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Event Sourcing Pattern in Microservices (With Real-World Example)
Learn how the Event Sourcing pattern works in microservices. Understand how to store state changes as events, ensure data consistency, and use Kafka or EventStore for implementation.
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🚀 Introduction: What is Event Sourcing in Microservices?
In traditional database systems, when an entity is updated, the old data is overwritten. However, in distributed microservices, this approach leads to:
✔ Data inconsistency across multiple services
✔ Lack of historical data tracking
✔ Challenges in debugging and auditing
✅ Solution: The Event Sourcing Pattern
Instead of storing only the latest state, Event Sourcing stores all changes as a sequence of immutable events.
✔ Each event represents a state change (e.g., OrderCreated, OrderUpdated, OrderCancelled).
✔ The current state is derived by replaying all past events.
✔ This allows full history tracking and easy recovery of previous states.
1️⃣ Real-World Use Case: How Banks Use Event Sourcing
Imagine you’re managing bank transactions.
✔ When you deposit money, a record is updated.
✔ When you withdraw money, another record is updated.
✔ Over time, you lose historical records of each change.
Problem:
If a failure happens, there is no way to rebuild past transactions.
Solution: Event Sourcing
✅ Instead of storing just the current balance, store each transaction as an event.
📌 Example of Events:
1. DEPOSIT: +₹500
2. WITHDRAW: -₹200
3. TRANSFER: -₹100
