Inventory Service - Full Business Capabilities & Domain Architecture

Executive Summary

The Inventory Service is a mission-critical Core Bounded Context within the PakLog fulfillment platform that maintains real-time inventory accuracy across multiple warehouses and locations. Built with Event Sourcing and CQRS patterns, it serves as the single source of truth for inventory availability, reservations, and movements throughout the supply chain ecosystem.

Strategic Importance: CRITICAL - Zero tolerance for inventory discrepancies Architecture Pattern: Event Sourcing + CQRS with Hexagonal Architecture Technology Stack: Java 21, Spring Boot 3.2, PostgreSQL, Apache Kafka, Redis Domain Complexity: HIGH - Complex state management with concurrent operations

1. BOUNDED CONTEXT DEFINITION

1.1 Context Name: Inventory Management & Control

Core Purpose: Authoritative source for all inventory positions, movements, reservations, and availability across the entire fulfillment network with real-time accuracy and multi-warehouse support.

1.2 Context Boundaries

Responsibilities (What’s IN the Context):

• ✅ Real-time inventory tracking (on-hand, available, reserved, in-transit)
• ✅ Multi-warehouse inventory management with location tracking
• ✅ Inventory reservation and allocation for orders
• ✅ Stock movement tracking (receipts, picks, transfers, adjustments)
• ✅ Cycle counting and physical inventory reconciliation
• ✅ Inventory aging and expiration management
• ✅ Reorder point monitoring and low stock alerts
• ✅ Inventory valuation (FIFO, LIFO, weighted average)
• ✅ Lot and serial number tracking
• ✅ Inventory hold and release management

External Dependencies (What’s OUT of the Context):

• ❌ Product master data ownership (belongs to Product Catalog)
• ❌ Order creation and fulfillment (belongs to Order Management)
• ❌ Physical warehouse operations (belongs to Warehouse Operations)
• ❌ Supplier and purchase orders (belongs to Procurement)
• ❌ Shipping and transportation (belongs to Shipment & Transportation)
• ❌ Demand forecasting (belongs to Planning & Analytics)
• ❌ Pricing and promotions (belongs to Pricing Service)

1.3 Ubiquitous Language

The following terms define the common language used within this bounded context:

2. SUBDOMAIN CLASSIFICATION

2.1 Subdomain Map

graph TB
    subgraph "Inventory Bounded Context"
        Core1[Core: Real-time Inventory Tracking]
        Core2[Core: Reservation & Allocation]
        Support1[Supporting: Cycle Counting]
        Support2[Supporting: Inventory Valuation]
        Support3[Supporting: Reorder Management]
        Generic1[Generic: Event Publishing]
        Generic2[Generic: Reporting]
    end

    Core1 --> Core2
    Core1 --> Support1
    Core1 --> Support2
    Core2 --> Support3

2.2 Core Subdomain: Real-time Inventory Tracking

Classification: CORE DOMAIN Strategic Value: CRITICAL - Foundation for all fulfillment operations Investment Priority: HIGHEST - Zero tolerance for inaccuracy

Why It’s Core:

• Business Critical: Inventory accuracy directly impacts customer satisfaction
• Competitive Advantage: Real-time ATP enables superior customer experience
• Complex Problem: Handling concurrent updates with consistency guarantees
• Unique Requirements: Multi-warehouse, multi-channel inventory synchronization

Key Capabilities:

• Event sourcing for complete audit trail
• CQRS for optimized read/write patterns
• Pessimistic locking for critical operations
• Optimistic locking for high-throughput scenarios
• Real-time event streaming for inventory changes
• Snapshot optimization for performance

Domain Services:

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@DomainService
public class InventoryTrackingService {
    public StockPosition recordReceipt(
        SKU sku,
        WarehouseLocation location,
        Quantity quantity,
        ReceiptMetadata metadata
    );

    public StockPosition recordMovement(
        SKU sku,
        WarehouseLocation from,
        WarehouseLocation to,
        Quantity quantity
    );

    public StockPosition adjustInventory(
        SKU sku,
        WarehouseLocation location,
        AdjustmentReason reason,
        Quantity adjustment
    );
}

2.3 Core Subdomain: Reservation & Allocation Management

Classification: CORE DOMAIN Strategic Value: CRITICAL - Enables order fulfillment Investment Priority: HIGHEST - Direct revenue impact

Why It’s Core:

• Revenue Protection: Prevents overselling and stockouts
• Customer Trust: Ensures promised inventory is available
• Complex Logic: Multi-channel allocation with priorities
• Real-time Requirements: Millisecond response for e-commerce

