This work presents a holistic approach for monitoring machining processes of an industrial deep drilling machine. For that purpose, a machine tool was equipped with a multi-sensory monitoring system with the objective to detect and assess dynamic disturbances during the machining process. Disturbances are key characteristics of deep drilling processes and are intensified due to the high length to diameter ratios. Consequently, the machining processes are sensitive to dynamic instabilities such as chatter and whirling vibrations. The developed monitoring application is highly versatile and enables conducting experimental investigations on boring and trepanning association (BTA) deep drilling, counter boring and skiving processes. Different signal processing techniques were implemented in the application, e.g. a continuous short-time Fourier transformation (STFT) for the determination of chatter and whirling vibration frequencies during the cutting process. With a non-proprietary machine-to-machine communication protocol, it is possible to regulate and control the machining processes based on the information gained during measurement and data analyses. Hence, it is possible to respond to process instabilities with a computerised procedure that is controlled by an algorithm.