Spring Boot + Camunda 8 Integration Example

 Integrating Spring Boot with Camunda 8 allows developers to build scalable, cloud-native workflow applications where business processes (BPMN) are executed by external workers written in Java. In this blog, we’ll walk through a simple end-to-end integration example using Camunda 8, Zeebe, and Spring Boot.

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🔹 1. What Changes in Camunda 8?

Unlike Camunda 7, Camunda 8 follows a decoupled architecture:

• BPMN runs in the Zeebe engine

• Business logic runs in external Job Workers

• Spring Boot apps connect via the Zeebe client

• Communication is event-driven and asynchronous

👉 There is no embedded engine inside Spring Boot in Camunda 8.

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🔹 2. Architecture Overview

Flow:

1. BPMN process deployed to Camunda 8

2. Service Task creates a Job (with a type)

3. Spring Boot Job Worker subscribes to that type

4. Worker executes logic and updates process variables

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🔹 3. Prerequisites

• Java 17+

• Spring Boot 3+

• Camunda 8 (Self-Managed or SaaS)

• Camunda Modeler

• Maven

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🔹 4. Maven Dependency

Add the Camunda 8 Spring Boot starter:

<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>spring-boot-starter-camunda</artifactId>
</dependency>

This enables:

• Zeebe client

• @JobWorker annotation

• BPMN deployment support

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🔹 5. Spring Boot Configuration

Self-Managed Camunda 8 (application.yaml)

camunda:
  client:
    mode: self-managed
    zeebe:
      gateway-address: 127.0.0.1:26500
    auth:
      enabled: false

👉 For Camunda 8 SaaS, OAuth credentials are required instead.

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🔹 6. BPMN Process Configuration

Create a simple BPMN process in Camunda Modeler:

• Add a Service Task

• Implementation: Job Worker

• Type: order-worker

• Retries: 3

📌 The job type must match the Java worker.

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🔹 7. Spring Boot Job Worker Implementation

Example: Order Processing Worker

package com.example.worker;

import io.camunda.zeebe.client.api.response.ActivatedJob;
import io.camunda.zeebe.spring.client.annotation.JobWorker;
import org.springframework.stereotype.Component;

import java.util.HashMap;
import java.util.Map;

@Component
public class OrderWorker {

  @JobWorker(type = "order-worker", autoComplete = true)
  public Map<String, Object> handle(final ActivatedJob job) {

    Map<String, Object> vars = job.getVariablesAsMap();

    String orderId = (String) vars.get("orderId");
    Double amount = ((Number) vars.get("amount")).doubleValue();

    // Business logic
    String status = amount > 1000 ? "APPROVED" : "REVIEW";

    Map<String, Object> output = new HashMap<>();
    output.put("orderStatus", status);
    output.put("processedOrderId", orderId);

    return output;
  }
}

✅ Returning a map automatically updates workflow variables.

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🔹 8. Error Handling & Retries

Automatic retry (exception-based)

if (amount == null) {
  throw new RuntimeException("Amount is missing");
}

• Retries decrease automatically

• Incident appears in Operate when retries reach zero

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Manual control (autoComplete = false)

@JobWorker(type = "order-worker", autoComplete = false)
public void handle(ActivatedJob job) {

  try {
    Map<String, Object> out = Map.of("orderStatus", "APPROVED");

    job.getClient().newCompleteCommand(job.getKey())
        .variables(out)
        .send()
        .join();

  } catch (Exception e) {
    job.getClient().newFailCommand(job.getKey())
        .retries(job.getRetries() - 1)
        .errorMessage(e.getMessage())
        .send()
        .join();
  }
}

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🔹 9. Running the Example

1. Start Camunda 8 (Docker Compose)

2. Deploy BPMN from Modeler

3. Start a process instance with variables:

{
  "orderId": "ORD-101",
  "amount": 1500
}

4. Run Spring Boot application

5. Verify execution in Operate

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🔹 10. Common Integration Issues

❌ Worker not triggered:

• Job type mismatch

• Wrong gateway address

• Worker app not running

• Missing variables

❌ Serialization issues:

• Use JSON-friendly data

• Avoid Java object serialization

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✅ Conclusion

Integrating Spring Boot with Camunda 8 enables developers to build modern, scalable workflow systems where processes and business logic are cleanly separated. By using Job Workers, applications become more resilient, cloud-ready, and easier to maintain.

This architecture is ideal for microservices, event-driven systems, and enterprise-grade process automation.

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