Microservices architectures have become the cornerstone of modern software development, enabling scalable, flexible, and resilient systems. Despite their advantages, the distributed nature of microservices introduces substantial challenges in communication efficiency, security, and testing reliability. This study investigates the integration of advanced communication protocols, encryption methods, and intelligent testing frameworks to enhance both security and performance in microservices ecosystems. Specifically, we examine gRPC as a high-performance communication protocol compared to traditional REST and SOAP approaches, emphasizing the role of HTTP/3 and AES-256 encryption in securing inter-service communication (Khan & Ahamad, 2024; Newton Hedelin, 2024; Sangwai et al., 2023). Further, we explore the adoption of machine learning-based test automation to improve fault detection and coverage effectiveness, analyzing its impact on development workflows and software quality (Nama et al., 2021; Kochhar et al., 2015; Inozemtseva & Holmes, 2014). The study also examines API management practices and contract testing strategies to ensure reliable interactions in distributed environments (Owen, 2025; Sagar Kesarpu, 2025). Additionally, the integration of security controls within DevSecOps pipelines is assessed, highlighting both the challenges and practical solutions for contemporary software development (Sinan et al., 2025; Mousavi et al., 2025). Our findings demonstrate that leveraging modern communication protocols, robust encryption, intelligent testing, and structured API management significantly enhances the performance, reliability, and security of microservices-based systems. These insights provide a foundation for both academic research and practical implementation in industrial software engineering environments.

Microservices, API Management, Machine Learning Testing

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