Title :
A scalable lightweight performance monitoring tool for storage clusters
Author :
Bauer, Daniel ; Feridun, Metin
Author_Institution :
IBM Res. Zurich Lab., Rüschlikon, Switzerland
Abstract :
Distributed infrastructures providing cloud services as well as compute- and storage clusters are notoriously difficult to administer and optimize. Management applications benefit from up-to-date data on system performance. This paper describes the Performance Monitoring and Management System (PMMS), a light-weight and versatile performance monitoring tool that collects hundreds of thousands of metrics per second and delivers this information as time-series in near real-time. At its core lies an in-memory database that scales through federation to large clusters of several hundreds of nodes. Data is collected using sensors which collect and periodically send their metric data to the PMMS collectors. Designed as a component that is embeddable into a larger system, PMMS is light-weight, with little impact on the system resources and it is easy to install and to configure.
Keywords :
cloud computing; database management systems; monitoring; pattern clustering; storage management; time series; PMMS collector; cloud services; compute-cluster; distributed infrastructure; in-memory database; lightweight performance monitoring tool; metric data; performance monitoring and management system; storage cluster; system performance; time-series; versatile performance monitoring tool; Databases; Measurement; Memory management; Monitoring; Sensor systems; Servers; Monitoring; clusters; distributed systems;
Conference_Titel :
Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on
Conference_Location :
Ottawa, ON
DOI :
10.1109/INM.2015.7140426