Integration optimization using machine learning algorithms

A method comprising:

• receiving configuration data comprising a plurality of parameters of at least one computing environment;
• wherein one or more of the plurality of parameters correspond to integration of one or more elements of the least one computing environment with one or more other elements at least one of within and external to the least one computing environment;
• analyzing the plurality of parameters to detect one or more anomalies in the configuration data;
• inputting the configuration data and the one or more detected anomalies to one or more machine learning models;
• determining, using the one or more machine learning models, one or more modifications to at least one of the plurality of parameters based on the inputted configuration data and one or more detected anomalies;
• and
• transmitting the determination comprising the one or more modifications to a user over a communications network;
• wherein the method is performed by at least one processing platform comprising at least one processing device comprising a processor coupled to a memory.

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing platform causes said at least one processing platform:

• to receive configuration data comprising a plurality of parameters of at least one computing environment;
• wherein one or more of the plurality of parameters correspond to integration of one or more elements of the least one computing environment with one or more other elements at least one of within and external to the least one computing environment;
• to analyze the plurality of parameters to detect one or more anomalies in the configuration data;
• to input the configuration data and the one or more detected anomalies to one or more machine learning models;
• to determine, using the one or more machine learning models, one or more modifications to at least one of the plurality of parameters based on the inputted configuration data and one or more detected anomalies;
• and
• to transmit the determination comprising the one or more modifications to a user over a communications network.