With the rapid development of blockchain technology and microservices, their common characteristics have gradually attracted attention. Based on these shared features, we propose an innovative smart contract architecture aimed at significantly improving the efficiency and scalability of decentralized application systems. Our approach supports developers in writing smart contracts using multiple programming languages and optimizes system performance through load balancing and parallel execution techniques. The architecture employs a dual-layer model, with the lower layer comprising microservices responsible for core data processing and atomic operations and the upper layer integrating microservices with diverse functionalities. This structure enables a “plugand-play” mode for microservices, thereby significantly enhancing the system’s adaptability. To optimize the deployment of smart contracts on blockchain nodes, we introduce a reinforcement learning algorithm. By transforming real-world microservice demonstrations into smart contracts and evaluating various deployment strategies, we have verified the effectiveness of the proposed architecture and the outstanding performance of the Decision Transformer (DT) algorithm in smart contract deployment. This study provides new insights for the future integration of microservices and blockchain technology and offers an innovative solution for the design and implementation of decentralized applications.