Cloud Native GIS - The value of development velocity in GIS
summary
Argues that moving GIS to kubernetes cuts ops overhead and speeds iteration by using containers, orchestration and portability; demonstrates a Postgres cluster (kubeDB, Debian image) running in-cluster with external proxy VM for safety, a scalable GeoServer+GeoWebCache split with a small microservice to push shared config and a shared filesystem for performance. A three-person team spends ~a week on the caching proxy and a few hours on the config sync; system runs reliably with no major incidents apart from cloud-provider outages.
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chapters (10)
- 0:00Introduction to cloud native GIS
- 1:30Traditional GIS deployment challenges
- 5:16What is cloud native technology
- 7:47Kubernetes for GIS applications
- 11:46Running databases in Kubernetes
- 13:41Scaling GeoServer clusters
- 15:34GeoWebCache integration issues
- 17:20Cloud native GIS lessons learned
- 18:50Q&A on database in Kubernetes
- 20:45Q&A on cloud native effort
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