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The Complete Kubernetes Guide

You're reading from   The Complete Kubernetes Guide Become an expert in container management with the power of Kubernetes

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Product type Course
Published in May 2019
Publisher Packt
ISBN-13 9781838647346
Length 628 pages
Edition 1st Edition
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Authors (3):
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Jesse White Jesse White
Author Profile Icon Jesse White
Jesse White
Gigi Sayfan Gigi Sayfan
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Gigi Sayfan
Jonathan Baier Jonathan Baier
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Jonathan Baier
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Toc

Table of Contents (26) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Introduction to Kubernetes FREE CHAPTER 2. Understanding Kubernetes Architecture 3. Building a Foundation with Core Kubernetes Constructs 4. Working with Networking, Load Balancers, and Ingress 5. Using Critical Kubernetes Resources 6. Exploring Kubernetes Storage Concepts 7. Monitoring and Logging 8. Monitoring, Logging, and Troubleshooting 9. Operating Systems, Platforms, and Cloud and Local Providers 10. Creating Kubernetes Clusters 11. Cluster Federation and Multi-Tenancy 12. Cluster Authentication, Authorization, and Container Security 13. Running Stateful Applications with Kubernetes 14. Rolling Updates, Scalability, and Quotas 15. Advanced Kubernetes Networking 16. Kubernetes Infrastructure Management 17. Customizing Kubernetes - API and Plugins 18. Handling the Kubernetes Package Manager 19. The Future of Kubernetes 1. Other Books You May Enjoy Index

InfluxDB backend


InfluxDB is a modern and robust distributed time-series database. It is very well-suited and used broadly for centralized metrics and logging. It is also the preferred Heapster backend (outside the Google Cloud Platform). The only thing is InfluxDB clustering; high availability is part of enterprise offering.

The storage schema

The InfluxDB storage schema defines the information that Heapster stores in InfluxDB, and it is available for querying and graphing later. The metrics are divided into multiple categories, named measurements. You can treat and query each metric separately, or you can query a whole category as one measurement and receive the individual metrics as fields. The naming convention is <category>/<metrics name> (except for uptime, which has a single metric). If you have an SQL background, you can think of measurements as tables. Each metric is stored per container. Each metric is labeled with the following information:

  • pod_id: A unique ID of a pod...
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