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DevOps Engineer Learning Path

This path matches how production platforms are built: operating systems, shell automation, Python for structured data and APIs, networks, cloud, version control, pipelines, containers, orchestration, then Infrastructure as Code.

Ready modules (complete in order)

# Track Start here Status
1 Linux Linux Fundamentals — Distributions and Architecture Ready — 16 modules · 25 tutorials
2 Shell Scripting Shell Fundamentals — Bash vs sh and Execution Ready — 18 modules · 18 tutorials
3 Python for DevOps Install, venv, and Tooling Ready — 27 modules · 27 tutorials
4 Networking Introduction to Networking Ready — 25 tutorials
5 AWS AWS Fundamentals and Global Infrastructure Ready — 16 modules · 16 tutorials
6 Git Introduction to Git Ready — 20 tutorials
7 GitLab CI/CD GitLab CI/CD Fundamentals Ready — 18 modules (GitLab CI)
8 Docker Introduction to Containers Ready — 20 tutorials
9 Kubernetes Introduction to Kubernetes Ready — 20 tutorials
10 Terraform Introduction to Terraform Ready — 20 tutorials

Why Linux first?

Every cloud VM, container node, and CI runner is Linux underneath. Finish the 16 Cloud & DevOps modules (fundamentals through production) before Shell. See also Linux for Cloud & DevOps.

Why Shell after Linux?

Linux teaches the tools; Shell Scripting turns them into reviewed, schedulable automation for admins and DevOps. Take it before Networking so later labs can assume solid Bash habits.

Why Python after Shell?

Bash remains the launcher. Python owns JSON/YAML, HTTP clients, tests, and packaged CLIs. See also the dedicated Python for DevOps Engineers path.

Why CI/CD after Git?

Pipelines are triggered by Git events. Learn branching and reviews first, then automate build/test/deploy with GitLab CI before deep Docker/Kubernetes deploy labs.

Supporting assets

Asset Linux Shell Python Networking AWS Git CI/CD Docker Kubernetes Terraform
Cheat sheet open open open open open open open open open open
Interview prep open open open open open open open open open open
Quiz course fundamentals · fundamentals · servers course fundamentals course fundamentals production fundamentals fundamentals open open

Standalone labs

When you finish… Practise with
Linux modules on systemd and logs Linux Production Incident Triage
Linux security / storage / ops labs Firewall hardening · Ops toolkit · App server from zero
Shell Scripting (any module) Shell labs · Ops Script Hardening · Operations Toolkit
Python Modules 1–2 Python Log Analyser · Linux Health Checker · YAML Config Validator · JSON Validator
DNS, firewalls, troubleshooting DNS and Firewall Site-Down Triage
Networking Module 7 (LB/DNS/ACL/IR) Networking Edge Failover
AWS IAM + VPC AWS IAM and VPC Reachability Triage
AWS SSM + S3 Secure EC2 via SSM and S3
Rebase, conflicts, safe force-push Git History and PR Recovery
CI/CD pipeline failures CI/CD Pipeline Failure Triage
CI/CD Docker + deploy gate Docker Build, Scan, and Deploy Gate
Docker Compose and networking Docker Compose Stack Recovery
Deployments and probes Kubernetes Deployment Triage
Terraform CLI + CI concepts Terraform Plan Review Workflow

Browse all labs: Labs

Quizzes

Self-mark after finishing a track: Quizzes — Linux, Shell Scripting, Python for DevOps, Networking production, AWS, CI/CD, Docker, and Kubernetes.

Portfolio project

After the labs above: Status API Portfolio Build — Git → Docker → Kubernetes → Terraform metadata. Python projects: Log Analysis Tool through Automation platform.

Coming next on this path

Azure, GCP, monitoring, and DevSecOps remain on the roadmap.

Study rules

  • Finish each tutorial lab before skipping ahead
  • Keep a short incident notebook (symptom → cause → fix)
  • Use interview questions as a gate between modules
  • Never print secrets in pipeline logs; prefer OIDC/short-lived tokens