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test examples - Support for async testing, AI service mocking, and database testing ## 🧹 Cleanup - Removed 9 duplicate/outdated documentation files - Eliminated conflicting technology references (Node.js/TypeScript) - Consolidated overlapping content into comprehensive guides - Cleaned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]
Release Information
- Version: [Version Number]
- Release Date: [Date]
- Release Type: [Feature/Hotfix/Security/Maintenance]
- Release Manager: [Name]
Release Summary
Brief description of what's being deployed, major features, and business impact.
✨ New Features
- [Feature 1]: Description and business value
- [Feature 2]: Description and business value
🐛 Bug Fixes
- [Bug Fix 1]: Description of issue resolved
- [Bug Fix 2]: Description of issue resolved
🔧 Technical Improvements
- [Improvement 1]: Performance/security/maintenance improvement
- [Improvement 2]: Infrastructure or code quality improvement
Pre-Deployment Checklist
✅ Quality Assurance
- All automated tests passing (unit, integration, E2E)
- Manual testing completed and signed off
- Performance testing completed
- Security scan passed with no critical issues
- Cross-browser testing completed
- Mobile responsiveness verified
- Accessibility requirements met
🔐 Security & Compliance
- Security review completed
- Dependency vulnerabilities resolved
- Environment variables secured
- Database migration reviewed for data safety
- Backup procedures verified
- Compliance requirements met
📋 Documentation & Communication
- Release notes prepared
- API documentation updated
- User documentation updated
- Stakeholders notified of deployment
- Support team briefed on changes
- Rollback plan documented
🏗️ Infrastructure & Environment
- Staging environment matches production
- Database migrations tested on staging
- Environment variables configured
- SSL certificates valid and updated
- Monitoring and alerting configured
- Backup systems operational
Environment Configuration
Environment Variables
# Required Environment Variables
NODE_ENV=production
DATABASE_URL=postgresql://user:pass@host:port/dbname
REDIS_URL=redis://host:port
JWT_SECRET=your-secure-jwt-secret
API_BASE_URL=https://api.yourdomain.com
# Third-party Services
STRIPE_SECRET_KEY=sk_live_...
SENDGRID_API_KEY=SG...
SENTRY_DSN=https://...
# Optional Configuration
LOG_LEVEL=info
RATE_LIMIT_MAX=1000
SESSION_TIMEOUT=3600
Database Configuration
-- Database migration checklist
-- [ ] Backup current database
-- [ ] Test migration on staging
-- [ ] Verify data integrity
-- [ ] Update indexes if needed
-- [ ] Check foreign key constraints
-- Example migration
-- Migration: 2024-01-01-add-user-preferences.sql
ALTER TABLE users ADD COLUMN preferences JSONB DEFAULT '{}';
CREATE INDEX idx_users_preferences ON users USING GIN (preferences);
Deployment Procedure
Step 1: Pre-Deployment Verification
# Verify current system status
curl -f https://api.yourdomain.com/health
curl -f https://yourdomain.com/health
# Check system resources
docker stats
df -h
# Verify monitoring systems
# Check Sentry, DataDog, or monitoring dashboard
Step 2: Database Migration (if applicable)
# 1. Create database backup
pg_dump $DATABASE_URL > backup_$(date +%Y%m%d_%H%M%S).sql
# 2. Run migration in staging (verify first)
npm run migrate:staging
# 3. Verify migration succeeded
npm run migrate:status
# 4. Run migration in production (when ready)
npm run migrate:production
Step 3: Application Deployment
Option A: Automated Deployment (CI/CD)
# GitHub Actions / GitLab CI deployment
deployment_trigger:
- push_to_main_branch
- manual_trigger_from_dashboard
deployment_steps:
1. run_automated_tests
2. build_application
3. deploy_to_staging
4. run_smoke_tests
5. wait_for_approval
6. deploy_to_production
7. run_post_deployment_tests
Option B: Manual Deployment
# 1. Pull latest code
git checkout main
git pull origin main
# 2. Install dependencies
npm ci --production
# 3. Build application
npm run build
# 4. Deploy using platform-specific commands
# Vercel
vercel --prod
# Heroku
git push heroku main
# Docker
docker build -t app:latest .
docker push registry/app:latest
kubectl set image deployment/app app=registry/app:latest
Step 4: Post-Deployment Verification
# 1. Health checks
curl -f https://api.yourdomain.com/health
curl -f https://yourdomain.com/health
# 2. Smoke tests
npm run test:smoke:production
# 3. Verify key functionality
curl -X POST https://api.yourdomain.com/api/auth/login \
-H "Content-Type: application/json" \
-d '{"email":"test@example.com","password":"test123"}'
# 4. Check error rates and performance
# Monitor for first 30 minutes after deployment
Monitoring & Alerting
Key Metrics to Monitor
application_metrics:
- response_time_p95: < 500ms
- error_rate: < 1%
- throughput: requests_per_second
- database_connections: < 80% of pool
infrastructure_metrics:
- cpu_usage: < 70%
- memory_usage: < 80%
- disk_usage: < 85%
- network_latency: < 100ms
business_metrics:
- user_registrations: normal_levels
- conversion_rates: no_significant_drop
- payment_processing: functioning_normally
Alert Configuration
critical_alerts:
- error_rate > 5%
- response_time > 2000ms
- database_connections > 90%
- application_crashes
warning_alerts:
- error_rate > 2%
- response_time > 1000ms
- cpu_usage > 80%
- memory_usage > 85%
notification_channels:
- slack: #alerts-critical
- email: devops@company.com
- pagerduty: production-alerts
Rollback Plan
When to Rollback
- Critical application errors affecting > 10% of users
- Data corruption or data loss incidents
- Security vulnerabilities exposed
- Performance degradation > 50% from baseline
- Core functionality completely broken
Rollback Procedure
# Option 1: Platform rollback (recommended)
# Vercel
vercel rollback [deployment-url]
# Heroku
heroku rollback v[previous-version]
# Kubernetes
kubectl rollout undo deployment/app
# Option 2: Git revert (if platform rollback unavailable)
git revert HEAD
git push origin main
# Option 3: Database rollback (if needed)
# Restore from backup taken before deployment
pg_restore -d $DATABASE_URL backup_[timestamp].sql
Post-Rollback Actions
- Immediate: Verify system stability
- Within 1 hour: Investigate root cause
- Within 4 hours: Fix identified issues
- Within 24 hours: Plan and execute re-deployment
Communication Plan
Pre-Deployment Communication
**Subject**: Scheduled Deployment - [Application Name] v[Version]
**Team**: [Development Team]
**Date**: [Deployment Date]
**Time**: [Deployment Time with timezone]
**Duration**: [Expected duration]
**Changes**:
- [Brief list of major changes]
**Impact**:
- [Any expected user impact or downtime]
**Support**: [Contact information for deployment team]
Post-Deployment Communication
**Subject**: Deployment Complete - [Application Name] v[Version]
**Status**: ✅ Successful / ❌ Failed / ⚠️ Partial
**Completed At**: [Time]
**Duration**: [Actual duration]
**Verification**:
- ✅ Health checks passing
- ✅