DevOps Automation Project – Assignment 2

Author: Michael McKibbin
Student ID: 20092733
LinkedIn: michaelkevinmckibbin

📘 Overview

This project automates the provisioning and monitoring of a scalable web application infrastructure on AWS using Python and Bash. It was submitted as part of the DevOps module (26670, 2023–2024) for my BSc in Computer Science at SETU Waterford.

🚀 Features

• Launches EC2 instances using Boto3 (up to 3 in a single call)
• Installs Apache and hosts a dynamic index.html page with instance metadata
• Uploads and runs monitoring scripts (monitor.sh and memv2.sh) via SCP and SSH
• Deploys and starts a custom Node.js app (app.js)
• Sets up AWS CloudWatch alarms for auto-scaling based on CPU utilization
• Describes and outputs active alarms from CloudWatch

📁 File Descriptions

File	Description
devops_2.py	Main Python script to automate EC2 provisioning, app deployment, and CloudWatch alarm setup.
monitor.sh	Bash script to extract and display EC2 instance status, Apache metrics, and system info.
memv2.sh	Bash script to push custom metrics (memory, connections, I/O wait) to AWS CloudWatch.
Devops-Assignment-2-Report-mmckibbin-20092733.pdf	Detailed PDF report documenting architecture, implementation, and testing.
DevOps Assignment 2 Grading.xlsx	Checklist used to ensure assignment met all required criteria.

🛠️ Tools & Technologies

• AWS EC2, CloudWatch, Auto Scaling
• Python 3, Boto3
• Bash scripting
• Apache HTTP Server
• Node.js
• AMI creation
• Custom monitoring metrics

🖼️ Architecture

• VPC with 3 Availability Zones
• Public and private subnets
• Load Balancer and Auto Scaling Group
• Custom AMI for efficient scaling
• CloudWatch alarms:
  • Scale out above 50% CPU
  • Scale in below 30% CPU

See the full diagram and deployment flow in the PDF report.

🧪 Testing

• Auto-scaling behavior tested using synthetic traffic (e.g. curl loops)
• Confirmed load balancer routing, CloudWatch triggering, and instance termination
• Verified monitoring output from monitor.sh and memv2.sh

📷 Screenshots

The report includes:

• Full VPC setup
• Load balancer and scaling screenshots
• Monitoring output and metrics visualizations

📜 License

This project was developed for academic purposes. Code and scripts may be reused for personal learning or non-commercial educational use with attribution.

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Michael McKibbin
BSc Computer Science (Computer Forensics & Security)
AWS Cloud Practitioner | CompTIA Security+ | Oracle Java SE 7
GitHub | LinkedIn