To help enhance the value you can derive from that SMF data, IntelliMagic Vision provides two complementary types of automated anomaly detection.

  • Health insights views, which leverage best practices thresholds to detect when underlying infrastructure is at risk of not delivering responsive service, and
  • Change detection views, which detect when significant changes occur in workloads or key metrics

This video demonstrates both types of automated anomaly detection in a z/OS environment.


Use Cases for Automated Change Detection

  1. CPU by System
  2. CPU by WLM Importance Level
  3. CICS CPU per Transaction
  4. Db2 Getpage Rate
  5. Coupling Facility Request Rate
  6. Batch Job Elapsed Time
  7. CICS Max Tasks
  8. Health Insights and Change Detection

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