# Computational and Communication Infrastructure Challenges for Resilient Cloud Services
## 5 Platform Resilience Mechanisms
### Traffic Management and Fault Tolerance
#### 5.1.1 Network Infrastructure Adaptation and Fault Tolerance
tolerant network architecture to support the Kubernetes cluster, offering redundant paths to guarantee that all the containers of the microservices in Kubernetes remain connected. This setup can also be used for IoT applications with nodes prone to failure. Fault-tolerant frameworks are also applicable for fog computing. [PERSON] et al., propose in [68], a model based on a Markov chain to use it as a fault-tolerant system. This system allows them to predict the number of fog nodes that can fail and change them to reduce delays and costs. This approach is focused only on nodes, whereas our work is focused on microservices that can be used with resilience mechanisms to reduce the impact of different types of failures. [PERSON] in [69] proposes a scheduling algorithm that integrates fault tolerance and cost reduction for applications in the cloud. [PERSON]'s model is based on the DAG model, which considers task priorities to select the best VM for executing the entire application. At the same time, the scheduling algorithm tries to find a backup to support the task that is not running correctly in the VM previously selected. The goal of our approach is not to schedule or allocate applications. Still, it is to provide a infrastructure with some resilient mechanisms to support the execution of applications. ## 8 Conclusions

In this paper, we provide a first evaluation of the computational and communications infrastructure requirements that must be met by a resilient cloud system. We present the design and implementation of a microservices-based platform that provides resilience to applications and evaluate it by deploying and testing a high-latency analytics application. Resiliency features such as hot migration and modification, redundancy, autoscaling, optimal computing and storage resource allocation systems, and load balancing services are crucial for this type of platform. In regard to the computing infrastructure requirements, the need for performance isolation mechanisms based on virtualization solutions and software containers was evidenced. These solutions also allow for the provision of lightweight, loosely coupled microservices and their distribution through public repositories. In terms of the communications infrastructure requirements, resilient solutions must support fault-tolerance mechanisms and traffic management in order to minimize the impacts on the quality of service when failures occur. Services should use lightweight, standardized communication interfaces based on protocols such as HTTP. In the same way, the use of protocols and technologies with low energy consumption is imperative. Performance isolation in the network and adaptation of the network infrastructure to failure, supported by efficient monitoring systems, are also required features. Trying to meet these requirements, we proposed a computational platform and demonstrated its ability to provide resilience to high-latency analytics applications. Our microservice-based platform, which leverages current container and orchestration technologies, allowed us to quantify the impact of different resilience mechanisms. Conceptualization, O.H.M. ; Investigation, O.H.M. and H.A.R. ; Methodology, O.H.M., H.A.R. and J.M. ; Software, H.F.M. and J.M. ; Supervision, O.H.M. ; Validation, H.F.M. and J.M. ; Visualization, J.M. ; Writing-original draft, H.F.M., O.H.M., H.A.R. and J.M. This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** All data were presented in main text. **Conflicts of Interest:** The authors declare no conflict of interest. ## References

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