Build a Complete URL Shortener with Spring Boot & PostgreSQL | System Design + Code Walkthrough

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Welcome back to Dev Portal. In this video, I'll guide you through building a production-ready URL Shortener using Spring Boot, while also covering real-world system design practices that scale.

Whether you’re preparing for a system design interview or building your own side project, this video will help you understand key backend concepts.

What You'll Learn:
- Project Overview: Understand the architecture and components of the URL shortener.
- API Endpoints: Explore the various endpoints created, their purposes, and how they interact.
- Global Exception Handling: Learn how to implement a centralized exception handling mechanism to provide meaningful error responses and improve user experience.
- Rate Limiting: Protect your endpoints from abuse using a sliding window algorithm, prevent throttling and ensure service stability.
- Redis Caching: Discover how integrating Redis can significantly boost application performance by caching frequently accessed data.
- Short Code Generation Strategy: Generate short codes using a 6-character random string (a–z, A–Z, 0–9). However, this approach requires checking for collisions in the database, which can slow down performance with millions of records. Learn why this isn't optimal at scale and explore better alternatives like UUID-based short codes, Hashing the original URL or Encoding with a secret key
- Hit Count Tracking: See how to implement a feature that tracks the number of times a shortened URL is accessed.
- Asynchronous Processing & Kafka (Planned): Discuss the challenges of sync updates on hit count and how to move to async updates using @Async or Kafka for handling bulk updates without blocking requests.
- Logging Best Practices: Log application and audit-level data in separate log files with date-based naming. Automatically create log folders at startup.
- VMSS & Load Balancing Concepts: Understand how Virtual Machine Scale Sets (VMSS) and Load Balancers with round-robin techniques help distribute traffic and scale your application under high load.
- Connection Pooling: Use database connection pooling to handle large numbers of concurrent transactions efficiently, especially for bulk updates.
- Frontend Roadmap: Discussion about upcoming frontend implementation using Angular for a complete full-stack application.

Technologies Used:
- Backend: Spring Boot (Java 8), Hibernate, Redis, PostgreSQL
- Caching: Redis
- Logging: Logback (custom log file per day)
- Async Processing: Java @Async, Kafka (future)
- Infrastructure Concepts: VMSS, Load Balancer, Round Robin, Connection Pool
- Frontend: Angular (planned)

Key Takeaways:
- Build and deploy a scalable, real-world Spring Boot microservice.
- Apply critical system design and performance best practices.
- Improve user experience through clean error handling and logging.
- Learn about infrastructure concepts like load balancing, VM scaling, and resilience techniques.
- Prepare for interviews with hands-on examples of Redis, exception handling, async architecture, and rate limiting.
- Understand architectural trade-offs and future scalability planning.

- Don’t forget to like, subscribe, and comment if this video helped you or gave you some new ideas.
- Comment below if you want a deep-dive session on Kafka integration or frontend development.

Chapters:
00:00 - Introduction
00:34 - URL Shortener Overview
02:01 - Database table structure
04:31 - Backend code overview (Java + Spring Boot)
05:00 - Explained Controller & Dispacter Servlet
06:53 - Discussed about Service and Repository annotation
07:50 - Difference between Controller and RestContoller annotation
09:33 - How backend application connecting to database
13:04 - Accessing first end point (shorten)
17:42 - Short Code Generation Strategy
23:02 - Global Exception Handling
33:12 - VMSS & Load Balancing Concepts discussion
35:35 - Rate Limiting to prevent throttling and ensure service stability
42:34 - Accessing second end point (expand)
45:13 - Redis Caching to improve performance
49:25 - Logging (SLF4J dependency)
52:03 - Jackson property to remove null values from response body
53:08 - Updating Hit Count, Asynchronous Processing & Kafka
01:00:11 - Accessing second end point (getAllURLMappings)
01:00:50 - Ending

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