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# Migration Architect
**Tier:** POWERFUL
**Category:** Engineering - Migration Strategy
**Purpose:** Zero-downtime migration planning, compatibility validation, and rollback strategy generation
## Overview
The Migration Architect skill provides comprehensive tools and methodologies for planning, executing, and validating complex system migrations with minimal business impact. This skill combines proven migration patterns with automated planning tools to ensure successful transitions between systems, databases, and infrastructure.
## Components
### Core Scripts
1. **migration_planner.py** - Automated migration plan generation
2. **compatibility_checker.py** - Schema and API compatibility analysis
3. **rollback_generator.py** - Comprehensive rollback procedure generation
### Reference Documentation
- **migration_patterns_catalog.md** - Detailed catalog of proven migration patterns
- **zero_downtime_techniques.md** - Comprehensive zero-downtime migration techniques
- **data_reconciliation_strategies.md** - Advanced data consistency and reconciliation strategies
### Sample Assets
- **sample_database_migration.json** - Example database migration specification
- **sample_service_migration.json** - Example service migration specification
- **database_schema_before.json** - Sample "before" database schema
- **database_schema_after.json** - Sample "after" database schema
## Quick Start
### 1. Generate a Migration Plan
```bash
python3 scripts/migration_planner.py \
--input assets/sample_database_migration.json \
--output migration_plan.json \
--format both
```
**Input:** Migration specification with source, target, constraints, and requirements
**Output:** Detailed phased migration plan with risk assessment, timeline, and validation gates
### 2. Check Compatibility
```bash
python3 scripts/compatibility_checker.py \
--before assets/database_schema_before.json \
--after assets/database_schema_after.json \
--type database \
--output compatibility_report.json \
--format both
```
**Input:** Before and after schema definitions
**Output:** Compatibility report with breaking changes, migration scripts, and recommendations
### 3. Generate Rollback Procedures
```bash
python3 scripts/rollback_generator.py \
--input migration_plan.json \
--output rollback_runbook.json \
--format both
```
**Input:** Migration plan from step 1
**Output:** Comprehensive rollback runbook with procedures, triggers, and communication templates
## Script Details
### Migration Planner (`migration_planner.py`)
Generates comprehensive migration plans with:
- **Phased approach** with dependencies and validation gates
- **Risk assessment** with mitigation strategies
- **Timeline estimation** based on complexity and constraints
- **Rollback triggers** and success criteria
- **Stakeholder communication** templates
**Usage:**
```bash
python3 scripts/migration_planner.py [OPTIONS]
Options:
--input, -i Input migration specification file (JSON) [required]
--output, -o Output file for migration plan (JSON)
--format, -f Output format: json, text, both (default: both)
--validate Validate migration specification only
```
**Input Format:**
```json
{
"type": "database|service|infrastructure",
"pattern": "schema_change|strangler_fig|blue_green",
"source": "Source system description",
"target": "Target system description",
"constraints": {
"max_downtime_minutes": 30,
"data_volume_gb": 2500,
"dependencies": ["service1", "service2"],
"compliance_requirements": ["GDPR", "SOX"]
}
}
```
### Compatibility Checker (`compatibility_checker.py`)
Analyzes compatibility between schema versions:
- **Breaking change detection** (removed fields, type changes, constraint additions)
- **Data migration requirements** identification
- **Suggested migration scripts** generation
- **Risk assessment** for each change
**Usage:**
```bash
python3 scripts/compatibility_checker.py [OPTIONS]
Options:
--before Before schema file (JSON) [required]
--after After schema file (JSON) [required]
--type Schema type: database, api (default: database)
--output, -o Output file for compatibility report (JSON)
--format, -f Output format: json, text, both (default: both)
```
**Exit Codes:**
- `0`: No compatibility issues
- `1`: Potentially breaking changes found
- `2`: Breaking changes found
### Rollback Generator (`rollback_generator.py`)
Creates comprehensive rollback procedures:
- **Phase-by-phase rollback** steps
- **Automated trigger conditions** for rollback
- **Data recovery procedures**
- **Communication templates** for different audiences
- **Validation checklists** for rollback success
**Usage:**
```bash
python3 scripts/rollback_generator.py [OPTIONS]
Options:
--input, -i Input migration plan file (JSON) [required]
--output, -o Output file for rollback runbook (JSON)
--format, -f Output format: json, text, both (default: both)
```
## Migration Patterns Supported
### Database Migrations
- **Expand-Contract Pattern** - Zero-downtime schema evolution
- **Parallel Schema Pattern** - Side-by-side schema migration
- **Event Sourcing Migration** - Event-driven data migration
### Service Migrations
- **Strangler Fig Pattern** - Gradual legacy system replacement
- **Parallel Run Pattern** - Risk mitigation through dual execution
- **Blue-Green Deployment** - Zero-downtime service updates
### Infrastructure Migrations
- **Lift and Shift** - Quick cloud migration with minimal changes
- **Hybrid Cloud Migration** - Gradual cloud adoption
- **Multi-Cloud Migration** - Distribution across multiple providers
## Sample Workflow
### 1. Database Schema Migration
```bash
# Generate migration plan
python3 scripts/migration_planner.py \
--input assets/sample_database_migration.json \
--output db_migration_plan.json
# Check schema compatibility
python3 scripts/compatibility_checker.py \
--before assets/database_schema_before.json \
--after assets/database_schema_after.json \
--type database \
--output schema_compatibility.json
# Generate rollback procedures
python3 scripts/rollback_generator.py \
--input db_migration_plan.json \
--output db_rollback_runbook.json
```
### 2. Service Migration
```bash
# Generate service migration plan
python3 scripts/migration_planner.py \
--input assets/sample_service_migration.json \
--output service_migration_plan.json
# Generate rollback procedures
python3 scripts/rollback_generator.py \
--input service_migration_plan.json \
--output service_rollback_runbook.json
```
## Output Examples
### Migration Plan Structure
```json
{
"migration_id": "abc123def456",
"source_system": "Legacy User Service",
"target_system": "New User Service",
"migration_type": "service",
"complexity": "medium",
"estimated_duration_hours": 72,
"phases": [
{
"name": "preparation",
"description": "Prepare systems and teams for migration",
"duration_hours": 8,
"validation_criteria": ["All backups completed successfully"],
"rollback_triggers": ["Critical system failure"],
"risk_level": "medium"
}
],
"risks": [
{
"category": "technical",
"description": "Service compatibility issues",
"severity": "high",
"mitigation": "Comprehensive integration testing"
}
]
}
```
### Compatibility Report Structure
```json
{
"overall_compatibility": "potentially_incompatible",
"breaking_changes_count": 2,
"potentially_breaking_count": 3,
"issues": [
{
"type": "required_column_added",
"severity": "breaking",
"description": "Required column 'email_verified_at' added",
"suggested_migration": "Add default value initially"
}
],
"migration_scripts": [
{
"script_type": "sql",
"description": "Add email verification columns",
"script_content": "ALTER TABLE users ADD COLUMN email_verified_at TIMESTAMP;",
"rollback_script": "ALTER TABLE users DROP COLUMN email_verified_at;"
}
]
}
```
## Best Practices
### Planning Phase
1. **Start with risk assessment** - Identify failure modes before planning
2. **Design for rollback** - Every step should have a tested rollback procedure
3. **Validate in staging** - Execute full migration in production-like environment
4. **Plan gradual rollout** - Use feature flags and traffic routing
### Execution Phase
1. **Monitor continuously** - Track technical and business metrics
2. **Communicate proactively** - Keep stakeholders informed
3. **Document everything** - Maintain detailed logs for analysis
4. **Stay flexible** - Be prepared to adjust based on real-world performance
### Validation Phase
1. **Automate validation** - Use automated consistency and performance checks
2. **Test business logic** - Validate critical business processes end-to-end
3. **Load test** - Verify performance under expected production load
4. **Security validation** - Ensure security controls function properly
## Integration
### CI/CD Pipeline Integration
```yaml
# Example GitHub Actions workflow
name: Migration Validation
on: [push, pull_request]
jobs:
validate-migration:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Validate Migration Plan
run: |
python3 scripts/migration_planner.py \
--input migration_spec.json \
--validate
- name: Check Compatibility
run: |
python3 scripts/compatibility_checker.py \
--before schema_before.json \
--after schema_after.json \
--type database
```
### Monitoring Integration
The tools generate metrics and alerts that can be integrated with:
- **Prometheus** - For metrics collection
- **Grafana** - For visualization and dashboards
- **PagerDuty** - For incident management
- **Slack** - For team notifications
## Advanced Features
### Machine Learning Integration
- Anomaly detection for data consistency issues
- Predictive analysis for migration success probability
- Automated pattern recognition for migration optimization
### Performance Optimization
- Parallel processing for large-scale migrations
- Incremental reconciliation strategies
- Statistical sampling for validation
### Compliance Support
- GDPR compliance tracking
- SOX audit trail generation
- HIPAA security validation
## Troubleshooting
### Common Issues
**"Migration plan validation failed"**
- Check JSON syntax in migration specification
- Ensure all required fields are present
- Validate constraint values are realistic
**"Compatibility checker reports false positives"**
- Review excluded fields configuration
- Check data type mapping compatibility
- Adjust tolerance settings for numerical comparisons
**"Rollback procedures seem incomplete"**
- Ensure migration plan includes all phases
- Verify database backup locations are specified
- Check that all dependencies are documented
### Getting Help
1. **Review documentation** - Check reference docs for patterns and techniques
2. **Examine sample files** - Use provided assets as templates
3. **Check expected outputs** - Compare your results with sample outputs
4. **Validate inputs** - Ensure input files match expected format
## Contributing
To extend or modify the Migration Architect skill:
1. **Add new patterns** - Extend pattern templates in migration_planner.py
2. **Enhance compatibility checks** - Add new validation rules in compatibility_checker.py
3. **Improve rollback procedures** - Add specialized rollback steps in rollback_generator.py
4. **Update documentation** - Keep reference docs current with new patterns
## License
This skill is part of the claude-skills repository and follows the same license terms.

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---
name: "migration-architect"
description: "Migration Architect"
---
# Migration Architect
**Tier:** POWERFUL
**Category:** Engineering - Migration Strategy
**Purpose:** Zero-downtime migration planning, compatibility validation, and rollback strategy generation
## Overview
The Migration Architect skill provides comprehensive tools and methodologies for planning, executing, and validating complex system migrations with minimal business impact. This skill combines proven migration patterns with automated planning tools to ensure successful transitions between systems, databases, and infrastructure.
## Core Capabilities
### 1. Migration Strategy Planning
- **Phased Migration Planning:** Break complex migrations into manageable phases with clear validation gates
- **Risk Assessment:** Identify potential failure points and mitigation strategies before execution
- **Timeline Estimation:** Generate realistic timelines based on migration complexity and resource constraints
- **Stakeholder Communication:** Create communication templates and progress dashboards
### 2. Compatibility Analysis
- **Schema Evolution:** Analyze database schema changes for backward compatibility issues
- **API Versioning:** Detect breaking changes in REST/GraphQL APIs and microservice interfaces
- **Data Type Validation:** Identify data format mismatches and conversion requirements
- **Constraint Analysis:** Validate referential integrity and business rule changes
### 3. Rollback Strategy Generation
- **Automated Rollback Plans:** Generate comprehensive rollback procedures for each migration phase
- **Data Recovery Scripts:** Create point-in-time data restoration procedures
- **Service Rollback:** Plan service version rollbacks with traffic management
- **Validation Checkpoints:** Define success criteria and rollback triggers
## Migration Patterns
### Database Migrations
#### Schema Evolution Patterns
1. **Expand-Contract Pattern**
- **Expand:** Add new columns/tables alongside existing schema
- **Dual Write:** Application writes to both old and new schema
- **Migration:** Backfill historical data to new schema
- **Contract:** Remove old columns/tables after validation
2. **Parallel Schema Pattern**
- Run new schema in parallel with existing schema
- Use feature flags to route traffic between schemas
- Validate data consistency between parallel systems
- Cutover when confidence is high
3. **Event Sourcing Migration**
- Capture all changes as events during migration window
- Apply events to new schema for consistency
- Enable replay capability for rollback scenarios
#### Data Migration Strategies
1. **Bulk Data Migration**
- **Snapshot Approach:** Full data copy during maintenance window
- **Incremental Sync:** Continuous data synchronization with change tracking
- **Stream Processing:** Real-time data transformation pipelines
2. **Dual-Write Pattern**
- Write to both source and target systems during migration
- Implement compensation patterns for write failures
- Use distributed transactions where consistency is critical
3. **Change Data Capture (CDC)**
- Stream database changes to target system
- Maintain eventual consistency during migration
- Enable zero-downtime migrations for large datasets
### Service Migrations
#### Strangler Fig Pattern
1. **Intercept Requests:** Route traffic through proxy/gateway
2. **Gradually Replace:** Implement new service functionality incrementally
3. **Legacy Retirement:** Remove old service components as new ones prove stable
4. **Monitoring:** Track performance and error rates throughout transition
```mermaid
graph TD
A[Client Requests] --> B[API Gateway]
B --> C{Route Decision}
C -->|Legacy Path| D[Legacy Service]
C -->|New Path| E[New Service]
D --> F[Legacy Database]
E --> G[New Database]
```
#### Parallel Run Pattern
1. **Dual Execution:** Run both old and new services simultaneously
2. **Shadow Traffic:** Route production traffic to both systems
3. **Result Comparison:** Compare outputs to validate correctness
4. **Gradual Cutover:** Shift traffic percentage based on confidence
#### Canary Deployment Pattern
1. **Limited Rollout:** Deploy new service to small percentage of users
2. **Monitoring:** Track key metrics (latency, errors, business KPIs)
3. **Gradual Increase:** Increase traffic percentage as confidence grows
4. **Full Rollout:** Complete migration once validation passes
### Infrastructure Migrations
#### Cloud-to-Cloud Migration
1. **Assessment Phase**
- Inventory existing resources and dependencies
- Map services to target cloud equivalents
- Identify vendor-specific features requiring refactoring
2. **Pilot Migration**
- Migrate non-critical workloads first
- Validate performance and cost models
- Refine migration procedures
3. **Production Migration**
- Use infrastructure as code for consistency
- Implement cross-cloud networking during transition
- Maintain disaster recovery capabilities
#### On-Premises to Cloud Migration
1. **Lift and Shift**
- Minimal changes to existing applications
- Quick migration with optimization later
- Use cloud migration tools and services
2. **Re-architecture**
- Redesign applications for cloud-native patterns
- Adopt microservices, containers, and serverless
- Implement cloud security and scaling practices
3. **Hybrid Approach**
- Keep sensitive data on-premises
- Migrate compute workloads to cloud
- Implement secure connectivity between environments
## Feature Flags for Migrations
### Progressive Feature Rollout
```python
# Example feature flag implementation
class MigrationFeatureFlag:
def __init__(self, flag_name, rollout_percentage=0):
self.flag_name = flag_name
self.rollout_percentage = rollout_percentage
def is_enabled_for_user(self, user_id):
hash_value = hash(f"{self.flag_name}:{user_id}")
return (hash_value % 100) < self.rollout_percentage
def gradual_rollout(self, target_percentage, step_size=10):
while self.rollout_percentage < target_percentage:
self.rollout_percentage = min(
self.rollout_percentage + step_size,
target_percentage
)
yield self.rollout_percentage
```
### Circuit Breaker Pattern
Implement automatic fallback to legacy systems when new systems show degraded performance:
```python
class MigrationCircuitBreaker:
def __init__(self, failure_threshold=5, timeout=60):
self.failure_count = 0
self.failure_threshold = failure_threshold
self.timeout = timeout
self.last_failure_time = None
self.state = 'CLOSED' # CLOSED, OPEN, HALF_OPEN
def call_new_service(self, request):
if self.state == 'OPEN':
if self.should_attempt_reset():
self.state = 'HALF_OPEN'
else:
return self.fallback_to_legacy(request)
try:
response = self.new_service.process(request)
self.on_success()
return response
except Exception as e:
self.on_failure()
return self.fallback_to_legacy(request)
```
## Data Validation and Reconciliation
### Validation Strategies
1. **Row Count Validation**
- Compare record counts between source and target
- Account for soft deletes and filtered records
- Implement threshold-based alerting
2. **Checksums and Hashing**
- Generate checksums for critical data subsets
- Compare hash values to detect data drift
- Use sampling for large datasets
3. **Business Logic Validation**
- Run critical business queries on both systems
- Compare aggregate results (sums, counts, averages)
- Validate derived data and calculations
### Reconciliation Patterns
1. **Delta Detection**
```sql
-- Example delta query for reconciliation
SELECT 'missing_in_target' as issue_type, source_id
FROM source_table s
WHERE NOT EXISTS (
SELECT 1 FROM target_table t
WHERE t.id = s.id
)
UNION ALL
SELECT 'extra_in_target' as issue_type, target_id
FROM target_table t
WHERE NOT EXISTS (
SELECT 1 FROM source_table s
WHERE s.id = t.id
);
```
2. **Automated Correction**
- Implement data repair scripts for common issues
- Use idempotent operations for safe re-execution
- Log all correction actions for audit trails
## Rollback Strategies
### Database Rollback
1. **Schema Rollback**
- Maintain schema version control
- Use backward-compatible migrations when possible
- Keep rollback scripts for each migration step
2. **Data Rollback**
- Point-in-time recovery using database backups
- Transaction log replay for precise rollback points
- Maintain data snapshots at migration checkpoints
### Service Rollback
1. **Blue-Green Deployment**
- Keep previous service version running during migration
- Switch traffic back to blue environment if issues arise
- Maintain parallel infrastructure during migration window
2. **Rolling Rollback**
- Gradually shift traffic back to previous version
- Monitor system health during rollback process
- Implement automated rollback triggers
### Infrastructure Rollback
1. **Infrastructure as Code**
- Version control all infrastructure definitions
- Maintain rollback terraform/CloudFormation templates
- Test rollback procedures in staging environments
2. **Data Persistence**
- Preserve data in original location during migration
- Implement data sync back to original systems
- Maintain backup strategies across both environments
## Risk Assessment Framework
### Risk Categories
1. **Technical Risks**
- Data loss or corruption
- Service downtime or degraded performance
- Integration failures with dependent systems
- Scalability issues under production load
2. **Business Risks**
- Revenue impact from service disruption
- Customer experience degradation
- Compliance and regulatory concerns
- Brand reputation impact
3. **Operational Risks**
- Team knowledge gaps
- Insufficient testing coverage
- Inadequate monitoring and alerting
- Communication breakdowns
### Risk Mitigation Strategies
1. **Technical Mitigations**
- Comprehensive testing (unit, integration, load, chaos)
- Gradual rollout with automated rollback triggers
- Data validation and reconciliation processes
- Performance monitoring and alerting
2. **Business Mitigations**
- Stakeholder communication plans
- Business continuity procedures
- Customer notification strategies
- Revenue protection measures
3. **Operational Mitigations**
- Team training and documentation
- Runbook creation and testing
- On-call rotation planning
- Post-migration review processes
## Migration Runbooks
### Pre-Migration Checklist
- [ ] Migration plan reviewed and approved
- [ ] Rollback procedures tested and validated
- [ ] Monitoring and alerting configured
- [ ] Team roles and responsibilities defined
- [ ] Stakeholder communication plan activated
- [ ] Backup and recovery procedures verified
- [ ] Test environment validation complete
- [ ] Performance benchmarks established
- [ ] Security review completed
- [ ] Compliance requirements verified
### During Migration
- [ ] Execute migration phases in planned order
- [ ] Monitor key performance indicators continuously
- [ ] Validate data consistency at each checkpoint
- [ ] Communicate progress to stakeholders
- [ ] Document any deviations from plan
- [ ] Execute rollback if success criteria not met
- [ ] Coordinate with dependent teams
- [ ] Maintain detailed execution logs
### Post-Migration
- [ ] Validate all success criteria met
- [ ] Perform comprehensive system health checks
- [ ] Execute data reconciliation procedures
- [ ] Monitor system performance over 72 hours
- [ ] Update documentation and runbooks
- [ ] Decommission legacy systems (if applicable)
- [ ] Conduct post-migration retrospective
- [ ] Archive migration artifacts
- [ ] Update disaster recovery procedures
## Communication Templates
### Executive Summary Template
```
Migration Status: [IN_PROGRESS | COMPLETED | ROLLED_BACK]
Start Time: [YYYY-MM-DD HH:MM UTC]
Current Phase: [X of Y]
Overall Progress: [X%]
Key Metrics:
- System Availability: [X.XX%]
- Data Migration Progress: [X.XX%]
- Performance Impact: [+/-X%]
- Issues Encountered: [X]
Next Steps:
1. [Action item 1]
2. [Action item 2]
Risk Assessment: [LOW | MEDIUM | HIGH]
Rollback Status: [AVAILABLE | NOT_AVAILABLE]
```
### Technical Team Update Template
```
Phase: [Phase Name] - [Status]
Duration: [Started] - [Expected End]
Completed Tasks:
✓ [Task 1]
✓ [Task 2]
In Progress:
🔄 [Task 3] - [X% complete]
Upcoming:
⏳ [Task 4] - [Expected start time]
Issues:
⚠️ [Issue description] - [Severity] - [ETA resolution]
Metrics:
- Migration Rate: [X records/minute]
- Error Rate: [X.XX%]
- System Load: [CPU/Memory/Disk]
```
## Success Metrics
### Technical Metrics
- **Migration Completion Rate:** Percentage of data/services successfully migrated
- **Downtime Duration:** Total system unavailability during migration
- **Data Consistency Score:** Percentage of data validation checks passing
- **Performance Delta:** Performance change compared to baseline
- **Error Rate:** Percentage of failed operations during migration
### Business Metrics
- **Customer Impact Score:** Measure of customer experience degradation
- **Revenue Protection:** Percentage of revenue maintained during migration
- **Time to Value:** Duration from migration start to business value realization
- **Stakeholder Satisfaction:** Post-migration stakeholder feedback scores
### Operational Metrics
- **Plan Adherence:** Percentage of migration executed according to plan
- **Issue Resolution Time:** Average time to resolve migration issues
- **Team Efficiency:** Resource utilization and productivity metrics
- **Knowledge Transfer Score:** Team readiness for post-migration operations
## Tools and Technologies
### Migration Planning Tools
- **migration_planner.py:** Automated migration plan generation
- **compatibility_checker.py:** Schema and API compatibility analysis
- **rollback_generator.py:** Comprehensive rollback procedure generation
### Validation Tools
- Database comparison utilities (schema and data)
- API contract testing frameworks
- Performance benchmarking tools
- Data quality validation pipelines
### Monitoring and Alerting
- Real-time migration progress dashboards
- Automated rollback trigger systems
- Business metric monitoring
- Stakeholder notification systems
## Best Practices
### Planning Phase
1. **Start with Risk Assessment:** Identify all potential failure modes before planning
2. **Design for Rollback:** Every migration step should have a tested rollback procedure
3. **Validate in Staging:** Execute full migration process in production-like environment
4. **Plan for Gradual Rollout:** Use feature flags and traffic routing for controlled migration
### Execution Phase
1. **Monitor Continuously:** Track both technical and business metrics throughout
2. **Communicate Proactively:** Keep all stakeholders informed of progress and issues
3. **Document Everything:** Maintain detailed logs for post-migration analysis
4. **Stay Flexible:** Be prepared to adjust timeline based on real-world performance
### Validation Phase
1. **Automate Validation:** Use automated tools for data consistency and performance checks
2. **Business Logic Testing:** Validate critical business processes end-to-end
3. **Load Testing:** Verify system performance under expected production load
4. **Security Validation:** Ensure security controls function properly in new environment
## Integration with Development Lifecycle
### CI/CD Integration
```yaml
# Example migration pipeline stage
migration_validation:
stage: test
script:
- python scripts/compatibility_checker.py --before=old_schema.json --after=new_schema.json
- python scripts/migration_planner.py --config=migration_config.json --validate
artifacts:
reports:
- compatibility_report.json
- migration_plan.json
```
### Infrastructure as Code
```terraform
# Example Terraform for blue-green infrastructure
resource "aws_instance" "blue_environment" {
count = var.migration_phase == "preparation" ? var.instance_count : 0
# Blue environment configuration
}
resource "aws_instance" "green_environment" {
count = var.migration_phase == "execution" ? var.instance_count : 0
# Green environment configuration
}
```
This Migration Architect skill provides a comprehensive framework for planning, executing, and validating complex system migrations while minimizing business impact and technical risk. The combination of automated tools, proven patterns, and detailed procedures enables organizations to confidently undertake even the most complex migration projects.

