We demonstrate Grano 1 , an end-to-end anomaly detection and root cause analysis (or RCA for short) system for cloud-native distributed data platform by providing a holistic view of the system component topology, alarms and application events. Grano provides: a Detection Layer to process large amount of time-series monitoring data to detect anomalies at logical and physical system components; an Anomaly Graph Layer with novel graph modeling and algorithms for leveraging system topology data and detection results to identify the root cause relevance at the system component level; and an Application Layer that automatically notifies on-call personnel and presents real-time and on-demand RCA support through an interactive graph interface. The system is deployed and evaluated using eBay's production data to help on-call personnel to shorten the identification of root cause from hours to minutes.

For several years, the lectures in our introductory Electrical Engineering and Computer Science (EECS) courses have been videotaped and webcast, mainly as an aid to students with time conflicts that prevent them from attending class. We present the Weiner Lecture Archives - a project to identify, archive, filter, and make available the best of these lectures with their notes on the web. We provide a hierarchical, ontology-driven interface to entire courses, which allows users to choose any topic and/or subtopic to view, from a small snippet of one lecture to one that spans many lectures. Once the topic is chosen, our system launches RealPlayer to play the lecture video in one window while showing synchronized lecture notes or slides in another window. By the spring of 2007, we had finished encoding our department's entire four-course introductory sequence into this system. Student and worldwide use was greater than 100,000 views last year alone, direct feedback has been encouraging, and we hope to expand to other EECS courses in the future.