Open
Description
Describe the Feature:
- Add a feature in the
leverage
CLI that detects when changes are being made to the AWS SSO layer and automatically output a warning message. This warning should remind users to verify the IAM fallback mechanism is in place. - Additionally, implement similar warnings for any changes that could impact the
apps-prd
account or similar high-impact layers / accounts eg: security-base that could block wrongly configured public buckets. - Consider the specific cae when deploying in a single account project where this account will have both
dev
andprd
envs consolidated in it.
NOTE: For more info and context check https://binbashar.slack.com/archives/GG0PJ78J3/p1713380015074299
Expected Behavior:
When developers or operations teams initiate changes to the AWS SSO layer or related high-impact layers the cli should:
- Automatically detect the nature of the change.
- Display a clear and concise warning in the CLI output advising to proceed carefully
- Suggest verifying configurations that ensure continued access and operational stability.
- communicate that the user should ideally check the IAM fallback mechanisms before applying changes in this layer.
Use Case:
This feature is designed to prevent operational disruptions by enhancing user awareness of the need to be extra careful and to have a fallback mechanisms before applying changes that could lock out users or disrupt service continuity.
Describe Ideal Solution:
The ideal solution would integrate with existing CLI operations, using context-aware programming to detect specific changes to the AWS SSO layer or similar critical configurations. Upon detection, the CLI should:
- Prompt a warning message that is immediately visible in the CLI output.
- Offer a direct suggestion or reminder to check and verify IAM fallback settings.
- Provide quick links or commands that help the user confirm or set up the necessary fallback mechanisms.
Alternatives Considered:
- Manual reminders or documentation updates to check fallback settings—less effective due to reliance on user compliance and memory.
- Pre-change checklists or manual approvals—could slow down operations and still miss specific edge cases without automated detection.