AI-Driven Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture

  • Authors

    • M. Riyaz Mohammed Assistant professor, Department of IT, Jamal Mohammed College (Autonomous), Tiruchirappalli, Tamil Nadu, India. Author

    Published 2026-01-04

  • Microservices Architecture, Monolithic Applications, AI-Driven Dependency Analysis, Application Migration, System Dependency Graph, Partition Refinement, Distributed Transactions, Performance Optimization

    Issue

    Vol. 1 No. 1 (2026)

    Section

    Articles

    How to Cite

    [1]
    R. Mohammed, “AI-Driven Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture”, IJAIDT, vol. 1, no. 1, pp. 22–28, Jan. 2026, Accessed: Mar. 02, 2026. [Online]. Available: https://worldcometresearchgroup.com/index.php/ijaidt/article/view/68

  • Abstract

    Microservices Architecture (MSA) has become a de-facto standard for designing cloud-native enterprise applications due to its efficient infrastructure setup, service availability, elastic scalability, dependability, and enhanced security. Transitioning existing monolithic systems to microservices is essential to leverage these benefits. However, manual decomposition of large-scale applications is labor-intensive and prone to errors. AI-based systems offer promising solutions for automating this process. This paper introduces CARGO (Context-sensitive lAbel pRopaGatiOn), a novel un-/semi-supervised partition refinement technique that utilizes a context- and flow-sensitive system dependency graph of monolithic applications. CARGO refines and enhances the partitioning quality of existing microservice partitioning algorithms. Experiments demonstrate that CARGO improves partition quality, reduces distributed transactions, and enhances performance metrics such as latency and throughput in microservice applications. ​

  • References

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