Abstract: An exemplary system, method, and computer-accessible medium for classifying data associated with an application performance management (“APM”) agent(s) deployed on a server(s), can include, for example, receiving first information related to data to be read by the APM agent(s) located at the server(s), generating second information by assigning a score to the first information using machine learning procedure(s), classifying the data based on the second information. A data plugin(s) associated with the data can be determined based on the classification. A determination can be made as to whether the data is labeled as a data type. The second information can be generated based on (i) a log(s) associated with the data, (ii) transaction data associated with the data, (iii) server metrics associated with the data, (iv) a time stamp(s) associated with the data, (v) infrastructure data associated with the data, (vi) domain knowledge, or (vii) environment knowledge.

Abstract: An exemplary system, method, and computer-accessible medium for classifying data associated with an application performance management (“APM”) agent(s) deployed on a server(s), can include, for example, receiving first information related to data to be read by the APM agent(s) located at the server(s), generating second information by assigning a score to the first information using machine learning procedure(s), classifying the data based on the second information. A data plugin(s) associated with the data can be determined based on the classification. A determination can be made as to whether the data is labeled as a data type. The second information can be generated based on (i) a log(s) associated with the data, (ii) transaction data associated with the data, (iii) server metrics associated with the data, (iv) a time stamp(s) associated with the data, (v) infrastructure data associated with the data, (vi) domain knowledge, or (vii) environment knowledge.