Key Capabilities:

• Soft reservations with expiration
• Hard allocations for confirmed orders
• Multi-channel inventory pooling
• Priority-based allocation rules
• Reservation transfers between channels
• Backorder management

2.4 Supporting Subdomain: Cycle Counting & Physical Inventory

Classification: SUPPORTING DOMAIN Strategic Value: HIGH - Maintains accuracy Investment Priority: MEDIUM - Essential but not differentiating

Key Capabilities:

• ABC analysis for count frequency
• Blind counting workflows
• Variance analysis and approval
• Count task generation and assignment
• Mobile counting applications
• Reconciliation workflows

2.5 Supporting Subdomain: Inventory Valuation

Classification: SUPPORTING DOMAIN Strategic Value: MEDIUM - Financial reporting requirement Investment Priority: MEDIUM - Compliance necessity

Key Capabilities:

• FIFO/LIFO/Weighted Average costing
• Real-time valuation calculations
• Period-end closing processes
• Cost adjustment handling
• Landed cost tracking
• Inventory aging reports

2.6 Generic Subdomain: Event Publishing & Integration

Classification: GENERIC DOMAIN Strategic Value: LOW - Standard infrastructure Investment Priority: LOW - Use platform capabilities

Key Capabilities:

• CloudEvents standard implementation
• Kafka event streaming
• Event versioning and compatibility
• Dead letter queue handling
• Event replay capabilities

3. DOMAIN MODEL

3.1 Aggregate Design

classDiagram
    class InventoryItem {
        <<Aggregate Root>>
        -InventoryItemId id
        -SKU sku
        -WarehouseLocation location
        -StockPosition position
        -List~Reservation~ reservations
        -List~InventoryEvent~ events
        -LocalDateTime lastModified
        +receive(quantity, metadata)
        +reserve(quantity, orderId, expiry)
        +allocate(reservationId)
        +release(reservationId)
        +adjust(quantity, reason)
        +transfer(toLocation, quantity)
        +getAvailableToPromise()
    }

    class StockPosition {
        <<Value Object>>
        -Quantity onHand
        -Quantity reserved
        -Quantity allocated
        -Quantity inTransit
        -Quantity onHold
        +available()
        +total()
    }

    class Reservation {
        <<Entity>>
        -ReservationId id
        -OrderId orderId
        -Quantity quantity
        -ReservationType type
        -LocalDateTime createdAt
        -LocalDateTime expiresAt
        -ReservationStatus status
        +expire()
        +convert()
        +cancel()
    }

    class InventoryMovement {
        <<Entity>>
        -MovementId id
        -MovementType type
        -SKU sku
        -WarehouseLocation fromLocation
        -WarehouseLocation toLocation
        -Quantity quantity
        -MovementStatus status
        -LocalDateTime createdAt
        +complete()
        +cancel()
    }

    InventoryItem --> StockPosition
    InventoryItem --> Reservation

3.2 Value Objects

classDiagram
    class SKU {
        <<Value Object>>
        -String value
        -ProductCategory category
        +validate()
        +equals()
    }

    class WarehouseLocation {
        <<Value Object>>
        -WarehouseId warehouse
        -Zone zone
        -Aisle aisle
        -Bay bay
        -Shelf shelf
        -Bin bin
        +toString()
        +isPickable()
    }

    class Quantity {
        <<Value Object>>
        -BigDecimal value
        -UnitOfMeasure unit
        +add()
        +subtract()
        +isNegative()
        +isZero()
    }

    class LotNumber {
        <<Value Object>>
        -String value
        -LocalDate manufactureDate
        -LocalDate expirationDate
        +isExpired()
        +daysUntilExpiration()
    }

    class SerialNumber {
        <<Value Object>>
        -String value
        -String manufacturer
        +validate()
    }

