In this post, we will discuss how we can build microservices with event-driven architecture. As part of the post, I will also show an example of an event-driven microservice. If you don’t know what a microservice is, you can start with my primer here.
Microservices – Event-Driven Architecture
Traditionally, we would use a REST Based Microservice. In this microservice, a client would request data and then the server would respond with the data. But there were disadvantages in that client has to wait for the server to respond. A server can be down or serving other requests, in-process of delaying the response to the current client requests.
In short, when a system becomes slow because of synchronized connections, we can use event-driven architecture to make the system asynchronous.
Event-Drive microservices use an eventually consistent approach. Each service publishes event data whenever there is an update or transaction. Other services subscribe to this service publishing events. When these subscribed services receive an event, they update their data.
A simple example of this approach: When a customer redeems a gift card, a single redemption event is created and consumed by different services.
- A Reward Service that can write a redemption record in the database
- A Customer receiving getting an item bought through a gift card
- A Partner Service verifying the gift card and allowing the redemption and accordingly processing of the item that the customer bought.
Event-Driven architecture is either through queues or the pub-sub model. In Pub/Sub model, a service publishes the event, and subscribed services consume that event. It is not much different from what queues and topics do.
Benefits of Event-Driven Architecture
- Loose Coupling – Services don’t need to depend on other services. Considering the architecture is reactive, services can be independent of each other.
- Asynchronous – A publishing service will publish the event. A subscribing service can consume the event whenever it is ready to consume. The major advantage of asynchronous architecture is that services don’t block resources.
- Scaling – Since the services are independent, most services perform a single task. It becomes easier to scale as well to find out bottle-neck.
Drawbacks of Event-Driven Architecture
Every design is a trade-off. We do not have a perfect design in distributed systems. With event-driven architecture, one can easily over-engineer the solution by separating concerns.
Event-Driven architecture needs upfront investment. Since the data is not necessarily available immediately, it can cause some concerns with transactions. Eventual consistency can be hard to investigate if there are issues with data. There can be possibilities of duplicate events, resulting in duplicate data. Event-driven models do not support ACID transactions.
Framework for Architecture
Irrespective of those drawbacks, event-driven architecture is fast and delivers results successfully. So the next question arises what framework to choose to build this architecture. Currently, there are two choices
- Message Processing
- Stream Processing
Message Processing
In message processing, a service creates a message and sends it to the destination. A subscribing service picks up the message from that destination. In AWS, we use SNS (Simple Notification Service) and SQS (Simple Queue Service). A service sends a message to a topic and a queue subscribing to that topic picks up that message and processes it further.
SNS and SQS are not the only frameworks out there. Message queues use a store and forward system of brokers where events travel from broker to broker. ActiveMQ and RabbitMQ are the other two examples of message queues
Stream Processing
In stream processing, a service sends an event and subscribed service picks up that event. Nevertheless, events are not for a particular target.
Usually, a producer of events emits events and can store them in storage. A consumer of events can consume those events from the data storage. The most popular framework for stream processing is Kafka. Basically, it follows a pub-sub model.
Above all, stream processors (like Kafka) offer the durability of data. Data is not lost and if the system goes offline, it can reproduce the history of events.
Demo of Event-Driven Architecture Based Microservice
As part of this demo, we will implement a Spring Boot application along with the ActiveMQ message broker service.
ActiveMQ Messaging Service
ActiveMQ is an open-source message broker. Presently, it supports clients written in Java, Python, .Net, C++, and more.
Download the ActiveMQ from here. Once, you extract the downloaded folder on your machine, you can go to bin directory to start the ActiveMQ server with a command activemq.bat start. This will start the ActiveMQ server at http://localhost:8161.
Sender Application with Spring Boot
Now, let’s create a Message Sender application using Spring Boot. We will need the following dependencies
dependencies {
implementation 'org.springframework.boot:spring-boot-starter-activemq'
implementation 'org.springframework.boot:spring-boot-starter-web'
testImplementation 'org.springframework.boot:spring-boot-starter-test'
}
We will add JMS Configuration to create an ActiveMQ Queue.
@Configuration
public class JmsConfig
{
@Bean
public Queue queue()
{
return new ActiveMQQueue("demo-queue");
}
}
This creates a bean for our queue demo-queue. To send message to this queue through our sender application, we will create a REST API as follows:
@RestController
@RequestMapping("/v1/betterjavacode/api")
public class MessageController
{
@Autowired
private Queue queue;
@Autowired
private JmsTemplate jmsTemplate;
@GetMapping("/message/")
public ResponseEntity sendMessage(@RequestBody String message)
{
jmsTemplate.convertAndSend(queue, message);
return new ResponseEntity(message, HttpStatus.OK);
}
}
Subsequently, we have injected queue and jmsTemplate beans in our RestController so we can send the message.
On the other hand, we will also have a receiver application which will be a destination service or consumer service consuming the message from the sender application.
Create a message consumer class in our receiver application
@Component
@EnableJms
public class MessageConsumer
{
private final Logger logger = LoggerFactory.getLogger(MessageConsumer.class);
@JmsListener(destination = "demo-queue")
public void receiveMessage(String message)
{
// TO-DO
logger.info("Received a message = {}", message);
}
}
The annotation of @JmsListener with destination makes the application to listen to that queue. @EnableJms enables the annotation @JmsListener.
We still need to add ActiveMQ properties so that both applications know where ActiveMQ server is running. So, add the following properties to application.properties
spring.activemq.broker-url=tcp://localhost:61616
spring.activemq.user=admin
spring.activemq.password=admin
Now start both of the Spring Boot applications. Sender Application is running on 8080 and Receiver Application is running on 8081.
Now if we check the logs of receiver application, we will see that it has consumed that message from ActiveMQ queue demo-queue.
We can also see the status of queue in ActiveMQ server.
Here, you can see there have been two messages that the queue has received from the sender and delivered to the consumer. The code for this demo is available on my github repository.
Conclusion
In this post, I discussed Event-Driven architecture for microservices. We also discussed the benefits and drawbacks of this architecture. At last, we showed how we can use ActiveMQ to set up an event-driven architecture-based microservice for asynchronous communication.
On another note, if you still haven’t bought my book for Spring Security, you can buy here OR you can read about it more here.
References
Event-Driven Microservices using ActiveMQ – ActiveMQ