According to “IT Optimization through Predictive Capacity Management”*, an Enterprise Management Associates white paper commissioned by CA Technologies, “real-time configuration, performance, and utilization data constitutes the baseline for any accurate capacity calculation…When analyzing [this] data, it is essential to not only take a look at peak and average activity, but also include mid and long-term resource usage patterns. This information helps the IT department understand how workloads are currently growing and how they might contend for resources in the future. To ensure accuracy, capacity management software must include algorithms to validate the quality and completeness of the imported data.”
CA Capacity Management uniquely provides advanced scalability and capacity analysis for the cross-platform enterprise to provide customers with the prescriptive insight needed to make informed business decisions to enhance quality of service and quality of experience. For example, the new version of the solution helps customers to:
• Model mainframe capacity and perform what-if analyses for complete, end-to-end capacity modeling;
• Preview how applications will perform and how much they will cost when considering hybrid cloud migration initiatives;
• Efficiently reserve capacity for upcoming projects, application roll-outs, and users or companies being added to the environment; and
• Achieve greater data center efficiency, higher resource utilization rates, and even more accurate predictions on application performance with expanded support for CA Infrastructure Management and Microsoft SCOM environments.
“Virtualization and cloud computing have raised a variety of challenges for companies in managing the performance of business services. They need to anticipate how their applications will perform in new environments; if they have adequate infrastructure capacity to deliver on their SLAs; when they will need to bring additional infrastructure on-line to support demand; and whether these services are being delivered as efficiently as possible,” said Rick Fitz, Senior Vice President, Product Management, Service Assurance, CA Technologies. “The new predictive analytics capabilities in CA Capacity Management provide the insight that help IT organizations ensure the delivery of high quality, reliable services while optimizing their investment in supporting infrastructure and freeing up investment for other innovative projects.”
Customers can use the operational intelligence of CA Capacity Management to determine the impact on performance, capacity and response time as a result of changing workloads, configurations and platforms. These platforms include public cloud vendors, such as Amazon™, Microsoft®, Rackspace®, Savvis® and Verizon Terremark; virtualization platforms, such as VMware®; and hardware/OS environments, including Windows®, Linux® on either Intel® or AMD, and z/OS® on the mainframe.
“Cost analysis is very important to customers in their cloud migration initiatives and it is very cool to be able to see utilization and cost levels when comparing cloud vendor platforms for migration efforts in the new release of CA Capacity Management,” said Torsten Volk, Research Director, Systems Management, Enterprise Management Associates. “The new enhancements in the latest release of CA Capacity Management are in-line with what my current field research is producing. It is essential for organizations to take advantage of a capacity planning and analysis tool such as CA Capacity Management, especially when deploying cloud solutions.”
For more information about how CA Capacity Management enables customers improve data center efficiency, deliver on service levels and align IT with the business, please visit:
• Data Sheet
• YouTube Use Case Demo: Cost Optimize Your IT Infrastructure
• Customer Success: Global Food and Beverage Manufacturer
• Customer Success: Global Communications Service Provider
• Webcast: Capacity Management: Improving End-to-End Data Center Efficiency
• White Paper: Efficiency, Optimization and Predictive Reliability
*Source: Enterprise Management Associates, “IT Optimization through Predictive Capacity Management”, March 2012.