Microservices changed cloud computing by moving the applications' complexity from one monolithic executable to thousands of network interactions between small components. Given the increasing deployment sizes, the architectural exploitation challenges, and the impact on data-centers' power consumption, we need to efficiently track this complexity. Within this article, we propose a black-box monitoring approach to track microservices at scale, focusing on architectural metrics, power consumption, application performance, and network performance. The proposed approach is transparent w.r.t. the monitored applications, generates less overhead w.r.t. black-box approaches available in the state-of-the-art, and provides fine-grain accurate metrics.

A Black-box Monitoring Approach to Measure Microservices Runtime Performance

Brondolin R.;Santambrogio M. D.
2020-01-01

Abstract

Microservices changed cloud computing by moving the applications' complexity from one monolithic executable to thousands of network interactions between small components. Given the increasing deployment sizes, the architectural exploitation challenges, and the impact on data-centers' power consumption, we need to efficiently track this complexity. Within this article, we propose a black-box monitoring approach to track microservices at scale, focusing on architectural metrics, power consumption, application performance, and network performance. The proposed approach is transparent w.r.t. the monitored applications, generates less overhead w.r.t. black-box approaches available in the state-of-the-art, and provides fine-grain accurate metrics.
cloud computing
docker
kubernetes
Microservices
network performance monitoring
performance monitoring
power attribution
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1163691
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