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Intelligent system monitoring on large clusters
| Content Provider | ACM Digital Library |
|---|---|
| Author | Strunk, John D. Ganger, Gregory R. Hoke, Evan Faloutsos, Christos Sun, Jimeng |
| Abstract | Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon, a prototype monitoring and mining system for data centers. It uses the SNMP protocol to monitor a new data center at Carnegie Mellon. It stores the monitoring data in a MySQL database, allowing visualization of the time-series data using a JSP web-based frontend interface for system administrators. What sets InteMon apart from other cluster monitoring systems is its ability to automatically analyze correlations in the monitoring data in real time and alert administrators of potential anomalies. It uses efficient, state of the art stream mining methods to report broken correlations among input streams. It also uses these methods to intelligently compress historical data and avoid the need for administrators to configure threshold-based monitoring bands. |
| Starting Page | 47 |
| Ending Page | 52 |
| Page Count | 6 |
| File Format | |
| DOI | 10.1145/1315903.1315914 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2006-09-11 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
