Use case diagrams in LLD - Scalability & System Analysis

Scalability Analysis - Use case diagrams

Growth Table: Use Case Diagrams

Users/Projects	What Changes
100 users	Simple diagrams with few actors and use cases. Mostly manual drawing or small tools.
10K users	Need for collaborative tools, version control, and reuse of diagram components. Performance starts to matter.
1M users	Cloud-based platforms with multi-tenant support, real-time collaboration, and integration with other design tools.
100M users	Global distributed systems, heavy caching, AI-assisted diagram generation, and advanced analytics on usage patterns.

First Bottleneck

At small scale, the bottleneck is usually the tool's ability to handle multiple actors and use cases without clutter. As users grow, the bottleneck shifts to collaboration and version control systems that manage concurrent edits and diagram history. At very large scale, the bottleneck becomes the backend infrastructure supporting real-time updates and data synchronization across many users.

Scaling Solutions

• Small scale: Use simple desktop tools or lightweight web apps.
• Medium scale: Implement collaboration features with locking or operational transformation to handle concurrent edits.
• Large scale: Use cloud infrastructure with horizontal scaling, real-time databases (like Firebase), and CDN for static assets.
• Very large scale: Employ sharding of user data, caching of frequently accessed diagrams, and AI to assist in diagram creation and error detection.

Cost Analysis

Assuming 10K active users editing diagrams:

• Requests per second: ~167 (assuming 1 edit per user per minute)
• Storage: Each diagram ~100KB, with 10K users and average 5 diagrams each = ~5GB storage
• Bandwidth: Edits and updates ~50KB per request, 167 RPS = ~8.35MB/s (~66.8Mbps)

Scaling to 1M users multiplies these numbers by 100, requiring distributed storage, load balancing, and CDN usage.

Interview Tip

When discussing scalability of use case diagram tools, start by identifying user growth and collaboration needs. Explain how concurrency and data synchronization become challenges. Discuss backend scaling, caching, and real-time update strategies. Always relate solutions to user experience and system responsiveness.

Self Check

Your diagram collaboration backend handles 1000 QPS. Traffic grows 10x. What do you do first?

Answer: Add read replicas and implement caching to reduce database load. Also, consider horizontal scaling of application servers to handle increased concurrent connections.

Key Result

Use case diagram tools scale from simple single-user apps to complex cloud platforms requiring real-time collaboration and distributed infrastructure as user count grows from hundreds to millions.