Data centers are extensively used in computer science research and development, in varying degrees for performing computations that require more power or easier access than personal computers can ever provide. Cloud service providers organize their infrastructure into multiple such data centers. These resources are effectively managed and utilized through several levels of automation. The provision of multiple such on-demand services catered by these clusters makes it a particularly challenging task for system administrators to monitor and manage these data centers. Contemporary tools and technologies for overall resource management are either commercially available or provide isolated modules in the compute monitoring and management pipeline. The temporal variations of workloads in academic institutions/data centers are huge as compared to any of the large-scale data centers of real-world businesses. Thus, it requires an efficient monitoring and management system to match the varying resource demands with the finite capacity infrastructure. This paper addresses the challenges through (i) virtualized resource allocation and monitoring (ii) an end-end pipeline with open-source tools, tailored for small and medium-scale enterprises and institutions (iii) effective visualization of the data center resource utilization.