Marginal metric utility for autonomic cloud application management

Abstract

Managing Cloud applications with variable resource requirements over time is an insipid task that could benefit from autonomic application management. The management platform will then need to know what the application owner considers a good deployment for the current execution context, which is normally captured by a utility function. However, it is often difficult to define such a function directly by first principles in a way that would perfectly capture the application owner's preferences. This paper proposes a methodology for defining the utility function only from the monitoring measurements taken to assess the state and context of the running application.