Vmware, Inc.

Susobhit Panigrahi

Ritesh Ranjan Jha

Mageshwaran Rajendran

Reghuram Vasanthakumari

Soumya Panigrahi

Narayanasamy Ramesh

Arihant Jain

A system and method for sampling application programming interface (API) execution traces in a computer system uses feature vectors of the API execution traces that are generated using trace-context information. The feature vectors are then used to group the API execution traces into clusters. For the cluster, sampling rates are generated so that a sampling rate is assigned to each of the clusters. The sampling rates are then applied to the API execution traces to adaptively sample the API execution traces based on the clusters to which the API execution traces belong.

System and method for adaptively sampling application programming interface execution traces based on clustering

The current document is directed to methods and systems that employ network metrics collected by distributed-computer-system metrics-collection services to determine a service-call-based topology for distributed service-oriented applications. In a described implementation, network metrics are collected over a number of network-metric monitoring periods. Independent component analysis is used to extract, from the collected network metrics, signals corresponding to sequences of service calls initiated by calls to the application-programming interface of a distributed service-oriented application. The signals, in combination with call traces obtained from a distributed-services call-tracing utility or service, are then used to construct representations of distributed-service-oriented-application topologies. The distributed-service-oriented-application topologies provide a basis for any additional types of distributed-computer-system functionalities, utilities, and facilities.

Method and system that determines application topology using network metrics

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Bengaluru, India

Susobhit Panigrahi