# US 2026/0093597 A1 · Systems and methods for monitoring and predicting technology component performance and generating real time alerts > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2026/0093597 A1 - Document ID: US20260093597A1 - Status: Published application - Kind: A1 - Application number: 18/903,660 - Filed: 2024-10-01 - Published: 2026-04-02 - Earliest claimed: 2024-10-01 - Assignees: Bank of America Corporation - Applicants: Bank of America Corporation - Inventors: John Andres Lozes; Aaron Gee; Aisha Jenkins; Andrea M. Weisberger; Aravind Singtalur; Manonmani Palanichamy; Naresh Kumar Petapalle; Mohammad Saleem Gaziani; Tonya Kyra Miller; Amer Ali - Web page: https://patentgrep.com/patent/US20260093597A1 ## CPC - G06F 11/3452: {Performance evaluation by statistical analysis} - G06F 11/0709: {in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems} - G06F 11/076: {by exceeding a count or rate limit, e.g. word- or bit count limit} - G06F 11/3006: {where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50)} - G06F 11/3065: {Monitoring arrangements determined by the means or processing involved in reporting the monitored data (error or fault reporting or logging G06F11/0766)} - G06F 11/324: {Display of status information} - G06F 2201/81: Threshold - G06F 2201/88: Monitoring involving counting - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Systems, computer program products, and methods are described herein for monitoring and predicting technology component performance and generating real time alerts. The present disclosure is configured to collect, from at least one source component, metric data at a pre-defined interval; cluster the metric data into at least one bucket based on a type of the metric data and the pre-defined interval; collect historical metric data associated with the at least one source component at a plurality of historical pre-defined intervals; apply the at least one bucket and the historical metric data associated with the at least one source component to a prediction module; and determine, by the prediction module, a predicted trend for the at least one source component. ## Claims ### Claim 1 A system for monitoring and predicting technology component performance and generating real time alerts, the system comprising: a memory device with computer-readable program code stored thereon; at least one processing device operatively coupled to the at least one memory device and the at least one communication device, wherein executing the computer-readable code is configured to cause the at least one processing device to: collect, from at least one source component, metric data at a pre-defined interval; cluster the metric data into at least one bucket based on a type of the metric data and the pre-defined interval; collect historical metric data associated with the at least one source component at a plurality of historical pre-defined intervals; apply the at least one bucket and the historical metric data associated with the at least one source component to a prediction module; and determine, by the prediction module, a predicted trend for the at least one source component. ### Claim 2 (depends on 1) The system of claim 1, wherein the prediction module comprises at least one of a least squares regression algorithm, a linear regression algorithm, a polynomial regression algorithm, a KMeans clustering algorithm, or a stepwise regression algorithm. ### Claim 3 (depends on 1) The system of claim 1, wherein the predicted trend comprises a linear trend. ### Claim 4 (depends on 1) The system of claim 1, wherein the pre-defined interval comprises at least one of a five minute interval, a minute interval, a ten minute interval, a fifteen minute interval, a thirty minute interval, or an hour interval. ### Claim 5 (depends on 1) The system of claim 1, wherein executing the computer-readable code is further configured to cause the at least one processing device to: generate a dashboard interface component comprising the metric data associated with the at least one source component at a current instance; transmit the dashboard interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and trigger a configuration of the graphical user interface of the user device with the dashboard interface component. ### Claim 6 (depends on 1) The system of claim 1, wherein executing the computer-readable code is further configured to cause the at least one processing device to: generate a prediction interface component comprising the predicted trend for the at least one source component; transmit the prediction interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and trigger a configuration of the graphical user interface of the user device with the prediction interface component. ### Claim 7 (depends on 1) The system of claim 1, wherein executing the computer-readable code is further configured to cause the at least one processing device to: determine a difference score between at least one of the metric data in the at least one bucket or the predicted trend and the historical metric data associated with the at least one source component; and compare the difference score to a difference threshold. ### Claim 8 (depends on 7) The system of claim 7, wherein executing the computer-readable code is further configured to cause the at least one processing device to: determine, based on the comparison of the difference score and the difference threshold, the difference score meets