Workbench Anomaly Detection (AD) is a Machine Learning (ML) feature of Workbench.
With Workbench Anomaly Detection (AD) installed, the customer is able to observe unusual, anomalous events.
Use the Workbench Anomaly Detection (AD) feature to visualize Workbench Insights in the dedicated Workbench Insights Console, these Insights will be autonomously and predictively raised based on abnormal/unusual/anomalous modelled analysis of ingested metric data (i.e. CPU/RAM/DISK/NETWORK Metrics).
Key AD Features
- A dedicated Workbench Insights Console to view and analyze anomalies
- Workbench Anomaly Detection can proactively, autonomously and predictively detect anomalous events/issues based on Workbench ingested Metric data
- Example shipped Anomaly Detection Insights Dashboards and Visualizations providing an at-a-glance view of anomalies
- A graphical/textual "Correlation" view of Workbench Insights providing additional anomaly context
- Self-learning Machine Learning model based on the Workbench stored metric data (i.e. CPU/RAM/DISK/NETWORK) ingested from remote hosts via Workbench Remote Agents
- Workbench Anomaly Detection is high availability capable; installing 2 or more AD Nodes/Hosts at each Data-Center enables AD HA
- Workbench Anomaly Detection 9.2 is only compatible with Genesys Workbench 9.2+
- The Workbench 9.2 core components (i.e. WB IO, WB Elasticsearch, WB Kibana, WB Logstash, WB Heartbeat, WB ZooKeeper, WB Agents [for WB Hosts] and Workbench Agent Remotes [WAR's for remote Hosts]) should be installed prior to installing the Workbench Anomaly Detection (AD) 9.2 components
- The Anomaly Detection components must be installed on separate hosts from the Workbench (WB) core components - i.e. do NOT install AD on the WB Hosts
This page was last edited on January 7, 2022, at 16:09.
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