Dynamic allocation algorithm for power computing resources in a digital microservices architecture

The traditional power computing resource allocation algorithm adopts a fixed allocation mode based on historical data, which is difficult to adapt to dynamic business needs and has low resource utilization efficiency. Therefore, this study investigates a dynamic allocation algorithm for power computing resources within a digital microservices architecture. A power computing resource model is established to measure the degree of resource compatibility between resources and power tasks. A digital microservices collaborative architecture for power computing resources is constructed, partitioning resources into multiple microservice modules and defining collaborative mechanisms. Leveraging the resource model's precise understanding of resources and the flexible support of the collaborative architecture, task weights and priorities are dynamically assigned based on real-time resource status and task requirements, achieving optimal resource allocation. The experimental results show that the resource utilization rate of the method proposed in this paper can reach up to 92%, providing new theoretical methods and practical ideas for dynamic allocation of power computing resources.