Consider this example: A company virtualized much of its data center and suddenly a user's application became non-responsive. After two days of work, application support realized a server the application depended on had been converted to a VM, yet the application was still making calls to the original physical machine.

An application-centric ASM approach would have mapped shifting application relationships as they migrated to a virtual infrastructure, allowing support to follow the application, isolate the problem, and save days and thousands of dollars in downtime and diagnostics.

Physical-to-Virtual (P2V) projects

The application-centric approach also becomes an imperative as dynamic data centers change the shape of the application ecosystem. For example, virtualization can add a processing strain by offloading network I/O, which goes beyond simply stacking too many VMs on top of a host server. Virtualization causes network I/O -- and often storage I/O -- to be handled multiple times by the same CPU complex. This generates new CPU overhead directly associated with I/O functions.

As the number of transactions and dependencies involved in that environment grow (such as those associated with n-tier business applications and service-oriented architecture deployments) applications do not scale as simply as one might expect. Applications and infrastructure teams need to do their homework on application I/O to prepare for increased CPU utilization in advance of a P2V conversion. To accomplish this, they need tools that can monitor these issues in real time as their VM environments change.