US-20260127517-A1 - TRAINING OPERATORS BASED ON HISTORICAL DATA AND USER CONTEXT

US20260127517A1US 20260127517 A1US20260127517 A1US 20260127517A1US-20260127517-A1

Abstract

Managing operator requests through intercepting, in a data processing environment, an incoming operator request from an operator, retrieving historical data related to commands and command outcomes of the operator in the data processing environment, determine a skill level of the operator based on analysis of the retrieved historical data, and predicting a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment. By blocking or allowing execution of the incoming operator request based on information about the skill level of the operator and the potential impact, the data processing environment can be secured against actions that can degrade the functioning on the environment. A skill of the operator is updated based on an outcome of the incoming operator request.

Inventors

Carl Albert Petersson
Francisco Javier Rodriguez
Hidematsu Atom Sueki
Jacob Michael Zielny

Assignees

INTERNATIONAL BUSINESS MACHINES CORPORATION

Dates

Publication Date: 20260507
Application Date: 20241107

Claims (20)

1 . A method of managing operator requests, comprising: intercepting, in a data processing environment, an incoming operator request from an operator; retrieving historical data related to commands and command outcomes of the operator in the data processing environment; characterizing a skill level of the operator based on analysis of the retrieved historical data; predicting a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment; blocking an execution of the incoming operator request based on information about the skill level of the operator and the potential impact; and updating a characterization of the skill level of the operator based on an outcome of the incoming operator request.
2 . The method of claim 1 further comprising assessing the incoming operator request for the prediction of the potential impact based on factors including dependencies and configuration changes of the data processing environment.
3 . The method of claim 1 , further comprising generating the understanding of the mode of operation of the data processing environment using a trained machine learning model.
4 . The method of claim 3 , further comprising generating the understanding of the mode of operation of the data processing environment through interpreting one or more of corpora including documentation, changelogs, past incidents, and aggregated historical actions of the data processing environment.
5 . The method of claim 1 , further comprising providing to the operator, responsive to the blocking, real-time feedback about alternative operator requests that meet a positive impact criterion.
6 . The method of claim 1 , further comprising updating a state of the data processing environment to reflect changes of the data processing environment in real time.
7 . The method of claim 1 , wherein the data processing environment is a Kubernetes-based cloud environment.
8 . The method of claim 1 , further comprising tracking an identity of the operator based on authenticating the operator.
9 . A computing device comprising: a processor; and a memory, in communication with the processor, with one or more computer program instructions stored on the memory, the computer program instructions, when executed by the processor, cause the computing device to perform operations comprising: intercepting, in a data processing environment, an incoming operator request from an operator; retrieving historical data related to commands and command outcomes of the operator in the data processing environment; characterizing a skill level of the operator based on analysis of the retrieved historical data; predicting a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment; blocking an execution of the incoming operator request based on information about the skill level of the operator and the potential impact; and updating a characterization of the skill level of the operator based on an outcome of the incoming operator request.
10 . The computing device of claim 9 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: assessing the incoming operator request for prediction of the potential impact based on factors including dependencies and configuration changes of the data processing environment.
11 . The computing device of claim 9 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: generating the understanding of the mode of operation of the data processing environment using a trained machine learning model.
12 . The computing device of claim 11 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: generating the understanding of the mode of operation of the data processing environment through interpreting one or more of corpora including documentation, changelogs, past incidents, and aggregated historical actions of the data processing environment.
13 . The computing device of claim 11 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: providing to the operator, responsive to the blocking, real-time feedback about alternative operator requests that meet a positive impact criterion.
14 . The computing device of claim 11 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: updating a state of the data processing environment to reflect changes of the data processing environment in real time.
15 . The computing device of claim 11 , wherein the data processing environment is a Kubernetes-based cloud environment.
16 . The computing device of claim 11 , wherein the execution of the program instructions by the processor further configures the computing device to perform operations comprising: tracking an identity of the operator based on authenticating the operator.
17 . A computer program product for managing operator requests, the computer program product comprising: one or more computer-readable storage devices and program instructions stored on the at least one of the one or more computer-readable storage devices, the program instructions executable by a processor, the program instructions comprising: program instructions to intercept, in a data processing environment, an incoming operator request from an operator; program instructions to retrieve historical data related to commands and command outcomes of the operator in the data processing environment; program instructions to characterize a skill level of the operator based on analysis of the retrieved historical data; program instructions to predict a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment; program instructions to block an execution of the incoming operator request based on information about the skill level of the operator and the potential impact; and program instructions to update a characterization of the skill level of the operator based on an outcome of the incoming operator request.
18 . The computer program product of claim 17 , wherein the program instructions further comprise: program instructions to assess the incoming operator request for prediction of the potential impact based on factors including dependencies and configuration changes of the data processing environment.
19 . The computer program product of claim 17 , wherein the program instructions further comprise: program instructions to provide to the operator, responsive to the blocking, real-time feedback about alternative operator requests that meet a positive impact criterion.
20 . The computer program product of claim 17 , wherein the program instructions further comprise: program instructions to track an identity of the operator based on authenticating the operator.

