DataBuff is an AI-native APM built on Opentelemetry，with multi-agent troubleshooting out of the box.
C-Rank Grade: A (Welcoming) - 56/100
External PR Merge Rate: 67%
Response Time: 1h
First Timer Success: 50%
databufflabs/databuff has a recorded first-timer success rate of 50.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in databufflabs/databuff respond to incoming external pull requests in approximately 1.5 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
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 56.5 places databufflabs/databuff in the A tier.
The external contributor pull request merge rate for databufflabs/databuff is 66.7%, based on public PR activity from non-core contributors.
databufflabs/databuff does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Rigorous architecture standards (100% critical review signals). Ensure PRs strictly follow guidelines before requesting review in databufflabs/databuff.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/databufflabs/databuff?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
Calculating local time...
Calculating local time...
Detected: UTC
Maintainers are most responsive around 07:00 UTC (07:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 00:00 to 04:00 UTC (00:00 - 04:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (83% approval). Large PRs (>500 lines) take ~7 hours (30% approval). Keep your diff compact for rapid review.
Description Many Python developers want to connect their applications to DataBuff via OpenTelemetry. Currently there are quick-start guides for Docker and Spring Boot, but not for Python — one of the most popular OTel languages. Task Create a new document docs/快速入门/python-otlp-integration.md (and optionally _en.md) that walks through: Starting DataBuff (link to the Docker install guide) Installing the OpenTelemetry Python SDK and OTLP exporter Configuring the OTLP exporter endpoint to the DataBuff ingest endpoint Instrumenting a minimal Python application (e.g., Flask or FastAPI) Verifying traces and metrics appear in the DataBuff UI Files to create/change New file: docs/快速入门/python-otlp-integration.md Optionally: docs/快速入门/python-otlp-integration_en.md Acceptance criteria New guide is created with step-by-step instructions Includes Python code snippets (e.g., pip install, SDK initialization) References existing Docker install docs for DataBuff setup
Description The alerts manual (docs/使用手册/告警.md) describes concepts and menu navigation but lacks concrete configuration examples. New users often ask "how do I set up a simple error rate alert?" — a working YAML/JSON example would help them get started immediately. Task Add a new section "配置示例" (Configuration Example) to the alerts manual with a practical alert rule example, such as a threshold alert for service error rate > 5% sustained for 5 minutes. Include: The rule configuration fields (metric, threshold, duration, etc.) A screenshot of the alert creation UI (optional, bonus) Notes on how the alert appears in the Events list Files to change docs/使用手册/告警.md (and optionally docs/使用手册/告警_en.md for the English version) Acceptance criteria New "配置示例" section added to docs/使用手册/告警.md Example includes a realistic threshold rule (e.g., error rate > 5% for 5 min) Fields are explained in plain language English versio
Rate what actually matters after opening a pull request here.
Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.
When evaluating whether to contribute to databufflabs/databuff, 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 databufflabs/databuff acknowledge new external contributions in approximately 1 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 66.7% were successfully merged into the primary branch.
databufflabs/databuff has a recorded first-timer success rate of 50.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~1 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
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 56.5 places databufflabs/databuff in the Welcoming tier.
The external pull request merge rate is 66.7%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
databufflabs/databuff does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for databufflabs/databuff 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.