Today, AWS announces the general availability of a suite of machine-learning powered log analytics capabilities in CloudWatch, including automated log pattern analysis and anomaly detection. Using these new capabilities, you will be able to easily interpret your logs, identify unusual events, and use these insights to steer and accelerate your investigation.

With ever increasing volume and complexity of log data, customers find it challenging to detect issues when they occur and quickly sift through tens of thousands of log entries to identify the root cause. Today’s announcement unlocks three new capabilities for your log deep-dives. First, the patterns view allows you to easily visualize recurring patterns while querying your logs. Second, compare mode in Logs Insights helps you quickly find “what changed” between two time periods. Third, Logs Anomaly Detection surfaces potentially anomalous trends by constantly evaluating incoming logs against historical baselines. With CloudWatch Log Anomaly Detection, you can be automatically notified of emerging issues such as new error messages occurring in your logs.

CloudWatch Logs Anomaly Detection is available in all AWS Commercial regions where Amazon CloudWatch Logs is available, excluding the AWS China (Beijing) Region, the AWS China (Ningxia) Region and AWS Israel (Tel Aviv) Region.

To get started, enable Anomaly Detection for logs groups of interest in the CloudWatch Logs console. Use the new patterns tab and compare button in CloudWatch Logs Insights console for log pattern analytics. See the CloudWatch Logs Anomaly Detection documentation and the CloudWatch Logs Insights documentation to learn more.ENnbsp;