Cascading Failure Modes in Model-as-a-Service Architectures : When Your Dependencies Think

Authors

  • Sheriff Adepoju Prairie View A&M University, Texas, USA Author

DOI:

https://doi.org/10.32628/IJSRCE237530

Keywords:

Model-as-a-Service, cascading failures, machine learning reliability, resilient architectures, circuit breakers, fallback strategies, graceful degradation, service orchestration, decision uncertainty, infrastructure risk, AI system dependability, intelligent dependencies

Abstract

Following an increased move towards machine learning becoming a runtime dependency of contemporary software systems, the Model-as-a-Service (MaaS) architecture is subjected to a new category of systemic risks where failure at one component propagates across decision-making when it comes to systems. In contrast to the failure of standard microservices, failure modes in services that rely on machine learning can silently propagate throughout workflows, multiplying uncertainty, reducing the quality of decisions, and destabilizing downstream services. In this study, the authors investigated the cascading failure modes of MaaS architectures and stated that resilience should be explicitly designed based on intelligent dependencies. Based on cascading failure theory, service-oriented architectures, and critical infrastructure systems, this study conceptualizes how a combination of data inconsistencies, variability in model behavior, orchestration misalignment, and the disruptive behavior of infrastructure amplify failure. This article proposes a resilience-based architectural viewpoint that revolves around circuit breakers, fallback plans, and graceful degradation systems that are specific to machine-learning-reliant systems. Circuit breakers are re-conceptualized as resilience to erratic inference behavior and delays in decision-making; fallback strategies are re-conceptualized as goal-preserving, which does not lead to dramatic service outages but gradual decay in decision faithfulness; and graceful degradation is re-conceptualized as a controlled decline in decision faithfulness as opposed to a sudden crash in the service

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Published

15-12-2023

Issue

Vol. 7 No. 6 (2023): November-December

Section

Research Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

https://creativecommons.org/licenses/by/4.0

How to Cite

[1]
Sheriff Adepoju, “Cascading Failure Modes in Model-as-a-Service Architectures : When Your Dependencies Think”, Int J Sci Res Civil Engg, vol. 7, no. 6, pp. 109–120, Dec. 2023, doi: 10.32628/IJSRCE237530.