Skip to content

Demo to show how Apache Kafka can be used for communication between microservices

License

Notifications You must be signed in to change notification settings

NickEm/microservice-kafka

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

63 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Microservice Kafka Sample

Deutsche Anleitung zum Starten des Beispiels

This is a sample to show how Kafka can be used for the communication between microservices.

The project creates Docker containers.

It uses three microservices:

  • Order to create orders. This services sends messages to Kafka. It uses the KafkaTemplate.
  • Shipment receives the orders and extract the information needed to ship the items.
  • Invoicing receives the messages, too. It extracts all information to send out an invoice. It uses @KafkaListener just like Shipment.

This is done using a topic order. It has five partitions. Shipment and invoicing each have a separate consumer group. So multiple instances of shipment and invoicing can be run. Each instance would get specific events.

Technologies

  • Spring Boot
  • Spring Kafka
  • Apache httpd
  • Kafka
  • Zookeeper
  • Postgres
  • Docker Compose to link the containers.

How To Run

See How to run for details.

Once you create an order in the order application, after a while the invoice and the shipment should be shown in the other applications.

Remarks on the Code

The microservices are:

The data of an order is copied - including the data of the customer and the items. So if a customer or item changes in the order system this does not influence existing shipments and invoices. It would be odd if a change to a price would also change existing invoices. Also only the information needed for the shipment and the invoice are copied over to the other systems.

The Order microservice uses Spring's KafkaTemplate to send message while the other two microservices use the annotation @KafkaListener on the methods that should be called if a new record comes in. All records are put in the order topic. It has five partitions to allow for scalability.

For tests an embedded Kafka server is used. A @ClassRule starts it. And a method annotated with @BeforeClass configures Spring Kafka to use the embedded Kafka server.

The orders are serialized as JSON. So the Order object of the order microservice is serialized as a JSON data structure. The other two microservices just read the data they need for shipping and invoicing. So the invoicing microservices reads the Invoiceobject and the delivery microservice the Deliveryobject. This avoids code dependencies between the microservices. Order contains all the data for Invoice as well as Delivery. JSON serialization is flexible. So when an Order is deserialized into Invoice and Delivery just the needed data is read. The additional data is just ignored.

There are three Docker container for the microservices. The other Docker containers are for Apache httpd, Kafka, Zookeeper and Postgres.

Incoming http request are handled by the Apache httpd server. It is available at port 8080 of the Docker host e.g. http://localhost:8080. HTTP requests are forwarded to the microservices. Kafka is used for the communication between the microservices. Kafka needs Zookeeper to coordinate instances. Postgres is used by all microservices to store data. Each microservices uses its own database in the Postgres instance so they are decoupled in that regard.

You can scale the listener with e.g. docker-compose scale shipping=2. The logs (docker logs mskafka_shipping_1) will show which partitions the instances listen to and which records they handle.

You can also start a shell on the Kafka server docker exec -it mskafka_kafka_1 /bin/sh and then take a look at the records in the topic using kafka-console-consumer.sh --bootstrap-server kafka:9092 --topic order --from-beginning.

About

Demo to show how Apache Kafka can be used for communication between microservices

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Java 76.9%
  • HTML 21.2%
  • Dockerfile 1.5%
  • Shell 0.4%