Why Design a notification system in HLD? - Purpose & Use Cases

The Big Idea

What if you could tell millions about your news with just one click, perfectly every time?

The Scenario

Imagine you run a small online store and want to tell your customers about new deals. You try sending emails or messages one by one, copying and pasting each time.

It feels like shouting in a crowded room, hoping the right people hear you.

The Problem

Sending notifications manually is slow and tiring. You might forget someone or send the wrong message. It's hard to keep track of who got what and when.

This causes unhappy customers and lost sales.

The Solution

A notification system automates sending messages to many users at once. It organizes who should get what and when, making sure no one is missed.

This system can send emails, texts, or app alerts quickly and reliably.

Before vs After

✗ Before

for user in users:
    send_email(user.email, 'Sale today!')

✓ After

notification_service.send('Sale today!', users)

What It Enables

With a notification system, you can reach thousands instantly, keeping customers informed and engaged without extra effort.

Real Life Example

Social media apps use notification systems to alert you about likes, comments, or messages right away, so you never miss important updates.

Key Takeaways

Manual notifications are slow and error-prone.

A notification system automates and scales message delivery.

This keeps users informed and improves engagement effortlessly.

Practice

1. Which component in a notification system is responsible for deciding when to send a message to a user?

easy

A. Event processor

B. Notification sender

C. User preference manager

D. Message storage

Solution

1. Step 1: Understand the role of event processor

   The event processor detects events that trigger notifications, deciding when a message should be sent.

2. Step 2: Differentiate from other components

   The notification sender delivers messages, user preference manager stores user choices, and message storage keeps records.

3. Final Answer:

   Event processor -> Option A

4. Quick Check:

   Event detection = Event processor [OK]

Hint: Event timing is handled by the event processor [OK]

Common Mistakes:

• Confusing sender with event detector
• Thinking user preferences trigger events
• Assuming storage decides timing

2. Which data structure is best suited to store user notification preferences for quick lookup?

easy

A. Linked list

B. Hash map

C. Queue

D. Stack

Solution

1. Step 1: Identify quick lookup needs

   User preferences require fast access by user ID or key, so a data structure with O(1) average lookup is ideal.

2. Step 2: Match data structures to lookup speed

   Hash maps provide constant time lookup, unlike linked lists, queues, or stacks which are slower for direct access.

3. Final Answer:

   Hash map -> Option B

4. Quick Check:

   Fast key-value access = Hash map [OK]

Hint: Use hash map for fast user preference lookup [OK]

Common Mistakes:

• Choosing linked list which is slow for lookup
• Confusing queue or stack with lookup structures
• Ignoring key-based access needs

3. Consider this simplified flow: An event triggers a notification, which is stored in a queue before delivery. What happens if the queue is full?

medium

A. Queue automatically expands without limit

B. System crashes due to overflow

C. Notifications are sent immediately bypassing the queue

D. New notifications are dropped or delayed

Solution

1. Step 1: Understand queue capacity limits

   Queues have fixed or limited size; when full, they cannot accept new items immediately.

2. Step 2: Identify common handling of full queues

   Systems usually drop new notifications or delay them until space frees up; automatic unlimited expansion is rare to avoid resource exhaustion.

3. Final Answer:

   New notifications are dropped or delayed -> Option D

4. Quick Check:

   Full queue = drop or delay new notifications [OK]

Hint: Full queue means drop or delay notifications [OK]

Common Mistakes:

• Assuming infinite queue size
• Thinking notifications bypass queue
• Believing system crashes on full queue

4. A notification system sends duplicate messages to users. Which design mistake most likely causes this?

medium

A. Notifications sent synchronously

B. User preferences not stored

C. No deduplication in event processing

D. Using a single message queue

Solution

1. Step 1: Analyze duplicate message causes

   Duplicates often occur if the system processes the same event multiple times without checking if notification was already sent.

2. Step 2: Evaluate other options

   Missing user preferences or synchronous sending do not cause duplicates; a single queue can still handle duplicates if deduplication exists.

3. Final Answer:

   No deduplication in event processing -> Option C

4. Quick Check:

   Duplicates = missing deduplication [OK]

Hint: Duplicates mean missing deduplication step [OK]

Common Mistakes:

• Blaming user preferences for duplicates
• Confusing synchronous sending with duplication
• Assuming single queue causes duplicates

5. You need to design a notification system that supports email, SMS, and push notifications with user preferences and high scalability. Which architecture pattern best fits this requirement?

hard

A. Event-driven microservices with message queues and preference service

B. Batch processing system sending notifications once daily

C. Single database polling for notifications every minute

D. Monolithic application with direct notification calls

Solution

1. Step 1: Identify scalability and multi-channel needs

   Supporting multiple notification types and scaling requires decoupling components and asynchronous processing.

2. Step 2: Match architecture patterns

   Event-driven microservices with message queues allow independent scaling, handle user preferences, and support multiple channels efficiently.

3. Step 3: Eliminate unsuitable options

   Monolithic apps limit scalability; polling causes delays; batch processing is too slow for timely notifications.

4. Final Answer:

   Event-driven microservices with message queues and preference service -> Option A

5. Quick Check:

   Scalable multi-channel = event-driven microservices [OK]

Hint: Use event-driven microservices for scalable multi-channel notifications [OK]

Common Mistakes:

• Choosing monolithic for scalability
• Using batch processing for real-time needs
• Relying on polling causing delays