Scaling Memes

The Genie's Fourth Rule: No AWS

2 days ago 54.6K views 0 shares

The SRE just found the ultimate loophole to the genie's billion-dollar challenge, and the genie immediately shut that down faster than you can say "unexpected billing alert." Anyone who's ever deployed anything on AWS knows that mysterious $100M bill is just a few forgotten EC2 instances away. One day you're launching a "small test environment," the next day you're explaining to your CEO why your startup needs another funding round just to pay this month's cloud bill. Even supernatural beings with infinite cosmic power know better than to mess with AWS pricing. The fourth rule? "No cloud services that scale automatically and drain your life savings while you sleep."

Adding More Developers Won't Fix A Stuck Project

Programming Devops Agile Debugging

1 month ago 71.3K views 1 shares

Adding More Developers Won't Fix A Stuck Project

Adding more developers to a stuck project is like adding more people to drive a cart stuck in mud. The obvious solution? More horsepower to pull it out. The corporate solution? Add more drivers who'll just sit there smoking while the same horse struggles. Next sprint planning meeting, I'll just bring this picture instead of speaking. Saves everyone 45 minutes.

You Can't Have A Baby In 1 Month By Impregnating 9 Women

Programming Agile

1 month ago 72.8K views 0 shares

You Can't Have A Baby In 1 Month By Impregnating 9 Women

OH. MY. GOD. The absolute DELUSION of managers who think software development scales linearly! 💀 "The Mythical Man-Month" is basically the software developer's bible that screams "ADDING MORE PEOPLE TO A LATE PROJECT MAKES IT LATER!" But sure, let's give the boss TWO copies so he can misunderstand the concept TWICE as fast! Because apparently reading something twice simultaneously is just as impossible as having nine women produce a baby in one month. The savage irony of this gift is just *chef's kiss* - perfectly capturing every developer's silent scream when management decides that eight developers will finish in half the time of four. Spoiler alert: they won't!

Add More Resources

Backend Devops Programming Debugging Databases

1 month ago 74.1K views 0 shares

That moment when your janky prototype suddenly becomes "production-ready" because marketing did their job too well. Your spaghetti code that barely handled 10 concurrent users is now facing the wrath of 10,000. Time to frantically Google "how to scale horizontally at 3 AM" while the servers melt down and your phone won't stop buzzing with alerts. The classic developer prayer: "Dear CPU gods, please hold on until I can refactor this nightmare."

Found The Programmer

Programming Devops Algorithms Math

1 month ago 95.6K views 0 shares

SWEET MOTHER OF PARALLELISM! The teacher thinks cutting boards scales linearly (10 min = 2 pieces, so 15 min = 3 pieces), but our programming hero is having an existential crisis! 😱 They're thinking like a TRUE developer - if one woman takes 9 months to make a baby, then 9 women can make a baby in 1 month, right?! WRONG! Some processes just can't be parallelized, people! And that "multithreading pregnancy" comment? *chef's kiss* Pure genius! It's the perfect programmer response to the classic project manager delusion that throwing more resources at a problem magically makes it faster. Spoiler alert: your build time doesn't care about your deadlines!

The Great Architecture Debate: Monolith Vs. Microservices

Backend Devops Kubernetes Docker Programming

1 month ago 140.9K views 0 shares

The Great Architecture Debate: Monolith Vs. Microservices

The eternal architectural debate visualized with poop emojis. One massive monolith that's smiling confidently versus a scattered army of tiny microservices. The joke here is that both approaches can either be elegant solutions or complete crap depending on your team's competence. Nothing says "enterprise architecture" quite like discussing serious technical decisions with cartoon feces.

When Your "Big Data" Fits In A Spreadsheet

Databases Hardware Programming Cloud

2 months ago 149.2K views 0 shares

When Your "Big Data" Fits In A Spreadsheet

The joke here is that 60,000 rows is an absolutely tiny dataset in modern data engineering. Like, microscopic. A competent data engineer could process this on a 10-year-old laptop while running a YouTube video in the background. It's like bragging that your car overheated after driving to the end of your driveway. Any data pipeline that can't handle 60K rows without hardware failure is the computational equivalent of a paper airplane trying to carry passengers across the Atlantic. Real data engineers regularly process billions of rows without breaking a sweat. This is why everyone's laughing - it's the equivalent of someone claiming to be a weightlifting champion because they can lift a gallon of milk.

Cloud Bill Goes Brrrrr

Cloud Devops Kubernetes AWS Azure

2 months ago 163.5K views 0 shares

Hitting that "deploy to cloud" button feels like a heroic moment until you realize you've just signed up your credit card for an all-you-can-eat buffet where the servers never sleep. Your ancestors watch proudly as you configure auto-scaling without setting budget alerts. That $5/month estimate turns into $500 when your app gets three users and suddenly needs 17 microservices, a managed database, and enough storage to archive the Library of Congress. Future generations will be paying off your Kubernetes cluster long after you're gone.

Basically Ruby On Rails

Ruby Webdev Hardware Programming Debugging

2 months ago 103.2K views 0 shares

The Ruby on Rails philosophy in one image: why bother optimizing your code when you can just throw more CPU cores at it? This meme perfectly captures the "Rails magic" approach – your app runs like a three-legged dog until you upgrade your server. Then suddenly it's "fast enough" and everyone pretends the code isn't a dumpster fire underneath. Classic web framework solution: when in doubt, blame the hardware! Meanwhile, the Go developers are in the corner writing code that would run on a calculator.

Multithreading Be Like

Hardware Algorithms Programming Debugging Backend

2 months ago 143.9K views 0 shares

The CPU is making you an offer you can't refuse, mafia-style. It demands 32x more computational resources to give you a measly 1.7x speed boost in return. This is the classic multithreading paradox - throwing massive parallelism at a problem only to get diminishing returns because some tasks just don't scale linearly. It's like hiring 32 people to dig a hole when only 2 can fit in the space. The rest just stand around drinking coffee and collecting paychecks. The purple lighting really sets the mood for this computational extortion. Your CPU is basically saying "Nice application you got there... would be a shame if something happened to its performance."

The Fourth Rule: No AWS

AWS Devops Programming Cloud

2 months ago 124.0K views 0 shares

The fastest way to burn through $100M? Just whisper "AWS" and watch your bank account evaporate. That SRE knew exactly what they were doing - nothing drains a budget faster than spinning up a few "right-sized" EC2 instances and forgetting about them for a weekend. The genie immediately adding a fourth rule is basically Amazon's business model in a nutshell. Honestly, at least gambling gives you a chance of winning something back.

Must Be A DDoS Attack

Devops Networking Programming Debugging Backend

2 months ago 125.7K views 0 shares

Ah, the classic tech executive playbook: First, fire a third of your engineering team. Then, host a high-profile interview that everyone will want to watch. Finally, act surprised when your remaining skeleton crew can't handle the traffic spike. It's like removing three wheels from your car and then wondering why it can't complete a cross-country road trip. The distributed denial of service isn't from hackers—it's from your own distributed denial of common sense.

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