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{
"schema_version": "2.0",
"database": "user_management_v2",
"tables": {
"users": {
"columns": {
"id": {
"type": "bigint",
"nullable": false,
"primary_key": true,
"auto_increment": true
},
"username": {
"type": "varchar",
"length": 50,
"nullable": false,
"unique": true
},
"email": {
"type": "varchar",
"length": 320,
"nullable": false,
"unique": true
},
"password_hash": {
"type": "varchar",
"length": 255,
"nullable": false
},
"first_name": {
"type": "varchar",
"length": 100,
"nullable": true
},
"last_name": {
"type": "varchar",
"length": 100,
"nullable": true
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"updated_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
},
"is_active": {
"type": "boolean",
"nullable": false,
"default": true
},
"phone": {
"type": "varchar",
"length": 20,
"nullable": true
},
"email_verified_at": {
"type": "timestamp",
"nullable": true,
"comment": "When email was verified"
},
"phone_verified_at": {
"type": "timestamp",
"nullable": true,
"comment": "When phone was verified"
},
"two_factor_enabled": {
"type": "boolean",
"nullable": false,
"default": false
},
"last_login_at": {
"type": "timestamp",
"nullable": true
}
},
"constraints": {
"primary_key": ["id"],
"unique": [
"username",
"email"
],
"foreign_key": [],
"check": [
"email LIKE '%@%'",
"LENGTH(password_hash) >= 60",
"phone IS NULL OR LENGTH(phone) >= 10"
]
},
"indexes": [
{
"name": "idx_users_email",
"columns": ["email"],
"unique": true
},
{
"name": "idx_users_username",
"columns": ["username"],
"unique": true
},
{
"name": "idx_users_created_at",
"columns": ["created_at"]
},
{
"name": "idx_users_email_verified",
"columns": ["email_verified_at"]
},
{
"name": "idx_users_last_login",
"columns": ["last_login_at"]
}
]
},
"user_profiles": {
"columns": {
"id": {
"type": "bigint",
"nullable": false,
"primary_key": true,
"auto_increment": true
},
"user_id": {
"type": "bigint",
"nullable": false
},
"bio": {
"type": "text",
"nullable": true
},
"avatar_url": {
"type": "varchar",
"length": 500,
"nullable": true
},
"birth_date": {
"type": "date",
"nullable": true
},
"location": {
"type": "varchar",
"length": 100,
"nullable": true
},
"website": {
"type": "varchar",
"length": 255,
"nullable": true
},
"privacy_level": {
"type": "varchar",
"length": 20,
"nullable": false,
"default": "public"
},
"timezone": {
"type": "varchar",
"length": 50,
"nullable": true,
"default": "UTC"
},
"language": {
"type": "varchar",
"length": 10,
"nullable": false,
"default": "en"
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"updated_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
}
},
"constraints": {
"primary_key": ["id"],
"unique": [],
"foreign_key": [
{
"columns": ["user_id"],
"references": "users(id)",
"on_delete": "CASCADE"
}
],
"check": [
"privacy_level IN ('public', 'private', 'friends_only')",
"bio IS NULL OR LENGTH(bio) <= 2000",
"language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh')"
]
},
"indexes": [
{
"name": "idx_user_profiles_user_id",
"columns": ["user_id"],
"unique": true
},
{
"name": "idx_user_profiles_privacy",
"columns": ["privacy_level"]
},
{
"name": "idx_user_profiles_language",
"columns": ["language"]
}
]
},
"user_sessions": {
"columns": {
"id": {
"type": "varchar",
"length": 128,
"nullable": false,
"primary_key": true
},
"user_id": {
"type": "bigint",
"nullable": false
},
"ip_address": {
"type": "varchar",
"length": 45,
"nullable": true
},
"user_agent": {
"type": "text",
"nullable": true
},
"expires_at": {
"type": "timestamp",
"nullable": false
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"last_activity": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
},
"session_type": {
"type": "varchar",
"length": 20,
"nullable": false,
"default": "web"
},
"is_mobile": {
"type": "boolean",
"nullable": false,
"default": false
}
},
"constraints": {
"primary_key": ["id"],
"unique": [],
"foreign_key": [
{
"columns": ["user_id"],
"references": "users(id)",
"on_delete": "CASCADE"
}
],
"check": [
"session_type IN ('web', 'mobile', 'api', 'admin')"
]
},
"indexes": [
{
"name": "idx_user_sessions_user_id",
"columns": ["user_id"]
},
{
"name": "idx_user_sessions_expires",
"columns": ["expires_at"]
},
{
"name": "idx_user_sessions_type",
"columns": ["session_type"]
}
]
},
"user_preferences": {
"columns": {
"id": {
"type": "bigint",
"nullable": false,
"primary_key": true,
"auto_increment": true
},
"user_id": {
"type": "bigint",
"nullable": false
},
"preference_key": {
"type": "varchar",
"length": 100,
"nullable": false
},
"preference_value": {
"type": "json",
"nullable": true
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"updated_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
}
},
"constraints": {
"primary_key": ["id"],
"unique": [
["user_id", "preference_key"]
],
"foreign_key": [
{
"columns": ["user_id"],
"references": "users(id)",
"on_delete": "CASCADE"
}
],
"check": []
},
"indexes": [
{
"name": "idx_user_preferences_user_key",
"columns": ["user_id", "preference_key"],
"unique": true
}
]
}
},
"views": {
"active_users": {
"definition": "SELECT u.id, u.username, u.email, u.first_name, u.last_name, u.email_verified_at, u.last_login_at FROM users u WHERE u.is_active = true",
"columns": ["id", "username", "email", "first_name", "last_name", "email_verified_at", "last_login_at"]
},
"verified_users": {
"definition": "SELECT u.id, u.username, u.email FROM users u WHERE u.is_active = true AND u.email_verified_at IS NOT NULL",
"columns": ["id", "username", "email"]
}
},
"procedures": [
{
"name": "cleanup_expired_sessions",
"parameters": [],
"definition": "DELETE FROM user_sessions WHERE expires_at < NOW()"
},
{
"name": "get_user_with_profile",
"parameters": ["user_id BIGINT"],
"definition": "SELECT u.*, p.bio, p.avatar_url, p.privacy_level FROM users u LEFT JOIN user_profiles p ON u.id = p.user_id WHERE u.id = user_id"
}
]
}

View File

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{
"schema_version": "1.0",
"database": "user_management",
"tables": {
"users": {
"columns": {
"id": {
"type": "bigint",
"nullable": false,
"primary_key": true,
"auto_increment": true
},
"username": {
"type": "varchar",
"length": 50,
"nullable": false,
"unique": true
},
"email": {
"type": "varchar",
"length": 255,
"nullable": false,
"unique": true
},
"password_hash": {
"type": "varchar",
"length": 255,
"nullable": false
},
"first_name": {
"type": "varchar",
"length": 100,
"nullable": true
},
"last_name": {
"type": "varchar",
"length": 100,
"nullable": true
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"updated_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
},
"is_active": {
"type": "boolean",
"nullable": false,
"default": true
},
"phone": {
"type": "varchar",
"length": 20,
"nullable": true
}
},
"constraints": {
"primary_key": ["id"],
"unique": [
"username",
"email"
],
"foreign_key": [],
"check": [
"email LIKE '%@%'",
"LENGTH(password_hash) >= 60"
]
},
"indexes": [
{
"name": "idx_users_email",
"columns": ["email"],
"unique": true
},
{
"name": "idx_users_username",
"columns": ["username"],
"unique": true
},
{
"name": "idx_users_created_at",
"columns": ["created_at"]
}
]
},
"user_profiles": {
"columns": {
"id": {
"type": "bigint",
"nullable": false,
"primary_key": true,
"auto_increment": true
},
"user_id": {
"type": "bigint",
"nullable": false
},
"bio": {
"type": "varchar",
"length": 255,
"nullable": true
},
"avatar_url": {
"type": "varchar",
"length": 500,
"nullable": true
},
"birth_date": {
"type": "date",
"nullable": true
},
"location": {
"type": "varchar",
"length": 100,
"nullable": true
},
"website": {
"type": "varchar",
"length": 255,
"nullable": true
},
"privacy_level": {
"type": "varchar",
"length": 20,
"nullable": false,
"default": "public"
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"updated_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
}
},
"constraints": {
"primary_key": ["id"],
"unique": [],
"foreign_key": [
{
"columns": ["user_id"],
"references": "users(id)",
"on_delete": "CASCADE"
}
],
"check": [
"privacy_level IN ('public', 'private', 'friends_only')"
]
},
"indexes": [
{
"name": "idx_user_profiles_user_id",
"columns": ["user_id"],
"unique": true
},
{
"name": "idx_user_profiles_privacy",
"columns": ["privacy_level"]
}
]
},
"user_sessions": {
"columns": {
"id": {
"type": "varchar",
"length": 128,
"nullable": false,
"primary_key": true
},
"user_id": {
"type": "bigint",
"nullable": false
},
"ip_address": {
"type": "varchar",
"length": 45,
"nullable": true
},
"user_agent": {
"type": "varchar",
"length": 500,
"nullable": true
},
"expires_at": {
"type": "timestamp",
"nullable": false
},
"created_at": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP"
},
"last_activity": {
"type": "timestamp",
"nullable": false,
"default": "CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP"
}
},
"constraints": {
"primary_key": ["id"],
"unique": [],
"foreign_key": [
{
"columns": ["user_id"],
"references": "users(id)",
"on_delete": "CASCADE"
}
],
"check": []
},
"indexes": [
{
"name": "idx_user_sessions_user_id",
"columns": ["user_id"]
},
{
"name": "idx_user_sessions_expires",
"columns": ["expires_at"]
}
]
}
},
"views": {
"active_users": {
"definition": "SELECT u.id, u.username, u.email, u.first_name, u.last_name FROM users u WHERE u.is_active = true",
"columns": ["id", "username", "email", "first_name", "last_name"]
}
},
"procedures": [
{
"name": "cleanup_expired_sessions",
"parameters": [],
"definition": "DELETE FROM user_sessions WHERE expires_at < NOW()"
}
]
}

View File

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{
"type": "database",
"pattern": "schema_change",
"source": "PostgreSQL 13 Production Database",
"target": "PostgreSQL 15 Cloud Database",
"description": "Migrate user management system from on-premises PostgreSQL to cloud with schema updates",
"constraints": {
"max_downtime_minutes": 30,
"data_volume_gb": 2500,
"dependencies": [
"user_service_api",
"authentication_service",
"notification_service",
"analytics_pipeline",
"backup_service"
],
"compliance_requirements": [
"GDPR",
"SOX"
],
"special_requirements": [
"zero_data_loss",
"referential_integrity",
"performance_baseline_maintained"
]
},
"tables_to_migrate": [
{
"name": "users",
"row_count": 1500000,
"size_mb": 450,
"critical": true
},
{
"name": "user_profiles",
"row_count": 1500000,
"size_mb": 890,
"critical": true
},
{
"name": "user_sessions",
"row_count": 25000000,
"size_mb": 1200,
"critical": false
},
{
"name": "audit_logs",
"row_count": 50000000,
"size_mb": 2800,
"critical": false
}
],
"schema_changes": [
{
"table": "users",
"changes": [
{
"type": "add_column",
"column": "email_verified_at",
"data_type": "timestamp",
"nullable": true
},
{
"type": "add_column",
"column": "phone_verified_at",
"data_type": "timestamp",
"nullable": true
}
]
},
{
"table": "user_profiles",
"changes": [
{
"type": "modify_column",
"column": "bio",
"old_type": "varchar(255)",
"new_type": "text"
},
{
"type": "add_constraint",
"constraint_type": "check",
"constraint_name": "bio_length_check",
"definition": "LENGTH(bio) <= 2000"
}
]
}
],
"performance_requirements": {
"max_query_response_time_ms": 100,
"concurrent_connections": 500,
"transactions_per_second": 1000
},
"business_continuity": {
"critical_business_hours": {
"start": "08:00",
"end": "18:00",
"timezone": "UTC"
},
"preferred_migration_window": {
"start": "02:00",
"end": "06:00",
"timezone": "UTC"
}
}
}

View File

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{
"type": "service",
"pattern": "strangler_fig",
"source": "Legacy User Service (Java Spring Boot 2.x)",
"target": "New User Service (Node.js + TypeScript)",
"description": "Migrate legacy user management service to modern microservices architecture",
"constraints": {
"max_downtime_minutes": 0,
"data_volume_gb": 50,
"dependencies": [
"payment_service",
"order_service",
"notification_service",
"analytics_service",
"mobile_app_v1",
"mobile_app_v2",
"web_frontend",
"admin_dashboard"
],
"compliance_requirements": [
"PCI_DSS",
"GDPR"
],
"special_requirements": [
"api_backward_compatibility",
"session_continuity",
"rate_limit_preservation"
]
},
"service_details": {
"legacy_service": {
"endpoints": [
"GET /api/v1/users/{id}",
"POST /api/v1/users",
"PUT /api/v1/users/{id}",
"DELETE /api/v1/users/{id}",
"GET /api/v1/users/{id}/profile",
"PUT /api/v1/users/{id}/profile",
"POST /api/v1/users/{id}/verify-email",
"POST /api/v1/users/login",
"POST /api/v1/users/logout"
],
"current_load": {
"requests_per_second": 850,
"peak_requests_per_second": 2000,
"average_response_time_ms": 120,
"p95_response_time_ms": 300
},
"infrastructure": {
"instances": 4,
"cpu_cores_per_instance": 4,
"memory_gb_per_instance": 8,
"load_balancer": "AWS ELB Classic"
}
},
"new_service": {
"endpoints": [
"GET /api/v2/users/{id}",
"POST /api/v2/users",
"PUT /api/v2/users/{id}",
"DELETE /api/v2/users/{id}",
"GET /api/v2/users/{id}/profile",
"PUT /api/v2/users/{id}/profile",
"POST /api/v2/users/{id}/verify-email",
"POST /api/v2/users/{id}/verify-phone",
"POST /api/v2/auth/login",
"POST /api/v2/auth/logout",
"POST /api/v2/auth/refresh"
],
"target_performance": {
"requests_per_second": 1500,
"peak_requests_per_second": 3000,
"average_response_time_ms": 80,
"p95_response_time_ms": 200
},
"infrastructure": {
"container_platform": "Kubernetes",
"initial_replicas": 3,
"max_replicas": 10,
"cpu_request_millicores": 500,
"cpu_limit_millicores": 1000,
"memory_request_mb": 512,
"memory_limit_mb": 1024,
"load_balancer": "AWS ALB"
}
}
},
"migration_phases": [
{
"phase": "preparation",
"description": "Deploy new service and configure routing",
"estimated_duration_hours": 8
},
{
"phase": "intercept",
"description": "Configure API gateway to route to new service",
"estimated_duration_hours": 2
},
{
"phase": "gradual_migration",
"description": "Gradually increase traffic to new service",
"estimated_duration_hours": 48
},
{
"phase": "validation",
"description": "Validate new service performance and functionality",
"estimated_duration_hours": 24
},
{
"phase": "decommission",
"description": "Remove legacy service after validation",
"estimated_duration_hours": 4
}
],
"feature_flags": [
{
"name": "enable_new_user_service",
"description": "Route user service requests to new implementation",
"initial_percentage": 5,
"rollout_schedule": [
{"percentage": 5, "duration_hours": 24},
{"percentage": 25, "duration_hours": 24},
{"percentage": 50, "duration_hours": 24},
{"percentage": 100, "duration_hours": 0}
]
},
{
"name": "enable_new_auth_endpoints",
"description": "Enable new authentication endpoints",
"initial_percentage": 0,
"rollout_schedule": [
{"percentage": 10, "duration_hours": 12},
{"percentage": 50, "duration_hours": 12},
{"percentage": 100, "duration_hours": 0}
]
}
],
"monitoring": {
"critical_metrics": [
"request_rate",
"error_rate",
"response_time_p95",
"response_time_p99",
"cpu_utilization",
"memory_utilization",
"database_connection_pool"
],
"alert_thresholds": {
"error_rate": 0.05,
"response_time_p95": 250,
"cpu_utilization": 0.80,
"memory_utilization": 0.85
}
},
"rollback_triggers": [
{
"metric": "error_rate",
"threshold": 0.10,
"duration_minutes": 5,
"action": "automatic_rollback"
},
{
"metric": "response_time_p95",
"threshold": 500,
"duration_minutes": 10,
"action": "alert_team"
},
{
"metric": "cpu_utilization",
"threshold": 0.95,
"duration_minutes": 5,
"action": "scale_up"
}
]
}

