Abstract: A first compute server of a plurality of compute servers of a distributed cloud computing network receives an inference request. The first compute server determines that the received inference request triggers execution of code at the distributed cloud computing network, where the code is related to an artificial intelligence (AI) application that interacts with the inference request and causes input of the inference request to be run through an AI model. If the AI model is not loaded at the first compute server but is loaded at a second compute server, the inference request is routed to the second compute server for performing the inference operation.

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.