2 research outputs found
C2MS: Dynamic Monitoring and Management of Cloud Infrastructures
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.Comment: Proceedings of the The 5th IEEE International Conference on Cloud
Computing Technology and Science (CloudCom 2013), 8 page
Enhanced Usability of Managing Workflows in an Industrial Data Gateway
The Grid and Cloud User Support Environment (gUSE) enables users convenient and easy access to grid and cloud infrastructures by providing a general purpose, workflow-oriented graphical user interface to create and run workflows on various Distributed Computing Infrastructures (DCIs). Its arrangements for creating and modifying existing workflows are, however, non-intuitive and cumbersome due to the technologies and architecture employed by gUSE. In this paper, we outline the first integrated web-based workflow editor for gUSE with the aim of improving the user experience for those with industrial data workflows and the wider gUSE community. We report initial assessments of the editor's utility based on users' feedback. We argue that combining access to diverse scalable resources with improved workflow creation tools is important for all big data applications and research infrastructures