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The commercial cloud offers on-demand computational resources that could be revolutionary for the seismological community, especially as seismic datasets continue to grow. However, there are few educational examples for cloud use that target individual seismological researchers. Here, we present a reproducible earthquake detection and association workflow that runs on Microsoft Azure. The Python-based workflow runs on continuous time-series data using both template matching and machine learning. We provide tutorials for constructing cloud resources (both storage and computing) through a desktop portal and deploying the code both locally and remotely on the cloud resources. We report on scaling of compute times and costs to show that CPU-only processing is generally inexpensive, and is faster and simpler than using GPUs. When the workflow is applied to one year of continuous data from a mid-ocean ridge, the resulting earthquake catalogs suggest that template matching and machine learning are complementary methods whose relative performance is dependent on site-specific tectonic characteristics. Overall, we find that the commercial cloud presents a steep learning curve but is cost-effective. This report is intended as an informative starting point for any researcher considering migrating their own processing to the commercial cloud. 

Abstract Uturuncu volcano in southern Bolivia last erupted around 250 ka but is exhibiting signs of recent activity, including over 50 yr of surface uplift, elevated seismic activity, and fumarolic activity. We studied the spatial and temporal scales of surface deformation from 1992 to 2021 to better understand subsurface activity. We tracked Uturuncu’s recent deformation using interferometric synthetic aperture radar (InSAR) data and the global navigation satellite system (GNSS) station UTUR, located near Uturuncu’s summit. We observed a spatially coherent signal of uplift from 2014 to 2021 from Sentinel-1 A/B satellites that indicates the Altiplano-Puna magma body, located 19–24 km below ground level, and previously noted as the source of the large region of deformation, is still active. The ground is now uplifting at a rate of ~3 mm/yr compared to prior rates of ~10 mm/yr. We corroborated this waning uplift with in situ data from station UTUR. We combined the Sentinel-1 data with TerraSAR-X interferograms to constrain an ~25 km2 region of subsidence located 11 km SSW of Uturuncu, with a source depth of 2.1 km below ground level to an active period of ~2.5 yr with ~5 mm/yr subsidence. We developed a conceptual model that relates these varying depths and time scales of activity in a transcrustal magmatic system. We associate the surface uplift with pressurization from ascending gases and brines from magmatic reservoirs in the midcrust. We infer the existence of brine lenses in the shallow hydrothermal system based on low subsurface resistivity correlated with surface subsidence.