High-Performance Cloud-Based System Design and Performance Optimization Based on Microservice Architecture

With the rapid advancement of cloud computing and microservice architecture, designing cloud systems based on microservices has demonstrated significant potential for delivering efficient, flexible, and highly scalable services. As cloud systems expand in scale and service complexity increases, however, microservice architectures face substantial challenges in maintaining optimal performance. This study explores strategies for constructing high-performance cloud systems within a microservice framework, focusing on three critical aspects: module partitioning, inter-service communication mechanisms, and distributed data management. Specifically, it examines methods to optimize the granularity of microservice modules to balance system maintainability with performance efficiency, and investigates communication patterns that minimize latency and reduce inter-service overhead. The study further addresses strategies for distributed data handling, ensuring consistency, fault tolerance, and scalability across heterogeneous service nodes. To enhance overall system performance, measures such as efficient service interaction protocols, automated scaling and load balancing, and comprehensive performance monitoring coupled with proactive fault detection are proposed. Collectively, these strategies provide a structured approach to designing microservice-based cloud systems that are resilient, adaptive, and capable of sustaining high throughput under dynamic workloads.