Abstract: A method of identifying a root cause in a distributed computing environment is provided including collecting metric data of a plurality of application components, collecting metric correlation relationship data, collecting topology relationship data, and collecting transaction tracking relationship data that indicates a group of the application components used to execute a requested transaction. A graph is generated including a plurality of nodes corresponding to the application components by merging the metric correlation relationship data, the topology relationship data, and the transaction tracking relationship data. The nodes of the graph are traversed in an order based on a bi-directional weight for each of a plurality of edges connecting neighboring nodes among the plurality of nodes. A recommendation list is generated including at least one abnormal application component.

Abstract: A method of identifying a root cause in a distributed computing environment includes traversing a plurality of nodes in a call graph starting with an end user node. Each node corresponds to an application component. A response time is calculated between connected pairs of neighboring nodes. A weight is calculated for each of a plurality of edges connecting the neighboring nodes. The nodes are traversed starting with the end user node in an order based on the weight of each of the edges. A root cause score is calculated for each node based on traversing all of the nodes in the order based on the weight of each of the edges. A ranked list is generated.

Abstract: A method of operating a computer system including collecting, from the computer system, data indicative of variations in throughput and response time over a period of time, calculating processing power of the computer system over the period of time, recording a maximal power, calculating a standard deviation of the response time (RT-StdDev), recording the standard deviation of the response time corresponding to a time of the maximal power (RT-StdDevMaxPower), and generating a notification that the computer system is in a bottleneck state using a comparison of a current processing power to the maximal power and a comparison of the RT-StdDev to the RT-StdDevMaxPower.

Abstract: A method of operating a computer system including collecting, from the computer system, data indicative of variations in throughput and response time over a period of time, calculating processing power of the computer system over the period of time, recording a maximal power, calculating a standard deviation of the response time (RT-StdDev), recording the standard deviation of the response time corresponding to a time of the maximal power (RT-StdDevMaxPower), and generating a notification that the computer system is in a bottleneck state using a comparison of a current processing power to the maximal power and a comparison of the RT-StdDev to the RT-StdDevMaxPower.

Abstract: A method of identifying a root cause in a distributed computing environment is provided including collecting metric data of a plurality of application components, collecting metric correlation relationship data, collecting topology relationship data, and collecting transaction tracking relationship data that indicates a group of the application components used to execute a requested transaction. A graph is generated including a plurality of nodes corresponding to the application components by merging the metric correlation relationship data, the topology relationship data, and the transaction tracking relationship data. Target nodes are identified among the plurality of nodes that correspond to application components having a response time that is above a predefined threshold. A plurality of paths along the graph that include the target nodes are traversed to identify at least one node corresponding to an abnormal application component.

Abstract: A method of identifying a root cause in a distributed computing environment includes traversing a plurality of nodes in a call graph starting with an end user node. Each node corresponds to an application component. A response time is calculated between connected pairs of neighboring nodes. A weight is calculated for each of a plurality of edges connecting the neighboring nodes. The nodes are traversed starting with the end user node in an order based on the weight of each of the edges. A root cause score is calculated for each node based on traversing all of the nodes in the order based on the weight of each of the edges. A ranked list is generated.