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Prerequisites

Start here for the beginner foundations that lead into Kubernetes and platform work.

This hub is the front door to KubeDojo. It covers the terminal, containers, Kubernetes basics, declarative thinking, Git, and modern delivery practices.

  • absolute beginners who need a real starting point
  • learners who want a structured route into cloud-native systems
  • people who need enough fundamentals before choosing Linux, Kubernetes, cloud, platform, AI literacy, or AI/ML depth
  • you are still shaky on the terminal, files, SSH, or software installation
  • Kubernetes terminology still feels abstract
  • you are tempted to jump straight into advanced tracks because they look interesting

This layer gives later tracks a shared foundation; use it when these topics are unfamiliar.

Optional first-terminal preview: You can preview the existing terminal opening and prompt guide and first safe-command exercise before starting the full sequence. Return here and follow Zero to Terminal in order; the preview does not replace its modules. Use Module 0.2’s own platform guidance before attempting its exercise.


For absolute beginners. From “what is a computer?” to deploying your first server from the command line.

ModuleTopic
0.1What is a Computer?
0.2What is a Terminal?
0.3First Terminal Commands
0.4Files and Directories
0.5Editing Files
0.6Git Basics
0.7What is Networking?
0.8Servers and SSH
0.9Software and Packages
0.10What is the Cloud?
0.11Your First Server

Containers, Docker, Kubernetes, and the cloud-native ecosystem from first principles.

ModuleTopic
1.1What Are Containers?
1.2Docker Fundamentals
1.3What Is Kubernetes?
1.4Cloud Native Ecosystem
1.5Monolith to Microservices

The practical Kubernetes starter path with kubectl, Pods, Deployments, Services, config, and YAML.

ModuleTopic
1.1Your First Cluster
1.2kubectl Basics
1.3Pods - The Atomic Unit
1.4Deployments - Managing Apps
1.5Services - Stable Networking
1.6ConfigMaps & Secrets
1.7Namespaces & Labels
1.8YAML for Kubernetes

Why Kubernetes works the way it does, and which legacy patterns are not worth your time.

ModuleTopic
1.1Why Kubernetes Won
1.2Declarative vs Imperative
1.3What We Don’t Cover
1.4Dead Ends - Technologies to Avoid

The professional Git path. Internals, rebasing, recovery, scale, collaboration, and the bridge into GitOps.

ModuleTopic
1Git Internals
2Advanced Merging
3Interactive Rebasing
4Undo and Recovery
5Worktrees and Stashing
6Troubleshooting and Search
7Remotes and PRs
8Sparse Checkout and LFS
9Hooks and Rerere
10Bridge to GitOps

IaC, GitOps, CI/CD, observability, platform engineering, and DevSecOps.

ModuleTopic
1.1Infrastructure as Code
1.2GitOps
1.3CI/CD Pipelines
1.4Observability Fundamentals
1.5Platform Engineering
1.6Security Practices (DevSecOps)

Zero to Terminal
|
+--> Linux track (if you want deeper systems knowledge)
|
Cloud Native 101
|
Kubernetes Basics
|
Philosophy & Design
|
Git Deep Dive
|
Modern DevOps

Use Git Deep Dive after you are comfortable with basic Git from Zero to Terminal. It is not required before Cloud Native 101 or Kubernetes Basics, but it should be treated as a practical prerequisite before serious IaC, GitOps, CI/CD, and team workflows.

The practical rule is simple:

0.6 Git Basics
|
Git Deep Dive
|
Modern DevOps / IaC / GitOps / CI-CD

Git Is Not Optional For Modern Infrastructure Work

Section titled “Git Is Not Optional For Modern Infrastructure Work”

The sequence matters:

  • 0.6 Git Basics in Zero to Terminal gives you the minimum viable workflow
  • Git Deep Dive turns Git into an operational tool rather than just a backup mechanism
  • only after that do Modern DevOps, IaC, and GitOps become much easier to use correctly

If a learner skips the Git path, they can still read later modules, but they will be missing one of the core skills behind modern infrastructure practice.

  • Prerequisites -> Linux if you want stronger systems depth before operations-heavy work
  • Prerequisites -> Kubernetes Certifications if you want external goals and hands-on pressure
  • Prerequisites -> Cloud if your main goal is hyperscaler fluency after cluster basics
  • Prerequisites -> AI if you want a true beginner-friendly path into AI literacy and disciplined AI use
  • Prerequisites -> AI/ML Engineering if you already know you want to build AI systems, run local models, or move toward MLOps
  • Prerequisites -> Modern DevOps should usually mean Zero to Terminal -> Git Deep Dive -> Modern DevOps, not a direct jump that skips Git maturity

For a beginner route, place Platform Engineering after Kubernetes, Linux, or Cloud foundations rather than making it the immediate next stop.


These are not inside the prerequisites/ section, but they are common next steps:

PathWhy It Matters
LinuxGo deeper into processes, networking, storage, security, and operations
AIBuild practical AI literacy and AI working habits before advanced engineering depth
AI/ML EngineeringStart the AI/ML track if your goal is LLMs, MLOps, or AI infrastructure

Ready to specialize? Choose your next track:

GoalNext Step
Master LinuxLinux
Get certifiedKubernetes Certifications
Learn cloud providersCloud
Run Kubernetes on your own hardwareOn-Premises Kubernetes
Go deeper into platform practicesPlatform Engineering
Learn AI from zeroAI
Explore AI/ML systemsAI/ML Engineering