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
- CPU by System
- CPU by WLM Importance Level
- CICS CPU per Transaction
- Db2 Getpage Rate
- Coupling Facility Request Rate
- Batch Job Elapsed Time
- CICS Max Tasks
- Health Insights and Change Detection
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