Abstract: Methods, apparatus, and processor-readable storage media for implementing extensible upgrade and modification as a service are provided herein. An example computer-implemented method includes processing one or more modifiers, wherein each modifier includes an independent processing unit having a given canonical structure and is configured to execute one or more automated actions related to at least one of application modification and application migration; obtaining data pertaining to multiple applications across multiple computing environments; determining, based at least in part on processing at least a portion of the obtained data, at least one of the one or more modifiers applicable for use in executing at least one of the one or more automated actions in connection with at least a portion of the multiple applications; and executing the at least one of the one or more automated actions using the at least one determined modifier.

Abstract: A method comprises receiving data corresponding to execution of one or more applications, accessing at least one function from a codes as a service source, and training the at least one function based, at least in part, on one or more parameters, wherein the training is performed using a first portion of the data. In the method, a deployment version of the at least one function is generated based, at least in part, on the training, and the deployment version of the at least one function is applied to a second portion of the data to perform at least one service.

Abstract: A method comprises receiving data corresponding to execution of one or more applications, accessing at least one function from a codes as a service source, and training the at least one function based, at least in part, on one or more parameters, wherein the training is performed using a first portion of the data. In the method, a deployment version of the at least one function is generated based, at least in part, on the training, and the deployment version of the at least one function is applied to a second portion of the data to perform at least one service.

Abstract: A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more stored queries corresponding to the determined one or more types of the data are identified. The one or more stored queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the identified one or more stored queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Abstract: A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more queries corresponding to the determined one or more types of the data are dynamically generated. The one or more queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the one or more queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Abstract: Methods, apparatus, and processor-readable storage media for implementing extensible upgrade and modification as a service are provided herein. An example computer-implemented method includes processing one or more modifiers, wherein each modifier includes an independent processing unit having a given canonical structure and is configured to execute one or more automated actions related to at least one of application modification and application migration; obtaining data pertaining to multiple applications across multiple computing environments; determining, based at least in part on processing at least a portion of the obtained data, at least one of the one or more modifiers applicable for use in executing at least one of the one or more automated actions in connection with at least a portion of the multiple applications; and executing the at least one of the one or more automated actions using the at least one determined modifier.

Abstract: A method includes retrieving vendor specific data from one or more message oriented middleware servers of a message oriented middleware infrastructure, and inputting the vendor specific data from the one or more message oriented middleware servers into a back-end database. The vendor specific data is converted into commonly formatted data, and the commonly formatted data is inputted into a front-end database. The method also includes retrieving the commonly formatted data from the front-end database, and displaying the commonly formatted data on a user interface providing a visualization of a topology of the message oriented middleware infrastructure.

Abstract: A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more stored queries corresponding to the determined one or more types of the data are identified. The one or more stored queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the identified one or more stored queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Abstract: A method includes receiving a natural language query requesting data from a message oriented middleware infrastructure comprising a plurality of message oriented middleware providers, and analyzing the natural language query to determine one or more types of the data being requested. In the method, one or more queries corresponding to the determined one or more types of the data are dynamically generated. The one or more queries are in native command formats corresponding to respective ones of the plurality of message oriented middleware providers. The method also includes executing the one or more queries in the native command formats to retrieve the data from the plurality of message oriented middleware providers, and providing a response to the natural language query based on the retrieved data to a user via a user interface.

Abstract: A method includes retrieving vendor specific data from one or more message oriented middleware servers of a message oriented middleware infrastructure, and inputting the vendor specific data from the one or more message oriented middleware servers into a back-end database. The vendor specific data is converted into commonly formatted data, and the commonly formatted data is inputted into a front-end database. The method also includes retrieving the commonly formatted data from the front-end database, and displaying the commonly formatted data on a user interface providing a visualization of a topology of the message oriented middleware infrastructure.

Abstract: A method is disclosed including: obtaining one or more values of a system metric, the system metric being associated with a hardware resource of a computing device; detecting whether the system metric is approaching a threshold, the threshold being associated with a key performance indicator (KPI) of the computing device, the detecting being performed based on the obtained values of the system metric; calculating a predicted value of the system metric in response to detecting that the system metric is approaching the threshold, the predicted value of the system metric being calculated by using a linear predictor that is trained using unevenly-sampled training data; detecting whether the predicted value of the system metric exceeds the threshold; and reconfiguring the computing device to prevent the system metric from reaching the predicted value in response to detecting that the predicted value exceeds the threshold.

Abstract: A method is disclosed including: obtaining one or more values of a system metric, the system metric being associated with a hardware resource of a computing device; detecting whether the system metric is approaching a threshold, the threshold being associated with a key performance indicator (KPI) of the computing device, the detecting being performed based on the obtained values of the system metric; calculating a predicted value of the system metric in response to detecting that the system metric is approaching the threshold, the predicted value of the system metric being calculated by using a linear predictor that is trained using unevenly-sampled training data; detecting whether the predicted value of the system metric exceeds the threshold; and reconfiguring the computing device to prevent the system metric from reaching the predicted value in response to detecting that the predicted value exceeds the threshold.