Synthetic Aperture Radar (SAR) is rapidly becoming a key dataset in geospatial investigation. Unlike many other observational methods, SAR is not limited by illumination or cloud cover. In recent years, due to an ever-increasing number of orbital SAR instruments, and more yet to come, there has been a significant increase in data quality and availability requiring processing software to evolve. As a result, automated SAR-based analytical workflows can now run at-scale to solve problems across a wide range of disciplines including disaster preparation and response, urban development and land use, agriculture, change detection, and monitoring across land and sea.