Abstract: A computer implemented method and system for detecting one or more anomaly conditions in one or more computer devices. A Machine Learning (ML) model is trained for each of the one or more computer devices to determine threshold operating values for time-based metric data associated with each of the one or more computer devices. Utilizing the trained ML model, time-based metric data is compared for each of the one or more computer devices to the determined threshold operating values to determine if the time-based metric data falls outside of the determined threshold operating values. Provided is notification of an anomaly condition for a computer device responsive to determining the time-based metric data falls outside of the determined threshold operating values associated with the computer device.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.

Abstract: Systems, apparatuses, and methods are described for determining a notification based on device properties. A device identification database may associate device identifications with device properties. A device identification associated with a device may be received, and corresponding device properties may be determined. Based on the device properties, a notification may be determined and sent.