LEARNING-AUGMENTED APPLICATION DEPLOYMENT PIPELINE

LEARNING-AUGMENTED APPLICATION DEPLOYMENT PIPELINE

A method includes providing a neural network with metrics obtained from an execution of an application in a test environment to determine rule-related weights, scaling rule results with the rule-related weights to determine scaled rule results. The method also includes re-training the neural network...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Kadariya, Laxmi, Sorkin, Nicholas, Alatrakchi, Hasan, Kim, Bada, Gaskins, Taylor, Huang, Frank, Nalamati, Varun, Agrawal, Roli, Tirtapraja, Patrick
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Beschreibung
Zusammenfassung:A method includes providing a neural network with metrics obtained from an execution of an application in a test environment to determine rule-related weights, scaling rule results with the rule-related weights to determine scaled rule results. The method also includes re-training the neural network with the rule results of the application, an indication that the executed application is selected for deployment in the production environment, and rule results of other applications in the test environment in response to a determination that the scaled rule results fail a threshold but that the application is selected for deployment in a production environment. The method also includes providing the re-trained neural network with the rule results to generate updated rule-related weights and scaling the rule results by the updated rule-related weights to determine updated scaled rule results.