A widely used method for large scale experiment execution upon P2P or cluster computing platforms, is the exploitation of idle resources. Specifically in the case of clusters, administrators share their cluster's idle cycles into computational grids, for the execution of the so called bag-of-tasks applications. Fault-tolerance and scheduling are some of the important challenges that have arisen on the specific research field. On this paper, we present a simple, scalable, fault tolerant and user-transparent approach of harnessing idle cluster resources for executing grid bag-of-tasks applications. Our main interest lies on the large-scale deployment and evaluation of our lightweight grid computing approach, under real-life parameters. Under this context, we experiment with CIGRI and a fully transparent system-level checkpointing feature for scheduling and turnaround-time optimisation. We discuss the value of experimentation on computer science, we propose reproducible experiments based on real workload traces and we explain how our experimental methodology contributes on the development and evaluation of our grid platform.