PakLog Complete System Architecture Overview

Microservices Ecosystem - 21 Core Services

graph TB
    subgraph "Phase 1: Foundation Services"
        C[Cartonization<br/>3D Bin Packing]
        I[Inventory<br/>Stock Management]
        OM[Order Management<br/>Order Lifecycle]
        PC[Product Catalog<br/>SKU Master Data]
        ST[Shipment Transportation<br/>Carrier Integration]
    end

    subgraph "Phase 2: Execution Services"
        WP[Wave Planning<br/>Wave Optimization]
        TE[Task Execution<br/>Task Orchestration]
        PE[Pick Execution<br/>Path Optimization]
        PS[Pack & Ship<br/>Packing Station]
        PT[Physical Tracking<br/>License Plate]
        LM[Location Master<br/>Slotting]
        WL[Workload Planning<br/>Labor Forecast]
    end

    subgraph "Phase 3: Advanced Operations"
        RM[Returns Management<br/>RMA Processing]
        RF[Robotics Fleet<br/>AMR/AGV Control]
        WES[WES Orchestration<br/>Workflow Engine]
    end

    subgraph "Phase 4: Optimization & Intelligence"
        PA[Predictive Analytics<br/>ML Forecasting]
        YM[Yard Management<br/>Dock Scheduling]
        CD[Cross-Docking<br/>Flow-Through]
    end

    subgraph "Phase 5: Customer & Value Services"
        LMD[Last-Mile Delivery<br/>Route Planning]
        VAS[Value-Added Services<br/>Kitting/Customization]
        QC[Quality Compliance<br/>Inspection/SPC]
    end

    subgraph "Phase 6: Intelligence Platform"
        DT[Digital Twin<br/>Simulation]
        SM[Sustainability<br/>Carbon Tracking]
        CX[Customer Experience<br/>Self-Service]
        PI[Performance Intelligence<br/>KPI Analytics]
        EA[Equipment Assets<br/>Maintenance]
        FS[Financial Settlement<br/>3PL Billing]
    end

    %% Core Connections
    OM --> I
    OM --> C
    OM --> ST

    %% Wave and Task Flow
    OM --> WP
    WP --> TE
    TE --> PE
    PE --> PS
    PS --> ST

    %% Inventory Flow
    I --> LM
    I --> PT
    PT --> LM

    %% Advanced Operations
    WES --> TE
    RF --> TE
    RM --> I
    RM --> OM

    %% Analytics and Optimization
    PA --> WP
    PA --> WL
    YM --> ST
    CD --> TE

    %% Customer Services
    LMD --> ST
    VAS --> TE
    QC --> PE

    %% Intelligence Platform
    DT --> WP
    PI --> TE
    EA --> RF
    FS --> OM
    CX --> OM
    SM --> I

    classDef foundation fill:#e1f5e1,stroke:#4caf50,stroke-width:2px
    classDef execution fill:#e3f2fd,stroke:#2196f3,stroke-width:2px
    classDef advanced fill:#fff3e0,stroke:#ff9800,stroke-width:2px
    classDef optimization fill:#f3e5f5,stroke:#9c27b0,stroke-width:2px
    classDef customer fill:#fce4ec,stroke:#e91e63,stroke-width:2px
    classDef intelligence fill:#e0f2f1,stroke:#009688,stroke-width:2px

    class C,I,OM,PC,ST foundation
    class WP,TE,PE,PS,PT,LM,WL execution
    class RM,RF,WES advanced
    class PA,YM,CD optimization
    class LMD,VAS,QC customer
    class DT,SM,CX,PI,EA,FS intelligence

Service Categories and Responsibilities

Phase 1: Foundation Services (Core)

  1. Cartonization - 3D bin-packing optimization for shipping cartons
  2. Inventory - Real-time inventory tracking and management
  3. Order Management - Order lifecycle from creation to fulfillment
  4. Product Catalog - SKU master data and product information
  5. Shipment Transportation - Carrier integration and shipment tracking

Phase 2: Execution Services (Operational Layer)

  1. Wave Planning - Intelligent wave creation and optimization
  2. Task Execution - Task queue management and assignment
  3. Pick Execution - Mobile picking with path optimization (TSP)
  4. Pack & Ship - Packing station operations and shipping
  5. Physical Tracking - License plate and asset tracking
  6. Location Master - Warehouse location and slotting management
  7. Workload Planning - Labor forecasting and shift planning

Phase 3: Advanced Operations

  1. Returns Management - RMA processing and fraud detection
  2. Robotics Fleet Management - AMR/AGV orchestration with A* pathfinding
  3. WES Orchestration Engine - Workflow orchestration with saga pattern

Phase 4: Optimization & Intelligence

  1. Predictive Analytics Platform - ML-based forecasting and predictions
  2. Yard Management System - Dock door scheduling and trailer tracking
  3. Cross-Docking Operations - Flow-through and consolidation

Phase 5: Customer & Value Services

  1. Last-Mile Delivery - Route optimization with VRP algorithm
  2. Value-Added Services - Kitting, customization, gift wrapping
  3. Quality Compliance - Statistical Process Control (SPC) and inspection

Phase 6: Intelligence Platform (Supporting Services)

Technology Stack

Core Technologies

Architectural Patterns

Integration Points

Event-Driven Communication

All services communicate via Apache Kafka using CloudEvents specification:

REST APIs

Each service exposes RESTful APIs for:

External Integrations

Deployment Architecture

graph TB
    subgraph "Kubernetes Cluster"
        subgraph "Namespace: paklog-prod"
            subgraph "Core Services"
                CS[Core Services Pods<br/>6 services]
            end
            subgraph "Execution Services"
                ES[Execution Pods<br/>7 services]
            end
            subgraph "Advanced Services"
                AS[Advanced Pods<br/>9 services]
            end
        end

        subgraph "Infrastructure"
            K[Kafka Cluster]
            M[MongoDB ReplicaSet]
            R[Redis Cluster]
            P[PostgreSQL]
        end
    end

    subgraph "Monitoring"
        PROM[Prometheus]
        GRAF[Grafana]
        TRACE[Jaeger Tracing]
    end

    subgraph "External"
        LB[Load Balancer]
        API[API Gateway]
    end

    LB --> API
    API --> CS
    API --> ES
    API --> AS

    CS --> K
    ES --> K
    AS --> K

    CS --> M
    ES --> M
    AS --> M

    ES --> R
    AS --> R

    PROM --> CS
    PROM --> ES
    PROM --> AS

Key Architectural Decisions

  1. Microservices Architecture - Independent deployment and scaling
  2. Event-Driven Design - Loose coupling between services
  3. Hexagonal Architecture - Clean separation of domain and infrastructure
  4. Domain-Driven Design - Rich domain models with bounded contexts
  5. CQRS Pattern - Optimized read and write operations
  6. Saga Pattern - Managing distributed transactions
  7. MongoDB as Primary Store - Flexible document model for domain aggregates
  8. Kafka for Events - Reliable, scalable event streaming
  9. Redis for Caching - Fast access to frequently used data
  10. CloudEvents Specification - Standardized event format