Software sustainability is critical for Computational Science and Engineering (CSE) software. It is also challenging due to factors ranging from funding models to the typical lifecycle of a research code to the inherent challenges of running fast on the newest architectures. Furthermore, measuring sustainability is challenging because sustainability consists of many complex attributes. To identify useful metrics for measuring CSE software sustainability, we gathered data from multiple freely available sources, including GitHub, SLOCCount, and Metrix++. This paper discusses the challenges practitioners face when measuring the sustainability of CSE software. We present an analysis of data with associated observations and future directions to better understand CSE software sustainability and how this work can be used to support decisions and improve sustainability by observing trends in metrics over time.