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.
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