AWS AmazonCloudWatch documentation change
Summary
Expanded anomaly detection documentation to include both continuous monitoring and query-based approaches
Security assessment
Adds documentation about machine learning-based anomaly detection features that could support security monitoring workflows
Diff
diff --git a/AmazonCloudWatch/latest/logs/LogsAnomalyDetection.md b/AmazonCloudWatch/latest/logs/LogsAnomalyDetection.md index 7564cd0f6..d388ed715 100644 --- a//AmazonCloudWatch/latest/logs/LogsAnomalyDetection.md +++ b//AmazonCloudWatch/latest/logs/LogsAnomalyDetection.md @@ -9 +9,3 @@ Severity and priority of anomalies and patternsAnomaly visibility timeSuppressin -You can create a _log anomaly detector_ for each log group. The anomaly detector scans the log events ingested into the log group and find anomalies in the log data. Anomaly detection uses machine-learning and pattern recognition to establish baselines of typical log content. +You can detect anomalies in your log data in two ways: by creating a _log anomaly detector_ for continuous monitoring, or by using the [anomaly detection](./CWL_QuerySyntax-Anomaly.html) command in CloudWatch Logs Insights queries for on-demand analysis. + +A log anomaly detector scans the log events ingested into a log group and finds anomalies in the log data automatically. Anomaly detection uses machine-learning and pattern recognition to establish baselines of typical log content. For on-demand analysis, you can use the `anomaly detection` command in CloudWatch Logs Insights queries to identify unusual patterns in time-series data. For more information about query-based anomaly detection, see [Using anomaly detection in CloudWatch Logs Insights](./LogsAnomalyDetection-Insights.html). @@ -111 +113 @@ Generate a natural language summary from CloudWatch Logs Insights query results -Enable anomaly detection on a log group +Using anomaly detection in CloudWatch Logs Insights