Cloud Computing, Fall 2025 Semester

This repository contains the source code, scripts, and documentation for a Cloud Computing learning project, developed in Ubuntu Linux using command-line tools and cloud platforms. The project is structured as a series of weekly labs to build foundational skills in cloud concepts and deployment. Git and GitHub usage begins from Week 03 for version control and repository management.

Project Overview

• Path: /home/deepblue/cloud_computing
• Environment: Ubuntu Linux (e.g., VirtualBox VM), Python (Flask), Heroku CLI, OpenSSH
• Purpose: Learn cloud computing fundamentals through hands-on labs, with outputs verified via terminal logs and cloud dashboards.
• Structure: Weekly scripts and command histories called in lab sessions to demonstrate concepts.

Week 01: Course Introduction and Cloud Computing Overview

Objectives

• Understand the syllabus, tools, and basic terminology.
• Gain an overview of cloud computing history, benefits, and key players (e.g., AWS, Azure, Google Cloud).

Content

• Reviewed course outline: Focus on service models, deployment strategies, and hands-on deployments.
• Explored core concepts: Scalability, elasticity, virtualization, and economic models.

Week 02: Cloud Service Models

Objectives

• Differentiate between service models: IaaS (Infrastructure as a Service), CaaS (Container as a Service), PaaS (Platform as a Service), FaaS (Function as a Service), and SaaS (Software as a Service).
• Understand responsibilities, use cases, and trade-offs for each model.

Content

1. week02_service_models.md (or notes in Markdown):
   • IaaS: Full control over OS and apps (e.g., AWS EC2); user manages runtime, middleware, and data.
   • CaaS: Container orchestration (e.g., Kubernetes on Google Cloud); abstracts infrastructure but manages containers.
   • PaaS: Managed platform for app deployment (e.g., Heroku); handles runtime and middleware.
   • FaaS: Serverless execution (e.g., AWS Lambda); pay-per-use, no server management.
   • SaaS: Fully managed apps (e.g., Google Workspace); end-user consumption only.
   • Example: Diagram or table summarizing models (e.g., responsibility matrix).
2. Hands-on Lab: PaaS Deployment with Heroku and Flask:
   • Created a simple Flask app (app.py):

     from flask import Flask
     app = Flask(__name__)
     
     @app.route('/')
     def hello():
         return "Hello from PaaS on Heroku!"
     
     if __name__ == '__main__':
         app.run()

   • Created a requirments.txt file and a Procfile file.
   • Prepared for deployment (full Git-based push covered in Week 03): heroku create flask-hello-paas.

Week 03: Cloud Deployment Models

Objectives

• Explore deployment strategies: Public, Private, Hybrid, and Community clouds.
• Understand security, compliance, and scalability implications.
• Introduce Git and GitHub for version control, including repository setup and basic commands.

Content

1. week03_deployment_models.md (summary notes):
   • Public: Shared resources (e.g., AWS public cloud); cost-effective but less control.
   • Private: Dedicated infrastructure (e.g., on-premises VMware); high security for sensitive data.
   • Hybrid: Mix of public/private (e.g., burst to public during peaks); best for flexibility.
   • Community: Shared by specific groups (e.g., government clouds); balances cost and compliance.
   • Example: Use case scenarios, like a bank using hybrid for core vs. analytics workloads.
2. Hands-on Lab: IaaS Part 1 - OpenSSH Setup:
   • Installed OpenSSH server: sudo apt update && sudo apt install openssh-server -y.
   • Configured: Started service (sudo systemctl start ssh).
   • Tested: From local terminal, ssh deepblue@localhost (or remote VM IP).
   • Captured history: history >> command.txt.
3. Git and GitHub Introduction:
   • Installed Git: sudo apt install git -y.
   • Configured identity: git config --global user.name "Your Name" and git config --global user.email "your.email@example.com".
   • Initialized repository: git init, added files (git add .), committed (git commit -m "Initial commit"), and pushed to GitHub (git remote add origin <repo-url> && git push -u origin main).