Why Event sourcing in HLD? - Purpose & Use Cases

The Big Idea

What if you could rewind time and see every step your system took to reach its current state?

The Scenario

Imagine you run a busy store and keep track of every sale by writing it down on paper. When you want to know how much money you made, you have to add up all those notes manually.

The Problem

This manual way is slow and mistakes happen easily. If you lose a paper or forget to write something, your records are wrong. Also, fixing errors means digging through piles of notes, which is frustrating and time-consuming.

The Solution

Event sourcing changes this by saving every action (or event) as it happens in a clear, ordered list. Instead of just the final result, you keep the full story. This makes it easy to check, fix, or replay events to understand exactly what happened.

Before vs After

✗ Before

balance = 0
for sale in sales:
    balance += sale.amount

✓ After

events = []
for event in event_stream:
    apply(event, state)

What It Enables

With event sourcing, you can rebuild your system's state anytime and track every change, making your data reliable and easy to audit.

Real Life Example

Think of a bank that records every deposit and withdrawal as an event. If there's a dispute, they can replay all events to see exactly how the balance changed over time.

Key Takeaways

Manual record-keeping is slow and error-prone.

Event sourcing stores every change as an event, preserving history.

This approach improves reliability, debugging, and auditing.

Practice

1. What is the main idea behind event sourcing in system design?

easy

A. Store all changes as a sequence of events to reconstruct state

B. Store only the latest snapshot of data for quick access

C. Use events only for logging errors in the system

D. Send events to users as notifications without storing them

Solution

1. Step 1: Understand event sourcing concept

   Event sourcing means saving every change as an event, not just the final data.

2. Step 2: Identify how state is managed

   The current state is rebuilt by applying all stored events in order, not by snapshots alone.

3. Final Answer:

   Store all changes as a sequence of events to reconstruct state -> Option A

4. Quick Check:

   Event sourcing = store events to rebuild state [OK]

Hint: Event sourcing saves changes as events, not just snapshots [OK]

Common Mistakes:

• Confusing event sourcing with snapshot-only storage
• Thinking events are only for error logs
• Believing events are just notifications

2. Which of the following is the correct way to represent an event in an event sourcing system?

easy

A. { "eventType": "UserCreated", "timestamp": "2024-06-01T12:00:00Z", "data": { "userId": 123 } }

B. [ "UserCreated", 123, "2024-06-01" ]

C. "UserCreated: userId=123 at 2024-06-01"

D. CREATE USER 123 AT 2024-06-01

Solution

1. Step 1: Identify proper event structure

   Events should be structured data with type, timestamp, and data fields for clarity and processing.

2. Step 2: Compare options

   { "eventType": "UserCreated", "timestamp": "2024-06-01T12:00:00Z", "data": { "userId": 123 } } uses a clear JSON object with eventType, timestamp, and data, which is standard practice.

3. Final Answer:

   { "eventType": "UserCreated", "timestamp": "2024-06-01T12:00:00Z", "data": { "userId": 123 } } -> Option A

4. Quick Check:

   Event = structured JSON with type and data [OK]

Hint: Events are structured objects with type, timestamp, and data [OK]

Common Mistakes:

• Using unstructured strings for events
• Confusing event data with SQL commands
• Using arrays without keys for event details

3. Given these events in order:
[{"eventType":"AddItem","data":{"itemId":1}}, {"eventType":"AddItem","data":{"itemId":2}}, {"eventType":"RemoveItem","data":{"itemId":1}}]
What is the final state of the item list?

medium

A. [1, 2]

B. [2]

C. [1]

D. []

Solution

1. Step 1: Apply events in order to the item list

   Start with empty list. Add item 1 -> [1]. Add item 2 -> [1, 2]. Remove item 1 -> [2].

2. Step 2: Determine final list content

   After all events, only item 2 remains in the list.

3. Final Answer:

   [2] -> Option B

4. Quick Check:

   Apply events sequentially = final list [2] [OK]

Hint: Apply events one by one to get final state [OK]

Common Mistakes:

• Ignoring remove event
• Applying events out of order
• Assuming all added items remain

4. You notice that replaying all events to rebuild state is very slow. What is a common solution to improve performance in event sourcing?

medium

A. Store only the latest event for each entity

B. Delete old events after 1 day to reduce size

C. Use snapshots to save intermediate states periodically

D. Switch to storing only current state, no events

Solution

1. Step 1: Identify performance issue cause

   Replaying all events from the start can be slow as event count grows.

2. Step 2: Choose common optimization

   Snapshots save the full state at points in time, so replay starts from snapshot, reducing replay time.

3. Final Answer:

   Use snapshots to save intermediate states periodically -> Option C

4. Quick Check:

   Snapshots speed up event replay [OK]

Hint: Use snapshots to avoid replaying all events every time [OK]

Common Mistakes:

• Deleting events breaks history and audit
• Keeping only latest event loses full history
• Abandoning events loses event sourcing benefits

5. You design an event sourcing system for a bank. Which approach best ensures data consistency and auditability when multiple transactions happen concurrently?

hard

A. Process events in random order to improve throughput

B. Allow events to overwrite each other without checks for speed

C. Store only final balances without event history to simplify design

D. Use optimistic concurrency control with event versioning and conflict detection

Solution

1. Step 1: Understand concurrency challenges in event sourcing

   Concurrent transactions can cause conflicts if events overwrite each other or are applied out of order.

2. Step 2: Choose method to maintain consistency and audit

   Optimistic concurrency control uses event version numbers to detect conflicts and prevent overwrites, preserving history and correctness.

3. Final Answer:

   Use optimistic concurrency control with event versioning and conflict detection -> Option D

4. Quick Check:

   Optimistic concurrency = safe concurrent event handling [OK]

Hint: Use versioning to detect conflicts in concurrent events [OK]

Common Mistakes:

• Ignoring conflicts causes data corruption
• Dropping event history loses audit trail
• Processing events unordered breaks state correctness