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How OnCommand Insight anomaly detection works

OnCommand Insight contains machine-learning anomaly detection analytics to identify the normal operating workload range for an application and identify 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.

Anomaly analysis provides proactive visibility into the infrastructure supporting business critical applications and informs you of performance anomalies before they become service disruptions.

Anomalies are items, events, or observations that do not conform to an expected pattern or other items in a dataset. You 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