book

IoT Edge Computing with MicroK8s

Name: IoT Edge Computing with MicroK8s
Author: Karthikeyan Shanmugam
ISBN: 9781803230634

by Karthikeyan Shanmugam

September 2022

Intermediate to advanced

416 pages

9h 16m

English

Packt Publishing

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IoT Edge Computing with MicroK8s
ContributorsAbout the authorAbout the reviewers
Preface
Who this book is forWhat this book coversTo get the most out of this bookDownload the example code filesDownload the color imagesConventions usedGet in touchShare Your Thoughts
Part 1: Foundations of Kubernetes and MicroK8s
Chapter 1: Getting Started with Kubernetes
The evolution of containersKubernetes overview – understanding Kubernetes componentsInteracting with a Kubernetes clusterUnderstanding podsUnderstanding deploymentsUnderstanding StatefulSets and DaemonSetsStatefulSetsDaemonSetsUnderstanding jobs and CronJobsJobsCronJobUnderstanding servicesSummary
Chapter 2: Introducing MicroK8s
Introducing MicroK8s KubernetesQuick installationTechnical requirements Step 1 – InstallationStep 2 – Verify the installationDeploying a sample applicationEnabling add-onsFull list of add-onsStarting/stopping MicroK8sConfiguring MicroK8s to use local imagesConfiguring MicroK8s to use its built-in registryConfiguring MicroK8s to use private/public registriesConfiguring MicroK8s servicesTroubleshooting application and cluster issuesThe application levelThe cluster levelSummary
Part 2: Kubernetes as the Preferred Platform for IoT and Edge Computing
Chapter 3: Essentials of IoT and Edge Computing
What is IoT?Key elements of an IoT solutionWhat is edge computing?How are IoT and the edge related?Benefits of edge computingWhat does it take to enable edge computing, edge analytics, and edge intelligence?Summary
Chapter 4: Handling the Kubernetes Platform for IoT and Edge Computing
Deployment approaches for edge computingDeployment of the entire Kubernetes cluster at the edgeDeployment of Kubernetes nodes at the edgeDeployment of virtual Kubernetes nodes at the edgeDeployment of Kubernetes devices at the edgePropositions that Kubernetes offersSummary
Part 3: Running Applications on MicroK8s
Chapter 5: Creating and Implementing Updates on a Multi-Node Raspberry Pi Kubernetes Clusters
Creating a MicroK8s multi-node cluster using  a Raspberry PiWhat we are trying to achieve Configuring Wi-Fi access settingsInstalling and configuring MicroK8s Adding the worker nodeDeploying a sample containerized applicationPerforming rolling updates to the application with a new software versionScaling the application deploymentGuidelines on multi-node cluster configurationCluster-level configuration/settingsContainer life cycle managementDeploying and sharing HA applicationsSummary

