Activiti 5.20.0 Released

We’ve just released Activiti 5.20.0. This is a bugfix release (mainly fixing the bug around losing message and signal start event subscriptions on process definition redeployment, see ACT-4117).

Get it from the download page or of course via Maven.

“Orchestrating Work with Activiti and Spring Integration” by Josh Long

When my buddy Josh Long from Pivotal writes about Activiti and Spring, it’s always must-read material. No exception this time, so I do want to give it exposure here too:

Orchestrating Work With Activiti and Spring Integration

Nice conclusion too: “BPM adds a fair amount of cognitive load for simple integrations but offers a lot of value when business process descriptions must be model- and business analyst-friendly. One common misconception is that developers have to give up the ability to enhance the system once BPM is involved; NOT SO! Thanks to Spring Boot and some hard work from the Activiti team, Activiti works perfectly with all of Spring.”


Edit 11 Feb 2016: as promised in the comments below, forked the example and made it running on v6:

Activiti released

We just released Activiti

This is a bugfix release fixing following changes:

  • Security fix around using commons-collection (more info see the commit)
  • Upgrade to MyBatis 3.3.0
  • Enhancing AsyncExecutor for high load scenarios (especially when the job queue is full)
  • A few small bug fixes


Activiti Community Meetup Antwerp – March 2nd 2016 !

It’s been way too long ago we’ve had an Activiti meetup in Belgium (which is where I live, so there is no excuse really). Over a lunch with my good friend Yannick Spillemaeckers, we decided to rectify that.

So I’m proud to announce we’ll be having a meetup March 2nd 2016 in Antwerp! You can find all information about the event here:

Please do register on that Eventbrite page, seats are limited and full is really full! We’ve gone for an evening event, so that people can join after work hours and enjoy and evening of talking about Activiti with like-minded peers (a version 6 presentation by yours truly, amongst others). And of course, attending it is completely free.

For now (see the Eventbrite page), we have two sessions, but we’re still in planning mode. Check the page in the near future for updates …but do reserve your seat today! First come, first serve.

Activiti 6.0.0.Beta2 released

Just in time for Christmas, we’ve released the second beta of Activiti v6! You can get it through the usual channels: the website or through Maven.

This release is mainly a ‘refactoring-release’ that prepares the code for all the nifty stuff we want to do next: low in new features, but the internal kitchen has seen some major changes since beta1. We’ve been contacted by a few companies that are already giving the new pluggable persistence a go, and the feedback has been very positive.

In the new year, we’ll be ramping up the beta releases and add the ‘v6 specific features’, that will show off the huge work we did from v5 to v6 and make the upgrade worth the while. Version 6 is already feature-par with v5 (and as stable as v5). We’ll also start focussing on performance: we know that especially the simple cases probably are a tad slower (due to the richer execution tree, which means a few more row inserts), but likewise we’ve seen some complex examples being way more simpler and performant (due to the smarter execution tree). But all of that of course will be posted online in an open and reproducible way, as we always do! At the same time, we’ll ramp up on the documentation side of things: way more than in v5 we can now clearly document examples and how this translates to the internal execution.

Here’s the release highlights:

  • We’ve seriously refactored the persistence logic of the engine, making the persistence layer completely pluggable! Read more about it here.
  • Refactored the BpmnDeployer class and related logic to allow for easier pluggability/extensibility.
  • Refactored the internal execution tree structure when using multi instance behavior: there will now always be one execution to demarcate the ‘scope’ of the multi instance. This opens up future use cases (storing variables on that scope only, terminating only one instance or all, etc.)
  • Extended the ‘terminate all event’ behaviour to cover more use cases and be fully consistent with the BPMN spec. Also,
  • Added the DynamicBpmnService. Read more about it here.
  • Various and many small bugfixes all around.

All feedback of course, more than welcome!

Merry Christmas to all!


Activiti on !

In case you missed the following tweet last week


That’s right! Activiti is now on!

This is a huge deal – the Spring Initializr is the place where the journey for many Spring Boot projects start, so being on that page is a huge honour for us. Of course, couldn’t have done it without the help of my Spring friends Josh Long (who also contributed the Spring Boot + Activiti code) and Stéphane Nicoll.

