The shift-left principle in the industry requires us to test a software application as early as possible. Particularly, when code changes in a microservice application are committed to the code repository, we have to efficiently identify all public microservice interfaces impacted by the changes, such that the impacted interfaces can be tested as soon as possible. However, developing an efficient change impact analysis is extremely challenging in microservices because of the multilingual problem: microservice applications are often implemented using varying programming languages and involve diverse frameworks and configuration files. To address this issue, this paper presents Microscope, a language-agnostic change impact analysis that uniformly represents the code, configuration files, frameworks, and code changes by relational Datalog rules. Microscope then benefits from an efficient Datalog solver to identify impacted interfaces. Experiments based on the use of Microscope in a leading software company demonstrate that Microscope is both effective and fast as it successfully identifies interfaces impacted by 112 code commits, with moderate time overhead, and could reduce 97% of interfaces to test and save 73% of testing time after code changes.