View File

@@ -0,0 +1,577 @@
{
"runbook_id": "rb_921c0bca",
"migration_id": "23a52ed1507f",
"created_at": "2026-02-16T13:47:31.108500",
"rollback_phases": [
{
"phase_name": "rollback_cleanup",
"description": "Rollback changes made during cleanup phase",
"urgency_level": "medium",
"estimated_duration_minutes": 570,
"prerequisites": [
"Incident commander assigned and briefed",
"All team members notified of rollback initiation",
"Monitoring systems confirmed operational",
"Backup systems verified and accessible"
],
"steps": [
{
"step_id": "rb_validate_0_final",
"name": "Validate rollback completion",
"description": "Comprehensive validation that cleanup rollback completed successfully",
"script_type": "manual",
"script_content": "Execute validation checklist for this phase",
"estimated_duration_minutes": 10,
"dependencies": [],
"validation_commands": [
"SELECT COUNT(*) FROM {table_name};",
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';",
"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{column_name}';",
"SELECT COUNT(DISTINCT {primary_key}) FROM {table_name};",
"SELECT MAX({timestamp_column}) FROM {table_name};"
],
"success_criteria": [
"cleanup fully rolled back",
"All validation checks pass"
],
"failure_escalation": "Investigate cleanup rollback failures",
"rollback_order": 99
}
],
"validation_checkpoints": [
"cleanup rollback steps completed",
"System health checks passing",
"No critical errors in logs",
"Key metrics within acceptable ranges",
"Validation command passed: SELECT COUNT(*) FROM {table_name};...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH..."
],
"communication_requirements": [
"Notify incident commander of phase start/completion",
"Update rollback status dashboard",
"Log all actions and decisions"
],
"risk_level": "medium"
},
{
"phase_name": "rollback_contract",
"description": "Rollback changes made during contract phase",
"urgency_level": "medium",
"estimated_duration_minutes": 570,
"prerequisites": [
"Incident commander assigned and briefed",
"All team members notified of rollback initiation",
"Monitoring systems confirmed operational",
"Backup systems verified and accessible",
"Previous rollback phase completed successfully"
],
"steps": [
{
"step_id": "rb_validate_1_final",
"name": "Validate rollback completion",
"description": "Comprehensive validation that contract rollback completed successfully",
"script_type": "manual",
"script_content": "Execute validation checklist for this phase",
"estimated_duration_minutes": 10,
"dependencies": [],
"validation_commands": [
"SELECT COUNT(*) FROM {table_name};",
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';",
"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{column_name}';",
"SELECT COUNT(DISTINCT {primary_key}) FROM {table_name};",
"SELECT MAX({timestamp_column}) FROM {table_name};"
],
"success_criteria": [
"contract fully rolled back",
"All validation checks pass"
],
"failure_escalation": "Investigate contract rollback failures",
"rollback_order": 99
}
],
"validation_checkpoints": [
"contract rollback steps completed",
"System health checks passing",
"No critical errors in logs",
"Key metrics within acceptable ranges",
"Validation command passed: SELECT COUNT(*) FROM {table_name};...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH..."
],
"communication_requirements": [
"Notify incident commander of phase start/completion",
"Update rollback status dashboard",
"Log all actions and decisions"
],
"risk_level": "medium"
},
{
"phase_name": "rollback_migrate",
"description": "Rollback changes made during migrate phase",
"urgency_level": "medium",
"estimated_duration_minutes": 570,
"prerequisites": [
"Incident commander assigned and briefed",
"All team members notified of rollback initiation",
"Monitoring systems confirmed operational",
"Backup systems verified and accessible",
"Previous rollback phase completed successfully"
],
"steps": [
{
"step_id": "rb_validate_2_final",
"name": "Validate rollback completion",
"description": "Comprehensive validation that migrate rollback completed successfully",
"script_type": "manual",
"script_content": "Execute validation checklist for this phase",
"estimated_duration_minutes": 10,
"dependencies": [],
"validation_commands": [
"SELECT COUNT(*) FROM {table_name};",
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';",
"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{column_name}';",
"SELECT COUNT(DISTINCT {primary_key}) FROM {table_name};",
"SELECT MAX({timestamp_column}) FROM {table_name};"
],
"success_criteria": [
"migrate fully rolled back",
"All validation checks pass"
],
"failure_escalation": "Investigate migrate rollback failures",
"rollback_order": 99
}
],
"validation_checkpoints": [
"migrate rollback steps completed",
"System health checks passing",
"No critical errors in logs",
"Key metrics within acceptable ranges",
"Validation command passed: SELECT COUNT(*) FROM {table_name};...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH..."
],
"communication_requirements": [
"Notify incident commander of phase start/completion",
"Update rollback status dashboard",
"Log all actions and decisions"
],
"risk_level": "medium"
},
{
"phase_name": "rollback_expand",
"description": "Rollback changes made during expand phase",
"urgency_level": "medium",
"estimated_duration_minutes": 570,
"prerequisites": [
"Incident commander assigned and briefed",
"All team members notified of rollback initiation",
"Monitoring systems confirmed operational",
"Backup systems verified and accessible",
"Previous rollback phase completed successfully"
],
"steps": [
{
"step_id": "rb_validate_3_final",
"name": "Validate rollback completion",
"description": "Comprehensive validation that expand rollback completed successfully",
"script_type": "manual",
"script_content": "Execute validation checklist for this phase",
"estimated_duration_minutes": 10,
"dependencies": [],
"validation_commands": [
"SELECT COUNT(*) FROM {table_name};",
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';",
"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{column_name}';",
"SELECT COUNT(DISTINCT {primary_key}) FROM {table_name};",
"SELECT MAX({timestamp_column}) FROM {table_name};"
],
"success_criteria": [
"expand fully rolled back",
"All validation checks pass"
],
"failure_escalation": "Investigate expand rollback failures",
"rollback_order": 99
}
],
"validation_checkpoints": [
"expand rollback steps completed",
"System health checks passing",
"No critical errors in logs",
"Key metrics within acceptable ranges",
"Validation command passed: SELECT COUNT(*) FROM {table_name};...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH..."
],
"communication_requirements": [
"Notify incident commander of phase start/completion",
"Update rollback status dashboard",
"Log all actions and decisions"
],
"risk_level": "medium"
},
{
"phase_name": "rollback_preparation",
"description": "Rollback changes made during preparation phase",
"urgency_level": "medium",
"estimated_duration_minutes": 570,
"prerequisites": [
"Incident commander assigned and briefed",
"All team members notified of rollback initiation",
"Monitoring systems confirmed operational",
"Backup systems verified and accessible",
"Previous rollback phase completed successfully"
],
"steps": [
{
"step_id": "rb_schema_4_01",
"name": "Drop migration artifacts",
"description": "Remove temporary migration tables and procedures",
"script_type": "sql",
"script_content": "-- Drop migration artifacts\nDROP TABLE IF EXISTS migration_log;\nDROP PROCEDURE IF EXISTS migrate_data();",
"estimated_duration_minutes": 5,
"dependencies": [],
"validation_commands": [
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name LIKE '%migration%';"
],
"success_criteria": [
"No migration artifacts remain"
],
"failure_escalation": "Manual cleanup required",
"rollback_order": 1
},
{
"step_id": "rb_validate_4_final",
"name": "Validate rollback completion",
"description": "Comprehensive validation that preparation rollback completed successfully",
"script_type": "manual",
"script_content": "Execute validation checklist for this phase",
"estimated_duration_minutes": 10,
"dependencies": [
"rb_schema_4_01"
],
"validation_commands": [
"SELECT COUNT(*) FROM {table_name};",
"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';",
"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{column_name}';",
"SELECT COUNT(DISTINCT {primary_key}) FROM {table_name};",
"SELECT MAX({timestamp_column}) FROM {table_name};"
],
"success_criteria": [
"preparation fully rolled back",
"All validation checks pass"
],
"failure_escalation": "Investigate preparation rollback failures",
"rollback_order": 99
}
],
"validation_checkpoints": [
"preparation rollback steps completed",
"System health checks passing",
"No critical errors in logs",
"Key metrics within acceptable ranges",
"Validation command passed: SELECT COUNT(*) FROM {table_name};...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...",
"Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH..."
],
"communication_requirements": [
"Notify incident commander of phase start/completion",
"Update rollback status dashboard",
"Log all actions and decisions"
],
"risk_level": "medium"
}
],
"trigger_conditions": [
{
"trigger_id": "error_rate_spike",
"name": "Error Rate Spike",
"condition": "error_rate > baseline * 5 for 5 minutes",
"metric_threshold": {
"metric": "error_rate",
"operator": "greater_than",
"value": "baseline_error_rate * 5",
"duration_minutes": 5
},
"evaluation_window_minutes": 5,
"auto_execute": true,
"escalation_contacts": [
"on_call_engineer",
"migration_lead"
]
},
{
"trigger_id": "response_time_degradation",
"name": "Response Time Degradation",
"condition": "p95_response_time > baseline * 3 for 10 minutes",
"metric_threshold": {
"metric": "p95_response_time",
"operator": "greater_than",
"value": "baseline_p95 * 3",
"duration_minutes": 10
},
"evaluation_window_minutes": 10,
"auto_execute": false,
"escalation_contacts": [
"performance_team",
"migration_lead"
]
},
{
"trigger_id": "availability_drop",
"name": "Service Availability Drop",
"condition": "availability < 95% for 2 minutes",
"metric_threshold": {
"metric": "availability",
"operator": "less_than",
"value": 0.95,
"duration_minutes": 2
},
"evaluation_window_minutes": 2,
"auto_execute": true,
"escalation_contacts": [
"sre_team",
"incident_commander"
]
},
{
"trigger_id": "data_integrity_failure",
"name": "Data Integrity Check Failure",
"condition": "data_validation_failures > 0",
"metric_threshold": {
"metric": "data_validation_failures",
"operator": "greater_than",
"value": 0,
"duration_minutes": 1
},
"evaluation_window_minutes": 1,
"auto_execute": true,
"escalation_contacts": [
"dba_team",
"data_team"
]
},
{
"trigger_id": "migration_progress_stalled",
"name": "Migration Progress Stalled",
"condition": "migration_progress unchanged for 30 minutes",
"metric_threshold": {
"metric": "migration_progress_rate",
"operator": "equals",
"value": 0,
"duration_minutes": 30
},
"evaluation_window_minutes": 30,
"auto_execute": false,
"escalation_contacts": [
"migration_team",
"dba_team"
]
}
],
"data_recovery_plan": {
"recovery_method": "point_in_time",
"backup_location": "/backups/pre_migration_{migration_id}_{timestamp}.sql",
"recovery_scripts": [
"pg_restore -d production -c /backups/pre_migration_backup.sql",
"SELECT pg_create_restore_point('rollback_point');",
"VACUUM ANALYZE; -- Refresh statistics after restore"
],
"data_validation_queries": [
"SELECT COUNT(*) FROM critical_business_table;",
"SELECT MAX(created_at) FROM audit_log;",
"SELECT COUNT(DISTINCT user_id) FROM user_sessions;",
"SELECT SUM(amount) FROM financial_transactions WHERE date = CURRENT_DATE;"
],
"estimated_recovery_time_minutes": 45,
"recovery_dependencies": [
"database_instance_running",
"backup_file_accessible"
]
},
"communication_templates": [
{
"template_type": "rollback_start",
"audience": "technical",
"subject": "ROLLBACK INITIATED: {migration_name}",
"body": "Team,\n\nWe have initiated rollback for migration: {migration_name}\nRollback ID: {rollback_id}\nStart Time: {start_time}\nEstimated Duration: {estimated_duration}\n\nReason: {rollback_reason}\n\nCurrent Status: Rolling back phase {current_phase}\n\nNext Updates: Every 15 minutes or upon phase completion\n\nActions Required:\n- Monitor system health dashboards\n- Stand by for escalation if needed\n- Do not make manual changes during rollback\n\nIncident Commander: {incident_commander}\n",
"urgency": "medium",
"delivery_methods": [
"email",
"slack"
]
},
{
"template_type": "rollback_start",
"audience": "business",
"subject": "System Rollback In Progress - {system_name}",
"body": "Business Stakeholders,\n\nWe are currently performing a planned rollback of the {system_name} migration due to {rollback_reason}.\n\nImpact: {business_impact}\nExpected Resolution: {estimated_completion_time}\nAffected Services: {affected_services}\n\nWe will provide updates every 30 minutes.\n\nContact: {business_contact}\n",
"urgency": "medium",
"delivery_methods": [
"email"
]
},
{
"template_type": "rollback_start",
"audience": "executive",
"subject": "EXEC ALERT: Critical System Rollback - {system_name}",
"body": "Executive Team,\n\nA critical rollback is in progress for {system_name}.\n\nSummary:\n- Rollback Reason: {rollback_reason}\n- Business Impact: {business_impact}\n- Expected Resolution: {estimated_completion_time}\n- Customer Impact: {customer_impact}\n\nWe are following established procedures and will update hourly.\n\nEscalation: {escalation_contact}\n",
"urgency": "high",
"delivery_methods": [
"email"
]
},
{
"template_type": "rollback_complete",
"audience": "technical",
"subject": "ROLLBACK COMPLETED: {migration_name}",
"body": "Team,\n\nRollback has been successfully completed for migration: {migration_name}\n\nSummary:\n- Start Time: {start_time}\n- End Time: {end_time}\n- Duration: {actual_duration}\n- Phases Completed: {completed_phases}\n\nValidation Results:\n{validation_results}\n\nSystem Status: {system_status}\n\nNext Steps:\n- Continue monitoring for 24 hours\n- Post-rollback review scheduled for {review_date}\n- Root cause analysis to begin\n\nAll clear to resume normal operations.\n\nIncident Commander: {incident_commander}\n",
"urgency": "medium",
"delivery_methods": [
"email",
"slack"
]
},
{
"template_type": "emergency_escalation",
"audience": "executive",
"subject": "CRITICAL: Rollback Emergency - {migration_name}",
"body": "CRITICAL SITUATION - IMMEDIATE ATTENTION REQUIRED\n\nMigration: {migration_name}\nIssue: Rollback procedure has encountered critical failures\n\nCurrent Status: {current_status}\nFailed Components: {failed_components}\nBusiness Impact: {business_impact}\nCustomer Impact: {customer_impact}\n\nImmediate Actions:\n1. Emergency response team activated\n2. {emergency_action_1}\n3. {emergency_action_2}\n\nWar Room: {war_room_location}\nBridge Line: {conference_bridge}\n\nNext Update: {next_update_time}\n\nIncident Commander: {incident_commander}\nExecutive On-Call: {executive_on_call}\n",
"urgency": "emergency",
"delivery_methods": [
"email",
"sms",
"phone_call"
]
}
],
"escalation_matrix": {
"level_1": {
"trigger": "Single component failure",
"response_time_minutes": 5,
"contacts": [
"on_call_engineer",
"migration_lead"
],
"actions": [
"Investigate issue",
"Attempt automated remediation",
"Monitor closely"
]
},
"level_2": {
"trigger": "Multiple component failures or single critical failure",
"response_time_minutes": 2,
"contacts": [
"senior_engineer",
"team_lead",
"devops_lead"
],
"actions": [
"Initiate rollback",
"Establish war room",
"Notify stakeholders"
]
},
"level_3": {
"trigger": "System-wide failure or data corruption",
"response_time_minutes": 1,
"contacts": [
"engineering_manager",
"cto",
"incident_commander"
],
"actions": [
"Emergency rollback",
"All hands on deck",
"Executive notification"
]
},
"emergency": {
"trigger": "Business-critical failure with customer impact",
"response_time_minutes": 0,
"contacts": [
"ceo",
"cto",
"head_of_operations"
],
"actions": [
"Emergency procedures",
"Customer communication",
"Media preparation if needed"
]
}
},
"validation_checklist": [
"Verify system is responding to health checks",
"Confirm error rates are within normal parameters",
"Validate response times meet SLA requirements",
"Check all critical business processes are functioning",
"Verify monitoring and alerting systems are operational",
"Confirm no data corruption has occurred",
"Validate security controls are functioning properly",
"Check backup systems are working correctly",
"Verify integration points with downstream systems",
"Confirm user authentication and authorization working",
"Validate database schema matches expected state",
"Confirm referential integrity constraints",
"Check database performance metrics",
"Verify data consistency across related tables",
"Validate indexes and statistics are optimal",
"Confirm transaction logs are clean",
"Check database connections and connection pooling"
],
"post_rollback_procedures": [
"Monitor system stability for 24-48 hours post-rollback",
"Conduct thorough post-rollback testing of all critical paths",
"Review and analyze rollback metrics and timing",
"Document lessons learned and rollback procedure improvements",
"Schedule post-mortem meeting with all stakeholders",
"Update rollback procedures based on actual experience",
"Communicate rollback completion to all stakeholders",
"Archive rollback logs and artifacts for future reference",
"Review and update monitoring thresholds if needed",
"Plan for next migration attempt with improved procedures",
"Conduct security review to ensure no vulnerabilities introduced",
"Update disaster recovery procedures if affected by rollback",
"Review capacity planning based on rollback resource usage",
"Update documentation with rollback experience and timings"
],
"emergency_contacts": [
{
"role": "Incident Commander",
"name": "TBD - Assigned during migration",
"primary_phone": "+1-XXX-XXX-XXXX",
"email": "incident.commander@company.com",
"backup_contact": "backup.commander@company.com"
},
{
"role": "Technical Lead",
"name": "TBD - Migration technical owner",
"primary_phone": "+1-XXX-XXX-XXXX",
"email": "tech.lead@company.com",
"backup_contact": "senior.engineer@company.com"
},
{
"role": "Business Owner",
"name": "TBD - Business stakeholder",
"primary_phone": "+1-XXX-XXX-XXXX",
"email": "business.owner@company.com",
"backup_contact": "product.manager@company.com"
},
{
"role": "On-Call Engineer",
"name": "Current on-call rotation",
"primary_phone": "+1-XXX-XXX-XXXX",
"email": "oncall@company.com",
"backup_contact": "backup.oncall@company.com"
},
{
"role": "Executive Escalation",
"name": "CTO/VP Engineering",
"primary_phone": "+1-XXX-XXX-XXXX",
"email": "cto@company.com",
"backup_contact": "vp.engineering@company.com"
}
]
}

