Technical Constraints & Requirements
Defines platform, performance, security, and deployment constraints for a Scottish mountain weather app with native iOS/Android and PWA fallback.
What this file does
Defines platform, performance, security, and deployment constraints for a Scottish mountain weather app with native iOS/Android and PWA fallback.
When to use it
- Starting a weather or location-based mobile app with strict performance targets
- Documenting technical constraints for a cross-platform project with native development
- Planning infrastructure and budget for a data-intensive app with GDPR compliance
- Establishing integration requirements for multiple weather data sources
Assumes this stack
Technical Constraints & Requirements
This document defines the technical constraints, requirements, and architecture decisions for the Scottish Mountain Weather App development.
Platform & Compatibility Requirements
Mobile Platform Support
iOS Requirements:
- Minimum Version: iOS 13.0+ (covers 95% of active users)
- Target Devices: iPhone 8 and newer, iPad Air 2 and newer
- Development: Swift 5.0+ with UIKit/SwiftUI hybrid approach
- Distribution: Apple App Store with TestFlight for beta testing
- Features: Background app refresh, push notifications, Core Location
Android Requirements:
- Minimum Version: Android 8.0 (API level 26+) (covers 87% of active users)
- Target Devices: 3GB+ RAM, screens 4.7"-6.9"
- Development: Kotlin with Jetpack Compose for modern UI
- Distribution: Google Play Store with internal testing track
- Features: Foreground services, FCM notifications, Location Services
Progressive Web App (PWA):
- Browsers: Chrome 80+, Safari 13+, Firefox 75+, Edge 80+
- Features: Service Worker for offline, Web App Manifest
- Limitations: No background sync, limited push notification support on iOS
- Use Case: Fallback for users who prefer web access
Cross-Platform Framework Decision
Recommendation: Native Development
- Rationale: Weather apps require optimal performance and platform-specific features
- iOS: Swift/SwiftUI for modern declarative UI
- Android: Kotlin/Jetpack Compose for performance and modern architecture
- Shared: REST API backend, common design system principles
Alternative Considered: React Native
- Pros: Faster development, shared codebase
- Cons: Performance concerns for real-time weather data, platform-specific features complexity
- Decision: Not recommended for v1.0 due to performance requirements
Performance Requirements
Application Performance
Launch Time:
- Cold start: <2 seconds on iPhone 8/Galaxy S9 equivalent
- Warm start: <1 second
- First meaningful paint: <1.5 seconds
- Time to interactive: <3 seconds
Runtime Performance:
- Memory usage: <150MB for active use
- CPU usage: <20% during normal operation
- Battery drain: <5% per hour of active use
- Scroll performance: 60fps minimum, targeting 120fps on capable devices
Network Performance:
- API calls: <500ms response time for weather data
- Image loading: Progressive loading with placeholders
- Offline capability: Core functionality available for 24 hours
- Data usage: <1MB per weather check, <5MB per session
Backend Performance
API Response Times:
- Location search: <200ms (95th percentile)
- Weather data: <500ms (95th percentile)
- Weather comparison: <800ms (95th percentile)
- Health check: <50ms (99th percentile)
Scalability Requirements:
- Concurrent users: 1,000+ simultaneous API requests
- Daily requests: 100,000+ API calls
- Data throughput: 10GB+ daily weather data processing
- Uptime: 99.5% availability (4.38 hours downtime/month)
Technical Architecture Constraints
Backend Technology Stack
Primary Stack (Recommended):
Backend Framework: FastAPI (Python 3.9+)
Database: PostgreSQL 13+ with TimescaleDB extension
Cache: Redis 6.0+
Message Queue: Celery with Redis broker
Monitoring: Prometheus + Grafana
Logging: Structured JSON logging with ELK stack
Rationale:
- FastAPI: High performance, automatic API documentation, async support
- PostgreSQL + TimescaleDB: Excellent time-series data handling for weather
- Redis: High-performance caching and session storage
- Python: Leverage existing weather_scraper.py codebase
Alternative Stack (if Python constraints exist):
Backend Framework: Node.js with Express/Fastify
Database: PostgreSQL with time-series optimizations
Cache: Redis
Message Queue: Bull (Redis-based)
Infrastructure Requirements
Cloud Platform (Recommended: AWS):
Compute: ECS Fargate containers
Database: RDS PostgreSQL with read replicas
