Integration Systems Documentation¶

Overview¶

This document provides comprehensive analysis of all external system integrations for the Dispatch Center Application, including integration patterns, security requirements, data flow analysis, and implementation strategies.

Table of Contents¶

Integration Architecture
Source Data Systems Analysis
Integration Patterns
Integration Comparison Matrix
Security and Compliance
Data Flow and Transformation
Error Handling and Resilience
Monitoring and Observability
Implementation Roadmap

Integration Architecture¶

flowchart TB
    external["External Systems<br/>(Various)"]
    api_gateway["Azure API Management<br/>Gateway"]
    dispatch_app["Dispatch Center<br/>Application"]
    data_factory["Azure Data Factory<br/>(Batch)"]
    service_bus["Service Bus<br/>(Async)"]
    azure_sql["Azure SQL<br/>Database"]

    external --> api_gateway
    api_gateway --> dispatch_app
    external --> data_factory
    api_gateway --> service_bus
    dispatch_app --> azure_sql

Source Data Systems Analysis¶

Current State Assessment¶

Primary Challenge: Excessive data sharing with Reach system
Strategic Goal: Implement controlled, minimal data sharing architecture
Compliance Requirement: Reduce data exposure while maintaining operational efficiency
Timeline: Phased migration approach over 12-18 months

1. Reach - Legacy Dispatch System¶

System Overview¶

Type: Legacy dispatch and field service management
Current Status: Primary dispatch system (transitioning away)
Business Impact: High - Core operational dependency
Data Sensitivity: High - Customer PII, service history, technician data

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Hybrid approach - Real-time API for critical operations, batch synchronization for historical data migration

Q: Is this one-way or two-way integration? A: Two-way during transition period, transitioning to one-way (outbound only) as we reduce dependency

Q: What technology should be used for integration? A: RESTful APIs for real-time, Azure Data Factory for batch operations, Azure Service Bus for async messaging

Q: What are the security requirements? A: OAuth 2.0 authentication, TLS 1.3 encryption, data minimization (only essential fields), audit logging

Q: What is the data volume and frequency? A: ~10,000 service requests/month, real-time updates, 2TB historical data migration

Q: What are the error handling requirements? A: Retry logic with exponential backoff, dead letter queues, manual intervention for critical failures

Detailed Integration Specification¶

reach_integration:
  pattern: "Hybrid (API + Batch)"
  direction: "Bidirectional (transitioning to outbound)"
  technology:
    realtime: "RESTful API"
    batch: "Azure Data Factory"
    messaging: "Azure Service Bus"

  data_flow:
    inbound:
      - "Service request status updates"
      - "Technician availability"
      - "Customer communication logs"
    outbound:
      - "New service requests"
      - "Schedule updates"
      - "Customer information (minimal)"

  security:
    authentication: "OAuth 2.0"
    encryption: "TLS 1.3"
    data_minimization: true
    audit_logging: true

  sla:
    availability: "99.5%"
    response_time: "< 2 seconds"
    batch_window: "2 AM - 4 AM daily"

2. Maddenco - Equipment Management¶

System Overview¶

Type: Equipment lifecycle and maintenance management
Current Status: Active integration for asset tracking
Business Impact: Medium - Equipment visibility and maintenance scheduling
Data Sensitivity: Medium - Equipment specifications, maintenance history

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Request/Response API for real-time equipment status, batch sync for maintenance history

Q: Is this one-way or two-way integration? A: Primarily one-way inbound (equipment data into dispatch system)

Q: What technology should be used for integration? A: RESTful API with webhook notifications for equipment status changes

Q: What are the security requirements? A: API key authentication, HTTPS encryption, IP whitelisting

Q: What is the data volume and frequency? A: ~5,000 equipment records, status updates every 15 minutes, maintenance logs daily

Q: What are the error handling requirements? A: Standard retry logic, graceful degradation if equipment data unavailable

Detailed Integration Specification¶

maddenco_integration:
  pattern: "Request/Response + Webhooks"
  direction: "Primarily inbound"
  technology:
    primary: "RESTful API"
    notifications: "Webhooks"
    batch: "Daily synchronization"

  data_flow:
    inbound:
      - "Equipment status and location"
      - "Maintenance schedules"
      - "Equipment specifications"
      - "Warranty information"
    outbound:
      - "Work order completion status"
      - "Equipment usage reports"

  security:
    authentication: "API Key"
    encryption: "HTTPS/TLS 1.2+"
    ip_whitelisting: true
    rate_limiting: "1000 requests/hour"

3. Treadnet - Network Operations¶

System Overview¶

Type: Network infrastructure monitoring and management
Current Status: Monitoring integration for service impacts
Business Impact: Medium - Network outage correlation with service requests
Data Sensitivity: Low-Medium - Network topology, outage information

