Abstract: The present invention provides at least a method and system for forecasting usage costs and computer capacity. With respect to the present invention, performance data and information related to transactions collected from computing devices are used to calculate correlations. A cost-allocation factor is calculated to determine the computer's usage costs without a long manual analysis of large volumes of data and extensive testing. Performance data and transaction data are used to forecast computer capacity.

Abstract: The present invention provides at least a method and system for forecasting usage costs and computer capacity. With respect to the present invention, performance data and information related to transactions collected from computing devices are used to calculate correlations. A cost-allocation factor is calculated to determine the computer's usage costs without a long manual analysis of large volumes of data and extensive testing. Performance data and transaction data are used to forecast computer capacity.

Abstract: The present invention provides methods and systems for evaluating the performance of a computer system to enable capacity planning. With respect to the present invention, performance data (metrics) collected from computing devices are used to generate performance results. A set of utilization factors are calculated to forecast computing needs without a long manual analysis of large volumes of data. A user has access to a graphical representation of the utilization factors to determine a forecast of capacity needs based on the information calculated.

Abstract: A call-transaction forecasting tool taking the form of a computer-implemented method and medium in some embodiments is provided for retrieving, aggregating, sorting, and determining one or more maximum transactions within a communications network. The tool automates the process of manually extracting and analyzing call transactions pertaining to call-duration, call volume, traffic usage, bandwidth usage, processing usage and memory usage in order to properly forecast and predict future network growth and capacity within a providers network. The computer-implemented method includes retrieving transaction data files from a switch or server, merging the files in a commonly shared data structure, identifying one or more maximum transaction counts based upon an associated period of time, and displaying the maximum counts and associated period of time.

Abstract: The present invention provides at least a method and system for forecasting usage costs and computer capacity. With respect to the present invention, performance data and information related to transactions collected from computing devices are used to calculate correlations. A cost-allocation factor is calculated to determine the computer's usage costs without a long manual analysis of large volumes of data and extensive testing. Performance data and transaction data are used to forecast computer capacity.

Abstract: The present invention provides a method for modeling the performance of a system by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load. Additionally, a graph displaying both throughput and response time as a function of load may be displayed to a system operator in a graphical user interface to facilitate the evaluation of system performance.

Abstract: 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.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.

Abstract: The present invention provides at least a method and system for forecasting computer capacity. With respect to the present invention, performance data and information related to transactions collected from computing devices are used to calculate correlations. A usage factor is calculated to determine the computer's theoretical maximum capacity without a long manual analysis of large volumes of data and extensive testing.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.

Abstract: The present invention provides a method for modeling the performance of a system comprising computer software operating on computer hardware. In accordance with the present invention, system performance is modeled by fitting non-linear curves to data points for system performance parameters, such as response time and throughput, as a function of load. Data points may be measured in testing may be measured through monitoring a system operating in a production environment. While a variety of non-linear curves may be used in accordance with the present invention, a logarithmic curve may be used to model system throughput and an exponential curve may be used to model system response time. By defining a relationship between throughput and response time a distance may be calculated between the curves, and this distance may be used to determine an optimal load.