Predict Incidents Before They Happen
Every deployment is scored 0–100 using multiple validated risk signals. Know whether your next deploy is safe before you push the button. Block high-risk deploys automatically with GitHub Check Runs. No other platform does this.
Overall risk score
87
Research-validated risk signals
Every factor is backed by incident post-mortems and deployment failure research. Not guesswork — data.
Test Coverage
Files modified with low test coverage significantly increase deployment risk. Koalr integrates with Codecov and SonarCloud to pull real coverage percentages per file.
CODEOWNERS Compliance
If a PR modifies files owned by a team that has not reviewed it, the risk score increases substantially. Koalr syncs CODEOWNERS daily and validates against PR reviewers.
File Churn Rate
Files that change frequently are more error-prone. Koalr tracks 30-day churn rates per file and weights high-churn files more heavily in the risk calculation.
Author Experience
How familiar is the PR author with the files they changed? Koalr tracks commit history per author per file to estimate expertise. First-time changes to critical paths score higher risk.
PR Size
Large PRs are harder to review thoroughly and more likely to contain bugs. Risk increases progressively with changeset size, calibrated to your team’s typical PR patterns.
Deploy Timing
Deployments on Fridays, late afternoons, and during on-call low-staffing windows carry higher rollback risk. Koalr factors in time-of-day and day-of-week patterns.
Historical Failure Rate
Services with recent deployment failures, high MTTR, or frequent rollbacks receive elevated baseline risk. Koalr tracks per-service deployment health over the last 90 days.
Works with your existing deploy platform
More platforms added continuously. Don't see yours? Let us know.
Risk scores on every pull request
Every engineer sees deploy risk directly in their PR workflow. Koalr posts a GitHub Check Run on every pull request with a pass/fail status, numeric risk score, and full signal breakdown — no context switching, no separate dashboard to check.
Koalr Deploy Risk — Score: 23
Low risk — safe to deploy
Koalr Deploy Risk — Score: 87
High risk — coverage drop, missing CODEOWNERS review
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- GitHub PR Check Runs on every PR
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- Everything in Growth
- AI-powered risk explanations
- Autonomous reviewer assignment
- AI chat for metrics exploration
Not just a score — an explanation and a fix
Every high-risk PR tells you exactly which signals fired, why each one matters, and what specific action will lower the risk. No more guessing what to do with a red score.
Why this is risky
This PR contains database schema changes. DDL migrations require coordinated deploys and an explicit rollback plan. Deploying without these safeguards risks data loss.
This PR has not completed a review cycle. Unreviewed code has 2.6x higher defect rates (McIntosh et al. 2015).
1,240 lines changed across 18 files exceeds the recommended 400-line review limit. Larger diffs correlate with higher defect rates.
This PR scores 89 (CRITICAL) due to three compounding factors: a DDL migration with no rollback script, zero code review, and a 1,240-line changeset that overwhelms any single reviewer's ability to catch subtle regressions. Together they represent a high probability of production incident.
AI-generated analysis — Business plan
How to fix it
DDL Migration Detected
Add rollback migration
Create a down-migration that reverses the schema change so you can revert without manual SQL if the deploy causes issues.
Use multi-step deploy strategy
Deploy the migration separately from application code. Apply schema changes first, then deploy new code.
No Review Cycles
Request review from domain expert
Assign a reviewer with recent experience in the affected files. Suggested: @sarah-chen (payments, 3 in queue · 2h avg)
Per-repository risk gate thresholds
Different repos carry different risk tolerances. Set a custom block threshold per repository — strict for payments, permissive for internal tooling — without touching org-wide settings.
- Strict (40) — production-critical services, financial data
- Standard (60) — typical product repositories
- Permissive (80) — internal tools, low-traffic services
- Critical only (90) — experimental repositories
- Org default (75) — inherits organization-wide setting
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