Describes the baseline or expected behavior of a system, service, or component based on historical observations and measurements. It establishes reference points for comparison to detect anomalies, trends, and deviations from typical patterns.
Attributes
Section titled “Attributes”observation_parameter
- Type:
string_t - Requirement: required
The specific parameter or property being monitored. Examples include: CPU usage percentage, API response time in milliseconds, HTTP error rate, memory utilization, network latency, transaction volume, etc.
observations
- Type:
observation - Requirement: required
Collection of actual measured values, data points and observations recorded for this baseline.
observation_type
- Type:
string_t - Requirement: recommended
The type of analysis being performed to establish baseline behavior. Common types include: Frequency Analysis, Time Pattern Analysis, Volume Analysis, Sequence Analysis, Distribution Analysis, etc.
observed_pattern
- Type:
string_t - Requirement: recommended
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 the baseline behavior.