Asynchronous microservice-based supervised learning for adaptive message queue prioritization in data protection operations

A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for managing data access, the method comprising:

• obtaining, by a message prioritization service, data comprising a first set of messages, wherein the first set of messages are associated with communication between a production environment and a data protection system;
• and
• in response to obtaining the data:
• performing a data pre-processing on the data to obtain processed data, wherein the data pre-processing comprises identifying features of the data associated with the communication;
• performing a data partitioning of the processed data to obtain a training set and a testing set;
• performing a model training on the training set using the features by applying a k-nearest neighbors (KNN) algorithm on the training set to obtain a trained model;
• and
• deploying the trained model in a to perform message prioritization of messages.

A system, comprising:

• a processor, and
• memory comprising instructions, which when executed by the processor, cause the processor to perform a method, the method comprising:
• obtaining, by a message prioritization service, data comprising a first set of messages, wherein the first set of messages are associated with communication between a production environment and a data protection system;
• and
• in response to obtaining the data:
• performing a data pre-processing on the data to obtain processed data, wherein the data pre-processing comprises identifying features of the data associated with the communication;
• performing a data partitioning of the processed data to obtain a training set and a testing set;
• performing a model training on the training set using the features by applying a k-nearest neighbors (KNN) algorithm on the training set to obtain a trained model;
• and
• deploying the trained model in a to perform message prioritization of messages.