  Cloud computing has made federated database systems (FDBS) significantly more
practical to implement than in the past. As part of a recent Web-based
Geographic Information System (WebGIS) project, we are employing cloud-native
technologies (from the container ecosystem) to develop a federated database
(DB) infrastructure, to help manage and utilise the distributed and various
geospatial data. Unfortunately, there seem to be inherent challenges and
complexity of applying the container and Kubernetes technologies to building
and running DB systems. Considering that most of the geospatial and theme data
are pre-obtained and fixed in our WebGIS project, we decided to focus on the
read-only user queries and still resort to Kubernetes to implement an FDBS
instance to use. Unlike the de facto practices (e.g., using the StatefulSets
mechanism, extending Kuberentes APIs, or employing KubeFed), our solution for
Kubernetes-aided FDBS simplifies the tech stack by investigating the fractal
object of federated data management, inclusively containerising DB instances,
and using the lightweight Deployment mechanism to handle stateless DB
containers. Overall, this research not only reveals an easy-to-implement
approach to constructing read-only components in a fully-fledged FDBS, but also
proposes and demonstrates a novel methodology for FDBS investigations.
