Cost Estimate - Predicted Resource Usage
A cost estimate in the mainframe context refers to the prediction of resource consumption (e.g., CPU cycles, I/O operations, memory, storage) required to execute a specific workload, job, transaction, or application component on an IBM z/OS system. Its primary purpose is to provide insight into potential operational expenses, facilitate capacity planning, and aid in performance optimization.
Key Characteristics
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- Resource-centric: Focuses on quantifiable resource units such as
MSUs(Millions of Service Units),CPU time,EXCPs(Execute Channel Programs for I/O),DASDspace, andmemoryusage, which directly translate to operational costs. - Predictive: Involves analyzing historical
SMF(System Management Facilities) data, job profiles, program logic, and system configurations to forecast future resource needs for new or modified workloads. - Variability: Estimates can vary significantly based on factors like input data volume, transaction rates, system load, program efficiency (e.g.,
COBOLcode quality), and underlying hardware/software configurations. - Tools-assisted: Often relies on specialized mainframe performance and capacity planning tools,
SMFdata analysis utilities,RMF(Resource Measurement Facility) reports, and statistical analysis software (e.g.,SAS). - Iterative and Refinable: Initial estimates are often refined over time as actual usage data becomes available during testing or production, leading to more accurate models.
- Granular: Can range from high-level estimates for entire applications or
LPARs to detailed predictions for individualJCLjob steps,CICStransactions, orDB2queries.
- Resource-centric: Focuses on quantifiable resource units such as
Use Cases
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- Capacity Planning: Determining if existing
LPARs,CPCs (Central Processor Complexes), or storage subsystems have sufficient resources to handle new applications, anticipated growth, or peak workloads without impacting performance. - Chargeback/Showback: Allocating operational costs to specific departments, projects, or business units based on their estimated or actual resource consumption, fostering accountability.
- Performance Tuning and Optimization: Identifying resource-intensive jobs, programs, or transactions that exceed their estimated usage, prompting investigation and optimization efforts (e.g.,
COBOLcode refactoring,JCLtuning,DB2query optimization). - Budgeting and Financial Forecasting: Providing data for IT budget allocation, forecasting future mainframe operational expenses, and justifying hardware/software upgrades.
- Workload Management: Guiding decisions on workload placement, scheduling, and prioritization within
WLM(Workload Manager) policies to ensure critical applications meet their service goals.
- Capacity Planning: Determining if existing
Related Concepts
Cost estimates are intrinsically linked to SMF and RMF data, which provide the raw metrics for actual resource consumption and form the empirical basis for historical analysis and future predictions. They directly inform WLM policies by providing insights into the resource demands of different service classes and workloads. Furthermore, accurate estimates are crucial for effective capacity planning and performance management, ensuring that the mainframe environment can meet service level agreements (SLAs) efficiently and cost-effectively.
- Baseline Regularly: Establish a comprehensive baseline of resource usage for existing workloads using
SMFandRMFdata to provide a reliable reference point for new estimates and identify deviations. - Incorporate Growth Factors: Account for anticipated data growth, transaction volume increases, and new application deployments when making future resource predictions to avoid underestimation.
- Validate Estimates Against Actuals: Systematically compare estimated resource usage with actual consumption post-implementation or during testing phases, and adjust estimation models and assumptions as needed for continuous improvement.
- Leverage Specialized Tools: Utilize mainframe performance monitoring and capacity planning tools (e.g., IBM Z Performance and Capacity Analytics, third-party vendor solutions) for more accurate, automated, and sophisticated estimations.
- Document Assumptions: Clearly document all assumptions made during the estimation process (e.g., input data size, transaction rates, system configuration, program efficiency) to ensure transparency, facilitate future reviews, and aid in troubleshooting discrepancies.