Virtualization brings together previously siloed applications, infrastructure and services via software, producing a massive collection of machine data that ranges in variety.  Traditional virtualization toolsets focus on specific vendor technology rather than the entire technology stack. As a result, they are unable to provide complete visibility across physical and virtual infrastructures. For example, a storage management tool cannot provide an answer to an application performance problem, because the inter-linkages are not apparent across silos.

With every layer in the virtualized IT stack producing massive volumes of machine data of tremendous variety and velocity, there is a need to manage, easily access and analyze this data for troubleshooting, performance management, capacity planning, security and more. The opportunity is significant and at its core is a big data problem.