Energy-Aware Decision Making in Software Stack Upgrades

2026-05-26

AI Summary

This study addresses the lack of systematic evaluation of energy consumption impacts in software stack upgrades, which hinders sustainable operational decisions. It presents the first comprehensive quantification of energy differences across combinations of Spring Boot and JVM versions on multiple platforms. Through automated benchmarking and precise power measurements, the work demonstrates that significant energy savings can be achieved without modifying application code by leveraging newer JVM features—such as virtual threads introduced in Java 21 and 23. The findings reveal that judicious selection of software stack versions can substantially reduce energy consumption, offering empirical evidence and practical guidance for greener software upgrades.

Abstract

Software stack upgrades are a routine part of software maintenance and evolution, typically motivated by improved performance, stability, or functionality. Yet their impact on energy consumption - a growing concern for organizations pursuing sustainability - remains poorly understood. This paper presents a systematic method for measuring how different versions of core software stack components, such as Spring Boot and the Java Virtual Machine (JVM), influence the energy consumption of applications. Our approach evaluates combinations of framework versions, runtime versions, and execution platforms through automated benchmarking. Using a case study based on the Spring Petclinic REST application, we show that energy consumption varies substantially across Spring Boot and JVM versions, in some cases producing unexpected regressions. Notably, newer JVM releases and virtual threads (introduced in Java 21 and 23) yielded significant energy savings without requiring application changes. These results demonstrate that software upgrades can meaningfully affect energy usage and that measuring energy consumption provides valuable evidence for decision making in software maintenance and evolution.

Problem

• energy consumption
• software stack upgrades
• sustainability
• JVM
• Spring Boot

Innovation

• energy-aware software evolution
• software stack upgrades
• JVM virtual threads
• automated benchmarking
• sustainable software engineering