Course index
Terraform → Ansible → Liquibase → (Jenkins, Grafana) → Git, built on a Postgres Aurora cluster. Every page below follows the same rhythm: mental model first, then why a command matters, then the lab, then how to read what happened.
00 · Orientation
This index
The map. Six documents, each covering a different layer of the same project — start with Theory if you're new, or jump straight to a Lab if you're picking up where you left off.
01 · Theory
The toolchain: what each tool is actually for
What each of the six tools is, its architecture, and where it deliberately stops and hands off to the next one. Read this before any lab — it's the mental model everything else builds on.
02–04 · Concepts + Lab
Terraform: VPC & Aurora
Five sub-labs — read the default VPC, create a new one, wire up networking, stand up Aurora, and import an existing VPC (with a real troubleshooting case on why import ≠ config match).
Environment setup, steps 02–08
VS Code, Git, GitHub login, Copilot, AWS CLI, AWS authentication, Terraform install — each with the mental model, the why, and how to read the result.
Environment setup, steps 09–12
Liquibase, Ansible, Java/PostgreSQL prerequisites, and a final end-to-end verification across everything installed in 02–11.
05 · Reference
Every command, by tool
Pure lookup — no concepts taught here. Git, Terraform, AWS CLI, Ansible, Liquibase, psql, and a PowerShell section for auditing what's actually installed on Windows.
- Mental model before commands. Every topic opens with what's actually going on, not a command to type.
- Why before important commands. A command you understand the purpose of is one you won't forget.
- Expected output, not just output. Each key command says what to look for and what failure means.
- What changed, after every lab. A before/after diagram connects the command to the system state it produced.
- Can I explain it? Every learning unit ends with a checklist — the real test is reproducing it without the doc.