Context. Many software companies use application performance management (APM) to track the technical healthiness of their systems. Modern frameworks, that are used to instrument such systems, like OpenTelemetry or AppDynamics, allow for an easy observation of many technical metrics, such as response times, throughout or boot times. Problem. However, underneath each systems lies usually a complex business process with its own non-technical characteristics, so called domain metrics. These characteristics are often not directly observable by technical metrics, which makes them hard to measure and understand, resulting in a conceptual gap between developers and domain experts. Objective. This thesis presents the domain-driven instrumentation (DDI) approach, which eases the process of instrumenting a software system to measure domain metrics, by automatically injecting instrumentation points into a running system, based on a provided domain-architecture-mapping (DAM). Additionally, the approach is tested and demonstrate on a realistic mock system, to keep the results representative. Method. Based on these objectives, first the mock system, which is strongly based on real world industry system was developed. Then, based on the work of Hofer and Schwentner [HS21b] and Vernon [Ver13] a meta-model, that can be used to model a DAM, based on the concepts of domain-driven design (DDD) and domain storytelling (DST), was developed. This model was then implemented in to the dqualizer tool chain, and executed on the mock system, to show its feasibility. Result. The demonstration revealed, that this approach can be effectively used to instrument a modern software system for monitoring domain metrics, by successfully instrumenting the mock with tracing and metric monitoring probes. However, it also revealed some major open problems, when it comes to instrumenting asynchronous behavior on a domain level, resulting in the collection, but non-usability of some metrics. Conclusion. In conclusion, the work of the thesis was able to successfully implement and demonstrate an automated domain-driven instrumentation approach and demonstrate it on a system that is closely related to a real world setting.