Spring Zeebe

This project allows to leverage Zeebe (the orchestration engine that comes as part of Camunda Platform 8) within your Spring or Spring Boot environment easily. It is basically a wrapper around the Zeebe Java Client.

Examples

There are full examples, including test cases, are available here: Twitter Review example, Process Solution Template. Further, you might want to have a look into the examples/ folder.

Get Started

Create a new Spring Boot project (e.g. using Spring initializr), or open a pre-existing one you already have, or simply fork our Camunda Platform 8 Process Solution Template.

Add Spring Boot Starter to Your Project

Add the following Maven dependency to your Spring Boot Starter project:

<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>spring-zeebe-starter</artifactId>
  <version>8.0.7</version>
</dependency>

Although Spring Zeebe has a transitive dependency to the Zeebe Java Client, you could also add a direct dependency if you need to specify the concrete version in your pom.xml:

<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>zeebe-client-java</artifactId>
  <version>8.0.4</version>
</dependency>

Please note, that starting from spring-zeebe 8.0.2 you need Zeebe >= 8.0.0.

Configuring Camunda Platform 8 SaaS Connection

Connections to the Camunda SaaS can be easily configured, create the following entries in your src/main/resources/application.properties:

zeebe.client.cloud.cluster-id=xxx
zeebe.client.cloud.client-id=xxx
zeebe.client.cloud.client-secret=xxx
zeebe.client.cloud.region=bru-2

You can also configure the connection to a self-managed Zeebe broker:

zeebe.client.broker.gateway-address=127.0.0.1:26500
zeebe.client.security.plaintext=true

Connect to Zeebe

Add the @EnableZeebeClient annotation to your Spring Boot Application:

@SpringBootApplication
@EnableZeebeClient
public class MySpringBootApplication {

Now you can inject the ZeebeClient and work with it, e.g. to create new workflow instances:

@Autowired
private ZeebeClient client;

Deploy Process Models

Use the @ZeebeDeployment annotation:

@SpringBootApplication
@EnableZeebeClient
@ZeebeDeployment(resources = "classpath:demoProcess.bpmn")
public class MySpringBootApplication {

This annotation uses (which internally uses [https://docs.spring.io/spring-framework/docs/current/reference/html/core.html#resources-resourceloader] (the Spring resource loader) mechanism which is pretty powerful and can for example also deploy multiple files at once:

@ZeebeDeployment(resources = {"classpath:demoProcess.bpmn" , "classpath:demoProcess2.bpmn"})

or define wildcard patterns:

@ZeebeDeployment(resources = "classpath*:/bpmn/**/*.bpmn")

Implement Job Worker

@ZeebeWorker(type = "foo")
public void handleJobFoo(final JobClient client, final ActivatedJob job) {
  // do whatever you need to do
  client.newCompleteCommand(job.getKey()) 
     .variables("{\"fooResult\": 1}")
     .send()
     .exceptionally( throwable -> { throw new RuntimeException("Could not complete job " + job, throwable); });
}

Writing test cases

You can startup an in-memory test engine and do assertions by adding this Maven dependency:

<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>spring-zeebe-test</artifactId>
  <version>${spring-zeebe.version}</version>
  <scope>test</scope>
</dependency>

Note that the test engines requires Java version >= 17. If you cannot run on this Java version, you can use Testcontainers instead. Testcontainers require that you have a docker installation locally available on the developer machine. Use this dependency:

<!-- 
  Alternative dependency if you cannot run Java 17, so you will leverage Testcontainer 
  Make sure NOT to have spring-zeebe-test on the classpath in parallel!
-->
<dependency>
  <groupId>io.camunda</groupId>
  <artifactId>spring-zeebe-test-testcontainer</artifactId>
  <version>${spring-zeebe.version}</version>
  <scope>test</scope>
</dependency>

Then you need to startup the test engine in your test case by adding @ZeebeSpringTest

@SpringBootTest
@ZeebeSpringTest
public class TestMyProcess {
  // ...  

An example test case is available here.

Documentation

Workers

Fetch all variables

You can access all variables of a process via the job:

@ZeebeWorker(type = "foo")
public void handleJobFoo(final JobClient client, final ActivatedJob job) {
  String variable1 = (String)job.getVariablesAsMap().get("variable1");
  sysout(variable1);
  // ...
}

Define variables to fetch

You can specify that you only want to fetch some variables (instead of all) when executing a job, which can decrease load and improve performance:

@ZeebeWorker(type = "foo", fetchVariables={"variable1", "variable2"})
public void handleJobFoo(final JobClient client, final ActivatedJob job) {
  String variable1 = (String)job.getVariablesAsMap().get("variable1");
  System.out.println(variable1);
  // ...
}

Using @ZeebeVariable

By using the @ZeebeVariable annotation there is a shortcut to make variable retrieval simpler, including the type cast:

@ZeebeWorker(type = "foo")
public void handleJobFoo(final JobClient client, final ActivatedJob job, @ZeebeVariable String variable1) {
  System.out.println(variable1);
  // ...
}

With @ZeebeVariable or fetchVariables you limit which variables are loaded from the workflow engine. You can also overwrite this and force that all variables are loaded anyway:

@ZeebeWorker(type = "foo", forceFetchAllVariables = true)
public void handleJobFoo(final JobClient client, final ActivatedJob job, @ZeebeVariable String variable1) {
}

