While the Cloud-Edge continuum scheduling domain is well studied, and proposes numerous approaches, from high-level modeling to dynamic scheduling, monitoring means are rarely debated. Solving the ever-growing number of metrics, which can exist in different units and update frequencies, support various system scales and topologies, relies upon classical 2D features (made of charts, gauges, maps and lists) without proposing visual abstractions directed towards multi-layered architectures and distributed infrastructures. Moreover, the need for monitoring in modern Edge systems and applications exceeds system metrics, as other informational dimensions can be considered, such as the ones collected through web services or IoT devices and sensors in the user spaceWe propose with Palindrome.js a 3D monitoring probe, which enables multidimensional visual modeling and analysis. Through sets of metrics called layers, Palindrome.js builds in 3D a structured visual abstraction for any problem modeled with metrics or KPIs. We present in this article the solution initial background, the related works, its design principles, discuss experimental results, and conclude with our observations and future outcomes.