3.3 Domain Events

4. BUSINESS CAPABILITIES

4.1 Capability Hierarchy

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L1: Inventory Management
├── L2: Stock Position Management
│   ├── L3: Real-time Position Tracking
│   ├── L3: Multi-warehouse Inventory
│   ├── L3: Location-level Tracking
│   ├── L3: Lot/Serial Tracking
│   └── L3: Inventory Aging
├── L2: Reservation & Allocation
│   ├── L3: Order Reservation
│   ├── L3: Channel Allocation
│   ├── L3: Reservation Expiration
│   ├── L3: Backorder Management
│   └── L3: Priority Allocation
├── L2: Stock Movements
│   ├── L3: Receipts Processing
│   ├── L3: Picking & Allocation
│   ├── L3: Transfers & Relocations
│   ├── L3: Returns Processing
│   └── L3: Adjustments & Write-offs
├── L2: Inventory Control
│   ├── L3: Cycle Counting
│   ├── L3: Physical Inventory
│   ├── L3: Variance Analysis
│   ├── L3: Hold Management
│   └── L3: Quality Control
└── L2: Analytics & Reporting
    ├── L3: Inventory Valuation
    ├── L3: Turn Analysis
    ├── L3: ABC Classification
    ├── L3: Aging Reports
    └── L3: Stock Coverage

4.2 L1: Inventory Management

Business Goal: Maintain 99.95% inventory accuracy with real-time visibility

Key Business Outcomes:

• 99.95% inventory accuracy rate
• <100ms response time for ATP queries
• Zero overselling incidents
• 25% reduction in safety stock
• 15% improvement in inventory turns

Strategic Value: CRITICAL - Foundation for all fulfillment operations

4.3 L2: Stock Position Management

L3: Real-time Position Tracking

Purpose: Maintain accurate inventory positions across all states

Business Rules:

• On-hand quantity must never be negative
• Reserved quantity cannot exceed available
• All changes must be event-sourced
• Positions updated within 50ms of physical action
• Support for partial quantities and units of measure

Technical Implementation:

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@EventSourcedAggregate
public class InventoryItem {

    @CommandHandler
    public void handle(UpdateStockPositionCommand cmd) {
        // Validate business rules
        if (cmd.getQuantity().isNegative()) {
            throw new NegativeInventoryException();
        }

        // Calculate new position
        StockPosition newPosition = position.adjust(
            cmd.getQuantity(),
            cmd.getAdjustmentType()
        );

        // Apply event
        apply(new StockPositionUpdatedEvent(
            this.id,
            this.sku,
            this.location,
            newPosition,
            cmd.getReason()
        ));
    }

    @EventSourcingHandler
    public void on(StockPositionUpdatedEvent event) {
        this.position = event.getNewPosition();
        this.lastModified = event.getTimestamp();
    }
}

Metrics:

• Position accuracy: >99.95%
• Update latency: <50ms p99
• Event processing: >1000/sec

L3: Multi-warehouse Inventory

Purpose: Aggregate inventory across multiple facilities

Business Rules:

• Support for warehouse-specific availability
• Cross-warehouse transfers with in-transit tracking
• Virtual warehouse for drop-ship inventory
• Regional inventory pooling for fulfillment

Query Model:

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@QueryHandler
public class MultiWarehouseInventoryProjection {

    public NetworkInventory getNetworkInventory(SKU sku) {
        return NetworkInventory.builder()
            .sku(sku)
            .warehouses(
                warehouseRepository.findAll().stream()
                    .map(wh -> getWarehouseInventory(sku, wh))
                    .collect(Collectors.toList())
            )
            .totalAvailable(calculateTotalATP())
            .optimalFulfillmentLocation(findOptimalLocation())
            .build();
    }
}

L3: Location-level Tracking

Purpose: Track inventory at bin/shelf level for picking optimization

Capabilities:

• Hierarchical location structure (Warehouse > Zone > Aisle > Bay > Shelf > Bin)
• Pick face vs. reserve locations
• Location capacity constraints
• Slotting optimization support
• FEFO/FIFO picking by location

4.4 L2: Reservation & Allocation

L3: Order Reservation

Purpose: Guarantee inventory availability for customer orders

Business Rules:

• Soft reservation expires after configurable timeout (default 15 minutes)
• Hard reservation persists until order completion or cancellation
• Reservations must be atomic across multiple SKUs
• Support partial reservations with backorder
• Channel-specific reservation pools

Reservation State Machine:

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PENDING → CONFIRMED → ALLOCATED → FULFILLED
    ↓         ↓           ↓
  EXPIRED  CANCELLED   CANCELLED

Implementation:

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@Saga
public class OrderReservationSaga {

    @StartSaga
    @SagaEventHandler
    public void handle(OrderCreatedEvent event) {
        // Reserve each line item
        event.getLineItems().forEach(item -> {
            commandGateway.send(new ReserveInventoryCommand(
                item.getSku(),
                item.getQuantity(),
                event.getOrderId(),
                Duration.ofMinutes(15)
            ));
        });
    }

