Fix: Ignore historical assigned replicas when clusters no longer meet updated scheduling constraints.

[rohan-019]

What type of PR is this?
/kind bug

What this PR does / why we need it:
This PR fixes an issue in the Karmada scheduler where historical replica assignments (AssignedReplicasForCluster) were unconditionally added to a cluster’s available replicas, even when the cluster no longer satisfies the workload’s updated scheduling constraints (e.g., nodeAffinity, resourceRequests).

With the previous logic, clusters that became unsuitable after constraint changes could appear more attractive due to inflated available replicas, leading to suboptimal scheduling decisions.

This PR ensures that historical assignments are only counted for clusters that still meet the current constraints, so new replicas are scheduled to clusters that can actually accommodate them.
Which issue(s) this PR fixes:

Fixes #6771

Special notes for your reviewer:

Modified pkg/scheduler/core/spreadconstraint/group_clusters.go to conditionally include historical assignments.

Verified behavior with unit tests and scaling scenarios under constraint changes.

Does this PR introduce a user-facing change?: NO

karmada-scheduler: Fixed a scheduling bug where historical assigned replicas were incorrectly counted for clusters that no longer meet updated scheduling constraints, preventing suboptimal replica placement.

[gemini-code-assist]

Summary of Changes

Hello @rohan-019, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves a critical bug within the Karmada scheduler's replica assignment logic. Previously, historical replica assignments were unconditionally added to a cluster's available capacity, even if the cluster no longer satisfied the workload's updated scheduling constraints. This flaw could lead to inefficient and incorrect replica placement. The implemented fix introduces a conditional check, ensuring that historical assignments are only factored in for clusters that genuinely meet the current constraints, thereby promoting more accurate and optimal scheduling decisions.

Highlights

• Scheduling Logic Correction: Modified the generateClustersInfo function in the scheduler to conditionally include historical assigned replicas (AssignedReplicasForCluster) in a cluster's AvailableReplicas. This ensures that historical assignments are only considered if the cluster still has available capacity and meets current scheduling constraints.
• Bug Fix: Addresses a bug where clusters that no longer met updated scheduling constraints could still appear more attractive due to inflated available replica counts, leading to suboptimal scheduling decisions.

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[karmada-bot]

[APPROVALNOTIFIER] This PR is NOT APPROVED

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[gemini-code-assist]

Code Review

This pull request fixes a bug in the Karmada scheduler where historical replica counts could lead to poor scheduling decisions for clusters that no longer meet constraints. The proposed logic change correctly addresses this by only considering historical replicas if a cluster can accommodate new ones. My review includes a suggestion to improve a comment for clarity and strongly recommends adding a regression test to prevent this issue from recurring.

[codecov-commenter]

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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 45.75%. Comparing base (70411ab) to head (45c5120).
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Additional details and impacted files

@@           Coverage Diff           @@
##           master    #6779   +/-   ##
=======================================
  Coverage   45.74%   45.75%           
=======================================
  Files         689      689           
  Lines       57161    57163    +2     
=======================================
+ Hits        26149    26154    +5     
+ Misses      29383    29379    -4     
- Partials     1629     1630    +1     

Flag	Coverage Δ
unittests	45.75% <100.00%> (+<0.01%)	⬆️

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[rohan-019]

Hey, @GitHubxsy @zhzhuang-zju
please review!

[GitHubxsy]

Hey, @GitHubxsy @zhzhuang-zju please review!

@rohan-019 I apologize for the delay in seeing your PR. Your PR can only solve part of the scenario, such as when affinity rules are modified and the cluster has no nodes that meet the new affinity requirements. However, if the user modifies the resource requests (e.g., CPU/memory requests for the Pods), the current calculated maximum available replicas will still be incorrect.
My idea is to remove the existing logic from the karmada-scheduler and delegate the responsibility of providing an accurate maximum available replica count entirely to the karmada-scheduler-estimator.
​How the karmada-scheduler-estimator can accurately calculate the maximum available replicas:​​
The resource view snapshot maintained by the karmada-scheduler-estimator should subtract the resources already consumed by the Pods of this workload that are currently deployed. Perhaps we need to add a new selector parameter. This parameter would be used to match the Pods belonging to this specific workload, allowing us to accurately account for the resources they are already occupying within the resource view snapshot. Then, this updated resource view would be used to calculate the true maximum available replicas.