Cache: ElastiCache Redis cluster
Storage: S3 for static assets and backups
CDN: CloudFront for global distribution
Load Balancer: ALB with health checks
Alternative: Google Cloud Platform:
Compute: Cloud Run containers
Database: Cloud SQL PostgreSQL
Cache: Memorystore for Redis
Storage: Cloud Storage
CDN: Cloud CDN
Load Balancer: Cloud Load Balancing
Infrastructure Constraints:
- Region: EU-West (Ireland) for GDPR compliance
- Backup: Daily automated backups with 30-day retention
- Disaster Recovery: Cross-AZ deployment, <4 hour RTO
- Security: VPC isolation, WAF protection, DDoS mitigation
Data Storage Requirements
Weather Data Volume Estimates:
- Locations: ~500 Scottish mountains
- Updates: 4 times daily per location
- Data retention: 2 years of historical data
- Growth rate: ~100MB/month new data
- Total storage: ~5GB database, ~20GB with indexes and backups
Database Schema Constraints:
- Weather data: Time-series optimized (TimescaleDB hypertables)
- Location data: Spatial indexes for proximity queries
- User data: Minimal storage, encrypted preferences only
- Backups: Point-in-time recovery capability
Security & Privacy Constraints
Data Protection Requirements
GDPR Compliance (EU Users):
- Data minimization: Collect only necessary data
- Consent management: Clear opt-in for location services
- Right to erasure: Delete user data on request
- Data portability: Export user preferences in JSON format
- Privacy by design: Default to most private settings
Data Encryption:
- In transit: TLS 1.3 for all API communications
- At rest: AES-256 encryption for sensitive data
- Keys: AWS KMS or equivalent key management
- Certificates: Let's Encrypt with automatic renewal
Authentication & Authorization:
- API security: JWT tokens with short expiration
- Rate limiting: Prevent abuse and DoS attacks
- Input validation: Sanitize all user inputs
- SQL injection: Parameterized queries only
Privacy Constraints
Location Data:
- Permission: Explicit user consent required
- Usage: Only for nearby location suggestions
- Storage: No persistent location history
- Sharing: Never shared with third parties
Analytics & Monitoring:
- Personal data: No collection of personal identifiers
- Usage tracking: Anonymized analytics only
- Error reporting: Crash logs without personal data
- Compliance: Privacy-focused analytics (e.g., Plausible vs Google Analytics)
Integration Constraints
Weather Data Sources
Existing System Integration:
- weather_scraper.py: Enhance existing Python scraper
- YAML config: Maintain current configuration system
- Data format: Compatible with existing JSON output
- Scheduling: Keep current 4-hour update cycle
External API Constraints:
- MWIS: Free service, no API key, rate limiting unknown
- Met Office: DataPoint API, requires registration, 5000 calls/day free
- Mountain-Forecast.com: No official API, scraping only
- OpenWeatherMap: Current integration maintained
Data Quality Requirements:
- Accuracy target: >85% forecast accuracy vs actual conditions
- Freshness: Maximum 6 hours for safety-critical data
- Reliability: Graceful degradation when sources unavailable
- Validation: Cross-source consistency checking
Third-Party Service Constraints
Maps & Location:
- iOS: MapKit for maps, Core Location for GPS
- Android: Google Maps API (requires billing), Android Location Services
- Web: Mapbox GL JS (free tier available)
- Offline: Cache map tiles for essential mountain areas
Push Notifications:
- iOS: Apple Push Notification Service (APNs)
- Android: Firebase Cloud Messaging (FCM)
- Constraints: iOS requires annual developer program ($99/year)
Crash Reporting & Analytics:
- Options: Sentry (error tracking), Mixpanel (privacy-focused analytics)
- Requirements: GDPR compliant, minimal data collection
- Budget: <$100/month for production usage
Development Constraints
Team & Resource Constraints
Development Team Requirements:
- Full-stack developer: Python/FastAPI backend experience
- iOS developer: Swift/SwiftUI experience required
- Android developer: Kotlin/Jetpack Compose preferred
- DevOps engineer: AWS/Docker experience for deployment
- Designer: Mobile UI/UX with accessibility experience
Timeline Constraints:
- MVP deadline: 16 weeks from start
- Beta testing: 2 weeks before public launch
- App store approval: Allow 2-4 weeks for review process
- Seasonal factor: Launch before winter season (September) preferred
Budget Constraints:
- Infrastructure: $200-500/month initial costs
- Third-party services: $100-300/month
