Microservices architecture has become a dominant approach for building scalable, resilient, and flexible applications. However, monitoring these microservices presents unique challenges due to their distributed nature, fixed or limited resources, enterprise scale, and the dynamic nature of environments, such as Kubernetes clusters. The result is that in-process application agents often introduce significant overhead because they rely on intrusive instrumentation and frequent polling.