View File

@@ -0,0 +1,282 @@
================================================================================
ROLLBACK RUNBOOK: rb_921c0bca
================================================================================
Migration ID: 23a52ed1507f
Created: 2026-02-16T13:47:31.108500
EMERGENCY CONTACTS
----------------------------------------
Incident Commander: TBD - Assigned during migration
Phone: +1-XXX-XXX-XXXX
Email: incident.commander@company.com
Backup: backup.commander@company.com
Technical Lead: TBD - Migration technical owner
Phone: +1-XXX-XXX-XXXX
Email: tech.lead@company.com
Backup: senior.engineer@company.com
Business Owner: TBD - Business stakeholder
Phone: +1-XXX-XXX-XXXX
Email: business.owner@company.com
Backup: product.manager@company.com
On-Call Engineer: Current on-call rotation
Phone: +1-XXX-XXX-XXXX
Email: oncall@company.com
Backup: backup.oncall@company.com
Executive Escalation: CTO/VP Engineering
Phone: +1-XXX-XXX-XXXX
Email: cto@company.com
Backup: vp.engineering@company.com
ESCALATION MATRIX
----------------------------------------
LEVEL_1:
Trigger: Single component failure
Response Time: 5 minutes
Contacts: on_call_engineer, migration_lead
Actions: Investigate issue, Attempt automated remediation, Monitor closely
LEVEL_2:
Trigger: Multiple component failures or single critical failure
Response Time: 2 minutes
Contacts: senior_engineer, team_lead, devops_lead
Actions: Initiate rollback, Establish war room, Notify stakeholders
LEVEL_3:
Trigger: System-wide failure or data corruption
Response Time: 1 minutes
Contacts: engineering_manager, cto, incident_commander
Actions: Emergency rollback, All hands on deck, Executive notification
EMERGENCY:
Trigger: Business-critical failure with customer impact
Response Time: 0 minutes
Contacts: ceo, cto, head_of_operations
Actions: Emergency procedures, Customer communication, Media preparation if needed
AUTOMATIC ROLLBACK TRIGGERS
----------------------------------------
• Error Rate Spike
Condition: error_rate > baseline * 5 for 5 minutes
Auto-Execute: Yes
Evaluation Window: 5 minutes
Contacts: on_call_engineer, migration_lead
• Response Time Degradation
Condition: p95_response_time > baseline * 3 for 10 minutes
Auto-Execute: No
Evaluation Window: 10 minutes
Contacts: performance_team, migration_lead
• Service Availability Drop
Condition: availability < 95% for 2 minutes
Auto-Execute: Yes
Evaluation Window: 2 minutes
Contacts: sre_team, incident_commander
• Data Integrity Check Failure
Condition: data_validation_failures > 0
Auto-Execute: Yes
Evaluation Window: 1 minutes
Contacts: dba_team, data_team
• Migration Progress Stalled
Condition: migration_progress unchanged for 30 minutes
Auto-Execute: No
Evaluation Window: 30 minutes
Contacts: migration_team, dba_team
ROLLBACK PHASES
----------------------------------------
1. ROLLBACK_CLEANUP
Description: Rollback changes made during cleanup phase
Urgency: MEDIUM
Duration: 570 minutes
Risk Level: MEDIUM
Prerequisites:
✓ Incident commander assigned and briefed
✓ All team members notified of rollback initiation
✓ Monitoring systems confirmed operational
✓ Backup systems verified and accessible
Steps:
99. Validate rollback completion
Duration: 10 min
Type: manual
Success Criteria: cleanup fully rolled back, All validation checks pass
Validation Checkpoints:
☐ cleanup rollback steps completed
☐ System health checks passing
☐ No critical errors in logs
☐ Key metrics within acceptable ranges
☐ Validation command passed: SELECT COUNT(*) FROM {table_name};...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH...
2. ROLLBACK_CONTRACT
Description: Rollback changes made during contract phase
Urgency: MEDIUM
Duration: 570 minutes
Risk Level: MEDIUM
Prerequisites:
✓ Incident commander assigned and briefed
✓ All team members notified of rollback initiation
✓ Monitoring systems confirmed operational
✓ Backup systems verified and accessible
✓ Previous rollback phase completed successfully
Steps:
99. Validate rollback completion
Duration: 10 min
Type: manual
Success Criteria: contract fully rolled back, All validation checks pass
Validation Checkpoints:
☐ contract rollback steps completed
☐ System health checks passing
☐ No critical errors in logs
☐ Key metrics within acceptable ranges
☐ Validation command passed: SELECT COUNT(*) FROM {table_name};...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH...
3. ROLLBACK_MIGRATE
Description: Rollback changes made during migrate phase
Urgency: MEDIUM
Duration: 570 minutes
Risk Level: MEDIUM
Prerequisites:
✓ Incident commander assigned and briefed
✓ All team members notified of rollback initiation
✓ Monitoring systems confirmed operational
✓ Backup systems verified and accessible
✓ Previous rollback phase completed successfully
Steps:
99. Validate rollback completion
Duration: 10 min
Type: manual
Success Criteria: migrate fully rolled back, All validation checks pass
Validation Checkpoints:
☐ migrate rollback steps completed
☐ System health checks passing
☐ No critical errors in logs
☐ Key metrics within acceptable ranges
☐ Validation command passed: SELECT COUNT(*) FROM {table_name};...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH...
4. ROLLBACK_EXPAND
Description: Rollback changes made during expand phase
Urgency: MEDIUM
Duration: 570 minutes
Risk Level: MEDIUM
Prerequisites:
✓ Incident commander assigned and briefed
✓ All team members notified of rollback initiation
✓ Monitoring systems confirmed operational
✓ Backup systems verified and accessible
✓ Previous rollback phase completed successfully
Steps:
99. Validate rollback completion
Duration: 10 min
Type: manual
Success Criteria: expand fully rolled back, All validation checks pass
Validation Checkpoints:
☐ expand rollback steps completed
☐ System health checks passing
☐ No critical errors in logs
☐ Key metrics within acceptable ranges
☐ Validation command passed: SELECT COUNT(*) FROM {table_name};...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH...
5. ROLLBACK_PREPARATION
Description: Rollback changes made during preparation phase
Urgency: MEDIUM
Duration: 570 minutes
Risk Level: MEDIUM
Prerequisites:
✓ Incident commander assigned and briefed
✓ All team members notified of rollback initiation
✓ Monitoring systems confirmed operational
✓ Backup systems verified and accessible
✓ Previous rollback phase completed successfully
Steps:
1. Drop migration artifacts
Duration: 5 min
Type: sql
Script:
-- Drop migration artifacts
DROP TABLE IF EXISTS migration_log;
DROP PROCEDURE IF EXISTS migrate_data();
Success Criteria: No migration artifacts remain
99. Validate rollback completion
Duration: 10 min
Type: manual
Success Criteria: preparation fully rolled back, All validation checks pass
Validation Checkpoints:
☐ preparation rollback steps completed
☐ System health checks passing
☐ No critical errors in logs
☐ Key metrics within acceptable ranges
☐ Validation command passed: SELECT COUNT(*) FROM {table_name};...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.tables WHE...
☐ Validation command passed: SELECT COUNT(*) FROM information_schema.columns WH...
DATA RECOVERY PLAN
----------------------------------------
Recovery Method: point_in_time
Backup Location: /backups/pre_migration_{migration_id}_{timestamp}.sql
Estimated Recovery Time: 45 minutes
Recovery Scripts:
• pg_restore -d production -c /backups/pre_migration_backup.sql
• SELECT pg_create_restore_point('rollback_point');
• VACUUM ANALYZE; -- Refresh statistics after restore
Validation Queries:
• SELECT COUNT(*) FROM critical_business_table;
• SELECT MAX(created_at) FROM audit_log;
• SELECT COUNT(DISTINCT user_id) FROM user_sessions;
• SELECT SUM(amount) FROM financial_transactions WHERE date = CURRENT_DATE;
POST-ROLLBACK VALIDATION CHECKLIST
----------------------------------------
1. ☐ Verify system is responding to health checks
2. ☐ Confirm error rates are within normal parameters
3. ☐ Validate response times meet SLA requirements
4. ☐ Check all critical business processes are functioning
5. ☐ Verify monitoring and alerting systems are operational
6. ☐ Confirm no data corruption has occurred
7. ☐ Validate security controls are functioning properly
8. ☐ Check backup systems are working correctly
9. ☐ Verify integration points with downstream systems
10. ☐ Confirm user authentication and authorization working
11. ☐ Validate database schema matches expected state
12. ☐ Confirm referential integrity constraints
13. ☐ Check database performance metrics
14. ☐ Verify data consistency across related tables
15. ☐ Validate indexes and statistics are optimal
16. ☐ Confirm transaction logs are clean
17. ☐ Check database connections and connection pooling
POST-ROLLBACK PROCEDURES
----------------------------------------
1. Monitor system stability for 24-48 hours post-rollback
2. Conduct thorough post-rollback testing of all critical paths
3. Review and analyze rollback metrics and timing
4. Document lessons learned and rollback procedure improvements
5. Schedule post-mortem meeting with all stakeholders
6. Update rollback procedures based on actual experience
7. Communicate rollback completion to all stakeholders
8. Archive rollback logs and artifacts for future reference
9. Review and update monitoring thresholds if needed
10. Plan for next migration attempt with improved procedures
11. Conduct security review to ensure no vulnerabilities introduced
12. Update disaster recovery procedures if affected by rollback
13. Review capacity planning based on rollback resource usage
14. Update documentation with rollback experience and timings

View File

@@ -0,0 +1,317 @@
{
"migration_id": "23a52ed1507f",
"source_system": "PostgreSQL 13 Production Database",
"target_system": "PostgreSQL 15 Cloud Database",
"migration_type": "database",
"complexity": "critical",
"estimated_duration_hours": 95,
"phases": [
{
"name": "preparation",
"description": "Prepare systems and teams for migration",
"duration_hours": 19,
"dependencies": [],
"validation_criteria": [
"All backups completed successfully",
"Monitoring systems operational",
"Team members briefed and ready",
"Rollback procedures tested"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Backup source system",
"Set up monitoring and alerting",
"Prepare rollback procedures",
"Communicate migration timeline",
"Validate prerequisites"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "expand",
"description": "Execute expand phase",
"duration_hours": 19,
"dependencies": [
"preparation"
],
"validation_criteria": [
"Expand phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete expand activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "migrate",
"description": "Execute migrate phase",
"duration_hours": 19,
"dependencies": [
"expand"
],
"validation_criteria": [
"Migrate phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete migrate activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "contract",
"description": "Execute contract phase",
"duration_hours": 19,
"dependencies": [
"migrate"
],
"validation_criteria": [
"Contract phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete contract activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "cleanup",
"description": "Execute cleanup phase",
"duration_hours": 19,
"dependencies": [
"contract"
],
"validation_criteria": [
"Cleanup phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete cleanup activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
}
],
"risks": [
{
"category": "technical",
"description": "Data corruption during migration",
"probability": "low",
"impact": "critical",
"severity": "high",
"mitigation": "Implement comprehensive backup and validation procedures",
"owner": "DBA Team"
},
{
"category": "technical",
"description": "Extended downtime due to migration complexity",
"probability": "medium",
"impact": "high",
"severity": "high",
"mitigation": "Use blue-green deployment and phased migration approach",
"owner": "DevOps Team"
},
{
"category": "business",
"description": "Business process disruption",
"probability": "medium",
"impact": "high",
"severity": "high",
"mitigation": "Communicate timeline and provide alternate workflows",
"owner": "Business Owner"
},
{
"category": "operational",
"description": "Insufficient rollback testing",
"probability": "high",
"impact": "critical",
"severity": "critical",
"mitigation": "Execute full rollback procedures in staging environment",
"owner": "QA Team"
},
{
"category": "business",
"description": "Zero-downtime requirement increases complexity",
"probability": "high",
"impact": "medium",
"severity": "high",
"mitigation": "Implement blue-green deployment or rolling update strategy",
"owner": "DevOps Team"
},
{
"category": "compliance",
"description": "Regulatory compliance requirements",
"probability": "medium",
"impact": "high",
"severity": "high",
"mitigation": "Ensure all compliance checks are integrated into migration process",
"owner": "Compliance Team"
}
],
"success_criteria": [
"All data successfully migrated with 100% integrity",
"System performance meets or exceeds baseline",
"All business processes functioning normally",
"No critical security vulnerabilities introduced",
"Stakeholder acceptance criteria met",
"Documentation and runbooks updated"
],
"rollback_plan": {
"rollback_phases": [
{
"phase": "cleanup",
"rollback_actions": [
"Revert cleanup changes",
"Restore pre-cleanup state",
"Validate cleanup rollback success"
],
"validation_criteria": [
"System restored to pre-cleanup state",
"All cleanup changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 285
},
{
"phase": "contract",
"rollback_actions": [
"Revert contract changes",
"Restore pre-contract state",
"Validate contract rollback success"
],
"validation_criteria": [
"System restored to pre-contract state",
"All contract changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 285
},
{
"phase": "migrate",
"rollback_actions": [
"Revert migrate changes",
"Restore pre-migrate state",
"Validate migrate rollback success"
],
"validation_criteria": [
"System restored to pre-migrate state",
"All migrate changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 285
},
{
"phase": "expand",
"rollback_actions": [
"Revert expand changes",
"Restore pre-expand state",
"Validate expand rollback success"
],
"validation_criteria": [
"System restored to pre-expand state",
"All expand changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 285
},
{
"phase": "preparation",
"rollback_actions": [
"Revert preparation changes",
"Restore pre-preparation state",
"Validate preparation rollback success"
],
"validation_criteria": [
"System restored to pre-preparation state",
"All preparation changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 285
}
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Migration timeline exceeded by > 50%",
"Business-critical functionality unavailable",
"Security breach detected",
"Stakeholder decision to abort"
],
"rollback_decision_matrix": {
"low_severity": "Continue with monitoring",
"medium_severity": "Assess and decide within 15 minutes",
"high_severity": "Immediate rollback initiation",
"critical_severity": "Emergency rollback - all hands"
},
"rollback_contacts": [
"Migration Lead",
"Technical Lead",
"Business Owner",
"On-call Engineer"
]
},
"stakeholders": [
"Business Owner",
"Technical Lead",
"DevOps Team",
"QA Team",
"Security Team",
"End Users"
],
"created_at": "2026-02-16T13:47:23.704502"
}

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================================================================================
MIGRATION PLAN: 23a52ed1507f
================================================================================
Source System: PostgreSQL 13 Production Database
Target System: PostgreSQL 15 Cloud Database
Migration Type: DATABASE
Complexity Level: CRITICAL
Estimated Duration: 95 hours (4.0 days)
Created: 2026-02-16T13:47:23.704502
MIGRATION PHASES
----------------------------------------
1. PREPARATION (19h)
Description: Prepare systems and teams for migration
Risk Level: MEDIUM
Tasks:
• Backup source system
• Set up monitoring and alerting
• Prepare rollback procedures
• Communicate migration timeline
• Validate prerequisites
Success Criteria:
✓ All backups completed successfully
✓ Monitoring systems operational
✓ Team members briefed and ready
✓ Rollback procedures tested
2. EXPAND (19h)
Description: Execute expand phase
Risk Level: MEDIUM
Dependencies: preparation
Tasks:
• Complete expand activities
Success Criteria:
✓ Expand phase completed successfully
3. MIGRATE (19h)
Description: Execute migrate phase
Risk Level: MEDIUM
Dependencies: expand
Tasks:
• Complete migrate activities
Success Criteria:
✓ Migrate phase completed successfully
4. CONTRACT (19h)
Description: Execute contract phase
Risk Level: MEDIUM
Dependencies: migrate
Tasks:
• Complete contract activities
Success Criteria:
✓ Contract phase completed successfully
5. CLEANUP (19h)
Description: Execute cleanup phase
Risk Level: MEDIUM
Dependencies: contract
Tasks:
• Complete cleanup activities
Success Criteria:
✓ Cleanup phase completed successfully
RISK ASSESSMENT
----------------------------------------
CRITICAL SEVERITY RISKS:
• Insufficient rollback testing
Category: operational
Probability: high | Impact: critical
Mitigation: Execute full rollback procedures in staging environment
Owner: QA Team
HIGH SEVERITY RISKS:
• Data corruption during migration
Category: technical
Probability: low | Impact: critical
Mitigation: Implement comprehensive backup and validation procedures
Owner: DBA Team
• Extended downtime due to migration complexity
Category: technical
Probability: medium | Impact: high
Mitigation: Use blue-green deployment and phased migration approach
Owner: DevOps Team
• Business process disruption
Category: business
Probability: medium | Impact: high
Mitigation: Communicate timeline and provide alternate workflows
Owner: Business Owner
• Zero-downtime requirement increases complexity
Category: business
Probability: high | Impact: medium
Mitigation: Implement blue-green deployment or rolling update strategy
Owner: DevOps Team
• Regulatory compliance requirements
Category: compliance
Probability: medium | Impact: high
Mitigation: Ensure all compliance checks are integrated into migration process
Owner: Compliance Team
ROLLBACK STRATEGY
----------------------------------------
Rollback Triggers:
• Critical system failure
• Data corruption detected
• Migration timeline exceeded by > 50%
• Business-critical functionality unavailable
• Security breach detected
• Stakeholder decision to abort
Rollback Phases:
CLEANUP:
- Revert cleanup changes
- Restore pre-cleanup state
- Validate cleanup rollback success
Estimated Time: 285 minutes
CONTRACT:
- Revert contract changes
- Restore pre-contract state
- Validate contract rollback success
Estimated Time: 285 minutes
MIGRATE:
- Revert migrate changes
- Restore pre-migrate state
- Validate migrate rollback success
Estimated Time: 285 minutes
EXPAND:
- Revert expand changes
- Restore pre-expand state
- Validate expand rollback success
Estimated Time: 285 minutes
PREPARATION:
- Revert preparation changes
- Restore pre-preparation state
- Validate preparation rollback success
Estimated Time: 285 minutes
SUCCESS CRITERIA
----------------------------------------
✓ All data successfully migrated with 100% integrity
✓ System performance meets or exceeds baseline
✓ All business processes functioning normally
✓ No critical security vulnerabilities introduced
✓ Stakeholder acceptance criteria met
✓ Documentation and runbooks updated
STAKEHOLDERS
----------------------------------------
• Business Owner
• Technical Lead
• DevOps Team
• QA Team
• Security Team
• End Users

View File

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{
"migration_id": "21031930da18",
"source_system": "Legacy User Service (Java Spring Boot 2.x)",
"target_system": "New User Service (Node.js + TypeScript)",
"migration_type": "service",
"complexity": "critical",
"estimated_duration_hours": 500,
"phases": [
{
"name": "intercept",
"description": "Execute intercept phase",
"duration_hours": 100,
"dependencies": [],
"validation_criteria": [
"Intercept phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete intercept activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "implement",
"description": "Execute implement phase",
"duration_hours": 100,
"dependencies": [
"intercept"
],
"validation_criteria": [
"Implement phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete implement activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "redirect",
"description": "Execute redirect phase",
"duration_hours": 100,
"dependencies": [
"implement"
],
"validation_criteria": [
"Redirect phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete redirect activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "validate",
"description": "Execute validate phase",
"duration_hours": 100,
"dependencies": [
"redirect"
],
"validation_criteria": [
"Validate phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete validate activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
},
{
"name": "retire",
"description": "Execute retire phase",
"duration_hours": 100,
"dependencies": [
"validate"
],
"validation_criteria": [
"Retire phase completed successfully"
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
],
"tasks": [
"Complete retire activities"
],
"risk_level": "medium",
"resources_required": [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
}
],
"risks": [
{
"category": "technical",
"description": "Service compatibility issues",
"probability": "medium",
"impact": "high",
"severity": "high",
"mitigation": "Implement comprehensive integration testing",
"owner": "Development Team"
},
{
"category": "technical",
"description": "Performance degradation",
"probability": "medium",
"impact": "medium",
"severity": "medium",
"mitigation": "Conduct load testing and performance benchmarking",
"owner": "DevOps Team"
},
{
"category": "business",
"description": "Feature parity gaps",
"probability": "high",
"impact": "high",
"severity": "high",
"mitigation": "Document feature mapping and acceptance criteria",
"owner": "Product Owner"
},
{
"category": "operational",
"description": "Monitoring gap during transition",
"probability": "medium",
"impact": "medium",
"severity": "medium",
"mitigation": "Set up dual monitoring and alerting systems",
"owner": "SRE Team"
},
{
"category": "business",
"description": "Zero-downtime requirement increases complexity",
"probability": "high",
"impact": "medium",
"severity": "high",
"mitigation": "Implement blue-green deployment or rolling update strategy",
"owner": "DevOps Team"
},
{
"category": "compliance",
"description": "Regulatory compliance requirements",
"probability": "medium",
"impact": "high",
"severity": "high",
"mitigation": "Ensure all compliance checks are integrated into migration process",
"owner": "Compliance Team"
}
],
"success_criteria": [
"All data successfully migrated with 100% integrity",
"System performance meets or exceeds baseline",
"All business processes functioning normally",
"No critical security vulnerabilities introduced",
"Stakeholder acceptance criteria met",
"Documentation and runbooks updated"
],
"rollback_plan": {
"rollback_phases": [
{
"phase": "retire",
"rollback_actions": [
"Revert retire changes",
"Restore pre-retire state",
"Validate retire rollback success"
],
"validation_criteria": [
"System restored to pre-retire state",
"All retire changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 1500
},
{
"phase": "validate",
"rollback_actions": [
"Revert validate changes",
"Restore pre-validate state",
"Validate validate rollback success"
],
"validation_criteria": [
"System restored to pre-validate state",
"All validate changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 1500
},
{
"phase": "redirect",
"rollback_actions": [
"Revert redirect changes",
"Restore pre-redirect state",
"Validate redirect rollback success"
],
"validation_criteria": [
"System restored to pre-redirect state",
"All redirect changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 1500
},
{
"phase": "implement",
"rollback_actions": [
"Revert implement changes",
"Restore pre-implement state",
"Validate implement rollback success"
],
"validation_criteria": [
"System restored to pre-implement state",
"All implement changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 1500
},
{
"phase": "intercept",
"rollback_actions": [
"Revert intercept changes",
"Restore pre-intercept state",
"Validate intercept rollback success"
],
"validation_criteria": [
"System restored to pre-intercept state",
"All intercept changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": 1500
}
],
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Migration timeline exceeded by > 50%",
"Business-critical functionality unavailable",
"Security breach detected",
"Stakeholder decision to abort"
],
"rollback_decision_matrix": {
"low_severity": "Continue with monitoring",
"medium_severity": "Assess and decide within 15 minutes",
"high_severity": "Immediate rollback initiation",
"critical_severity": "Emergency rollback - all hands"
},
"rollback_contacts": [
"Migration Lead",
"Technical Lead",
"Business Owner",
"On-call Engineer"
]
},
"stakeholders": [
"Business Owner",
"Technical Lead",
"DevOps Team",
"QA Team",
"Security Team",
"End Users"
],
"created_at": "2026-02-16T13:47:34.565896"
}

