We argue in this paper that autonomic systems need to make their integrated monitoring adaptive in order to improve their "comprehensive" Quality of Service (QoS). We propose to design this adaptation based on high level objectives (called goals) related to the management of both the "functional system QoS" and the "monitoring system QoS". Starting from some previous works suggesting a model-driven adaptable monitoring framework composed of 3 layers (configurability, adaptability, governability), we introduce a methodology to identify the functional and monitoring high level goals (according to the agreed Service Level Agreement-SLA) in order to drive models' instanciations. This proposal is first applied to a cloud provider case study for which two high level goals are developed (respect metrics freshness and minimize monitoring cost), and then simulated to show how the quality of management decisions, as well as intelligent monitoring of dynamic SLA, could be improved.
Abstract. This paper argues that autonomic systems need to make their distributed monitoring adaptive in order to improve their "comprehensive" resulting quality; that means both the Quality of Service (QoS), and the Quality of Information (QoI). Thus, we propose a methodology to design monitoring adaptation based on high level objectives (goals) related to the management of quality requirements. One of the advantages of adopting a methodological approach, is that monitoring reconfiguration will be conducted through a consistent adaptation logic. Starting from a model-guided monitoring framework, we introduce our methodology to assist human administrators in eliciting the appropriate quality goals piloting the monitoring. Moreover, some monitoring adaptation patterns falling into reconfiguration dimensions are suggested and exploited in a cloud provider case-study illustrating the adaptation of Quality-Oriented monitoring.
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