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cloud-python

Structured Python learning repository focused on Cloud Engineering, AWS automation, and infrastructure tooling.

This repository documents a progressive journey from Python fundamentals to real-world cloud automation and AWS-based development.

The projects are organized into stages covering:

  • Python scripting fundamentals
  • Infrastructure-oriented utilities
  • AWS automation concepts
  • Error handling and validation
  • JSON and file processing
  • Logging and operational tooling
  • Future boto3 and serverless workflows

Repository Structure

cloud-python/
│
├── stage_1/
│   ├── aws_naming/
│   ├── ec2-audit/
│   ├── ec2-cost-report/
│   ├── ec2-tag-audit/
│   ├── env_inspector/
│   ├── error_handler/
│   └── file-io/
│
├── stage_2/
│   ├── boto3_setup/
│   ├── ec2-manager/
│   ├── s3-automation/
│   ├── security-groups/
│   └── utils/
│
├── requirements.txt
└── README.md

Stage 1 — Core Python for Cloud Engineering

Stage 1 focuses on building strong Python foundations applied to cloud and infrastructure scenarios.

Project Concepts Practiced
aws_naming Functions, reusable naming utilities
ec2-audit Lists, loops, EC2 filtering
ec2-cost-report Dictionaries, cost calculation
ec2-tag-audit Tag validation and infrastructure auditing
env_inspector Environment variables, logging, JSON output
error_handler Exception handling and simulated AWS API errors
file-io JSON parsing and report generation

Stage 2 — AWS Automation with boto3

Stage 2 focuses on real AWS interactions using the boto3 SDK, EC2 lifecycle management, S3 operations, and security group auditing.

Project Concepts Practiced
boto3_setup boto3 installation and connectivity verification
ec2-manager EC2 lifecycle management, auditing, and automation
s3-automation S3 bucket operations and file management
security-groups Security group auditing and compliance checks
utils Shared EC2 utilities and logging configuration

Technologies Used

  • Python 3.13
  • Python Virtual Environments (venv)
  • Git & GitHub
  • AWS CLI concepts
  • AWS Free Tier

Engineering Concepts Practiced

  • Modular code organization
  • Utility function design
  • Logging
  • Exception handling
  • Type hints
  • Input validation
  • JSON serialization
  • Environment variable management
  • Infrastructure-oriented scripting
  • Git branching and version control workflows

Roadmap

Stage 1 — Core Python for Cloud Engineering

  • Python fundamentals
  • Infrastructure scripting
  • File handling
  • Logging and validation

Stage 2 — AWS Automation with boto3

  • EC2 automation
  • S3 operations
  • IAM interaction
  • CloudWatch integration

Stage 3 — Serverless and Lambda

  • AWS Lambda
  • Event-driven workflows
  • API Gateway
  • Scheduled automation

Stage 4 — AI Agents on AWS

  • AI automation workflows
  • AWS-hosted agents
  • LLM integrations
  • Event orchestration

Stage 5 — CI/CD and Infrastructure as Code

  • GitHub Actions
  • Terraform
  • Docker
  • Deployment pipelines

Purpose

This repository was created as a practical learning portfolio focused on:

  • Cloud Engineering
  • AWS Solutions Architecture
  • Python automation
  • Infrastructure tooling
  • Backend operational scripting