    @SagaEventHandler
    public void handle(InventoryReservedEvent event) {
        reservedItems.add(event.getSku());

        if (allItemsReserved()) {
            commandGateway.send(new ConfirmOrderCommand(orderId));
            endSaga();
        }
    }

    @SagaEventHandler
    public void handle(ReservationFailedEvent event) {
        // Compensate by releasing successful reservations
        reservedItems.forEach(sku -> {
            commandGateway.send(new ReleaseInventoryCommand(
                sku,
                orderId
            ));
        });

        commandGateway.send(new CancelOrderCommand(
            orderId,
            "Insufficient inventory"
        ));
        endSaga();
    }
}

L3: Channel Allocation

Purpose: Manage inventory allocation across sales channels

Business Rules:

• Channel priorities (e.g., website > marketplace > wholesale)
• Dynamic reallocation based on demand
• Channel-specific safety stock
• Protect inventory for promotions/events

Configuration:

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allocation:
  channels:
    - name: website
      priority: 1
      reservation-pool: 60%
      safety-stock: 100
    - name: amazon
      priority: 2
      reservation-pool: 30%
      safety-stock: 50
    - name: wholesale
      priority: 3
      reservation-pool: 10%
      safety-stock: 20

4.5 L2: Stock Movements

L3: Receipts Processing

Purpose: Record incoming inventory from suppliers

Capabilities:

• ASN (Advanced Shipping Notice) processing
• Blind receiving workflows
• Quality inspection holds
• Cross-docking support
• Lot/serial number capture
• Putaway optimization

Event Flow:

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ASNReceived → ReceiptStarted → ItemsReceived → QualityChecked → PutawayCompleted

L3: Transfers & Relocations

Purpose: Move inventory between locations

Types:

• Inter-warehouse transfers
• Intra-warehouse moves
• Replenishment transfers
• Consolidation moves

Business Rules:

• In-transit inventory tracking
• Transfer approval workflows
• Cost allocation for transfers
• Minimum/maximum transfer quantities

4.6 L2: Inventory Control

L3: Cycle Counting

Purpose: Maintain accuracy through periodic counts

Strategy:

• ABC classification-based frequency
  • A items: Weekly
  • B items: Monthly
  • C items: Quarterly
• Exception-based counting (variances, adjustments)
• Location-based systematic counting
• High-value item focus

Workflow:

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@Component
public class CycleCountWorkflow {

    public CycleCountTask generateCountTask() {
        // Select items based on ABC classification and last count date
        List<SKU> itemsToCount = cycleCountStrategy.selectItems(
            LocalDate.now(),
            100 // items per task
        );

        return CycleCountTask.builder()
            .taskId(UUID.randomUUID())
            .items(itemsToCount)
            .assignedTo(selectCounter())
            .dueDate(LocalDate.now())
            .blind(true) // Don't show expected quantity
            .build();
    }

    public void processCountResults(
        CycleCountTask task,
        List<CountResult> results
    ) {
        results.forEach(result -> {
            Variance variance = calculateVariance(
                result.getSku(),
                result.getLocation(),
                result.getCountedQuantity()
            );

            if (variance.isSignificant()) {
                initiateRecountWorkflow(result);
            } else {
                applyAdjustment(result, variance);
            }
        });
    }
}

4.7 L2: Analytics & Reporting

L3: Inventory Valuation

Purpose: Calculate inventory value for financial reporting

Methods Supported:

• FIFO (First In, First Out)
• LIFO (Last In, First Out)
• Weighted Average Cost
• Specific Identification (for serialized items)

Calculation:

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@Component
public class InventoryValuationService {

    public InventoryValuation calculateValuation(
        ValuationMethod method,
        LocalDate asOfDate
    ) {
        return switch(method) {
            case FIFO -> calculateFIFO(asOfDate);
            case LIFO -> calculateLIFO(asOfDate);
            case WEIGHTED_AVERAGE -> calculateWeightedAverage(asOfDate);
            case SPECIFIC_ID -> calculateSpecificId(asOfDate);
        };
    }

    private InventoryValuation calculateFIFO(LocalDate date) {
        // Group receipts by date
        // Apply earliest costs first
        // Calculate total value
    }
}

L3: Turn Analysis

Purpose: Measure inventory efficiency

Metrics:

• Inventory Turnover Ratio = COGS / Average Inventory
• Days Sales of Inventory (DSI) = 365 / Turnover Ratio
• Stock Coverage = Current Stock / Average Daily Usage
• Slow-moving and Obsolete (SLOB) analysis

