Abstract
Context. Energy efficiency is gaining importance in the design of software systems, but is still marginally addressed in the area of microservice-based systems. Energy-related aspects often get neglected in favor of other software quality attributes, such as performance, service composition, maintainability, and security.
Goal. The aim of this study is to identify, synthesize and empirically evaluate the energy and performance overhead of monitoring tools employed in the microservices and DevOps context.
Method. We selected four representative monitoring tools in the microservices and DevOps context. These were evaluated via a controlled experiment on an open-source Docker-based microservice benchmark system.
Results. The results highlight: i) the specific frequency and workload conditions under which energy consumption and performance metrics are impacted by the tools; ii) the differences between the tools; iii) the relation between energy and performance overhead.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
- 11.
References
Microservices (2023). https://martinfowler.com/articles/microservices.html
Basili, V.R.: Software Modeling and Measurement: The Goal Question Metric Paradigm. Computer Science Technical Report Series, CS-TR-2956 (1992)
Cortellessa, V., Di Pompeo, D., Eramo, R., Tucci, M.: A model-driven approach for continuous performance engineering in microservice-based systems. J. Syst. Softw. 183, 111084 (2022)
Di Francesco, P., Lago, P., Malavolta, I.: Architecting with microservices: a systematic mapping study. J. Syst. Softw. 150, 77–97 (2019)
Ergasheva, S., Khomyakov, I., Kruglov, A., Succi, G.: Metrics of energy consumption in software systems: a systematic literature review. IOP Conf. Ser. Earth Environ. Sci. 431, 012051 (2020)
Fahad, M., Shahid, A., Manumachu, R.R., Lastovetsky, A.: A comparative study of methods for measurement of energy of computing. Energies 12(11), 2204 (2019)
Heward, G., Müller, I., Han, J., Schneider, J.G., Versteeg, S.: Assessing the performance impact of service monitoring. In: ASWEC 2010, pp. 192–201. IEEE (2010)
Hirst, J.M., Miller, J.R., Kaplan, B.A., Reed, D.D.: Watts up? pro ac power meter for automated energy recording (2013)
Khomh, F., Abtahizadeh, S.A.: Understanding the impact of cloud patterns on performance and energy consumption. J. Syst. Softw. 141, 151–170 (2018)
Liu, M., Peter, S., Krishnamurthy, A., Phothilimthana, P.M.: E3: energy-efficient microservices on smartnic-accelerated servers. In: USENIX, pp. 363–378 (2019)
Merkel, D., et al.: Docker: lightweight linux containers for consistent development and deployment. Linux j 239(2), 2 (2014)
Pierce, C.A., Block, R.A., Aguinis, H.: Cautionary note on reporting eta-squared values from multifactor ANOVA designs. Educ. Psychol. Meas. 64(6), 916–924 (2004)
Romano, J., Kromrey, J.D., Coraggio, J., Skowronek, J.: Appropriate statistics for ordinal level data: Should we really be using t-test and cohen’sd for evaluating group differences on the NSSE and other surveys. In: FAIR, vol. 177, p. 34 (2006)
Santos, E.A., McLean, C., Solinas, C., Hindle, A.: How does docker affect energy consumption? evaluating workloads in and out of docker containers. J. Syst. Softw. 146, 14–25 (2018)
Vegas, S., Apa, C., Juristo, N.: Crossover designs in software engineering experiments: benefits and perils. IEEE Trans. Softw. Eng. 42(2), 120–135 (2015)
Verdecchia, R., Lago, P., Ebert, C., de Vries, C.: Green it and green software. IEEE Softw. 38(6), 7–15 (2021)
Zhou, X., et al.: Benchmarking microservice systems for software engineering research. In: 40th ACM/IEEE International Conference on Software Engineering (ICSE) (2018)
Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skło- dowska-Curie grant agreement No 871342 “uDEVOPS”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Dinga, M., Malavolta, I., Giamattei, L., Guerriero, A., Pietrantuono, R. (2023). An Empirical Evaluation of the Energy and Performance Overhead of Monitoring Tools on Docker-Based Systems. In: Monti, F., Rinderle-Ma, S., Ruiz Cortés, A., Zheng, Z., Mecella, M. (eds) Service-Oriented Computing. ICSOC 2023. Lecture Notes in Computer Science, vol 14419. Springer, Cham. https://doi.org/10.1007/978-3-031-48421-6_13
Download citation
DOI: https://doi.org/10.1007/978-3-031-48421-6_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48420-9
Online ISBN: 978-3-031-48421-6
eBook Packages: Computer ScienceComputer Science (R0)