Rules (Advanced Automation)

Rules provide the most advanced way to build custom automation in GermainUX. After creating a rule, you can deploy it to a GermainUX component and run it continuously, on a schedule, or when specified conditions occur.

Rules use MVEL for expressions and custom logic. For more information, see the MVEL documentation.

🔧 Configuration Example

This example explains how to create a custom rule that parses errors from a web-server log used by Oracle Siebel CRM. The same process can be adapted to other applications and automation use cases.

📁 Create a Rule

You can create a rule through the wizard or directly from the Rules screen.

✨ Using the Wizard

Go to GermainUX Workspace -> Left Menu → Settings → Wizards -> Rule.

🖥️ Using the Rules Screen

Go to GermainUX Workspace -> Left Menu → Settings → Analytics -> Rules, and then click +.

📋 Define and Validate the Rule

Step	Instructions
Enter a name	Enter a unique rule name, such as custom-parser-siebel-web-drl.
Add the content	Paste the contents of the .drl file into the Content field.
Edit the rule	Modify the rule as required. Use the expand icon in the upper-right corner to enlarge or restore the editing area.
Validate	Click Validate to identify syntax or configuration issues.
Finish	After validation succeeds, click Finish, and then Close.

The new rule will appear in the Rules list.

🔗 Assign the Rule to a Component

After creating the rule:

Test custom rules in a non-production environment before deploying them to production.

🚀 Execute a Command from a Rule

A rule can execute a nested command and process its output within the same rule file.

The example below executes an AWS CLI command and analyzes its result.

The resulting command is similar to:

aws cloudwatch list-metrics --namespace AWS/EC2 --metric-name "EBSIOBalance%" --query "Metrics[*].Dimensions[0].Value" --output text

The implementation follows this sequence:

1. Assign the command name EC2 BurstBalance Instances.

2. Set the executable to aws.

3. Add the required arguments using cmd.arguments.add().

4. Optionally define a regular expression in cmd.pattern to filter or parse the output.

5. Execute the command with exec.executeCommand().

6. Create a result-handling rule in the same rule file.

7. Give that rule the same name as the command: EC2 BurstBalance Instances.

The matching rule receives the command output and can analyze it, generate data, trigger another action, or apply additional automation logic.

Ensure that commands run with the minimum required permissions. Store credentials securely, validate command arguments, and apply execution limits to prevent unintended or repeated operations.