Within large environments, certain aspects of your system may consistently trigger alerts that are unecessary because they relate to non-severe known issues that don't require a human response. Such alert noise may come from non-critical components or build machines that are low on resources, but aren't in a critical state.
To reduce such alert noise and avoid alert spamming, the Dynatrace AI causation engine automatically detects regularly occurring issues that originate from sub-optimal, though acceptable, conditions. Dynatrace detects such frequent issues by reviewing the problem patterns of monitored entities within specified observation periods of one day and one week.
When the same problem is detected multiple times within these periods, Dynatrace evaluates the problem based on the actual severity of a threshold breach combined with the duration of the problem. It then compares the severities and durations of past problem alerts on the same entity and only alerts if the severity of the problem has increased. The following diagram illustrates this process.
Problems that are less severe and have a shorter duration than previous alerts are considered to be frequent issues and so alerts are suppressed for these. For details on event severities, see event types.
This intelligent approach to detection and handling of frequent issues guarantees that you receive alerts for problems that increase in severity over time while simultaneously avoiding alert spamming.
Entity overview pages that are subject to frequent issues include a
Frequent issue message, as shown in the example below.