5. INTEGRATION CONTEXT MAP

5.1 Upstream Dependencies

graph LR
    PC[Product Catalog] -->|Product Master Data| IS[Inventory Service]
    WMS[Warehouse Operations] -->|Physical Movements| IS
    PROC[Procurement] -->|Purchase Orders| IS

    style PC fill:#f9f,stroke:#333,stroke-width:2px
    style WMS fill:#f9f,stroke:#333,stroke-width:2px
    style PROC fill:#f9f,stroke:#333,stroke-width:2px
    style IS fill:#bbf,stroke:#333,stroke-width:4px

Product Catalog Context (Conformist Pattern)

Relationship Type: CONFORMIST

• We conform to their product model
• No influence on their data structure
• Must adapt to their changes

Integration Details:

• Protocol: REST API + Event Streaming
• Data Retrieved: SKU, dimensions, weight, categories, attributes
• Caching: Product data cached for 1 hour
• Resilience: Circuit breaker with fallback to cache

Warehouse Operations Context (Partnership Pattern)

Relationship Type: PARTNERSHIP

• Bidirectional dependency
• Coordinated model evolution
• Shared operational workflows

Integration Details:

• Protocol: Event streaming via Kafka
• Events Consumed: PickCompleted, ReceiptCompleted, TransferCompleted
• Events Published: InventoryAllocated, InventoryReleased
• Consistency: Eventual consistency with compensation

5.2 Downstream Consumers

Order Management System (Customer-Supplier)

Relationship Type: CUSTOMER-SUPPLIER

• They are our customer
• We provide inventory availability services
• They depend on our accuracy

Published Interface:

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GET /api/v1/inventory/availability/{sku}
POST /api/v1/inventory/reservations
DELETE /api/v1/inventory/reservations/{reservationId}
POST /api/v1/inventory/allocations

Analytics & Reporting (Open Host Service)

Relationship Type: OPEN HOST SERVICE

• Published data model for analytics
• Standardized reporting interface
• Multiple consumers

Published Events:

• Inventory position snapshots (hourly)
• Movement events (real-time)
• Adjustment events (real-time)

6. ARCHITECTURAL IMPLEMENTATION

6.1 Event Sourcing + CQRS Architecture

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┌─────────────────────────────────────────────────────────┐
│                    Command Side                          │
│  ┌──────────────┐        ┌──────────────┐              │
│  │   REST API   │        │   Kafka      │              │
│  │  Commands    │        │   Commands   │              │
│  └──────┬───────┘        └──────┬───────┘              │
│         │                        │                       │
│         ▼                        ▼                       │
│  ┌────────────────────────────────────┐                │
│  │      Command Handlers              │                │
│  │   ┌──────────────────────────┐     │                │
│  │   │    Aggregate Roots       │     │                │
│  │   │  - InventoryItem         │     │                │
│  │   │  - InventoryMovement     │     │                │
│  │   └──────────┬───────────────┘     │                │
│  │              │                      │                │
│  │              ▼                      │                │
│  │   ┌──────────────────────────┐     │                │
│  │   │    Event Store           │     │                │
│  │   │  (PostgreSQL + Kafka)    │     │                │
│  │   └──────────────────────────┘     │                │
│  └────────────────────────────────────┘                │
│                                                          │
│                    Query Side                            │
│  ┌────────────────────────────────────┐                │
│  │      Event Processors              │                │
│  │   ┌──────────────────────────┐     │                │
│  │   │    Projections           │     │                │
│  │   │  - Inventory Positions   │     │                │
│  │   │  - Available to Promise  │     │                │
│  │   │  - Movement History      │     │                │
│  │   └──────────┬───────────────┘     │                │
│  │              │                      │                │
│  │              ▼                      │                │
│  │   ┌──────────────────────────┐     │                │
│  │   │    Read Models           │     │                │
│  │   │  (PostgreSQL + Redis)    │     │                │
│  │   └──────────────────────────┘     │                │
│  └────────────────────────────────────┘                │
│         ▲                        ▲                       │
│         │                        │                       │
│  ┌──────┴───────┐        ┌──────┴───────┐              │
│  │   REST API   │        │   GraphQL    │              │
│  │   Queries    │        │   Queries    │              │
│  └──────────────┘        └──────────────┘              │
└─────────────────────────────────────────────────────────┐

