refactor: switch diskNormalized strategy to be more tune-able

[jtuglu1]

Description

Goal here is to make the diskNormalized strategy more tunable. Given the new, working version has not yet been included in a major release I've done some refactoring to make things easier to tune based on experience of running this in production.

The primary changes are making the utilizationThreshold more intuitive: increasing the threshold increases the "tolerance" of the strategy, while decreasing pushes nodes' disk utilization closer together. Prior to these changes, the tuning of the threshold config wasn't as straightforward and could result in under/over-aggressive segment movement. With these changes, you can expect the config value to be approximately equal to the absolute difference between the min/max disk utilized servers' utilization within a tier.

Release note

Make the diskNormalized strategy more tunable. The primary changes are making the utilizationThreshold more intuitive: increasing the threshold increases the "tolerance" of the strategy, while decreasing pushes nodes' disk utilization closer together.

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This PR has:

• been self-reviewed.
  • using the concurrency checklist (Remove this item if the PR doesn't have any relation to concurrency.)
• added documentation for new or modified features or behaviors.
• a release note entry in the PR description.
• added Javadocs for most classes and all non-trivial methods. Linked related entities via Javadoc links.
• added or updated version, license, or notice information in licenses.yaml
• added comments explaining the "why" and the intent of the code wherever would not be obvious for an unfamiliar reader.
• added unit tests or modified existing tests to cover new code paths, ensuring the threshold for code coverage is met.
• added integration tests.
• been tested in a test Druid cluster.

[FrankChen021]

I have reviewed the code for correctness, edge cases, concurrency, and integration risks; no issues found.

Reviewed 7 of 7 changed files.

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This is an automated review by Codex GPT-5.5

[maytasm]

LGTM