Why booking tests availability and concurrency in LLD - Architecture Impact

System Overview - Why booking tests availability and concurrency

This system manages booking tests for users, ensuring that test slots are available and preventing double bookings. It must handle many users trying to book at the same time without errors or conflicts.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Booking Service <-> Cache
  |
  v
Database
  |
  v
Message Queue
  |
  v
Notification Service

Components

User

client

Person or system requesting to book a test slot

Load Balancer

load_balancer

Distributes incoming requests evenly to prevent overload

API Gateway

api_gateway

Handles routing, authentication, and request validation

Booking Service

service

Processes booking requests, checks availability, and manages concurrency

Cache

cache

Stores frequently accessed availability data for fast reads

Database

database

Stores persistent booking data and test slot information

Message Queue

queue

Handles asynchronous tasks like sending booking confirmations

Notification Service

service

Sends booking confirmation messages to users

Request Flow - 11 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → Booking Service

Booking Service → Cache

Cache → Booking Service

Booking Service → Database

Database → Booking Service

Booking Service → Cache

Booking Service → Message Queue

Message Queue → Notification Service

Notification Service → User

Failure Scenario

Component Fails:Database

Impact:New bookings cannot be saved; availability data may become outdated; users may see stale availability or booking failures.

Mitigation:Reads can still be served from cache for availability; implement database replication and failover to reduce downtime; queue booking requests for retry when DB recovers.

Architecture Quiz - 3 Questions

Why does the Booking Service check the Cache before the Database?

A Because the cache stores user personal data

B To get availability data faster and reduce database load

C To avoid sending notifications

D Because the database is only for backups

Design Principle

This design uses caching to speed up availability checks and reduce database load. Concurrency control in the Booking Service ensures no double bookings happen even with many simultaneous requests. Asynchronous messaging decouples booking confirmation notifications, improving system responsiveness and reliability.