System and method for auto-determining solutions for dynamic issues in a distributed network

A method comprising:

• detecting an application issue associated with an application running at a network node at a particular timestamp;
• receiving a set of data objects associated with the application issue;
• classifying, by a machine learning model, the set of the data objects of the application issue into one or more issue patterns, wherein the machine learning model is trained based on a plurality of sets of the data objects and corresponding issue patterns associated with corresponding previous application issues;
• processing, through a neural network, the one or more issue patterns and application information associated with the application issue at the network node to determine a series of executable operations for solving the application issue, wherein the neural network is trained based on the plurality of the issue patterns and associations between the issue patterns and the plurality of series of the executable operations;
• and
• deploying the series of the executable operations for solving the application issue at the network node to prevent a failure operation of the application.

A non-transitory computer-readable medium storing instructions that when executed by a processor cause the processor to:

• detect an application issue associated with an application running at a network node at a particular timestamp;
• receive a set of data objects associated with the application issue;
• classify, by a machine learning model, the set of the data objects of the application issue into one or more issue patterns, wherein the machine learning model is trained based on a plurality of sets of the data objects and corresponding issue patterns associated with corresponding previous application issues;
• process, through a neural network, the one or more issue patterns and application information associated with the application issue at the network node to determine a series of executable operations for solving the application issue, wherein the neural network is trained based on the plurality of the issue patterns and associations between the issue patterns and the plurality of series of the executable operations;
• and
• deploy the series of the executable operations to solve the application issue at the network node to prevent a failure operation of the application.