Abstract:
An application monitoring system determines the health of one or more resources used to process a transaction, business application, or other computer process. Performance data is generated in response to monitoring application execution and processed to determine and an actual and baseline value for resource usage data. Resource usage baseline data may be determined from previous resource usage data associated with a resource and particular transaction (a resource-transaction pair). The baseline values are compared to actual values to determine a deviation for the actual value. Deviation information for the time series data can be reported through an interface or some other manner.
Abstract:
One embodiment of the present invention provides a system that facilitates testing a system-under-test with functional-test software and a transformation accelerator. During operation, the system receives a functional-test template at the transformation accelerator. The system also receives a test signal at the transformation accelerator, wherein the test signal comprises testing parameters. Next, the system manipulates the functional-test template at the transformation accelerator according to the testing parameters to create one or more functional-test transactions. The system then sends the one or more functional-test transactions to the system-under-test. Next, the system receives results for the one or more functional-test transactions from the system-under-test. Finally, the system queues the results.
Abstract:
Techniques are provided for generically controlling one or more resources associated with at least one computing system. In one aspect of the invention, the technique comprises evaluating one or more performance metrics associated with the one or more resources given one or more configurations of the one or more resources. The technique then causes a change in the one or more configurations of the one or more resources based on the performance metric evaluating step. The one or more performance metrics and the one or more configurations are expressed in generic formats.
Abstract:
In one aspect, a method of instructing at least one operator in a best practices implementation of a process for managing resource capacity in an information technology (IT) environment is provided. The method comprising providing instructions to the at least one operator to perform acts of: (A) creating at least one model of at least some aspects of the IT environment; (B) analyzing the at least one model to determine cost information relating to the modeled IT environment; (C) applying at least one simulated use condition to the at least one model; (D) analyzing performance of the at least one model under the at least one simulated use condition to determine information relating to at least a utilization of resources in the modeled IT environment and to determine resources in the modeled IT environment that create performance bottlenecks in the modeled IT environment; and (E) modifying at least one aspect of the at least one model impacting resource capacity based on the information determined in (B) and/or (D).
Abstract:
Method and apparatus for identifying a cause for a response time problem for a transaction in a distributed computing system that includes a central server and a plurality of subsystems. Data is stored at each subsystem relating to sub-transactions of transactions performed by the subsystems. When a problem is discovered in connection with the completion of a particular transaction, each subsystem of the plurality of subsystems that was involved in the particular transaction is identified, and both instance data relating to all of the sub-transactions of the particular transaction stored at each identified subsystem and current hourly aggregate data stored at each identified subsystem is forwarded to the central server. Root-Cause Analysis is then performed using the forwarded instance data and aggregate data to identify the particular subsystem that caused the transaction problem.
Abstract:
A method for analyzing performance of an information processing system having information processing apparatuses providing services to each other. Communication packets sent or received between the apparatuses are acquired. The apparatuses receive calls from other apparatuses for providing services indicated in the packets. A service call count aji of the calls received by the apparatuses during period j of m periods for the service i of n services is computed. A busy time bj is computed by summing processing times by the apparatuses for performing the services pertaining to the calls received by the apparatuses during period j. An average processing time di is computed by the apparatuses for each service i, as is an error εj in di wherein εj=bj−Σiajidi, by minimizing an index indicative of εj. The average processing time di is stored in a storage device and/or displayed on a display device.
Abstract:
A method for gathering operational metrics can include the step of identifying a host within a grid environment, wherein the host can be a software object. A ghost agent can be associated with the host. The ghost agent can replicate actions of the host. Operational metrics for at least a portion of the replicated actions can be determined. The operational metrics can be recorded. The host can move within the grid environment. The ghost agent can responsively move in accordance with movement of the host.
Abstract:
Method and a corresponding system for performance monitoring of distributed applications. A sensor intercepts every request of service for a server that is generated on a client. If the request meets a filtering condition (for example, defined by the address of the server, the web page from which the request is originated and/or the selected link) the measuring of a corresponding transaction on the client is enabled; at the same time, the request is updated by inserting a correlator. The request is then transmitted to the server. If the request includes the correlator, the measuring of a sub-transaction originating from the request is also enabled on the server. The parameters measured on the client and on the server are then associated with the correlator.
Abstract:
Gaming machines may be remotely reconfigured and/or reprogrammed, data remotely collected, and a comparison performed between at least two different configurations. Such may be done to determine optimal configurations of gaming machines for various periods (e.g., days, times, months, Holidays). The reconfiguration and/or reprogramming may, for example, change a minimum or maximum wager limit, change a payout schedule, change an aspect of a bonus, progressive or other jackpot, and/or change allocation an of gaming machines between Class II and Class III. Reports may be produced indicative of the effects of the reconfiguration or reprogramming.
Abstract:
A method includes storing a first transaction entry to a first software configurable storage location, storing a second transaction entry to a second software configurable storage location, determining that a first transaction indicated by the first transaction entry has occurred, determining that a second transaction indicated by the second transaction entry has occurred subsequent to the first transaction, and, in response to determining that the first transaction occurred and the second transaction occurred, storing at least one transaction attribute captured during at least one clock cycle subsequent to the second transaction. The first and second software configurable storage locations may be located in a trace buffer, where the at least one transaction attribute is stored to the trace buffer and overwrites the first and second transaction attributes. Each transaction entry may include a dead cycle field, a consecutive transaction requirement field, and a last entry field.