| CPC G06Q 30/016 (2013.01) | 15 Claims |
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1. A method, performed by a computer system, for adjusting operations of a customer service application based on metrics generated as a result of real-time monitoring of entity states within the customer service application, the method comprising:
receiving at a bus entity events from a plurality of services provided by the customer service application;
tracking states of entities in real time in a state machine for the customer service application based on the events received from the bus and the state machine logic for the customer service application, wherein tracking states of entities includes 1) identifying any entities in an anomalous state and 2) for each state entered by an entity, tracking a time in which the entity enters a state;
sending information on any entities identified by the state machine as being in an anomalous state back to the bus, wherein the bus transports the information to an indexer, and wherein the indexer creates an index of entities in an anomalous state;
for each non-anomalous state transition, calculating one or more state transition measurements, including how long an entity has been in a state;
generating per-entity metrics and aggregate metrics, wherein the per-entity metrics and aggregate metrics include network metrics, at a metrics calculator for the customer service application based at least in part on the state transition measurements for entities in a non-anomalous state, wherein anomalous per-entity metrics are filtered out before calculating the aggregate metrics;
adjusting in a performance optimizer the operations of the customer service application in real time based on the per-entity metrics and the aggregate metrics, wherein adjusting the operations of the customer service application in real time based on the per-entity metrics and the aggregate metrics comprises:
determining based on the per-entity metrics and the aggregate metrics generated from customers' interactions with the customer service application that an external entity is attempting to infiltrate the computer system, and
in response to determining based on the per-entity metrics and the aggregate metrics that the external entity is attempting to infiltrate the computer system, the performance optimizer automatically and proactively blocking the infiltration attempt by the external entity against the computer system; and
displaying information related to the per-entity metrics and the aggregate metrics and the index of entities in an anomalous state in a user interface dashboard.
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