Chapter 6: Configuring Connectivity for Containers
CNI overviewCommunication flow from Pod 3 to Pod 6Configuring Calico Requirements Step 1 – Creating a MicroK8s Raspberry Pi cluster Step 2 – Enabling the Calico CNI add-on Step 3 – Deploying a sample containerized applicationStep 4 – Applying isolation by using NetworkPolicyStep 5 – Enabling access Configuring Cilium Step 1 – Enabling the Cilium add-on Step 2 – Enabling the DNS add-on Step 3 – Deploying a sample containerized applicationStep 4 – Applying isolation by using NetworkPolicyStep 5 – Enabling access Configuring Flannel CNI Disabling the HA cluster to enable the Flannel add-on Guidelines on choosing a CNI providerKey considerations when choosing a CNI providerSummary
Chapter 7: Setting Up MetalLB and Ingress for Load Balancing
Overview of MetalLB and IngressConfiguring MetalLB to load balance across the clusterRequirements Step 1 – Creating a MicroK8s Raspberry Pi cluster Step 2 – Enabling the MetalLB add-on Step 3 – Deploying a sample containerized applicationStep 4 – Verifying the load balancer mechanism Configuring Ingress to expose Services outside the clusterOption 1 – Using the Ingress NodePort methodOption 2 – Using Ingress and a load balancer Guidelines on how to choose the right load balancer for your applicationsSummary
Chapter 8: Monitoring the Health of Infrastructure and Applications
Overview of monitoring, logging, and alerting optionsConfiguring a monitoring and alerting stack using the Prometheus, Grafana, and Alertmanager toolsRequirements for setting up a MicroK8s Raspberry Pi clusterStep 1 – Creating a MicroK8s Raspberry Pi cluster Step 2 – Configuring Prometheus, Grafana, and AlertmanagerStep 3 – Accessing Prometheus, Grafana, and AlertmanagerConfiguring a logging, monitoring, and alerting stack using the EFK toolset Step 1 – Enabling the Fluentd add-on Step 2 – Defining an index pattern Step 3 – Filtering and viewing the data Key metrics that need to be monitored Kubernetes eventsSummary
Chapter 9: Using Kubeflow to Run AI/MLOps Workloads
Overview of the ML workflowIntroduction – Kubeflow and its componentsIntroduction to the ML workflowKubeflow components in each phaseKubeflow PipelinesDeploying Kubeflow What we are trying to achieve Step 1 – Installing and configuring MicroK8sStep 2 – Installing Juju Operator Lifecycle Manager Step 3 – Post-installation configurationsAccessing the Kubeflow dashboardCreating a Kubeflow pipeline to build, train, and deploy a sample ML modelStep 1 – launching a new notebook server from the Kubeflow dashboardStep 2 – creating a Kubeflow pipelineStep 3 – compiling and runningRecommendations – running AL/ML workloads on Kubernetes Best practices for running AI/ML workloads Summary
Chapter 10: Going Serverless with Knative and OpenFaaS Frameworks
Overview of the Knative frameworkBuild componentsServing componentsEventing componentsEnabling the Knative add-onDeploying and running a sample service on KnativeOverview of the OpenFaaS framework Enabling the OpenFaaS add-onDeploying and running a sample function on OpenFaaSBest practices for developing and deploying serverless applicationsServerless function = specific function Using microservicesUsing appropriate stacks for various resourcesApplying the principle of least privilege Performing load testingUsing a CI/CD pipelineConstant monitoring is requiredAuditing in addition to monitoringAuditing software dependenciesSummary
Part 4: Deploying and Managing Applications on MicroK8s
Chapter 11: Managing Storage Replication with OpenEBS
Overview of OpenEBS Control planeData planeStorage enginesConfiguring and implementing a PostgreSQL stateful workload Requirements Step 1 – Creating the MicroK8s Raspberry Pi cluster Step 2 – Enabling the OpenEBS add-on Step 3 – Deploying the PostgreSQL stateful workload Step 4 – Creating the test data Step 5 – Simulating node failureKubernetes storage best practicesGuidelines on choosing OpenEBS data enginesSummary
Chapter 12: Implementing Service Mesh for Cross-Cutting Concerns
Overview of the Linkerd service meshEnabling the Linkerd add-on and running a sample applicationStep 1 – Enabling the Linkerd add-on Step 2 – Deploying the sample applicationStep 3 – Exploring the Linkerd dashboardOverview of the Istio service meshEnabling the Istio add-on and running a sample applicationStep 1 – Enabling the Istio add-on Step 2 – Deploying the sample applicationStep 3 – Exploring the Istio service dashboardCommon use cases for a service meshGuidelines on choosing a service meshBest practices for configuring a service meshSummary
Chapter 13: Resisting Component Failure Using HA Clusters
An overview of HA topologiesSetting up an HA Kubernetes clusterRequirementsStep 1 – Creating the MicroK8s Raspberry Pi clusterStep 2 – Examining the HA setupStep 3 – Deploying a sample containerized applicationStep 3 – Simulating control plane node failureKubernetes HA best practicesSummary
Chapter 14: Hardware Virtualization for Securing Containers
Overview of Kata ContainersHow Kata Containers worksEnabling the Kata add-on and running a sample applicationStep 1 – Enabling the Kata add-on Step 2 – Deploying a sample applicationContainer security best practices Utilizing DevSecOpsScanning external vulnerabilities via dependency scanningAnalyzing container images using image scanning toolsEnforcing image content trustSecuring registriesSecuring your hostSecuring your runtimeReviewing container privileges Using real-time event and log auditingMonitoring resource usageCommon security misconfigurations and remediationSummary
Chapter 15: Implementing Strict Confinement for Isolated Containers
Overview of Snap, Snapcraft, and Ubuntu CoreSetting up Ubuntu Core on a Raspberry Pi boardWhat we are trying to achieve RequirementsStep 1 – Setting up an Ubuntu Core image to an SD cardStep 2 – Creating an Ubuntu SSO accountStep 3 – Generating an SSH key pairStep 4 – Booting Ubuntu Core on Raspberry PiSetting up MicroK8s on Ubuntu CoreAdding the worker nodeDeploying a sample containerized applicationSummary
Chapter 16: Diving into the Future
How MicroK8s is uniquely positioned for accelerating IoT and Edge deploymentsSome of the notable challenges in operating IoT edgeHow MicroK8s Kubernetes is benefiting edge devicesLooking forward – Kubernetes trends and industry outlookTrend 1 – security is still everyone’s concernTrend 2 – GitOps for continuous deploymentTrend 3 – App store for operatorsTrend 4 – Serverless computing and containersTrend 5 – AI/ML and data platformsTrend 6 – Stateful applicationsSummaryFurther reading
Frequently Asked Questions About MicroK8s
Index
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Overview

IoT Edge Computing with MicroK8s is your practical guide to mastering the deployment and management of Kubernetes for IoT and edge computing use cases. By exploring the capabilities of MicroK8s, a lightweight and efficient Kubernetes distribution, you will gain the skills to deploy applications, secure environments, and manage services on edge platforms effectively.

What this Book will help me do

Understand and set up MicroK8s to facilitate Kubernetes-based operations for IoT and edge computing.
Learn to create and manage multi-node Kubernetes clusters on portable platforms such as Raspberry Pi.
Integrate AI/ML workloads into IoT and Edge setups using platforms like Kubeflow.
Effectively monitor and secure applications and infrastructure using logs, metrics, and security tools.
Implement high availability, service mesh, and durability strategies for production-grade edge computing.

Author(s)

Karthikeyan Shanmugam brings his extensive experience in cloud-native technologies and Kubernetes to this written work. As a developer and tech leader, Karthikeyan focuses on making DevOps and edge computing accessible to professionals worldwide. With a passion for IoT innovations, his thorough yet approachable writing style aims to empower developers and architects alike.

Who is it for?

This book is perfect for DevOps engineers, Site Reliability Engineers (SREs), and developers aiming to integrate Kubernetes into IoT and edge computing. It is tailored for professionals seeking to enhance their knowledge in cloud-native setups and deploy scalable applications on innovative platforms. With basic knowledge of containers and networking, readers will find this book invaluable.

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ISBN: 9781803230634

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