Telemetry-Driven Microservices Orchestration in Cloud-Edge Environments

The orchestration of distributed microservices-based applications, particularly within geo-distributed Cloud-to-Edge environments, poses significant challenges. While Kubernetes stands as the predominant container orchestration standard in Cloud data centers, its static container scheduling approach presents limitations in deploying complex, distributed microservices-based applications across Edge environments. Presently, the scheduling process in Kubernetes fails to consider current infrastructure network conditions, resource usage, or runtime application statecrucial factors for mitigating the heterogeneous and dynamic nature of Cloud-to-Edge infrastructure and optimizing application response times. In this study, we propose an enhancement of the Kubernetes platform by implementing a load and network-aware microser-vices scheduling and orchestration strategy. The idea is to extend the Kubernetes control and scheduling logic with a dynamic orchestration strategy, continuously adapting application place-ment based on the real-time state of both the infrastructure and the application itself. We evaluate the efficacy of our approach by comparing it with the default Kubernetes orchestration and scheduling strategy.