With the continuous development of information technology and the rapid growth of data scale, traditional data processing and storage architectures have gradually exposed many bottlenecks, making it difficult to meet the high performance, high availability, and high scalability requirements of big data applications. This article proposes a resilient architecture design and implementation scheme for big data information systems based on cloud computing. This architecture utilizes the resource elasticity and scalability of cloud computing platforms to achieve dynamic adjustment and load balancing of big data processing systems. It can automatically allocate and release computing resources based on real-time load requirements, ensuring the stability and efficiency of the system when facing massive data and high concurrency access. Specifically, this article first analyzes the characteristics of big data information systems and their requirements for elastic architecture. Then, a cloud computing based elastic architecture model is designed, and containerization technology and microservice architecture are used to achieve modularity and scalability of the system. In addition, based on specific cases, this article has implemented a big data processing system based on a cloud computing platform, verifying the effectiveness and feasibility of the proposed architecture. The experimental results show that this architecture can significantly improve the performance, maintainability, and resource utilization of the system, with strong adaptability and scalability, providing a new solution for big data applications.

Hang Yang, Wanqi Zhang. Design and Implementation of Elastic Architecture for Big Data Information System Based on Cloud Computing. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 1: 80-86. https://doi.org/10.25236/AJCIS.2025.080111.

[1] Huang J. Research on Cloud Computing Resource Scheduling Method Based on Machine Learning [J]. Heilongjiang Science, 2025, (1): 124-126.

[2] Lan L, Liu Z Y. Design of power automation monitoring system based on cloud computing [J]. Electronic Engineering ＆ Product World, 2025, (1): 53-55.

[3] Zhao J. Revision and Application of The Standard for Cloud Computing Service Security Capability Requirements [J]. Information Technology ＆ Standardization. 2024, (12): 61-65.