Recent advances in distributed fiber optic sensing enable new opportunities in geotechnical monitoring and characterization. Distributed acoustic sensing (DAS) is a distributed fiber optic sensing technology relying on Rayleigh light backscattering to detect and locate disturbances in near real-time along tens of kilometers of fiber optic cable. The dynamic strain sensing capabilities of DAS have prompted numerous research initiatives from the seismology community over the past decade. Although research on DAS for seismic applications is well established, studies on DAS for geotechnical monitoring applications are less common. Here, we present results from two studies involving DAS for geotechnical monitoring at a tailings storage facility and at a slow-moving landslide. The first study considers DAS data acquired from May to September 2021 at an active mine site in northern Canada. The fiber optic cable was buried ~1 m below ground level, along the downstream crest of multiple tailings dams. The data were processed and analysed using a method known as passive seismic interferometry, to infer changes of seismic velocities in the subsurface. A correlation between the seismic velocity changes and daily resampled surface-temperature variations was observed. The results highlight that surface-temperature variations may impact seismic velocity changes at the observation depth [1]. The second study considers data from the Hollin Hill Landslide Observatory. DAS data were acquired by the British Geological Survey and OptaSense, over a three-day period of rainfall. The low frequency (<1 Hz) components of the data are studied to resolve propagation of transient near-surface strain fronts in time and space. Displacement changes inferred from DAS strain correlate with nearby in-situ geotechnical instrumentation (ShapeArraysTM). Our work supports the interpretation of the triggering and retrogression failure mechanism of the landslide [2]. This presentation will synthesize the findings from these case studies and discuss considerations of DAS for geotechnical monitoring applications.