Abstract: A system for conserving computing and operator resources by streamlining the installation and management of applications on a remote host system, such as a cloud-based system. The system may receive from an operator, a requested modification of an application installation image stored in a secure registry of the remote host system. In response, the system may authenticate the operator, and verify that the requested modification is a permitted modification. The system can also transmit a notification of the requested modification to other operators to allow the other operators an opportunity to object to the requested modification. In the absence of objections, the system may cause the requested modification to be executed.

Abstract: A system for conserving computing and operator resources by streamlining the installation and management of applications on a remote host system, such as a cloud-based system. The system may receive from an operator, a requested modification of an application installation image stored in a secure registry of the remote host system. In response, the system may authenticate the operator, and verify that the requested modification is a permitted modification. The system can also transmit a notification of the requested modification to other operators to allow the other operators an opportunity to object to the requested modification. In the absence of objections, the system may cause the requested modification to be executed.

Abstract: A computing system for determining the presence of one or more duplicate action execution requests among multiple received action execution requests is disclosed. The system can train a machine-learning model on training data including historical action execution information associated with a plurality of historical actions executed by one or more action execution applications, to generate a trained a machine-learning model. The trained machine-learning model can subsequently identify duplicate requests among newly received action execution requests by recognizing patterns in associated action execution information received with the action execution requests. An action execution request that is determined to be a duplicate action execution request by the trained a machine-learning model can then be identified for removal or automatically removed from the system.

Abstract: A system for conserving computing and memory resources and enhancing security by performing application-level multifactor level authentication of a client requesting execution of an action by the system. A request to execute an action sent by the client and received by an action execution application of the system may include compiled client authentication information. The compiled client authentication information may comprise at least a client digital certificate and client login credentials that are unique to the action execution application. The action execution application can authenticate the client relative to the requested action by validating the received client digital certificate against a stored set of previously validated digital certificates, in addition to validating the received client login credentials against a stored set of previously validated login credentials. In response to authenticating the client, the action execution application may execute the requested action.

Abstract: A system for conserving computing and memory resources and enhancing security by performing application-level multifactor level authentication of a client requesting execution of an action by the system. A request to execute an action sent by the client and received by an action execution application of the system may include compiled client authentication information. The compiled client authentication information may comprise at least a client digital certificate and client login credentials that are unique to the action execution application. The action execution application can authenticate the client relative to the requested action by validating the received client digital certificate against a stored set of previously validated digital certificates, in addition to validating the received client login credentials against a stored set of previously validated login credentials. In response to authenticating the client, the action execution application may execute the requested action.

Abstract: A computing system for determining the presence of one or more duplicate action execution requests among multiple received action execution requests is disclosed. The system can train a machine-learning model on training data including historical action execution information associated with a plurality of historical actions executed by one or more action execution applications, to generate a trained a machine-learning model. The trained machine-learning model can subsequently identify duplicate requests among newly received action execution requests by recognizing patterns in associated action execution information received with the action execution requests. An action execution request that is determined to be a duplicate action execution request by the trained a machine-learning model can then be identified for removal or automatically removed from the system.

Abstract: A system for conserving computing and operator resources by streamlining the installation and management of applications on a remote host system, such as a cloud-based system. The system may receive from an operator, a requested modification of an application installation image stored in a secure registry of the remote host system. In response, the system may authenticate the operator, and verify that the requested modification is a permitted modification. The system can also transmit a notification of the requested modification to other operators to allow the other operators an opportunity to object to the requested modification. In the absence of objections, the system may cause the requested modification to be executed.

Abstract: A system for conserving computing and operator resources by streamlining the installation and management of applications on a remote host system, such as a cloud-based system. The system may receive from an operator, a requested modification of an application installation image stored in a secure registry of the remote host system. In response, the system may authenticate the operator, and verify that the requested modification is a permitted modification. The system can also transmit a notification of the requested modification to other operators to allow the other operators an opportunity to object to the requested modification. In the absence of objections, the system may cause the requested modification to be executed.

Abstract: A system for processing a request to execute an action by a future date is disclosed. The system may access training data including historical action data, historical execution times, and historical utilization rate information for one or more execution objects, and can use the training data to train a machine-learning model. Upon receipt of a request to execute an action at a future date, action execution information provided in the request, the future date, and at least the current date, can be input to the trained machine-learning model, which may be configured to generate an output indicating a time-shifted target date on which the execution objects are available to execute the requested action that is no later than the future date. The system can then schedule the requested action for execution by the execution objects on the time-shifted target date.

Abstract: A system for processing a request to execute an action by a future date is disclosed. The system may receive a request to execute an action by a future date and may thereafter provide information included in the request as input data to a trained machine-learning model configured to output a time-shifted target date on which one or more execution objects are available to execute the action. An application for future execution of the action may be generated and the time-shifted target date may be assigned thereto as a future action execution date. A draft status label may also be assigned to the application, which may thereafter be temporarily saved to a future action execution queue. The application may be retrieved from the future action execution queue on the future action execution date and submitted to the one or more execution objects for execution of the action.

Abstract: Systems, apparatuses, and computer-implemented methods provide for technology that extracts textual data from a plurality of different sources in accordance with a plurality of variables, wherein the textual data is to be associated with a plurality of errors, groups the textual data into a plurality of categories, and trains an NLP prediction model based on the textual data and the plurality of categories.