MICROSERVICES ARCHITECTURE OPTIMIZATION FRAMEWORK: A DYNAMIC SERVICE MESH AND AUTOMATED FAULT MITIGATION PROTOCOL FOR SCALABLE CLOUD SOFTWARE ENGINEERING

Abstract

Distributed microservices improve deployment independence and selective scaling, but remote calls introduce communication overhead and expose applications to dependency failures. This paper proposes the Microservices Reliability and Optimization Engine (MROE), a conceptual service mesh framework that combines a streamlined proxy data plane, telemetry-informed endpoint selection, and localized circuit breaking. The design uses bounded observation windows and exponentially weighted moving averages to summarize endpoint latency, error frequency, and queue utilization. A normalized endpoint cost guides request allocation, while a circuit-breaker state machine controls isolation and gradual re-entry. The framework separates local request handling from policy distribution and makes fallback behavior dependent on application semantics. We formalize sequential-path latency and request-based availability, describe a proposed routing and isolation procedure, and define a reproducible evaluation protocol covering load, injected failures, resource consumption, and component ablations. Hypothetical numerical scenarios illustrate metric calculations; they are neither experimental measurements nor validated performance predictions. A targeted review synthesizes published empirical findings on proxy overhead, adaptive control, and policy correctness while distinguishing them from MROE validation. The contribution is an explicit integration design and a testable evaluation plan. Implementation, calibration, and controlled benchmarking are required before claims about throughput, latency reduction, availability, or recovery time can be established.