Docker Compose Illustrated

The ultimate parent-child relationship of our time: CPU interrogating Docker about its resource consumption. Based on the children's rhyme "Johnny Johnny Yes Papa," this meme captures the eternal deception between Docker containers and system resources. Docker swears it's not hogging RAM, but the final panel reveals the cold, hard truth: 9.06 GB of memory consumed by a single container. The CPU might as well ask, "Where did all my gigabytes go?" while Docker sits there with the computational equivalent of chocolate all over its face. Every DevOps engineer knows that feeling when Docker promises to be lightweight and then proceeds to eat resources like they're free samples at Costco.

Pour one out for the classic developer alibi that died on March 19, 2013. The day before Docker launched, developers everywhere enjoyed their final blissful moments of saying "but it works on MY machine!" with zero consequences. Then containerization nation attacked, and suddenly your local environment excuse became as extinct as Internet Explorer's security updates. Now when code fails in production, your team lead just smugly whispers "docker build" while maintaining uncomfortable eye contact.

The formal announcement of creating your first Dockerfile is peak developer evolution. You start thinking it's some mystical container sorcery, only to discover it's basically just a glorified text file with instructions like "COPY this" and "RUN that." The aristocratic frog perfectly captures that moment of unwarranted self-importance when you realize you've joined the DevOps nobility by writing what amounts to a fancy shopping list. Next step: explaining containerization at parties like you invented it.

Modern infrastructure is like those Russian nesting dolls, except each layer has amnesia about how it got there. First you run whoami to confirm your identity crisis, then whereami reveals you're trapped in containerception—a Docker container inside Kubernetes inside a VM inside a hypervisor inside someone else's datacenter. And when you desperately ask howdidigethere , the system responds with brutal honesty: absolutely zero recollection of the deployment decisions that led to this beautiful disaster. It's cloud computing's version of waking up in Vegas with no memory but a receipt for 17 EC2 instances.

Ah, the classic "added login functionality" commit that touches 41 files. Nothing says "I definitely understand authentication best practices" like modifying every single file in your codebase to implement a login system. That security.py file is probably just for show – the real authentication logic is scattered across 40 other files like a treasure hunt for future developers. This is the coding equivalent of saying "I tidied up the house" when you've actually just shoved everything under the bed, in drawers, and behind the couch. Future you will definitely not curse present you when trying to debug this masterpiece.

The bell curve of developer intelligence has spoken: only the truly enlightened (bottom 0.1% and top 0.1%) understand that standalone binaries are superior, while the mediocre 68% in the middle are screaming about containerized environments like they've discovered fire. It's the perfect illustration of how software development fashion works - the beginners and masters quietly compile to binaries while everyone with average intelligence overcomplicates deployment with Docker manifests, Kubernetes configs, and seventeen layers of abstraction just to run "Hello World." The cosmic joke? Those containers are ultimately running binaries anyway. Full circle, but with extra steps.