Predictive and forecast reports
To ensure the IT service provider continues to provide the required service levels, the Capacity Management process must predict future workloads and growth. To do this, future component and service capacity and performance must be forecast. This can be done in a variety of ways, depending on the techniques and the technology used. Changes to workloads by the development and implementation of new functionality and services must be considered alongside growth in the current functionality and services driven by business growth. A simple example of a capacity forecast is a correlation between a business driver and a component utilization, e.g. processor utilization against the number of customer accounts. This data can be correlated to find the effect that an increase in the number of customer accounts will have on the processor utilization. If the forecasts on future capacity requirements identify a requirement for increased resource, this requirement needs to be input into the Capacity Plan and included within the IT budget cycle.
Often capacity reports are consolidated together and stored on an intranet site so that anyone can access and refer to them.
188.8.131.52 Capacity Management Information System
Often capacity data is stored in technology-specific tools and databases, and full value of the data, the information and its analysis is not obtained. The true value of the data can only be obtained when the data is combined into a single set of integrated, information repositories or set of databases.
The Capacity Management Information System (CMIS) is the cornerstone of a successful Capacity Management process. Information contained within the CMIS is stored and analysed by all the sub-processes of Capacity Management because it is a repository that holds a number of different types of data, including business, service, resource or utilization and financial data, from all areas of technology.
However, the CMIS is unlikely to be a single database, and probably exists in several physical locations. Data from all areas of technology, and all components that make up the IT services, can then be combined for analysis and provision of technical and management reporting. Only when all of the information is integrated can ‘end-to-end’ service reports be produced. The integrity and accuracy of the data within the CMIS needs to be carefully managed. If the CMIS is not part of an overall CMS or SKMS, then links between these systems need to be implemented to ensure consistency and accuracy of the information recorded within them.
The information in the CMIS is used to form the basis of performance and Capacity Management reports and views that are to be delivered to customers, IT management and technical personnel. Also, the data is utilized to generate future capacity forecasts and allow Capacity Management to plan for future capacity requirements. Often a web interface is provided to the CMIS to provide the different access and views required outside of the Capacity Management process itself.
The full range of data types stored within the CMIS is as follows.
It is essential to have quality information on the current and future needs of the business. The future business plans of the organization need to be considered and the effects on the IT services understood. The business data is used to forecast and validate how changes in business drivers affect the capacity and performance of the IT infrastructure. Business data should include business transactions or measurements such as the number of accounts, the number of invoices generated, the number of product lines.
To achieve a service-orientated approach to Capacity Management, service data should be stored within the CMIS. Typical service data are transaction response times, transaction rates, workload volumes, etc. In general, the SLAs and SLRs provide the service targets for which the Capacity Management process needs to record and monitor data. To ensure that the targets in the SLAs are achieved, SLM thresholds should be included, so that the monitoring activity can measure against these service thresholds and raise exception warnings and reports before service targets are breached.