Kubernetes Cookbook (Sebastien Goasguen Michael Hausenblas)（Z-Library）

【One-Line Pitch】 A hands-on recipe collection for developers and sysadmins moving to cloud-native, covering everything from local Minikube setups to production cluster creation, workload management, and extending Kubernetes—ideal for quick problem-solving and practical learning. 【Book Arc】 - **Opening (~0%–9%)**: Introduces the book’s purpose, audience, and structure—over 80 recipes across 14 chapters in a Problem-Solution-Discussion format, with Kubernetes 1.7 as the baseline (compatible down to 1.4). Sets expectations for independent, skimmable recipes and prerequisites like bash and package management. - **Early (~9%–25%)**: Focuses on getting started—installing `kubectl` via various methods (curl, Homebrew, gcloud), setting up Minikube for local development, and using its CLI commands (`start`, `stop`, `ip`, `ssh`, `dashboard`, `docker-env`) to run a single-node cluster for testing or training. - **Early (~25%–34%)**: Covers initial interactions with the cluster—using `kubectl run` and `kubectl expose` as generators to create Deployments and Services, and accessing the Kubernetes dashboard via Minikube to deploy apps (e.g., Redis) and observe pods, replica sets, and deployments. - **Middle (~38%–47%)**: Moves to full cluster creation—installing `kubeadm` on all hosts, bootstrapping a cluster with networking add-ons (CNI), downloading official Kubernetes releases from GitHub (with hash verification), and fetching client/server binaries via scripts or direct URLs. - **Middle (~47%–53%)**: Explores advanced setup options—using the `hyperkube` Docker image to run master components (API server, scheduler, controller, etcd) in containers, and starting a minimal API server locally with three containers for testing or development. 【Key Takeaways】 - **Start local with Minikube** (Early): Minikube launches a single-node Kubernetes cluster in a VM, ideal for development and training; commands like `minikube dashboard` and `docker-env` simplify the workflow. (Early) - **Master `kubectl` basics** (Early): Install via curl, package managers, or gcloud; verify with `kubectl version`—it’s the primary CLI for interacting with any cluster. (Early) - **Use generators for quick deploys** (Early): `kubectl run` creates Deployments and `kubectl expose` creates Services, letting you launch apps without writing YAML—great for testing. (Early) - **Build clusters with `kubeadm`** (Middle): Install on master and nodes, then bootstrap; add a CNI network plug-in to get nodes READY—this is the standard path for custom clusters. (Middle) - **Download releases safely** (Middle): Get `kubernetes.tar.gz` from GitHub or binaries from `dl.k8s.io`, but always verify SHA256 hashes to ensure integrity. (Middle) - **Run masters with `hyperkube`** (Middle): Use the all-in-one Docker image to start API server, scheduler, controller, and etcd in containers—useful for containerized control planes. (Middle) - **Recipes are independent** (Opening): Each recipe stands alone with references to others, so you can jump to specific problems without reading linearly—perfect for on-the-job reference. (Opening) 【Reading Tips】 - **Skim the first chapters** if you’re experienced; focus on recipes 1.3–1.6 for Minikube setup and dashboard use, then jump to cluster creation (Chapter 2) for production concerns. - **Deep-read the Discussion sections**—they explain why solutions work, not just how, which is crucial for troubleshooting and adapting recipes to newer Kubernetes versions. - **Use the companion repo** (`github.com/k8s-cookbook/recipes`) for code examples, but note they’re minimal, not production-optimized—treat them as starting points. - **Watch for version notes**: The book targets Kubernetes 1.7, but stable APIs should work on newer releases; pay attention to explicit minimum version requirements in recipes. - **Leverage the index** for command-specific lookups—it highlights connections between recipes and commands, making it a quick reference tool. 【Coverage Limits】 This guide covers the opening, early, and middle sections (up to ~53% of the book), focusing on setup, local development, and cluster creation. Later chapters on workloads, storage, security, and extending Kubernetes are not covered in the sampled excerpts.