OMEGAMON AI for CICS space

Dashboards in this space focus on identifying anomalies within CICS functioning.

Example of an OMEGAMON AI for CICS starter dashboard

The following image displays a summary view of the starter IBM Z® OMEGAMON® AI for CICS dashboard.

summary view of OM AI Insights CICS dashboard
Figure 1. A summary view of the OMEGAMON AI for CICS dashboard
drilled down view of OM AI Insights CICS dashboard
Figure 2. Drilled down view of the OMEGAMON AI for CICS dashboard
drilled down view of OM AI Insights CICS dashboard

The starter dashboard provided contains the following graphs or tables:

Table 1. Graphs and tables in OMEGAMON AI for CICS space for hourly anomalies per Region for CPU Time metrics
KPI Purpose
Header - System ID Filter on System ID
Header - Region Filter on Region Name
System ID - Top Over Consumer LPAR most affected by anomalies
Region ID - Top Over Consumer Region most affected by anomalies
[Hourly Anomalies] - Severity of anomalies Distribution of anomalies by severity
[Hourly Anomalies] - Summary table List of the pairs of System ID and Regions where anomalies are found, ordered by global severity:
  • Over Consumption: sum of anomalies for a period
  • Severity: Maximum severity of anomalies found within a specific period
  • Count of records: Number of anomalies found within the specific period
[Hourly Anomalies] - Severity of anomalies over time Time series KPI showing the severity distribution of filtered anomalies over a specific period
[Hourly Anomalies] - Detailed View Time series KPI displaying:
  • Hourly consumption for System ID and Region
  • Consumption forecast interval
  • Detected consumption anomalies
[Hourly Anomalies] - Activity - Transaction Count Region activity, transaction rate correlated to consumption
Errors - Abends count Number of abends usually related to anomalies
Resource Bottlenecks Region CPU usage provisioning
Average Wait Times Region CPU usage provisioning
Average Db2, ENQs and FC Times Detailed times where delays can happen
Top 10 - Slow Responders Top 10 region with low response time
Top 10 - High Consumers Top 10 regions with high CPU Consumption
Table 2. Graphs and tables in OMEGAMON AI for CICS space for hourly anomalies per Region for Response Time metrics
KPI Purpose
Header - System ID Filter on System ID
Header - Region Filter on Region Name
System ID - Top Slow Responder LPAR most affected by anomalies
Region ID - Top Slow Responder Region most affected by anomalies
[Hourly Anomalies] - Severity of anomalies Distribution of anomalies by severity
[Hourly Anomalies] - Summary table List of the pairs of System ID and Regions where anomalies are found, ordered by activity:
  • Transaction count: sum of transactions for a period
  • Average Response Time: Overall average response time for a period
  • Active: Whether the region is deemed active or not
  • Count of records: Number of anomalies found within the specific period
[Hourly Anomalies] - Severity of anomalies over time per activity Time series KPI showing the severity distribution of filtered anomalies over a specific period
[Hourly Anomalies] - Detailed View Time series KPI displaying:
  • Hourly average response time for System ID and Region
  • Response Time forecast interval
  • Detected response time anomalies
[Hourly Anomalies] - Activity - Transaction Count Region activity, transaction rate correlated to consumption
Errors - Abends count Number of abends usually related to anomalies
Resource Bottlenecks Region CPU usage provisioning
Average Wait Times Region CPU usage provisioning
Average Db2, ENQs and FC Times Detailed times where delays can happen
Top 10 - Slow Responders Top 10 regions with low response time
Top 10 - High Consumers Top 10 regions with high CPU Consumption