Spring Boot + Kafka + Camunda 8 Project Example

 Modern microservices architectures rely heavily on event-driven communication. In this article, we will build a real example project combining:

• Spring Boot

• Apache Kafka

• Camunda 8

This project demonstrates how to:

• Start a workflow from a Kafka event

• Publish Kafka events from Camunda

• Handle asynchronous orchestration

• Maintain clean separation of concerns

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🎯 Use Case: Order Processing System

Scenario:

1. An Order Service publishes an event to Kafka.

2. A Kafka Consumer receives the event.

3. Camunda 8 starts a workflow.

4. The workflow triggers a Payment Service.

5. Payment result is published back to Kafka.

6. Camunda correlates the message and completes the process.

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🏗 Architecture Overview

Components:

• Spring Boot App

• Kafka Broker

• Camunda 8 (Zeebe)

• Payment Worker

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🛠 Step 1: Project Setup

Create Spring Boot project with:

Dependencies:

• Spring Web

• Spring Kafka

• Camunda Zeebe Client

• Lombok

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📦 Maven Dependencies

<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>zeebe-client-java</artifactId>
  <version>8.x.x</version>
</dependency>

<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
</dependency>

---

🚀 Step 2: Start Camunda 8 (Local)

Use Docker:

docker compose up

Or connect to Camunda SaaS.

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📨 Step 3: Kafka Producer (Order Event)

@Service
@RequiredArgsConstructor
public class OrderProducer {

    private final KafkaTemplate<String, String> kafkaTemplate;

    public void sendOrder(String orderJson) {
        kafkaTemplate.send("order-created", orderJson);
    }
}

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📥 Step 4: Kafka Consumer → Start Camunda Process

@KafkaListener(topics = "order-created")
public void consume(String message) {

    zeebeClient.newCreateInstanceCommand()
        .bpmnProcessId("order-process")
        .latestVersion()
        .variables(message)
        .send()
        .join();
}

This starts the workflow.

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📊 Step 5: BPMN Model

Basic BPMN Flow:

Service Task type: process-payment

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🔄 Step 6: Job Worker → Publish Payment Event

@JobWorker(type = "process-payment")
public void processPayment(ActivatedJob job) {

    kafkaTemplate.send("payment-request", job.getVariables());

    jobClient.newCompleteCommand(job.getKey())
        .send()
        .join();
}

---

🔔 Step 7: Payment Service → Publish Result

@KafkaListener(topics = "payment-request")
public void processPayment(String message) {

    kafkaTemplate.send("payment-completed", message);
}

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🔗 Step 8: Kafka → Correlate Message to Camunda

@KafkaListener(topics = "payment-completed")
public void correlate(String message) {

    zeebeClient.newPublishMessageCommand()
        .messageName("PaymentCompleted")
        .correlationKey(extractOrderId(message))
        .variables(message)
        .send()
        .join();
}

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⚠ Important Production Considerations

1️⃣ Idempotency

Kafka may deliver duplicates.
Always ensure process instances are unique by business key.

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2️⃣ Retry Strategy

Use:

• Zeebe retry mechanism

• Kafka retry topics

• Dead letter queue

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3️⃣ Error Handling

Use BPMN:

• Boundary error events

• Incident monitoring

---

4️⃣ Monitoring

Monitor:

• Kafka lag

• Zeebe backpressure

• Job failure rate

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🧠 Why This Architecture Works

• Kafka handles high-volume events.

• Camunda handles business orchestration.

• Spring Boot keeps services modular.

• Each component scales independently.

This is a clean enterprise-grade pattern.

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📌 Final Thoughts

This example shows how to combine:

• Event streaming (Kafka)

• Workflow orchestration (Camunda 8)

• Business logic (Spring Boot)

This architecture is widely used in:

• FinTech

• E-commerce

• Logistics

• Enterprise SaaS

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