Saga
Last updated
Last updated
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.
How to implement transactions that span services?
[[2PC]] is not an option
Implement each business transaction that spans multiple services is 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
An e-commerce application that uses this approach would create an order using a choreography-based saga that consists of the following steps:
The Order Service
receives the POST /orders
request and creates an Order
in a PENDING
state
It then emits an Order Created
event
The Customer Service
's event handler attempts to reserve credit
It then emits an event indicating the outcome
The OrderService
's event handler either approves or rejects the Order
An e-commerce application that uses this approach would create an order using an orchestration-based saga that consists of the following steps:
The Order Service
receives the POST /orders
request and creates the Create Order
saga orchestrator
The saga orchestrator creates an Order
in the PENDING
state
It then sends a Reserve Credit
command to the Customer Service
The Customer Service
attempts to reserve credit
It then sends back a reply message indicating the outcome
The saga orchestrator either approves or rejects the Order
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:
The programming model is more complex. For example, a developer must design compensating transactions that explicitly undo changes made earlier in a saga.
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.
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]]
Read these blog posts on the Saga pattern:
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.
My presentations on sagas and asynchronous microservices.
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