The University of California, Los Angeles (UCLA), founded in 1919, is a public research university committed to the creation, dissemination, preservation, and application of knowledge for the advancement of global society. It offers a dynamic environment that combines the engaging atmosphere of a spirited public institution with expansive opportunities in a world-class city. We have partnered with UCLA on vision-language research and the development of generative adversarial networks. Our collaboration has improved the integration of visual and textual data for tasks such as image captioning, retrieval, and cross-modal learning. Please read about our latest news and collaborative publications with the University of California, Los Angeles.

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LogLens: A Real-time Log Analysis System

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Administrators of most user-facing systems depend on periodic log data to get an idea of the health and status of production applications. Logs report information, which is crucial to diagnose the root cause of complex problems. In this paper, we present a real-time log analysis system called LogLens that automates the process of anomaly detection from logs with no (or minimal) target system knowledge and user specification. In LogLens, we employ unsupervised machine learning based techniques to discover patterns in application logs, and then leverage these patterns along with the real-time log parsing for designing advanced log analytics applications. Compared to the existing systems which are primarily limited to log indexing and search capabilities, LogLens presents an extensible system for supporting both stateless and stateful log analysis applications. Currently, LogLens is running at the core of a commercial log analysis solution handling millions of logs generated from the large-scale industrial environments and reported up to 12096x man-hours reduction in troubleshooting operational problems compared to the manual approach.

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