Building Scalable Design Systems: A Blueprint for Short Link Projects Serving 30M Users

JackyNote ⭐️
3 min readApr 26, 2024


In the realm of web development, the design system is the backbone that supports scalability, reliability, and user satisfaction. For a short link project catering to a user base of 30 million, meticulous planning and implementation are paramount. Let’s explore a detailed strategy, complete with specific examples and numbers, to craft an effective design system for such a project.

Understanding the Scale

With 30 million users, the system’s architecture must be robust enough to handle a massive influx of data and requests. Let’s break down the numbers:

  • Data Capacity Model: Assume an average of 100 link creations per user per month. This translates to approximately 3 billion link creations per month across the entire user base. Each link creation operation involves storing metadata such as the original URL, shortened URL, creation timestamp, and user ID.
  • Bandwidth Requirements: Assuming an average link redirection rate of 10 requests per second per user, the system needs to handle approximately 300 million redirection requests per second during peak hours.

Tech Stack Selection:

To meet the demanding requirements of the project, we propose the following tech stack:

  1. Spring Boot for Backend: Spring Boot provides a powerful and efficient framework for building Java-based microservices. Its lightweight nature and extensive ecosystem make it an ideal choice for handling the massive scale of our short link project.
  2. Redis for Caching: Leveraging Redis for caching frequently accessed data such as recently generated short links and their corresponding metadata can significantly reduce database load. With Redis, we can achieve sub-millisecond response times, ensuring a seamless user experience even under heavy load.
  3. MongoDB for Data Storage: MongoDB’s document-oriented database structure and horizontal scalability make it well-suited for storing the vast amount of link-related data generated by millions of users. With sharding and replication, MongoDB can handle billions of documents with ease while maintaining high availability and performance.

Designing the System Architecture:

Let’s delve into the architectural components and their scalability measures:

  • Microservices Architecture: Break down the system into microservices to ensure modularity and scalability. For example:
  • Link Generation Service: Responsible for creating and storing shortened links.
  • Redirection Service: Handles incoming requests and redirects users to the original URLs.
  • Analytics Service: Collects and processes data for user analytics and link performance metrics.
  • Load Balancing and Horizontal Scaling: Employ load balancers to distribute incoming traffic evenly across multiple instances of each microservice. Horizontal scaling, facilitated by containerization technologies like Docker and orchestration tools like Kubernetes, enables the system to scale up or down dynamically based on demand.
  • Caching Strategies: Utilize Redis as a caching layer to store frequently accessed data and alleviate the burden on the database. For example, cache recently generated short links and their metadata to reduce database read operations and improve response times.


Designing a scalable design system for a short link project serving 30 million users requires a meticulous approach backed by specific examples and numbers. By leveraging the proposed tech stack and implementing best practices in system architecture design, we can build a robust platform capable of handling billions of link creations and redirection requests while maintaining optimal performance and reliability.

In conclusion, a well-designed system architecture, coupled with the right technologies and scalability measures, is essential for meeting the demands of high-traffic web applications. With careful planning and implementation, we can create a design system that not only meets current requirements but also scales seamlessly to accommodate future growth and user engagement.

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JackyNote ⭐️

🚀 Software Engineer | Full Stack Java 7 Years of Experience | Tech Enthusiast | Startup Lover | Coffee