6.2 Technology Stack

6.3 Performance Characteristics

7. BUSINESS VALUE & METRICS

7.1 Key Performance Indicators (KPIs)

7.2 Business Impact Analysis

Financial Impact

• Revenue Protection: $5M annually from stockout prevention
• Working Capital: $8M reduction through improved turns
• Write-off Reduction: $1M saved from obsolescence management
• Labor Efficiency: $500K saved through automated processes

Operational Impact

• Order Fulfillment Rate: 99.7% on-time fulfillment
• Customer Satisfaction: 4.8/5 rating for availability
• Warehouse Efficiency: 25% improvement in picking accuracy
• Supplier Relations: 15% reduction in emergency orders

Strategic Impact

• Competitive Advantage: Best-in-class inventory visibility
• Scalability: Supports 10x growth without architectural changes
• Market Responsiveness: Real-time inventory enables flash sales
• Data-Driven Decisions: ML-ready data for demand forecasting

7.3 Cost-Benefit Analysis

Implementation Costs:

• Development: $2M (12 developers × 6 months)
• Infrastructure: $500K annually
• Maintenance: $300K annually

Annual Benefits:

• Revenue protection: $5M
• Working capital reduction: $8M
• Operational savings: $1.5M
• ROI: 520% first year

8. RISK ASSESSMENT & MITIGATION

8.1 Technical Risks

8.2 Business Risks

8.3 Compliance & Security

Current Security Measures:

• ✅ Role-based access control (RBAC)
• ✅ Audit logging for all changes
• ✅ Encryption at rest and in transit
• ✅ PII data masking

Compliance Requirements:

• SOX compliance for financial reporting
• GDPR for customer data handling
• Industry-specific regulations (FDA, etc.)

9. EVOLUTION ROADMAP

9.1 Phase 1: Foundation (Q1 2025) ✅

• ✅ Event sourcing implementation
• ✅ CQRS pattern adoption
• ✅ Basic inventory operations
• ✅ Multi-warehouse support

9.2 Phase 2: Advanced Features (Q2 2025)

• 🔄 Serial/lot tracking
• 🔄 Advanced reservation logic
• 🔄 Consignment inventory
• 🔄 Drop-ship integration

9.3 Phase 3: Intelligence (Q3 2025)

• 📋 ML-based reorder points
• 📋 Predictive stockout alerts
• 📋 Demand sensing integration
• 📋 Dynamic safety stock

9.4 Phase 4: Optimization (Q4 2025)

• 📋 Inventory optimization algorithms
• 📋 Multi-echelon inventory
• 📋 Network optimization
• 📋 Autonomous replenishment

10. TEAM & GOVERNANCE

10.1 Domain Ownership

• Domain Owner: Supply Chain Operations
• Technical Lead: Platform Architecture Team
• Product Owner: Inventory Management

10.2 Service Level Agreements (SLAs)

• Availability: 99.99% uptime
• ATP Query Response: p95 < 100ms
• Event Processing: < 1 second end-to-end
• Support: 24/7 on-call rotation

10.3 Change Management

• API Versioning: Major.Minor.Patch with 6-month deprecation
• Event Schema: Backward compatible changes only
• Database Migration: Zero-downtime deployments
• Testing Requirements: 90% code coverage, integration tests

APPENDIX A: API REFERENCE

REST Endpoints

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/api/v1/inventory/availability:
  get:
    summary: Get available to promise inventory
    parameters:
      - name: sku
        required: true
      - name: warehouse
        required: false
    responses:
      200:
        schema:
          $ref: '#/components/schemas/AvailableToPromise'

/api/v1/inventory/reservations:
  post:
    summary: Create inventory reservation
    requestBody:
      schema:
        $ref: '#/components/schemas/ReservationRequest'
    responses:
      201:
        description: Reservation created

/api/v1/inventory/movements:
  post:
    summary: Record inventory movement
    requestBody:
      schema:
        $ref: '#/components/schemas/MovementRequest'

Event Schemas

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// InventoryReservedEvent
{
  "specversion": "1.0",
  "type": "com.paklog.inventory.reserved.v1",
  "source": "/inventory-service",
  "id": "evt-123",
  "time": "2025-01-20T10:00:00Z",
  "datacontenttype": "application/json",
  "data": {
    "reservationId": "res-abc123",
    "orderId": "order-456",
    "sku": "SKU-789",
    "quantity": 5,
    "warehouse": "WH-001",
    "expiresAt": "2025-01-20T10:15:00Z"
  }
}

APPENDIX B: GLOSSARY

Document Version: 1.0.0 Last Updated: 2025-01-20 Status: APPROVED Next Review: 2025-04-20