Kubernetes Tutorial: From Zero to Production
How to deploy and manage containerized applications with Kubernetes — from spinning up a local k3d cluster and writing YAML manifests, to Helm, advanced workloads, and running production Kubernetes on AWS EKS, Google GKE, and Azure AKS.
Get the Full Source Code on GitHub
This article is a summary. The full, runnable tutorial —
six in-depth chapters plus a core concepts reference guide,
complete with YAML manifests, Helm charts, and docs — lives
in the audoir/kubernetes-tutorial repository.
What is Kubernetes?
Kubernetes (often abbreviated as K8s) is an open-source container orchestration platform originally developed by Google. It automates the deployment, scaling, and management of containerized applications across a cluster of machines — answering the question: “I have many containers — how do I run them reliably, at scale, across multiple machines?”
The kubernetes-tutorial repository walks through six chapters, from a local cluster to production. This post summarizes what each chapter covers — head to the repo for the full YAML manifests, Helm charts, and step-by-step instructions.
Self-Healing
Automatically restarts failed containers, replaces and reschedules them when nodes die — keeping your application running without manual intervention.
Horizontal Scaling
Scale your application up or down with a single command or automatically based on CPU/memory usage using the Horizontal Pod Autoscaler.
Load Balancing & Service Discovery
Distributes network traffic so deployments are stable. Containers can find each other by name without hardcoded IPs.
Secret & Config Management
Store and manage sensitive information separately from your container image using ConfigMaps & Secrets.
When Should You Use Kubernetes?
Kubernetes is powerful, but it's not always the right tool. Use it when you have multiple microservices that scale independently, need fine-grained resource control, run stateful workloads alongside stateless ones, need multi-cloud portability, or operate at significant scale. For simple frontend-heavy apps or unpredictable, pay-per-use traffic, serverless platforms are often a better fit.
| Scenario | Best Choice |
|---|---|
| Microservices at scale | ✅ Kubernetes |
| Simple web app / frontend | ⚡ Serverless (Vercel, Netlify) |
| Full control over OS/hardware | 🖥️ EC2 / VMs |
| Multi-service backend with APIs | ✅ Kubernetes |
| Unpredictable traffic, pay-per-use | ⚡ Serverless |
| Portable, cloud-agnostic deployment | ✅ Kubernetes |
Prerequisites
You'll need a computer running macOS, Linux, or Windows (WSL2 recommended), basic command-line familiarity, and Docker installed and running. No prior Kubernetes experience required.
Six Chapters, Zero to Production
The tutorial is organized into six chapters plus a core concepts reference guide. Work through them in order for the best learning experience.
🛠️ Setup
Install the required tools, create your first k3d cluster, and explore it with kubectl. Ends with a fully functional local Kubernetes cluster running on your machine.
🚀 Deployment
Write YAML manifests, create namespaces, deploy an application, and verify it with BusyBox — the fundamental building blocks: Pods, ReplicaSets, and Deployments.
🌐 Services and Beyond
Expose your app with a LoadBalancer Service, add resource limits, and learn Kubernetes architecture — how traffic flows from the outside world into your cluster.
⛵ Helm
Use Helm — the Kubernetes package manager — to install, upgrade, and roll back applications on a k3d cluster with podinfo.
🔬 Advanced Topics
Pod controllers (Deployment, DaemonSet, Job), stateful workloads, security contexts, Snyk scanning, Prometheus & Grafana monitoring, and the Horizontal Pod Autoscaler.
☁️ Kubernetes in Production
How this tutorial compares to on-prem and managed cloud Kubernetes — a deep dive on AWS EKS, Google GKE, and Azure AKS.
📚 Core Concepts Reference
New to containers or Docker? The repository includes a core-concepts/ reference guide covering the foundational ideas Kubernetes is built
on — containers, Docker, and key Kubernetes objects like Pods, Nodes,
Namespaces, and Services. See the repository for the full guide.
Conclusion
This tutorial takes you from zero to a solid understanding of Kubernetes — from spinning up your first local cluster with k3d, to writing YAML manifests, deploying applications, exposing them with Services and Ingress, managing them with Helm, exploring advanced topics like DaemonSets, StatefulSets, security contexts, and the HPA, and finally understanding how production Kubernetes works on AWS EKS, Google GKE, and Azure AKS.
The key insight is that the Kubernetes API is the same everywhere. Every concept you learn — Pods, Deployments, Services, Ingress, ConfigMaps, Secrets, PVCs, Jobs, HPA, Helm — works identically on any Kubernetes cluster, whether it's running on your laptop with k3d or in production on a managed cloud service. The cloud-specific differences are only in the infrastructure layer beneath Kubernetes.
Ready to Build It Yourself?
Clone the repository, spin up a local k3d cluster, and work through all six chapters — from your first Pod to production Kubernetes on AWS, GCP, or Azure.
Clone kubernetes-tutorial on GitHubAbout the Author
Wayne Cheng is the founder and AI app developer at Audoir, LLC. Prior to founding Audoir, he worked as a hardware design engineer for Silicon Valley startups and an audio engineer for creative organizations. He holds an MSEE from UC Davis and a Music Technology degree from Foothill College.
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Further Exploration
Explore the kubernetes-tutorial repository and experiment with extending the examples. Consider deploying a real multi-service application, setting up a CI/CD pipeline that deploys to your cluster, or migrating one of the chapters to a managed cloud provider to deepen your understanding of production Kubernetes.
For more AI-powered development tools and tutorials, visit Audoir .