- App store fees: $99/year iOS, $25 one-time Android
- SSL certificates: Free (Let's Encrypt)
- Total monthly operational cost: <$1000
Development Environment
Code Repository:
- Git hosting: GitHub with private repositories
- Branching: GitFlow with feature branches
- CI/CD: GitHub Actions for automated testing and deployment
- Code quality: ESLint/SwiftLint, automated testing required
Testing Requirements:
- Unit tests: >80% code coverage
- Integration tests: Critical user flows covered
- Performance tests: API response time validation
- Device testing: Physical devices for both iOS and Android
- Accessibility testing: VoiceOver and TalkBack compatibility
Deployment & Operations Constraints
Deployment Strategy
Backend Deployment:
- Containerization: Docker containers for consistency
- Orchestration: ECS Fargate or Google Cloud Run
- Blue-green deployment: Zero-downtime updates
- Database migrations: Automated with rollback capability
Mobile App Deployment:
- iOS: TestFlight beta → App Store review → Production
- Android: Internal testing → Open testing → Production
- Feature flags: Gradual rollout capability
- Update strategy: Forced updates for critical security fixes
Monitoring & Alerting
Application Monitoring:
- Uptime: External monitoring (UptimeRobot or similar)
- Performance: APM with response time tracking
- Errors: Real-time error alerting with Sentry
- Logs: Centralized logging with search capability
Business Metrics:
- User engagement: Daily/monthly active users
- App performance: Crash rates, load times
- Weather accuracy: Forecast vs actual condition tracking
- API usage: Request patterns and error rates
Compliance & Legal Constraints
App Store Requirements
iOS App Store:
- Content guidelines: Weather apps generally approved
- Technical requirements: 64-bit support, privacy labels
- Metadata: Accurate description, appropriate age rating
- Review time: 24-48 hours typical, up to 7 days possible
Google Play Store:
- Policy compliance: Data safety section required
- Target API: Must target recent Android API levels
- Content rating: PEGI/ESRB rating for content
- Review time: Usually within 24 hours
Accessibility Requirements
Legal Compliance:
- UK: Equality Act 2010 compliance
- EU: EN 301 549 standard
- US: Section 508 for government users
- International: WCAG 2.1 AA standard
Technical Implementation:
- Screen readers: VoiceOver (iOS) and TalkBack (Android) support
- Color contrast: 4.5:1 minimum ratio
- Text size: Dynamic type support
- Motor accessibility: 44pt minimum touch targets
Risk Mitigation
Technical Risks
Data Source Reliability:
- Risk: Weather sources become unavailable
- Mitigation: Multiple backup sources, graceful degradation
- Monitoring: Automated source health checking
Performance Degradation:
- Risk: App becomes slow under load
- Mitigation: Performance testing, auto-scaling infrastructure
- Monitoring: Real-time performance metrics
Security Vulnerabilities:
- Risk: Data breaches or service attacks
- Mitigation: Security audit, penetration testing, monitoring
- Response: Incident response plan, security patches
Operational Risks
App Store Rejection:
- Risk: Apps rejected for policy violations
- Mitigation: Follow guidelines strictly, test submission process
- Contingency: PWA fallback option
GDPR Violations:
- Risk: Privacy law non-compliance
- Mitigation: Privacy by design, legal review
- Monitoring: Data processing audit trail
This technical specification provides a comprehensive foundation for development while acknowledging real-world constraints and limitations.
What's inside
10 sections covering platform support, performance, architecture, security, integrations, development, deployment, compliance, and risk mitigation
Change this for your project
- Replace
Scottish Mountain Weather Appwith your project name - Replace
weather_scraper.pywith your existing scraper or data source - Replace
~500 Scottish mountainswith your location count and names - Replace
MWIS,Met Office,Mountain-Forecast.com,OpenWeatherMapwith your data sources
Where it goes
Keep it in your repository where the agent or team that needs it will read it.
Worth borrowing
- Separating platform-specific requirements (iOS, Android, PWA) with explicit version targets and device ranges
- Including alternative stacks (Node.js, GCP) alongside the primary recommendation for flexibility
- Listing concrete budget figures and timeline constraints to ground architectural decisions
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