EonSight utilizes AI models and advanced analytics to detect performance anomalies. By continuously gathering essential operational data—including CPU usage, CPU Load Average, and memory utilization—it evaluates current performance metrics against historical values. This comparison allows EonSight to identify deviations from historical ranges, providing timely insights into the risk levels associated with the cluster and highlighting conditions or anomalies that may impact performance.

Procedure

1. Go to EonOne for KS > Monitor > Resource Usage
2. Click on the tab of CPU or Memory
3. You could check the resource usage historical range.
4. Abnormal intervals will be highlighted in red when actual resource usage significantly differs from the predicted range and last over 10min.

Note:

The AI needs at least 7 days resource data to analysis and generate baseline, if the data is insufficient, it will not show the baseline in graphical dashboards.