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Proper planning helps IT organizations optimize the planning and delivery of services. Data centers typically house more computing capacity than is needed. Virtualization helps, but it still doesn’t solve the underlying problem - optimizing and managing the planning and delivery of IT services.

Capacity planning tools should play a role with virtualization, SOA, BSM, ITIL and "green" initiatives. Using these tools before and after implementation can mean the difference between sluggish response and a lean, well-oiled machine.

Getting the Information
The best capacity planning/performance management software can help you reclaim as much as 50 percent of your IT resources that are sitting idle in your data center. After discovering your underutilized resources, you will have what you need to deploy new services without spending more on capital.

By providing accurate information at the front-end, capacity planning software can predict response times from different components in a multi-tier environment and be prepared to process forecasted increases in business while meeting service level agreements without wasting resources. You can even mitigate the risk of stacking multiple applications on a single server by understanding the impact on service before consolidation.

Performance tools can also report on service levels, analyze end-to-end performance, and investigate bottlenecks in a variety of ways (e.g., drilling down to the users and processes active at the time of a problem), explore cause-effect relationships, and uncover cycles and patterns in system behavior.

The best capacity planning/performance management companies will help you reduce costs by:

• Identifying underutilized resources for redeployment
• Consolidating servers with confidence
• Meeting service levels at a minimum cost
• Accurately planning for future business requirements

Techniques for Success
A variety of capacity planning techniques is available - each useful in different situations:

Trending uses simple extrapolation of resource utilization over time. The advantage of this technique is that it does not require sophisticated tools. A spreadsheet will do, but it can be difficult to take into account non-linear behavior buried deep within a multi-tiered system.

Linear trend analysis looks at historical data and projects a linear trend line into the future, applying upper and lower confidence intervals as well as a threshold at which resources will become inadequate. This capacity planning method is a quick sanity check and identifies over-utilized resources, but it does not allow for experimentation with different configurations.

Simulation modeling, a much more sophisticated capacity planning technique than trending, actually simulates the queuing events that occur during execution. The downside of simulation modeling is that it can be time-consuming to build and run the models.

Analytic modeling uses mathematics to calculate how a queuing network will perform. A model is built based on a description of the system. From there, hypothetical changes can be made to system configuration or business workloads, and the model will predict how the changes will affect performance. Done properly, analytic modeling is a fast and accurate capacity planning technique.

Analytic modeling and load testing can be used together to determine the optimal configuration for meeting required service levels when rolling out new or modified applications. Time and cost considerations often make it prohibitive to conduct such tests on the actual hardware using production-level workloads. Instead, smaller but representative loads can be applied to a scaled-down set of test servers while performance analysis software takes a baseline reading of performance. Analytic modeling can then be used to rapidly predict how various configurations will perform under a production-level workload, all without the need to purchase and test with the actual configurations under consideration.

Continuous Cycle Capacity planning is an ongoing, strategic function that helps IT leaders address hot topics such as cost reduction, risk mitigation, alignment with business priorities and disaster recovery.

By creating an optimization plan, IT will be more proactive and will help the company meet/exceed customer expectations.