Microsoft Technology Licensing, LLC

Dinko Papak

Dmitri A Klementiev

Varun Jain

Michail Zervos

Dhruv Gakkhar

LeninaDevi Thangavel

Igor Sakhnov

Richard Gregory Endean, Jr

Kateryna Boikovska

Methods, systems, apparatuses, and computer program products are described herein that enable detecting anomalies in time series. An anomaly detection technique is selected from a plurality of detection techniques, and is applied to a first time-series data set (having a first set of dimensions). In response to detecting an anomaly in the time-series data set, the anomaly detection technique is applied to a second time-series data set that is a subset of the first time-series data set. The first time-series data set includes the first set of dimensions plus one or more additional dimensions.

Combination of techniques to detect anomalies in multi-dimensional time series

A system determines a topology of a distributed system and determines, based on the topology, one or more injection points in the distributed system to inject failure scenarios. Each failure scenario including one or more faults and parameters for each of the faults. The system prioritizes the failure scenarios and injects a failure scenario from the prioritized failure scenarios into the distributed system via the one or more injection points. The system determines whether the injected failure scenario causes a response of the distributed system to fall below a predetermined level. The system determines resiliency of the distributed system to one or more faults in the injected failure scenario based on whether the injected failure scenario causes the response of the distributed system to fall below the predetermined level.

Scenarios based fault injection

A method and system for assessing resiliency of a system is provided. A fault injection system may, for each of a plurality of dimensions of a fault profile, access an indication of possible values for the dimension, which may be specified by a user. The fault injection system may, for each of a plurality of fault profiles, automatically create the fault profile by, for each of the plurality of dimensions, selecting by the computing system a possible value for that dimension. For at least some of the fault profiles, the fault injection system injects a fault based on the fault profile into the system and determines whether a failure was detected while the fault was injected.

Distributed system resiliency assessment using faults

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Dinko Papak