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Impact:New bookings cannot be saved; availability data may become outdated; users may see stale availability or booking failures.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

Practice

1. Why is it important to handle concurrency when booking test slots in a system?

easy

A. To allow unlimited bookings for the same slot

B. To slow down the booking process intentionally

C. To prevent multiple users from booking the same slot at the same time

D. To avoid showing available slots to users

Solution

1. Step 1: Understand concurrency in booking

   Concurrency means multiple users try to book the same slot simultaneously.

2. Step 2: Identify the problem caused by concurrency

   If concurrency is not handled, multiple users can book the same slot, causing double bookings.

3. Final Answer:

   To prevent multiple users from booking the same slot at the same time -> Option C

4. Quick Check:

   Concurrency handling = prevent double bookings [OK]

Hint: Concurrency means multiple users booking simultaneously [OK]

Common Mistakes:

• Thinking concurrency allows unlimited bookings
• Ignoring the need to prevent double bookings
• Assuming concurrency slows down the system intentionally

2. Which of the following is a correct way to ensure availability checks during booking in a system?

easy

A. Check slot availability after booking confirmation

B. Lock the slot before confirming the booking

C. Allow booking without checking availability

D. Ignore concurrency and rely on user honesty

Solution

1. Step 1: Understand locking in booking systems

   Locking a slot means reserving it temporarily to prevent others from booking it simultaneously.

2. Step 2: Identify when to check availability

   Availability must be checked and locked before confirming booking to avoid conflicts.

3. Final Answer:

   Lock the slot before confirming the booking -> Option B

4. Quick Check:

   Lock before confirm = correct availability check [OK]

Hint: Lock slot before booking to avoid conflicts [OK]

Common Mistakes:

• Checking availability after booking causes errors
• Ignoring availability checks leads to double bookings
• Relying on user honesty is not a system design

3. Consider this simplified booking flow code snippet:

def book_slot(slot_id):
    if is_available(slot_id):
        reserve(slot_id)
        confirm_booking(slot_id)
        return 'Booked'
    else:
        return 'Unavailable'

What issue can arise if two users call book_slot at the same time for the same slot_id?

medium

A. Both users might get 'Booked' causing double booking

B. The system crashes due to race condition

C. Both users get 'Unavailable' response

D. Only one user can call the function at a time automatically

Solution

1. Step 1: Analyze the code flow for concurrency

   Both users check availability before reservation without locking, so both may see the slot as available.

2. Step 2: Understand race condition effect

   Without locking, both reserve and confirm booking, causing double booking.

3. Final Answer:

   Both users might get 'Booked' causing double booking -> Option A

4. Quick Check:

   Race condition = double booking risk [OK]

Hint: Check-then-act without lock causes double booking [OK]

Common Mistakes:

• Assuming system crashes automatically
• Thinking both get 'Unavailable' response
• Believing function serializes calls automatically

4. In a booking system, the code uses a simple availability check without locking:

if check_availability(slot):
    book(slot)

Users report double bookings. What is the best fix?

medium

A. Add a lock or transaction around availability check and booking

B. Remove availability check to speed up booking

C. Increase server hardware to handle more requests

D. Notify users to book slower

Solution

1. Step 1: Identify the cause of double bookings

   Without locking, multiple users can pass availability check simultaneously causing conflicts.

2. Step 2: Apply concurrency control

   Using locks or transactions ensures only one booking proceeds at a time for the same slot.

3. Final Answer:

   Add a lock or transaction around availability check and booking -> Option A

4. Quick Check:

   Locking fixes concurrency issues [OK]

Hint: Use locks or transactions to fix concurrency bugs [OK]

Common Mistakes:

• Removing availability check causes more errors
• Upgrading hardware does not fix concurrency logic
• Telling users to slow down is not a system fix

5. You are designing a test booking system that must handle thousands of users booking slots concurrently. Which design approach best ensures availability and prevents double bookings?

hard

A. Show all slots as available and accept bookings first come, first served

B. Allow users to book without checks and fix conflicts later manually

C. Use a single global lock for all bookings to serialize requests

D. Use optimistic locking with retries and real-time slot availability updates

Solution

1. Step 1: Understand scalability needs

   Thousands of users require a scalable approach that avoids bottlenecks.

2. Step 2: Evaluate locking strategies

   Single global lock serializes all requests causing delays; manual fixes cause poor user experience.

3. Step 3: Choose optimistic locking with retries

   This approach allows concurrent attempts, detects conflicts, retries, and updates availability promptly.

4. Final Answer:

   Use optimistic locking with retries and real-time slot availability updates -> Option D

5. Quick Check:

   Optimistic locking + updates = scalable concurrency [OK]

Hint: Optimistic locking scales better than global locks [OK]

Common Mistakes:

• Using global lock causes slow system
• Ignoring concurrency leads to double bookings
• Manual conflict fixes harm user experience