Hybrid Cloud environments allow the utilization of local resources in private Clouds with resources from public Clouds when needed. Such environments represent systems with high failure rates because they feature heterogeneous components, a large number of servers with intensive workload are built as complex architectures. For these reasons, the availability of such systems could be easily compromised if the failure of these heterogeneous components is not handled correctly, which may cause request rejection and frequent performance degradation. Providing highly reliable Cloud applications, in particular in a hybrid Cloud environment, is a challenging and critical research problem. Therefore, the question we address in this paper is how to provision resources to user requests in the presence of failures in a hybrid Cloud environment. To this end, we propose a reconfigurable formal model of the hybrid Cloud architecture, then we utilize instantiations of this model, simulation and real-time execution runs to estimate different performance metrics related to fault detection and self-recovery strategies in hybrid Cloud. Our approach is based on the combination of the model-based and the probabilistic approaches.

混合云环境允许在需要时利用私有云中的本地资源和公共云中的资源。这样的环境表示系统具有较高的故障率，因为它们具有异构组件，大量工作量大的服务器被构建为复杂的体系结构。由于这些原因，如果未正确处理这些异构组件的故障，则很容易损害此类系统的可用性，这可能会导致请求拒绝和频繁的性能下降。提供高度可靠的云应用程序，尤其是在混合云环境中，是一个充满挑战且至关重要的研究问题。因此，我们在本文中要解决的问题是在混合云环境中出现故障时如何为用户请求提供资源。为此，我们提出了混合云架构的可重构形式模型，然后利用该模型的实例化，仿真和实时执行运行来估计与混合云中的故障检测和自我恢复策略相​​关的不同性能指标。我们的方法是基于模型的方法和概率方法的结合。