Design an Edge System for the Cloud Native Edge Infrastructure

Design an Edge System for the Cloud Native Edge Infrastructure

In the previous article, I discussed how Rancher’s K3s lightweight Kubernetes distribution, Calico networking software, and the Portworx open source cloud native storage platform become the foundation for modern artificial intelligence (AI) and IoT systems that run at the edge. Let’s design and deploy a solution that runs on this infrastructure. Based on a hypothetical …

In the previous article, I discussed how Rancher’s K3s lightweight Kubernetes distribution, Calico networking software, and the Portworx open source cloud native storage platform become the foundation for modern artificial intelligence (AI) and IoT systems that run at the edge. Let’s design and deploy a solution that runs on this infrastructure.

Based on a hypothetical scenario of monitoring fans belonging to turbines, we will build a predictive maintenance solution that will detect anomalies in fans. This acts as a reference architecture for designing and architecting an IoT/edge solution that leverages various open source and the cloud native technologies.

Problem Statement

We are expected to design and deploy a solution that can ingest telemetry data from multiple fans and use the real-time stream to predict failures before they occur. The solution runs on the edge infrastructure running on low-end machines such as Intel NUCs. The infrastructure is based on K3s, Calico, and Portworx that provide the core building blocks of the Kubernetes cluster.

Solution Architecture

The sensors attached to the fans of the turbine provide the current rotational speed, vibration, temperature, and noise level. This telemetry data stream along with the deviceID from each fan acts as the input to the predictive maintenance solution.

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