And just to prove how awesome it is, here’s a short movie that starts on and finishes with a REST endpoint that starts a process instance is about 5 minutes!

Achievement Unlocked: 5000 Forum Posts!


I just passed the 5000 forum posts on the Activiti Forum. Out of a total of 41792 posts, so you can only blame me for  12% of the content on there ;-).

Just thinking about it humbles me tremendously. The forum is such an important tool for improving the Activiti Engine, guarding the quality and getting fresh ideas for features.

Also, doing the math that averages to 2.5 posts/day (not taking in account any weekends and holidays). Crazy! Thank you for all the conversations over the past years!

Multi-Tenancy with separate database schemas in Activiti

One feature request we’ve heard in the past is that of running the Activiti engine in a multi-tenant way where the data of a tenant is isolated from the others. Certainly in certain cloud/SaaS environments this is a must.

A couple of months ago I was approached by Raphael Gielen, who is a student at the university of Bonn, working on a master thesis about multi-tenancy in Activiti. We got together in a co-working coffee bar a couple of weeks ago, bounced ideas and hacked together a first prototype with database schema isolation for tenants. Very fun :-).

Anyway, we’ve been refining and polishing that code and committed it to the Activiti codebase. Let’s have a look at the existing ways of doing multi-tenancy with Activiti in the first two sections below. In the third section, we’ll dive into the new multi-tenant multi-schema feature sprinkled with some real-working code examples!

Shared Database Multi-tenancy

Activiti has been multi-tenant capable for a while now (since version 5.15). The approach taken was that of a shared database: there is one (or more) Activiti engines and they all go to the same database. Each entry in the database table has a tenant identifier, which is best to be understood as a sort of tag for that data. The Activiti engine and API’s then read and use that tenant identifier to perform its various operations in the context of a tenant.

For example, as shown in the picture below, two different tenants can have a process definition with the same key. The engine and API’s make sure there is no mixup of data.

Screenshot 2015-10-06 12.57.00

The benefit of this approach is the simplicity of deployment, as there is no difference from setting up a ‘regular’ Activiti engine. The downside is that you have to remember to use the right API calls (i.e. those that take in account the tenant identifier). Also, it has the same problem as any system with shared resources: there will always be competition for the resources between tenants. In most use cases this is fine, but there are use cases that can’t be done in this way, like giving certain tenants more or less system resources.

Multi-Engine Multi-Tenancy

Another approach, which has been possible since the very first version of Activiti is simply having one engine instance for each tenant:

Screenshot 2015-10-06 13.12.56

In this setup, each tenant can have different resource configurations or even run on different physical servers. Each engine in this picture here can of course be multiple engines for more performance/failover/etc. The benefit now is that the resources are tailored for the tenant. The downside is the more complex setup (multiple database schemas, having a different configuration file for each tenant, etc.). Each engine instance will take up memory (but that’s very low with Activiti). Also, you’d need t write some routing component that knows somehow the current tenant context and routes to the correct engine.

Screenshot 2015-10-06 13.18.36

Multi-Schema Multi-Tenancy

The latest addition to the Activiti multi-tenancy story was added two weeks ago (here’s the commit), simultaneously on version 5 and 6. Here, there is a database (schema) for each tenant, but only one engine instance. Again, in practice there might be multiple instances for performance/failover/etc., but the concept is the same:

Screenshot 2015-10-06 13.41.20

The benefit is obvious: there is but one engine instance to manage and configure and the API’s are exactly the same as with a non-multi-tenant engine. But foremost, the data of a tenant is completely separated from the data of other tenants. The downside (similar to the multi-engine multi-tenant approach) is that someone needs to manage and configure different databases. But the complex engine management is gone.

The commit I linked to above also contains a unit test showing how the Multi-Schema Multi-Tenant engine works.

