ray-project/kuberay - Open Source PR Review Scorecard

A toolkit to run Ray applications on Kubernetes

C-Rank Grade: A (Welcoming) - 62/100

External PR Merge Rate: 47%

Response Time: 2d

First Timer Success: 41%

Frequently Asked Questions

Is ray-project/kuberay welcoming to first-time open-source contributors?

ray-project/kuberay has a recorded first-timer success rate of 41.2%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in ray-project/kuberay respond to incoming external pull requests in approximately 41.5 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 62.3 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 62.3 places ray-project/kuberay in the A tier.

What is the external contributor pull request merge rate for ray-project/kuberay?

The external contributor pull request merge rate for ray-project/kuberay is 46.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in ray-project/kuberay?

ray-project/kuberay currently has 19 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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A toolkit to run Ray applications on Kubernetes

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AI Maintainer Review Guidelines

Review Persona

Strict Quality Architect

Warmth Score
6.9/10
Patience Score
7.4/10
Nitpick Rate
39%

Balanced & professional review environment in ray-project/kuberay. Maintains strict focus on technical quality and test standards.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Use conventional commit messages and clean branch names
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
1 days+
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
46.7%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
41.2%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
69 core
Highly collaborative maintainer core
Diagnostic Health HUD
46.7%
Merge Gauge
41.2%
1st-Timer
Community Vibe31/100

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Active Good First Issues (5)

View on GitHub

Description We have a constant defined in: kuberay/ray-operator/controllers/ray/utils/constant.go Lines 197 to 198 in 8614968 // RAY_AUTH_TOKEN_SECRET_KEY is the key used in the Secret containing Ray auth token RAY_AUTH_TOKEN_SECRET_KEY = "auth_token" But there are still some places use hard-coded "auth_token". They should all use the constant. Here are files that contains hard-coded value: ray-operator/controllers/ray/raycluster_controller.go ray-operator/controllers/ray/raycluster_controller_unit_test.go kubectl-plugin/pkg/cmd/get/get_token_test.go

📅 Opened Oct 4, 2026💬 2 comments
Quality: 80/100Contribute

Follow-ups after the History Server e2e switched from MinIO to RustFS (#5339). Cleanup Update the History Server docs to use RustFS instead of MinIO Remove historyserver/config/minio.yaml

📅 Opened Sep 30, 2026💬 1 comment
Quality: 65/100Contribute

Description Related to #5347 (comment). With Ray < 2.58, the task detail page cannot show task logs. We should bump the Ray image in the history server example YAMLs and e2e test data from 2.56.0 to 2.58.0. Tasks: Update YAMLs in historyserver/config/ and historyserver/test/testdata/ to use Ray version 2.58 Can use command like this to update all of them at once. Need to manually validate the result grep -rl "rayproject/ray:2.56.0" historyserver/config historyserver/test/testdata | xargs sed -i '' 's#rayproject/ray:2.56.0#rayproject/ray:2.58.0#g' Update History server docs prerequisite section https://docs.ray.io/en/latest/cluster/kubernetes/user-guides/kuberay-history-server.html#prerequisites in Ray repo

📅 Opened Sep 30, 2026💬 2 comments
Quality: 80/100Contribute

Search before asking I had searched in the issues and found no similar feature requirement. KubeRay Component ray-operator Description RayClusterMetricsManager emits rayClusterConditionProvisioned in Collect(), but its Desc is not included in Describe(): kuberay/ray-operator/controllers/ray/metrics/ray_cluster_metrics.go Lines 23 to 30 in f72fa09 // RayClusterMetricsManager implements the prometheus.Collector and RayClusterMetricsObserver interface to collect ray cluster metrics. type RayClusterMetricsManager struct { rayClusterProvisionedDurationSeconds *prometheus.GaugeVec rayClusterInfo *prometheus.Desc rayClusterConditionProvisioned *prometheus.Desc

📅 Opened Sep 17, 2026💬 1 comment
Quality: 80/100Contribute

Search before asking I searched the issues and found no similar issues. KubeRay Component ray-operator KubeRay Version main Ray Version No response Environment N/A What happened + What you expected to happen The operator supports configuring the log encoder in two ways: Command-line flags Config file When using --config, the logStdoutEncoder and logFileEncoder are loaded into config, but main.go still uses the flag variables directly when creating the encoders: kuberay/ray-operator/main.go Lines 168 to 181 in f72fa09 stdoutEncoder, err := newLogEncoder(logStdoutEncoder) exitOnError(err, "failed to create log encoder for stdout") opts.Encoder = stdoutEncoder if config.LogFile != "" {

📅 Opened Sep 17, 2026💬 1 comment
Quality: 80/100Contribute
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Contributor Compatibility & Review Speed Analysis for ray-project/kuberay

When evaluating whether to contribute to ray-project/kuberay, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of ray-project/kuberay acknowledge new external contributions in approximately 1 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 46.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to ray-project/kuberay

01

Is ray-project/kuberay welcoming to first-time open-source contributors?

ray-project/kuberay has a recorded first-timer success rate of 41.2%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~1 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 62.3 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 62.3 places ray-project/kuberay in the Welcoming tier.

04

What is the external contributor pull request merge rate for ray-project/kuberay?

The external pull request merge rate is 46.7%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in ray-project/kuberay?

Yes, ray-project/kuberay currently has 19 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for ray-project/kuberay are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.