CodeRaptor
Impact Detection

Detect Downstream Impact in Pull Requests

Understand how code changes affect dependent services, APIs, and components before merging. Prevent breaking changes from reaching production.

85%
Incidents Prevented

Breaking changes caught before merge

<5s
Analysis Time

Impact detected in seconds

100+
Dependencies Tracked

Per repository average

3x
Fewer Rollbacks

After enabling impact detection

See Downstream Impact Detection in Action

Visualize how changes propagate through your codebase

PR #2847: Update AuthService

Changes to authentication module detected

High Impact
12
Services Affected
47
Files Impacted
3
Breaking Changes
5
Teams to Notify

Impact Chain

auth/AuthService.ts
Changed: validateToken() signature
middleware/AuthMiddleware.ts
Uses validateToken() - needs update
UserService

Downstream consumer

OrderService

Downstream consumer

PaymentService

Downstream consumer

Breaking Changes Detected

Parameter RemovedHigh

validateToken() no longer accepts `options` parameter

8 consumers affected

Return Type ChangedHigh

validateToken() now returns Promise<TokenResult> instead of Promise<boolean>

12 consumers affected

Method RenamedMedium

refreshToken() renamed to renewToken()

5 consumers affected

Impact Detection Features

Everything you need to understand the blast radius of code changes

Dependency Graph Analysis

Automatically builds and maintains a graph of all dependencies in your codebase to trace impact.

  • Auto-generated graphs
  • Cross-repo tracking
  • Real-time updates

Breaking Change Detection

Detects changes to function signatures, APIs, and interfaces that may break downstream consumers.

  • API contract checks
  • Signature analysis
  • Type compatibility

Service Impact Mapping

Maps which microservices and applications are affected by changes in shared libraries.

  • Microservice tracing
  • Shared lib analysis
  • Team notifications

Blast Radius Scoring

Get a quantified risk score based on how many components and services are affected.

  • Risk quantification
  • Severity levels
  • Historical comparison

Pre-merge Validation

Block merges that would introduce breaking changes without proper coordination.

  • Quality gates
  • Approval workflows
  • Safe deployment

Instant Notifications

Alert dependent teams when changes affect their services so they can prepare.

  • Team alerts
  • Slack integration
  • Email notifications

Teams Trust Our Impact Detection

See how engineering teams prevent breaking changes

We caught a breaking change that would have affected 14 downstream services. Impact detection paid for itself in one PR.

Michael Chen
Principal Engineer at Stripe

Detecting downstream impact before merge has completely changed how we review PRs in shared libraries.

Sarah Kim
Platform Lead at Uber

Our deployment rollback rate dropped by 70% after we started using downstream impact detection.

David Miller
SRE Manager at Datadog

Downstream Impact FAQ

Common questions about detecting impact in pull requests

Downstream impact detection analyzes how changes in your pull requests affect dependent code, services, and applications. It traces the dependency graph to identify all components that could break due to your changes, helping you understand the 'blast radius' before merging.

CodeRaptor builds a comprehensive dependency graph by analyzing imports, API contracts, and service dependencies. When you open a PR, it traces which functions and modules are changed, then follows the dependency chain to identify all affected consumers.

Yes! CodeRaptor analyzes function signatures, parameter types, return types, and API contracts. It detects breaking changes like removed parameters, changed types, renamed functions, and modified response schemas.

Absolutely! CodeRaptor tracks dependencies across microservices through shared libraries, API contracts (OpenAPI/GraphQL), and event schemas. It alerts teams when their services might be affected by changes in dependencies.

The blast radius score is calculated based on: number of affected files, number of dependent services, criticality of affected components, frequency of use, and historical incident data. Higher scores indicate changes that need more careful review.

Yes! You can configure quality gates to require additional reviewers, specific approvals from affected teams, or completely block merges when blast radius exceeds thresholds. Rules are customizable per repository.

Stop breaking changes before they break production

Detect downstream impact in every pull request automatically