View File

@@ -0,0 +1,154 @@
================================================================================
MIGRATION PLAN: 21031930da18
================================================================================
Source System: Legacy User Service (Java Spring Boot 2.x)
Target System: New User Service (Node.js + TypeScript)
Migration Type: SERVICE
Complexity Level: CRITICAL
Estimated Duration: 500 hours (20.8 days)
Created: 2026-02-16T13:47:34.565896
MIGRATION PHASES
----------------------------------------
1. INTERCEPT (100h)
Description: Execute intercept phase
Risk Level: MEDIUM
Tasks:
• Complete intercept activities
Success Criteria:
✓ Intercept phase completed successfully
2. IMPLEMENT (100h)
Description: Execute implement phase
Risk Level: MEDIUM
Dependencies: intercept
Tasks:
• Complete implement activities
Success Criteria:
✓ Implement phase completed successfully
3. REDIRECT (100h)
Description: Execute redirect phase
Risk Level: MEDIUM
Dependencies: implement
Tasks:
• Complete redirect activities
Success Criteria:
✓ Redirect phase completed successfully
4. VALIDATE (100h)
Description: Execute validate phase
Risk Level: MEDIUM
Dependencies: redirect
Tasks:
• Complete validate activities
Success Criteria:
✓ Validate phase completed successfully
5. RETIRE (100h)
Description: Execute retire phase
Risk Level: MEDIUM
Dependencies: validate
Tasks:
• Complete retire activities
Success Criteria:
✓ Retire phase completed successfully
RISK ASSESSMENT
----------------------------------------
HIGH SEVERITY RISKS:
• Service compatibility issues
Category: technical
Probability: medium | Impact: high
Mitigation: Implement comprehensive integration testing
Owner: Development Team
• Feature parity gaps
Category: business
Probability: high | Impact: high
Mitigation: Document feature mapping and acceptance criteria
Owner: Product Owner
• Zero-downtime requirement increases complexity
Category: business
Probability: high | Impact: medium
Mitigation: Implement blue-green deployment or rolling update strategy
Owner: DevOps Team
• Regulatory compliance requirements
Category: compliance
Probability: medium | Impact: high
Mitigation: Ensure all compliance checks are integrated into migration process
Owner: Compliance Team
MEDIUM SEVERITY RISKS:
• Performance degradation
Category: technical
Probability: medium | Impact: medium
Mitigation: Conduct load testing and performance benchmarking
Owner: DevOps Team
• Monitoring gap during transition
Category: operational
Probability: medium | Impact: medium
Mitigation: Set up dual monitoring and alerting systems
Owner: SRE Team
ROLLBACK STRATEGY
----------------------------------------
Rollback Triggers:
• Critical system failure
• Data corruption detected
• Migration timeline exceeded by > 50%
• Business-critical functionality unavailable
• Security breach detected
• Stakeholder decision to abort
Rollback Phases:
RETIRE:
- Revert retire changes
- Restore pre-retire state
- Validate retire rollback success
Estimated Time: 1500 minutes
VALIDATE:
- Revert validate changes
- Restore pre-validate state
- Validate validate rollback success
Estimated Time: 1500 minutes
REDIRECT:
- Revert redirect changes
- Restore pre-redirect state
- Validate redirect rollback success
Estimated Time: 1500 minutes
IMPLEMENT:
- Revert implement changes
- Restore pre-implement state
- Validate implement rollback success
Estimated Time: 1500 minutes
INTERCEPT:
- Revert intercept changes
- Restore pre-intercept state
- Validate intercept rollback success
Estimated Time: 1500 minutes
SUCCESS CRITERIA
----------------------------------------
✓ All data successfully migrated with 100% integrity
✓ System performance meets or exceeds baseline
✓ All business processes functioning normally
✓ No critical security vulnerabilities introduced
✓ Stakeholder acceptance criteria met
✓ Documentation and runbooks updated
STAKEHOLDERS
----------------------------------------
• Business Owner
• Technical Lead
• DevOps Team
• QA Team
• Security Team
• End Users

View File

@@ -0,0 +1,192 @@
{
"schema_before": "{\n \"schema_version\": \"1.0\",\n \"database\": \"user_management\",\n \"tables\": {\n \"users\": {\n \"columns\": {\n \"id\": {\n \"type\": \"bigint\",\n \"nullable\": false,\n \"primary_key\": true,\n \"auto_increment\": true\n },\n \"username\": {\n \"type\": \"varchar\",\n \"length\": 50,\n \"nullable\": false,\n \"unique\": true\n },\n \"email\": {\n \"type\": \"varchar\",\n \"length\": 255,\n \"nullable\": false,\n...",
"schema_after": "{\n \"schema_version\": \"2.0\",\n \"database\": \"user_management_v2\",\n \"tables\": {\n \"users\": {\n \"columns\": {\n \"id\": {\n \"type\": \"bigint\",\n \"nullable\": false,\n \"primary_key\": true,\n \"auto_increment\": true\n },\n \"username\": {\n \"type\": \"varchar\",\n \"length\": 50,\n \"nullable\": false,\n \"unique\": true\n },\n \"email\": {\n \"type\": \"varchar\",\n \"length\": 320,\n \"nullable\": fals...",
"analysis_date": "2026-02-16T13:47:27.050459",
"overall_compatibility": "potentially_incompatible",
"breaking_changes_count": 0,
"potentially_breaking_count": 4,
"non_breaking_changes_count": 0,
"additive_changes_count": 0,
"issues": [
{
"type": "check_added",
"severity": "potentially_breaking",
"description": "New check constraint 'phone IS NULL OR LENGTH(phone) >= 10' added to table 'users'",
"field_path": "tables.users.constraints.check",
"old_value": null,
"new_value": "phone IS NULL OR LENGTH(phone) >= 10",
"impact": "New check constraint may reject existing data",
"suggested_migration": "Validate existing data complies with new constraint",
"affected_operations": [
"INSERT",
"UPDATE"
]
},
{
"type": "check_added",
"severity": "potentially_breaking",
"description": "New check constraint 'bio IS NULL OR LENGTH(bio) <= 2000' added to table 'user_profiles'",
"field_path": "tables.user_profiles.constraints.check",
"old_value": null,
"new_value": "bio IS NULL OR LENGTH(bio) <= 2000",
"impact": "New check constraint may reject existing data",
"suggested_migration": "Validate existing data complies with new constraint",
"affected_operations": [
"INSERT",
"UPDATE"
]
},
{
"type": "check_added",
"severity": "potentially_breaking",
"description": "New check constraint 'language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh')' added to table 'user_profiles'",
"field_path": "tables.user_profiles.constraints.check",
"old_value": null,
"new_value": "language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh')",
"impact": "New check constraint may reject existing data",
"suggested_migration": "Validate existing data complies with new constraint",
"affected_operations": [
"INSERT",
"UPDATE"
]
},
{
"type": "check_added",
"severity": "potentially_breaking",
"description": "New check constraint 'session_type IN ('web', 'mobile', 'api', 'admin')' added to table 'user_sessions'",
"field_path": "tables.user_sessions.constraints.check",
"old_value": null,
"new_value": "session_type IN ('web', 'mobile', 'api', 'admin')",
"impact": "New check constraint may reject existing data",
"suggested_migration": "Validate existing data complies with new constraint",
"affected_operations": [
"INSERT",
"UPDATE"
]
}
],
"migration_scripts": [
{
"script_type": "sql",
"description": "Create new table user_preferences",
"script_content": "CREATE TABLE user_preferences (\n id bigint NOT NULL,\n user_id bigint NOT NULL,\n preference_key varchar NOT NULL,\n preference_value json,\n created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,\n updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP\n);",
"rollback_script": "DROP TABLE IF EXISTS user_preferences;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.tables WHERE table_name = 'user_preferences';"
},
{
"script_type": "sql",
"description": "Add column email_verified_at to table users",
"script_content": "ALTER TABLE users ADD COLUMN email_verified_at timestamp;",
"rollback_script": "ALTER TABLE users DROP COLUMN email_verified_at;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'users' AND column_name = 'email_verified_at';"
},
{
"script_type": "sql",
"description": "Add column phone_verified_at to table users",
"script_content": "ALTER TABLE users ADD COLUMN phone_verified_at timestamp;",
"rollback_script": "ALTER TABLE users DROP COLUMN phone_verified_at;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'users' AND column_name = 'phone_verified_at';"
},
{
"script_type": "sql",
"description": "Add column two_factor_enabled to table users",
"script_content": "ALTER TABLE users ADD COLUMN two_factor_enabled boolean NOT NULL DEFAULT False;",
"rollback_script": "ALTER TABLE users DROP COLUMN two_factor_enabled;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'users' AND column_name = 'two_factor_enabled';"
},
{
"script_type": "sql",
"description": "Add column last_login_at to table users",
"script_content": "ALTER TABLE users ADD COLUMN last_login_at timestamp;",
"rollback_script": "ALTER TABLE users DROP COLUMN last_login_at;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'users' AND column_name = 'last_login_at';"
},
{
"script_type": "sql",
"description": "Add check constraint to users",
"script_content": "ALTER TABLE users ADD CONSTRAINT check_users CHECK (phone IS NULL OR LENGTH(phone) >= 10);",
"rollback_script": "ALTER TABLE users DROP CONSTRAINT check_users;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.table_constraints WHERE table_name = 'users' AND constraint_type = 'CHECK';"
},
{
"script_type": "sql",
"description": "Add column timezone to table user_profiles",
"script_content": "ALTER TABLE user_profiles ADD COLUMN timezone varchar DEFAULT UTC;",
"rollback_script": "ALTER TABLE user_profiles DROP COLUMN timezone;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'user_profiles' AND column_name = 'timezone';"
},
{
"script_type": "sql",
"description": "Add column language to table user_profiles",
"script_content": "ALTER TABLE user_profiles ADD COLUMN language varchar NOT NULL DEFAULT en;",
"rollback_script": "ALTER TABLE user_profiles DROP COLUMN language;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'user_profiles' AND column_name = 'language';"
},
{
"script_type": "sql",
"description": "Add check constraint to user_profiles",
"script_content": "ALTER TABLE user_profiles ADD CONSTRAINT check_user_profiles CHECK (bio IS NULL OR LENGTH(bio) <= 2000);",
"rollback_script": "ALTER TABLE user_profiles DROP CONSTRAINT check_user_profiles;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.table_constraints WHERE table_name = 'user_profiles' AND constraint_type = 'CHECK';"
},
{
"script_type": "sql",
"description": "Add check constraint to user_profiles",
"script_content": "ALTER TABLE user_profiles ADD CONSTRAINT check_user_profiles CHECK (language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh'));",
"rollback_script": "ALTER TABLE user_profiles DROP CONSTRAINT check_user_profiles;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.table_constraints WHERE table_name = 'user_profiles' AND constraint_type = 'CHECK';"
},
{
"script_type": "sql",
"description": "Add column session_type to table user_sessions",
"script_content": "ALTER TABLE user_sessions ADD COLUMN session_type varchar NOT NULL DEFAULT web;",
"rollback_script": "ALTER TABLE user_sessions DROP COLUMN session_type;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'user_sessions' AND column_name = 'session_type';"
},
{
"script_type": "sql",
"description": "Add column is_mobile to table user_sessions",
"script_content": "ALTER TABLE user_sessions ADD COLUMN is_mobile boolean NOT NULL DEFAULT False;",
"rollback_script": "ALTER TABLE user_sessions DROP COLUMN is_mobile;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.columns WHERE table_name = 'user_sessions' AND column_name = 'is_mobile';"
},
{
"script_type": "sql",
"description": "Add check constraint to user_sessions",
"script_content": "ALTER TABLE user_sessions ADD CONSTRAINT check_user_sessions CHECK (session_type IN ('web', 'mobile', 'api', 'admin'));",
"rollback_script": "ALTER TABLE user_sessions DROP CONSTRAINT check_user_sessions;",
"dependencies": [],
"validation_query": "SELECT COUNT(*) FROM information_schema.table_constraints WHERE table_name = 'user_sessions' AND constraint_type = 'CHECK';"
}
],
"risk_assessment": {
"overall_risk": "medium",
"deployment_risk": "safe_independent_deployment",
"rollback_complexity": "low",
"testing_requirements": [
"integration_testing",
"regression_testing",
"data_migration_testing"
]
},
"recommendations": [
"Conduct thorough testing with realistic data volumes",
"Implement monitoring for migration success metrics",
"Test all migration scripts in staging environment",
"Implement migration progress monitoring",
"Create detailed communication plan for stakeholders",
"Implement feature flags for gradual rollout"
]
}

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================================================================================
COMPATIBILITY ANALYSIS REPORT
================================================================================
Analysis Date: 2026-02-16T13:47:27.050459
Overall Compatibility: POTENTIALLY_INCOMPATIBLE
SUMMARY
----------------------------------------
Breaking Changes: 0
Potentially Breaking: 4
Non-Breaking Changes: 0
Additive Changes: 0
Total Issues Found: 4
RISK ASSESSMENT
----------------------------------------
Overall Risk: medium
Deployment Risk: safe_independent_deployment
Rollback Complexity: low
Testing Requirements: ['integration_testing', 'regression_testing', 'data_migration_testing']
POTENTIALLY BREAKING ISSUES
----------------------------------------
• New check constraint 'phone IS NULL OR LENGTH(phone) >= 10' added to table 'users'
Field: tables.users.constraints.check
Impact: New check constraint may reject existing data
Migration: Validate existing data complies with new constraint
Affected Operations: INSERT, UPDATE
• New check constraint 'bio IS NULL OR LENGTH(bio) <= 2000' added to table 'user_profiles'
Field: tables.user_profiles.constraints.check
Impact: New check constraint may reject existing data
Migration: Validate existing data complies with new constraint
Affected Operations: INSERT, UPDATE
• New check constraint 'language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh')' added to table 'user_profiles'
Field: tables.user_profiles.constraints.check
Impact: New check constraint may reject existing data
Migration: Validate existing data complies with new constraint
Affected Operations: INSERT, UPDATE
• New check constraint 'session_type IN ('web', 'mobile', 'api', 'admin')' added to table 'user_sessions'
Field: tables.user_sessions.constraints.check
Impact: New check constraint may reject existing data
Migration: Validate existing data complies with new constraint
Affected Operations: INSERT, UPDATE
SUGGESTED MIGRATION SCRIPTS
----------------------------------------
1. Create new table user_preferences
Type: sql
Script:
CREATE TABLE user_preferences (
id bigint NOT NULL,
user_id bigint NOT NULL,
preference_key varchar NOT NULL,
preference_value json,
created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
);
2. Add column email_verified_at to table users
Type: sql
Script:
ALTER TABLE users ADD COLUMN email_verified_at timestamp;
3. Add column phone_verified_at to table users
Type: sql
Script:
ALTER TABLE users ADD COLUMN phone_verified_at timestamp;
4. Add column two_factor_enabled to table users
Type: sql
Script:
ALTER TABLE users ADD COLUMN two_factor_enabled boolean NOT NULL DEFAULT False;
5. Add column last_login_at to table users
Type: sql
Script:
ALTER TABLE users ADD COLUMN last_login_at timestamp;
6. Add check constraint to users
Type: sql
Script:
ALTER TABLE users ADD CONSTRAINT check_users CHECK (phone IS NULL OR LENGTH(phone) >= 10);
7. Add column timezone to table user_profiles
Type: sql
Script:
ALTER TABLE user_profiles ADD COLUMN timezone varchar DEFAULT UTC;
8. Add column language to table user_profiles
Type: sql
Script:
ALTER TABLE user_profiles ADD COLUMN language varchar NOT NULL DEFAULT en;
9. Add check constraint to user_profiles
Type: sql
Script:
ALTER TABLE user_profiles ADD CONSTRAINT check_user_profiles CHECK (bio IS NULL OR LENGTH(bio) <= 2000);
10. Add check constraint to user_profiles
Type: sql
Script:
ALTER TABLE user_profiles ADD CONSTRAINT check_user_profiles CHECK (language IN ('en', 'es', 'fr', 'de', 'it', 'pt', 'ru', 'ja', 'ko', 'zh'));
11. Add column session_type to table user_sessions
Type: sql
Script:
ALTER TABLE user_sessions ADD COLUMN session_type varchar NOT NULL DEFAULT web;
12. Add column is_mobile to table user_sessions
Type: sql
Script:
ALTER TABLE user_sessions ADD COLUMN is_mobile boolean NOT NULL DEFAULT False;
13. Add check constraint to user_sessions
Type: sql
Script:
ALTER TABLE user_sessions ADD CONSTRAINT check_user_sessions CHECK (session_type IN ('web', 'mobile', 'api', 'admin'));
RECOMMENDATIONS
----------------------------------------
1. Conduct thorough testing with realistic data volumes
2. Implement monitoring for migration success metrics
3. Test all migration scripts in staging environment
4. Implement migration progress monitoring
5. Create detailed communication plan for stakeholders
6. Implement feature flags for gradual rollout

