Abstract
Cloud computing has gained popularity in recent years due to its pay-as-you-go business model, high availability of services, and scalability. Service unavailability does not affect just user experience but is also translated into direct costs for cloud providers and companies. Part of this costs is due to SLA breaches, once interruption time greater than those signed in the contract generate financial penalties. Thus, cloud providers have tried to identify failure points and estimate the availability of their services. This paper proposes models to assess the availability of services running in a cloud data center infrastructure. The models follow the TIA-942 standard. We propose Tier I and IV models using the Reliability Block Diagram (RBD) to allow modeling of different types of applications, and Stochastic Petri Net (SPN) to represent the failure behavior of information technology (IT) components in a data center. We perform stationary analysis to measure the service availability, and sensitivity analysis to understand which metrics have major impacts on data center availability.
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