Real-time anomaly detection helps you respond immediately to unusual patterns as soon as they arise. This guide provides essential information to set up, configure, and optimize your online anomaly detection process using TimeGPT, ensuring timely responses in critical scenarios.

Online anomaly detection with TimeGPT helps maintain system reliability by highlighting data points that may signal emerging issues or opportunities.

Always validate flagged anomalies against known baseline patterns. False positives can occur, so track and refine parameters to improve accuracy.

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Additional Resources

Below are direct links to deeper dives and examples:

Online anomaly detection

A quick-start guide discussing setup and basic usage for TimeGPT’s online anomaly detection.

How to adjust the detection process

Learn how to fine-tune parameters such as window size, threshold values, or update frequency.

Univariate vs. multiseries anomaly detection

Explore differences between monitoring a single time series vs. multiple time series simultaneously.

Maintain continuous monitoring and regularly re-evaluate your detection thresholds to ensure optimal performance in changing environments.