Pattern: Saga

pattern transaction management sagas service collaboration implementing commands

Context

You have applied the Database per Service pattern. Each service has its own database. Some business transactions, however, span multiple service so you need a mechanism to implement transactions that span services. For example, let’s imagine that you are building an e-commerce store where customers have a credit limit. The application must ensure that a new order will not exceed the customer’s credit limit. Since Orders and Customers are in different databases owned by different services the application cannot simply use a local ACID transaction.

Problem

How to implement transactions that span services?

Forces

• 2PC is not an option

Solution

Implement each business transaction that spans multiple services as a saga. A saga is a sequence of local transactions. Each local transaction updates the database and publishes a message or event to trigger the next local transaction in the saga. If a local transaction fails because it violates a business rule then the saga executes a series of compensating transactions that undo the changes that were made by the preceding local transactions.

There are two ways of coordination sagas:

• Choreography - each local transaction publishes domain events that trigger local transactions in other services
• Orchestration - an orchestrator (object) tells the participants what local transactions to execute

Example: Choreography-based saga

An e-commerce application that uses this approach would create an order using a choreography-based saga that consists of the following steps:

1. The Order Service receives the POST /orders request and creates an Order in a PENDING state
2. It then emits an Order Created event
3. The Customer Service’s event handler attempts to reserve credit
4. It then emits an event indicating the outcome
5. The OrderService’s event handler either approves or rejects the Order

Take a tour of an example saga

Example: Orchestration-based saga

An e-commerce application that uses this approach would create an order using an orchestration-based saga that consists of the following steps:

1. The Order Service receives the POST /orders request and creates the Create Order saga orchestrator
2. The saga orchestrator creates an Order in the PENDING state
3. It then sends a Reserve Credit command to the Customer Service
4. The Customer Service attempts to reserve credit
5. It then sends back a reply message indicating the outcome
6. The saga orchestrator either approves or rejects the Order

Take a tour of an example saga

Resulting context

This pattern has the following benefits:

• It enables an application to maintain data consistency across multiple services without using distributed transactions

This solution has the following drawbacks:

• Lack of automatic rollback - a developer must design compensating transactions that explicitly undo changes made earlier in a saga rather than relying on the automatic rollback feature of ACID transactions

• Lack of isolation (the “I” in ACID) - the lack of isolation means that there’s risk that the concurrent execution of multiple sagas and transactions can use data anomalies. consequently, a saga developer must typical use countermeasures, which are design techniques that implement isolation. Moreover, careful analysis is needed to select and correctly implement the countermeasures. See Chapter 4/section 4.3 of my book Microservices Patterns for more information.

There are also the following issues to address:

• In order to be reliable, a service must atomically update its database and publish a message/event. It cannot use the traditional mechanism of a distributed transaction that spans the database and the message broker. Instead, it must use one of the patterns listed below.

• A client that initiates the saga, which an asynchronous flow, using a synchronous request (e.g. HTTP POST /orders) needs to be able to determine its outcome. There are several options, each with different trade-offs:

  • The service sends back a response once the saga completes, e.g. once it receives an OrderApproved or OrderRejected event.
  • The service sends back a response (e.g. containing the orderID) after initiating the saga and the client periodically polls (e.g. GET /orders/{orderID}) to determine the outcome
  • The service sends back a response (e.g. containing the orderID) after initiating the saga, and then sends an event (e.g. websocket, web hook, etc) to the client once the saga completes.

Related patterns

• The Database per Service pattern creates the need for this pattern
• The following patterns are ways to atomically update state and publish messages/events:
  • Event sourcing
  • Transactional Outbox
• A choreography-based saga can publish events using Aggregates and Domain Events
• The Command-side replica is an alternative pattern, which can replace saga step that query data

Learn more

• My book Microservices patterns describes this pattern in a lot more detail. The book’s example application implements orchestration-based sagas using the Eventuate Tram Sagas framework
• Take a look at my self-paced, online bootcamp that teaches you how to use the Saga, API Composition, and CQRS patterns to design operations that span multiple services.
• Read these articles about the Saga pattern
• My presentations on sagas and asynchronous microservices.

Example code

The following examples implement the customers and orders example in different ways:

• Choreography-based saga where the services publish domain events using the Eventuate Tram framework
• Orchestration-based saga where the Order Service uses a saga orchestrator implemented using the Eventuate Tram Sagas framework
• Choreography and event sourcing-based saga where the services publish domain events using the Eventuate event sourcing framework