Edge offloading is widely used to support the execution of near real-time mobile applications. However, offloading on edge infrastructures can suffer from failures due to the absence of supporting systems and environmental factors. We propose a fault-tolerant offloading method modeled as a Markov Decision Process (MDP) based on predictions performed through Support Vector Regression (SVR). SVR is used to estimate offloading service availability, which is used by MDP for offloading decisions. Our approach is implemented in a real-world test-bed and compared with the default Kubernetes scheduler augmented with hybrid fault-tolerance.

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