Probe photobleaching and a specimen's sensitivity to phototoxicity severely limit the number of possible excitation cycles in time-lapse fluorescent microscopy experiments. Consequently, when a study of cellular processes requires measurements over hours or days, temporal resolution is limited, and spontaneous or rapid events may be missed, thus limiting conclusions about transduction events. We have developed ALISSA, a design framework and reference implementation for an automated live-cell imaging system for signal transduction analysis. It allows an adaptation of image modalities and laser resources tailored to the biological process, and thereby extends temporal resolution from minutes to seconds. The system employs online image analysis to detect cellular events that are then used to exercise microscope control. It consists of a reusable image analysis software for cell segmentation, tracking, and time series extraction, and a measurement-specific process control software that can be easily adapted to various biological settings. We have applied the ALISSA framework to the analysis of apoptosis as a demonstration case for slow onset and rapid execution signaling. The demonstration provides a clear proof-of-concept for ALISSA, and offers guidelines for its application in a broad spectrum of signal transduction studies.