URL Shortener

A backend service that creates short URLs and redirects them to their original destination.

The project is built to demonstrate common backend engineering patterns such as caching, background job processing, rate limiting, and containerized infrastructure.

More detailed design explanations are available in the docs/architecture.md document.

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Architecture

The system runs as multiple containers:

• FastAPI API service
• PostgreSQL database
• Redis for caching and queues
• RQ worker for background jobs
• Prometheus for metrics
• Grafana for visualization

Docker Compose is used to run the entire stack locally.

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Tech Stack

Backend

• Python
• FastAPI
• SQLAlchemy

Infrastructure

• PostgreSQL
• Redis
• RQ (Redis Queue)
• Docker / Docker Compose
• Prometheus
• Grafana

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Features

• URL shortening API
• Redis caching for fast redirects
• Redis-based rate limiting
• asynchronous analytics processing with background workers
• Prometheus metrics
• containerized architecture using Docker

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API Endpoints

Method	Endpoint	Description
POST	/shorten	create short URL
GET	/url/{short_code}	redirect to original URL
GET	/url/stats/{short_code}	retrieve analytics
GET	/health	system health check
GET	/metrics	Prometheus metrics

Interactive API docs are available at:

http://localhost:8000/docs

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Running the Project

Requirements:

• Docker
• Docker Compose

Start the system:

docker compose up --build

Services started:

url_shortener_api
url_shortener_worker
url_shortener_postgres
url_shortener_redis
url_shortener_prometheus
url_shortener_grafana

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Observability

Metrics are exposed by the API at:

/metrics

Prometheus scrapes the API periodically to collect operational metrics.

Grafana can be used to visualize request traffic, cache performance, and latency.

Grafana UI: http://localhost:3000
Prometheus UI: http://localhost:9090

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Example Request

Create a short URL

POST /shorten

{
  "original_url": "https://google.com"
}

Response

{
  "short_url": "http://localhost:8000/url/a1B"
}

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Documentation

Detailed system design and implementation notes:

docs/architecture.md

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K6 load testing results:

docs/load-testing.md

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Purpose

This project demonstrates backend engineering concepts such as:

• API design
• caching strategies
• asynchronous background processing
• rate limiting
• containerized service architecture
• observability with metrics and dashboards
• load testing and performance analysis