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Event-driven messaging for network alerts, batch sync for historical data

Q: Is this one-way or two-way integration? A: One-way inbound (network events into dispatch system)

Q: What technology should be used for integration? A: SNMP traps converted to Service Bus messages, REST API for historical queries

Q: What are the security requirements? A: Network segmentation, VPN connectivity, certificate-based authentication

Q: What is the data volume and frequency? A: ~500 network events/day, real-time alerting, historical data on-demand

Q: What are the error handling requirements? A: Event buffering, duplicate detection, correlation with service requests

Detailed Integration Specification¶

treadnet_integration:
  pattern: "Event-driven messaging"
  direction: "Inbound only"
  technology:
    events: "SNMP to Service Bus conversion"
    queries: "RESTful API"
    processing: "Azure Functions"

  data_flow:
    inbound:
      - "Network outage alerts"
      - "Service impact notifications"
      - "Network topology changes"
      - "Performance degradation events"

  security:
    connectivity: "VPN tunnel"
    authentication: "Certificate-based"
    network_segmentation: true

4. Dayforce - Human Resources¶

System Overview¶

Type: HR information system and workforce management
Current Status: Employee data synchronization
Business Impact: Medium - Technician information and scheduling
Data Sensitivity: High - Employee PII, compensation, schedules

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Batch synchronization for employee data, real-time API for schedule changes

Q: Is this one-way or two-way integration? A: Primarily one-way inbound (employee data), limited outbound (time tracking)

Q: What technology should be used for integration? A: Dayforce REST API, Azure Data Factory for batch operations

Q: What are the security requirements? A: OAuth 2.0, strong encryption, data minimization (only work-related data)

Q: What is the data volume and frequency? A: ~200 employee records, daily sync, real-time schedule updates

Q: What are the error handling requirements? A: Data validation, conflict resolution, manual review for discrepancies

Detailed Integration Specification¶

dayforce_integration:
  pattern: "Batch + Real-time API"
  direction: "Bidirectional (limited outbound)"
  technology:
    batch: "Azure Data Factory"
    realtime: "Dayforce REST API"
    scheduling: "Logic Apps"

  data_flow:
    inbound:
      - "Employee master data"
      - "Work schedules"
      - "Skills and certifications"
      - "Availability status"
    outbound:
      - "Time tracking data"
      - "Work order completion"

  security:
    authentication: "OAuth 2.0"
    encryption: "TLS 1.3"
    data_minimization: true
    gdpr_compliance: true

5. GeoTab - Vehicle Tracking¶

System Overview¶

Type: Fleet management and GPS tracking
Current Status: Real-time vehicle location tracking
Business Impact: High - Route optimization and technician dispatching
Data Sensitivity: Medium - Vehicle locations, driver behavior

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Real-time API for location tracking, webhooks for geofence events

Q: Is this one-way or two-way integration? A: Primarily one-way inbound (location data), limited outbound (route assignments)

Q: What technology should be used for integration? A: GeoTab API, SignalR for real-time updates to dispatch interface

Q: What are the security requirements? A: API authentication, encrypted data transmission, location data privacy

Q: What is the data volume and frequency? A: ~50 vehicles, GPS updates every 30 seconds, 100MB/day data volume

Q: What are the error handling requirements? A: GPS signal loss handling, data interpolation, alert for extended offline periods

Detailed Integration Specification¶

geotab_integration:
  pattern: "Real-time API + Event notifications"
  direction: "Bidirectional"
  technology:
    tracking: "GeoTab MyGeotab API"
    realtime: "SignalR Hub"
    events: "Webhook notifications"

  data_flow:
    inbound:
      - "Real-time GPS coordinates"
      - "Vehicle status and diagnostics"
      - "Driver behavior data"
      - "Geofence entry/exit events"
    outbound:
      - "Route assignments"
      - "Job site locations"

  security:
    authentication: "OAuth 2.0"
    encryption: "TLS 1.3"
    data_retention: "30 days GPS history"
    privacy_compliance: true

6. Merchant Partners - Payment Processing¶

System Overview¶

Type: Payment gateway and financial transaction processing
Current Status: Payment processing for customer billing
Business Impact: High - Revenue collection and financial operations
Data Sensitivity: Very High - PCI DSS compliance required

Integration Analysis Questions & Answers¶

Q: What integration pattern is most appropriate? A: Secure API integration with tokenization, batch settlement reporting

Q: Is this one-way or two-way integration? A: Two-way (payment requests outbound, confirmations inbound)

Q: What technology should be used for integration? A: PCI-compliant payment gateway API, tokenization service

Q: What are the security requirements? A: PCI DSS Level 1 compliance, tokenization, encryption, fraud detection

