Criticality-aware Monitoring and Orchestration for Containerized Industry 4.0 Environments

Abstract

The evolution of industrial environments makes the reconfigurability and flexibility key requirements to rapidly adapt to changeable market needs. Computing paradigms like Edge/Fog computing are able to provide the required flexibility and scalability while guaranteeing low latencies and response times. Orchestration systems play a key role in these environments, enforcing automatic management of resources and workloads’ lifecycle, and drastically reducing the need for manual interventions. However, they do not currently meet industrial non-functional requirements, such as real-timeliness, determinism, reliability, and support for mixed-criticality workloads. In this article, we present k4.0s, an orchestration system for Industry 4.0 (I4.0) environments, which enables the support for real-time and mixed-criticality workloads. We highlight through experiments the need for novel monitoring approaches and propose a workflow for selecting monitoring metrics, which depends on both workload requirements and hosting node guarantees. We introduce new abstractions for the components of a cluster in order to enable criticality-aware monitoring and orchestration of real-time industrial workloads. Finally, we design an orchestration system architecture that reflects the proposed model, introducing new components and prototyping a Kubernetes-based implementation, taking the first steps towards a fully I4.0-enabled orchestration system.