Summary
As companies embrace digital transformation, Industry 4.0, industrial automation, smart manufacturing, and all the advanced use cases that these initiatives provide, the relevance of Kubernetes, edge, and cloud collaborating to drive intelligent business decisions is becoming clear. We've looked at a different approach that shows how Kubernetes may be used for running edge workloads. In the next chapters, we'll go over the deployment of a whole Kubernetes cluster at the edge approach in depth. Other approaches are beyond the scope of this book.
In the following chapters, we'll go over implementation aspects of common edge computing applications using MicroK8s in detail, such as running your applications on a multi-node Raspberry Pi cluster; configuring load balancing; installing/configuring different CNI plugins for network connectivity; configuring logging, monitoring, and alerting options; and building/deploying ML models and serverless applications.
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