1. A method for monitoring live-data flow through a network, comprising: monitoring, at a first processing node, a mirrored live-data flow of the live-data flow passing through a selected point within the network, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data in a database; decoding, at the first processing node, each packet within the mirrored live-data flow according to each protocol associated with a packet, wherein packets having a plurality of protocols associated therewith are decoded in parallel with each other; comparing, at the first processing node, each of the decoded packets to at least one of a set of predetermined or deduced conditions; executing at least one predetermined or deduced response based upon detection of at least one predetermined or deduced condition within the decoded packets; processing, at a second processing node, at least a portion of the decoded packets of the live-data flow causing execution of the at least one predetermined or deduced response using a relational language processing to determine a manner for controlling an operation of the network at a same time the live-data flow is in active transmission between the endpoints in the network, wherein the step of processing further comprises steps of: receiving an indication of detection of one of the at least one predetermined or deduced conditions; assigning at least one predefined application associated with the indication; processing the decoded data flow using the assigned at least one predefined application to generate at least one control action for controlling the operation in the network at the same time the live-data flow is in active transmission between the endpoints in the network, the step of processing further including processing at least a portion of the decoded packets of the live-data flow causing execution of the predetermined response and the deducing of dynamically created conditions responsive to historical data, the dynamically deduced conditions established as part of a learning process including statistical models and pattern recognition, operating within the second processing node with the option to provide the dynamically deduced conditions to the first processing node to update the deduced conditions; and controlling the operation of the network using the at least one control action.