Automating SLA monitoring involves minimizing human involvement in the overall monitoring process. SLA monitoring is difficult to automate as it would need precise and unambiguous specification and a customizable engine that collects the right measurement, models the data and evaluates the SLA at certain times or when certain events happen. Also most of the SLA neglect client side measurement or restrict SLAs to measurements based only on server side. In a cross-enerprise scenario like web services it will be important to obtain measurements at multiple sites and to guarantee SLAs on them. In this article we propose an automated and distributed SLA monitoring engine.

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Service providers and their customers agree on certain quality of service guarantees through Service Level Agreements (SLA). An SLA contains one or more Service Level Objectives (SLO)s that describe the agreed-upon quality requirements at the service level. Translating these SLOs into lower-level policies that can then be used for design and monitoring purposes is a difficult problem. Usually domain experts are involved in this translation that often necessitates application of domain knowledge to this problem. In this article, we propose an approach that combines performance modeling with regression analysis to solve this problem. We demonstrate that our approach is practical and that it can be applied to different n-tier services. Our experiments show that for a typical 3-tier e-commerce application in a virtualized environment, the SLA can be met while improving CPU utilization by up to 3 times.

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