feat: support new topologySpread scheduling constraints

[jmdeal]

Fixes #430

Description
This PR adds support for the following topology spread constraint fields:

• matchLabelKeys
• nodeAffinityPolicy
• nodeTaintsPolicy

How was this change tested?
make test

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

[coveralls]

Pull Request Test Coverage Report for Build 10602954452

Details

• 125 of 132 (94.7%) changed or added relevant lines in 10 files are covered.
• 2 unchanged lines in 1 file lost coverage.
• Overall coverage increased (+0.1%) to 80.89%

---

Changes Missing Coverage	Covered Lines	Changed/Added Lines	%
pkg/controllers/provisioning/provisioner.go	12	14	85.71%
pkg/controllers/provisioning/scheduling/topology.go	28	30	93.33%
pkg/utils/pod/scheduling.go	1	4	25.0%

Files with Coverage Reduction	New Missed Lines	%
pkg/controllers/node/termination/controller.go	2	66.47%

Totals
Change from base Build 10590933041:	0.1%
Covered Lines:	8432
Relevant Lines:	10424

---

💛 - Coveralls

[jmdeal]

Holding to include matchLabelKeys for pod affinity with k8s v1.29.

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/lifecycle stale

[jmdeal]

/remove-lifecycle stale

[Bryce-Soghigian]

/lifecycle frozen

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[Bryce-Soghigian]

Is there a way to keep stalebot away for PRs?

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[APPROVALNOTIFIER] This PR is NOT APPROVED

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[jmdeal]

Benchmarking results (against 37db06f4742eada19934f76e616f2b1860aca57b):

goos: darwin
goarch: arm64
pkg: sigs.k8s.io/karpenter/pkg/controllers/provisioning/scheduling
                  │ old_results.txt │           new_results.txt            │
                  │     sec/op      │    sec/op      vs base               │
Scheduling1-10         99.67µ ± 42%   103.39µ ± 30%       ~ (p=0.989 n=20)
Scheduling50-10        305.6µ ±  6%    305.5µ ±  7%       ~ (p=0.265 n=20)
Scheduling100-10       488.9µ ±  6%    451.0µ ±  5%  -7.76% (p=0.001 n=20)
Scheduling500-10       1.929m ±  1%    1.859m ±  2%  -3.66% (p=0.002 n=20)
Scheduling1000-10      3.955m ±  3%    3.999m ±  7%       ~ (p=0.478 n=20)
Scheduling2000-10      7.518m ±  7%    8.072m ±  4%  +7.38% (p=0.013 n=20)
Scheduling5000-10      19.45m ±  9%    17.96m ±  4%  -7.69% (p=0.038 n=20)
geomean                1.494m          1.477m        -1.13%

                  │ old_results.txt │           new_results.txt           │
                  │      nodes      │   nodes     vs base                 │
Scheduling1-10           1.000 ± 0%   1.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling50-10          5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling100-10         5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling500-10         5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling1000-10        5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling2000-10        5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
Scheduling5000-10        5.000 ± 0%   5.000 ± 0%       ~ (p=1.000 n=20) ¹
geomean                  3.973        3.973       +0.00%
¹ all samples are equal

                  │ old_results.txt │           new_results.txt            │
                  │      pods       │    pods      vs base                 │
Scheduling1-10          1.000 ±  0%   1.000 ±  0%       ~ (p=1.000 n=20) ¹
Scheduling50-10         29.00 ± 17%   29.00 ± 24%       ~ (p=0.814 n=20)
Scheduling100-10        25.50 ± 25%   26.00 ± 23%       ~ (p=0.732 n=20)
Scheduling500-10        28.00 ± 50%   25.00 ± 32%       ~ (p=0.587 n=20)
Scheduling1000-10       35.50 ± 21%   29.00 ± 21%       ~ (p=0.279 n=20)
Scheduling2000-10       29.50 ± 39%   28.00 ± 29%       ~ (p=0.815 n=20)
Scheduling5000-10       34.00 ± 41%   31.00 ± 35%       ~ (p=0.344 n=20)
geomean                 18.48         17.36        -6.10%
¹ all samples are equal

                  │ old_results.txt │           new_results.txt           │
                  │    pods/sec     │   pods/sec    vs base               │
Scheduling1-10        10.044k ± 30%   9.672k ± 24%       ~ (p=0.984 n=20)
Scheduling50-10        163.6k ±  6%   163.7k ±  8%       ~ (p=0.265 n=20)
Scheduling100-10       204.5k ±  6%   221.8k ±  5%  +8.42% (p=0.001 n=20)
Scheduling500-10       259.2k ±  1%   269.0k ±  2%  +3.80% (p=0.002 n=20)
Scheduling1000-10      252.9k ±  3%   250.0k ±  8%       ~ (p=0.478 n=20)
Scheduling2000-10      266.1k ±  7%   247.8k ±  4%  -6.91% (p=0.013 n=20)
Scheduling5000-10      257.0k ± 10%   278.4k ±  3%  +8.32% (p=0.038 n=20)
geomean                147.3k         149.0k        +1.12%

Ran this comparison a few times, this was the set of results with the largest difference. Marginally faster overall surprisingly, with a slight decrease in first round scheduled pods (though I noticed this stat varied wildly between runs).

[jmdeal]

/remove blocked

[abrazouski]

Sorry @jmdeal for bothering, but any plans for moving forward with this?
We're really rely on this feature

[k8s-ci-robot]

PR needs rebase.

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[hamishforbes]

Hi @jmdeal is there anything blocking this or any way I can help to move this on (testing a custom build or something)?

[engedaam]

/assign @njtran

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[engedaam]

/assign @njtran