Software systems are often built on microservices, which are small, independent applications developed by different teams that interact to meet enterprise needs. Microservices are commonly used for flexibility and scalability, but while they enable decentralized development across independent teams, they add complexity because they need to be integrated, and distinct teams are not familiar with the details other teams handle. Developers and testers often struggle to comprehend how these services interact or become interdependent across teams. In the midst of system evolution, developers struggle to verify and validate that their local changes do not impact others, risking breaking system functionality before shipping updates to production and resulting in complex root cause analysis later on. There are existing tools for automated code suggestions, code summaries, and microservice dependency visualizations to aid final integration; however, they either have a marginal impact on quality assurance or require significant manual effort and runtime resource overhead. There is a notable gap regarding the verifiable impact of change on system functionality, quality, and operations in microservice systems. Lack of tooling support leads development teams to blind spots in both the comprehension and quality assurance of their updates that go to production, potentially leading to time-consuming rework and costly launch delays.