On Evaluating Self-Adaptive and Self-Healing Systems using Chaos
Engineering
- URL: http://arxiv.org/abs/2208.13227v1
- Date: Sun, 28 Aug 2022 14:38:57 GMT
- Title: On Evaluating Self-Adaptive and Self-Healing Systems using Chaos
Engineering
- Authors: Moeen Ali Naqvi and Sehrish Malik and Merve Astekin and Leon Moonen
- Abstract summary: We propose CHESS, an approach for the systematic evaluation of self-adaptive and self-healing systems.
Chaos engineering is a methodology for subjecting a system to unexpected conditions and scenarios.
We investigate the viability of this approach through an exploratory study on a self-healing smart office environment.
- Score: 0.6117371161379209
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: With the growing adoption of self-adaptive systems in various domains, there
is an increasing need for strategies to assess their correct behavior. In
particular self-healing systems, which aim to provide resilience and
fault-tolerance, often deal with unanticipated failures in critical and highly
dynamic environments. Their reactive and complex behavior makes it challenging
to assess if these systems execute according to the desired goals. Recently,
several studies have expressed concern about the lack of systematic evaluation
methods for self-healing behavior.
In this paper, we propose CHESS, an approach for the systematic evaluation of
self-adaptive and self-healing systems that builds on chaos engineering. Chaos
engineering is a methodology for subjecting a system to unexpected conditions
and scenarios. It has shown great promise in helping developers build resilient
microservice architectures and cyber-physical systems. CHESS turns this idea
around by using chaos engineering to evaluate how well a self-healing system
can withstand such perturbations. We investigate the viability of this approach
through an exploratory study on a self-healing smart office environment. The
study helps us explore the promises and limitations of the approach, as well as
identify directions where additional work is needed. We conclude with a summary
of lessons learned.
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