Book Image

IoT Edge Computing with MicroK8s

By : Karthikeyan Shanmugam
Book Image

IoT Edge Computing with MicroK8s

By: Karthikeyan Shanmugam

Overview of this book

Are you facing challenges with developing, deploying, monitoring, clustering, storing, securing, and managing Kubernetes in production environments as you're not familiar with infrastructure technologies? MicroK8s - a zero-ops, lightweight, and CNCF-compliant Kubernetes with a small footprint is the apt solution for you. This book gets you up and running with production-grade, highly available (HA) Kubernetes clusters on MicroK8s using best practices and examples based on IoT and edge computing. Beginning with an introduction to Kubernetes, MicroK8s, and IoT and edge computing architectures, this book shows you how to install, deploy sample apps, and enable add-ons (like DNS and dashboard) on the MicroK8s platform. You’ll work with multi-node Kubernetes clusters on Raspberry Pi and networking plugins (such as Calico and Cilium) and implement service mesh, load balancing with MetalLB and Ingress, and AI/ML workloads on MicroK8s. You’ll also understand how to secure containers, monitor infrastructure and apps with Prometheus, Grafana, and the ELK stack, manage storage replication with OpenEBS, resist component failure using a HA cluster, and more, as well as take a sneak peek into future trends. By the end of this book, you’ll be able to use MicroK8 to build and implement scenarios for IoT and edge computing workloads in a production environment.
Table of Contents (24 chapters)
1
Part 1: Foundations of Kubernetes and MicroK8s
4
Part 2: Kubernetes as the Preferred Platform for IOT and Edge Computing
7
Part 3: Running Applications on MicroK8s
14
Part 4: Deploying and Managing Applications on MicroK8s
21
Frequently Asked Questions About MicroK8s

Summary

In this chapter, we looked at how to set up an HA MicroK8s Kubernetes cluster using the stacked cluster HA topology. We utilized the three nodes to install and configure MicroK8s on each of them, as well as simulating node failure to see whether the cluster could tolerate component failures and still continue to function normally.

We discussed some of the best practices for implementing Kubernetes applications on your production-ready cluster. We also covered the fact that MicroK8s’ HA option has been simplified and enabled by default.

HA is a vital feature for organizations looking to deploy containers and pods that can deliver the kind of reliability required at scale. We also recognized the value of Canonical's lightweight Dqlite SQL database, which is used to provide HA clustering. By embedding the database into Kubernetes, Dqlite reduces the cluster’s memory footprint and eliminates process overhead. For IoT or Edge applications, this is critical...