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Release: Australia · Updated: 2026-03-12 · Official documentation · View source

How Health Log Analytics generates alerts

Health Log Analytics identifies patterns in your log data and learns pattern behavior. When HLA's AI engine detects anomalous behavior, it sends an event to the ServiceNow Event Management application. As an operator, you can use these predictive alerts to handle emerging IT issues before they impact users.

Log anomaly detection

Anomalies are abnormal or unexpected behavior that occur when activities deviate from established baselines. There are many kinds of anomalies. In this example, the system tracks the baseline rate (the average number of events per minute) for a specific log pattern. When this typically inactive log generates a spike in events, the system detects the deviation from the baseline and generates an alert.

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Anomaly seen as a spike in the rate of messages of a particular type.

Health Log Analytics uses various methods to detect anomalies and generate alerts.

Alert metrics

Health Log Analytics monitors multiple metrics in the log stream to detect anomalous behavior. Each metric is associated with a unique source: the combination of service instance and component. When the system identifies an anomalous pattern for a metric, it generates an alert.

As an operator, you can provide feedback about the generated alerts. Your feedback "teaches" Health Log Analytics that a specific alert is significant or irrelevant to you. The application then either raises the priority of the alert metric or mutes it to reduce noise.

Lexical keywords

Health Log Analytics scans your logs for words that can indicate important issues. Lexical keywords such as "crashed" or "failed" signal a condition that can merit attention.

The system sets a threshold for each lexical keyword that is based on what it considers the normal occurrence pattern and frequency of that keyword in your logs. When it scans your logs, it finds all occurrences of the keyword. If the number exceeds the threshold, it generates an alert. For more information, see View the lexical keywords that generate alerts in Health Log Analytics.

For information about managing global keywords, see Add, edit, or delete lexical keywords in Health Log Analytics. To create or delete keywords for a specific source type, see Configure source type capabilities in Health Log Analytics.

Correlations

Log correlators are keys or values in log data that detect correlations between alerts. For example, a log correlator could detect when the ID of a particular network device occurs simultaneously in multiple warnings across different service instances. For more information, see Identifying related alerts in log data by using log correlators in Health Log Analytics.

Advanced alert filtering

Add advanced log alert filters to scan alerts for conditions that you specify. The filters reduce noise by dropping alerts that do not indicate a significant issue. While developing a filter, you can test, update, publish, or activate the filter at any time. For more information, see Create advanced log alert filters.

Custom alert rules

Define a Log Analytics alert rule when you encounter log data that should generate an alert. The alert rule generates an alert for a specified metric with a threshold that you specify and sets the properties of the generated alert. For more information, see Alert rules in Health Log Analytics.

Parent Topic:Exploring Health Log Analytics