Performance analysis is vital for optimizing the execution of high performance computing applications. Today different techniques for gathering, processing, and analyzing application performance data exist. Application level instrumentation for example is a powerful method that provides detailed insight into an application’s behavior. However, it is difficult to predict the instrumentation-induced perturbation as it largely depends on the application and its input data. Thus, sampling is a viable alternative to instrumentation for gathering information about the execution of an application by recording its state at regular intervals. This method provides a statistical overview of the application execution and its overhead is more predictable than with instrumentation. Taking into account the specifics of these techniques, this paper makes the following contributions: (I) A comprehensive overview of existing techniques for application performance analysis. (II) A novel tracing approach that combines instrumentation and sampling to offer the benefits of complete information where needed with reduced perturbation. We provide examples using selected instrumentation and sampling methods to detail the advantage of such mixed information and discuss arising challenges and prospects of this approach.