Configuration management technology using tree structures of ICT systems

  • Authors:
  • Atsuji Sekiguchi;Kuniaki Shimada;Yuji Wada;Akio Ooba;Ryouji Yoshimi;Akiko Matsumoto

  • Affiliations:
  • Cloud Computing Research Center, Fujitsu Laboratories Limited, Kawasaki, Japan;Cloud Computing Research Center, Fujitsu Laboratories Limited, Kawasaki, Japan;Cloud Computing Research Center, Fujitsu Laboratories Limited, Kawasaki, Japan;Fujitsu Limited, Kawasaki, Japan;Fujitsu Limited, Kawasaki, Japan;Fujitsu Limited, Kawasaki, Japan

  • Venue:
  • Proceedings of the 15th Communications and Networking Simulation Symposium
  • Year:
  • 2012

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Abstract

In large-scale ICT (Information and Communication Technology) systems, such as cloud computing, a reduction of operation management workloads and stabilization of the systems are requested. Configuration management copes with these problems. Configuration management is a process of the design, verification, and deployment of configurations of ICT systems. Configuration management can reduce the workloads and improper settings of design by describing the rules for the design and verifying the configurations. However, the problem is that it is too hard for non-experts to describe the rules correctly. We thus focused on the characteristics of the configurations that have relationships (such as same/different) between two devices or software that corresponds to the tree structure of the ICT system (such as servers, racks, and data centers). By using the relationships as verification rules that should be satisfied by the configurations, we developed configuration management technology that does not require rules written by operation managers. This technology reduces the workloads on design and verification by consolidating the same configurations and reducing the number of managed configurations. Moreover, the technology discovers improper settings by verifying the configurations based on the relationships. We implemented a prototype of our technology and applied it to real systems. As a result, the following effects were confirmed. 1) 94 percent (117,632/125,286) of the configurations converged under an environment of servers with uniform configurations, and 94 percent of the workloads were also reduced. 2) Improper settings were successfully discovered under two different systems.