strimzi/strimzi-kafka-operator - Open Source PR Review Scorecard

Apache Kafka® running on Kubernetes

C-Rank Grade: S (Elite) - 72/100

External PR Merge Rate: 83%

Response Time: -

First Timer Success: 82%

Frequently Asked Questions

Is strimzi/strimzi-kafka-operator welcoming to first-time open-source contributors?

strimzi/strimzi-kafka-operator has a recorded first-timer success rate of 81.8%. Repositories ranked S 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 strimzi/strimzi-kafka-operator respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 71.5 C-Rank™ score (S 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 71.5 places strimzi/strimzi-kafka-operator in the S tier.

What is the external contributor pull request merge rate for strimzi/strimzi-kafka-operator?

The external contributor pull request merge rate for strimzi/strimzi-kafka-operator is 82.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in strimzi/strimzi-kafka-operator?

strimzi/strimzi-kafka-operator currently has 4 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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strimzi/strimzi-kafka-operator

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Apache Kafka® running on Kubernetes

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
8.1/10
Patience Score
8.4/10
Nitpick Rate
30%

Highly welcoming maintainers in strimzi/strimzi-kafka-operator. Prompt code reviews with positive guidance for new contributors.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
82.7%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
81.8%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
27 core
Highly collaborative maintainer core
Diagnostic Health HUD
82.7%
Merge Gauge
81.8%
1st-Timer
Community Vibe58/100

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Active Good First Issues (5)

View on GitHub

Description Summary Make the KafkaRoller retry/backoff configurable for cases where a broker is temporarily unsafe to restart. The existing safety checks should remain unchanged. The enhancement is only to allow operators to configure how long KafkaRoller retries before giving up on the current reconciliation. Background This follows the behavior reported in #12649 and discussed in Discussion #12650. In the reported environment: Strimzi 0.40.0 Kafka 3.7.0 9 brokers replication factor 3 min.insync.replicas=2 broker startup/init path can take approximately 5 minutes additional time is required for replica catch-up and ISR re-entry During a Strimzi-managed rolling update, after one broker restarts, the next broker can temporarily be unsafe to restart while replicas from the previous broker are still catching up. KafkaRoller correctly detects this and waits, but currently gives up after the fixed retry sequence: giving up after 10 attempts. Total delay between attempts 127750ms In this

📅 Opened Aug 14, 2026💬 5 comments
Quality: 70/100Contribute

#10188 (comment) revealed that there might be useful metrics that we collect but do not include in the example dashboards. For example, metrics such as kafka_controller_kafkacontroller_fencedbrokercount or kafka_server_replicamanager_offlinereplicacount would be useful metrics to include in the dashboard. This task is to review the metrics mentioned in this comment and consider adding them to the dashboard.

📅 Opened Aug 5, 2026💬 2 comments
Quality: 45/100Contribute

Related problem Currently quotas are applied only on the User, when the need to be more granular by giving each User Client a specific Quota or add a "Default" Quota the Strimzi Operator does not offer this functionality. Suggested solution Ideally the CDR should allow something similar to the following snippet. apiVersion: kafka.strimzi.io/v1beta2 kind: KafkaUser metadata: name: otel-user labels: strimzi.io/cluster: local-cluster spec: authentication: type: tls quotas: producerByteRate: 1048576 consumerByteRate: 2097152 clientQuotas: - producerByteRate: 3333 - clientId: otel-client-id producerByteRate: 4444 consumerByteRate: 2222 requestPercentage: 42 controllerMutationRate: 10 clientQuotas: type: array items: type: object properties: clientId: type: string pattern: ^.

📅 Opened Aug 3, 2026💬 9 comments
Quality: 80/100Contribute

Description The KafkaClusterTest test class is getting too bog and is getting too close to the per-file NCSS checkstyle limit (2000) which cannot be silenced by annotation anymore. We should consider breaking it down along some lines to make it easier to work with and to get within the NCSS limit. (However, as there are some shared fields, we should think about how to do it without too much duplciation)

📅 Opened Aug 3, 2026💬 6 comments
Quality: 80/100Contribute

As described in #12878, we should replace the CompletableFuture with CompletionStage in the APIs (e.g. method return types) of KafkaNodeUnregistration.

📅 Opened Jul 8, 2026💬 7 comments
Quality: 55/100Contribute
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Contributor Compatibility & Review Speed Analysis for strimzi/strimzi-kafka-operator

When evaluating whether to contribute to strimzi/strimzi-kafka-operator, 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 strimzi/strimzi-kafka-operator acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 82.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to strimzi/strimzi-kafka-operator

01

Is strimzi/strimzi-kafka-operator welcoming to first-time open-source contributors?

strimzi/strimzi-kafka-operator has a recorded first-timer success rate of 81.8%. Repositories ranked Elite 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 71.5 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 71.5 places strimzi/strimzi-kafka-operator in the Elite tier.

04

What is the external contributor pull request merge rate for strimzi/strimzi-kafka-operator?

The external pull request merge rate is 82.7%. 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 strimzi/strimzi-kafka-operator?

Yes, strimzi/strimzi-kafka-operator currently has 4 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 strimzi/strimzi-kafka-operator 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.