AWS DevOps Project Case Study

Simple Configuration Service - A Complete DevOps Journey

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10+
AWS Services
5
Pipeline Stages
95%
Test Coverage
300 users
Load Capacity

Project Overview

This comprehensive case study details the development and deployment of a "Simple Configuration Service", a web API designed to efficiently manage key-value pairs. The core objective was to build a complete and functional CI/CD pipeline and a robust, scalable cloud infrastructure on AWS, transforming source code into a containerized application accessible via the web.

This project served as a foundational learning experience for junior DevOps professionals, providing hands-on exposure to a wide array of industry-standard tools and services.

The Challenge

The primary challenge was to create a web service capable of storing and retrieving simple key-value configurations, akin to parameters or small settings. This involved several key aspects:

API Development

Building a simple REST API using Python and Flask with defined endpoints for writing (POST /config) and reading (GET /config/{key}) data.

Data Persistence

Integrating a managed NoSQL database to reliably store the key-value pairs.

Containerization

Encapsulating the application within Docker containers to ensure consistent execution across different environments.

Automated CI/CD

Establishing a fully automated pipeline for building, testing, and deploying the application upon every code change.

Cloud Infrastructure Design

Architecting a resilient and scalable cloud environment on AWS, capable of hosting the containerized application.

Security

Ensuring secure management of AWS credentials and network access.

Solution & Implementation

Results & Performance Analysis

Load and stress tests were conducted using Locust to assess the Flask application's ability to handle expected traffic volumes and identify performance bottlenecks.

Stress Test Results

Failure Point:~227 users
CPU Utilization:99.9%
Peak Requests:36.7k

Load Test Results

Avg Response Time:16.16s
Throughput:3.3 TPS
Error Rate:9.93%

Implemented Improvements

  • Auto Scaling Group implementation improved resilience (300 users for ~2 min with 3 instances)
  • CloudWatch monitoring with dashboards and alarms for proactive issue detection
  • Multi-region disaster recovery with DynamoDB Global Tables

Conclusion & Future Directions

This project successfully built a fully functional "Simple Configuration Service" with a complete DevOps architecture, encompassing Flask application development, Docker containerization, Bitbucket Pipelines for CI/CD, and a robust AWS infrastructure.

Future Enhancements

AWS Lambda Automation

Automate multi-region failover and database restoration

Container Orchestration

Migrate to AWS ECS/Fargate for simplified deployment

Infrastructure as Code

Define infrastructure using Terraform or CloudFormation

Custom Domain

Integrate Route 53 for better accessibility and branding

This project served as an invaluable opportunity to apply fundamental DevOps concepts and gain hands-on experience with widely used tools and services in the industry.

Architecture Visualization

AWS DevOps Architecture Flow

CI/CD Pipeline Flow

1
Code Push
2
Build & Test
3
Docker Build
4
Push to ECR
5
Deploy to EC2

Tech Stack

Python/Flask

Backend

Docker

Container

AWS EC2

Machines

DynamoDB

Database

CloudFront

CDN

Bitbucket

CI/CD

Pytest

Testing

CloudWatch

Monitoring

Key Takeaways

Scalability Achieved

Auto Scaling Groups enabled handling 300 concurrent users with 3+ instances

Full Automation

Complete CI/CD pipeline from code commit to production deployment

High Availability

Multi-region DR setup using DynamoDB Global Tables