Edge Computing Systems With Kubernetes

Understand how to use K3s and k3OS for different use cases and discover best practices for building an edge computing system Key FeaturesA guide to implementing an edge computing environmentReduce latency and costs for real-time applications running at the edgeFind stable and relevant cloud native open source software to complement your edge environmentsBook 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 use the content of these chapters as small pieces to create your own edge computing system. What you will learnConfigure k3OS and K3s for development and production scenariosPackage applications into K3s for shipped-node scenariosDeploy in occasionally connected scenarios, from one node to one million nodesManage GitOps for applications across different locationsUse open source cloud native software to complement your edge computing systemsImplement observability event-driven and serverless edge applicationsCollect and process data from sensors at the edge and visualize it into the cloudWho 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.

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.

A step-by-step, comprehensive guide that includes real-world use cases to help you successfully develop and run applications and mission-critical workloads using MicroK8s Key FeaturesAn easy-to-follow guide that helps you get started with MicroK8s and other Kubernetes componentsUnderstand the key concepts and constraints for building IoT and edge architecturesGet guidance on how to develop and deploy use cases and examples on IoT and edge computing platformsBook Description 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. What you will learnGet a holistic view of MicroK8s features using a sample applicationUnderstand IoT and edge computing and their architecture constraintsCreate, scale, and update HA Raspberry Pi multi-node clustersImplement AI/ML use cases with the Kubeflow platformWork with various networking plugins, and monitoring and logging toolsPerform service mesh integrations using Istio and LinkerdRun serverless applications using Knative and OpenFaaS frameworksSecure your containers using Kata and strict confinement optionsWho this book is for This book is for DevOps and cloud engineers, SREs, and application developers who want to implement efficient techniques for deploying their software solutions. It will also be useful for technical architects and technology leaders who are looking to adopt cloud-native technologies. A basic understanding of container-based application design and development, virtual machines, networking, databases, and programming will be helpful for using this book.

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. It starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from Edge Computing platforms. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms. Chapter 5 introduces AI/ML pipelines to efficiently process generated data on the edge. Chapter 6 introduces ways to implement AI/ML systems on the edge and ways to deal with their training and inferencing procedures considering the limited resources available at the edge-nodes. Chapter 7 motivates the creation of a new orchestrator independent object model to descriptive objects (nodes, applications, etc.) and requirements (SLAs) for underlying edge platforms. To provide hands-on experience to students and step-by-step improve their technical capabilities, seven sets of Tutorials-and-Labs (TaLs) are also designed. Codes and Instructions for each TaL is provided on the book website, and accompanied by videos to facilitate their learning process.

Introducing "Edge Computing 101: Novice to Pro" - your ultimate guide to mastering edge computing from beginner to expert level. This comprehensive book bundle includes four essential volumes packed with expert techniques and practical applications to propel your understanding and proficiency in edge computing. Book 1, "Edge Computing Fundamentals: A Beginner's Guide to Distributed Systems," provides a solid foundation for understanding the core principles of distributed systems. Whether you're new to the field or seeking to reinforce your knowledge, this book equips you with the fundamental concepts necessary to embark on your journey into the world of edge computing. In Book 2, "Edge Computing Architectures: Design Principles and Best Practices," you'll delve deeper into the intricacies of designing effective edge computing architectures. From deployment models to optimization techniques, this volume offers invaluable insights and best practices to help you build robust and scalable edge systems. For those looking to advance their skills, Book 3, "Advanced Edge Computing: Scalability, Security, and Optimization Strategies," explores advanced techniques and strategies for overcoming scalability challenges, enhancing security measures, and optimizing performance in edge environments. With real-world examples and case studies, you'll gain practical expertise to tackle complex issues and achieve optimal outcomes. Finally, Book 4, "Edge Computing in Industry 4.0: Practical Applications and Future Trends," focuses on the practical applications of edge computing across various industries, with a special emphasis on Industry 4.0. Discover how edge computing is transforming manufacturing, healthcare, smart cities, and more, and gain insights into future trends shaping the industry. Whether you're a novice looking to build a strong foundation or a seasoned professional aiming to stay ahead of the curve, "Edge Computing 101: Novice to Pro" has you covered. With its comprehensive coverage, expert guidance, and practical insights, this book bundle is your essential companion for mastering the dynamic world of edge computing. Get your copy today and take your edge computing skills to the next level!

Fueled by ubiquitous computing ambitions, the edge is at the center of confluence of many emergent technological trends such as hardware-rooted trust and code integrity, 5G, data privacy and sovereignty, blockchains and distributed ledgers, ubiquitous sensors and drones, autonomous systems and real-time stream processing. Hardware and software pattern maturity have reached a tipping point so that scenarios like smart homes, smart factories, smart buildings, smart cities, smart grids, smart cars, smart highways are in reach of becoming a reality. While there is a great desire to bring born-in-the-cloud patterns and technologies such as zero-downtime software and hardware updates/upgrades to the edge, developers and operators alike face a unique set of challenges due to environmental differences such as resource constraints, network availability and heterogeneity of the environment. The first part of the book discusses various edge computing patterns which the authors have observed, and the reasons why these observations have led them to believe that there is a need for a new architectural paradigm for the new problem domain. Edge computing is examined from the app designer and architect’s perspectives. When they design for edge computing, they need a new design language that can help them to express how capabilities are discovered, delivered and consumed, and how to leverage these capabilities regardless of location and network connectivity. Capability-Oriented Architecture is designed to provide a framework for all of these. This book is for everyone who is interested in understanding what ubiquitous and edge computing means, why it is growing in importance and its opportunities to you as a technologist or decision maker. The book covers the broad spectrum of edge environments, their challenges and how you can address them as a developer or an operator. The book concludes with an introduction to a new architectural paradigm called capability-based architecture, which takes into consideration the capabilities provided by an edge environment. .

This reference text presents the state-of-the-art in edge computing, its primitives, devices and simulators, applications, and healthcare-based case studies. The text provides integration of blockchain with edge computing systems and integration of edge with Internet of Things (IoT) and cloud computing. It will facilitate readers to setup edge-based environment and work with edge analytics. It covers important topics, including cluster computing, fog computing, networking architecture, edge computing simulators, edge analytics, privacy-preserving schemes, edge computing with blockchain, autonomous vehicles, and cross-domain authentication. Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology, this text: Discusses edge data storage security with case studies and blockchain integration with the edge computing system Covers theoretical methods with the help of applications, use cases, case studies, and examples Provides healthcare real-time case studies elaborated by utilizing the virtues of homomorphic encryption Discusses real-time interfaces, devices, and simulators in detail

The success of the Internet of Things and rich cloud services have helped create the need for edge computing, in which data processing occurs in part at the network edge, rather than completely in the cloud. In Edge Computing: A Primer the vision and definition of Edge computing is introduced, as well as several key techniques that enable Edge computing. Then, four applications that benefit from Edge computing are presented as case studies, ranging from smart homes and public safety to medical services, followed by a discussion of several open challenges and opportunities in Edge computing. Finally, several key tools for edge computing such as virtualization and resource management are explained.