Forecast - Prediction

Enhanced Definition

In the mainframe context, forecasting and prediction refer to the process of analyzing historical operational data to anticipate future trends in resource consumption, system performance, and workload demands. This proactive approach helps mainframe professionals make informed decisions regarding capacity planning, performance optimization, and service delivery to ensure the continued efficiency and reliability of critical business systems.

Key Characteristics

- Data-Driven Analysis: Relies heavily on historical performance metrics collected from sources like SMF (System Management Facilities) and RMF (Resource Measurement Facility) records, application logs, and database statistics (e.g., DB2, IMS).
- Resource-Focused: Primarily concerned with predicting the future utilization of critical mainframe resources such as CPU, memory (real and auxiliary storage), I/O operations, network bandwidth, and DASD (Direct Access Storage Device) space.
- Trend Identification: Involves identifying patterns, growth rates, and cyclic behaviors (e.g., daily, weekly, monthly peaks) within the collected time-series data to project future states.
- Proactive Management: Enables system administrators and capacity planners to anticipate potential bottlenecks, resource shortages, or performance degradation *before* they impact critical business applications and user experience.
- Tool-Assisted: Often performed using specialized capacity planning software (e.g., IBM Z Performance and Capacity Analytics, third-party tools) that provides advanced analytical capabilities,