Kubernetes radically changes the way applications are built and deployed in the cloud. Since its introduction in 2014, this container orchestrator has become one of the largest and most popular open source projects in the world. The updated edition of this practical book shows developers and ops personnel how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency.
Kelsey Hightower, Brendan Burns, and Joe Beda--who've worked on Kubernetes at Google and beyond--explain how this system fits into the lifecycle of a distributed application. You'll learn how to use tools and APIs to automate scalable distributed systems, whether it's for online services, machine learning applications, or a cluster of Raspberry Pi computers.
Create a simple cluster to learn how Kubernetes works
Dive into the details of deploying an application using Kubernetes
Learn specialized objects in Kubernetes, such as DaemonSets, jobs, ConfigMaps, and secrets
Explore deployments that tie together the lifecycle of a complete application
Get practical examples of how to develop and deploy real-world applications in Kubernetes
AI Reading Assistant
Whole-book reading guide from stratified index samples; jump to passages in the text
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# Kubernetes: Up and Running — Reading Guide
## 【One-Line Pitch】
A practical, hands-on guide by three Kubernetes co-creators that teaches developers and ops professionals how to build, deploy, and maintain scalable containerized applications using Kubernetes. If you want to move beyond Docker basics and understand how modern cloud-native infrastructure actually works, this is your definitive starting point.
## 【Book Arc】
- **Opening (~0%–9%)**: Introduces the core philosophy—velocity, immutability, declarative configuration, and self-healing systems—and explains why Kubernetes matters for modern software delivery. Sets up the mental model before any hands-on work.
- **Early (~9%–27%)**: Covers the fundamentals: container basics, cluster setup, kubectl commands, then the core building blocks—Pods, labels/annotations, Services, Ingress, and ReplicaSets. This is the "deploy your first app" section.
- **Middle (~27%–52%)**: Moves into production-grade objects: Deployments for lifecycle management, DaemonSets for node-level services, Jobs/CronJobs for batch work, and ConfigMaps/Secrets for configuration. Also covers RBAC for security and storage integration.
- **Late (~52%–75%)**: Explores advanced topics: extending Kubernetes with custom resources, operators, and integrating external storage solutions like MySQL and MongoDB. Includes practical patterns for real-world reliability.
- **Ending (~75%–100%)**: Walks through deploying complete real-world applications (Jupyter, parse-server, Ghost, Redis) and discusses organizing applications in source control—tying everything together with end-to-end examples.
## 【Key Takeaways】
- **Velocity means shipping while staying available** (Early): The goal isn't raw feature speed but the ability to deploy frequently without downtime. Kubernetes enables this through immutable infrastructure, declarative config, and self-healing systems.
- **Immutability transforms how you upgrade software** (Middle): Instead of patching running systems (mutable infrastructure), you build a complete new image and replace the old one entirely. This eliminates configuration drift and makes rollbacks trivial.
- **Declarative configuration is safer than imperative commands** (Middle): Saying "replicas equals three" instead of "run A, run B, run C" means the system's desired state is explicit, reviewable, and reversible. This enables infrastructure-as-code practices like source control and code review.
- **Kubernetes is a self-healing system, not a one-shot deployer** (Middle): It continuously compares current state to desired state and takes corrective action. This reduces operator burden and improves reliability compared to human-driven incident response.
- **Pods are the atomic unit, but Deployments manage the lifecycle** (Early): Understanding the relationship between Pods, ReplicaSets, and Deployments is essential—Deployments provide rolling updates, rollback, and scaling while abstracting away the underlying Pod management.
- **Specialized objects solve specific problems** (Middle): DaemonSets run one Pod per node (logging, monitoring), Jobs handle batch processing, and ConfigMaps/Secrets separate configuration from container images—each addresses a distinct operational need.
- **RBAC is essential for production security** (Middle): Role-Based Access Control lets you define who can do what in the cluster. Managing RBAC in source control and testing with `can-i` are practical techniques for maintaining security at scale.
- **Kubernetes is extensible beyond built-in objects** (Late): Custom resources and operators let you encode domain-specific operational knowledge into the platform itself, turning complex application management into declarative Kubernetes-native patterns.
## 【Reading Tips】
1. **Skim Chapter 1 if you're experienced with containers**—the philosophy is important, but if you already understand immutable infrastructure and declarative config, jump to Chapter 2 for the practical container review.
2. **Deep-read Chapters 5–10** (Pods through Deployments)—these are the core concepts you'll use daily. Don't skip the ReplicaSet chapter even though Deployments supersede it; understanding the underlying mechanism is crucial for debugging.
3. **Skip Chapters 11–13 on first pass if you're a beginner**—the authors explicitly say DaemonSets, Jobs, and ConfigMaps can be deferred until you have hands-on experience. Return when you hit real production needs.
4. **Set up a cluster as you read**—Chapter 3 provides easy setup methods, and the book is designed for hands-on learning. Reading without doing will leave you with abstract knowledge that doesn't stick.
5. **Treat Chapter 17 as your capstone project**—the real-world application walkthroughs (Jupyter, Ghost, Redis) tie together everything from earlier chapters. If you're short on time, read this chapter to see how the pieces fit.
## 【Coverage Limits】
This guide covers the book's core progression from fundamentals through advanced topics based on the available excerpts. Detailed code examples, specific YAML configurations, and the full source control chapter (18) are not covered in this guide but are present in the book.
##
Excerpt 1
caling Abstracting Your Infrastructure Efficiency Summary 2. Creating and Running Containers Container Images The Docker Image Format Building Application Im...
banners. —Joe Beda For Klarissa and Kelis, who keep me sane. And for my Mom, who taught me a strong work ethic and how to rise above all odds. —Kelsey Highto...
ds or other text that should be typed literally by the user. Constant width italic Shows text that should be replaced with user-supplied values or by values...
ur new software, kill the old server, and start the new one. You can build a new container image, push it to a container registry, kill the existing containe...
s associated with forecasting growth of computing resources. Scaling Development Teams with Microservices As noted in a variety of research, the ideal team s...
his is where containers and the Kubernetes workflow come in. Kubernetes provides tools that automate the distribution of applications across a cluster of mac...
the filesystem. This is an example of an overlay filesystem. The overlay system is used both when packaging up the image and when the image is actually being...
ter all, when you run the image, it is no longer accessible. But in fact it is still present in layer A, which means that whenever you push or pull the image...
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