Description

BACKGROUND Technical Field The present disclosure generally relates to enhancing operator efficiency in IT (information technology) environments through real-time feedback and training and more particularly, to a leveraging historical data and user context to assess operator actions, blocks potentially harmful commands, and provide adaptive learning opportunities in hybrid cloud settings. Description of the Related Art Intelligent systems for workforce development and management focus on leveraging different technologies to optimize the processes of hiring, training, and managing employees. In the IT space, developers may go through structured onboarding processes to introduce them to coding standards, software architecture, and development workflows. This may help in understanding the intricacies of the codebase and processes in place to maintain code quality. Further, code reviews may be used when a developer writes new code or modifies existing code, wherein the code may be typically reviewed by peers or managers before being merged into the main codebase. This process helps catch potential issues that might disrupt existing functionality and ensures adherence to best coding practices. BRIEF SUMMARY According to an illustrative embodiment, a method discloses managing operator requests through intercepting, in a data processing environment, an incoming operator request from an operator, retrieving historical data related to commands and command outcomes of the operator in the data processing environment, and generating information about a skill level of the operator based on analysis of the retrieved historical data. The method includes predicting a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment. By blocking or allowing the incoming operator request based on information about the potential impact and a skill level of the operator, the data processing environment can be protected against actions that can degrade the functioning on the environment. A skill of the operator is updated based on an outcome of the incoming operator request. In one embodiment, upon blocking the incoming operator request in real time, real-time feedback about alternative operator requests that meet a positive impact criterion is provided to the operator. In one embodiment, the data processing environment is a Kubernetes-based cloud environment. According to an embodiment of the present disclosure, a computing device includes a processor and a memory with computer program instructions that, when executed, enable the device to intercept, in a data processing environment, an incoming operator request from an operator, retrieve historical data related to commands and command outcomes of the operator in the data processing environment, and generate information about a skill level of the operator based on contextual analysis of the retrieved historical data. The program instructions further cause the computing device to predict a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment. The program instructions further cause the computing device to block the incoming operator request based on information about the skill level of the operator and the potential impact and update the skill level value of the operator based on an outcome of the incoming operator request. According to an embodiment of the present disclosure, a computer program product includes a computer-readable storage device and program instructions executable by a processor, comprising program instructions to to intercept, in a data processing environment, an incoming operator request from an operator, retrieve historical data related to commands and command outcomes of the operator in the data processing environment, and generate information about a skill level of the operator based on contextual analysis of the retrieved historical data. The program instructions further include program instructions to cause the computing device to predict a potential impact of the incoming operator request on the data processing environment based on an understanding of a mode of operation of the data processing environment. The program instructions further include program instructions to cause the computing device to block the incoming operator request based on information about the skill level of the operator and the potential impact and update the skill of the operator based on an outcome of the incoming operator request. BRIEF DESCRIPTION OF THE DRAWINGS To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced. FIG. 1 depicts a block diagram of a network of data processing systems in accordance with an illustrative e