While Kubernetes has greatly simplified the task of deploying containerized applications, managing this orchestration framework on a daily basis can still be a complex undertaking. With this practical book, site reliability and DevOps engineers will learn how to build, operate, manage, and upgrade a Kubernetes cluster—whether it resides on cloud infrastructure or on-premises.
Brendan Burns, cofounder of Kubernetes, and Craig Tracey, staff field engineer at Heptio, dissect how Kubernetes works internally and demonstrate ways to maintain, adjust, and improve the cluster to suit your particular use case. You’ll learn how to make architectural choices for designing a cluster, managing access control, monitoring and alerting, and upgrading Kubernetes. Dive in and discover how to take full advantage of this orchestration framework’s capabilities.
* Learn how your cluster operates, how developers use it to deploy applications, and how Kubernetes can facilitate a developer’s job
* Adjust, secure, and tune your cluster by understanding Kubernetes APIs and configuration options
* Detect cluster-level problems early and learn the steps necessary to respond and recover quickly
* Determine how and when to add libraries, tools, and platforms that build on, extend, or otherwise improve a Kubernetes cluster
Author(s): Brendan Burns; Craig Tracey
Publisher: O'Reilly Media
Year: 2018
Language: English
Commentary: Second Release - 2018-11-06
Pages: 187
Cover
Copyright
Table of Contents
Preface
Who should read This Book
Why we wrote This Book
Navigating This Book
Conventions Used in This Book
Using Code Examples
O’Reilly Safari
How to Contact Us
Acknowledgments
Chapter 1. Introduction
How the Cluster Operates
Adjust, Secure, and Tune the Cluster
Responding When Things Go Wrong
Extending the System with New and Custom Functionality
Summary
Chapter 2. An Overview of Kubernetes
Containers
Container Orchestration
The Kubernetes API
Basic Objects: Pods, ReplicaSets, and Services
Organizing Your Cluster with Namespaces, Labels, and Annotations
Advanced Concepts: Deployments, Ingress, and StatefulSets
Batch Workloads: Job and ScheduledJob
Cluster Agents and Utilities: DaemonSets
Summary
Chapter 3. Kubernetes Architecture
Concepts
Declarative Configuration
Reconciliation or Controllers
Implicit or Dynamic Grouping
Structure
Unix Philosophy of Many Components
API-Driven Interactions
Components
Head Node Components
Components On All Nodes
Scheduled Components
Summary
Chapter 4. The Kubernetes API Server
Basic Characteristics for Manageability
Pieces of the API Server
API Management
API Paths
API Discovery
OpenAPI Spec Serving
API Translation
Request Management
Types of Requests
Life of a Request
API Server Internals
CRD Control Loop
Debugging the API Server
Basic Logs
Audit Logs
Activating Additional Logs
Debugging kubectl Requests
Summary
Chapter 5. Scheduler
An Overview of Scheduling
Scheduling Process
Predicates
Priorities
High-Level Algorithm
Conflicts
Controlling Scheduling with Labels, Affinity, Taints, and Tolerations
Node Selectors
Node Affinity
Taints and Tolerations
Summary
Chapter 6. Installing Kubernetes
kubeadm
Requirements
kubelet
Installing the Control Plane
kubeadm Configuration
Preflight Checks
Certificates
etcd
kubeconfig
Taints
Installing Worker Nodes
Add-Ons
Phases
High Availability
Upgrades
Summary
Chapter 7. Authentication and User Management
Users
Authentication
kubeconfig
Service Accounts
Summary
Chapter 8. Authorization
REST
Authorization
Role-Based Access Control
Role and ClusterRole
RoleBinding and ClusterRoleBinding
Testing Authorization
Summary
Chapter 9. Admission Control
Configuration
Common Controllers
PodSecurityPolicies
ResourceQuota
LimitRange
Dynamic Admission Controllers
Validating Admission Controllers
Mutating Admission Controllers
Summary
Chapter 10. Networking
Container Network Interface
Choosing a Plug-in
kube-proxy
Service Discovery
DNS
Environment Variables
Network Policy
Service Mesh
Summary
Chapter 11. Monitoring Kubernetes
Goals for Monitoring
Differences Between Logging and Monitoring
Building a Monitoring Stack
Getting Data from Your Cluster and Applications
Aggregating Metrics and Logs from Multiple Sources
Storing Data for Retrieval and Querying
Visualizing and Interacting with Your Data
What to Monitor?
Monitoring Machines
Monitoring Kubernetes
Monitoring Applications
Blackbox Monitoring
Streaming Logs
Alerting
Summary
Chapter 12. Disaster Recovery
High Availability
State
Application Data
Persistent Volumes
Local Data
Worker Nodes
etcd
Ark
Summary
Chapter 13. Extending Kubernetes
Kubernetes Extension Points
Cluster Daemons
Use Cases for Cluster Daemons
Installing a Cluster Daemon
Operational Considerations for Cluster Daemons
Hands-On: Example of Creating a Cluster Daemon
Cluster Assistants
Use Cases for Cluster Assistants
Installing a Cluster Assistant
Operational Considerations for Cluster Assistants
Hands-On: Example of Cluster Assistants
Extending the Life Cycle of the API Server
Use Cases for Extending the API Life Cycle
Installing API Life Cycle Extensions
Operational Considerations for Life Cycle Extensions
Hands-On: Example of Life Cycle Extensions
Adding Custom APIs to Kubernetes
Use Cases for Adding New APIs
Custom Resource Definitions and Aggregated API Servers
Architecture for Custom Resource Definitions
Installing Custom Resource Definitions
Operational Considerations for Custom Resources
Summary
Chapter 14. Conclusions
Index
About the Authors
Colophon
