela de Moraes Rossetto, Luis Augusto Silva, Paul Crocker, Valderi Reis Quietinho Leithardt

Resultado de pesquisa › revisão de pares

Resumo

This research presents software for empirically analyzing Java Virtual Machine (JVM) parameter configurations to enhance web application performance. Using tools like JMeter and cAdvisor in a controlled hardware environment, it collects and analyzes performance metrics. Tailored JVM settings for high request loads improved CPU efficiency by 20% and reduced memory usage by 15% compared to standard configurations. For I/O intensive operations with large files, optimized JVM configurations decreased response times by 30% and CPU usage by 25%. These findings highlight the impact of tailored JVM settings on application responsiveness and resource management, providing valuable guidance for developers and engineers.

Idioma original	Inglês
Número do artigo	101933
Revista	SoftwareX
Volume	28
DOIs	https://doi.org/10.1016/j.softx.2024.101933
Estado da publicação	Publicadas - 1 dez. 2024
Publicado externamente	Sim

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Publisher Copyright:
© 2024 The Authors

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Financiadoras/-es	Número do financiador
Fundação para a Ciência e a Tecnologia	UIDB/50008/2020

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10.1016/j.softx.2024.101933

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title = "JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance",

abstract = "This research presents software for empirically analyzing Java Virtual Machine (JVM) parameter configurations to enhance web application performance. Using tools like JMeter and cAdvisor in a controlled hardware environment, it collects and analyzes performance metrics. Tailored JVM settings for high request loads improved CPU efficiency by 20% and reduced memory usage by 15% compared to standard configurations. For I/O intensive operations with large files, optimized JVM configurations decreased response times by 30% and CPU usage by 25%. These findings highlight the impact of tailored JVM settings on application responsiveness and resource management, providing valuable guidance for developers and engineers.",

keywords = "Garbage collection, JVM optimization, Performance metrics, Resource management, Web application efficiency",

author = "Darlan Noetzold and {de Moraes Rossetto}, {Anubis Graciela} and Silva, {Luis Augusto} and Paul Crocker and Leithardt, {Valderi Reis Quietinho}",

note = "Publisher Copyright: {\textcopyright} 2024 The Authors",

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doi = "10.1016/j.softx.2024.101933",

language = "English",

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AU - Noetzold, Darlan

AU - de Moraes Rossetto, Anubis Graciela

AU - Silva, Luis Augusto

AU - Crocker, Paul

AU - Leithardt, Valderi Reis Quietinho

PY - 2024/12/1

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N2 - This research presents software for empirically analyzing Java Virtual Machine (JVM) parameter configurations to enhance web application performance. Using tools like JMeter and cAdvisor in a controlled hardware environment, it collects and analyzes performance metrics. Tailored JVM settings for high request loads improved CPU efficiency by 20% and reduced memory usage by 15% compared to standard configurations. For I/O intensive operations with large files, optimized JVM configurations decreased response times by 30% and CPU usage by 25%. These findings highlight the impact of tailored JVM settings on application responsiveness and resource management, providing valuable guidance for developers and engineers.

AB - This research presents software for empirically analyzing Java Virtual Machine (JVM) parameter configurations to enhance web application performance. Using tools like JMeter and cAdvisor in a controlled hardware environment, it collects and analyzes performance metrics. Tailored JVM settings for high request loads improved CPU efficiency by 20% and reduced memory usage by 15% compared to standard configurations. For I/O intensive operations with large files, optimized JVM configurations decreased response times by 30% and CPU usage by 25%. These findings highlight the impact of tailored JVM settings on application responsiveness and resource management, providing valuable guidance for developers and engineers.

KW - Garbage collection

KW - JVM optimization

KW - Performance metrics

KW - Resource management

KW - Web application efficiency

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VL - 28

JO - SoftwareX

JF - SoftwareX

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JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance

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