Anomaly

anomaly

Describes an anomaly or deviation detected in a system. Anomalies are unexpected activity patterns that could indicate potential issues needing attention.

Attributes

CaptionNameTypeDescription
Observation Parameter observation_parameter String The specific parameter, metric or property where the anomaly was observed. Examples include: CPU usage percentage, API response time in milliseconds, HTTP error rate, memory utilization, network latency, transaction volume, etc. This helps identify the exact aspect of the system exhibiting anomalous behavior.
Observation Type observation_type String The type of analysis methodology used to detect the anomaly. This indicates how the anomaly was identified through different analytical approaches. Common types include: Frequency Analysis, Time Pattern Analysis, Volume Analysis, Sequence Analysis, Distribution Analysis, etc.
Observations observations Observation[] Details about the observed anomaly or observations that were flagged as anomalous compared to expected baseline behavior.
Observed Pattern observed_pattern String The specific pattern identified within the observation type. For Frequency Analysis, this could be 'FREQUENT', 'INFREQUENT', 'RARE', or 'UNSEEN'. For Time Pattern Analysis, this could be 'BUSINESS_HOURS', 'OFF_HOURS', or 'UNUSUAL_TIME'. For Volume Analysis, this could be 'NORMAL_VOLUME', 'HIGH_VOLUME', or 'SURGE'. The pattern values are specific to each observation type and indicate how the observed behavior relates to the baseline.
Raw Data raw_data JSON Group:context
The event data as received from the event source.
Record ID record_id String Group:primary
Unique identifier for the object
Unmapped unmapped Unmapped[] Data from the source that was not mapped into the schema.

Relationships

Anomaly shown in context

Inbound Relationships

These objects and events reference Anomaly in their attributes:

Outbound Relationships

Anomaly references the following objects and events in its attributes:

This page describes qdm-1.5.1+ocsf-1.6.0