Book Image

Mastering Kubernetes - Third Edition

By : Gigi Sayfan
Book Image

Mastering Kubernetes - Third Edition

By: Gigi Sayfan

Overview of this book

The third edition of Mastering Kubernetes is updated with the latest tools and code enabling you to learn Kubernetes 1.18’s latest features. This book primarily concentrates on diving deeply into complex concepts and Kubernetes best practices to help you master the skills of designing and deploying large clusters on various cloud platforms. The book trains you to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. With the two new chapters, you will gain expertise in serverless computing and utilizing service meshes. As you proceed through the chapters, you will explore different options for network configuration and learn to set up, operate, and troubleshoot Kubernetes networking plugins through real-world use cases. Furthermore, you will understand the mechanisms of custom resource development and its utilization in automation and maintenance workflows. By the end of this Kubernetes book, you will graduate from an intermediate to advanced Kubernetes professional.
Table of Contents (19 chapters)
17
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18
Index

Summary

In this chapter, we covered the topics of monitoring, observability, and, in general, day 2 operations. We started with a review of the various aspects of monitoring: logs, metrics, error reporting, and distributed tracing. Then, we discussed how to incorporate monitoring capabilities into your Kubernetes cluster. We looked at several CNCF projects like Fluentd for log aggregation, Prometheus for metrics collection and alert management, Grafana for visualization, and Jaeger for distributed tracing. Then, we explored troubleshooting large distributed systems. We realized how difficult it can be and why we need so many different tools to conquer the issues.

In the next chapter, we will take things to the next level and dive into service meshes. I'm super excited about service meshes because they take much of the complexity related to cloud-native, microservice-based applications and externalize them outside of the microservices. That has a lot of real-world value.

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