Q: What is the data volume and frequency? A: ~1,000 transactions/month, real-time authorization, daily settlement

Q: What are the error handling requirements? A: Payment retry logic, fraud detection, chargeback management

Detailed Integration Specification¶

merchant_partners_integration:
  pattern: "Secure payment gateway"
  direction: "Bidirectional"
  technology:
    payment_api: "PCI-compliant gateway"
    tokenization: "Payment tokenization service"
    settlement: "Batch reporting"

  data_flow:
    outbound:
      - "Payment authorization requests"
      - "Customer billing information"
      - "Invoice amounts and details"
    inbound:
      - "Payment confirmations"
      - "Settlement reports"
      - "Fraud alerts"
      - "Chargeback notifications"

  security:
    compliance: "PCI DSS Level 1"
    encryption: "End-to-end encryption"
    tokenization: true
    fraud_detection: true

  sla:
    authorization_time: "< 3 seconds"
    availability: "99.9%"
    settlement_window: "Next business day"

Integration Patterns¶

1. Request/Response - RESTful API¶

Use Cases: Real-time data queries, immediate responses required - Implementation: Azure API Management gateway - Security: OAuth 2.0, rate limiting, request validation - Error Handling: HTTP status codes, retry logic - Examples: Reach status updates, Maddenco equipment queries

2. Event-Driven Messaging¶

Use Cases: Asynchronous notifications, loose coupling - Implementation: Azure Service Bus with topics/subscriptions - Security: Shared Access Signatures, message encryption - Error Handling: Dead letter queues, retry policies - Examples: Treadnet network alerts, GeoTab geofence events

3. Batch Processing¶

Use Cases: Large data volumes, scheduled synchronization - Implementation: Azure Data Factory pipelines - Security: Managed Identity, encrypted storage - Error Handling: Pipeline monitoring, automatic retry - Examples: Dayforce employee sync, historical data migration

4. Webhook Notifications¶

Use Cases: Real-time event notifications, reverse API calls - Implementation: HTTPS endpoints with validation - Security: Signature verification, IP whitelisting - Error Handling: Retry mechanisms, acknowledgment patterns - Examples: Payment confirmations, equipment status changes

Integration Comparison Matrix¶

System	Pattern	Direction	Technology	Security	Data Volume	Frequency	Criticality
Reach	Hybrid	Bidirectional → Outbound	REST API + ADF	OAuth 2.0, TLS 1.3	High (2TB historical)	Real-time + Daily	Critical
Maddenco	Request/Response + Webhooks	Inbound	REST API	API Key, HTTPS	Medium (5K records)	15 min intervals	Medium
Treadnet	Event-driven	Inbound	SNMP → Service Bus	Certificate-based	Low (500 events/day)	Real-time	Medium
Dayforce	Batch + Real-time	Bidirectional	REST API + ADF	OAuth 2.0, TLS 1.3	Low (200 employees)	Daily + Real-time	Medium
GeoTab	Real-time API	Bidirectional	REST API + SignalR	OAuth 2.0, TLS 1.3	Medium (100MB/day)	30 sec intervals	High
Merchant Partners	Payment Gateway	Bidirectional	Payment API	PCI DSS Level 1	Low (1K trans/month)	Real-time	Critical

Integration Complexity Analysis¶

System	Technical Complexity	Business Complexity	Risk Level	Implementation Effort
Reach	High	Very High	High	8-12 months
Maddenco	Medium	Low	Low	2-3 months
Treadnet	Medium	Medium	Medium	3-4 months
Dayforce	Medium	Medium	Medium	4-6 months
GeoTab	High	Low	Medium	3-4 months
Merchant Partners	High	High	Very High	6-8 months

Data Sensitivity and Compliance Matrix¶

System	PII Data	Financial Data	Compliance Requirements	Data Retention
Reach	Yes (Customer)	No	GDPR, State Privacy Laws	7 years
Maddenco	No	No	Industry Standards	5 years
Treadnet	No	No	Internal Policies	2 years
Dayforce	Yes (Employee)	Yes (Payroll)	GDPR, Labor Laws	7 years
GeoTab	Limited (Driver)	No	Privacy Laws	30 days
Merchant Partners	Yes (Customer)	Yes (Payment)	PCI DSS, GDPR	7 years

Security and Compliance¶

Authentication Methods by System¶

authentication_matrix:
  oauth2_systems:
    - "Reach"
    - "Dayforce" 
    - "GeoTab"
    - "Merchant Partners"

  api_key_systems:
    - "Maddenco"

  certificate_based:
    - "Treadnet"

