Understanding Container-based Services under Software Aging: Dependability and Performance Views

TL;DR

This paper presents a semi-Markov model to evaluate how OS rejuvenation affects dependability and performance in container-based services, providing insights into optimal rejuvenation intervals without restrictive assumptions.

Contribution

It introduces a comprehensive semi-Markov approach that relaxes common assumptions, enabling accurate evaluation of OS rejuvenation impacts on container service dependability and performance.

Findings

Identifies optimal container-migration trigger intervals for dependability.

Shows how rejuvenation timing influences performance degradation.

Provides a quantitative tool for managing software aging in container services.

Abstract

Container technology, as the key enabler behind microservice architectures, is widely applied in Cloud and Edge Computing. A long and continuous running of operating system (OS) host-ing container-based services can encounter software aging that leads to performance deterioration and even causes system fail-ures. OS rejuvenation techniques can mitigate the impact of software aging but the rejuvenation trigger interval needs to be carefully determined to reduce the downtime cost due to rejuve-nation. This paper proposes a comprehensive semi-Markov-based approach to quantitatively evaluate the effect of OS reju-venation on the dependability and the performance of a con-tainer-based service. In contrast to the existing studies, we nei-ther restrict the distributions of time intervals of events to be exponential nor assume that backup resources are always avail-able. Through the numerical study, we show the optimal con-tainer-migration trigger intervals that can maximize the de-pendability or minimize the performance of a container-based service.