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.