Kubernetes for Builders
Kubernetes is the industry-standard container orchestration system used by every major cloud provider and most serious engineering teams. This course gives you the practical Kubernetes knowledge builders need: pods, deployments, services, config management, Helm charts, and the kubectl commands you will use every week.
What you'll learn
Course outline
Free — start now
Why Kubernetes: from Docker to orchestration
The problems that arise when you run containers at scale — and how Kubernetes solves them
Pods: the smallest deployable unit
What pods are, how to run them, and the essential kubectl commands for inspecting them
Deployments: rolling updates and rollbacks
Run multiple replicas, update without downtime, and roll back instantly when something goes wrong
Full course — $69 one-time
Services: stable networking for dynamic pods
How Kubernetes routes traffic to the right pods even as they are created and destroyed
ConfigMaps and Secrets: externalising configuration
Keep credentials and config outside your container images — the right way to handle environment-specific settings
Namespaces: environment isolation
Organise workloads, separate environments, and enforce resource quotas with Kubernetes namespaces
Persistent Volumes: storage that outlives pods
How Kubernetes handles stateful workloads — databases, file uploads, and anything that needs durable storage
Ingress: routing HTTP traffic to services
One load balancer, many services — path-based routing, TLS termination, and cert-manager
Helm: package manager for Kubernetes
Stop copy-pasting YAML between environments — package, version, and deploy your Kubernetes apps with Helm
kubectl mastery: the commands you will use every week
Context management, resource inspection, port-forwarding, exec, events, and jsonpath — the full practical toolkit
Get the full course
All 10 lessons. Pods to Helm charts — practical Kubernetes for engineers who deploy real workloads.
Written by the RadarTrek editorial team · Reviewed June 2026
About this course
Kubernetes is the industry-standard system for running containerised applications at scale — once you have more than a handful of Docker containers to manage, Kubernetes provides the orchestration layer that handles deployment, scaling, self-healing, and networking automatically. Every major cloud provider offers managed Kubernetes: Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS), and Azure Kubernetes Service (AKS) all let you spin up a cluster without managing the control plane yourself. In 2026, Kubernetes knowledge is expected for any developer working in a cloud-native environment, and the kubectl command-line tool is as fundamental to DevOps workflows as git is to code development.
This course is designed for builders who already understand Docker and want to graduate from running single containers to managing production deployments with proper resource management, rolling updates, and infrastructure-as-code patterns. You will learn the core Kubernetes objects — Pods, Deployments, Services, ConfigMaps, Secrets, PersistentVolumes, and Ingress — with real YAML examples you can adapt for your own workloads. The final section covers Helm, the Kubernetes package manager, and the kubectl commands you will reach for every working day. By the end of this course you will be able to deploy a multi-service application to a managed Kubernetes cluster, roll out updates without downtime, and manage configuration securely.
Frequently asked questions
Do I need to know Docker before learning Kubernetes?
Yes — Docker is a hard prerequisite. Kubernetes orchestrates containers, so you need to understand what a container is, how to build a Docker image, and what a Dockerfile does before Kubernetes concepts will make sense. The Docker and DevOps course covers everything you need. If you are already comfortable building images, writing docker-compose files, and understanding port mapping and volumes, you are ready for Kubernetes.
Is Kubernetes too complex for solo builders and small teams?
For most early-stage products and solo builders, yes — Kubernetes is significant operational overhead relative to simpler alternatives. Railway, Render, and Fly.io give you container deployments, scaling, and managed databases without any Kubernetes knowledge. If your traffic is modest and you have one or two services, Kubernetes is likely overkill. It becomes worth learning when you have multiple services with different scaling requirements, need precise resource control, or join a team that already uses it.
What is the difference between a Pod and a Deployment?
A Pod is the smallest deployable unit in Kubernetes — a wrapper around one or more containers that share network and storage. Pods are ephemeral: if a Pod dies, it is not automatically recreated. A Deployment manages a set of identical Pods (replicas) and ensures the desired number are always running. If a Pod crashes, the Deployment controller spins up a replacement. In practice you almost never create bare Pods — you create Deployments that manage Pods for you.
Do I need to run my own Kubernetes cluster or can I use a managed service?
For learning and production, managed Kubernetes is almost always the right choice. GKE, EKS, and AKS manage the control plane (the API server, etcd, scheduler) for you — you only manage the worker nodes and your workloads. This significantly reduces operational burden. For local development, tools like minikube, kind, or k3d run a single-node cluster on your laptop. This course uses a managed cluster for production examples and kind for local practice.
Is Kubernetes worth learning in 2026 or are there simpler alternatives?
It depends on your role and goals. If you are a developer joining an existing engineering team at a mid-to-large company, Kubernetes knowledge is almost certainly expected and highly valuable. If you are a solo builder shipping a product, simpler platforms like Railway or Fly.io offer 90% of the value with a fraction of the complexity. The ideal path is to learn the simpler platforms first, ship product, and add Kubernetes knowledge when you join a team that uses it or when scale demands it. This course is optimised for that "joining a Kubernetes shop" scenario.