Server clustering is a common design principle employed by many organisations who require high availability, scalability and easier management of their infrastructure. Servers are typically clustered according to the service they provide whether it be the application(s) installed, the role of the server or server accessibility for example. In order to optimize performance, manage load and maintain availability, servers may migrate from one cluster group to another making it difficult for server monitoring tools to continuously monitor these dynamically changing groups. Server monitoring tools are usually statically configured and with any change of group membership requires manual reconfiguration, an unreasonable task to undertake on large-scale cloud infrastructures. In this paper we present the Cloudlet Control and Management System (C2MS), a system for monitoring and controlling dynamic groups of physical or virtual servers within cloud infrastructures. The C2MS extends Ganglia - an open source scalable system performance monitoring tool - by allowing system administrators to define, monitor and modify server groups without the need for server reconfiguration. In turn administrators can easily monitor group and individual server metrics on large-scale dynamic cloud infrastructures where roles of servers may change frequently. Furthermore, we complement group monitoring with a control element allowing administrator-specified actions to be performed over servers within service groups as well as introduce further customized monitoring metrics. This paper outlines the design, implementation and evaluation of the C2MS.
The Ganglia framework relies on two daemons: and @cite_14 . For brevity, the daemon collects resource usage information about the host it runs upon (remote server) and sends periodic heartbeat messages via a UDP multicast protocol to the entire Ganglia cluster. The daemon collects the aggregated XML and exports it to the PHP web interface hosted on a central server.
@cite_14
2339804275
Written by Ganglia designers and maintainers, this book shows you how to collect and visualize metrics from clusters, grids, and cloud infrastructures at any scale. Want to track CPU utilization from 20,000 hosts every ten seconds? Ganglia is just the tool you need, once you know how its main components work together. This hands-on book helps experienced system administrators take advantage of Ganglia 3.x. Learn how to extend the base set of metrics you collect, fetch current values, see aggregate views of metrics, and observe time-series trends in your data. Youll also examine real-world case studies of Ganglia installs that feature challenging monitoring requirements. Determine whether Ganglia is a good fit for your environment Learn how Ganglias gmond and gmetad daemons build a metric collection overlay Plan for scalability early in your Ganglia deployment, with valuable tips and advice Take data visualization to a new level with gweb, Ganglias web frontend Write plugins to extend gmonds metric-collection capability Troubleshoot issues you may encounter with a Ganglia installation Integrate Ganglia with the sFlow and Nagios monitoring systems Contributors include: Robert Alexander, Jeff Buchbinder, Frederiko Costa, Alex Dean, Dave Josephsen, Peter Phaal, and Daniel Pocock.