or exceeds the difference threshold; generate an alert interface component comprising the difference score and the at least one of the metric data or the predicted trend the difference score is based on; transmit the alert interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and trigger a configuration of the graphical user interface of the user device with the alert interface component. ### Claim 9 (depends on 7) The system of claim 7, wherein executing the computer-readable code is further configured to cause the at least one processing device to: determine, based on the comparison of the difference score and the difference threshold, the difference score does not meet or exceed the difference threshold; and update a dashboard interface component with the difference score, wherein the dashboard interface component further comprises the metric data associated with the at least one source component at a current instance with the difference score. ### Claim 10 A computer program product for monitoring and predicting technology component performance and generating real time alerts, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to: collect, from at least one source component, metric data at a pre-defined interval; cluster the metric data into at least one bucket based on a type of the metric data and the pre-defined interval; collect historical metric data associated with the at least one source component at a plurality of historical pre-defined intervals; apply the at least one bucket and the historical metric data associated with the at least one source component to a prediction module; and determine, by the prediction module, a predicted trend for the at least one source component. ### Claim 11 (depends on 10) The computer program product of claim 10, wherein the prediction module comprises at least one of a least squares regression algorithm, a linear regression algorithm, a polynomial regression algorithm, a KMeans clustering algorithm, or a stepwise regression algorithm. ### Claim 12 (depends on 10) The computer program product of claim 10, wherein the predicted trend comprises a linear trend. ### Claim 13 (depends on 10) The computer program product of claim 10, wherein the pre-defined interval comprises at least one of a five minute interval, a minute interval, a ten minute interval, a fifteen minute interval, a thirty minute interval, or an hour interval. ### Claim 14 (depends on 10) The computer program product of claim 10, wherein the computer program product comprising the non-transitory computer-readable medium comprising code further causes the apparatus to: generate a dashboard interface component comprising the metric data associated with the at least one source component at a current instance; transmit the dashboard interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and trigger a configuration of the graphical user interface of the user device with the dashboard interface component. ### Claim 15 (depends on 10) The computer program product of claim 10, wherein the computer program product comprising the non-transitory computer-readable medium comprising code further causes the apparatus to: generate a prediction interface component comprising the predicted trend for the at least one source component; transmit the prediction interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and trigger a configuration of the graphical user interface of the user device with the prediction interface component. ### Claim 16 A computer implemented method for monitoring and predicting technology component performance and generating real time alerts, the computer implemented method comprising: collecting, from at least one source component, metric data at a pre-defined interval; clustering the metric data into at least one bucket based on a type of the metric data and the pre-defined interval; collecting historical metric data associated with the at least one source component at a plurality of historical pre-defined intervals; applying the at least one bucket and the historical metric data associated with the at least one source component to a prediction module; and determining, by the prediction module, a predicted trend for the at least one source component. ### Claim 17 (depends on 16) The computer implemented method of claim 16, wherein the prediction module comprises at least one of a least squares regression algorithm, a linear regression algorithm, a polynomial regression algorithm, a KMeans clustering algorithm, or a stepwise regression algorithm. ### Claim 18 (depends on 16) The computer implemented method of claim 16, wherein the predicted trend comprises a linear trend. ### Claim 19 (depends on 16) The computer implemented method of claim 16, wherein the pre-defined interval comprises at least one of a five minute interval, a minute interval, a ten minute interval, a fifteen minute interval, a thirty minute interval, or an hour interval. ### Claim 20 (depends on 16) The computer implemented method of claim 16, further comprising: generating a dashboard interface component comprising the metric data associated with the at least one source component at a current instance; transmitting the dashboard interface component to a user device associated with the at least one source component, wherein the user device comprises a graphical user interface; and triggering a configuration of the graphical user interface of the user device with the dashboard interface component.