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This invention describes a way to keep an eye on how well a service is doing by regularly checking data from machines to get important performance numbers. A user can tell the system how sensitive it should be to changes, and based on that setting, the system will point out any unusual or unexpected numbers. These checks are specifically set to run on a schedule or at a certain frequency.
Why it matters: Filed before advanced machine learning models for time-series forecasting and anomaly detection became widely accessible. The "predicted value" aspect and the statistical querying needed in 2022 are now significantly easier to implement with off-the-shelf AI tools and cloud services.
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