34. The Credit Card Raise Approval Project

In this use case we should handle the automation of a credit card limit raise approval process. Most card issuers allow customers to request an increased credit limit through their websites, mobile apps or over the phone. Let’s consider we need to deliver this automation for a bank that wants to achieve a similar use case within an event-driven architecture.

The existing process is started via REST. It has a step for automatic request validation using DMN, and if the request not approved, it goes to a manual analysis. If approved, the service responsible for updating the cc limit is invoked via REST (the diagram only represents this REST call with a script task since this is not relevant for this lab's scenario). Finally, the process ends either with an approved or denied request.

Now, with the architecture shift, the service responsible for increasing the credit card limit should not be invoked via REST anymore. The external service now listens to the topic “request-approved” in order to track when to execute the limit raise. The business process should get started based on events, and whenever the process finishes, it should post a message to a specific topic depending on whether the request was approved or not.

Process v2. Whenever a new event happens in a topic, a new instance will be triggered. Depending on how this process ends, an event is published in a different topic, therefore, different services can react based on the approval status

In this strategy we have a resilient way of communication between services where the broker is responsible for storing and providing the events. Adding to that, the tech team can evolve the solutions by using the features available in Kafka itself, like the possibility to replay all the events that happened in a specific time, in chronological order.

34.1 Importing the project

Let's import the existing project so we can start implementing the eventing capabilities.

1. Access business central, and import the following project: https://github.com/kmacedovarela/cc-limit-approval-app-step1

2. Let's check the existing project. Open the cc-limit-raise-approval process. Notice it is a traditional process. Processes like this can be started either via REST or JMS.

35. Reacting to events

The first task we'll do, is to enable the existing process to react to events that are published in a specific topic. Whenever a new event is published, a new process instance should be created.

1. To allow this process definition to be started with events, the first step is to change the start event to a start message event:

2. Whenever a customer make a new request (independently of the channel used) an event should be published on the incoming-requests Kafka topic. With that, a new process instance should be started whenever a new event is published in this topic. Let's configure the start message event:

Important: we need to receive the data that is the event data. The KIE Server provides automatic marshalling to help us mapping the input directly to a Data Object (a POJO). This project has an object named LimitRaiseRequest.java which we will use to receive the incoming data.

1. On the properties panel of the Start Message Event, configure the input data:

   • Name: request
   • Data Type: LimitRaiseRequest
   • Target: request

   

2. Save the process. Your process should now look like this:

35.1 Deploying the project

Now, let's deploy and test the project.

1. On the breadcrumb, click on "cc-limit-approval-app-step1" to go back to the Project Explorer view.

2. Click on the "Deploy" button.

35.2 Testing the project

Let's publish a new event in the incoming-requests topic using the Kafka producer CLI tool.

1. Open a new tab in your terminal and access the strimzi-all-in-one project folder.
   $ cd ~/enablement/amq-examples/strimzi-all-in-one

2. Next, use the Kafka producer to publish new messages on the topic incoming-requests.

   $ docker-compose exec kafka bin/kafka-console-producer.sh --topic incoming-requests --bootstrap-server localhost:9092
   

3. You can send the following data, and press enter: {"data" : {"customerId": 1, "customerScore": 250, "requestedValue":1500}}

   

4. Back to the browser, open Business Central. On the top menu, go to Menu -> Manage -> Process Instances.

5. On the left column, filter by "Completed" State. You should see as many instances as the number of events you published on Kafka:

   

6. Select a process instance, and next, select the tab Diagram. You should see something like: