\section{Conclusions} \label{Comments}

In this paper, we proposed a stochastic approach for managing database service requirements, in SOA-based systems. 
By predicting the performance of DB transactions upon the variation of the workload, we provided support for planning suitable SLA for the response time, considering a range of possible arrival rates. 
In a inverse way, we also established SLA for the highest workload supported by a DB system, without overcome a previously agreed response time. These are only examples of possible information mined from our approach.

In order to illustrate our contributions, we compared the simulated results against those measured from a real DB implementation. 
The comparison shows that our estimates remain close with the measured samples, whatever the existent variability. 
Moreover, we established two examples of SLA requirements and, based on our estimates, we identified possible solutions for them. 
We remember that these analysis were conducted without requiring real-time measures. 
However, by focusing on representing the dynamic system behavior, we provide support at design-time and/or run-time, which contributes to avoid legal issues with SLA compliance. 

Prospects of future works aim to extend the performance model, inserting a timeout mechanism. 
So, would be possible to register the DB failure rate, establishing availability metrics. 
Moreover, by crossing failure and performance metrics, we could discover possible bottlenecks delaying DB transactions, so planning structural upgrades, access policies, load balancing and so one.
