Ca, Inc.

Computer Associates Think, Inc.

Wily Technology, Inc.

Zahur Peracha

Jyoti Bansal

Rajpal Singh Sodhi

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.

Automatic baselining of resource consumption for transactions

Application health is determined by calculating baseline deviation for one or more transactions based on past data having the same context as current data being examined. The performance data is generated in response to monitoring one or more applications that perform transactions during a time period. The performance data may include transaction metric data and the context data describing conditions under which one or more transactions were performed. A baseline is determined by predicting current or recent transaction performance data values using past transaction performance data associated with the same context. Based on the comparison of the actual and predicted data with the same or similar context, a deviation from the baseline value is determined for the transaction and reported, for example to a user through an interface.

Automatic context-based baselining for transactions

Application data is reported in response to monitoring an application transaction. Application data is obtained for an initial period of time. A function which estimates the application data is then identified for the reported application data. After identifying the function, subsequent application data is obtained, and function data is generated from the subsequent application data. The function data may be associated with function parameters associated with the identified function. A function can then be constructed from the reported function data. The function constructed from the function data may estimate application data associated with the monitored transactions.

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Zahur Peracha