Datacenters have a growing need to monitor and maintain complicated computing machines and verify their systems are functioning at a high level. In order to achieve this goal, it is critical that administrators are able to readily verify basic user operations and survey system performance, quickly discerning when a configuration is sub-optimal. We have created a system health and performance monitoring tool that enables tracking both health and historical performance. The tool presents this data visually and enables the identification of realized and potential problems intuitively. This tool leverages Slurm, a workload manager common in, yet critical to High Performance Computing workflows. We construct the tool around Jenkins, a popular and well-supported testing automation framework which has been used in recent system health and regression testing, as well as PyTest, an assertion-driven Python unit test framework, after evaluating several potential automation tools and testing frameworks. This project develops a test harness for the Texas Advanced Computing Center to run multiple extendable suites of benchmarking and system health applications demonstrated on the Stampede2 and Lonestar5 HPC systems. The applications chosen to run within the test harness include existing in-house benchmarks, such as the Performance Assessment Workbench, and community benchmarks, e.g. STREAM, in addition to newly created system health monitoring scripts.