Distributed Systems¶

Muneris Mobile Ordering implements a distributed systems architecture that prioritizes predictable restaurant operations through regional deployment, automatic scaling, and distributed coordination strategies. The performance design balances throughput optimization with operational simplicity for restaurant environments.

Regional Architecture Design¶

Three-Region European Deployment¶

Geographic Distribution Strategy:

Primary Regions: Three Azure regions within Europe for high availability
Traffic Management: Azure Traffic Manager with DNS-based load balancing
Health Monitoring: Continuous regional availability checks every 30 seconds
Automatic Failover: Unhealthy regions automatically removed from rotation

Regional Endpoints:

Primary Domain: api.muneris.app (Traffic Manager endpoint)
Regional Access: api1.muneris.app, api2.muneris.app, api3.muneris.app
Admin Portal: admin.muneris.app with regional distribution
Documentation: docs.muneris.app with multi-region hosting

Performance Benefits of Regional Distribution¶

Latency Optimization:

Geographic Proximity: Users automatically routed to nearest healthy region
Network Path Reduction: Shorter network paths reduce connection time
Local Data Processing: All operations occur within user's geographic region
CDN Integration: Static assets distributed via regional content delivery networks

Availability Enhancement:

99.99% Uptime Target: Multi-region deployment enables high availability commitment
Regional Independence: Single region outage doesn't affect other regions
Graceful Degradation: Remaining regions handle full traffic load during failures
Planned Maintenance: Regions can be taken offline individually for updates

Auto-Scaling Architecture¶

Azure Functions Scaling Model¶

Serverless Scaling Characteristics:

Demand-Based Scaling: Automatic instance creation based on incoming request volume
Zero-to-Scale Capability: Scale from zero instances to handle traffic spikes
Pay-Per-Use Model: Costs aligned with actual restaurant traffic patterns
Regional Independence: Each region scales independently based on local demand

Restaurant Traffic Accommodation:

Variable Load Handling: System designed for restaurant peak and off-peak patterns
Rush Period Scaling: Automatic scaling during lunch and dinner rush periods
Off-Peak Efficiency: Minimal resource usage during restaurant closed hours
Event Traffic Management: Scaling capability for special events and promotions

Component Scaling Strategies¶

API Layer Scaling:

Function App Isolation: Separate function apps for authentication, orders, and configuration
Resource Optimization: Automatic memory and CPU allocation based on function requirements
Instance Lifecycle: Automatic instance creation, warm-up, and retirement based on demand
Regional Coordination: Traffic distributed across healthy regions during scaling events

Data Layer Performance:

Azure Table Storage: Optimized for property-based access patterns
Partition Strategy: Property codes serve as partition keys for optimal performance
Query Optimization: Index strategy designed for company and property-based queries
Regional Storage: Independent storage per region for data sovereignty

Distributed Systems Trade-offs¶

Consistency vs. Availability Design¶

Regional Consistency Model:

Strong Consistency: ACID properties maintained within each region
Eventual Consistency: Cross-region data synchronization handled manually when needed
Restaurant Requirements: Order accuracy requires strong consistency within region
Business Continuity: Manual procedures for cross-region business scenarios

Availability Prioritization: - Regional Independence: Regions operate completely independently - Partition Tolerance: Regional network partitions don't affect other regions - Data Sovereignty: GDPR and compliance requirements drive regional independence - Graceful Degradation: Services reduce functionality rather than complete failure

Master Region Coordination¶

Centralized Operations:

STS Token Management: One region designated for token refresh coordination
Token Distribution: Refreshed tokens replicated to other regions
12-Hour Refresh Cycle: Proactive token management with 10-day token lifetime
Master Failover: Manual intervention required for master region reassignment

Distributed State Management: - No Shared State: Regions maintain completely independent operational state - Local Session Management: User sessions scoped to single region only - Independent Configuration: Regional configuration management without synchronization - Autonomous Operation: Regions operate without cross-region dependencies

Performance Strategies¶

Integration Performance¶

Oracle Simphony Optimization:

Direct STS Communication: API calls bypass Muneris backend for menu and order operations
Token Lifecycle Management: Automatic token refresh prevents authentication delays
Connection Optimization: Efficient connection pooling for STS API communication
Error Recovery: Exponential backoff and retry logic for transient failures

Payment Provider Efficiency:

Multi-Provider Support: Viva, Softpay, Worldline, Adyen integration options
Provider Abstraction: Consistent interface regardless of backend provider
Regional Provider Selection: Optimal provider selection per geographic region
Timeout Management: Appropriate timeout configuration for payment processing

Caching Architecture¶

Multi-Layer Caching Strategy:

Menu Data Caching: Local storage enables offline order composition
Configuration Caching: Property settings cached to reduce API dependency
Regional Cache Management: Independent cache management per region
Update Synchronization: Cache invalidation patterns for data freshness

