Microsoft Technology Licensing, LLC

Linkedin Corporation

Toon Sripatanaskul

Badrinath K Sridharan

Liang Zhang

Deepak Agarwal

Yang Yang

David Q He

Sanjay Sureshchandra Dubey

Cuong Huu Tran

Ruixuan Hou

Ritesh Maheshwari

Steven Scott Noble

Jieying Chen

Christopher Coleman

Thomas Goetze

Nicholas P Baggott

The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of components of a time-series performance metric associated with an anomaly in a performance of one or more monitored systems. For each component in the set of components, the system performs a statistical hypothesis test on the component to assess a deviation of the component from a baseline value of the component. When the statistical hypothesis test identifies a statistically significant deviation of the component from the baseline value, the system outputs an alert comprising a root cause of the anomaly that is represented by the statistically significant deviation of the component from the baseline value.

Root cause investigation of site speed performance anomalies

The disclosed embodiments provide a system for processing data. During operation, the system obtains a component of a time-series performance metric associated with a server-side root cause of an anomaly in the time-series performance metric. Next, the system obtains a call graph representation of the component, wherein the call graph representation includes a parent node having a parent value of the component and a set of child nodes of the parent node, each child node having a corresponding child value of the component. The system then analyzes the call graph representation to identify one or more of the child nodes as sources of the anomaly. Finally, the system outputs an alert that identifies the sources of the anomaly.

Analysis of site speed performance anomalies caused by server-side issues

Techniques for categorizing exceptions and logs are described. For example, exception data of an exception that occurred on a machine is accessed. The exception data includes a stack trace of the exception. A determination is made that the exception is unique based on the stack track of the exception. Responsive to the determination that the exception is unique, the exception is categorized, by a machine including a memory and at least one processor, into one or more categories based on the stack trace of the exception.

Systems and methods for categorizing exceptions and logs

Techniques for generating, storing, and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Service call graphs for website performance

Techniques for generating and using service call graphs are provided. In one technique, trace data items generated by different services are correlated to generate a service call graph. Trace data indicates when certain services are called and their respective latencies as a result of a client request. A service call graph may reflect a single trace or multiple traces over a particular period of time. A service call graph may be analyzed to inform administrators of a web site how a web application and the services it relies on are performing. A service call graph may be used to determine whether there are sufficient resources to support a projected increase in traffic to a web application. A service call graph may be used to estimate a cost of a web application. Multiple service call graphs may be compared to determine one or more root causes of a performance problem.

Estimating latency of an application

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Menlo Park, CA, United States of America

Toon Sripatanaskul