Organizations today are rapidly virtualizing their infrastructures. In doing so, they are experiencing a whole new set of systems management challenges. These challenges cannot be solved with traditional toolsets in an acceptable timeframe to match the velocity at which organizations are virtualizing. In a virtual server infrastructure where all resources are shared, optimal performance can only be achieved with proactive capacity management and proper allocation of shared resources.
The biggest challenge is finding the vast amount of time or automated technology to do this. Not allocating enough resources can cause bottlenecks in CPU, memory, storage and disk I/O, which can lead to performance problems and costly downtime events. However, over-allocating resources can drive up your cost per virtual machine, making a ROI harder to achieve and halting future projects.
To address this, organizations should consider a life cycle approach to performance assurance in order to proactively prevent performance issues-starting in preproduction and continually monitoring the production environments. By modeling, validating, monitoring, analyzing and charging, the Performance Assurance Lifecycle (PAL) addresses resource allocation and management. It significantly reduces performance problems, ensures optimal performance of the virtual infrastructure and helps organizations to continually meet service-level agreements (SLAs).
The following are the five components of the PAL. These components allow organizations to maximize the performance and utilization of their virtual infrastructures, while streamlining costs and delivering a faster ROI.
Component No. 1: Modeling
Modeling addresses preproduction planning to post-production additions, as well as changes to the virtual infrastructure. With capabilities to quickly model thousands of "what if" scenarios-from adding more virtual machines to changing configuration settings-IT staff can immediately see whether or not resource constraints will be exceeded and if performance issues will occur. In this way, modeling provides proactive prevention.
Four common modeling scenarios are:
1. See the effect on resource capacity and utilization of adding a new host/virtual machine or removing existing ones.
2. What will happen when a host is suspended for maintenance or a virtual machine is powered down?
3. Pre-testing VMotion scenarios to make sure sufficient resources exist.
4. How will performance be affected if resource changes are made to hosts, clusters and/or resource pools?