Building the process engine is easy, as there is a MultiSchemaMultiTenantProcessEngineConfiguration that abstracts away most of the details:

config = new MultiSchemaMultiTenantProcessEngineConfiguration(tenantInfoHolder);

config.registerTenant("alfresco", createDataSource("jdbc:h2:mem:activiti-mt-alfresco;DB_CLOSE_DELAY=1000", "sa", ""));
config.registerTenant("acme", createDataSource("jdbc:h2:mem:activiti-mt-acme;DB_CLOSE_DELAY=1000", "sa", ""));
config.registerTenant("starkindustries", createDataSource("jdbc:h2:mem:activiti-mt-stark;DB_CLOSE_DELAY=1000", "sa", ""));
processEngine = config.buildProcessEngine();

This looks quite similar to booting up a regular Activiti process engine instance. The main difference is that we’re registring tenants with the engine. Each tenant needs to be added with its unique tenant identifier and Datasource implementation. The datasource implementation of course needs to have its own connection pooling. This means you can effectively give certain tenants different connection pool configuration depending on their use case. The Activiti engine will make sure each database schema has been either created or validated to be correct.

The magic to make this all work is the TenantAwareDataSourceThis is a javax.sql.DataSource implementation that delegates to the correct datasource depending on the current tenant identifier. The idea of this class was heavily influenced by Spring’s AbstractRoutingDataSource (standing on the shoulders of other open-source projects!).

The routing to the correct datasource is being done by getting the current tenant identifier from the TenantInfoHolder instance. As you can see in the code snippet above, this is also a mandatory argument when constructing a MultiSchemaMultiTenantProcessEngineConfiguration. The TenantInfoHolder is an interface you need to implement, depending on how users and tenants are managed in your environment. Typically you’d use a ThreadLocal to store the current user/tenant information (much like Spring Security does) that gets filled by some security filter. This class effectively acts as the routing component’ in the picture below:

Screenshot 2015-10-06 13.53.13

In the unit test example, we use indeed a ThreadLocal to store the current tenant identifier, and fill it up with some demo data:

 private void setupTenantInfoHolder() {
    DummyTenantInfoHolder tenantInfoHolder = new DummyTenantInfoHolder();
    tenantInfoHolder.addUser("alfresco", "joram");
    tenantInfoHolder.addUser("alfresco", "tijs");
    tenantInfoHolder.addUser("alfresco", "paul");
    tenantInfoHolder.addUser("alfresco", "yvo");
    tenantInfoHolder.addUser("acme", "raphael");
    tenantInfoHolder.addUser("acme", "john");
    tenantInfoHolder.addUser("starkindustries", "tony");
    this.tenantInfoHolder = tenantInfoHolder;

We now start some process instance, while also switching the current tenant identifier. In practice, you have to imagine that multiple threads come in with requests, and they’ll set the current tenant identifier based on the logged in user:


The startProcessInstances method above will set the current user and tenant identifier and start a few process instances, using the standard Activiti API as if there was no multi tenancy at all (the completeTasks method similarly completes a few tasks).

Also pretty cool is that you can dynamically register (and delete) new tenants, by using the same method that was used when building the process engine. The Activiti engine will make sure the database schema is either created or validated.

config.registerTenant("dailyplanet", createDataSource("jdbc:h2:mem:activiti-mt-daily;DB_CLOSE_DELAY=1000", "sa", ""));

Here’s a movie showing the unit test being run and the data effectively being isolated:

Multi-Tenant Job Executor

The last piece to the puzzle is the job executor. Regular Activiti API calls ‘borrow’ the current thread to execute its operations and thus can use any user/tenant context that has been set before on the thread.

The job executor however, runs using a background threadpool and has no such context. Since the AsyncExecutor in Activiti is an interface, it isn’t hard to implement a multi-schema multi-tenant job executor. Currently, we’ve added two implementations. The first implementation is called the SharedExecutorServiceAsyncExecutor:

config.setAsyncExecutor(new SharedExecutorServiceAsyncExecutor(tenantInfoHolder));

This implementations (as the name implies) uses one threadpool for all tenants. Each tenant does have its own job acquisition threads, but once the job is acquired, it is put on the shared threadpool. The benefit of this system is that the number of threads being used by Activiti is constrained.

