On Kubernetes-aided Federated Database Systems

TL;DR

This paper presents a simplified, Kubernetes-based approach for implementing read-only federated database systems in cloud environments, focusing on geospatial data management within WebGIS projects.

Contribution

It introduces a novel, streamlined methodology for deploying read-only federated databases using Kubernetes, avoiding complex extensions and focusing on containerized stateless instances.

Findings

Kubernetes can effectively support read-only federated databases.

The proposed approach simplifies deployment and management of FDBS.

Demonstrates practical application in a WebGIS context.

Abstract

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.