In this article, we focus on implementing error rate-based detection for log analysis, enhancing your system's ability to detect anomalies related to error frequency.
By updating the LogEvent model to include HIGH_ERROR_RATE, we can efficiently signal elevated error levels and adjust our detection mechanisms accordingly.
The revised LogEntry now contains crucial information like ipAddress and isError flag to provide better context for tracking and analyzing potential system issues.
This implementation not only improves real-time anomaly detection but also helps in dynamically adjusting error thresholds based on observed system behavior.
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