Abstract: A device receives application information associated with a cloud application provided in a cloud computing environment, and utilizes a first AI model to generate test cases and test data based on the application information. The device utilizes a second AI model to generate optimized test cases and optimized test data based on the test cases and the test data, and utilizes a third AI model to generate test classes based on the optimized test cases and the optimized test data. The device executes the test classes to generate results, and utilizes a fourth AI model to generate an analysis of the results, recommendations for the cloud application based on the analysis of the results, or a code coverage report associated with the cloud application. The device automatically causes an action to be performed based on the analysis of the results, the recommendations, or the code coverage report.

Abstract: A device may receive information that identifies a resource utilization, by another device, of a cloud computing resource. The device may determine a current score based on the information that identifies the resource utilization and information that identifies a threshold. The current score may be indicative of the resource utilization relative to the threshold. The device may determine a prediction of a future score related to the resource utilization based on the current score and based on the threshold. The prediction of the future score may relate to satisfaction of the threshold. The device may determine a set of recommendations. The set of recommendations may be related to the resource utilization. The device may provide information that identifies the current score, the prediction of the future score, or the set of recommendations to permit or cause an action to be performed. The action may be related to the resource utilization.

Abstract: A device receives application information associated with a cloud application provided in a cloud computing environment, and utilizes a first AI model to generate test cases and test data based on the application information. The device utilizes a second AI model to generate optimized test cases and optimized test data based on the test cases and the test data, and utilizes a third AI model to generate test classes based on the optimized test cases and the optimized test data. The device executes the test classes to generate results, and utilizes a fourth AI model to generate an analysis of the results, recommendations for the cloud application based on the analysis of the results, or a code coverage report associated with the cloud application. The device automatically causes an action to be performed based on the analysis of the results, the recommendations, or the code coverage report.

Abstract: A device may receive information that identifies a resource utilization, by another device, of a cloud computing resource. The device may determine a current score based on the information that identifies the resource utilization and information that identifies a threshold. The current score may be indicative of the resource utilization relative to the threshold. The device may determine a prediction of a future score related to the resource utilization based on the current score and based on the threshold. The prediction of the future score may relate to satisfaction of the threshold. The device may determine a set of recommendations. The set of recommendations may be related to the resource utilization. The device may provide information that identifies the current score, the prediction of the future score, or the set of recommendations to permit or cause an action to be performed. The action may be related to the resource utilization.