1. An integrated Overload Monitoring System (OMS), for Critical Service Level Agreement (CSLA) Identification based on bandwidth (BW) and Near-Optimal Traffic Analysis for Forecasting BW-related CSLA Operator Violations at a future time point, comprising of: a) a subsystem for the identification of critical SLAs from the data obtained from external repositories wherein a critical SLA is an SLA which is of strategic importance to an operator and hence requiring the monitoring of the same; b) a subsystem to regionalize (cluster) the nodes in the network, using a hierarchical clustering based on similar load behavior, wherein the nodes under consideration are the nodes in a provider's network; c) a Forecast Model (FM) selection subsystem to select horizontal and vertical usage pattern models based on the usage pattern exhibited in the historical data; d) a subsystem to determine the overall load due to critical SLAs by determining Usage Upper Bound for all non-critical SLAs at periodic time intervals and further reduce the load due to non-critical SLAs from the overall load on the network; e) a subsystem for offline SLA load prediction to predict the load due to a critical SLA at a future time point based on historical traffic data using vertical FM; f) plurality of universal network probes that execute the role of master and/or slave probes to perform a near-optimal analysis of the network traffic for critical SLAs; g) a subsystem for network traffic analysis by the network probes based on two distinct configurable clocks with different frequencies to minimize the monitor-data flow across the network; h) a subsystem for real-time SLA load prediction to predict the load due to critical SLAs at a future time point based on current traffic data using horizontal FM; and i) a subsystem to predict alarm set points based on horizontal and vertical FMs to generate alarms based on alarm set point consistency, and further to escalate in case of no acknowledgement for the generated alarm.