IAmazonCloudWatchLogs.CreateLogAnomalyDetector (CreateLogAnomalyDetectorRequest)

Method

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Creates an anomaly detector that regularly scans one or more log groups and look for patterns and anomalies in the logs.

An anomaly detector can help surface issues by automatically discovering anomalies in your log event traffic. An anomaly detector uses machine learning algorithms to scan log events and find patterns. A pattern is a shared text structure that recurs among your log fields. Patterns provide a useful tool for analyzing large sets of logs because a large number of log events can often be compressed into a few patterns.

The anomaly detector uses pattern recognition to find anomalies, which are unusual log events. It uses the evaluationFrequency to compare current log events and patterns with trained baselines.

Fields within a pattern are called tokens. Fields that vary within a pattern, such as a request ID or timestamp, are referred to as dynamic tokens and represented by <*>.

The following is an example of a pattern:

[INFO] Request time: <*> ms

This pattern represents log events like [INFO] Request time: 327 ms and other similar log events that differ only by the number, in this csse 327. When the pattern is displayed, the different numbers are replaced by <*>

Any parts of log events that are masked as sensitive data are not scanned for anomalies. For more information about masking sensitive data, see Help protect sensitive log data with masking.

Namespace: Amazon.CloudWatchLogs
Assembly: AWSSDK.CloudWatchLogs.dll
Version: 3.x.y.z