The second implementation is called the ExecutorPerTenantAsyncExecutor:

config.setAsyncExecutor(new ExecutorPerTenantAsyncExecutor(tenantInfoHolder));

As the name implies, this class acts as a ‘proxy’ AsyncExecutor. For each tenant registered, a complete default AsyncExecutor is booted. Each with its own acquisition threads and execution threadpool. The ‘proxy’ simply delegates to the right AsyncExecutor instance. The benefit of this approach is that each tenant can have a fine-grained job executor configuration, tailored towards the needs of the tenant.


As always, all feedback is more than welcome. Do give the multi-schema multi-tenancy a go and let us know what you think and what could be improved for the future!

Pluggable persistence in Activiti 6

In the past years, we’ve often heard the request (both from community and our customers) on how to swap the persistence logic of Activiti from relational database to something else. When we announced Activiti 6, one of the promises we made was that we would make exactly this possible.

People that have dived into the code of the Activiti engine will know that this is a serious refactoring, as the persistence code is tightly coupled with the regular logic. Basically, in Activiti v5, there were:

  • Entity classes: these contain the data from the database. Typically one database row is one Entity instance
  • EntityManager: these classes group operations related to entities (find, delete,… methods)
  • DbSqlSession: low-level operations (CRUD) using MyBatis. Also contains command-duration caches and manages the flush of the data to the database.

The problems in version 5 were the following:

  • No interfaces. Everything is a class, so replacing logic gets really hard.
  • The low-level DbSqlSession was used everywhere across the code base.
  • a lot of the logic for entities was contained within the entity classes. For example look at the TaskEntity complete method. You don’t have to be an Activiti expert to understand that this is not a nice design:
    • It fires an event
    • it involves users
    • It calls a method to delete the task
    • It continues the process instance by calling signal

Now don’t get me wrong. The v5 code has brought us very far and powers many awesome stuff all over the world. But when it comes to swapping out the persistence layer … it isn’t something to be proud of.

And surely, we could hack our way in into the version 5 code (for example by swapping out the DbSqlSession with something custom that responds to the methods/query names being used there), but it still would be not quite nice design-wise and quite relational-database-like. And that doesn’t necessarily match the data store technology you might using.

No, for version 6 we wanted to do it properly. And oh boy … we knew it was going to be a lot of work … but it was even more work than we could imagine (just look at the commits on the v6 branch for the last couple of weeks). But we made it … and the end result is just beautiful (I’m biased, true). So let’s look at the new architecture in v6 (forgive me my powerpoint pictures. I’m a coder not a designer!):

Screenshot 2015-09-17 17.14.00

So, where in v5 there were no interfaces, there are interfaces everywhere in v6. The structure above is applied for all of the Entity types in the engine (currently around 25). So for example for the TaskEntity, there is a TaskEntityImpl, a TaskEntityManager, a TaskEntityManagerImpl, a TaskDataManager and a TaskDataManagerImpl class (and yes I know, they still need javadoc).  The same applies for all entities.

Let me explain the diagram above:

  • EntityManager: this is the interface that all the other code talks to whenever it comes to anything around data. It is the only entrypoint when it comes to data for a specific entity type.
  • EntityManagerImpl: implementation of the EntityManager class.The operations are often high level and do multiple things at the same time. For example an Execution delete might also delete tasks, jobs, identityLinks, etc and fire relevant events. Every EntityManager implementation has a DataManager. Whenever it needs data from the persistence store, it uses this DataManager instance to get or write the relevant data.
  • DataManager: this interface contains the ‘low level’ operations. Typically contains CRUD methods for the Entity type it manages and specific find methods when data for a particular use case is needed
  • DataManagerImpl: implementation of the DataManager interface. Contains the actual persistence code. In v6, this is the only class that now uses the DbSqlSession classes to communicate with the database using MyBatis. This is typically the class you will want to swap out.
  • Entity: interface for the data. Contains only getters and setters.
  • EntityImpl: implementation of the above interface. In Activiti v6, this is a regular pojo, but the interface allows you to switch to different  technologies such as Neo4 with spring-dataj, JPA, … (which use annotations). Without it, you would need to wrap/unwrap the entities if the default implementation would not work on your persistence technology.


