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.
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.
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 the following Maven dependency to your Spring Boot Starter project:
<dependency>
<groupId>io.camunda</groupId>
<artifactId>spring-zeebe-starter</artifactId>
<version>8.0.9</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.
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
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;
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")
@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); });
}
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>
Using Maven profiles you can also switch the test dependencies based on the available Java version.
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.
You can configure the job type via the ZeebeWorker
annotation:
@ZeebeWorker(type = "foo")
public void handleJobFoo() {
// handles jobs of type 'foo'
}
If you don't specify the type
the method name is used as default:
@ZeebeWorker
public void foo() {
// handles jobs of type 'foo'
}
As a third possibility, you can set a default job type:
zeebe.client.worker.default-type=foo
This is used for all workers that do not set a task type via the annoation.
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);
// ...
}
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);
// ...
}
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) {
}
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
refers to your own class):
@ZeebeWorker(type = "foo", autoComplete = true)
public ProcessVariables handleFoo(@ZeebeVariablesAsType MyProcessVariables variables){
// do whatever you need to do
variables.getMyAttributeX();
variables.setMyAttributeY(42);
// return variables object if something has changed, so the changes are submitted to Zeebe
return variables;
}
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.
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
, orObject
, 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...");
}
}
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;
}
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...");
}
}
zeebe.client.broker.gateway-address=127.0.0.1:26500
zeebe.client.security.plaintext=true
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.
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
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.
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);
}
}
You can disable workesr via the enabled
parameter of the @ZeebeWorker
annotation :
class SomeClass {
@ZeebeWorker(type = "foo", enabled = false)
public void handleJobFoo() {
// worker's code - now disabled
}
}
You can also overwrite this setting via the your application.properties
file:
zeebe.client.worker.override.foo.enabled=false
This is especially useful, if you have a bigger code base including many workers, but want to start only some of them. Typical use cases are
- Testing: You only want one specific worker to run at a time
- Load Balancing: You want to control which workers run on which instance of cluster nodes
- Migration: There are two applications, and you want to migrate a worker from one to another. With this switch, you can simply disable workers via configuration in the old application once they are available within the new.
You can override the ZeebeWorker
annotation's values, as you could see in the example above where the enabled
property is overwritten:
zeebe.client.worker.override.foo.enabled=false
In this case, foo
is the type of the worker that we want to customize.
You can overwrite all supported configuration options for a worker, e.g.:
zeebe.client.worker.override.foo.timeout=10000
You could also provide a custom class that can customize the ZeebeWorker
configuration values by implementing the io.camunda.zeebe.spring.client.annotation.customizer.ZeebeWorkerValueCustomizer
interface.
This project adheres to the Contributor Covenant Code of Conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior to code-of-conduct@zeebe.io.