Azure Cloud Engineering Essentials

From Local Application to Production-Style Azure Workload

This is a hands-on Azure cloud engineering course that follows one workload from local development through progressively more realistic Azure architecture and operations.

Why it exists

Many cloud tutorials teach isolated services or certification terminology. This project teaches cloud concepts through an accumulating practical system. The method is: build it → understand it → secure it → automate it → observe it → break it → recover it → evaluate it.

Current state

• The complete course structure, navigation, and ten-layer/98-session map exist.
• Sessions 1–3 are initially developed.
• Sessions 4–98 are structured planning pages, not fabricated lessons.
• The author is personally walking through, validating, correcting, and improving the material.
• The course is not completely validated. See docs/VALIDATION.md.

Intended audience

Experienced application developers who want a structured, practical introduction to cloud engineering with Azure. Basic C#, web application, and Git familiarity is assumed.

Repository structure

• tools/, public/: static course generator and visual system
• src/, tests/CloudJourney.Tests/: continuing ASP.NET Core workload and tests
• infrastructure/: Bicep and safe parameter examples
• scripts/: setup, deploy, verification, and guarded cleanup
• labs/: lab support added as sessions are validated
• architecture/: decisions and progressive architecture record
• course-status.json: machine-readable session state
• .github/: Pages publishing and contribution templates

Status legend

• Planned: purpose, objectives, dependencies, and intended outcome exist.
• Drafted: substantive text exists but remains under review.
• Implemented: lesson, examples, and supporting files exist.
• Validated: relevant commands and builds succeeded in a recorded environment.
• Personally completed: author completed the learner journey end to end.
• Published: lesson is on the public course site.

These states are independent. Implemented does not mean validated.

Prerequisites

PowerShell 7, Git, Node.js 22 or newer, npm, .NET 8 SDK, Azure CLI, and an Azure account for Session 3 onward.

Run locally

git clone <repository-url>
Set-Location azure-cloud-engineering-essentials
npm ci
npm run dev

Open http://localhost:4173. Build and check documentation with npm run check.

Run the continuing workload:

dotnet restore
dotnet test
dotnet run --project .\src\CloudJourney.Web

Use the URL printed by .NET and verify /health.

Publish with GitHub Pages

The included workflow builds dist/ and deploys it. After creating a GitHub repository yourself, push main, then select GitHub Actions as the Pages source in repository settings. No remote or publication is created by this scaffold.

Costs and safety

Azure resources may incur charges. Learners are responsible for reviewing costs, confirming tenant/subscription/resource-group scope, and running cleanup. Guarded scripts refuse mismatched subscriptions, unexpected names, and untagged deletion targets, but always inspect the command and target yourself.

Never commit credentials, tenant IDs, subscription IDs, deployment outputs, or local environment files.

AI disclosure

Artificial intelligence tools were used to help organize the curriculum, draft explanations, create initial code and documentation, and assist with review. The course direction is based on the author’s professional software-development and DevOps experience, along with an extended process of discussing, refining, and connecting practical cloud-engineering concepts. AI-generated output is not assumed correct. The author is personally working through the labs, testing commands, reconciling the code with the documentation, and revising the material as the course develops.

Technical sources

Developed sessions cite Microsoft Learn and official Azure documentation. Large passages are not copied. Course conventions, teaching simplifications, and unvalidated future plans are identified as such.

Project Status

This project is intentionally public while it is still evolving.

The repositories in this academy are my personal learning and reference material. They combine my professional software engineering experience, topics I am actively learning, and ideas developed through extensive discussions with AI.

AI has been used to help organize the curriculum, generate initial drafts, create code examples, suggest exercises, review documentation, and accelerate development.

That does not mean I assume the generated content is correct.

The purpose of publishing these repositories early is to make the material easily accessible from anywhere and to document my own learning journey. As I work through each course, I personally review, validate, correct, refactor, expand, and sometimes completely rewrite sections based on what I learn.

Because of that, some sessions may be fully validated while others remain drafts or works in progress. Each repository includes status indicators so readers can distinguish between planned, drafted, implemented, and validated content.

If you discover an error, inconsistency, or a better approach, please assume it is part of an evolving project rather than a finished product. Constructive feedback is always appreciated.

The goal is not to present myself as the ultimate authority on these subjects. The goal is to build a high-quality collection of practical engineering references that improve over time through testing, experience, and continual refinement.