Moving all of the operations into interfaces gave us a clear overview of what methods were spread across the codebase. Did you know for example there were at least five different methods to delete an Execution (named ‘delete’, ‘remove’, ‘destroy’, etc…)? They did almost the same, but with subtle differences. Or sometimes not subtle at all.

A lot of the work over the past weeks included consolidating all of this logic into one method. Now, in the current codebase, there is but one way to do something. Which is quite important for people that want to use different persistence technologies. Making them implement all varieties and subtleties would be madness.

In-memory implementation

To prove the pluggability of the persistence layer, I’ve made a small ‘in-memory’ prototype. Meaning that, instead of a relational database, we use plain old HashMaps to store our entities as {entityId, entities}. The queries then become if-clauses.

The code can be found on Github:

(people have sometimes on the forum asked how hard it was to run Activiti purely in memory, for simple use cases that don’t mandate the use of a database. Well, now it’s not hard at all anymore! Who knows … this little prototype might become something if people like it!)

As expected, we swap out the DataManager implementations with our in-memory version, see InMemoryProcessEngineConfiguration :

 protected void initDataManagers() {
   this.deploymentDataManager = new InMemoryDeploymentDataManager(this);
   this.resourceDataManager = new InMemoryResourceDataManager(this);
   this.processDefinitionDataManager = new InMemoryProcessDefinitionDataManager(this);
   this.jobDataManager = new InMemoryJobDataManager(this);
   this.executionDataManager = new InMemoryExecutionDataManager(this);
   this.historicProcessInstanceDataManager = new InMemoryHistoricProcessInstanceDataManager(this);
   this.historicActivityInstanceDataManager = new InMemoryHistoricActivityInstanceDataManager(this);
   this.taskDataManager = new InMemoryTaskDataManager(this);
   this.historicTaskInstanceDataManager = new InMemoryHistoricTaskInstanceDataManager(this);
   this.identityLinkDataManager = new InMemoryIdentityLinkDataManager(this);
   this.variableInstanceDataManager = new InMemoryVariableInstanceDataManager(this);
   this.eventSubscriptionDataManager = new InMemoryEventSubscriptionDataManager(this);

Such DataManager implementations are quite simple. See for example the InMemoryTaskDataManager who needs to implement the data retrieval/write methods for a TaskEntity:

public List<TaskEntity> findTasksByExecutionId(String executionId) {
   List<TaskEntity> results = new ArrayList<TaskEntity>();
   for (TaskEntity taskEntity : entities.values()) {
     if (taskEntity.getExecutionId() != null && taskEntity.getExecutionId().equals(executionId)) {
 return results;

To prove it works, let’s deploy, start a simple process instance, do a little task query and check some history. This code is exactly the same as the ‘regular’ Activiti usage.

public class Main {
 public static void main(String[] args) {
   InMemoryProcessEngineConfiguration config = new InMemoryProcessEngineConfiguration();
   ProcessEngine processEngine = config.buildProcessEngine();
   RepositoryService repositoryService = processEngine.getRepositoryService();
   RuntimeService runtimeService = processEngine.getRuntimeService();
   TaskService taskService = processEngine.getTaskService();
   HistoryService historyService = processEngine.getHistoryService();
   Deployment deployment = repositoryService.createDeployment().addClasspathResource("oneTaskProcess.bpmn20.xml").deploy();
   System.out.println("Process deployed! Deployment id is " + deployment.getId());
   ProcessInstance processInstance = runtimeService.startProcessInstanceByKey("oneTaskProcess");
   List<Task> tasks = taskService.createTaskQuery().processInstanceId(processInstance.getId()).list();
   System.out.println("Got " + tasks.size() + " tasks!");
   System.out.println("Number of process instances = " + historyService.createHistoricProcessInstanceQuery().count());
   System.out.println("Number of active process instances = " + historyService.createHistoricProcessInstanceQuery().finished().count());
   System.out.println("Number of finished process instances = " + historyService.createHistoricProcessInstanceQuery().unfinished().count());


Which, if you run it gives you this (blazingly fast as it’s all in memory!):

Process deployed! Deployment id is 27073df8-5d54-11e5-973b-a8206642f7c5

Got 1 tasks!

