Why library management tests CRUD design in LLD - Design It to Understand It

Design: Library Management System

Focus on CRUD operations for books and users. Exclude advanced features like recommendation engines or digital content management.

Functional Requirements

FR1: Add new books to the library catalog

FR2: Update book details such as title, author, and availability

FR3: Delete books that are no longer in the collection

FR4: Retrieve book information for users and staff

FR5: Manage user accounts and borrowing records

Non-Functional Requirements

NFR1: Support up to 10,000 books and 1,000 concurrent users

NFR2: API response time under 300ms for CRUD operations

NFR3: Ensure data consistency and integrity

NFR4: Availability target of 99.9% uptime

Think Before You Design

Questions to Ask

❓ Question 1

❓ Question 2

❓ Question 3

❓ Question 4

❓ Question 5

Key Components

Database for storing book and user data

API layer for CRUD operations

Authentication and authorization module

Cache for frequently accessed book data

Logging and monitoring tools

Design Patterns

CRUD design pattern

Repository pattern for data access

Optimistic locking for concurrent updates

Caching pattern for read-heavy operations

Soft delete pattern for safe deletion

Reference Architecture

Client
  |
  v
API Gateway
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  v
Auth Service
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  v
Database (Books, Users)
  |
  v
Cache Layer (Redis)
  |
  v
Logging & Monitoring

Components

API Gateway

RESTful API

Handle client requests and route to appropriate services

Auth Service

OAuth 2.0 / JWT

Authenticate users and authorize access to resources

Database

Relational DB (PostgreSQL)

Store book and user data with ACID properties

Cache Layer

Redis

Cache frequently accessed book data to reduce DB load

Logging & Monitoring

ELK Stack / Prometheus

Track system health and audit operations

Request Flow

1. Client sends a request to add/update/delete/retrieve a book via API Gateway

2. API Gateway authenticates the user via Auth Service

3. If authorized, API Gateway forwards request to Database or Cache

4. For read requests, Cache is checked first; if miss, query Database

5. For write requests, Database is updated with transaction support

6. Cache is updated or invalidated after write operations

7. Operation details are logged for monitoring and audit

Database Schema

Entities: Book (id, title, author, isbn, availability, created_at, updated_at), User (id, name, email, role, created_at), BorrowRecord (id, user_id, book_id, borrow_date, return_date) Relationships: User 1:N BorrowRecord, Book 1:N BorrowRecord

Scaling Discussion

Bottlenecks

Database write throughput limits with many concurrent updates

Cache consistency issues leading to stale data

API Gateway becoming a single point of failure

Authentication service latency under high load

Solutions

Use database sharding or read replicas to distribute load

Implement cache invalidation strategies and TTLs

Deploy API Gateway in a load-balanced cluster

Scale Auth Service horizontally and use token caching

Interview Tips

Time: Spend 10 minutes understanding requirements and clarifying scope, 20 minutes designing components and data flow, 10 minutes discussing scaling and trade-offs, 5 minutes summarizing

Explain importance of CRUD as foundation for system functionality

Discuss data consistency and concurrency control

Highlight caching benefits for read-heavy workloads

Address security and authorization considerations

Show awareness of scaling challenges and mitigation