Architectural Patterns and Challenges in Spring Boot for Microservices: Evaluating Automation Strategies for Scaling, Monitoring, and Deployment in Complex Software Ecosystems

Abstract

This paper investigates the architectural patterns and challenges involved in im- plementing microservices with Spring Boot, emphasizing automation strategies for scaling, monitoring, and deployment. Microservices, though offering scalability and flexibility, introduce complexities in managing distributed systems. We explore key architectural patterns such as Service Registry and Discovery, API Gateway, Circuit Breaker, Event-Driven Architecture, and Database Per Service, which are essen- tial for creating robust and maintainable systems. The paper also addresses the challenges in scaling microservices, particularly in managing state, load balancing, distributed transactions, and handling service interdependencies. Effective scaling requires careful planning and the use of tools like Kubernetes and Spring Boot’s ecosystem. Automation plays a pivotal role in overcoming these challenges, facili- tating continuous integration and delivery (CI/CD), and enabling efficient monitor- ing and deployment strategies. We evaluate the use of Infrastructure as Code (IaC), automated monitoring with tools like Prometheus, and deployment techniques such as Blue-Green and Canary deployments, which help in minimizing downtime and ensuring seamless updates. Auto-scaling strategies, particularly in conjunction with Kubernetes, are also discussed as critical for maintaining performance under vary- ing loads. The study concludes that a combination of well-established architectural patterns and robust automation strategies is crucial for successfully deploying and managing Spring Boot microservices in complex, large-scale software ecosystems