Nomination Evidence: macsko

Project: kubernetes/kubernetes Period: 2025-03-02 to 2026-03-02

Summary

macsko contributes both code (53 PRs) and reviews (151 reviews), with a strong focus on welcoming newcomers (103 first-timer PR reviews), 8 of 26 authored PRs scored as high-complexity.

Highlights

Contribution statistics

Code contributions (GitHub)

  • PRs opened: 53
  • PRs merged: 49
  • Lines added: 26,283
  • Lines deleted: 6,073
  • Commits: 109

Code review

  • PRs reviewed: 151
  • Review comments given: 1704
  • Issue comments: 604
    • APPROVED: 0 (0%)
    • CHANGES_REQUESTED: 0 (0%)
    • COMMENTED: 542 (100%)

Composite score

DimensionScoreNotes
Complexity6.2/108 high-complexity PRs of 26 scored
Stewardship7.5/1028% maintenance work, 89% consistency
Review depth9.8/103.4 comments/review, 28% questions, 77 contributors
Composite7.8/10out of 1195 contributors

Review relationships

People this contributor reviews most

  • ania-borowiec: 58 reviews
  • yliaog: 48 reviews
  • brejman: 45 reviews
  • utam0k: 43 reviews
  • sanposhiho: 32 reviews
  • vshkrabkov: 28 reviews
  • tosi3k: 20 reviews
  • Argh4k: 19 reviews
  • bart0sh: 19 reviews
  • KobayashiD27: 19 reviews

People who review this contributor's PRs most

  • sanposhiho: 81 reviews
  • dom4ha: 69 reviews
  • utam0k: 14 reviews
  • wojtek-t: 14 reviews
  • thockin: 9 reviews
  • ania-borowiec: 8 reviews
  • helayoty: 7 reviews
  • togettoyou: 7 reviews
  • ingvagabund: 5 reviews
  • liggitt: 4 reviews

Newcomer welcoming

macsko reviewed 103 PRs from contributors with 3 or fewer PRs in the project, including AustinBenoit, romanbaron, flpanbin, ravisastryk, mrvarmazyar and 5 others.

Community health profile

Relational metrics: how this contributor strengthens the community beyond code output.

  • Net reviewer ratio: 2.8x
  • Interaction breadth: 77 unique contributors (concentration: 11%)
  • Newcomer welcoming: 103 reviews on PRs from contributors with 3 or fewer PRs
    • Names: AustinBenoit, romanbaron, flpanbin, ravisastryk, mrvarmazyar, pjsharath28, mohitsethia, fj-naji, sairameshv, Bowser1704
  • Helping ratio: 80% of GitHub comments directed at others' PRs
  • Review depth: 3.4 comments/review, 28% questions (1852 comments on 542 reviews)
  • Stewardship: 28% of work is maintenance (165/599 PRs: 20 authored, 145 reviewed)
  • Consistency: 89% (48/54 weeks active)
  • Feedback responsiveness: 28% iteration rate, 163.2h median turnaround, 60% reply rate (25 PRs with feedback)

Complexity of authored work

  • PRs scored: 26
  • High complexity (>= 0.5): 8
  • Low complexity (< 0.5): 18
  • Average complexity: 0.356

Highest-complexity authored PRs

  • PR #132451 (Fix race in scheduler integration tests)
    • Complexity score: 0.699
    • Probing ratio: 40.0%
    • Review rounds: 9
    • Probing topics: have any impact, change needed
  • PR #136618 (KEP-4671: Introduce Workload Scheduling Cycle)
    • Complexity score: 0.683
    • Probing ratio: 23.3%
    • Review rounds: 81
    • Probing topics: extract the common, validate that property, pass onwait callback, have happened in, scheduling queue, race condition, actually add some, be replaced soon
  • PR #134564 (KEP-4671: Add Workload API)
    • Complexity score: 0.676
    • Probing ratio: 18.9%
    • Review rounds: 114
    • Probing topics: start with immutability, same namespace, index is string, field is immutable, breaking change, description more detailed, replicated group is, somehow change the, workload object, be great if, call this field, comment somehow, wait until the
  • PR #132523 (KEP-5229: Implement API dispatcher)
    • Complexity score: 0.651
    • Probing ratio: 12.8%
    • Review rounds: 52
    • Probing topics: memory leak, k8s world, consider adding synchronization, is executed only, be protection from
  • PR #134722 (KEP-4671: Implement Gang scheduling in kube-scheduler)
    • Complexity score: 0.637
    • Probing ratio: 15.3%
    • Review rounds: 69
    • Probing topics: negative value, scheduling framework runtime, make it configurable

