Deployment Intelligence™ — unique to Koalr

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.

Deploy risk — PR #2847 feat/payments-v2

Overall risk score

87

HIGH RISKRecommend blocking
87%
Coverage drop
88
CODEOWNERS missing
82
File churn (high)
74
PR size (large)
68
Deploy timing
58
Recent failure history
52
Author experience
40

Research-validated risk signals

Every factor is backed by incident post-mortems and deployment failure research. Not guesswork — data.

01

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.

02

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.

03

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.

04

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.

05

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.

06

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.

07

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

GitHub Deployments
Vercel
Railway
Netlify
Render
Fly.io
AWS CodeDeploy
ArgoCD
Jenkins

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.

GitHub Check Runs

Koalr Deploy Risk — Score: 23

Low risk — safe to deploy

PASS

Koalr Deploy Risk — Score: 87

High risk — coverage drop, missing CODEOWNERS review

FAIL

Free

$0/month

  • Deploy risk dashboard
  • 10 PR risk checks per week
  • Up to 5 contributors

Growth

Popular

$39/contributor/mo

  • Everything in Free
  • GitHub PR Check Runs on every PR
  • Score + full signal breakdown
  • Unlimited PR risk checks

Business

$55/contributor/mo

  • 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

HIGHDDL Migration Detected

This PR contains database schema changes. DDL migrations require coordinated deploys and an explicit rollback plan. Deploying without these safeguards risks data loss.

HIGHNo Review Cycles

This PR has not completed a review cycle. Unreviewed code has 2.6x higher defect rates (McIntosh et al. 2015).

MEDIUMLarge Changeset

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

REQUIRED

Add rollback migration

Create a down-migration that reverses the schema change so you can revert without manual SQL if the deploy causes issues.

RECOMMENDED

Use multi-step deploy strategy

Deploy the migration separately from application code. Apply schema changes first, then deploy new code.

No Review Cycles

REQUIRED

Request review from domain expert

Assign a reviewer with recent experience in the affected files. Suggested: @sarah-chen (payments, 3 in queue · 2h avg)

Enterprise control

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
Settings → Risk Gates
payments-serviceStrict (40)
api-gatewayStandard (60)
internal-toolsPermissive (80)
koalr-webOrg default (75)

Try the deploy risk calculator — free, no signup

Paste your PR URL and get an instant risk score. See exactly which factors are driving risk and what you can do to lower it.

Try it free — no signup needed →