π§ Why Do We Need the SAGA Pattern?
In modern distributed systems, especially microservices and rich client-side apps, the traditional database transaction (ACID) model doesn't hold up. Here's why we need the SAGA pattern:
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π Ensures eventual consistency across services
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β Handles partial failure gracefully
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π€ Enables complex, multi-step workflows
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β Avoids complexity and tight-coupling of 2-phase commits (2PC)
π What Is the SAGA Pattern?
A SAGA is a sequence of local transactions. Each service updates its data and publishes an event. If a step fails, compensating transactions are triggered to undo the impact of prior actions.
βοΈ Two Main Styles:
| Pattern | Description |
|---|---|
| Orchestration | Centralized controller manages the saga |
| Choreography | Services communicate via events |
π» SAGA in Java (Spring Boot)
ποΈ E-Commerce Checkout Flow
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Create Order
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Reserve Inventory
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Charge Payment
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Initiate Shipping
β If Payment Fails:
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Refund
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Release Inventory
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Cancel Order
β¨ Java Orchestration Example
public class OrderSagaOrchestrator {
public void startSaga(OrderEvent event) {
try {
inventoryService.reserveItem(event.getProductId());
paymentService.charge(event.getUserId(), event.getAmount());
shippingService.shipOrder(event.getOrderId());
} catch (Exception e) {
rollbackSaga(event);
}
}
public void rollbackSaga(OrderEvent event) {
shippingService.cancelShipment(event.getOrderId());
paymentService.refund(event.getUserId(), event.getAmount());
inventoryService.releaseItem(event.getProductId());
orderService.cancelOrder(event.getOrderId());
}
}
π Tools & Frameworks:
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Spring Boot
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Kafka/RabbitMQ
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Axon Framework / Eventuate
βοΈ SAGA in React (redux-saga)
πͺ Multi-Step Login Workflow
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Authenticate User
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Fetch Profile
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Load Preferences
β If Fetch Profile Fails:
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Logout
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Show Error
function* loginSaga(action) {
try {
const token = yield call(loginAPI, action.payload);
yield put({ type: 'LOGIN_SUCCESS', token });
const profile = yield call(fetchProfile, token);
yield put({ type: 'PROFILE_SUCCESS', profile });
const prefs = yield call(fetchPreferences, token);
yield put({ type: 'PREFERENCES_SUCCESS', prefs });
} catch (err) {
yield put({ type: 'LOGIN_FAILURE', error: err.message });
yield call(logoutUser);
yield put({ type: 'SHOW_ERROR', message: 'Login failed' });
}
}
π§ Key Concepts:
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redux-saga = orchestrator
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yield call()= async step -
Rollback = logout/cleanup
π Real-Life Use Cases
Backend:
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Booking systems (flight + hotel)
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Wallet fund transfers
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eCommerce checkouts
Frontend:
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Multi-step login/signup
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Form wizard undo
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Order confirmation with rollback
π Architectural Deep Dive
π¨ Orchestration
ββββββββββββββββββ
β Orchestratorβ
ββββββββββββββββββ
β
ββββββββββββββββββ
β Order Created β
ββββββββββββββββββ
βΌ
Inventory β Payment β Shipping
β β β
Release β Refund β Cancel
π What's Next?
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Event Sourcing
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CQRS (Command Query Responsibility Segregation)
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Outbox Pattern
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Retry Patterns
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Step Functions / State Machines
π Interview Questions
| Question | Tip |
|---|---|
| What is a SAGA pattern? | Explain distributed transaction and compensation |
| Orchestration vs Choreography? | Orchestrator vs Event-based |
| SAGA in React? | Use redux-saga, show generator pattern |
| How to rollback in microservices? | Compensating transaction |
| Why not 2PC? | Not scalable, tight coupling |
π§ Self-Test Questions
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Design a SAGA for flight + hotel combo
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SAGA with Kafka vs SAGA with REST
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Difference: retry vs compensation
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How to ensure idempotency in SAGA?
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Drawbacks of SAGA? Latency, complexity?
π Summary: Backend vs Frontend
| Feature | Java (Spring) | React (redux-saga) |
|---|---|---|
| Purpose | Distributed data consistency | UI flow control |
| Pattern | Event-driven Orchestration | Generator-based orchestration |
| Rollback | Compensating transaction | State rollback/logout |
| Communication | Kafka, REST, RabbitMQ | Redux actions, async calls |
Ready to master distributed consistency like a pro? SAGA is your first step to engineering Olympic-level microservice systems and stateful UI flows!
