5 AM Study

Code, learn, and conquer before the world wakes up.

About The Project

This repository contains all the code, scripts, and notes from my daily 5 AM study sessions on my journey to becoming a world-class Site Reliability Engineer.
This is a public log of my progress, a library of my solutions, and a testament to the power of daily, focused effort.

Here you'll find my work on various SRE topics, including:

Linux Internals & Networking

Kubernetes & Containerization

Machine learning & AI

Programming in Python, Go and C

Repository Structure

This repository is organized by topic to make it easy to navigate and find specific information.

fiveamstudy-code/
  ├── CSAPP/                         # Computer Systems: A Programmer's Perspective
  ├── programming/                   # Core programming exercises
  │   ├── C/                         # C programming exercises
  │   │   ├── K&R/                   # K&R C Programming Language book exercises
  │   ├── go/                        # Go programming exercises
  │   ├── python/                    # Python implementations
  │   ├── leetcode/                  # LeetCode problem solutions (24 problems)
  │   ├── asm/                       # Assembly language programs
  │   └── algorithm_design_manual/   # Algorithm Design Manual exercises
  ├── docs-hands-on/                 # Implementing documentation and papers
  ├── machine_learning/              # Machine learning implementations
  ├── devops/                        # DevOps configurations
  └── vllm/                          # vLLM inference server things

Getting Started

Most of the code in this repository is for learning and demonstration purposes. To run a specific script or project, navigate to its directory and follow the instructions in the local README.md file, if available.

For example, to run a Python script:

cd /path/to/script_directory
pip install -r requirements.txt
python main.py

Contributing

This is a personal learning project, but if you spot an error, have a suggestion, or want to discuss a topic, feel free to open an issue or pull request. All contributions are welcome!

Fork the Project

Create your Feature Branch (git checkout -b feature/AmazingFeature)

Commit your Changes (git commit -m 'Add some AmazingFeature')

Push to the Branch (git push origin feature/AmazingFeature)

Open a Pull Request

License

Distributed under the MIT License.

Contact

Pat - youtube.com/@thefiveamstudy

Project Link: https://github.com/pat-sre/fiveamstudy-code