# US 2026/0087352 A1 · Ai-powered adaptable drift management system for computer servers

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- Number: US 2026/0087352 A1
- Document ID: US20260087352A1
- Status: Published application
- Kind: A1
- Application number: 18/897,317
- Filed: 2024-09-26
- Published: 2026-03-26
- Earliest claimed: 2024-09-26
- Assignees: Bank of America Corporation
- Applicants: Bank of America Corporation
- Inventors: Amer Ali; Mohammad Saleem Gaziani; Aaron Gee; Aisha Jenkins; John Lozes; Tonya Kyra Miller; Manonmani Palanichamy; Naresh Kumar Petapalle; Aravind Singtalur; Pramod Bhadravathi Srinivasa; Asha Thekkumpurath; Andrea M. Weisberger
- Web page: https://patentgrep.com/patent/US20260087352A1

## CPC

- G06N 3/09: Supervised learning
- G06F 16/116: {Details of conversion of file system types or formats}
- G06N 3/084: Backpropagation, e.g. using gradient descent
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

Systems, computer program products, and methods are described herein for an AI-powered adaptable drift management system for computer servers. The present invention is configured to retrieve a server template of a server; extract template parameter values from the server template; extract data for a current server configuration of the server; generate server parameter values from the data or via feature engineering of the data; convert the generated server parameter values into a formatted file; transmit the formatted file; receive an additional formatted file containing deviated parameter values; analyze server performance under combinations of the deviated parameter values and the template parameter values; identify a combination of parameter values that optimizes server performance; adjust the server configuration using the identified combination parameter values; update the server template with the identified combination of parameter; transmit the updated server template; and transmit a report of the updates to the server template.

## Claims

### Claim 1

A system for AI-powered adaptable drift management for computer servers, the system comprising:
at least one memory device with computer-readable program code stored thereon;
at least one processing device operatively coupled to the at least one memory device, wherein executing the computer-readable code is configured to cause the at least one processing device to:
retrieve a server template of a server from the at least one memory device;
extract template parameter values from the server template;
extract hardware data, resource usage data, metrics data, and performance data for a current server configuration of the server;
generate server parameter values from the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data or via feature engineering of the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data;
convert the generated server parameter values into a formatted file;
transmit the formatted file;
receive an additional formatted file containing deviated parameter values;
analyze server performance under combinations of the deviated parameter values and the template parameter values;
identify a combination of the server parameter values and the deviated parameter values that optimizes server performance;
adjust the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance;
update the server template with the identified combination of the server parameter values and the deviated parameter values that optimizes server performance;
transmit the updated server template; and
transmit a report of the updates to the server template.

### Claim 2 (depends on 1)

The system of claim 1, wherein an external database is configured to receive and store the formatted file, and wherein the external database is operatively coupled to an engine configured to:
receive the formatted file from the external database;
extract the generated server parameter values from the formatted file;
retrieve the template parameter values from the external database;
compare the template parameter values and the generated server parameter values to identify deviations between the template parameter values and the server parameter values;
create the additional formatted file containing the deviated parameter values; and
return the additional formatted file.

### Claim 3 (depends on 2)

The system of claim 2, comprising an AI model configured to:
request historical data of the server from the external database;
receive historical data of the server;
analyze the historical data in conjunction with the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data to extract trends in the performance of the server;
generate future parameter values based on the trends that optimize the server performance; and
transmit a notification of recommended future parameter values.

### Claim 4 (depends on 2)

The system of claim 2, wherein the external database is configured to receive the updated server template and update the current template parameter values with the updated template parameter values of the updated server template.

### Claim 5 (depends on 1)

The system of claim 1, comprising an AI model configured to:
input a combination of the template parameter values and the deviated parameter values on a test server;
run the test server under the combination;
monitor the performance of the test server under the combination;
extract hardware data, resource usage data, metrics data, and performance data for the test server under the combination;
generate an overall performance metric for the test server under the combination;
compare the overall performance metric against a previous overall performance metric;
store the better performing of the overall performance metric and the previous overall performance metric; and
repeat for a new combination of the template parameter values and the deviated parameter values.

### Claim 6 (depends on 5)

The system of claim 5, wherein the AI model is configured to transmit and receive instructions from a DevOPs tools and to automate DevOPs processes.

### Claim 7 (depends on 1)

The system of claim 1, wherein executing the computer-readable code is configured to cause the at least one processing device to, before adjusting the server configuration:
determine if changes to the server configuration caused by adjusting the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance satisfy a threshold;
if the changes satisfy the threshold, request administrator authorization to update the server configuration and the server template; and
if the changes do not satisfy the threshold, update the server configuration and the server template automatically.

### Claim 8

A computer program product for AI-powered adaptable drift management for computer servers, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to:
retrieve a server template of a server;
extract template parameter values from the server template;
extract hardware data, resource usage data, metrics data, and performance data for a current server configuration of the server;
generate server parameter values from the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data or via feature engineering of the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data;
convert the generated server parameter values into a formatted file;
transmit the formatted file;
receive an additional formatted file containing deviated parameter values;
analyze server performance under combinations of the deviated parameter values and the template parameter values;
identify a combination of server parameter values and deviated parameter values that optimizes server performance;
adjust the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance;
update the server template with the identified combination of the server parameter values and the deviated parameter values that optimizes server performance;
transmit the updated server template; and
transmit a report of the updates to the server template.

