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Train events to identify event anomalies

See this idea on ideas.ibm.com

Events are received continuously and have a corresponding/expected payload which is used to perform important backend processing, e.g. policies will trigger incident creation based on field values, events are grouped based on scope values settings, events are associated to topology resources based on their matchToken values. If  event data sources like a SCOM or Zabbix system will change the payload due to updates or config changes, the backend processing might stop to work. If the events would be trained, AiOps would know how typical events will look like (field value settings) and can detect anomalies if a value does change suddenly, a field becomes empty which is wasn't before or is completly missing in the payload. Detecting these kind of deviations are hard to be executed by an human being but AI can easily learn the "normal" event payload (baseline) and detect anomalies if events start to look different than before.

Idea priority Urgent
  • Guest
    Reply
    |
    Apr 2, 2025

    I am confused about "learn normal event payloads (baseline)".
    I know we can learn metrics (which are time series data) with a baseline and detect anomalies when deviating from it, but I cannot match this on events. Events are not time series based, they come in asynchronously with not time series, so the MAD component would not be applicable (when adding a Gateway or connector for it to MAD). And I am not aware of any other training module learning these event anomalies You say, it "It's essential to distinguish between metrics and events" and I agree, this actually makes up my confusion. So how would we be able to detect "event anomalies" then?
    To be more clear, the event anomaly would be in case of the "payload format". As an example: normally a Zabbix would always send events with 5 fields set and an anomaly here would be, if this changes suddenly from 5 to 6 fields, or if field no. 3 always has a text string as content but now suddenly the field is empty (or including an integer values instead. But the standard payload format depends on the sender (source). For other senders like Instana, there are for example 10 (partially different) fields and those have no relationship to the Zabbix events at all. So this request is about learning how a common event payload of a sender looks like and if it changes suddenly (called as event anomaly here, maybe the term is not the right one and causing the confusion).
    Does this make sense or should be plan for a quick meeting to discuss it for clarification?

  • Guest
    Reply
    |
    Mar 31, 2025

    I will get in touch with you directly for more context during this week. Thx Detlef