Disaster management, such as early warnings for earthquakes, hurricanes, and fires, requires IoT sensors and cameras, which produce tremendous amounts of data.To avoid network bandwidth congestion, much of this data needs to be processed close to where it is produced, as enabled by Mobile Edge Clouds (MEC). However, for such use cases, the disaster itself may take out the MEC, hence hindering disaster management efforts. We present a fault tolerance infrastructure tailored specifically for MEC systems to address various types of failures as part of a holistic disaster recovery solution. Our research investigates using current technologies, such as Kubernetes, to effectively handle fault tolerance in situations involving the failure of one or several edge nodes and RabbitMQ as a resilient message broker in our proposed infrastructure to ensure dependable message transmission, even during network outages. To evaluate our framework, we conduct a case study using weather stations as mission-critical assets within an urban setting next to forests where edge nodes are placed as safely as possible. The experiments demonstrate that the infrastructure can handle two node failures simultaneously. The proposed infrastructure ensures 99.966\% availability for both the system and mission-critical applications.