Administration of virtualization infrastructures, such as virtual datacenters, is increasingly complex. One of the biggest challenges in virtualized deployments is keeping track of the basic health of the infrastructure. Administrators would like to quickly be informed when problems occur and would also like to have guidance about how to solve issues when they arise. These problems are frequently exacerbated as the virtualized deployments increase in scale. Conventional means for monitoring these large environments typically focus on aggregating and summarizing the amount of data to manageable quantities. Reducing this data is typically challenging, in that both identifying serious issues in the virtualization and intelligent data visualization techniques are valuable.
Automated techniques for monitoring the health of virtualization infrastructure have become increasingly prevalent and helpful. Such approaches typically leverage the collection and analysis of a large number of metrics across an environment in order to provide a concise, simplified view of the status of the entire environment. However, despite the success of such tools, significant amounts of training is often still required in order to obtain to obtain proficiency at understanding and using the output of such tools.