About log anomaly detection - natural language

Natural language log anomaly detection is an unsupervised learning algorithm that uses Natural Language Processing (NLP) on a subset of your log data to discover abnormal behavior.

Deprecated: The natural language log anomaly detection algorithm is to be deprecated in a future release. The recommended action is to use log anomaly detection - golden signals as a replacement.

Log anomaly detection takes large amounts of log data and trains on it to learn what is normal behavior for a particular component. This model goes beyond just looking at error states or frequency of metadata around log messages. Instead, it determines when something becomes an anomaly compared to what patterns it typically exhibits.

To train this AI algorithm, you must complete some initial setup tasks, as described in Setting up training for log anomaly detection - natural language

For more information about natural language log anomaly detection, see the following topics:

• Workflow
• Examples