the archive
Articles
60 deep dives, ~19 hours of hands-on builds. Filter by topic, or press ⌘K to search everything.
60 articles
30 Days of DevOps
30 articles
Git from Zero — Your First Commit, Branches, and the Two Workflows Real Teams Use
Git tutorial for beginners: install Git, make your first commit, and learn branching hands-on — then compare GitFlow vs trunk-based development, the two workflows real DevOps teams use.
Dockerize Any Application the Right Way — Multi-Stage Builds & Best Practices
Docker multi-stage build tutorial: shrink a 1.2 GB image to 47 MB with a distroless, non-root Dockerfile, and verify the security gains with Docker Scout. Dockerfile best practices.
Docker Compose for a Full Local Dev Stack — Node.js, PostgreSQL, Redis, and Nginx
Docker Compose tutorial: run a full local dev stack — Node.js REST API, PostgreSQL, Redis, and Nginx — wired together with health checks, named volumes, and startup ordering.
GitHub Actions CI/CD — Automated Build, Test, Scan, and Push on Every Commit
GitHub Actions CI/CD tutorial: build a 3-job pipeline that tests your Docker image, blocks bad merges, scans for CVEs, and pushes to GHCR on every commit — in under 2 minutes.
Kubernetes Fundamentals — Local Cluster with kind, Pods, Services, and Zero-Downtime Rollouts
Kubernetes tutorial for beginners: run a local cluster with kind, deploy a containerised app, add liveness and readiness probes, and ship a zero-downtime rolling update — no cloud needed.
Helm — Package Manager for Kubernetes. Charts, Templates, and Multi-Environment Releases
Helm tutorial for Kubernetes: turn raw YAML into a reusable Helm chart, configure dev vs prod with values.yaml, then install, upgrade, and roll back releases with single commands.
Python for AI Engineering
30 articles
Set Up Python on Any OS and Write Your First Program
Day 1 of Python for AI Engineering. Install Python on macOS, Windows or Linux, set up VS Code and your first virtual environment, then write and run a real Python program — an interactive intro-card generator. No prior coding experience needed; everything runs on your own laptop.
Variables, Numbers, Strings & Booleans
Day 2 of Python for AI Engineering. Master the raw materials of every program: variables, the four core data types (int, float, str, bool), arithmetic, string formatting, comparisons, and the type conversions that make user input usable. You'll build an interactive tip & bill-splitting calculator.
Lists, Tuples, Sets & Dictionaries
Day 3 of Python for AI Engineering. Meet Python's four built-in collections — lists, tuples, sets and dictionaries — learn exactly when to reach for each, and the operations you'll use daily. You'll build a contact book that uses all four together.
Loops & Conditionals
Day 4 of Python for AI Engineering. Make your programs decide and repeat: if/elif/else, the and/or/not logic, for loops over collections, while loops, and break/continue. You'll turn the contact book into a real menu-driven app you can use again and again.
Functions & Return Values
Day 5 of Python for AI Engineering. Learn to package code into reusable functions: def, parameters and arguments, return values (and how they differ from print), default and keyword arguments, and multiple return values. You'll refactor the contact book so every menu action becomes a clean function.
Scope, Imports & Modules
Day 6 of Python for AI Engineering. The last piece of the foundations: where variables live (scope), how to split code across files (modules), how to import your own code and Python's huge standard library, and the if __name__ == '__main__' idiom. You'll split the contact book into a reusable module and a main program.