Number of process instances = 1

Number of active process instances = 0

Number of finished process instances = 1

In this prototype, I didn’t add transactional semantics. Meaning that if two users would complete the same user task at the very same time the outcome would be indeterminable. It’s of course possible to have in-memory transaction-like logic which you expect from the Activiti API, but I didn’t implement that yet. Basically you would need to keep all objects you touch in a little cache until flush/commit time and do some locking/synchronisation at that point. And of course, I do accept pull requests 😉

What’s next?

Well, that’s pretty much up to you. Let us know what you think about it,  try it out!

We’re in close contact with one of our community members/customers who plan to try it out very soon. But we want to play with it ourselves too of course and we’re looking at what would be a cool first choice (I myself still have a special place in my heart for Neo4j … which would be a great fit as it’s transactional).

But the most important bit is: in Activiti v6 it is now possible to cleanly swap out the persistence layer. We’re very proud of how it looks now. And we hope you like it too!

The performance impact of scripting in processes

We often see people using the scripting (for example in a service task, execution listener, etc.) for various purposes. Using scripts versus Java logic makes often sense:

  • It does not need to be packaged into a jar and put on the classpath
  • It makes the process definition more understandable: no need to look into different files
  • The logic is part of the process definition, which means no hassling to make sure the correct version of logic is being used

However, it’s important to also keep in mind the performance aspect of using scripting within the process definition, and balance those requirements with the benefits above.

The two scripting languages we typically see being used with Activiti is Javascript and Groovy. Javascript comes bundled with the JDK (Rhino for JDK 6 and 7) and Nashorn for JDK 8, which makes it easy to pick up. For Groovy, the Groovy scripting engine needs to be added to the classpath.

But let me tell you, I’m no fan of using Javascript as the scripting language choice, as there are subtle changes when moving between JDK versions (read more in a previous post of me here and here, and those are the ones that were documented …). So that means you could write your logic one day and it all happily works and the next day after a JDK upgrade it all fails. I rather spend my time on actually coding.

To verify the performance I made a very small microbenchmark:

Screenshot 2015-09-08 23.06.34and where the script did something silly like (the point was to have a getVariable() and setVariable() in there and something extra like getting the current day):

var input = execution.getVariable(‘input’);
var today = new Date().getDay();
execution.setVariable(‘result’, input * today);

The same code in a Java service task:

public class MyDelegate implements JavaDelegate {

    public void execute(DelegateExecution execution) throws Exception {
        Integer input = (Integer) execution.getVariable("input");
        int today = Calendar.getInstance().get(Calendar.DAY_OF_MONTH);
        execution.setVariable("result", input * today);

and the Groovy counterpart:

def input = execution.getVariable('input');
int today = Calendar.getInstance().get(Calendar.DAY_OF_MONTH);
execution.setVariable('result', input * today);

I started that process instance 10.000 times and simply noted down the total execution time, I think the numbers speak for themselves:

  • JavaDelegate: 6255 ms
  • Groovy: 7248 ms
  • Javascript: 27314 ms

The JDK version used was the latest version (1.8.0_60). The first time I ran the tests I was on 1.8.0_20, and the Javascript results were 25% higher (I read that performance improvements went in in JDK 1.8.0_40). For Groovy I used version 2.4.4 (which you should be using giving older versions have a security problem!)

Just to give a visual idea of the difference between the options:



Using Groovy for the scripting language seems to be a far better choice performance-wise compared to using Javascript. Do take in account this is a microbenchmark for one very simple use case. But given our troubles in the past with JDK upgrades that break Javascript scripts and this result, it’s very hard to make a case for selecting Javascript by default.


UPDATE 11 SEPT ’15: Quite a few people have asked me why the difference is of that magnitude. My assumption is that it’s because the javascript engine in the JDK is not thread safe and thus cannot be reused nor cached, thus having a costly bootup of the ScriptingEngine every time. If you take a look at, you can read that there is a special parameter THREADING, which we use in Activiti: to determine if the scripting engine can be cached. Nashorn (and Rhino) returns null here, meaning it can’t be used to execute scripts on multiple threads, i.e. each thread needs it’s own instance. I can only assume that the ScriptEngineManager in the JDK does something similar.