Virtual Infrastructure Optimization: Essential For Virtualizing Business-Critical Applications

As virtualization continues to be deployed with business-critical applications, IT organizations are requiring production-grade performance management and infrastructure optimization solutions to cost-effectively maintain service levels. A number of leading industry analysts have identified a new category of solutions, called Virtual Infrastructure Optimization (VIO), now emerging to address these requirements.

VIO solutions extend and enhance device management and capacity planning, efforts that are severely complicated by server and storage virtualization. The ability to quickly move virtual machines, and the dynamic nature of the connections they make to physical and virtual resources, commonly cause new levels of contention and significant capacity problems. These are not properly addressed by existing products designed for more static environments. Specifically, storage and I/O performance issues are often the biggest challenge to successful server virtualization deployments. New configuration, conflict, and contention issues arise that expose the lack of complete visibility across the server, network and storage domains. Virtual Infrastructure Optimization solutions solve this problem by offering cross-domain visibility with a focus on the performance of the entire virtual infrastructure, including deep insight into the storage area network – the biggest potential performance bottleneck. 

Virtualization Meets Business-Critical Applications

Over the last decade, server virtualization has primarily been used in the development, test and lower-end file serving applications.  Today, virtualization solutions, such as VMware, are now considered production-grade. As IT organizations deploy virtual servers into production,  it is imperative to recognize that design and deployment strategies for business-critical applications are not the same as they were in the dev/test environment.

Server consolidation initiatives for development and test generally provided users with similar or slightly improved performance, mainly due to the fact that larger, more powerful physical servers were deployed, shared storage was implemented, and dev/test virtual machines are frequently idle. Sharing actually led to better service because the shared resources were typically over-provisioned. Server consolidation ratios (enabled primarily by more efficient use of available CPU cycles) were acceptable and generated enough capital expense reductions to justify some excess capacity in the storage or memory realms. As a result, server virtualization optimization efforts to date have mainly been focused on capacity savings. Performance gains as experienced by users are an artifact, as opposed to having been architected. Contention, when it occurs, is typically resolved manually by moving a virtual machine or resizing it after users complain. 

Capacity-focused planning and reactive contention management in a virtualized production environment, can not only mask serious underlying architectural problems, but can also quickly become operationally devastating. Early-mover enterprises that have deployed business-critical applications on virtualized infrastructures have exposed many unforeseen and complex contention problems. As virtualization becomes mainstream for business-critical applications , it requires a new class of performance planning and utilization optimization tools.

You Can’t Optimize What you Can’t Measure