Major documentation overhaul: Transform to Python/FastAPI web application
This comprehensive update transforms Job Forge from a generic MVP concept to a production-ready Python/FastAPI web application prototype with complete documentation, testing infrastructure, and deployment procedures. ## 🏗️ Architecture Changes - Updated all documentation to reflect Python/FastAPI + Dash + PostgreSQL stack - Transformed from MVP concept to deployable web application prototype - Added comprehensive multi-tenant architecture with Row Level Security (RLS) - Integrated Claude API and OpenAI API for AI-powered document generation ## 📚 Documentation Overhaul - **CLAUDE.md**: Complete rewrite as project orchestrator for 4 specialized agents - **README.md**: New centralized documentation hub with organized navigation - **API Specification**: Updated with comprehensive FastAPI endpoint documentation - **Database Design**: Enhanced schema with RLS policies and performance optimization - **Architecture Guide**: Transformed to web application focus with deployment strategy ## 🏗️ New Documentation Structure - **docs/development/**: Python/FastAPI coding standards and development guidelines - **docs/infrastructure/**: Docker setup and server deployment procedures - **docs/testing/**: Comprehensive QA procedures with pytest integration - **docs/ai/**: AI prompt templates and examples (preserved from original) ## 🎯 Team Structure Updates - **.claude/agents/**: 4 new Python/FastAPI specialized agents - simplified_technical_lead.md: Architecture and technical guidance - fullstack_developer.md: FastAPI backend + Dash frontend implementation - simplified_qa.md: pytest testing and quality assurance - simplified_devops.md: Docker deployment and server infrastructure ## 🧪 Testing Infrastructure - **pytest.ini**: Complete pytest configuration with coverage requirements - **tests/conftest.py**: Comprehensive test fixtures and database setup - **tests/unit/**: Example unit tests for auth and application services - **tests/integration/**: API integration test examples - Support for async testing, AI service mocking, and database testing ## 🧹 Cleanup - Removed 9 duplicate/outdated documentation files - Eliminated conflicting technology references (Node.js/TypeScript) - Consolidated overlapping content into comprehensive guides - Cleaned up project structure for professional development workflow ## 🚀 Production Ready Features - Docker containerization for development and production - Server deployment procedures for prototype hosting - Security best practices with JWT authentication and RLS - Performance optimization with database indexing and caching - Comprehensive testing strategy with quality gates This update establishes Job Forge as a professional Python/FastAPI web application prototype ready for development and deployment. 🤖 Generated with Claude Code (https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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# Deployment Guide: [Release Version]
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## Release Information
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- **Version**: [Version Number]
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- **Release Date**: [Date]
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- **Release Type**: [Feature/Hotfix/Security/Maintenance]
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- **Release Manager**: [Name]
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## Release Summary
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Brief description of what's being deployed, major features, and business impact.
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### ✨ New Features
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- [Feature 1]: Description and business value
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- [Feature 2]: Description and business value
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### 🐛 Bug Fixes
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- [Bug Fix 1]: Description of issue resolved
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- [Bug Fix 2]: Description of issue resolved
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### 🔧 Technical Improvements
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- [Improvement 1]: Performance/security/maintenance improvement
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- [Improvement 2]: Infrastructure or code quality improvement
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## Pre-Deployment Checklist
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### ✅ Quality Assurance
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- [ ] All automated tests passing (unit, integration, E2E)
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- [ ] Manual testing completed and signed off
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- [ ] Performance testing completed
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- [ ] Security scan passed with no critical issues
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- [ ] Cross-browser testing completed
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- [ ] Mobile responsiveness verified
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- [ ] Accessibility requirements met
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### 🔐 Security & Compliance
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- [ ] Security review completed
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- [ ] Dependency vulnerabilities resolved
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- [ ] Environment variables secured
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- [ ] Database migration reviewed for data safety
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- [ ] Backup procedures verified
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- [ ] Compliance requirements met
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### 📋 Documentation & Communication
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- [ ] Release notes prepared
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- [ ] API documentation updated
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- [ ] User documentation updated
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- [ ] Stakeholders notified of deployment
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- [ ] Support team briefed on changes
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- [ ] Rollback plan documented
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### 🏗️ Infrastructure & Environment
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- [ ] Staging environment matches production
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- [ ] Database migrations tested on staging
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- [ ] Environment variables configured
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- [ ] SSL certificates valid and updated
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- [ ] Monitoring and alerting configured
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- [ ] Backup systems operational
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## Environment Configuration
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### Environment Variables
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```bash
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# Required Environment Variables
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NODE_ENV=production
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DATABASE_URL=postgresql://user:pass@host:port/dbname
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REDIS_URL=redis://host:port
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JWT_SECRET=your-secure-jwt-secret
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API_BASE_URL=https://api.yourdomain.com
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# Third-party Services
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STRIPE_SECRET_KEY=sk_live_...
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SENDGRID_API_KEY=SG...
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SENTRY_DSN=https://...
