Abstract: This disclosure relates generally to memory suspect detection, and more particularly to system and method for detection of memory suspects in an application runtime environment. The method includes systematically executing a plurality of transactions associated with an application. Executing the plurality of transactions results in generation of metrics. Said metrics includes application memory information and memory allocation information associated with the transactions. Said metrics are periodically captured, Based on the metrics that are periodically captured, a set of transactions are detected from amongst the plurality of transactions that are impacted due to suspected memory allocations.

Abstract: The present subject matter relates to a method and system for correlation analysis of performance metrics. In one embodiment, a computing system for correlation analysis of performance metrics is described. The computing system includes a processor, and a memory which is coupled to the processor. Further, the memory comprises a profiler agent, a correlation engine, and a graphics controller. The profiler agent collects the performance metrics based on execution of a target application. The correlation engine establishes correlation between the performance metrics based on a predefined parameter. The graphics controller generates a consolidated interface of the performance metrics depicting the established correlation between the performance metrics.

Abstract: This disclosure relates generally to anomaly detection, and more particularly to system and method for detecting anomalies. In one embodiment, the method includes executing at least one thread associated with the application. Executing the at least one thread results in invoking one or more methods associated with the at least one thread. During the execution metrics associated with the one or more methods are captured. The metrics are systematically arranged in a data structure to represent a plurality of thread-method pairs and the metrics corresponding to each of the plurality of thread-method pairs. One or more anomalies associated with the one or more methods are identified from the data structure based on a detection of at least one predetermined condition in the data structure. An anomaly of the one or more anomalies includes one of un-exited anomaly, an exception anomaly and a user-defined anomaly.

Abstract: This disclosure relates generally to anomaly detection, and more particularly to system and method for detecting anomalies. In one embodiment, the method includes executing at least one thread associated with the application. Executing the at least one thread results in invoking one or more methods associated with the at least one thread. During the execution metrics associated with the one or more methods are captured. The metrics are systematically arranged in a data structure to represent a plurality of thread-method pairs and the metrics corresponding to each of the plurality of thread-method pairs. One or more anomalies associated with the one or more methods are identified from the data structure based on a detection of at least one predetermined condition in the data structure. An anomaly of the one or more anomalies includes one of un-exited anomaly, an exception anomaly and a user-defined anomaly.

Abstract: This disclosure relates generally to memory suspect detection, and more particularly to system and method for detection of memory suspects in an application runtime environment. The method includes systematically executing a plurality of transactions associated with an application. Executing the plurality of transactions results in generation of metrics. Said metrics includes application memory information and memory allocation information associated with the transactions. Said metrics are periodically captured. Based on the metrics that are periodically captured, a set of transactions are detected from amongst the plurality of transactions that are impacted due to suspected memory allocations.

Abstract: The present subject matter relates to a method and system for correlation analysis of performance metrics. In one embodiment, a computing system for correlation analysis of performance metrics is described. The computing system includes a processor, and a memory which is coupled to the processor. Further, the memory comprises a profiler agent, a correlation engine, and a graphics controller. The profiler agent collects the performance metrics based on execution of a target application. The correlation engine establishes correlation between the performance metrics based on a predefined parameter. The graphics controller generates a consolidated interface of the performance metrics depicting the established correlation between the performance metrics.

Abstract: Systems and methods for real time performance monitoring of an application are described. In one implementation, when a metrics collection request is obtained from a user device, a data storage location is selected from a plurality of data storage locations based on a location status associated with the data storage location. The metrics data, for monitoring the performance of the application, is then provided to the user device through a data store from the selected data storage location in real time.