Using @ZeebeVariablesAsType

When using autoComplete (see below) you can also use your own class into which the process variables are mapped to (comparable to getVariablesAsType() in the API). Therefore use the @ZeebeVariablesAsType annotation (MyProcessVariables referes to your own class):

@ZeebeWorker(type = "foo", autoComplete = true)
public ProcessVariables handleFoo(@ZeebeVariablesAsType MyProcessVariables variables){
  // do whatever you need to do
  variables.getMyAttribueX();
  variables.setMyAttribueY(42);
  // return variables object if something has changed, so the changes are submitted to Zeebe
  return variables;
}

Completing the job

As a default, your job handler code has to also complete the job, otherwise Zeebe will not know you did your work correctly:

@ZeebeWorker(type = "foo")
public void handleJobFoo(final JobClient client, final ActivatedJob job) {
  // do whatever you need to do
  client.newCompleteCommand(job.getKey()) 
     .send()
     .exceptionally( throwable -> { throw new RuntimeException("Could not complete job " + job, throwable); });
}

Ideally, you don't use blocking behavior like send().join(), as this is a blocking call to wait for the issues command to be executed on the workflow engine. While this is very straightforward to use and produces easy-to-read code, blocking code is limited in terms of scalability.

That's why the worker showed a different pattern:

send().whenComplete((result, exception) -> {})

This registers a callback to be executed if the command on the workflow engine was executed or resulted in an exception. This allows for parallelism. This is discussed in more detail in this blog post about writing good workers for Camunda Cloud.

Auto-completing jobs

To ease things, you can also set autoComplete=true for the worker, than the Spring integration will take care if job completion for you:

@ZeebeWorker(type = "foo", autoComplete = true)
public void handleJobFoo(final ActivatedJob job) {
  // do whatever you need to do
  // but no need to call client.newCompleteCommand()...
}

Note that the code within the handler method needs to be synchronously executed, as the completion will be triggered right after the method has finished.

When using autoComplete you can:

• Return a Map, String, InputStream, or Object, which then will be added to the process variables
• Throw a ZeebeBpmnError which results in a BPMN error being sent to Zeebe
• Throw any other Exception that leads in an failure handed over to Zeebe

@ZeebeWorker(type = "foo", autoComplete = true)
public Map<String, Object> handleJobFoo(final ActivatedJob job) {
  // some work
  if (successful) {
    // some data is returned to be stored as process variable
    return variablesMap;
  } else {
   // problem shall be indicated to the process:
   throw new ZeebeBpmnError("DOESNT_WORK", "This does not work because...");
  }
}

@ZeebeCustomHeaders

In the same manner you can also access the headers using @ZeebeCustomHeaders

@ZeebeWorker(type = "foo", autoComplete = true)
public void handleFoo(final ActivatedJob job, @ZeebeCustomHeaders Map<String, String> headers){
  // do whatever you need to do
} 

Or using both @ZeebeVariablesAsType and @ZeebeCustomHeaders

@ZeebeWorker(type = "foo", autoComplete = true)
public ProcessVariables handleFoo(@ZeebeVariablesAsType ProcessVariables variables, @ZeebeCustomHeaders Map<String, String> headers){
  // do whatever you need to do
  return variables;
}

Throwing ZeebeBpmnError's

Whenever your code hits a problem that should lead to a BPMN error being raised, you can simply throw a ZeebeBpmnError providing the error code used in BPMN:

@ZeebeWorker(type = "foo")
public void handleJobFoo() {
  // some work
  if (!successful) {
   // problem shall be indicated to the process:
   throw new ZeebeBpmnError("DOESNT_WORK", "This does not work because...");
  }
}

Additional Configuration Options

Configuring Self-managed Zeebe Connection

zeebe.client.broker.gateway-address=127.0.0.1:26500
zeebe.client.security.plaintext=true

Configure different cloud environments

If you don't connect to the Camunda SaaS production environment you might have to also adjust these properties:

zeebe.client.cloud.base-url=zeebe.camunda.io
zeebe.client.cloud.port=443
zeebe.client.cloud.auth-url=https://login.cloud.camunda.io/oauth/token

As an alternative you can use the Zeebe Client environment variables.

Default task type

If you build a worker that only serves one thing, it might also be handy to define the worker job type globally - and not in the annotation:

zeebe.client.worker.defaultType=foo

Configure jobs in flight and thread pool

Number of jobs that are polled from the broker to be worked on in this client and thread pool size to handle the jobs:

zeebe.client.worker.max-jobs-active=32
zeebe.client.worker.threads=1

For a full set of configuration options please see ZeebeClientConfigurationProperties.java

Note that we generally do not advise to use a thread pool for workers, but rather implement asynchronous code, see Writing Good Workers.

ObjectMapper customization

If you need to customize the ObjectMapper that the Zeebe client uses to work with variables, you can declare a bean with type io.camunda.zeebe.client.api.JsonMapper like this:

@Configuration
class MyConfiguration {
  @Bean
  public JsonMapper jsonMapper() {
    new ZeebeObjectMapper().enable(DeserializationFeature.ACCEPT_EMPTY_ARRAY_AS_NULL_OBJECT);
  }
}

Code of Conduct

This project adheres to the Contributor Covenant Code of Conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to [email protected].