Getting Started¶
REBASH Academy is a free, open-source learning platform for Cloud, DevOps, Linux, and platform engineering. It exists so you can learn the way production teams work: concepts first, then hands-on labs, then projects you can show in an interview.
What makes it different:
- Hands-on — almost every tutorial includes a lab you run yourself
- Production-focused — patterns used on real platforms, not toy demos
- Cloud-native — containers, Kubernetes, GitOps, and observability in context
- Vendor-neutral where possible — skills transfer across AWS, Azure, and GCP
- Career-shaped — follow a career path or browse by technology
Who this is for¶
| Audience | Why you are here |
|---|---|
| Students | Build a portfolio with Linux → cloud → containers before your first role |
| Linux administrators | Deepen ops skills, then automate with Shell and Python |
| Cloud engineers | Design and operate AWS (Azure and GCP tracks are expanding) |
| DevOps engineers | Connect Git, CI/CD, Docker, Kubernetes, and Terraform end to end |
| Platform engineers | Move toward internal platforms, GitOps, and developer experience |
| Site reliability engineers | Strengthen Linux, networking, and observability foundations |
| DevSecOps engineers | Layer security onto containers, pipelines, and cloud |
| Cloud architects | Combine multi-cloud design with IaC and delivery |
If you are unsure, start with the Beginner or DevOps Engineer path.
How to use the academy¶
There are two ways to navigate. Use both when it helps — tutorials are shared, not duplicated.
1. Browse by career path¶
Open Career Paths when you have a job goal (for example DevOps Engineer or Kubernetes Engineer). The path gives an ordered roadmap across technologies, plus labs, projects, and certification hints.
Use this when: you want a guided sequence and clear “what next”.
2. Browse by technology¶
Open a technology under Technologies in the nav (Linux, Docker, Terraform, …) when you need a specific skill or are filling a gap.
Use this when: your team already uses a tool, or you are revising one topic deeply.
Career paths¶
| Path | Level | Duration | Outcome |
|---|---|---|---|
| Beginner | Beginner | 4–6 weeks | Linux, Shell, Networking, and Git foundations |
| Linux Administrator | Beginner | 8–12 weeks | Production Linux ops and automation habits |
| Cloud Engineer | Intermediate | 12–16 weeks | Build and operate cloud infrastructure (AWS first) |
| DevOps Engineer | Intermediate | 20–28 weeks | Full delivery stack from OS to IaC and pipelines |
| Kubernetes Engineer | Intermediate | 12–16 weeks | Containers, workloads, Helm, and cluster ops |
| Platform Engineer | Advanced | 16–24 weeks | Platform, GitOps, and observability skills |
| DevSecOps Engineer | Advanced | 14–20 weeks | Shift-left security across pipelines and cloud |
| Site Reliability Engineer | Advanced | 16–24 weeks | Reliability, incidents, and observability |
| Cloud Architect | Expert | 20–28 weeks | Multi-cloud design and IaC at scale |
| AI for DevOps Engineer | Intermediate | 10–14 weeks | Practical AI on a solid Python and ops base |
Technologies¶
Each technology track is organised the same way so you always know where you are:
| Section | What you get |
|---|---|
| Overview | Why the technology matters in production |
| Learning objectives | Outcomes you can tick off |
| Modules | Ordered groups of tutorials |
| Tutorials | Concept + lab lessons |
| Hands-on labs | Scenario drills in the Labs catalog |
| Projects | Portfolio builds in Projects |
| Cheat sheets | Quick reference under Cheat Sheets |
| Interview questions | Role prep under Interview Guides |
| Certification mapping | Exam alignment under Certifications |
Ready tracks today include Linux, Shell, Python, Networking, AWS, Git, GitLab CI/CD, Docker, Kubernetes, and Terraform. Planned tracks appear as stubs until content ships.
Learning flow¶
Choose a career path (or one technology if you know your gap), work through tutorials and labs, build projects and a capstone, then use interview and certification material as exit gates.
Difficulty levels¶
Tutorials and paths use four levels:
| Level | Meaning |
|---|---|
| Beginner | Assumes little prior experience; safe to start cold |
| Intermediate | Needs fundamentals (for example Linux or Git) already in place |
| Advanced | Production judgement, multi-tool workflows |
| Expert | Architecture and multi-domain design |
Frontmatter on each tutorial states its level and estimated time.
Tutorial structure¶
Every tutorial follows the same shape:
- Overview and prerequisites
- Learning objectives
- Theory (and architecture diagrams when they help)
- Hands-on lab
- Validation — how you know it worked
- Best practices
- Security notes
- Troubleshooting
- Interview questions
- Summary and official references
You can move between topics without relearning the format.
Hands-on learning¶
| Format | Role |
|---|---|
| Labs | Short scenarios after a module or track |
| Mini projects | Small portfolio pieces inside a technology |
| Enterprise-style projects | Multi-tool builds under Projects |
| Capstones | End-to-end proofs (for example Status API: Git → Docker → Kubernetes → Terraform) |
Reading without typing is not enough. Treat broken labs as part of the learning.
Certification preparation¶
Paths and technologies map toward industry exams when the content is ready. Examples:
- RHCSA / RHCE — Linux (and Shell for RHCE depth)
- CKA / CKAD / CKS — Kubernetes (and security for CKS)
- Terraform Associate — Terraform
- AWS / Azure / Google Cloud associate and architect-style exams — matching cloud tracks
See Certifications for the current mapping. Coverage grows as tracks ship; do not wait for 100% coverage to start studying.
Interview preparation¶
Each mature technology includes:
- Interview question themes
- Real-world scenarios
- Troubleshooting drills
- Production best practices
Use Interview Guides after you finish a track’s labs — not as a substitute for hands-on work.
Recommended first path (DevOps)¶
If your goal is a DevOps role, complete these ready tracks in order. Each checkpoint opens that course — same sequence as the DevOps Engineer career path.
New to Linux?
Begin with Linux Fundamentals — Distributions and Architecture. Finish the Linux modules, then Shell, then Python. Do not skip the labs.
CI/CD is GitLab-first today
Pipelines are taught under GitLab CI/CD. GitHub Actions and Jenkins tracks are planned — start with GitLab CI now.
Best way to learn¶
- Choose a career path (or one technology if you already know the gap).
- Complete tutorials in order — prerequisites matter.
- Perform every lab — type the commands; break and fix things.
- Build projects from the catalog.
- Complete a capstone when the path is ready for it.
- Prepare interview questions for that track before moving on.
What you need on day one¶
| Requirement | Notes |
|---|---|
| Laptop or VM | Linux preferred (Ubuntu 22.04+ / 24.04); WSL2 is fine |
| Terminal comfort | Basic shell use is enough to begin |
| Curiosity | Labs are meant to be broken and repaired |
Add tools as you reach each track (Python 3.12+, Docker, kubectl, Terraform, AWS Free Tier with a billing alarm, and so on). Prefer disposable lab VMs with snapshots.
Choose your learning path¶
| Go here | When |
|---|---|
| Career Paths | You want a job-shaped roadmap |
| Technologies | You want a specific skill (start with Linux if unsure) |
| Labs | You want scenario practice |
| Projects | You want portfolio builds |
| Capstones | You want an end-to-end proof |
| Interview Preparation | You are preparing for interviews |
| Cheat Sheets | You need a quick command reference |
| Certifications | You are mapping study to exams |
Suggested first click: Beginner career path or Linux Fundamentals.