DevOps Learning Repo

This repository is a hands-on collection of small examples and notes you can use to upskill your DevOps knowledge. The content is organized by folder name; most folders contain ready-to-run examples or short documentation. Use this README as a quick map and a suggested learning path.

How to use this repo

1. Clone the repo locally and open it in your editor of choice.
2. Read the Readme.md inside each folder when present (some folders have a single README). If a folder has no README but contains files, open those files — their names usually describe the content.
3. Try the examples locally (many are small Docker/Python demos). Run one example end-to-end, then read and tweak the code or Dockerfile to learn how changes affect behavior and the image.
4. Repeat: pick a different folder and try a new exercise. Track what you learned in a personal notes file or a PR-style change in the repo.

Folder overview

• Docker/ — Practical Docker examples and notes. This is the most content-rich area right now.

  • Portforwarding.md — A focused document that explains port forwarding with Docker containers (read this to understand host<->container networking basics).
  • subfolders include container examples such as bind_mount, Container_with_localDB, demo, interactive-mode, multiple_container, userinfo, and working_with_api — each contains a Dockerfile and small demo scripts like myapp.py or sql_demo.py.
  • Suggested exercises: build and run each Docker example, inspect image layers, experiment with --no-cache-dir for pip installs, and try Docker BuildKit cache mounts for faster iterative builds.

• Git&github/ — A folder with Readme.md containing Git and GitHub notes/exercises. Start here if you want to strengthen your source-control workflows (branches, PRs, rebasing, tags, hooks).

• yaml/ — Various YAML and related config examples. There is no Readme.md here yet, but the filenames are descriptive:

  • datatypes.yml, advanceDatatype.yml, hello.yaml, school.yml and also school.json / school.xml for format comparison.
  • Suggested exercises: validate YAML with yamllint/yq, convert JSON↔YAML, write a small Kubernetes manifest based on these examples, and try templating with Helm or Kustomize.

Quick learning path (suggested)

1. Git fundamentals: open Git&github/Readme.md and follow the exercises there. Practice branching, committing, pushing, and making PRs.
2. Docker basics: read Docker/Portforwarding.md then build and run Docker/demo and Docker/userinfo examples to get comfortable with Dockerfiles, volumes, and ports.
3. Intermediate Docker: try Container_with_localDB and multiple_container to learn about multi-container setups, bind mounts, and networking between containers.
4. Configuration and manifests: use yaml/ to practice writing and validating configuration files and transform them into simple Kubernetes manifests.
5. Automation & CI: once comfortable, add a GitHub Actions workflow to build and test one Docker example on push.

Commands to try (zsh / Linux)

Open a terminal and run these from the repo root:

# list top-level folders
ls -la

# explore Docker examples
cd Docker
ls -la

# build a specific example (adjust the path to the folder you want)
docker build -f Container_with_localDB/Dockerfile -t my-sql-demo ./Container_with_localDB

# run the image interactively (if the demo supports it)
docker run --rm -it my-sql-demo

# validate a YAML file (install yamllint or yq first)
yamllint yaml/hello.yaml

Note: some examples use Python. If a Dockerfile installs Python packages, you may see --no-cache-dir used with pip to avoid leaving pip's download cache in the final image (this keeps images smaller).

Prerequisites

• Docker installed and running
• (Optional) Python 3.11+ for running local scripts outside containers
• (Optional) yamllint / yq if you want to validate and manipulate YAML locally

Next steps and ideas

• Add Readme.md files for the yaml/ folder and for other Docker subfolders that don't have one, describing how to run each demo.
• Add simple GitHub Actions workflows that build Docker images for Docker/demo and run any included tests.
• Convert a few yaml/ examples into Kubernetes manifests and add kubectl --dry-run=client -f checks.

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If you'd like, I can:

• create missing Readme.md files inside yaml/ and other folders with run instructions, or
• add a minimal GitHub Actions workflow that builds one of the Docker examples.

Tell me which follow-up you'd prefer and I'll implement it.