{"ID":2882017,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.11571","arxiv_id":"2508.11571","title":"Temporal Network Analysis of Microservice Architectural Degradation","abstract":"Microservice architecture can be modeled as a network of microservices making calls to each other, commonly known as the service dependency graph. Network Science can provide methods to study such networks. In particular, temporal network analysis is a branch of Network Science that analyzes networks evolving with time. In microservice systems, temporal networks can arise if we examine the architecture of the system across releases or monitor a deployed system using tracing. In this research summary paper, I discuss the challenges in obtaining temporal networks from microservice systems and analyzing them with the temporal network methods. In particular, the most complete temporal network that we could obtain contains 7 time instances and 42 microservices, which limits the potential analysis that could be applied.","short_abstract":"Microservice architecture can be modeled as a network of microservices making calls to each other, commonly known as the service dependency graph. Network Science can provide methods to study such networks. In particular, temporal network analysis is a branch of Network Science that analyzes networks evolving with time...","url_abs":"https://arxiv.org/abs/2508.11571","url_pdf":"https://arxiv.org/pdf/2508.11571v1","authors":"[\"Alexander Bakhtin\"]","published":"2025-08-15T16:26:20Z","proceeding":"cs.SE","tasks":"[\"cs.SE\",\"cs.DM\"]","methods":"[]","has_code":false}