PIReporter for CICS

Performance Intelligence > Products > PIReporter for zOS > PIReporter for CICS

PIReporter for CICS provides performance data collection and analysis for CICS transactions and intervals based on performance data gathered by SMF or ASG TMON.

 

Response time is the cornerstone of CICS performance and planning for transaction performance is the key to a smooth customer experience. When performance degrades, critical CICS applications can leave users waiting and customer experience and satisfaction is often directly linked to the organization's ability to provide fast, effective service and meet performance expectations.

 

PIReporter for CICS provides vital transaction, user and interval historical performance information. Use it to analyze performance bottlenecks, spot performance trends, plan for future needs and ensure expected service levels. System managers and programmers can use the reports and the analysis provided to understand resource consumption needs, ensure appropriate service levels and utilize expensive resources effectively.

 

Additional benefits include:

· Data collection from performance records and historical archiving

· Off-loading performance data storage and analysis to a non-critical platform

· Analysis applications that allow users to author reports without IT support

· Pre-defined reports used by real-world users to solve real-world issues

· KPI-driven analysis processes help users follow best practices for CICS performance management

 

Other features and highlights of PIReporter for CICS include:

· Advanced data selection-date, system id, transaction id, user or terminal id, name pattern/exclusion lists)

· Multiple Summary Levels-transaction, user/terminal, date, time interval, system id

· KPI analysis-CPU/response time, database/file time, transaction count

· Period Comparison-tab and graphic displays for trend analysis

· Classification that helps integration between technical names and real-world projects and applications to aid with the use of performance data.

 

 

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View and Models:

Interval Analysis

Customer Analysis

Transaction Analysis

 
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