Abstract: The present disclosure relates to methods, systems, and computer readable media for analyzing log files for a wide variety of services (e.g., cloud computing services or microservices) to determine whether the services are operating as designed over some period of time associated with the log file(s). The present disclosure includes features and functionality for training or otherwise generating a model being configured to predict whether portions of an input log file include data reflective of normal operations of a corresponding service used to generate the input log file. The present disclosure provides a domain-agnostic approach to training an outlier detection model to analyze log files for a wide variety of services.

Abstract: A web service request is received, and a stored performance metric value, generated for other web service requests of the same type, is compared to a threshold value. If the stored performance metric value meets the threshold value, then the received web service request is routed to a sandboxed instance of the web service for execution. If the stored performance metric value does not meet the threshold value then the received web service request is routed to a default web service instance for execution. In either case, the performance metric is monitored during execution of the received web service request, and the stored performance metric value is updated based upon the monitored performance metric generated for the received web service request.

Abstract: A web service request is received, and a stored performance metric value, generated for other web service requests of the same type, is compared to a threshold value. If the stored performance metric value meets the threshold value, then the received web service request is routed to a sandboxed instance of the web service for execution. If the stored performance metric value does not meet the threshold value then the received web service request is routed to a default web service instance for execution. In either case, the performance metric is monitored during execution of the received web service request, and the stored performance metric value is updated based upon the monitored performance metric generated for the received web service request.