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# Migration Patterns Catalog
## Overview
This catalog provides detailed descriptions of proven migration patterns, their use cases, implementation guidelines, and best practices. Each pattern includes code examples, diagrams, and lessons learned from real-world implementations.
## Database Migration Patterns
### 1. Expand-Contract Pattern
**Use Case:** Schema evolution with zero downtime
**Complexity:** Medium
**Risk Level:** Low-Medium
#### Description
The Expand-Contract pattern allows for schema changes without downtime by following a three-phase approach:
1. **Expand:** Add new schema elements alongside existing ones
2. **Migrate:** Dual-write to both old and new schema during transition
3. **Contract:** Remove old schema elements after validation
#### Implementation Steps
```sql
-- Phase 1: Expand
ALTER TABLE users ADD COLUMN email_new VARCHAR(255);
CREATE INDEX CONCURRENTLY idx_users_email_new ON users(email_new);
-- Phase 2: Migrate (Application Code)
-- Write to both columns during transition period
INSERT INTO users (name, email, email_new) VALUES (?, ?, ?);
-- Backfill existing data
UPDATE users SET email_new = email WHERE email_new IS NULL;
-- Phase 3: Contract (after validation)
ALTER TABLE users DROP COLUMN email;
ALTER TABLE users RENAME COLUMN email_new TO email;
```
#### Pros and Cons
**Pros:**
- Zero downtime deployments
- Safe rollback at any point
- Gradual transition with validation
**Cons:**
- Increased storage during transition
- More complex application logic
- Extended migration timeline
### 2. Parallel Schema Pattern
**Use Case:** Major database restructuring
**Complexity:** High
**Risk Level:** Medium
#### Description
Run new and old schemas in parallel, using feature flags to gradually route traffic to the new schema while maintaining the ability to rollback quickly.
#### Implementation Example
```python
class DatabaseRouter:
def __init__(self, feature_flag_service):
self.feature_flags = feature_flag_service
self.old_db = OldDatabaseConnection()
self.new_db = NewDatabaseConnection()
def route_query(self, user_id, query_type):
if self.feature_flags.is_enabled("new_schema", user_id):
return self.new_db.execute(query_type)
else:
return self.old_db.execute(query_type)
def dual_write(self, data):
# Write to both databases for consistency
success_old = self.old_db.write(data)
success_new = self.new_db.write(transform_data(data))
if not (success_old and success_new):
# Handle partial failures
self.handle_dual_write_failure(data, success_old, success_new)
```
#### Best Practices
- Implement data consistency checks between schemas
- Use circuit breakers for automatic failover
- Monitor performance impact of dual writes
- Plan for data reconciliation processes
### 3. Event Sourcing Migration
**Use Case:** Migrating systems with complex business logic
**Complexity:** High
**Risk Level:** Medium-High
#### Description
Capture all changes as events during migration, enabling replay and reconciliation capabilities.
#### Event Store Schema
```sql
CREATE TABLE migration_events (
event_id UUID PRIMARY KEY,
aggregate_id UUID NOT NULL,
event_type VARCHAR(100) NOT NULL,
event_data JSONB NOT NULL,
event_version INTEGER NOT NULL,
occurred_at TIMESTAMP WITH TIME ZONE DEFAULT NOW(),
processed_at TIMESTAMP WITH TIME ZONE
);
```
#### Migration Event Handler
```python
class MigrationEventHandler:
def __init__(self, old_store, new_store):
self.old_store = old_store
self.new_store = new_store
self.event_log = []
def handle_update(self, entity_id, old_data, new_data):
# Log the change as an event
event = MigrationEvent(
entity_id=entity_id,
event_type="entity_migrated",
old_data=old_data,
new_data=new_data,
timestamp=datetime.now()
)
self.event_log.append(event)
# Apply to new store
success = self.new_store.update(entity_id, new_data)
if not success:
# Mark for retry
event.status = "failed"
self.schedule_retry(event)
return success
def replay_events(self, from_timestamp=None):
"""Replay events for reconciliation"""
events = self.get_events_since(from_timestamp)
for event in events:
self.apply_event(event)
```
## Service Migration Patterns
### 1. Strangler Fig Pattern
**Use Case:** Legacy system replacement
**Complexity:** Medium-High
**Risk Level:** Medium
#### Description
Gradually replace legacy functionality by intercepting calls and routing them to new services, eventually "strangling" the legacy system.
#### Implementation Architecture
```yaml
# API Gateway Configuration
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
name: user-service-migration
spec:
http:
- match:
- headers:
migration-flag:
exact: "new"
route:
- destination:
host: user-service-v2
- route:
- destination:
host: user-service-v1
```
#### Strangler Proxy Implementation
```python
class StranglerProxy:
def __init__(self):
self.legacy_service = LegacyUserService()
self.new_service = NewUserService()
self.feature_flags = FeatureFlagService()
def handle_request(self, request):
route = self.determine_route(request)
if route == "new":
return self.handle_with_new_service(request)
elif route == "both":
return self.handle_with_both_services(request)
else:
return self.handle_with_legacy_service(request)
def determine_route(self, request):
user_id = request.get('user_id')
if self.feature_flags.is_enabled("new_user_service", user_id):
if self.feature_flags.is_enabled("dual_write", user_id):
return "both"
else:
return "new"
else:
return "legacy"
```
### 2. Parallel Run Pattern
**Use Case:** Risk mitigation for critical services
**Complexity:** Medium
**Risk Level:** Low-Medium
#### Description
Run both old and new services simultaneously, comparing outputs to validate correctness before switching traffic.
#### Implementation
```python
class ParallelRunManager:
def __init__(self):
self.primary_service = PrimaryService()
self.candidate_service = CandidateService()
self.comparator = ResponseComparator()
self.metrics = MetricsCollector()
async def parallel_execute(self, request):
# Execute both services concurrently
primary_task = asyncio.create_task(
self.primary_service.process(request)
)
candidate_task = asyncio.create_task(
self.candidate_service.process(request)
)
# Always wait for primary
primary_result = await primary_task
try:
# Wait for candidate with timeout
candidate_result = await asyncio.wait_for(
candidate_task, timeout=5.0
)
# Compare results
comparison = self.comparator.compare(
primary_result, candidate_result
)
# Record metrics
self.metrics.record_comparison(comparison)
except asyncio.TimeoutError:
self.metrics.record_timeout("candidate")
except Exception as e:
self.metrics.record_error("candidate", str(e))
# Always return primary result
return primary_result
```
### 3. Blue-Green Deployment Pattern
**Use Case:** Zero-downtime service updates
**Complexity:** Low-Medium
**Risk Level:** Low
#### Description
Maintain two identical production environments (blue and green), switching traffic between them for deployments.
#### Kubernetes Implementation
```yaml
# Blue Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: app-blue
labels:
version: blue
spec:
replicas: 3
selector:
matchLabels:
app: myapp
version: blue
template:
metadata:
labels:
app: myapp
version: blue
spec:
containers:
- name: app
image: myapp:v1.0.0
---
# Green Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: app-green
labels:
version: green
spec:
replicas: 3
selector:
matchLabels:
app: myapp
version: green
template:
metadata:
labels:
app: myapp
version: green
spec:
containers:
- name: app
image: myapp:v2.0.0
---
# Service (switches between blue and green)
apiVersion: v1
kind: Service
metadata:
name: app-service
spec:
selector:
app: myapp
version: blue # Change to green for deployment
ports:
- port: 80
targetPort: 8080
```
## Infrastructure Migration Patterns
### 1. Lift and Shift Pattern
**Use Case:** Quick cloud migration with minimal changes
**Complexity:** Low-Medium
**Risk Level:** Low
#### Description
Migrate applications to cloud infrastructure with minimal or no code changes, focusing on infrastructure compatibility.
#### Migration Checklist
```yaml
Pre-Migration Assessment:
- inventory_current_infrastructure:
- servers_and_specifications
- network_configuration
- storage_requirements
- security_configurations
- identify_dependencies:
- database_connections
- external_service_integrations
- file_system_dependencies
- assess_compatibility:
- operating_system_versions
- runtime_dependencies
- license_requirements
Migration Execution:
- provision_target_infrastructure:
- compute_instances
- storage_volumes
- network_configuration
- security_groups
- migrate_data:
- database_backup_restore
- file_system_replication
- configuration_files
- update_configurations:
- connection_strings
- environment_variables
- dns_records
- validate_functionality:
- application_health_checks
- end_to_end_testing
- performance_validation
```
### 2. Hybrid Cloud Migration
**Use Case:** Gradual cloud adoption with on-premises integration
**Complexity:** High
**Risk Level:** Medium-High
#### Description
Maintain some components on-premises while migrating others to cloud, requiring secure connectivity and data synchronization.
#### Network Architecture
```hcl
# Terraform configuration for hybrid connectivity
resource "aws_vpc" "main" {
cidr_block = "10.0.0.0/16"
enable_dns_hostnames = true
enable_dns_support = true
}
resource "aws_vpn_gateway" "main" {
vpc_id = aws_vpc.main.id
tags = {
Name = "hybrid-vpn-gateway"
}
}
resource "aws_customer_gateway" "main" {
bgp_asn = 65000
ip_address = var.on_premises_public_ip
type = "ipsec.1"
tags = {
Name = "on-premises-gateway"
}
}
resource "aws_vpn_connection" "main" {
vpn_gateway_id = aws_vpn_gateway.main.id
customer_gateway_id = aws_customer_gateway.main.id
type = "ipsec.1"
static_routes_only = true
}
```
#### Data Synchronization Pattern
```python
class HybridDataSync:
def __init__(self):
self.on_prem_db = OnPremiseDatabase()
self.cloud_db = CloudDatabase()
self.sync_log = SyncLogManager()
async def bidirectional_sync(self):
"""Synchronize data between on-premises and cloud"""
# Get last sync timestamp
last_sync = self.sync_log.get_last_sync_time()
# Sync on-prem changes to cloud
on_prem_changes = self.on_prem_db.get_changes_since(last_sync)
for change in on_prem_changes:
await self.apply_change_to_cloud(change)
# Sync cloud changes to on-prem
cloud_changes = self.cloud_db.get_changes_since(last_sync)
for change in cloud_changes:
await self.apply_change_to_on_prem(change)
# Handle conflicts
conflicts = self.detect_conflicts(on_prem_changes, cloud_changes)
for conflict in conflicts:
await self.resolve_conflict(conflict)
# Update sync timestamp
self.sync_log.record_sync_completion()
async def apply_change_to_cloud(self, change):
"""Apply on-premises change to cloud database"""
try:
if change.operation == "INSERT":
await self.cloud_db.insert(change.table, change.data)
elif change.operation == "UPDATE":
await self.cloud_db.update(change.table, change.key, change.data)
elif change.operation == "DELETE":
await self.cloud_db.delete(change.table, change.key)
self.sync_log.record_success(change.id, "cloud")
except Exception as e:
self.sync_log.record_failure(change.id, "cloud", str(e))
raise
```
### 3. Multi-Cloud Migration
**Use Case:** Avoiding vendor lock-in or regulatory requirements
**Complexity:** Very High
**Risk Level:** High
#### Description
Distribute workloads across multiple cloud providers for resilience, compliance, or cost optimization.
#### Service Mesh Configuration
```yaml
# Istio configuration for multi-cloud service mesh
apiVersion: networking.istio.io/v1beta1
kind: ServiceEntry
metadata:
name: aws-service
spec:
hosts:
- aws-service.company.com
ports:
- number: 443
name: https
protocol: HTTPS
location: MESH_EXTERNAL
resolution: DNS
---
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
name: multi-cloud-routing
spec:
hosts:
- user-service
http:
- match:
- headers:
region:
exact: "us-east"
route:
- destination:
host: aws-service.company.com
weight: 100
- match:
- headers:
region:
exact: "eu-west"
route:
- destination:
host: gcp-service.company.com
weight: 100
- route: # Default routing
- destination:
host: user-service
subset: local
weight: 80
- destination:
host: aws-service.company.com
weight: 20
```
## Feature Flag Patterns
### 1. Progressive Rollout Pattern
**Use Case:** Gradual feature deployment with risk mitigation
**Implementation:**
```python
class ProgressiveRollout:
def __init__(self, feature_name):
self.feature_name = feature_name
self.rollout_percentage = 0
self.user_buckets = {}
def is_enabled_for_user(self, user_id):
# Consistent user bucketing
user_hash = hashlib.md5(f"{self.feature_name}:{user_id}".encode()).hexdigest()
bucket = int(user_hash, 16) % 100
return bucket < self.rollout_percentage
def increase_rollout(self, target_percentage, step_size=10):
"""Gradually increase rollout percentage"""
while self.rollout_percentage < target_percentage:
self.rollout_percentage = min(
self.rollout_percentage + step_size,
target_percentage
)
# Monitor metrics before next increase
yield self.rollout_percentage
time.sleep(300) # Wait 5 minutes between increases
```
### 2. Circuit Breaker Pattern
**Use Case:** Automatic fallback during migration issues
```python
class MigrationCircuitBreaker:
def __init__(self, failure_threshold=5, timeout=60):
self.failure_count = 0
self.failure_threshold = failure_threshold
self.timeout = timeout
self.last_failure_time = None
self.state = 'CLOSED' # CLOSED, OPEN, HALF_OPEN
def call_new_service(self, request):
if self.state == 'OPEN':
if self.should_attempt_reset():
self.state = 'HALF_OPEN'
else:
return self.fallback_to_legacy(request)
try:
response = self.new_service.process(request)
self.on_success()
return response
except Exception as e:
self.on_failure()
return self.fallback_to_legacy(request)
def on_success(self):
self.failure_count = 0
self.state = 'CLOSED'
def on_failure(self):
self.failure_count += 1
self.last_failure_time = time.time()
if self.failure_count >= self.failure_threshold:
self.state = 'OPEN'
def should_attempt_reset(self):
return (time.time() - self.last_failure_time) >= self.timeout
```
## Migration Anti-Patterns
### 1. Big Bang Migration (Anti-Pattern)
**Why to Avoid:**
- High risk of complete system failure
- Difficult to rollback
- Extended downtime
- All-or-nothing deployment
**Better Alternative:** Use incremental migration patterns like Strangler Fig or Parallel Run.
### 2. No Rollback Plan (Anti-Pattern)
**Why to Avoid:**
- Cannot recover from failures
- Increases business risk
- Panic-driven decisions during issues
**Better Alternative:** Always implement comprehensive rollback procedures before migration.
### 3. Insufficient Testing (Anti-Pattern)
**Why to Avoid:**
- Unknown compatibility issues
- Performance degradation
- Data corruption risks
**Better Alternative:** Implement comprehensive testing at each migration phase.
## Pattern Selection Matrix
| Migration Type | Complexity | Downtime Tolerance | Recommended Pattern |
|---------------|------------|-------------------|-------------------|
| Schema Change | Low | Zero | Expand-Contract |
| Schema Change | High | Zero | Parallel Schema |
| Service Replace | Medium | Zero | Strangler Fig |
| Service Update | Low | Zero | Blue-Green |
| Data Migration | High | Some | Event Sourcing |
| Infrastructure | Low | Some | Lift and Shift |
| Infrastructure | High | Zero | Hybrid Cloud |
## Success Metrics
### Technical Metrics
- Migration completion rate
- System availability during migration
- Performance impact (response time, throughput)
- Error rate changes
- Rollback execution time
### Business Metrics
- Customer impact score
- Revenue protection
- Time to value realization
- Stakeholder satisfaction
### Operational Metrics
- Team efficiency
- Knowledge transfer effectiveness
- Post-migration support requirements
- Documentation completeness
## Lessons Learned
### Common Pitfalls
1. **Underestimating data dependencies** - Always map all data relationships
2. **Insufficient monitoring** - Implement comprehensive observability before migration
3. **Poor communication** - Keep all stakeholders informed throughout the process
4. **Rushed timelines** - Allow adequate time for testing and validation
5. **Ignoring performance impact** - Benchmark before and after migration
### Best Practices
1. **Start with low-risk migrations** - Build confidence and experience
2. **Automate everything possible** - Reduce human error and increase repeatability
3. **Test rollback procedures** - Ensure you can recover from any failure
4. **Monitor continuously** - Use real-time dashboards and alerting
5. **Document everything** - Create comprehensive runbooks and documentation
This catalog serves as a reference for selecting appropriate migration patterns based on specific requirements, risk tolerance, and technical constraints.

