Sprint Communications Comapny L.p.

Sprint Communication Cômpany L.p.

Margaret Mary McMahon

Brian John Washburn

Justin Alan Martin

Dean Lee Saghier

Richard Michael Wyett

A method of maintaining server performance comprises receiving, at an analysis server, server performance metrics from at least one monitored server, wherein server performance metrics comprise information about processor usage, memory usage, and network activity and comparing the received metrics with a baseline of values that was established for the server performance metrics based on a variance analysis of historical values. The method further comprises determining that the value of at least one server performance metric of the monitored server is consistently above an upper limit of a range of acceptable deviation from the baseline, analyzing historical occurrences of similar departures of server performance metrics from the range of acceptable deviation, and generating an alert indicating that a risk pattern has been identified and suggesting shutting down a locked process on the monitored server in order to return the server performance metrics to values within the range of acceptable deviation.

Method for qualitative analysis of system performance correlation factors

A system is provided comprising processor, memory, and application that captures production server metrics, and accesses an analytical model modeling response times and system utilization. The system enters a configuration into the model simulating the production environment and comprises a load and growth factor, generates modeled response times, calculates throughput rates, and determines a baseline production load. The system combines throughput rates and response times with the baseline production to project future throughput rates and response times. The system identifies at least one production server load metric associated with at least one of a projected future throughput rate and response time approaching a constant and executes a work order for a hardware or software change in the production environment based on at least one observed production server load metric associated with at the least one of a projected future throughput rate and a projected future response time approaching a constant.

Automated determination of system scalability and scalability constraint factors

The present invention implements computing systems in a configuration to reduce downtime. The computing systems are configured, without implementing a hot stand-by or mirrored configuration, to handle mission critical applications without failing. A user may determine the benefit of implementing the configuration over traditional methods, and may forecast estimated revenues generated from business operations in the configuration.

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Kansas City, MO, United States of America

Margaret Mary McMahon