Energy-Efficient Microservices Architecture for Large-Scale E-Commerce Platforms

The more significant the e-commerce websites are and the greater the number of users and transactions each day, the greater the energy demand, both economically and environmentally. The architecture for energy efficiency without compromising performance or scalability is proposed in this paper as an AI-powered hybrid edge-cloud microservices system. The infrastructure intelligently distributes workloads across edge and cloud nodes using AI to identify traffic trends, dynamically assign resources, and run energy efficiently. The design principles are energy-aware microservices, resource scalability, and real-time energy monitoring. The solution saves on overhead using lightweight containerization and allows for elasticity to change. Testing on the ground has proven the architecture to save energy consumption at high-demand times such as Black Friday or latency-sensitive tasks such as personalized retail offers. Implementation issues, scaling of edge nodes, data security are discussed, and more generally, the consequences for viable e-commerce. It builds the basis for greener IT infrastructures and catalyzes innovation toward a sustainable digital future.