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#!/usr/bin/env python3
"""
Compatibility Checker - Analyze schema and API compatibility between versions
This tool analyzes schema and API changes between versions and identifies backward
compatibility issues including breaking changes, data type mismatches, missing fields,
constraint violations, and generates migration scripts suggestions.
Author: Migration Architect Skill
Version: 1.0.0
License: MIT
"""
import json
import argparse
import sys
import re
import datetime
from typing import Dict, List, Any, Optional, Tuple, Set
from dataclasses import dataclass, asdict
from enum import Enum
class ChangeType(Enum):
"""Types of changes detected"""
BREAKING = "breaking"
POTENTIALLY_BREAKING = "potentially_breaking"
NON_BREAKING = "non_breaking"
ADDITIVE = "additive"
class CompatibilityLevel(Enum):
"""Compatibility assessment levels"""
FULLY_COMPATIBLE = "fully_compatible"
BACKWARD_COMPATIBLE = "backward_compatible"
POTENTIALLY_INCOMPATIBLE = "potentially_incompatible"
BREAKING_CHANGES = "breaking_changes"
@dataclass
class CompatibilityIssue:
"""Individual compatibility issue"""
type: str
severity: str
description: str
field_path: str
old_value: Any
new_value: Any
impact: str
suggested_migration: str
affected_operations: List[str]
@dataclass
class MigrationScript:
"""Migration script suggestion"""
script_type: str # sql, api, config
description: str
script_content: str
rollback_script: str
dependencies: List[str]
validation_query: str
@dataclass
class CompatibilityReport:
"""Complete compatibility analysis report"""
schema_before: str
schema_after: str
analysis_date: str
overall_compatibility: str
breaking_changes_count: int
potentially_breaking_count: int
non_breaking_changes_count: int
additive_changes_count: int
issues: List[CompatibilityIssue]
migration_scripts: List[MigrationScript]
risk_assessment: Dict[str, Any]
recommendations: List[str]
class SchemaCompatibilityChecker:
"""Main schema compatibility checker class"""
def __init__(self):
self.type_compatibility_matrix = self._build_type_compatibility_matrix()
self.constraint_implications = self._build_constraint_implications()
def _build_type_compatibility_matrix(self) -> Dict[str, Dict[str, str]]:
"""Build data type compatibility matrix"""
return {
# SQL data types compatibility
"varchar": {
"text": "compatible",
"char": "potentially_breaking", # length might be different
"nvarchar": "compatible",
"int": "breaking",
"bigint": "breaking",
"decimal": "breaking",
"datetime": "breaking",
"boolean": "breaking"
},
"int": {
"bigint": "compatible",
"smallint": "potentially_breaking", # range reduction
"decimal": "compatible",
"float": "potentially_breaking", # precision loss
"varchar": "breaking",
"boolean": "breaking"
},
"bigint": {
"int": "potentially_breaking", # range reduction
"decimal": "compatible",
"varchar": "breaking",
"boolean": "breaking"
},
"decimal": {
"float": "potentially_breaking", # precision loss
"int": "potentially_breaking", # precision loss
"bigint": "potentially_breaking", # precision loss
"varchar": "breaking",
"boolean": "breaking"
},
"datetime": {
"timestamp": "compatible",
"date": "potentially_breaking", # time component lost
"varchar": "breaking",
"int": "breaking"
},
"boolean": {
"tinyint": "compatible",
"varchar": "breaking",
"int": "breaking"
},
# JSON/API field types
"string": {
"number": "breaking",
"boolean": "breaking",
"array": "breaking",
"object": "breaking",
"null": "potentially_breaking"
},
"number": {
"string": "breaking",
"boolean": "breaking",
"array": "breaking",
"object": "breaking",
"null": "potentially_breaking"
},
"boolean": {
"string": "breaking",
"number": "breaking",
"array": "breaking",
"object": "breaking",
"null": "potentially_breaking"
},
"array": {
"string": "breaking",
"number": "breaking",
"boolean": "breaking",
"object": "breaking",
"null": "potentially_breaking"
},
"object": {
"string": "breaking",
"number": "breaking",
"boolean": "breaking",
"array": "breaking",
"null": "potentially_breaking"
}
}
def _build_constraint_implications(self) -> Dict[str, Dict[str, str]]:
"""Build constraint change implications"""
return {
"required": {
"added": "breaking", # Previously optional field now required
"removed": "non_breaking" # Previously required field now optional
},
"not_null": {
"added": "breaking", # Previously nullable now NOT NULL
"removed": "non_breaking" # Previously NOT NULL now nullable
},
"unique": {
"added": "potentially_breaking", # May fail if duplicates exist
"removed": "non_breaking" # No longer enforcing uniqueness
},
"primary_key": {
"added": "breaking", # Major structural change
"removed": "breaking", # Major structural change
"modified": "breaking" # Primary key change is always breaking
},
"foreign_key": {
"added": "potentially_breaking", # May fail if referential integrity violated
"removed": "potentially_breaking", # May allow orphaned records
"modified": "breaking" # Reference change is breaking
},
"check": {
"added": "potentially_breaking", # May fail if existing data violates check
"removed": "non_breaking", # No longer enforcing check
"modified": "potentially_breaking" # Different validation rules
},
"index": {
"added": "non_breaking", # Performance improvement
"removed": "non_breaking", # Performance impact only
"modified": "non_breaking" # Performance impact only
}
}
def analyze_database_schema(self, before_schema: Dict[str, Any],
after_schema: Dict[str, Any]) -> CompatibilityReport:
"""Analyze database schema compatibility"""
issues = []
migration_scripts = []
before_tables = before_schema.get("tables", {})
after_tables = after_schema.get("tables", {})
# Check for removed tables
for table_name in before_tables:
if table_name not in after_tables:
issues.append(CompatibilityIssue(
type="table_removed",
severity="breaking",
description=f"Table '{table_name}' has been removed",
field_path=f"tables.{table_name}",
old_value=before_tables[table_name],
new_value=None,
impact="All operations on this table will fail",
suggested_migration=f"CREATE VIEW {table_name} AS SELECT * FROM replacement_table;",
affected_operations=["SELECT", "INSERT", "UPDATE", "DELETE"]
))
# Check for added tables
for table_name in after_tables:
if table_name not in before_tables:
migration_scripts.append(MigrationScript(
script_type="sql",
description=f"Create new table {table_name}",
script_content=self._generate_create_table_sql(table_name, after_tables[table_name]),
rollback_script=f"DROP TABLE IF EXISTS {table_name};",
dependencies=[],
validation_query=f"SELECT COUNT(*) FROM information_schema.tables WHERE table_name = '{table_name}';"
))
# Check for modified tables
for table_name in set(before_tables.keys()) & set(after_tables.keys()):
table_issues, table_scripts = self._analyze_table_changes(
table_name, before_tables[table_name], after_tables[table_name]
)
issues.extend(table_issues)
migration_scripts.extend(table_scripts)
return self._build_compatibility_report(
before_schema, after_schema, issues, migration_scripts
)
def analyze_api_schema(self, before_schema: Dict[str, Any],
after_schema: Dict[str, Any]) -> CompatibilityReport:
"""Analyze REST API schema compatibility"""
issues = []
migration_scripts = []
# Analyze endpoints
before_paths = before_schema.get("paths", {})
after_paths = after_schema.get("paths", {})
# Check for removed endpoints
for path in before_paths:
if path not in after_paths:
for method in before_paths[path]:
issues.append(CompatibilityIssue(
type="endpoint_removed",
severity="breaking",
description=f"Endpoint {method.upper()} {path} has been removed",
field_path=f"paths.{path}.{method}",
old_value=before_paths[path][method],
new_value=None,
impact="Client requests to this endpoint will fail with 404",
suggested_migration=f"Implement redirect to replacement endpoint or maintain backward compatibility stub",
affected_operations=[f"{method.upper()} {path}"]
))
# Check for modified endpoints
for path in set(before_paths.keys()) & set(after_paths.keys()):
path_issues, path_scripts = self._analyze_endpoint_changes(
path, before_paths[path], after_paths[path]
)
issues.extend(path_issues)
migration_scripts.extend(path_scripts)
# Analyze data models
before_components = before_schema.get("components", {}).get("schemas", {})
after_components = after_schema.get("components", {}).get("schemas", {})
for model_name in set(before_components.keys()) & set(after_components.keys()):
model_issues, model_scripts = self._analyze_model_changes(
model_name, before_components[model_name], after_components[model_name]
)
issues.extend(model_issues)
migration_scripts.extend(model_scripts)
return self._build_compatibility_report(
before_schema, after_schema, issues, migration_scripts
)
def _analyze_table_changes(self, table_name: str, before_table: Dict[str, Any],
after_table: Dict[str, Any]) -> Tuple[List[CompatibilityIssue], List[MigrationScript]]:
"""Analyze changes to a specific table"""
issues = []
scripts = []
before_columns = before_table.get("columns", {})
after_columns = after_table.get("columns", {})
# Check for removed columns
for col_name in before_columns:
if col_name not in after_columns:
issues.append(CompatibilityIssue(
type="column_removed",
severity="breaking",
description=f"Column '{col_name}' removed from table '{table_name}'",
field_path=f"tables.{table_name}.columns.{col_name}",
old_value=before_columns[col_name],
new_value=None,
impact="SELECT statements including this column will fail",
suggested_migration=f"ALTER TABLE {table_name} ADD COLUMN {col_name}_deprecated AS computed_value;",
affected_operations=["SELECT", "INSERT", "UPDATE"]
))
# Check for added columns
for col_name in after_columns:
if col_name not in before_columns:
col_def = after_columns[col_name]
is_required = col_def.get("nullable", True) == False and col_def.get("default") is None
if is_required:
issues.append(CompatibilityIssue(
type="required_column_added",
severity="breaking",
description=f"Required column '{col_name}' added to table '{table_name}'",
field_path=f"tables.{table_name}.columns.{col_name}",
old_value=None,
new_value=col_def,
impact="INSERT statements without this column will fail",
suggested_migration=f"Add default value or make column nullable initially",
affected_operations=["INSERT"]
))
scripts.append(MigrationScript(
script_type="sql",
description=f"Add column {col_name} to table {table_name}",
script_content=f"ALTER TABLE {table_name} ADD COLUMN {self._generate_column_definition(col_name, col_def)};",
rollback_script=f"ALTER TABLE {table_name} DROP COLUMN {col_name};",
dependencies=[],
validation_query=f"SELECT COUNT(*) FROM information_schema.columns WHERE table_name = '{table_name}' AND column_name = '{col_name}';"
))
# Check for modified columns
for col_name in set(before_columns.keys()) & set(after_columns.keys()):
col_issues, col_scripts = self._analyze_column_changes(
table_name, col_name, before_columns[col_name], after_columns[col_name]
)
issues.extend(col_issues)
scripts.extend(col_scripts)
# Check constraint changes
before_constraints = before_table.get("constraints", {})
after_constraints = after_table.get("constraints", {})
constraint_issues, constraint_scripts = self._analyze_constraint_changes(
table_name, before_constraints, after_constraints
)
issues.extend(constraint_issues)
scripts.extend(constraint_scripts)
return issues, scripts
def _analyze_column_changes(self, table_name: str, col_name: str,
before_col: Dict[str, Any], after_col: Dict[str, Any]) -> Tuple[List[CompatibilityIssue], List[MigrationScript]]:
"""Analyze changes to a specific column"""
issues = []
scripts = []
# Check data type changes
before_type = before_col.get("type", "").lower()
after_type = after_col.get("type", "").lower()
if before_type != after_type:
compatibility = self.type_compatibility_matrix.get(before_type, {}).get(after_type, "breaking")
if compatibility == "breaking":
issues.append(CompatibilityIssue(
type="incompatible_type_change",
severity="breaking",
description=f"Column '{col_name}' type changed from {before_type} to {after_type}",
field_path=f"tables.{table_name}.columns.{col_name}.type",
old_value=before_type,
new_value=after_type,
impact="Data conversion may fail or lose precision",
suggested_migration=f"Add conversion logic and validate data integrity",
affected_operations=["SELECT", "INSERT", "UPDATE", "WHERE clauses"]
))
scripts.append(MigrationScript(
script_type="sql",
description=f"Convert column {col_name} from {before_type} to {after_type}",
script_content=f"ALTER TABLE {table_name} ALTER COLUMN {col_name} TYPE {after_type} USING {col_name}::{after_type};",
rollback_script=f"ALTER TABLE {table_name} ALTER COLUMN {col_name} TYPE {before_type};",
dependencies=[f"backup_{table_name}"],
validation_query=f"SELECT COUNT(*) FROM {table_name} WHERE {col_name} IS NOT NULL;"
))
elif compatibility == "potentially_breaking":
issues.append(CompatibilityIssue(
type="risky_type_change",
severity="potentially_breaking",
description=f"Column '{col_name}' type changed from {before_type} to {after_type} - may lose data",
field_path=f"tables.{table_name}.columns.{col_name}.type",
old_value=before_type,
new_value=after_type,
impact="Potential data loss or precision reduction",
suggested_migration=f"Validate all existing data can be converted safely",
affected_operations=["Data integrity"]
))
# Check nullability changes
before_nullable = before_col.get("nullable", True)
after_nullable = after_col.get("nullable", True)
if before_nullable != after_nullable:
if before_nullable and not after_nullable: # null -> not null
issues.append(CompatibilityIssue(
type="nullability_restriction",
severity="breaking",
description=f"Column '{col_name}' changed from nullable to NOT NULL",
field_path=f"tables.{table_name}.columns.{col_name}.nullable",
old_value=before_nullable,
new_value=after_nullable,
impact="Existing NULL values will cause constraint violations",
suggested_migration=f"Update NULL values to valid defaults before applying NOT NULL constraint",
affected_operations=["INSERT", "UPDATE"]
))
scripts.append(MigrationScript(
script_type="sql",
description=f"Make column {col_name} NOT NULL",
script_content=f"""
-- Update NULL values first
UPDATE {table_name} SET {col_name} = 'DEFAULT_VALUE' WHERE {col_name} IS NULL;
-- Add NOT NULL constraint
ALTER TABLE {table_name} ALTER COLUMN {col_name} SET NOT NULL;
""",
rollback_script=f"ALTER TABLE {table_name} ALTER COLUMN {col_name} DROP NOT NULL;",
dependencies=[],
validation_query=f"SELECT COUNT(*) FROM {table_name} WHERE {col_name} IS NULL;"
))
# Check length/precision changes
before_length = before_col.get("length")
after_length = after_col.get("length")
if before_length and after_length and before_length != after_length:
if after_length < before_length:
issues.append(CompatibilityIssue(
type="length_reduction",
severity="potentially_breaking",
description=f"Column '{col_name}' length reduced from {before_length} to {after_length}",
field_path=f"tables.{table_name}.columns.{col_name}.length",
old_value=before_length,
new_value=after_length,
impact="Data truncation may occur for values exceeding new length",
suggested_migration=f"Validate no existing data exceeds new length limit",
affected_operations=["INSERT", "UPDATE"]
))
return issues, scripts
def _analyze_constraint_changes(self, table_name: str, before_constraints: Dict[str, Any],
after_constraints: Dict[str, Any]) -> Tuple[List[CompatibilityIssue], List[MigrationScript]]:
"""Analyze constraint changes"""
issues = []
scripts = []
for constraint_type in ["primary_key", "foreign_key", "unique", "check"]:
before_constraint = before_constraints.get(constraint_type, [])
after_constraint = after_constraints.get(constraint_type, [])
# Convert to sets for comparison
before_set = set(str(c) for c in before_constraint) if isinstance(before_constraint, list) else {str(before_constraint)} if before_constraint else set()
after_set = set(str(c) for c in after_constraint) if isinstance(after_constraint, list) else {str(after_constraint)} if after_constraint else set()
# Check for removed constraints
for constraint in before_set - after_set:
implication = self.constraint_implications.get(constraint_type, {}).get("removed", "non_breaking")
issues.append(CompatibilityIssue(
type=f"{constraint_type}_removed",
severity=implication,
description=f"{constraint_type.replace('_', ' ').title()} constraint '{constraint}' removed from table '{table_name}'",
field_path=f"tables.{table_name}.constraints.{constraint_type}",
old_value=constraint,
new_value=None,
impact=f"No longer enforcing {constraint_type} constraint",
suggested_migration=f"Consider application-level validation for removed constraint",
affected_operations=["INSERT", "UPDATE", "DELETE"]
))
# Check for added constraints
for constraint in after_set - before_set:
implication = self.constraint_implications.get(constraint_type, {}).get("added", "potentially_breaking")
issues.append(CompatibilityIssue(
type=f"{constraint_type}_added",
severity=implication,
description=f"New {constraint_type.replace('_', ' ')} constraint '{constraint}' added to table '{table_name}'",
field_path=f"tables.{table_name}.constraints.{constraint_type}",
old_value=None,
new_value=constraint,
impact=f"New {constraint_type} constraint may reject existing data",
suggested_migration=f"Validate existing data complies with new constraint",
affected_operations=["INSERT", "UPDATE"]
))
scripts.append(MigrationScript(
script_type="sql",
description=f"Add {constraint_type} constraint to {table_name}",
script_content=f"ALTER TABLE {table_name} ADD CONSTRAINT {constraint_type}_{table_name} {constraint_type.upper()} ({constraint});",
rollback_script=f"ALTER TABLE {table_name} DROP CONSTRAINT {constraint_type}_{table_name};",
dependencies=[],
validation_query=f"SELECT COUNT(*) FROM information_schema.table_constraints WHERE table_name = '{table_name}' AND constraint_type = '{constraint_type.upper()}';"
))
return issues, scripts
def _analyze_endpoint_changes(self, path: str, before_endpoint: Dict[str, Any],
after_endpoint: Dict[str, Any]) -> Tuple[List[CompatibilityIssue], List[MigrationScript]]:
"""Analyze changes to an API endpoint"""
issues = []
scripts = []
for method in set(before_endpoint.keys()) & set(after_endpoint.keys()):
before_method = before_endpoint[method]
after_method = after_endpoint[method]
# Check parameter changes
before_params = before_method.get("parameters", [])
after_params = after_method.get("parameters", [])
before_param_names = {p["name"] for p in before_params}
after_param_names = {p["name"] for p in after_params}
# Check for removed required parameters
for param_name in before_param_names - after_param_names:
param = next(p for p in before_params if p["name"] == param_name)
if param.get("required", False):
issues.append(CompatibilityIssue(
type="required_parameter_removed",
severity="breaking",
description=f"Required parameter '{param_name}' removed from {method.upper()} {path}",
field_path=f"paths.{path}.{method}.parameters",
old_value=param,
new_value=None,
impact="Client requests with this parameter will fail",
suggested_migration="Implement parameter validation with backward compatibility",
affected_operations=[f"{method.upper()} {path}"]
))
# Check for added required parameters
for param_name in after_param_names - before_param_names:
param = next(p for p in after_params if p["name"] == param_name)
if param.get("required", False):
issues.append(CompatibilityIssue(
type="required_parameter_added",
severity="breaking",
description=f"New required parameter '{param_name}' added to {method.upper()} {path}",
field_path=f"paths.{path}.{method}.parameters",
old_value=None,
new_value=param,
impact="Client requests without this parameter will fail",
suggested_migration="Provide default value or make parameter optional initially",
affected_operations=[f"{method.upper()} {path}"]
))
# Check response schema changes
before_responses = before_method.get("responses", {})
after_responses = after_method.get("responses", {})
for status_code in before_responses:
if status_code in after_responses:
before_schema = before_responses[status_code].get("content", {}).get("application/json", {}).get("schema", {})
after_schema = after_responses[status_code].get("content", {}).get("application/json", {}).get("schema", {})
if before_schema != after_schema:
issues.append(CompatibilityIssue(
type="response_schema_changed",
severity="potentially_breaking",
description=f"Response schema changed for {method.upper()} {path} (status {status_code})",
field_path=f"paths.{path}.{method}.responses.{status_code}",
old_value=before_schema,
new_value=after_schema,
impact="Client response parsing may fail",
suggested_migration="Implement versioned API responses",
affected_operations=[f"{method.upper()} {path}"]
))
return issues, scripts
def _analyze_model_changes(self, model_name: str, before_model: Dict[str, Any],
after_model: Dict[str, Any]) -> Tuple[List[CompatibilityIssue], List[MigrationScript]]:
"""Analyze changes to an API data model"""
issues = []
scripts = []
before_props = before_model.get("properties", {})
after_props = after_model.get("properties", {})
before_required = set(before_model.get("required", []))
after_required = set(after_model.get("required", []))
# Check for removed properties
for prop_name in set(before_props.keys()) - set(after_props.keys()):
issues.append(CompatibilityIssue(
type="property_removed",
severity="breaking",
description=f"Property '{prop_name}' removed from model '{model_name}'",
field_path=f"components.schemas.{model_name}.properties.{prop_name}",
old_value=before_props[prop_name],
new_value=None,
impact="Client code expecting this property will fail",
suggested_migration="Use API versioning to maintain backward compatibility",
affected_operations=["Serialization", "Deserialization"]
))
# Check for newly required properties
for prop_name in after_required - before_required:
issues.append(CompatibilityIssue(
type="property_made_required",
severity="breaking",
description=f"Property '{prop_name}' is now required in model '{model_name}'",
field_path=f"components.schemas.{model_name}.required",
old_value=list(before_required),
new_value=list(after_required),
impact="Client requests without this property will fail validation",
suggested_migration="Provide default values or implement gradual rollout",
affected_operations=["Request validation"]
))
# Check for property type changes
for prop_name in set(before_props.keys()) & set(after_props.keys()):
before_type = before_props[prop_name].get("type")
after_type = after_props[prop_name].get("type")
if before_type != after_type:
compatibility = self.type_compatibility_matrix.get(before_type, {}).get(after_type, "breaking")
issues.append(CompatibilityIssue(
type="property_type_changed",
severity=compatibility,
description=f"Property '{prop_name}' type changed from {before_type} to {after_type} in model '{model_name}'",
field_path=f"components.schemas.{model_name}.properties.{prop_name}.type",
old_value=before_type,
new_value=after_type,
impact="Client serialization/deserialization may fail",
suggested_migration="Implement type coercion or API versioning",
affected_operations=["Serialization", "Deserialization"]
))
return issues, scripts
def _build_compatibility_report(self, before_schema: Dict[str, Any], after_schema: Dict[str, Any],
issues: List[CompatibilityIssue], migration_scripts: List[MigrationScript]) -> CompatibilityReport:
"""Build the final compatibility report"""
# Count issues by severity
breaking_count = sum(1 for issue in issues if issue.severity == "breaking")
potentially_breaking_count = sum(1 for issue in issues if issue.severity == "potentially_breaking")
non_breaking_count = sum(1 for issue in issues if issue.severity == "non_breaking")
additive_count = sum(1 for issue in issues if issue.type == "additive")
# Determine overall compatibility
if breaking_count > 0:
overall_compatibility = "breaking_changes"
elif potentially_breaking_count > 0:
overall_compatibility = "potentially_incompatible"
elif non_breaking_count > 0:
overall_compatibility = "backward_compatible"
else:
overall_compatibility = "fully_compatible"
# Generate risk assessment
risk_assessment = {
"overall_risk": "high" if breaking_count > 0 else "medium" if potentially_breaking_count > 0 else "low",
"deployment_risk": "requires_coordinated_deployment" if breaking_count > 0 else "safe_independent_deployment",
"rollback_complexity": "high" if breaking_count > 3 else "medium" if breaking_count > 0 else "low",
"testing_requirements": ["integration_testing", "regression_testing"] +
(["data_migration_testing"] if any(s.script_type == "sql" for s in migration_scripts) else [])
}
# Generate recommendations
recommendations = []
if breaking_count > 0:
recommendations.append("Implement API versioning to maintain backward compatibility")
recommendations.append("Plan for coordinated deployment with all clients")
recommendations.append("Implement comprehensive rollback procedures")
if potentially_breaking_count > 0:
recommendations.append("Conduct thorough testing with realistic data volumes")
recommendations.append("Implement monitoring for migration success metrics")
if migration_scripts:
recommendations.append("Test all migration scripts in staging environment")
recommendations.append("Implement migration progress monitoring")
recommendations.append("Create detailed communication plan for stakeholders")
recommendations.append("Implement feature flags for gradual rollout")
return CompatibilityReport(
schema_before=json.dumps(before_schema, indent=2)[:500] + "..." if len(json.dumps(before_schema)) > 500 else json.dumps(before_schema, indent=2),
schema_after=json.dumps(after_schema, indent=2)[:500] + "..." if len(json.dumps(after_schema)) > 500 else json.dumps(after_schema, indent=2),
analysis_date=datetime.datetime.now().isoformat(),
overall_compatibility=overall_compatibility,
breaking_changes_count=breaking_count,
potentially_breaking_count=potentially_breaking_count,
non_breaking_changes_count=non_breaking_count,
additive_changes_count=additive_count,
issues=issues,
migration_scripts=migration_scripts,
risk_assessment=risk_assessment,
recommendations=recommendations
)
def _generate_create_table_sql(self, table_name: str, table_def: Dict[str, Any]) -> str:
"""Generate CREATE TABLE SQL statement"""
columns = []
for col_name, col_def in table_def.get("columns", {}).items():
columns.append(self._generate_column_definition(col_name, col_def))
return f"CREATE TABLE {table_name} (\n " + ",\n ".join(columns) + "\n);"
def _generate_column_definition(self, col_name: str, col_def: Dict[str, Any]) -> str:
"""Generate column definition for SQL"""
col_type = col_def.get("type", "VARCHAR(255)")
nullable = "" if col_def.get("nullable", True) else " NOT NULL"
default = f" DEFAULT {col_def.get('default')}" if col_def.get("default") is not None else ""
return f"{col_name} {col_type}{nullable}{default}"
def generate_human_readable_report(self, report: CompatibilityReport) -> str:
"""Generate human-readable compatibility report"""
output = []
output.append("=" * 80)
output.append("COMPATIBILITY ANALYSIS REPORT")
output.append("=" * 80)
output.append(f"Analysis Date: {report.analysis_date}")
output.append(f"Overall Compatibility: {report.overall_compatibility.upper()}")
output.append("")
# Summary
output.append("SUMMARY")
output.append("-" * 40)
output.append(f"Breaking Changes: {report.breaking_changes_count}")
output.append(f"Potentially Breaking: {report.potentially_breaking_count}")
output.append(f"Non-Breaking Changes: {report.non_breaking_changes_count}")
output.append(f"Additive Changes: {report.additive_changes_count}")
output.append(f"Total Issues Found: {len(report.issues)}")
output.append("")
# Risk Assessment
output.append("RISK ASSESSMENT")
output.append("-" * 40)
for key, value in report.risk_assessment.items():
output.append(f"{key.replace('_', ' ').title()}: {value}")
output.append("")
# Issues by Severity
issues_by_severity = {}
for issue in report.issues:
if issue.severity not in issues_by_severity:
issues_by_severity[issue.severity] = []
issues_by_severity[issue.severity].append(issue)
for severity in ["breaking", "potentially_breaking", "non_breaking"]:
if severity in issues_by_severity:
output.append(f"{severity.upper().replace('_', ' ')} ISSUES")
output.append("-" * 40)
for issue in issues_by_severity[severity]:
output.append(f"{issue.description}")
output.append(f" Field: {issue.field_path}")
output.append(f" Impact: {issue.impact}")
output.append(f" Migration: {issue.suggested_migration}")
if issue.affected_operations:
output.append(f" Affected Operations: {', '.join(issue.affected_operations)}")
output.append("")
# Migration Scripts
if report.migration_scripts:
output.append("SUGGESTED MIGRATION SCRIPTS")
output.append("-" * 40)
for i, script in enumerate(report.migration_scripts, 1):
output.append(f"{i}. {script.description}")
output.append(f" Type: {script.script_type}")
output.append(" Script:")
for line in script.script_content.split('\n'):
output.append(f" {line}")
output.append("")
# Recommendations
output.append("RECOMMENDATIONS")
output.append("-" * 40)
for i, rec in enumerate(report.recommendations, 1):
output.append(f"{i}. {rec}")
output.append("")
return "\n".join(output)
def main():
"""Main function with command line interface"""
parser = argparse.ArgumentParser(description="Analyze schema and API compatibility between versions")
parser.add_argument("--before", required=True, help="Before schema file (JSON)")
parser.add_argument("--after", required=True, help="After schema file (JSON)")
parser.add_argument("--type", choices=["database", "api"], default="database", help="Schema type to analyze")
parser.add_argument("--output", "-o", help="Output file for compatibility report (JSON)")
parser.add_argument("--format", "-f", choices=["json", "text", "both"], default="both", help="Output format")
args = parser.parse_args()
try:
# Load schemas
with open(args.before, 'r') as f:
before_schema = json.load(f)
with open(args.after, 'r') as f:
after_schema = json.load(f)
# Analyze compatibility
checker = SchemaCompatibilityChecker()
if args.type == "database":
report = checker.analyze_database_schema(before_schema, after_schema)
else: # api
report = checker.analyze_api_schema(before_schema, after_schema)
# Output results
if args.format in ["json", "both"]:
report_dict = asdict(report)
if args.output:
with open(args.output, 'w') as f:
json.dump(report_dict, f, indent=2)
print(f"Compatibility report saved to {args.output}")
else:
print(json.dumps(report_dict, indent=2))
if args.format in ["text", "both"]:
human_report = checker.generate_human_readable_report(report)
text_output = args.output.replace('.json', '.txt') if args.output else None
if text_output:
with open(text_output, 'w') as f:
f.write(human_report)
print(f"Human-readable report saved to {text_output}")
else:
print("\n" + "="*80)
print("HUMAN-READABLE COMPATIBILITY REPORT")
print("="*80)
print(human_report)
# Return exit code based on compatibility
if report.breaking_changes_count > 0:
return 2 # Breaking changes found
elif report.potentially_breaking_count > 0:
return 1 # Potentially breaking changes found
else:
return 0 # No compatibility issues
except FileNotFoundError as e:
print(f"Error: File not found: {e}", file=sys.stderr)
return 1
except json.JSONDecodeError as e:
print(f"Error: Invalid JSON: {e}", file=sys.stderr)
return 1
except Exception as e:
print(f"Error: {e}", file=sys.stderr)
return 1
if __name__ == "__main__":
sys.exit(main())