Mobile App Performance:

Offline Operation: Cached data enables continued operation during connectivity issues
Startup Optimization: Essential data cached for faster app startup
Background Sync: Configuration updates synchronized during idle periods
Bandwidth Optimization: Differential updates to minimize data transfer

Operational Resilience¶

Failure Handling Strategies¶

Component Failure Isolation:

Regional Failure Impact: Regional failures don't impact other regions
Service Isolation: Individual service failures don't cascade across region
Priority Operations: Order processing prioritized over configuration management
Automatic Recovery: Azure Functions automatic restart and scaling

External Service Resilience:

STS Integration Resilience: Automatic token refresh and connection retry logic
Payment Provider Backup: Multiple providers available for redundancy
Queue Management: Orders queued during temporary STS connectivity issues
Manual Recovery: Restaurant procedures for extended integration failures

Monitoring and Health Management¶

Regional Health Monitoring:

Continuous Monitoring: Real-time tracking of API endpoint availability
Database Health: Regional database connectivity and performance monitoring
External Service Status: Oracle STS and payment provider health tracking
Composite Health: Overall regional health based on component availability

Performance Monitoring: - Response Time Tracking: Continuous monitoring of API response times - Throughput Measurement: Request volume and processing capacity tracking - Error Rate Monitoring: Error frequency and type analysis - Resource Utilization: CPU, memory, and storage usage tracking

Technology Decisions¶

Platform Selection Rationale¶

Azure Functions Benefits:

Restaurant Traffic Alignment: Serverless model matches restaurant operational patterns
Cost Efficiency: Pay-per-use model reduces costs during off-peak hours
Automatic Scaling: Eliminates manual capacity planning and management
Regional Deployment: Native support for multi-region distributed deployment

Azure Table Storage Advantages:

Property-Based Partitioning: Natural alignment with restaurant property structure
Horizontal Scaling: Automatic scaling based on storage and throughput requirements
Regional Replication: Built-in support for regional data distribution
Cost Optimization: Storage costs scale with actual data usage

Performance vs. Cost Balance¶

Resource Optimization:

Automatic Resource Allocation: Functions scale resources based on actual demand
Regional Cost Distribution: Costs distributed across regions based on usage
Off-Peak Cost Reduction: Minimal infrastructure costs during restaurant closed hours
Predictable Scaling: Cost scaling aligned with restaurant growth patterns

Long-Term Scalability:

Restaurant Growth Accommodation: Architecture scales with customer restaurant expansion
Multi-Location Support: Efficient support for restaurant chains and franchises
Regional Expansion: Architecture ready for geographic market expansion
Technology Evolution: Platform flexibility for future technology adoption

Distributed Patterns¶

Service Discovery and Routing¶

Traffic Management Coordination:

DNS-Based Load Balancing: Azure Traffic Manager coordinates regional routing
Health-Based Routing: Automatic traffic redirection based on health status
Geographic Proximity: Users routed to nearest healthy region
Failover Coordination: Automatic failover with minimal service interruption

Regional Service Coordination:

Independent Service Discovery: Each region maintains independent service registry
Local Health Checks: Regional health monitoring without cross-region dependencies
Service Mesh Independence: No service mesh coordination required across regions
Configuration Independence: Regional configuration management without synchronization

Data Consistency Patterns¶

Regional Data Boundaries:

Customer Regional Assignment: Customers assigned to single region only
Property Regional Binding: Restaurant properties operate within single region
Configuration Independence: Regional configuration management without synchronization
Manual Cross-Region Operations: Business procedures for rare cross-region scenarios

Conflict Avoidance Strategies:

Data Boundary Enforcement: Technical prevention of cross-region data conflicts
Business-Level Resolution: Manual resolution for cross-region business scenarios
Regional Backup Independence: Each region maintains independent backup and recovery
Emergency Procedures: Manual export/import for business continuity scenarios

Future Considerations¶

Scalability Planning¶

Restaurant Industry Growth:

Market Expansion: Architecture designed for geographic market expansion
Customer Growth: Scalable foundation for increasing customer base
Feature Enhancement: Performance architecture supports new feature development
Technology Evolution: Platform flexibility for emerging restaurant technology trends

Performance Enhancement Opportunities:

Caching Optimization: Enhanced caching strategies for improved response times
Database Performance: Query optimization and indexing improvements
Integration Efficiency: Streamlined external service communication patterns
Regional Optimization: Region-specific performance tuning and optimization

System Integration: See System Architecture for component interaction details
Security Performance: See Security Architecture for security-related performance considerations
Implementation Setup: See Getting Started for performance optimization procedures

This performance and distributed systems analysis demonstrates how Muneris Mobile Ordering delivers consistent performance across European regions while maintaining operational independence and cost efficiency for restaurant operations.