Project CloudDrop: Reducing the Complexity of Multi-Cloud Deployments and Management Through Infinite Canvases and Multi-Layered Meta-Mapping

Abstract

This thesis explores various concepts that can simplify cloud architectures and their management, by utilizing the abilities enabled by a visual canvas. As cloud computing continues to dominate the technology landscape, the ability to efficiently manage and set up cloud environments becomes increasingly crucial. This project proposes innovative approaches to visualize and manage cloud configurations using a dynamic, user-friendly interface that reduces the cognitive load typically associated with such tasks. Visual canvases are increasingly used in various applications, offering an intuitive interface where users interact with technology beyond their display limits. These canvases typically allow for the placement of elements on an infinitely large planar surface, connecting them with lines that symbolize relationships. Although promising, there has been limited research on integrating visual canvases into cloud management systems. Through an exploratory approach involving terminology standardization, discovering relationships, and data collection, this study proposes concepts that not only support cloud administrators but also provide valuable insights for other organizational roles. The aim is to enhance the accessibility of cloud architectures, promoting a more intuitive interaction with cloud services and facilitating a better understanding of the overall architecture. The findings suggest that a visual, multi-layered approach has great potential in simplifying both cloud management and cloud architecture understanding, making it more accessible to users with different organizational roles. This research contributes to the broader field of cloud computing by providing ideas for solving the complexities of cloud architecture management, potentially leading to more efficient and comprehensible cloud architecture diagrams.