Reviewing AI's config architecture proposal

You're reviewing GreenGrid's monitoring pipeline code, which has all its settings hardcoded in Python files. The terminal shows the current code with hardcoded thresholds, API settings, database credentials, and energy calculation constants.

Your task: Copy the code into the AI chat and ask it to propose which values should move to config files. Pay attention to how the AI distinguishes between operational settings and domain-validated constants.

After analyzing the code with AI, which value should remain in source code rather than being externalized to configuration?