### Is there an existing issue for this?

- [X] I have searched the existing issues

### Current Behavior

```
6:48:04 AM | CREATE_FAILED        | AWS::StepFunctions::StateMachine | BuildSourceCodeWor...ateMachine67076E41
An error occurred (InvalidDefinition) when calling the CreateStateMachine operation: Error=NotImplementedError Args=["Unsupported service: 'ecs'."] in definition '{"StartAt":"Update Deployment: Status=BUILD_IN_PROGRESS","States"
```

I get the above error when trying to deploy my step functions workflow with CDKLocal

### Expected Behavior

The stack should deploy successfully

### How are you starting LocalStack?

With a docker-compose file

### Steps To Reproduce

#### How are you starting localstack (e.g., `bin/localstack` command, arguments, or `docker-compose.yml`)

    docker run localstack/localstack

#### Client commands (e.g., AWS SDK code snippet, or sequence of "awslocal" commands)

    awslocal s3 mb s3://mybucket


### Environment

```markdown
- OS: Linux
- LocalStack: latest
```


### Anything else?

_No response_
self,
        env: Environment,
        resource_runtime_part: ResourceRuntimePart,
        normalised_parameters: dict,
    ):
        service_name = self._get_boto_service_name()
        api_action = self._get_boto_service_action()
        sfn_client = boto_client_for(
            region=resource_runtime_part.region,
            account=resource_runtime_part.account,
            service=service_name,
        )
        response = getattr(sfn_client, api_action)(**normalised_parameters)
        response.pop("ResponseMetadata", None)
        env.stack.append(response)
    def _sync_to_start_machine(
        self,
        env: Environment,
        resource_runtime_part: ResourceRuntimePart,
        sync2_response: bool,
    ) -> None:
        sfn_client = boto_client_for(
            region=resource_runtime_part.region,
            account=resource_runtime_part.account,
            service="stepfunctions",
        )
        submission_output: dict = env.stack.pop()
        execution_arn: str = submission_output["ExecutionArn"]
        def _has_terminated() -> Optional[dict]: