Coordinating Change in Karma #

Karma can accept configuration change requests — but in a system with dependencies, propagation must be coordinated carefully to maintain system integrity.

This page outlines a proposal for managing graph-aware change requests safely.

The Problem #

Changing the config for one component might:

• Break downstream consumers if done out of order
• Require reloading or redeploying related components
• Involve validation before it’s safe to apply

Karma’s Role #

Karma should:

1. Receive a change request
2. Analyze impact in the graph
3. Determine what downstream actions are required
4. Apply the change and update the graph (or queue it)
5. Log the request and outcome for auditing

Change Lifecycle (Proposed) #

Client → karma-api: POST /request-change
               ↓
         Karma validates config
               ↓
         Karma builds proposed graph patch
               ↓
         Karma checks for conflicts or blocking dependencies
               ↓
         If safe: write to config + update graph
         Else: reject or queue for later

Use Cases #

Request Format (Example) #

{
  "component": "serverless-site/karma-dev",
  "proposed_change": {
    "cloudfront_aliases": ["www.usekarma.dev"]
  },
  "requested_by": "ted@strall.com"
}

Result Format #

{
  "status": "applied",
  "affected_components": [
    "route53-zone/karma-dev",
    "cloudfront-distribution/karma-dev"
  ],
  "warnings": [],
  "log_entry_id": "log-1fd742f"
}

Implementation Notes #

• Karma can start with “just apply” mode and evolve toward full change propagation
• Validation and rollback paths are key to correctness
• A dry-run or “plan” endpoint should be available

In the future, Karma can act as a safe graph mutation gateway — analyzing dependencies, proposing valid transitions, and enabling dynamic reconfiguration through a structured request model.