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High availability (HA) is a main key performance indicator for cloud deployed services. Cloud providers offer different availability zones possibly located in different geographical regions. To protect cloud services against failures and natural disasters, it is recommended to deploy the applications on redundant resources across multiple zones and distribute the workload through a load-balancer. Different cloud infrastructure, located in different geographical zones with different energy source powering, hardware quality, etc., may have different reliability levels. Scheduling a cloud service on different zones while meeting the service level agreement availability requirements necessitate a solution to assess the expected availability of a given deployment. To quantify the expected availability offered by an application deployment, a formal stochastic model is required to capture the stochastic behavior of failures. This paper proposes a stochastic Petri Net model that captures the stochastic characteristics of cloud services and translates them into elements of an availability model. The model evaluates the availability of cloud services and their deployments in geographically distributed data centers (DCs). The results are useful to generate guidelines for an HA-aware scheduling.

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