How OnCommand Insight anomaly detection works

OnCommand Insight contains machine-learning anomaly detection analytics which provide visibility into an application's infrastructure and identifies performance anomalies before they become service disruptions.

Anomaly analysis helps you identify the normal operating workload range for an application and informs when changes in performance are outside of expected levels. The application anomaly detection engine ingests performance metrics collected by Insight and identifies anomalies in the application infrastructure.

You can use anomaly detection to perform these tasks:
The anomaly detection engine uses Insight data for application analysis. When monitoring is first started, up to 14 days of historical performance data can be ingested by the analysis engine. Data is collected for weeks or even months, providing more accurate data about a given resource. The data includes totals for the following counters:
Objects Counter
VM Latency, IOPS
Hypervisor CPU utilization, IOPS
Edge port BB credit zero
Storage Node Latency, utilization, IOPS
Volume Latency, IOPS
Internal volume Latency, IOPS
Storage pool IOPS, utilization

Data collected by the anomaly detection engine is archived when Performance Data Archiving is enabled on the Insight server. See the System Health page to determine if archiving is enabled.

The anomaly detection engine is runs on a separate server than the Insight server. It can be configured on a physical machine or a VM. See the OnCommand Insight Installation Guide for Windows or Linux for more information.