ML-based Alert
In the Detect panel, you can view a summary of the ML-based alert specific to the container.
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Details of the anomaly, Type, and Category of the alert.
The description explains the reasons why the anomaly was triggered by ML in the system.
Click > to expand the Target that represents details of the affected entity and its dependencies that might be the cause of the anomaly predicted by ML.
The list of the top metrics that the ML found deviated from the expected values per the learned behavior model.
Click > to expand Anomaly Condition to list the following details:
State of the anomaly with the first occurrence and recent occurrence time with other details.
On the right side of the Detect panel, you can also view:
The history of logs, metrics, events, and configuration details to analyze the previous behavior of the affected container learned by ML.
Quick links to analyze the past behavior of the container are Logs, Metrics, Events, Configs, and Dashboard. Previous logs for the following:
Container: The state of the container listed in detail from the time of anomaly occurred.
Pods: The state of pods in which the container is hosted.
Nodes: The state of nodes in which the pods are hosted.
You can compare the current metric data with the previous metric through the following quick links:
Configs: You can view or download the YAML file for configuration details of the particular entity deployment.
Application state: To identify the state of containers.
Metrics history: To determine the past metric health of containers recorded at each time interval.
Events history: To determine the history of events that are created due to a state in the cluster due to container impact such as (failing, restarting, re-scheduling, or exceeding memory of the container).
Related topics: