Visualizing Kubernetes Distributed Systems: An Exploratory Study

TL;DR: This study aims to analyze and evaluate existing software visualization tools for distributed applications on the Kubernetes platform, and proposes guidelines followed by a synthesized visualization that can guide further research and development in this area.

Abstract: Distributed applications running on virtualization- based systems and cloud computing have become popular solutions, allowing developers to focus on application logic rather than dealing with the complexities of distributed systems. However, these applications often become increasingly complex, presenting multiple management challenges. To address this issue, software visualization approaches offer valuable solutions by pro-viding real-time insights into resources and their functionalities, offering a comprehensive overview. This study aims to analyze and evaluate existing software visualization tools for distributed applications on the Kubernetes platform. The objective is to comprehensively examine these tools' features, capabilities, and limitations to understand their effectiveness in visualizing complex distributed systems. Our findings provide valuable insights into the strengths and weaknesses of the available visualization tools, enabling researchers and practitioners to make informed decisions and advancements in software visualization for distributed applications on the Kubernetesplatform. Our research identified eight Kubernetes visualization tools, which were examined and compared based on relevant char-acteristics related to distributed applications and software vi-sualization standards. However, it is worth noting that despite the excellent work done by the community in establishing these first proposals, these tools currently only support, on average, a visualization of 9 % of the total resource types available, as mentioned in the official documentation. Therefore, we propose guidelines followed by a synthesized visualization that can guide further research and development in this area. Our study will assist users in selecting the most suitable Kubernetes visualization tool and encourage researchers and the community to explore new approaches in Kubernetes visualization.