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#!/usr/bin/env python3
"""
Migration Planner - Generate comprehensive migration plans with risk assessment
This tool analyzes migration specifications and generates detailed, phased migration plans
including pre-migration checklists, validation gates, rollback triggers, timeline estimates,
and risk matrices.
Author: Migration Architect Skill
Version: 1.0.0
License: MIT
"""
import json
import argparse
import sys
import datetime
import hashlib
import math
from typing import Dict, List, Any, Optional, Tuple
from dataclasses import dataclass, asdict
from enum import Enum
class MigrationType(Enum):
"""Migration type enumeration"""
DATABASE = "database"
SERVICE = "service"
INFRASTRUCTURE = "infrastructure"
DATA = "data"
API = "api"
class MigrationComplexity(Enum):
"""Migration complexity levels"""
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
CRITICAL = "critical"
class RiskLevel(Enum):
"""Risk assessment levels"""
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
CRITICAL = "critical"
@dataclass
class MigrationConstraint:
"""Migration constraint definition"""
type: str
description: str
impact: str
mitigation: str
@dataclass
class MigrationPhase:
"""Individual migration phase"""
name: str
description: str
duration_hours: int
dependencies: List[str]
validation_criteria: List[str]
rollback_triggers: List[str]
tasks: List[str]
risk_level: str
resources_required: List[str]
@dataclass
class RiskItem:
"""Individual risk assessment item"""
category: str
description: str
probability: str # low, medium, high
impact: str # low, medium, high
severity: str # low, medium, high, critical
mitigation: str
owner: str
@dataclass
class MigrationPlan:
"""Complete migration plan structure"""
migration_id: str
source_system: str
target_system: str
migration_type: str
complexity: str
estimated_duration_hours: int
phases: List[MigrationPhase]
risks: List[RiskItem]
success_criteria: List[str]
rollback_plan: Dict[str, Any]
stakeholders: List[str]
created_at: str
class MigrationPlanner:
"""Main migration planner class"""
def __init__(self):
self.migration_patterns = self._load_migration_patterns()
self.risk_templates = self._load_risk_templates()
def _load_migration_patterns(self) -> Dict[str, Any]:
"""Load predefined migration patterns"""
return {
"database": {
"schema_change": {
"phases": ["preparation", "expand", "migrate", "contract", "cleanup"],
"base_duration": 24,
"complexity_multiplier": {"low": 1.0, "medium": 1.5, "high": 2.5, "critical": 4.0}
},
"data_migration": {
"phases": ["assessment", "setup", "bulk_copy", "delta_sync", "validation", "cutover"],
"base_duration": 48,
"complexity_multiplier": {"low": 1.2, "medium": 2.0, "high": 3.0, "critical": 5.0}
}
},
"service": {
"strangler_fig": {
"phases": ["intercept", "implement", "redirect", "validate", "retire"],
"base_duration": 168, # 1 week
"complexity_multiplier": {"low": 0.8, "medium": 1.0, "high": 1.8, "critical": 3.0}
},
"parallel_run": {
"phases": ["setup", "deploy", "shadow", "compare", "cutover", "cleanup"],
"base_duration": 72,
"complexity_multiplier": {"low": 1.0, "medium": 1.3, "high": 2.0, "critical": 3.5}
}
},
"infrastructure": {
"cloud_migration": {
"phases": ["assessment", "design", "pilot", "migration", "optimization", "decommission"],
"base_duration": 720, # 30 days
"complexity_multiplier": {"low": 0.6, "medium": 1.0, "high": 1.5, "critical": 2.5}
},
"on_prem_to_cloud": {
"phases": ["discovery", "planning", "pilot", "migration", "validation", "cutover"],
"base_duration": 480, # 20 days
"complexity_multiplier": {"low": 0.8, "medium": 1.2, "high": 2.0, "critical": 3.0}
}
}
}
def _load_risk_templates(self) -> Dict[str, List[RiskItem]]:
"""Load risk templates for different migration types"""
return {
"database": [
RiskItem("technical", "Data corruption during migration", "low", "critical", "high",
"Implement comprehensive backup and validation procedures", "DBA Team"),
RiskItem("technical", "Extended downtime due to migration complexity", "medium", "high", "high",
"Use blue-green deployment and phased migration approach", "DevOps Team"),
RiskItem("business", "Business process disruption", "medium", "high", "high",
"Communicate timeline and provide alternate workflows", "Business Owner"),
RiskItem("operational", "Insufficient rollback testing", "high", "critical", "critical",
"Execute full rollback procedures in staging environment", "QA Team")
],
"service": [
RiskItem("technical", "Service compatibility issues", "medium", "high", "high",
"Implement comprehensive integration testing", "Development Team"),
RiskItem("technical", "Performance degradation", "medium", "medium", "medium",
"Conduct load testing and performance benchmarking", "DevOps Team"),
RiskItem("business", "Feature parity gaps", "high", "high", "high",
"Document feature mapping and acceptance criteria", "Product Owner"),
RiskItem("operational", "Monitoring gap during transition", "medium", "medium", "medium",
"Set up dual monitoring and alerting systems", "SRE Team")
],
"infrastructure": [
RiskItem("technical", "Network connectivity issues", "medium", "critical", "high",
"Implement redundant network paths and monitoring", "Network Team"),
RiskItem("technical", "Security configuration drift", "high", "high", "high",
"Automated security scanning and compliance checks", "Security Team"),
RiskItem("business", "Cost overrun during transition", "high", "medium", "medium",
"Implement cost monitoring and budget alerts", "Finance Team"),
RiskItem("operational", "Team knowledge gaps", "high", "medium", "medium",
"Provide training and create detailed documentation", "Platform Team")
]
}
def _calculate_complexity(self, spec: Dict[str, Any]) -> str:
"""Calculate migration complexity based on specification"""
complexity_score = 0
# Data volume complexity
data_volume = spec.get("constraints", {}).get("data_volume_gb", 0)
if data_volume > 10000:
complexity_score += 3
elif data_volume > 1000:
complexity_score += 2
elif data_volume > 100:
complexity_score += 1
# System dependencies
dependencies = len(spec.get("constraints", {}).get("dependencies", []))
if dependencies > 10:
complexity_score += 3
elif dependencies > 5:
complexity_score += 2
elif dependencies > 2:
complexity_score += 1
# Downtime constraints
max_downtime = spec.get("constraints", {}).get("max_downtime_minutes", 480)
if max_downtime < 60:
complexity_score += 3
elif max_downtime < 240:
complexity_score += 2
elif max_downtime < 480:
complexity_score += 1
# Special requirements
special_reqs = spec.get("constraints", {}).get("special_requirements", [])
complexity_score += len(special_reqs)
if complexity_score >= 8:
return "critical"
elif complexity_score >= 5:
return "high"
elif complexity_score >= 3:
return "medium"
else:
return "low"
def _estimate_duration(self, migration_type: str, migration_pattern: str, complexity: str) -> int:
"""Estimate migration duration based on type, pattern, and complexity"""
pattern_info = self.migration_patterns.get(migration_type, {}).get(migration_pattern, {})
base_duration = pattern_info.get("base_duration", 48)
multiplier = pattern_info.get("complexity_multiplier", {}).get(complexity, 1.5)
return int(base_duration * multiplier)
def _generate_phases(self, spec: Dict[str, Any]) -> List[MigrationPhase]:
"""Generate migration phases based on specification"""
migration_type = spec.get("type")
migration_pattern = spec.get("pattern", "")
complexity = self._calculate_complexity(spec)
pattern_info = self.migration_patterns.get(migration_type, {})
if migration_pattern in pattern_info:
phase_names = pattern_info[migration_pattern]["phases"]
else:
# Default phases based on migration type
phase_names = {
"database": ["preparation", "migration", "validation", "cutover"],
"service": ["preparation", "deployment", "testing", "cutover"],
"infrastructure": ["assessment", "preparation", "migration", "validation"]
}.get(migration_type, ["preparation", "execution", "validation", "cleanup"])
phases = []
total_duration = self._estimate_duration(migration_type, migration_pattern, complexity)
phase_duration = total_duration // len(phase_names)
for i, phase_name in enumerate(phase_names):
phase = self._create_phase(phase_name, phase_duration, complexity, i, phase_names)
phases.append(phase)
return phases
def _create_phase(self, phase_name: str, duration: int, complexity: str,
phase_index: int, all_phases: List[str]) -> MigrationPhase:
"""Create a detailed migration phase"""
phase_templates = {
"preparation": {
"description": "Prepare systems and teams for migration",
"tasks": [
"Backup source system",
"Set up monitoring and alerting",
"Prepare rollback procedures",
"Communicate migration timeline",
"Validate prerequisites"
],
"validation_criteria": [
"All backups completed successfully",
"Monitoring systems operational",
"Team members briefed and ready",
"Rollback procedures tested"
],
"risk_level": "medium"
},
"assessment": {
"description": "Assess current state and migration requirements",
"tasks": [
"Inventory existing systems and dependencies",
"Analyze data volumes and complexity",
"Identify integration points",
"Document current architecture",
"Create migration mapping"
],
"validation_criteria": [
"Complete system inventory documented",
"Dependencies mapped and validated",
"Migration scope clearly defined",
"Resource requirements identified"
],
"risk_level": "low"
},
"migration": {
"description": "Execute core migration processes",
"tasks": [
"Begin data/service migration",
"Monitor migration progress",
"Validate data consistency",
"Handle migration errors",
"Update configuration"
],
"validation_criteria": [
"Migration progress within expected parameters",
"Data consistency checks passing",
"Error rates within acceptable limits",
"Performance metrics stable"
],
"risk_level": "high"
},
"validation": {
"description": "Validate migration success and system health",
"tasks": [
"Execute comprehensive testing",
"Validate business processes",
"Check system performance",
"Verify data integrity",
"Confirm security controls"
],
"validation_criteria": [
"All critical tests passing",
"Performance within acceptable range",
"Security controls functioning",
"Business processes operational"
],
"risk_level": "medium"
},
"cutover": {
"description": "Switch production traffic to new system",
"tasks": [
"Update DNS/load balancer configuration",
"Redirect production traffic",
"Monitor system performance",
"Validate end-user experience",
"Confirm business operations"
],
"validation_criteria": [
"Traffic successfully redirected",
"System performance stable",
"User experience satisfactory",
"Business operations normal"
],
"risk_level": "critical"
}
}
template = phase_templates.get(phase_name, {
"description": f"Execute {phase_name} phase",
"tasks": [f"Complete {phase_name} activities"],
"validation_criteria": [f"{phase_name.title()} phase completed successfully"],
"risk_level": "medium"
})
dependencies = []
if phase_index > 0:
dependencies.append(all_phases[phase_index - 1])
rollback_triggers = [
"Critical system failure",
"Data corruption detected",
"Performance degradation > 50%",
"Business process failure"
]
resources_required = [
"Technical team availability",
"System access and permissions",
"Monitoring and alerting systems",
"Communication channels"
]
return MigrationPhase(
name=phase_name,
description=template["description"],
duration_hours=duration,
dependencies=dependencies,
validation_criteria=template["validation_criteria"],
rollback_triggers=rollback_triggers,
tasks=template["tasks"],
risk_level=template["risk_level"],
resources_required=resources_required
)
def _assess_risks(self, spec: Dict[str, Any]) -> List[RiskItem]:
"""Generate risk assessment for migration"""
migration_type = spec.get("type")
base_risks = self.risk_templates.get(migration_type, [])
# Add specification-specific risks
additional_risks = []
constraints = spec.get("constraints", {})
if constraints.get("max_downtime_minutes", 480) < 60:
additional_risks.append(
RiskItem("business", "Zero-downtime requirement increases complexity", "high", "medium", "high",
"Implement blue-green deployment or rolling update strategy", "DevOps Team")
)
if constraints.get("data_volume_gb", 0) > 5000:
additional_risks.append(
RiskItem("technical", "Large data volumes may cause extended migration time", "high", "medium", "medium",
"Implement parallel processing and progress monitoring", "Data Team")
)
compliance_reqs = constraints.get("compliance_requirements", [])
if compliance_reqs:
additional_risks.append(
RiskItem("compliance", "Regulatory compliance requirements", "medium", "high", "high",
"Ensure all compliance checks are integrated into migration process", "Compliance Team")
)
return base_risks + additional_risks
def _generate_rollback_plan(self, phases: List[MigrationPhase]) -> Dict[str, Any]:
"""Generate comprehensive rollback plan"""
rollback_phases = []
for phase in reversed(phases):
rollback_phase = {
"phase": phase.name,
"rollback_actions": [
f"Revert {phase.name} changes",
f"Restore pre-{phase.name} state",
f"Validate {phase.name} rollback success"
],
"validation_criteria": [
f"System restored to pre-{phase.name} state",
f"All {phase.name} changes successfully reverted",
"System functionality confirmed"
],
"estimated_time_minutes": phase.duration_hours * 15 # 25% of original phase time
}
rollback_phases.append(rollback_phase)
return {
"rollback_phases": rollback_phases,
"rollback_triggers": [
"Critical system failure",
"Data corruption detected",
"Migration timeline exceeded by > 50%",
"Business-critical functionality unavailable",
"Security breach detected",
"Stakeholder decision to abort"
],
"rollback_decision_matrix": {
"low_severity": "Continue with monitoring",
"medium_severity": "Assess and decide within 15 minutes",
"high_severity": "Immediate rollback initiation",
"critical_severity": "Emergency rollback - all hands"
},
"rollback_contacts": [
"Migration Lead",
"Technical Lead",
"Business Owner",
"On-call Engineer"
]
}
def generate_plan(self, spec: Dict[str, Any]) -> MigrationPlan:
"""Generate complete migration plan from specification"""
migration_id = hashlib.md5(json.dumps(spec, sort_keys=True).encode()).hexdigest()[:12]
complexity = self._calculate_complexity(spec)
phases = self._generate_phases(spec)
risks = self._assess_risks(spec)
total_duration = sum(phase.duration_hours for phase in phases)
rollback_plan = self._generate_rollback_plan(phases)
success_criteria = [
"All data successfully migrated with 100% integrity",
"System performance meets or exceeds baseline",
"All business processes functioning normally",
"No critical security vulnerabilities introduced",
"Stakeholder acceptance criteria met",
"Documentation and runbooks updated"
]
stakeholders = [
"Business Owner",
"Technical Lead",
"DevOps Team",
"QA Team",
"Security Team",
"End Users"
]
return MigrationPlan(
migration_id=migration_id,
source_system=spec.get("source", "Unknown"),
target_system=spec.get("target", "Unknown"),
migration_type=spec.get("type", "Unknown"),
complexity=complexity,
estimated_duration_hours=total_duration,
phases=phases,
risks=risks,
success_criteria=success_criteria,
rollback_plan=rollback_plan,
stakeholders=stakeholders,
created_at=datetime.datetime.now().isoformat()
)
def generate_human_readable_plan(self, plan: MigrationPlan) -> str:
"""Generate human-readable migration plan"""
output = []
output.append("=" * 80)
output.append(f"MIGRATION PLAN: {plan.migration_id}")
output.append("=" * 80)
output.append(f"Source System: {plan.source_system}")
output.append(f"Target System: {plan.target_system}")
output.append(f"Migration Type: {plan.migration_type.upper()}")
output.append(f"Complexity Level: {plan.complexity.upper()}")
output.append(f"Estimated Duration: {plan.estimated_duration_hours} hours ({plan.estimated_duration_hours/24:.1f} days)")
output.append(f"Created: {plan.created_at}")
output.append("")
# Phases
output.append("MIGRATION PHASES")
output.append("-" * 40)
for i, phase in enumerate(plan.phases, 1):
output.append(f"{i}. {phase.name.upper()} ({phase.duration_hours}h)")
output.append(f" Description: {phase.description}")
output.append(f" Risk Level: {phase.risk_level.upper()}")
if phase.dependencies:
output.append(f" Dependencies: {', '.join(phase.dependencies)}")
output.append(" Tasks:")
for task in phase.tasks:
output.append(f"{task}")
output.append(" Success Criteria:")
for criteria in phase.validation_criteria:
output.append(f"{criteria}")
output.append("")
# Risk Assessment
output.append("RISK ASSESSMENT")
output.append("-" * 40)
risk_by_severity = {}
for risk in plan.risks:
if risk.severity not in risk_by_severity:
risk_by_severity[risk.severity] = []
risk_by_severity[risk.severity].append(risk)
for severity in ["critical", "high", "medium", "low"]:
if severity in risk_by_severity:
output.append(f"{severity.upper()} SEVERITY RISKS:")
for risk in risk_by_severity[severity]:
output.append(f"{risk.description}")
output.append(f" Category: {risk.category}")
output.append(f" Probability: {risk.probability} | Impact: {risk.impact}")
output.append(f" Mitigation: {risk.mitigation}")
output.append(f" Owner: {risk.owner}")
output.append("")
# Rollback Plan
output.append("ROLLBACK STRATEGY")
output.append("-" * 40)
output.append("Rollback Triggers:")
for trigger in plan.rollback_plan["rollback_triggers"]:
output.append(f"{trigger}")
output.append("")
output.append("Rollback Phases:")
for rb_phase in plan.rollback_plan["rollback_phases"]:
output.append(f" {rb_phase['phase'].upper()}:")
for action in rb_phase["rollback_actions"]:
output.append(f" - {action}")
output.append(f" Estimated Time: {rb_phase['estimated_time_minutes']} minutes")
output.append("")
# Success Criteria
output.append("SUCCESS CRITERIA")
output.append("-" * 40)
for criteria in plan.success_criteria:
output.append(f"{criteria}")
output.append("")
# Stakeholders
output.append("STAKEHOLDERS")
output.append("-" * 40)
for stakeholder in plan.stakeholders:
output.append(f"{stakeholder}")
output.append("")
return "\n".join(output)
def main():
"""Main function with command line interface"""
parser = argparse.ArgumentParser(description="Generate comprehensive migration plans")
parser.add_argument("--input", "-i", required=True, help="Input migration specification file (JSON)")
parser.add_argument("--output", "-o", help="Output file for migration plan (JSON)")
parser.add_argument("--format", "-f", choices=["json", "text", "both"], default="both",
help="Output format")
parser.add_argument("--validate", action="store_true", help="Validate migration specification only")
args = parser.parse_args()
try:
# Load migration specification
with open(args.input, 'r') as f:
spec = json.load(f)
# Validate required fields
required_fields = ["type", "source", "target"]
for field in required_fields:
if field not in spec:
print(f"Error: Missing required field '{field}' in specification", file=sys.stderr)
return 1
if args.validate:
print("Migration specification is valid")
return 0
# Generate migration plan
planner = MigrationPlanner()
plan = planner.generate_plan(spec)
# Output results
if args.format in ["json", "both"]:
plan_dict = asdict(plan)
if args.output:
with open(args.output, 'w') as f:
json.dump(plan_dict, f, indent=2)
print(f"Migration plan saved to {args.output}")
else:
print(json.dumps(plan_dict, indent=2))
if args.format in ["text", "both"]:
human_plan = planner.generate_human_readable_plan(plan)
text_output = args.output.replace('.json', '.txt') if args.output else None
if text_output:
with open(text_output, 'w') as f:
f.write(human_plan)
print(f"Human-readable plan saved to {text_output}")
else:
print("\n" + "="*80)
print("HUMAN-READABLE MIGRATION PLAN")
print("="*80)
print(human_plan)
except FileNotFoundError:
print(f"Error: Input file '{args.input}' not found", file=sys.stderr)
return 1
except json.JSONDecodeError as e:
print(f"Error: Invalid JSON in input file: {e}", file=sys.stderr)
return 1
except Exception as e:
print(f"Error: {e}", file=sys.stderr)
return 1
return 0
if __name__ == "__main__":
sys.exit(main())