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# Optional Configuration
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LOG_LEVEL=info
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RATE_LIMIT_MAX=1000
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SESSION_TIMEOUT=3600
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```
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### Database Configuration
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```sql
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-- Database migration checklist
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-- [ ] Backup current database
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-- [ ] Test migration on staging
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-- [ ] Verify data integrity
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-- [ ] Update indexes if needed
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-- [ ] Check foreign key constraints
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-- Example migration
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-- Migration: 2024-01-01-add-user-preferences.sql
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ALTER TABLE users ADD COLUMN preferences JSONB DEFAULT '{}';
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CREATE INDEX idx_users_preferences ON users USING GIN (preferences);
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```
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## Deployment Procedure
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### Step 1: Pre-Deployment Verification
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```bash
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# Verify current system status
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curl -f https://api.yourdomain.com/health
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curl -f https://yourdomain.com/health
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# Check system resources
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docker stats
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df -h
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# Verify monitoring systems
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# Check Sentry, DataDog, or monitoring dashboard
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```
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### Step 2: Database Migration (if applicable)
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```bash
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# 1. Create database backup
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pg_dump $DATABASE_URL > backup_$(date +%Y%m%d_%H%M%S).sql
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# 2. Run migration in staging (verify first)
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npm run migrate:staging
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# 3. Verify migration succeeded
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npm run migrate:status
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# 4. Run migration in production (when ready)
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npm run migrate:production
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```
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### Step 3: Application Deployment
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#### Option A: Automated Deployment (CI/CD)
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```yaml
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# GitHub Actions / GitLab CI deployment
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deployment_trigger:
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- push_to_main_branch
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- manual_trigger_from_dashboard
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deployment_steps:
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1. run_automated_tests
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2. build_application
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3. deploy_to_staging
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4. run_smoke_tests
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5. wait_for_approval
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6. deploy_to_production
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7. run_post_deployment_tests
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```
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#### Option B: Manual Deployment
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```bash
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# 1. Pull latest code
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git checkout main
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git pull origin main
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# 2. Install dependencies
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npm ci --production
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# 3. Build application
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npm run build
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# 4. Deploy using platform-specific commands
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# Vercel
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vercel --prod
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# Heroku
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git push heroku main
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# Docker
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docker build -t app:latest .
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docker push registry/app:latest
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kubectl set image deployment/app app=registry/app:latest
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```
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### Step 4: Post-Deployment Verification
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```bash
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# 1. Health checks
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curl -f https://api.yourdomain.com/health
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curl -f https://yourdomain.com/health
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# 2. Smoke tests
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npm run test:smoke:production
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# 3. Verify key functionality
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curl -X POST https://api.yourdomain.com/api/auth/login \
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-H "Content-Type: application/json" \
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-d '{"email":"test@example.com","password":"test123"}'
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# 4. Check error rates and performance
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# Monitor for first 30 minutes after deployment
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```
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## Monitoring & Alerting
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### Key Metrics to Monitor
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```yaml
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application_metrics:
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- response_time_p95: < 500ms
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- error_rate: < 1%
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- throughput: requests_per_second
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- database_connections: < 80% of pool
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infrastructure_metrics:
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- cpu_usage: < 70%
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- memory_usage: < 80%
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- disk_usage: < 85%
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- network_latency: < 100ms
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business_metrics:
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- user_registrations: normal_levels
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- conversion_rates: no_significant_drop
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- payment_processing: functioning_normally
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```
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### Alert Configuration
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```yaml
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critical_alerts:
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- error_rate > 5%
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- response_time > 2000ms
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- database_connections > 90%
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- application_crashes
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warning_alerts:
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- error_rate > 2%
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- response_time > 1000ms
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- cpu_usage > 80%
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- memory_usage > 85%
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notification_channels:
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- slack: #alerts-critical
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- email: devops@company.com
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- pagerduty: production-alerts
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```
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## Rollback Plan
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### When to Rollback
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- Critical application errors affecting > 10% of users
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- Data corruption or data loss incidents
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- Security vulnerabilities exposed
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- Performance degradation > 50% from baseline
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- Core functionality completely broken
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### Rollback Procedure
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```bash
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# Option 1: Platform rollback (recommended)
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# Vercel
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vercel rollback [deployment-url]
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# Heroku
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heroku rollback v[previous-version]
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# Kubernetes
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kubectl rollout undo deployment/app
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# Option 2: Git revert (if platform rollback unavailable)
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git revert HEAD
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git push origin main
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# Option 3: Database rollback (if needed)
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# Restore from backup taken before deployment
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pg_restore -d $DATABASE_URL backup_[timestamp].sql
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```
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### Post-Rollback Actions
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1. **Immediate**: Verify system stability
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2. **Within 1 hour**: Investigate root cause
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3. **Within 4 hours**: Fix identified issues
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4. **Within 24 hours**: Plan and execute re-deployment
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## Communication Plan
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### Pre-Deployment Communication
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```markdown
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**Subject**: Scheduled Deployment - [Application Name] v[Version]
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**Team**: [Development Team]
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**Date**: [Deployment Date]
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**Time**: [Deployment Time with timezone]
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**Duration**: [Expected duration]
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**Changes**:
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- [Brief list of major changes]
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**Impact**:
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- [Any expected user impact or downtime]
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**Support**: [Contact information for deployment team]
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```
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### Post-Deployment Communication
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```markdown
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**Subject**: Deployment Complete - [Application Name] v[Version]
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**Status**: ✅ Successful / ❌ Failed / ⚠️ Partial
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**Completed At**: [Time]
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**Duration**: [Actual duration]
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**Verification**:
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- ✅ Health checks passing
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- ✅
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