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Executing a rule

To execute a rule, along with its associated tasks, you are required to provide all inputs, including application details, credentials, and any user inputs, within a file named inputs.yaml. This file is situated in your rule folder.

In the case of Python, it's essential to specify any third-party library dependencies within the requirements.txt file located in each of your task folders. As an illustration, for the GitHub use case, you need to include these two Python libraries, as suggested below.

aiohttp==3.8.3
PyGithub
Unit testing instructions (if you wish to test each task individually)

When you are unit testing a specific task, the inputs.yaml file located in your rule folder will be disregarded. Hence, it is imperative to modify all inputs within the inputs.yaml located in your task folder for accurate testing. It's worth noting that when executing an entire rule, the inputs.yaml files within your task folders will not be taken into account.

To perform individual task testing, execute either the autogenerated_main.go (for Go) or autogenerated_main.py (for Python) file located in your task folder.


Use the exec rule command to execute the rule, which will prompt you to select the rule.

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You will be presented with a comprehensive list of available rules, which includes entries from both the local catalog and the global catalog. Once you choose the rule, its execution will begin, allowing you to view the progress.

Upon executing a rule, it generates an output that furnishes valuable information according to the configuration outlined in the rule.yaml file situated within the rule folder. This output typically encompasses the following details:

  • Compliance Status: This indicates the outcome of the rule execution regarding compliance with the specified criteria, which can be categorized as either COMPLIANT, NON_COMPLIANT, or NOT_DETERMINED.
  • Compliance Percentage: If the calculation of the compliance percentage is integrated into the task logic, it will be included in the output. This percentage serves as a quantitative measure, quantifying the extent to which compliance has been achieved and providing a clear indicator of the rule's adherence.

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Troubleshooting​

If any errors occur, you can readily review the execution logs in Minio, accessible at http://localhost:9001/. To log in, use the username and password that you've set up in the etc/policycow.env configuration. The path to the log file in Minio is specified within the cowexecutions/execution.ndjson file (in the last line).