The budding yeast, Saccharomyces cerevisiae , has emerged as a model system for studying the aging processes in eukaryotic cells. However, the full complement of tools available in this organism has not been fully applied, in part because of limitations in throughput that restrict the ability to carry out detailed analyses. Recent advances in microfluidics have provided direct longitudinal observation of entire yeast lifespans, but have not yet achieved the normal scale of operation possible in this model system. Here we present a microfluidic platform, called the Yeast Lifespan Machine, where we combine improvements in microfluidics, image acquisition, and image analysis tools to increase robustness and throughput of lifespan measurements in aging yeast cells. We demonstrate the platform’s ability to measure the lifespan of large populations of cells and distinguish long- and short-lived mutants, all with minimal involvement of the experimenter. We also show that environmental pH is capable of significantly modulating lifespan depending on the growth media, highlighting how microfluidic technologies reveal determinants of lifespan that are otherwise difficult to ascertain.