Real-time characterization of evolving rupture is crucial for mitigating against seismic hazards exposed to potentially devastating earthquake events in EEWs (Earthquake Early Warning system). Currently, FinDer (Finite Fault Rupture Detector) algorithm explicitly utilizes observed ground motion pattern to solve for the evolving rupture to generate alerts for early warning purpose, which is currently contributing to ShakeAlert EEW system in West Coast of United States, within the area covered by the Advanced National Seismic System (ANSS) network. Here we implement FinDer offline to explore its feasibility assuming ideal field telemetry on a database of real earthquakes with magnitude M ≥5.0 occurring in Ridgecrest, Southern California in 2019. We specially focus on evaluating the performance of FinDer through end-user-orientated analysis in terms of warning time and accuracy of ground shaking prediction. Overall, FinDer classifies alerts with a rate of success over 74% across a broad range of alert criteria, substantial fraction of sites can be successfully alerted including the most difficult cases with high ground motion intensities regardless of invariable few seconds of warning time. FinDer can be configured to generate more useful alerts with higher cost savings by applying lower alert threshold during the Ridgecrest earthquake sequence. Furthermore, although large fractions of sites would have been timely alerted, it is significantly challenging for predicting accurately the moderate or worse intensities (Modified Mercalli Intensity > 5.5) in advance even if applying lower alert threshold and higher damage threshold. Nonetheless, FinDer performs well in an evolutionary manner to guarantee reliable alerts by resorting to a consistent description of point source or occurring rupture.