A choke point is a hop that many paths must cross. Remove it and every path through it closes at once. This is not a clever heuristic; it falls directly out of the graph once you have one.
An ordinary example
A machine identity used by a data ingest job has a trust policy that accepts any principal in the shared services account. Nine paths cross that identity. Narrowing the trust policy to the ingest task role is one pull request, one review and one deploy. Nine paths close.
The nine underlying findings do not disappear. They stop being urgent, which is a different and much cheaper state to be in.
Why this is hard without a graph
Findings-based tools cannot see overlap, because a finding has no notion of what else depends on the same hop. You end up with forty tickets across six teams, each individually reasonable and collectively enormous.
Forty tickets across six teams is not a plan. One change with a named owner and a date is a plan.
Choosing between choke points
- How many live paths does removing it close?
- What does the change cost the owning team, honestly measured?
- Does it hold under the next architecture change, or is it a patch on a patch?
- Can it be applied inside an existing maintenance window?
The last question decides more programmes than the first. A perfect fix that cannot be scheduled loses to a good fix that lands next Tuesday.
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