Cloud-Native Geospatial for Small Teams

Cloud-Native Geospatial for Small Teams: How the Utah Geological Survey Did It

What happens when a small, technical team at a state agency decides to go cloud native? They don't have terabytes of satellite imagery. They have lots of small datasets, lots of scientists and lots of people who just want to get at the data.

In this episode, I talk with Marshall Robinson and Clinton Lunn from the Data Management Program at the Utah Geological Survey. They moved from a traditional ArcGIS Server setup to Postgres and GeoServer, and then to a cloud-native pipeline built on GeoParquet, PMTiles, and a STAC catalog.

What I really wanted from this conversation was recipes. Picture a GIS person at a local council (say, here in New Zealand) who's curious about this stuff and needs a proof of concept to take to their manager. Where do they start?

We talk about:

Why "it's cheaper" isn't a good enough reason to switch, and why it had to work and be better (they still turned off two servers and saved around $25,000 a year)

Adding things in slowly instead of ripping everything out. Postgres is still their source of truth, and the cloud-native layer is bolted on top

The "why should I care?" question from data users, and how one layer can be exposed 10 different ways so nobody has to change their workflow

Using industrial-strength tools on small data, and whether that's worth it

How new data gets from the field (or the core warehouse) into their public web apps

New staff who know Python, pointing your favourite LLM at a STAC catalog, and why machines finding your data matters

Where this is going: Zarr, Icechunk, time-series data and derivative products