| Description |
1 online resource (458 p.) |
| Note |
Description based upon print version of record. |
| Contents |
Cover -- Title Page -- Copyright and Credits -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1: Edge Computing Basics -- Chapter 1: Edge Computing with Kubernetes -- Technical requirements -- Edge data centers using K3s and basic edge computing concepts -- The edge and edge computing -- Benefits of edge computing -- Containers, Docker, and containerd for edge computing -- Distributed systems, edge computing, and Kubernetes -- Edge clusters using K3s -- a lightweight Kubernetes -- Edge devices using ARM processors and micro data centers |
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Edge computing diagrams to build your system -- Edge cluster and public cloud -- Regional edge clusters and public cloud -- Single node cluster and public/private cloud -- Adapting your software to run at the edge -- Adapting Go to run on ARM -- Adapting Rust to run on ARM -- Adapting Python to run on ARM -- Adapting Java to run on ARM -- Summary -- Questions -- Further reading -- Chapter 2: K3s Installation and Configuration -- Technical requirements -- Introducing K3s and its architecture -- Preparing your edge environment to run K3s -- Hardware that you can use |
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Linux distributions for ARM devices -- Creating K3s single and multi-node clusters -- Creating a single node K3s cluster using Ubuntu OS -- Adding more nodes to your K3s cluster for multi-node configuration -- Extracting K3s kubeconfig to access your cluster -- Advanced configurations -- Using external MySQL storage for K3s -- Installing Helm to install software packages in Kubernetes -- Changing the default ingress controller -- Uninstalling K3s from the master node or an agent node -- Troubleshooting a K3s cluster -- Summary -- Questions -- Further reading |
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Chapter 3: K3s Advanced Configurations and Management -- Technical requirements -- Bare metal load balancer with MetalLB -- Load balancer services in Kubernetes -- KlipperLB and MetalLB as bare metal load balancers -- KlipperLB and MetalLB -- the goods and the bads -- Installing MetalLB -- Troubleshooting MetalLB -- Setting up Longhorn for storage -- Why use Longhorn? -- Installing Longhorn with ReadWriteMany mode -- Using Longhorn UI -- Upgrading your cluster -- Upgrading using K3s Bash scripts -- Upgrading K3s manually -- Restarting K3s -- Backing up and restoring your K3s configurations |
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Backups from SQLite -- Backups and restoring from the SQL database K3s backend -- Embedded etcd management -- Installing the etcd backend -- Creating and restoring etcd snapshots -- Summary -- Questions -- Further reading -- Chapter 4: k3OS Installation and Configurations -- Technical requirements -- k3OS -- the Kubernetes operating system -- k3OS installation for x86_64 devices using an ISO image -- Advanced installations of k3OS using config files -- k3OS config file sections -- Configurations for master and agent nodes -- Multi-node cluster creation using config files |
| Note |
Creating a multi-node K3s cluster using config files |
| Summary |
Understand how to use K3s and k3OS for different use cases and discover best practices for building an edge computing system Key Features A guide to implementing an edge computing environment Reduce latency and costs for real-time applications running at the edge Find stable and relevant cloud native open source software to complement your edge environments Book Description Edge computing is a way of processing information near the source of data instead of processing it on data centers in the cloud. In this way, edge computing can reduce latency when data is processed, improving the user experience on real-time data visualization for your applications. Using K3s, a light-weight Kubernetes and k3OS, a K3s-based Linux distribution along with other open source cloud native technologies, you can build reliable edge computing systems without spending a lot of money. In this book, you will learn how to design edge computing systems with containers and edge devices using sensors, GPS modules, WiFi, LoRa communication and so on. You will also get to grips with different use cases and examples covered in this book, how to solve common use cases for edge computing such as updating your applications using GitOps, reading data from sensors and storing it on SQL and NoSQL databases. Later chapters will show you how to connect hardware to your edge clusters, predict using machine learning, and analyze images with computer vision. All the examples and use cases in this book are designed to run on devices using 64-bit ARM processors, using Raspberry Pi devices as an example. By the end of this book, you will be able to build your own edge computing systems using the content of the chapters as Lego pieces to fit your needs. What you will learn Configure k3OS and K3s for development and production scenarios Package applications into K3s for shipped-node scenarios Deploy in occasionally connected scenarios, from one node to one million nodes Manage GitOps for applications across different locations Use open source cloud native software to complement your edge computing systems Implement observability event-driven and serverless edge applications Collect and process data from sensors at the edge and visualize it into the cloud Who this book is for This book is for engineers (developers and/or operators) seeking to bring the cloud native benefits of GitOps and Kubernetes to the edge. Anyone with basic knowledge of Linux and containers looking to learn Kubernetes using examples applied to edge computing and hardware systems will benefit from this book. |
| Subject |
Kubernetes.
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Edge computing.
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Edge computing |
| Other Form: |
Print version: Mendez, Sergio Edge Computing Systems with Kubernetes Birmingham : Packt Publishing, Limited,c2022 |
| ISBN |
9781800566989 |
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1800566980 |
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