🧵 Saga Pattern in Microservices: Orchestration vs Choreography

In a distributed microservices architecture, managing data consistency across services without using distributed transactions (which are fragile and complex) is a challenge. This is where the Saga Pattern comes into play.

In this blog, we’ll explore:

• What is the Saga Pattern?
• The two types: Choreography and Orchestration
• Real-world analogies
• Use cases, pros/cons
• Code and tools you can use

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💡 What is the Saga Pattern?

A Saga is a sequence of local transactions in each microservice, where each step triggers the next one. If something goes wrong, compensating transactions roll back the work done by previous steps.

It avoids 2-phase commits (2PC) and is asynchronous and event-driven.

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🧭 Two Types of Saga Patterns

Aspect	Choreography	Orchestration
Coordination	Distributed (each service listens)	Centralized (one service coordinates)
Communication	Events (event bus)	Commands/Events (often HTTP or messages)
Coupling	Loose	Tighter (central service knows others)
Complexity	Hidden (in event chains)	Visible (central logic)
Debugging	Harder (no single control flow)	Easier (centralized logic)

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1️⃣ Choreography Saga

📦 How It Works:

Each microservice emits an event after completing its task. Other services listen for events they care about and react accordingly.

🔁 Example: Order Fulfillment (Choreography)

1. Order Service emits OrderCreated
2. Payment Service listens → processes payment → emits PaymentCompleted
3. Inventory Service listens → reserves stock → emits StockReserved
4. Shipping Service listens → ships order

[Order Service] 
     │
     └── emits → OrderCreated
                  ↓
            [Event Bus]
                  ↓
[Payment Service] listens to OrderCreated
     │
     └── emits → PaymentCompleted
                  ↓
            [Event Bus]
                  ↓
[Inventory Service] listens to PaymentCompleted
     │
     └── emits → InventoryReserved
                  ↓
            [Event Bus]
                  ↓
[Shipping Service] listens to InventoryReserved
     │
     └── emits → OrderShipped

✅ Pros:

• Fully decentralized
• Scales well
• No single point of failure

❌ Cons:

• Harder to understand the whole flow
• Event storming can lead to complexity
• Difficult to debug/troubleshoot

🛠️ Tools:

• Kafka, RabbitMQ, AWS SNS/SQS, NATS

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2️⃣ Orchestration Saga

🧠 How It Works:

A central orchestrator service controls the entire saga. It sends commands to services and awaits replies or emits events accordingly.

🔁 Example: Order Fulfillment (Orchestration)

1. Order Service sends StartOrderSaga to Saga Orchestrator
2. Orchestrator → calls Payment Service via command (e.g., REST or Kafka)
3. On success → orchestrator calls Inventory Service
4. On success → orchestrator calls Shipping Service
5. On failure → orchestrator triggers compensating actions

[Order Service]
     │
     └── calls → [Saga Orchestrator]
                    ↓
         ┌────> [Payment Service] — emits → PaymentCompleted
         │
         ├────> [Inventory Service] — emits → InventoryReserved
         │
         └────> [Shipping Service] — emits → OrderShipped

✅ Pros:

• Clear control flow
• Easier to debug
• Business logic is centralized

❌ Cons:

• Orchestrator becomes a single point of failure
• More coupling
• Can turn into a God service if not modularized

🛠️ Tools:

• Camunda, Netflix Conductor, Axon, Temporal, or build-your-own with Spring Boot + Kafka

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🤔 When to Use What?

Use Case	Recommended Saga Type
Small services, loosely coupled	Choreography
Complex workflows, need for audit/debugging	Orchestration
Decentralized teams	Choreography
Complex compensating logic	Orchestration

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🧪 Bonus: Compensating Transactions

In either style, if a step fails, you must run compensating transactions to undo the work.

Example: If PaymentCompleted → but StockReserved fails → emit PaymentRefunded or call refund logic.

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🛠 Sample Technologies to Use

Task	Tools
Event Bus	Kafka, RabbitMQ, NATS, SNS/SQS
Saga Orchestrator	Temporal, Camunda, Conductor, Axon
Code Frameworks	Spring Boot, Micronaut, NestJS
Observability	Zipkin, Jaeger, OpenTelemetry

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📘 Final Thoughts

Both Choreography and Orchestration are valid saga implementations. Choosing one depends on:

• Your team size and autonomy
• Workflow complexity
• Operational maturity
• Failure handling needs

👉 For smaller, loosely coupled microservices: Choreography is cleaner
👉 For large workflows with rollback needs: Orchestration is safer

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📚 References:

• Chris Richardson’s Saga Pattern
• Camunda Saga Example
• Temporal Docs

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