### Claim 9 (depends on 8)

The computer program product of claim 8, wherein an external database is configured to receive and store the formatted file, and wherein the external database is operatively coupled to an engine configured to:
receive the formatted file from the external database;
extract the generated server parameter values from the formatted file;
retrieve the template parameter values from the external database;
compare the template parameter values and the generated server parameter values to identify deviations between the template parameter values and the server parameter values;
create the additional formatted file containing the deviated parameter values and;
return the additional formatted file.

### Claim 10 (depends on 9)

The computer program product of claim 9, comprising an AI model configured to:
request historical data of the server from the external database;
receive historical data of the server;
analyze the historical data in conjunction with the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data to extract trends in the performance of the server;
generate future parameter values based on the trends that will optimize the server performance; and
transmit a notification of recommended future parameter values.

### Claim 11 (depends on 9)

The computer program product of claim 9, wherein the external database is configured to receive the updated server template and update the current template parameter values with the updated template parameter values of the updated server template.

### Claim 12 (depends on 8)

The computer program product of claim 8, comprising an AI model configured to:
input a combination of the template parameter values and the deviated parameter values on a test server;
run the test server under the combination;
monitor the performance of the test server under the combination;
extract hardware data, resource usage data, metrics data, and performance data for the test server under the combination;
generate an overall performance metric for the test server under the combination;
compare the overall performance metric against a previous overall performance metric;
store the better performing of the overall performance metric and the previous overall performance metric; and
repeat for a new combination of the template parameter values and the deviated parameter values.

### Claim 13 (depends on 12)

The computer program product of claim 12, wherein the AI model is configured to transmit and receive instructions from a DevOPs tools and to automate DevOPs processes.

### Claim 14 (depends on 8)

The computer program product of claim 8, wherein the code causes the apparatus to, before adjusting the server configuration:
determine if changes to the server configuration caused by adjusting the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance satisfy a threshold;
if the changes satisfy the threshold, request administrator authorization to update the server configuration and the server template; and
if the changes do not satisfy the threshold, update the server configuration and the server template automatically.

### Claim 15

A method for AI-powered adaptable drift management for computer servers, the method comprising:
retrieving a server template of a server;
extracting template parameter values from the server template;
extracting hardware data, resource usage data, metrics data, and performance data for a current server configuration of the server;
generating server parameter values from the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data or via feature engineering of the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data;
converting the generated server parameter values into a formatted file;
transmitting the formatted file;
receiving an additional formatted file containing deviated parameter values;
analyzing server performance under combinations of the deviated parameter values and the template parameter values;
identifying a combination of server parameter values and deviated parameter values that optimizes server performance;
adjusting the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance;
updating the server template with the identified combination of the server parameter values and the deviated parameter values that optimizes server performance;
transmitting the updated server template; and
transmitting a report of the updates to the server template.

### Claim 16 (depends on 15)

The method of claim 15, wherein an external database is configured to receive and store the formatted file, and wherein the external database is operatively coupled to an engine configured for:
receiving the formatted file from the external database;
extracting the generated server parameter values from the formatted file;
retrieving the template parameter values from the external database;
comparing the template parameter values and the generated server parameter values to identify deviations between the template parameter values and the server parameter values;
creating the additional formatted file containing the deviated parameter values; and
returning the additional formatted file.

### Claim 17 (depends on 16)

The method of claim 16, comprising an AI model configured for:
requesting historical data of the server from the external database;
receiving historical data of the server;
analyzing the historical data in conjunction with the extracted hardware data, the extracted resource usage data, the extracted metrics data, and the extracted performance data to extract trends in the performance of the server;
generating future parameter values based on the trends that will optimize the server performance; and
transmitting a notification of recommended future parameter values.

### Claim 18 (depends on 16)

The method of claim 16, wherein the external database is configured for receiving the updated server template and updating the current template parameter values with the updated template parameter values of the updated server template.

### Claim 19 (depends on 15)

The method of claim 15, comprising an AI model configured for:
inputting a combination of the template parameter values and the deviated parameter values on a test server;
running the test server under the combination;
monitoring the performance of the test server under the combination;
extracting hardware data, resource usage data, metrics data, and performance data for the test server under the combination;
generating an overall performance metric for the test server under the combination;
comparing the overall performance metric against a previous overall performance metric;
storing the better performing of the overall performance metric and the previous overall performance metric; and
repeating for a new combination of the template parameter values and the deviated parameter values.

### Claim 20 (depends on 8)

The method of claim 8, wherein the method comprises, before adjusting the server configuration:
determining if changes to the server configuration caused by adjusting the server configuration using the identified combination of the server parameter values and the deviated parameter values that optimize server performance satisfy a threshold;
requesting, if the changes satisfy the threshold, administrator authorization to update the server configuration and the server template; and
updating, if the changes do not satisfy the threshold, the server configuration and the server template automatically.