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Mastering Kubernetes

Mastering Kubernetes

By : Gigi Sayfan
3.6 (10)
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Mastering Kubernetes

Mastering Kubernetes

3.6 (10)
By: Gigi Sayfan

Overview of this book

Kubernetes is an open source system that is used to automate the deployment, scaling, and management of containerized applications. If you are running more containers or want automated management of your containers, you need Kubernetes at your disposal. To put things into perspective, Mastering Kubernetes walks you through the advanced management of Kubernetes clusters. To start with, you will learn the fundamentals of both Kubernetes architecture and Kubernetes design in detail. You will discover how to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. Using real-world use cases, you will explore the options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you will get to grips with custom resource development and utilization in automation and maintenance workflows. To scale up your knowledge of Kubernetes, you will encounter some additional concepts based on the Kubernetes 1.10 release, such as Promethus, Role-based access control, API aggregation, and more. By the end of this book, you’ll know everything you need to graduate from intermediate to advanced level of understanding Kubernetes.
Table of Contents (16 chapters)
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Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
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1
Understanding Kubernetes Architecture
Understanding Kubernetes Architecture
What is Kubernetes?
What Kubernetes is not
Understanding container orchestration
Kubernetes concepts
Diving into Kubernetes architecture in-depth
The Kubernetes APIs
Kubernetes components
Kubernetes runtimes
Continuous integration and deployment
Summary
2
Creating Kubernetes Clusters
Creating Kubernetes Clusters
A quick single-node cluster with Minikube
Creating a multinode cluster using kubeadm
Creating clusters in the cloud (GCP, AWS, and Azure)
Creating a bare-metal cluster from scratch
The process
Using virtual private cloud infrastructure
Summary
3
Monitoring, Logging, and Troubleshooting
Monitoring, Logging, and Troubleshooting
Monitoring Kubernetes with Heapster
Installing Heapster
InfluxDB backend
Performance analysis with the dashboard
Detecting node problems
Troubleshooting scenarios
Designing robust systems
Hardware failure
Using Prometheus
Summary
4
High Availability and Reliability
High Availability and Reliability
High-availability concepts
High-availability best practices
Live cluster upgrades
Large-cluster performance, cost, and design trade-offs
Summary
5
Configuring Kubernetes Security, Limits, and Accounts
Configuring Kubernetes Security, Limits, and Accounts
Understanding Kubernetes security challenges
Hardening Kubernetes
Running a multiuser cluster
Summary
6
Using Critical Kubernetes Resources
Using Critical Kubernetes Resources
Designing the Hue platform
Using Kubernetes to build the Hue platform
Separating internal and external services
Using namespace to limit access
Launching jobs
Mixing non-cluster components
Employing Init Containers for orderly pod bring-up
Evolving the Hue platform with Kubernetes
Summary
7
Handling Kubernetes Storage
Handling Kubernetes Storage
Persistent volumes walk-through
Public storage volume types – GCE, AWS, and Azure
GlusterFS and Ceph volumes in Kubernetes
Flocker as a clustered container data volume manager
Integrating enterprise storage into Kubernetes
Projecting volumes
Using out-of-tree volume plugins with FlexVolume
The Container Storage Interface
Summary
8
Running Stateful Applications with Kubernetes
Running Stateful Applications with Kubernetes
Stateful versus stateless applications in Kubernetes
Shared environment variables versus DNS records for discovery
Running a Cassandra cluster in Kubernetes
Summary
9
Rolling Updates, Scalability, and Quotas
Rolling Updates, Scalability, and Quotas
Horizontal pod autoscaling
Performing rolling updates with autoscaling
Handling scarce resources with limits and quotas
Choosing and managing the cluster capacity
Pushing the envelope with Kubernetes
Summary
10
Advanced Kubernetes Networking
Advanced Kubernetes Networking
Understanding the Kubernetes networking model
Kubernetes networking solutions
Using network policies effectively
Load balancing options
Træfic
Writing your own CNI plugin
Summary
11
Running Kubernetes on Multiple Clouds and Cluster Federation
Running Kubernetes on Multiple Clouds and Cluster Federation
Understanding cluster federation
Managing a Kubernetes cluster federation
Running federated workloads
Summary
12
Customizing Kubernetes – API and Plugins
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Customizing Kubernetes – API and Plugins
Working with the Kubernetes API
Extending the Kubernetes API
Writing Kubernetes plugins
Employing access control webhooks
Summary
13
Handling the Kubernetes Package Manager
Handling the Kubernetes Package Manager
Understanding Helm
Using Helm
Creating your own charts
Summary
14
The Future of Kubernetes
The Future of Kubernetes
The road ahead
Competition
Education and training
Modularization and out-of-tree plugins
Service meshes and serverless frameworks
Summary
15
Other Books You May Enjoy
Other Books You May Enjoy
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Extending the Kubernetes API

Kubernetes is an extremely flexible platform. It allows you to extend its own API with new types of resources called custom resources. If that is not enough you can even provide your API server that integrates with the Kubernetes API server in a mechanism called API aggregation. What can you do with custom resources? Plenty. You can use them to manage the Kubernetes API resources that live outside the Kubernetes cluster, which your pods communicate with.

By adding those external resources as custom resources, you get a full picture of your system and you benefit from many Kubernetes API features such as the following:

  • Custom CRUD REST endpoints
  • Versioning
  • Watches
  • Automatic integration with generic Kubernetes tooling

Other use cases for custom resources are metadata for custom controllers and automation programs.

Custom resources that were introduced...

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