2016 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (2016)
Oct. 5, 2016 to Oct. 7, 2016
Cloud system's operations is complex due to the inherent cloud characteristics rapid elasticity, system automation and location independent resource pooling. Transparency and quality management of these cloud characteristics are crucial for the market and customer acceptance of each cloud provider. The necessary prerequisite for this is the definition and standardization of measurement methods of cloud characteristics as they are defined by NIST. The definition of measurement methods and metrics from the perspective of cloud providers is not finalized yet. This paper introduces two metrics: (1) the system operation learning rate and (2) the system entropy rate in the context of ITIL processes. Both metrics are used to evaluate the quality of IT service management processes (e.g. incident processes) and their relation to the rapid system growth in cloud systems. Moreover, the metrics indicate, if a resource expansion of a cloud is managed properly and how the ITIL processes are implemented within the cloud system. This paper concludes with a field study of both metrics in a long-time test and discussion.
Cloud computing, Measurement, Entropy, Production, Automation, NIST, Elasticity
A. Fiegler, A. Zwanziger, S. Herden and R. R. Dumke, "Quality Measurement of ITIL Processes in Cloud Systems," 2016 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement(IWSM Mensura), Berlin, Germany, 2016, pp. 87-94.