Quality of review contributions

Probing review comments (expressing uncertainty, challenging assumptions): 143

Most significant probing reviews (on highest-complexity PRs)

  • PR #135955 (scheduler: align the meaning of victim metrics between async preemption and sync preemption, score 0.798)
    • Topics: align the metric
    • Comment: "I'm not sure if we should align the metric with the old implementation. This met..."
  • PR #135573 (Update scoring function for balanced allocation to consider change to the node's balance, score 0.695)
    • Comment: "Why do we need this?"
  • PR #135725 (Fix extended resource handling for DRA-backed resources on pod admission, score 0.692)
    • Comment: "Can't we use the newTestDRAManager instead?"
  • PR #135725 (Fix extended resource handling for DRA-backed resources on pod admission, score 0.692)
    • Topics: value changed
    • Comment: "Why has this value changed?"
  • PR #136618 (KEP-4671: Introduce Workload Scheduling Cycle, score 0.683)
    • Comment: "But then we modify the result.status in two places instead of one. I'm not sure ..."

Highest-judgment review comments (on others' PRs)

(Selected by length, technical content, and presence of questions)

  • PR #134326 (Add global cache to map between the deviceclass and the extended resource) | https://github.com/kubernetes/kubernetes/pull/134326#discussion_r2480400887
    • File: staging/src/k8s.io/dynamic-resource-allocation/deviceclass/extendedresourcecache/extendedresourcecache.go
    • "> @macsko is it true the periodic retrying is going to be removed? that seems unreliable to rely soly on events Periodic retry that is currently 5 minutes is planned to be ultimately removed. But, it protects us from hard to detect bugs and races and we are still receiving bugs where this periodi"
  • PR #133929 (scheduler/volumebinding: passive assume cache) | https://github.com/kubernetes/kubernetes/pull/133929#discussion_r2332929498
    • File: pkg/scheduler/framework/plugins/volumebinding/assume_cache.go
    • "> Always up-to-date with informer, thus avoid race condition Using a single event handler (like for DRA) would also avoid race condition. > * Significantly simpler (less than half line of code) But we would have to maintain two versions of caches - one for volume binding and one for DRA. Do"
  • PR #135458 (Pass threshold to collected metrics in scheduler perf.) | https://github.com/kubernetes/kubernetes/pull/135458#discussion_r2567995222
    • File: test/integration/scheduler_perf/scheduler_perf.go
    • "Although this solution will be the easiest to display the threshold in perf-dash, it may not be the cleanest. The threshold would be displayed along with the results of each benchmark run, which could reduce readability. Perhaps perf-dash could be modified to display a straight line at the thresh"
  • PR #135368 (Scheduler: Fix GatedPods metric desync in unschedulable queue) | https://github.com/kubernetes/kubernetes/pull/135368#discussion_r2567656000
    • File: pkg/scheduler/backend/queue/scheduling_queue.go
    • "Sorry for a late reply. Generally speaking, I don't like multi-purpose functions such as addOrUpdate and that's why the activeQ and backoffQ now have this split into add and update. How can we be sure that the contributor who adds another unschedulablePods mutation remembers to call `update"
  • PR #134058 (Implement scoring for extended resources backed up by DRA) | https://github.com/kubernetes/kubernetes/pull/134058#discussion_r2420052324
    • File: pkg/scheduler/framework/plugins/noderesources/resource_allocation.go
    • "> What level of impact you'd consider acceptable, btw? Let's see the degradation first and then decide what steps we need to take. > One thing we shouldn't forget when assessing performance impact that by default extended resources are not scored. [Only CPU and memory are](https://github.com/k"

Area focus

Files touched (authored PRs)

  • staging/src/k8s.io (119 files)
  • pkg/scheduler/backend (76 files)
  • pkg/scheduler/framework (47 files)
  • test/integration/scheduler (36 files)
  • test/integration/scheduler_perf (32 files)
  • pkg/apis/scheduling (12 files)
  • test/compatibility_lifecycle/reference (9 files)
  • pkg/features/kube_features.go (8 files)

Areas reviewed (from PR titles)

  • testing (57 PRs)
  • metrics (53 PRs)
  • storage/log (35 PRs)
  • config (3 PRs)
  • storage (2 PRs)

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