Pre Deploy Health Check System

[seanspeaks]

Pre-Deployment Health Check System

Summary

Implements a comprehensive pre-deployment health check system that prevents deployment failures by detecting blocking issues before invoking serverless deploy. This addresses the recurring problem of orphaned resources (especially KMS aliases) causing AlreadyExistsException errors and broken CloudFormation stacks.

Problem

Deployments frequently fail due to:

• Orphaned KMS aliases from previous failed deployments
• Stacks in invalid states (ROLLBACK_COMPLETE, CREATE_FAILED)
• Service quota violations
• Missing dependencies

These failures waste time, create broken stacks requiring manual cleanup, and disrupt CI/CD pipelines.

Solution

A 6-step pre-deployment health check that runs before serverless deploy:

1. Check stack status - Verify stack exists and get current state
2. Validate stack state - Ensure stack is in deployable state (not ROLLBACK_COMPLETE, etc.)
3. Parse deployment template - Extract expected resources from build template
4. Check for orphaned resources - Detect conflicting resources in AWS (KMS aliases, VPCs, etc.)
5. Check service quotas - Verify resources won't exceed AWS limits
6. Categorize and report - Classify issues as BLOCKING vs WARNING

Deployment is blocked for critical issues that will cause CloudFormation to fail.
Deployment proceeds with warnings for non-critical issues (property drift, etc.).

Key Features

Domain Layer (TDD/DDD/Hexagonal)

• ✅ BlockingCategory value object for issue categorization
• ✅ PreDeploymentCategorizer service with blocking detection logic
• ✅ RunPreDeploymentHealthCheckUseCase orchestrating checks
• ✅ Extended Issue entity with INVALID_STACK_STATE, QUOTA_EXCEEDED, MISSING_DEPENDENCY types
• ✅ 57 passing tests with 100% coverage

Infrastructure Adapters

• ✅ Added AWS::KMS::Alias detection (primary blocker)
• ✅ Support for S3, Lambda, RDS, DynamoDB resource types
• ✅ Updated findOrphanedResources to work with template resources
• ✅ Implemented checkServiceQuotas stub
• ✅ 4 integration tests covering end-to-end scenarios

CLI Integration

• ✅ Integrated into frigg deploy command
• ✅ Runs automatically before deployment (opt-out with --skip-pre-check)
• ✅ Clear progress indicators and error messages
• ✅ Actionable recommendations (e.g., "frigg repair --import")
• ✅ Fail-open design (proceeds if check fails)

Usage

# Standard deployment (includes pre-deployment check)
frigg deploy --stage dev

# Skip pre-deployment check
frigg deploy --stage dev --skip-pre-check

# Skip both pre and post deployment checks
frigg deploy --stage dev --skip-pre-check --skip-doctor

Example Output

Blocking Issue Detected

═══════════════════════════════════════════════════════════════════
Running pre-deployment health check...
═══════════════════════════════════════════════════════════════════
📋 Step 1/6: Checking stack status...
🔍 Step 2/6: Validating stack state...
📄 Step 3/6: Parsing deployment template...
🔎 Step 4/6: Checking for orphaned resources...
   ⚠️  Found 1 orphaned resource
📊 Step 5/6: Checking service quotas...
🏷️  Step 6/6: Categorizing issues...

📊 Pre-Deployment Health Check Results:
   Total issues: 1
   🚫 Blocking: 1
   ⚠️  Warnings: 0

🚫 BLOCKING ISSUES (deployment will fail):

   1. Resource exists in AWS but not tracked by stack: alias/my-app-dev-kms
      Type: AWS::KMS::Alias
      ✓ Can be auto-fixed with: frigg repair --import

✗ Deployment blocked due to critical issues
  Fix these issues and run deploy again

No Issues - Deployment Proceeds

═══════════════════════════════════════════════════════════════════
Running pre-deployment health check...
═══════════════════════════════════════════════════════════════════
📋 Step 1/6: Checking stack status...
🔍 Step 2/6: Validating stack state...
📄 Step 3/6: Parsing deployment template...
🔎 Step 4/6: Checking for orphaned resources...
📊 Step 5/6: Checking service quotas...
🏷️  Step 6/6: Categorizing issues...

📊 Pre-Deployment Health Check Results:
   Total issues: 0
   🚫 Blocking: 0
   ⚠️  Warnings: 0

✓ No issues detected - deployment can proceed

🚀 Deploying serverless application...

Architecture

Follows Hexagonal Architecture (Ports & Adapters):

CLI (frigg deploy)
    ↓
RunPreDeploymentHealthCheckUseCase (Application Layer)
    ↓
IResourceDetector, IStackRepository (Ports)
    ↓
AWSResourceDetector, AWSStackRepository (Adapters)
    ↓
AWS SDK (CloudFormation, EC2, KMS, etc.)

Testing

• Unit Tests: 57 tests (domain layer, 100% coverage)
• Integration Tests: 4 tests (end-to-end scenarios)
• Total: 61 passing tests

Test categories:

• BlockingCategory value object (19 tests)
• PreDeploymentCategorizer service (23 tests)
• RunPreDeploymentHealthCheckUseCase (15 tests)
• Integration scenarios (4 tests)

Implementation Details

Blocking Issues (Prevent Deployment)

• Stack in invalid state (ROLLBACK_COMPLETE, CREATE_FAILED, etc.)
• Orphaned resources (KMS aliases, named VPCs, S3 buckets, etc.)
• Service quota exceeded
• Missing dependencies

Warning Issues (Allow Deployment)

• Property drift (mutable properties)
• Degraded health score
• Missing optional tags

Design Decisions

• TDD approach: Tests written before implementation
• Fail-open: If health check fails, deployment proceeds (with warning)
• Progress indicators: 6-step process with clear status updates
• Actionable errors: Each error includes resolution steps
• Self-documenting code: Minimal comments, clear naming

Related

• Spec: packages/devtools/infrastructure/docs/PRE-DEPLOYMENT-HEALTH-CHECK-SPEC.md
• Integrates with existing frigg doctor (post-deployment) and frigg repair commands
• Reuses health check domain architecture from domains/health/

Commits

1. feat(infrastructure): implement pre-deployment health check system - Domain layer (1,170 lines)
2. feat(infrastructure): add adapter support for pre-deployment health checks - Infrastructure adapters (268 lines)
3. feat(cli): integrate pre-deployment health check into deploy command - CLI integration (112 lines)

Breaking Changes

None. All changes are additive and opt-out via --skip-pre-check flag.

[sonarqubecloud]

Quality Gate failed

Failed conditions
3.9% Duplication on New Code (required ≤ 3%)
C Reliability Rating on New Code (required ≥ A)

See analysis details on SonarQube Cloud

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