Encryption Requirements¶

encryption_standards:
  in_transit:
    minimum: "TLS 1.2"
    preferred: "TLS 1.3"
    cipher_suites: ["ECDHE-RSA-AES256-GCM-SHA384"]

  at_rest:
    azure_storage: "AES-256"
    database: "Transparent Data Encryption"
    key_management: "Azure Key Vault"

Compliance Mapping¶

compliance_requirements:
  pci_dss:
    applicable_systems: ["Merchant Partners"]
    level: "Level 1"

  gdpr:
    applicable_systems: ["Reach", "Dayforce", "Merchant Partners"]
    requirements: ["Data minimization", "Right to erasure", "Consent management"]

  industry_standards:
    applicable_systems: ["All"]
    standards: ["ISO 27001", "SOC 2 Type II"]

Data Flow and Transformation¶

Data Mapping Strategy¶

data_transformation:
  customer_data:
    source_fields: ["customer_id", "name", "address", "phone"]
    target_schema: "CustomerMaster"
    transformations:
      - "Phone number standardization"
      - "Address geocoding"
      - "Data deduplication"

  service_requests:
    source_fields: ["request_id", "customer_id", "description", "priority"]
    target_schema: "ServiceRequest"
    transformations:
      - "Priority level mapping"
      - "Category classification"
      - "SLA calculation"

Data Quality Rules¶

data_quality:
  validation_rules:
    customer_data:
      - "Email format validation"
      - "Phone number format validation"
      - "Required field checks"

    financial_data:
      - "Amount range validation"
      - "Currency code validation"
      - "Duplicate transaction detection"

  cleansing_rules:
    - "Trim whitespace"
    - "Standardize phone formats"
    - "Normalize addresses"
    - "Remove special characters from IDs"

Error Handling and Resilience¶

Retry Policies by Integration Type¶

retry_policies:
  critical_systems:
    - systems: ["Reach", "Merchant Partners"]
    - max_retries: 5
    - backoff_strategy: "Exponential"
    - base_delay: "2 seconds"
    - max_delay: "30 seconds"

  standard_systems:
    - systems: ["Maddenco", "Dayforce", "GeoTab"]
    - max_retries: 3
    - backoff_strategy: "Linear"
    - base_delay: "5 seconds"

  monitoring_systems:
    - systems: ["Treadnet"]
    - max_retries: 2
    - backoff_strategy: "Fixed"
    - delay: "10 seconds"

Circuit Breaker Configuration¶

circuit_breaker:
  failure_threshold: 5
  timeout_duration: "60 seconds"
  success_threshold: 3
  monitoring_period: "5 minutes"

Dead Letter Queue Strategy¶

dlq_configuration:
  max_delivery_count: 3
  time_to_live: "7 days"
  auto_forward_on_message_expiration: false
  enable_dead_lettering_on_filter_evaluation_exceptions: true

Monitoring and Observability¶

Integration Health Monitoring¶

health_checks:
  endpoint_monitoring:
    frequency: "30 seconds"
    timeout: "10 seconds"
    success_criteria: "HTTP 200-299"

  data_quality_monitoring:
    frequency: "Hourly"
    metrics:
      - "Record count validation"
      - "Data freshness checks"
      - "Schema validation"

  performance_monitoring:
    metrics:
      - "Response time percentiles"
      - "Throughput (requests/minute)"
      - "Error rate percentage"
      - "Queue depth"

Alerting Thresholds¶

alert_thresholds:
  response_time:
    warning: "> 2 seconds"
    critical: "> 5 seconds"

  error_rate:
    warning: "> 1%"
    critical: "> 5%"

  availability:
    warning: "< 99%"
    critical: "< 95%"

Implementation Roadmap¶

Phase 1: Foundation (Months 1-3)¶

Priority: High-value, low-risk integrations
Systems: Maddenco, Treadnet
Deliverables: Basic integration framework, monitoring setup

Phase 2: Core Operations (Months 4-8)¶

Priority: Business-critical operations
Systems: GeoTab, Dayforce
Deliverables: Real-time dispatch capabilities, workforce integration

Phase 3: Financial Systems (Months 9-12)¶

Priority: Revenue and compliance
Systems: Merchant Partners
Deliverables: Payment processing, PCI compliance

Phase 4: Legacy Migration (Months 13-18)¶

Priority: Reach system migration
Systems: Reach (transition and reduction)
Deliverables: Data migration, reduced dependency, controlled data sharing

Risk Mitigation Strategies¶

risk_mitigation:
  technical_risks:
    - "Proof of concept development"
    - "Parallel running during migration"
    - "Automated testing and validation"

  business_risks:
    - "Stakeholder communication plan"
    - "Change management process"
    - "Rollback procedures"

  security_risks:
    - "Security assessments for each integration"
    - "Penetration testing"
    - "Compliance audits"

Document Version: 1.0
Last Updated: January 2026
Next Review: April 2026