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Edge Computing Systems with Kubernetes

You're reading from   Edge Computing Systems with Kubernetes A use case guide for building edge systems using K3s, k3OS, and open source cloud native technologies

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781800568594
Length 458 pages
Edition 1st Edition
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Author (1):
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Sergio Mendez Sergio Mendez
Author Profile Icon Sergio Mendez
Sergio Mendez
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Edge Computing Basics
2. Chapter 1: Edge Computing with Kubernetes FREE CHAPTER 3. Chapter 2: K3s Installation and Configuration 4. Chapter 3: K3s Advanced Configurations and Management 5. Chapter 4: k3OS Installation and Configurations 6. Chapter 5: K3s Homelab for Edge Computing Experiments 7. Part 2: Cloud Native Applications at the Edge
8. Chapter 6: Exposing Your Applications Using Ingress Controllers and Certificates 9. Chapter 7: GitOps with Flux for Edge Applications 10. Chapter 8: Observability and Traffic Splitting Using Linkerd 11. Chapter 9: Edge Serverless and Event-Driven Architectures with Knative and Cloud Events 12. Chapter 10: SQL and NoSQL Databases at the Edge 13. Part 3: Edge Computing Use Cases in Practice
14. Chapter 11: Monitoring the Edge with Prometheus and Grafana 15. Chapter 12: Communicating with Edge Devices across Long Distances Using LoRa 16. Chapter 13: Geolocalization Applications Using GPS, NoSQL, and K3s Clusters 17. Chapter 14: Computer Vision with Python and K3s Clusters 18. Chapter 15: Designing Your Own Edge Computing System 19. Index 20. Other Books You May Enjoy

Observability, monitoring, and analytics

To start, let’s get familiar with the observability concept. Peter Waterhouse mentioned, in his article in The New Stack, that "observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs." He also mentioned that observability is more of a property of a system and not something that you actually do.

There are two concepts that are close to each other in this context: monitoring and observability. In Steve Waterworth’s article, available at dzone.com, he mentioned this relation with the phrase, "If you are observable, I can monitor you."

What this means is that observability is achieved when data about systems is managed. Monitoring, on the other hand, it is the actual task of collecting and displaying this data. Finally, the analysis occurs after collecting data with a monitoring tool, and you perform it either manually or automatically.

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