shohelasad/messenger

Take home task

Approach

• Implement a Spring Boot REST API to handle user creation and message sending functionalities.
• Incorporate a PostgreSQL database system to store messages persistently.
• Integrate Apache Kafka into the system to facilitate message communication between users. Configure Apache Kafka with partitions and replicas for scalability and fault tolerance.
• Enable partitioning to maintain the order of messages. The producer service generates a partition number using the hash code of the sender ID and receiver ID, ensuring that messages are distributed across partitions effectively.
• Implement a consumer service to listen for messages from the Kafka topic and deliver them to the corresponding users.
• Integrate WebSocket functionality into the consumer service to enable real-time message delivery to users.
• To scale the application further, additional consumers can be added, each assigned to handle messages from specific partitions, ensuring efficient processing and load balancing.

Prerequisites

• Docker 19.03.x (for production level readiness)
• Docker Compose 1.25.x
• Maven 3

Used Technologies

• Spring Boot 3
• Spring Data
• Lombok
• Actuator
• Postgresql
• Apache Kafka
• Websocket

How to run

Package application as a JAR file

mvn clean install -DskipTests

Run Kafka with Zookeeper and Postgresql

docker-compose up -d

Run Spring Boot application

mvn spring-boot:run

Or, run as Java -jar

java -jar target/messenger-0.0.1-SNAPSHOT.jar