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Machine Learning (ML) alerts

Container Observability creates an alert whenever there is a deviation of the container from the normal behavior and ML learns such deviations. This behavior model is built on a curated set of container metrics. Container Observability can trigger ML-based alerts for containers, nodes, and App Objects.

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Note

Note: Currently, you cannot define a new set of conditions to create a new ML model as Container Observability does not support it in the system.

ML-based Alerts help you:

  • Compare the current metric value with what the ML model expects and trigger an alert if the behavior is not as expected by the model.

  • Track the occurrence time and updated time of the anomaly.

  • Allows you to view the RCA of the anomaly that occurred to determine the possible cause and its dependencies that can likely cause an error.

  • Enables predictive analysis to isolate the cause of the problem.