anchor.diff:  In this particular case we use both processes and rules to make sure we get the context right and react to the events
   behind the vegetable service. To be able to spot the erroneous situations we need to monitor two topics:
   
  -* vegetable - events from CDC
  -* transaction-context-data - events from vegetable service with additional context data
  +* `dbserver1.inventory.vegetable` - vegetable data change events
  +* `dbserver1.inventory.transaction_context_data` - events from vegetable service with additional context data
   
  -So for that we define two business processes where each will be started based on incoming message - from individual
  -Kafka topics
  +So for that we define two business processes where each will be started based on incoming messages - from individual
  +Kafka topics:
   
   ++++
   <div class="imageblock centered-image">
  
positive.code: </div>
  ++++
  
  Once the `Use case` and `User name` are provided the process will create a new transaction context event and push it
  to the Kafka topic and completes itself.
  
  After the missing transaction context data event has been put on the topic the log enricher will resume its operation
  and you will be able to see in the logs the following lines:
  
  [source, plain]
  ----
  
negative.code: 
  So let’s assume there is a need to do some maintenance on the inventory database that will essentially make changes to the data stored in the vegetable table. To make it simple, let's just add a new entry into the vegetable table:
  
  [source,sql]
  ----
  insert into inventory.vegetable (id, name, description) values (106, ‘cucumber, 'excellent');
  ----
  
  Once that is added you will see that the log enricher service is starting to print out quite a few log messages… and it does it constantly.
  
  [source, plain]
  ----
  