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IoT Edge Computing with MicroK8s

You're reading from   IoT Edge Computing with MicroK8s A hands-on approach to building, deploying, and distributing production-ready Kubernetes on IoT and Edge platforms

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803230634
Length 416 pages
Edition 1st Edition
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Author (1):
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Karthikeyan Shanmugam Karthikeyan Shanmugam
Author Profile Icon Karthikeyan Shanmugam
Karthikeyan Shanmugam
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Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1: Foundations of Kubernetes and MicroK8s
2. Chapter 1: Getting Started with Kubernetes FREE CHAPTER 3. Chapter 2: Introducing MicroK8s 4. Part 2: Kubernetes as the Preferred Platform for IoT and Edge Computing
5. Chapter 3: Essentials of IoT and Edge Computing 6. Chapter 4: Handling the Kubernetes Platform for IoT and Edge Computing 7. Part 3: Running Applications on MicroK8s
8. Chapter 5: Creating and Implementing Updates on a Multi-Node Raspberry Pi Kubernetes Clusters 9. Chapter 6: Configuring Connectivity for Containers 10. Chapter 7: Setting Up MetalLB and Ingress for Load Balancing 11. Chapter 8: Monitoring the Health of Infrastructure and Applications 12. Chapter 9: Using Kubeflow to Run AI/MLOps Workloads 13. Chapter 10: Going Serverless with Knative and OpenFaaS Frameworks 14. Part 4: Deploying and Managing Applications on MicroK8s
15. Chapter 11: Managing Storage Replication with OpenEBS 16. Chapter 12: Implementing Service Mesh for Cross-Cutting Concerns 17. Chapter 13: Resisting Component Failure Using HA Clusters 18. Chapter 14: Hardware Virtualization for Securing Containers 19. Chapter 15: Implementing Strict Confinement for Isolated Containers 20. Chapter 16: Diving into the Future 21. Frequently Asked Questions About MicroK8s
22. Index 23. Other Books You May Enjoy

Resisting Component Failure Using HA Clusters

In the previous chapter, we looked at how to enable Linkerd or Istio service mesh add-ons and inject sidecars into a sample application. We also looked at the dashboards that allow us to look at telemetry data in order to troubleshoot, manage, and improve applications. We then looked at how metrics, distributed traces, and access logs can help with overall service mesh observability. We additionally looked at some of the most common service mesh use cases today, as well as some recommendations for how to choose the correct service mesh. We also covered a list of service mesh configuration best practices.

Through the use of dynamic container scheduling, Kubernetes offers higher reliability and resiliency for distributed applications. But how can you ensure that Kubernetes itself remains operational when a component, or even an entire data center site, fails? In this chapter, we will look into our next use case on how to configure Kubernetes...

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