Resilient edge-to-cloud architecture with self-healing and self-correcting mechanisms for industrial data continuity

In the era of Industry 4.0, advanced technologies are transforming production processes, although their adoption introduces challenges related to integration, security and scalability in industrial environments. This study investigates the preservation of industrial data continuity under stress conditions. A structured literature review was conducted in Scopus and Web of Science, following the PRISMA methodology, to identify the resilience requirements. This was followed by the design and implementation of a hybrid edge-to-cloud (E2C) microservices architecture. The approach was validated through controlled overload and saturation experiments in a hybrid cloud–edge environment, utilising orchestration, monitoring, and alert-management tools such as Kubernetes, Rancher, Prometheus, Grafana, and Node-RED. The proposed architecture combines edge node execution with centralised cloud coordination (E2C) to address these challenges. A central motivation for this design is the recognition that industrial data represents a strategic asset. Interruptions or losses in data flows directly affect process traceability and degrade the performance of AI-driven monitoring and optimisation models. Such losses also trigger reprocessing, waste and suboptimal operational decisions. Therefore, ensuring data continuity and availability becomes an essential requirement for competitiveness and industrial sustainability. In this context, the study’s main contribution is integrating orchestration, alert management and monitoring tools into a closed-loop system that triggers self-healing and self-correcting actions when predefined thresholds are exceeded. This approach avoids systematic network failures, enables autonomous recovery without manual intervention and keeps system operations and data available. The paper validates the self-healing and self-correcting mechanisms through overload and saturation experiments. Results demonstrate the feasibility of a zero-touch strategy that enhances efficiency and sustainability in industrial automation, supporting the transition towards Industry 5.0. • A resilient Edge-to-Cloud (E2C) architecture is proposed to ensure data continuity for industrial environments. • It integrates orchestration, monitoring and alerting to enable self-healing and self-correcting mechanisms. • Prevents connectivity-driven data loss, ensuring continuous and reliable industrial data flows. • Validated through overload and saturation experiments, confirming autonomous recovery. • Supports efficient, sustainable automation and paves the way towards Industry 5.0.