Saga Pattern

The database per service pattern creates a need for this pattern. The Saga pattern is one in which the steps of a transaction are chronicled according to a set of predefined actions. This chronicle is called a saga. As each step in a transaction is executed, a controller service compares the result of the step against the saga definition. If a step is executed successfully, the next step in the saga is executed. Should a step fail, all the steps defined in the saga are set back to the last known good state.

The Saga pattern is well-suited to transactions that execute over various independent, loosely coupled services in which each service is hosted at a separate location.

Pros

• Makes transaction management in a loosely coupled, message-driven environment possible.
• It enables an application to maintain data consistency across multiple services without using distributed transactions

Cons

• Can be complex to manage, particularly if a transaction has a large number of steps and the environment is asynchronous.
• Requires a good deal of programming, particularly to support rollback in an asynchronous, message-driven environment.
• The programming model is more complex. For example, a developer must design compensating transactions that explicitly undo changes made earlier in a saga.

Specific Use cases

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

Ex 1: 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

Ex 2: 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

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.

Conclusion

Handling a transaction that occurs over a large number of loosely coupled or independent services is a difficult undertaking. It’s even more difficult when the transaction occurs in systems that use asynchronous communication. The Saga pattern addresses the issues head-on.

Basically, the pattern describes how a transaction is supposed to go. A controller will execute these steps among a variety of services. Should a step fail, the controller will restore all the services affected by the transaction back to the last known good state.

The Saga pattern can be difficult to implement, particularly in an asynchronous environment. But the safety it provides makes it worth the efforts required to implement the pattern.