Microsoft Technology Licensing, LLC

Alexander Robert Paul Grenier

Ziyad Ibrahim

Sudhakar Visweswara Prabhu

James David McCaffrey

Chad R Heinemann

Dharmanshu Kamra

Daniel James Carpenter

Ziyad Ahmad Ibrahim

James David Mccaffrey

Examples described herein generally relate to processing event logs where, for each of multiple events in an event log of the one or more event logs, a table of logged event instances can be generated for the event. For each of the multiple events, the table can be processed using an autoencoder to identify one or more of the logged event instances as anomalies, and an indication of at least a portion of the anomalies can be output. In addition, the event logs and/or corresponding tables of events can be used to train models for the autoencoders.

Techniques for detecting atypical events in event logs

Examples are disclosed that relate to managing workloads provided by a plurality of clients to a shared resource. One example provides a computing device comprising a processor and a storage device storing instructions executable by the processor. The instructions are executable to provide a first workload from a first client and a second workload from a second client to a shared memory accessible by the first client, the second client, and a resource configured to process the first workload and the second workload. The computing device is configured to determine that an exception has occurred while processing the first workload, and to take an action to prevent execution of at least some additional work from the first client. The instructions are further executable to receive a result of processing the second workload after taking the action to prevent the execution of the additional work.

Managing exceptions on a shared resource

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Seattle, WA, United States of America

Alexander Robert Paul Grenier